SERVICE FAILURES AND RECOVERY STRATEGIES- A STUDY OF INDIAN

AVIATION INDUSTRY SINCE 2000

A

Ph. D. THESIS SUBMITTED TO THE UNIVERSITY OF JAMMU

FOR THE AWARD OF DEGREE OF

DOCTOR OF PHILOSOPHY

IN

TOURISM MANAGEMENT

BY

POONAM SHARMA

UNDER THE SUPERVISION OF

PROF. DEEPAK RAJ GUPTA

PROFESSOR

SCHOOL OF HOSPITALITY & TOURISM MANAGEMENT

UNIVERSITY OF JAMMU

JAMMU

SCHOOL OF HOSPITALITY AND TOURISM MANAGEMENT

UNIVERSITY OF JAMMU

JAMMU

2012

ACKNOWLEDGEMENT

Dedicated to Ganpati, Satya Sai Baba, Bawewali Mata, Datta and Datti ji.

To write an acknowledgement, recalls the contribution of all the persons in the completion of first milestone

of my journey towards the research. The results of this work will be judged by others, but I can definitely say

that the process was enjoyable. So I am glad to complete it by remembering many wonderful people who

have contributed to it in various ways.

First of all, I express my gratitude and indebtedness to my teacher and my supervisor Professor Deepak Raj

Gupta, Director, School of Hospitality and Tourism Management. I feel blessed and enlightened to be

associated with him for more than a decade and his continuous guidance both in the professional and the

personal matters that helps me in resolving all the worries of my life.

Words cannot express my deep regard and admiration for Dr. Anil Gupta. His selfless guidance in every

aspect made me to complete this thesis. His better half, Dr. Neelika Gupta constantly encouraged and

motivated me to compile the work. I am very thankful for their never ending support.

I also acknowledge my thanks to the Director of The Business School, Prof. Neelu Rohmetra for her constant

inspiration and guidance. I would like to extend warm thanks to Prof. R.D. Sharma, Dean Academic Affairs

and also Dean, Faculty of Business Studies, for his guidance and encouragement in the accomplishment of

my work.

I extend my thanks to all the teachers in the faculty of SHTM and The Business School, University of Jammu

ever since I got associated with the Department, including Prof. Ashok Aima, Prof. Keshav Sharma, Prof.

Versha Mehta, Prof. B.C. Sharma, Dr. Alka Sharma, Dr. Rajendra Mishra, Dr. Sameer Gupta, Dr. Parikshit

Singh Manhas, Dr. Vinay Chauhan, Dr. Amisha Gupta, Dr. Jaya Bhasin and Dr. Rachana Sharma.

My special thanks to Dr. Desh Bandhu Gupta, Professor, Department of Commerce, University of Jammu

whose encouragement and help made me feel confident in completing my research programme.

I owe my thanks to Mrs. Preeti Gupta, Librarian, SHTM and Mrs. Anju Gupta, Librarian, The Business

School, University of Jammu in helping me with the books and journals from the library. My thanks are also

reserved for the Librarians of the Commerce Department, University of Jammu; Ratan Tata Library; Faculty

of Management Studies; MDI, Gurgoan; IITTM, Gwalior for providing me the required literature whenever I

approached them. My special thanks are also due to Mr. Sanjay Sharma who always supported and helped in

lots of things during the last five years. In addition to it I would also like to thank Mrs. Anju Choudhary and

non-teaching staff for helping me through out the process.

I owe a very special thanks to Mr. Ramjit for his valuable inputs and assistance from time to time in several

ways.

I express with lot of love, my gratitude to Dr. Pooja Jain, Mrs Manmeet Kour, Dr. Suvidha Khanna Sondhi,

Mr. Abhishek Sharma, Mr. Mukesh Sharma, Mrs Neetu Khajuria, Mr. Risheesh Khajuria, Dr. Komal Nagar,

Dr. Saranpreet Kaur Broca, Mrs Sudamini Mahey, Dr. Bindiya Kohli, Dr. Anuradha Sharma, Dr. Sonia

Sharma who have always been encouraging and contributed with their moral support.

I also owe my thanks to my juniors Ms. Milly, Ms. Nazuk, Mr. Surjeet, Mr. Sourabh, Mr. Arun and those

whom I didn’t know by face but they helped in one way or the other for the completion of the thesis.

On the home front, I owe my biggest debt of gratitude to my father Sh. Om Dutt Baru and my mother Smt.

Shashi Bala for what I am today and every support in life that I needed. I extend my very special thanks to

my grandfather Sh. Ishwar Dass Baru for his guidance and constant moral support.

I shall never be able to express to any degree of satisfaction my thankfulness for the love, care and blessings

of Smt. Rekha Sharma (my mother-in-law) and divine blessings of Late Sh. Bansi Lal Sharma (my father-

in-law).

My love and special thanks are due to my sisters Mrs. Meenakshi Vaid, Mrs. Rachana Khajuria, Mrs.

Archana Sehgal, Ms. Arti Sharma and Ms. Radhika Gudda; my bhabhi’s Mrs. Madhu Badial, Mrs. Shiwani

Sharma, Mrs. ShrutiNidhi Sharma, Mrs. Ruchi Dhamija Sharma, my brothers Mr. Atal Khajuria, Col.

Ashutosh Badial, Mr. Abhinav Vaid, Mr. Ajay Sehgal, Mr. Puneet Sharma, Mr. Munish Sharma, Mr. Vivek

Sharma, Mr. Ashish Sharma, Mr. Aniket Gudda and little gems of my family Abhishek, Aishwarya,

Rakshita, Ananay, Apurva and Parth.

I owe thanks to my uncle Mr. Rajesh Oswal and aunt Mrs. Suman Oswal for their encouragement and moral

support.

The best outcome of these past five years has been to find my best friend, soul-mate and husband, Mukul.

Staying away is the most difficult thing for us, thanks for being patient, supportive and helping at every stage

of life. Arrival of our angel, Mani is the most joyous part of our life. There is feeling of guilt in me, because

of my work schedule on account of which I kept a father and a daughter separated from each other. I truly

thank Mukul for standing by my side, even when I was irritable and depressed. Your unconditional love and

support without any complaint or regret has enabled me to complete this Ph.D thesis. I owe my every

achievement to my love, Mukul and Mani.

I am also grateful to all the respondents who came forward to provide me with the desired information on the

topic with sincerity and clarity. I wish to thank to all the academicians, scholars, writers and authors to whom

I have referred and quoted.

I thank one and all, for their explicit or implicitly associated with this work.

POONAM SHARMA

TABLE OF CONTENTS

Chapter Particulars Page No.

Acknowledgement

Preface

List of Tables

List of Figures

List of Abbreviations

(i-ii)

(iii-vii)

(vii)

(ix)

1 Introduction

1.1 Statement of the Problem

1.2 Rationale of the Present Study

1.3 Scope of the Study

1.4 Concept of Service

1.5 Model of Service Consumption

1.5.1 The Pre purchase Stage

1.5.2 The Service Encounter Stage

1.5.3 The Post-encounter Stage

1.6 Attribution Theory

1.7 Perceived Justice

1.8 Global Aviation Industry

1-42

3

3

4

6

10

10

10

17

20

22

26

2 Indian Aviation Sector

2.1 Introduction

2.2 A Brief History of Aviation Industry in India

2.3 Civil Aviation in India

2.3.1 Ministry of Civil Aviation

43-105

43

45

48

48

2.3.2 Organizations Under Ministry of Civil

Aviation

2.4 Civil Aviation Policy in India

2.5 Reasons for Boom in Indian Aviation Industry

2.6 Future of Aviation Industry in India

2.7 Nature of Airlines

2.8 Airlines in India

2.8.1 Air India

2.8.2 Jet Airways

2.8.3 Kingfisher Airline

2.8.4 Indigo

2.8.5 GoAir

2.8.6 Spice Jet

2.8.7 Jagson Airlines

2.8.8 Paramount Airways

2.9 Air Traffic Trends

50

50

56

58

61

65

69

74

79

86

89

92

95

97

98

3 Review of Literature

3.1 Service Encounter

3.2 Service Failure and Service Recovery

3.2.1 Perceived Justice

3.3 Highlights of the Present Study

3.4 Research Gap

106-178

107

125

151

163

164

4 Research Design and Methodology

4.1 Research Purpose

4.2 Research Objectives

179-204

179

180

4.3 Research Hypothesis

4.4 Research Design

4.5 Research Methods

4.5.1 Sampling

4.6 Instrument Development

4.7 Statistical Techniques Used

4.7.1 Critical Incident Technique

4.7.2 Analysis of Variance

4.7.3 Multiple Regression

4.7.4 Factor Analysis

180

180

181

182

183

187

187

191

196

199

Chapter 5: Data Analyses and Interpretation

5.1 Identification of Various Types of Service Failures

5.2 Section I- Demographic Profile of the Respondents

5.3 Section II- Descriptive Statistics of Level of

Seriousness, Frequency of Service Failures Encountered

and Effect on Satisfaction

5.4 Descriptive Statistics of Consumer Complaint

Behaviour (CCB) Intentions of Airline Passengers

5.5 Descriptive Statistics for Airline Passenger’s

Perceived Justice

5.6 Dimension Recovery Strategies

5.7 Dimension of Perceived Justice of Airline Passengers

5.8 Regression Analysis

5.9 Descriptive Statistics of Dimension Overall Airline

Satisfaction w.r.t. Each Airline

5.9.1 Comparison of Airlines on the Basis of

Overall Airline Satisfaction

205-282

205

224

227

247

254

259

260

266

270

271

5.10 Descriptive Statistics of Dimension Satisfaction

with Overall Quality of Airline

5.10.1 Comparison of Airlines on the Basis of

Satisfaction With the Overall Quality of Airline

274

276

Chapter 6: Conclusion and Suggestions

6.1 Objectives of the Study and their Achievement

6.2 Validity of Hypothesis Tested

6.3 Conclusion

6.4 Recommendations

6.5 Research Contributions

6.6 Limitations/Future Research Directions

283-301

283

286

288

293

296

296

Annexure

Questionnaire (Study I)

Questionnaire (Study II)

Bibliography

302-334

302

303

309

PREFACE

During the past few decades, interest has been growing among researchers and

practitioners towards the subject of service encounter, service failures and the

recovery actions taken by the service providers. And the consequences of service

failures and recovery strategies on the customer in terms of their satisfaction, trust,

loyalty, repurchase intentions and word of mouth are of great interest to marketing

managers and researchers alike. In this context, it becomes imperative to undertake a

synoptic view of the subject of service encounter and service failure.

It is inevitable that while providing services to customers, no failure occurs. But the

success of a firm depends on its capability to avoid failure and if occurred how to

rectify it successfully to make the customer satisfied. In particular, it is critical for the

survival of a company not only to retain its current customers but also to make them

loyal to the company. According to NOP, reducing customer defections can boost

profits by 25-85%. In 73% of cases, the organisation made no attempt to persuade

dissatisfied customers to stay; even though 35% said that a simple apology would

have prevented them from moving to the competitor.

The current research work is an attempt to find out the various types of service

failures which the customers of domestic airlines encounter while consuming their

services during travelling in domestic sectors of India and also study the effect of

service failures and recovery strategies on customer satisfaction. To take the research

to its logical conclusion, the entire study is divided into six chapters.

The first chapter contains a discussion on the introduction of the subject service and

model of service consumption.

The second chapter focuses entirely on the scenario of Indian Aviation sector.

The third chapter contains an expanded discussion on the literature with a completed

and comprehensive review of the various researches that have been carried out in the

related subject.

The fourth chapter contains the research methodology adopted to achieve the

objectives of the study and test the hypotheses framed.

The fifth chapter is about analysis and interpretation of results derived from applying

relevant statistical tools and techniques to the data.

The last chapter highlights conclusion and suggestions emerging from the

discussions.

LIST OF TABLES

S.No. Table No. Table Title Page No.

1. 2.1 Sources of Non-Ticket Revenue for LCA and FSC

Airlines

64

2. 2.2 Operational Airlines- List of Airlines Today in the

Market

65

3. 2.3 Air Traffic Trends: World Vs India 2000-2010 98

4. 2.4 Monthly Traffic and Operating Statistics of All

Indian Carriers on Scheduled Domestic Services

During 2009-2010

101

5. 2.5 Comparative Statement of Domestic Traffic on

Scheduled Services of All Indian Carriers During

2009-10

102

6. 2.6 Comparative Statement of Total Traffic on

Scheduled Services of All Indian Carriers During

2009-2010

103

7. 3.1 Bitner et al’s (1990) Group and Category

Classification by Type of Incident Outcome

112

8 5.1 Bitner et al’s (1990) Group and Category

Classification by Type of Incident Outcome

206

9. 5.2 Demographic Profile of Respondents 211

10. 5.3 Group and Category Classification by Type of

Incident Outcome

213

11. 5.4 Group 1 – Sample Incidents: Employee Response to

Service Delivery Failures

216

12. 5.5 Group 2– Sample Incidents: Employee Response to

Customer Needs and Requests

217

13. 5.6 Group 3 – Sample Incidents: Unprompted and

Unsolicited Employee Actions

218

14. 5.7 Comparison of Failure Frequency in Percentage 220

15. 5.8 Classification of Service Failures in Bitner et al’s

(1990) Group and Category Classification by Type

of Incident Outcome

221

16. 5.9 Classification of Twenty-six Identified Service

Failures into Groups and Categories

223-224

17. 5.10 Demographic Profile of the Respondents 226

18. 5.11 Statement Wise Response (Mean and Standard

Deviation) to Level of Seriousness, Frequency of

Failures Encountered and Effect on Satisfaction

228-229

19. 5.12 Statement Wise Response (Mean and Standard

Deviation) to Level of Seriousness, Frequency of

Failure Encountered and Effect on Satisfaction on

the basis of gender

231-232

20. 5.13 Statement Wise Response (Mean and Standard

Deviation) to Level of Seriousness on the Basis of

Travel Frequency

233-234

21. 5.14 Statement Wise Response (Mean and Standard

Deviation) to Frequency of Failure Encountered on

the Basis of Travel Frequency

235-236

22. 5.15 Statement Wise Response (Mean and Standard

Deviation) to Effect on Satisfaction on the Basis of

Travel Frequency

237-238

23. 5.16 Descriptive Statistics (Mean and Standard

Deviation) of Three Groups

245

24. 5.17 Comparison of Failure Frequency in Percentage 247

25. 5.18 Demographic Composition of Complainants and

Non-Complainants

248

26. 5.19 Statement wise response to Consumer Complaint

Behaviour (CCB) Intentions

249

27. 5.20 Descriptive Statistics (Mean and Standard

Deviation) of CCB Intentions of Complainants and

Non-Complainants

250

28. 5.21 Independent t-test Between Complainants and Non

Complainants

250

29. 5.22 Comparison of Descriptive Statistics (Mean and

Standard Deviation) of CCB intentions of

Complainants on the Basis of Gender

251

30. 5.23 Comparison of Descriptive Statistics (Mean and

Standard Deviation) of CCB Intentions of

Complainants On the Basis of Age

252

31. 5.24 Statement wise response to Perceived Justice of

Complainants

254

32. 5.25 Statement wise response to Perceived Justice of

Complainants on the Basis of Gender

255

33. 5.26 Statement wise response to Perceived Justice of

Complainants on the Basis of Age

256-57

34. 5.27 Recovery strategies used by airlines after service

failure

259

35. 5.28 Reliability of Perceived Justice Construct of Airline

Passengers

261

36. 5.29 Kaiser-Meyer-Olkin and Bartlett's Test of Sphericity 261

37. 5.30 Summary of Results from Scale Purification 264

38. 5.31 Regression Coefficient of Seriousness of the Service

Failure

267

39. 5.32 Regression Model for Seriousness of the Service

Failure (Summary)

267

40. 5.33 Regression Coefficient of Perceived Justice 268

41. 5.34 Regression Model for Perceived Justice (Summary) 268

42. 5.35 Regression Coefficient of Satisfaction with

Recovery

269

43. 5.36 Regression Model for Satisfaction with Recovery

(Summary)

269

44. 5.37 Descriptive Statistics (Mean and Standard

Deviation) of Overall Airline Satisfaction w.r.t Each

Airline

270

45. 5.38 Test of Homogeneity of Variances 271

46. 5.39 One Way ANOVA Results for Overall Airline

Satisfaction

271

47. 5.40 Tukey HSD Multiple Comparisons Test for Overall

Airline Satisfaction

272-274

48. 5.41 Descriptive Statistics (Mean and Standard

Deviation) of Satisfaction With the Overall Quality

of Each Airline

275

49. 5.42 Test of Homogeneity of Variances 275

50. 5.43 One Way ANOVA results for Satisfaction with

Overall Quality of Airline

276

51. 5.44 Tukey HSD Multiple Comparisons Test for

Satisfaction with Overall Quality of Airline

277-278

52. 5.45 Comparison of Number of Service Failures in Each

Group w.r.t. Each Airline

280

LIST OF FIGURES

S.No Figure

No.

Figure Title Page No.

1 1.1 Levels of Customer Contact with Service Organizations 13

2 2.1 Location of Domestic Airports in India 54

3 2.2 Location of International Airports in India 55

4 2.3 Forces Shaping the Future of the Airline Industry 60

5 2.4 Market Share of Scheduled Domestic Airlines (Dec, 2011) 67

6 2.5 Worldwide Passenger Traffic: % Growth Total 2000 to

2010F

99

7 2.6 India Passenger Traffic: % Growth Total 2000 to 2010F 99

8 2.7 Strong Domestic Passenger Traffic Growth 100

9 2.8 Load Factor at the Highest Level in a Decade 100

10 3.1 The Research Model 157

11 5.1 Comparison of Failure Frequency in Percentage (Study I) 219

12. 5.2 Comparison of Failure Frequency in Percentage (Study II) 246

13. 5.3 Recovery Actions taken by Airlines after Service Failure 258

14. 5.4 Scree Plot Representing the Factors of Perceived Justice 265

15. 5.5 Comparison of Number of Service Failures in each Group

w.r.t. Airline

279

LIST OF ABBREVATIONS

S.No. Abbreviation Full Form

1. ATF Aviation Turbine Fuel

2. ATM Automated Teller Machine

3. AVOD Audio Video On Demand

4. CAA Civil Aviation Authority

5. CAGR Compound Annual Growth Rate

6. CAPA Centre for Asia Pacific Aviation

7. CCB Consumer Complaint Behaviour

8. CIT Critical Incident Technique

9. DGCA Director General of Civil Aviation

10. DJ Distributive Justice

11. F/C First Class

12. FDI Foreign Direct Investment

13. FSA Full Service Airline

14. GDP Gross Domestic Product

15. IATA International Air Transport Association

16. IFE In Flight Entertainment

17. IJ Interactional Justice

18. LCA Low Cost Airline

19. NACIL National Aviation Company of India Limited

20. NRI Non Resident Indian

21. PJ Procedural Justice

22. SAARC South Asian Association for Regional Cooperation

23. SSTs Self Service Technologies

24. VFR Visiting Friends and Relatives

1

Customer complaints are the schoolbooks from which we learn.

-- Anon

Service organizations are facing more intense customer service pressures than ever

before. It does not matter how excellent the service a company delivers, every

company still often makes mistakes in meeting the expectations of today’s customers

who tend to be more demanding and less loyal than ever before. Bitner (1993) argues

that due to the unique nature of services it is impossible to ensure 100% error-free

service. The retention of customers, for any business, can be a critical activity,

promoting the long-term health of the business organization. In the service sector,

retention of customers can be extremely profitable: a slight reduction in customer

losses (5%) could lead to an increase of profits of 25 to 85% as reported by Reichheld

and Sasser (1990).

For all service firms and the airline industry in particular, the provision and delivery

of high quality service has become a requisite for competing effectively (Zeithaml,

Berry and Parasuraman, 1993). The airline industry is a complex business where the

airport, airline companies and ground staff need to work closely to provide effective

services to passengers. In today’s scenario, the airline industry faces a number of

challenges like intense competition, the fact that the demand for air transport has

decreased during the past few years due to a global economic decline (Fodness and

Murray, 2007); the lower profitability in the industry (the world’s airlines

cumulatively lost $43 billion between 2001-2005- Anon, 2006); the rising price of oil

CHAPTER-1

INTRODUCTION

2

(accounting for approximately 15% of an airline’s costs; oil costs for the industry

which surged to $97 billion in 2005 at an average price of $57 per barrel of oil-Anon,

2006); the reality that supply far exceeds demand and demand fluctuates by season,

day of the week and time of the day (Tierman, Rhoades and Waguespack, 2008;

Anon, 2006). Therefore, it becomes necessary for the airline companies that they

should deliver their services more efficiently to customers because customer is a

source of profitability for the organization, as costs can be reduced by offering

customers delight and retaining them, rather than continuously acquiring new

customers. Chang, Chen and Chang (2008) suggest that airlines face a very specific

problem that could influence the satisfaction of customers, namely that they offer

multiple opportunities for mistakes to occur during service delivery and are therefore

particularly prone to service failures, and many internal mistakes or external

disruptions could cause customers to experience service failures. It is specifically the

response to a service failure (service recovery) that could give airlines a competitive

advantage, as an organisation’s response to a service failure could either restore

customer satisfaction and reinforce loyalty, or aggravate the situation by driving the

customer to a competitor. Currently, there is no research that has examined the

service failures and their effect on customer satisfaction in the Indian context with

special reference to the services provided by the airline companies to the customers.

Thus the primary purpose of this research is to find out the type of service failures that

are encountered by the customers of airlines and their effect on satisfaction and what

recovery actions are taken by the airlines to overcome these failures from the

customer’s point of view. This would help the airline companies to know the types of

failures which effect the satisfaction of customers the most and they can take

appropriate actions to improve upon them.

3

1.1 STATEMENT OF THE PROBLEM

It is the intent of this research to study the types of service failures that are

encountered by the customers and their effect on satisfaction in the context of services

provided by the airline companies to the passengers in the domestic sectors of India

and the recovery actions taken by the airlines to overcome the failures. Further,

following the work of Bitner, Booms and Tetreault (1990) the research work will

classify the failures in the group and category classification by type of incident

outcome. Since there is no known study addressing this issue, this study will attempt

to answer the following research questions

1. Does the perceived justice effect the satisfaction of customers after recovery?

2. Does the satisfaction with recovery of customers effect the overall airline

satisfaction?

1.2 RATIONALE OF THE PRESENT STUDY

It is inevitable that in aviation industry like other service sectors there is no service

failure occurring. The top-flight companies provide us with several lessons on how to

give a company the direction it needs to stay customer focused. They base decisions

on what their customers want and expect. Service leaders have long known that if

their customers don’t like the experience provided, value it and think it meets their

needs and experience, they won’t come back. Not only that, a happy customer

typically tells 5 or 6 other potential customers about a happy experience, and an

unhappy customer tells 10 to 15 others (Stephen W. Brown, 2003). The analysis of

service failures and service recoveries is beneficial to service organizations as it

allows management to identify and rectify common failure situations (Hoffman, Kelly

4

and Rotalsky, 1995). Goodwin and Ross (1992) conducted an experiment

investigating consumer responses to service failures using an equity theory

framework. Their findings suggest when consumers are offered an apology or are

provided with the opportunity to express their concerns to a service representative

those perceptions of satisfaction and fairness are enhanced, particularly when

recovery outcomes are favourable. Many researches have consistently found a

relationship between satisfaction and repurchase intentions, satisfaction and word of

mouth (Spreng, Harrell and Mackoy, 1995).

There are many empirical researches conducted on service failures and service

recoveries in various service sectors (like restaurants, hotels, airlines, medical, self-

service technologies etc.) and their effect on consumer satisfaction. These studies

provide a guideline to the present study to identify the service failures and recovery

actions taken by airlines to overcome the service failures and their effect on

customer’s overall satisfaction in the context of passengers travelling in domestic

sectors of India.

1.3 SCOPE OF THE STUDY

This research focuses on the service failures and recovery strategies adopted by the

airlines to overcome the various failures and their effect on customer’s overall

satisfaction. This study focused on those service encounters faced by passengers that

occurred during the last five years of their travelling in domestic sectors of India only.

Bejou and Palmer (1998) explain that the airline industry is especially prone to

service failures due to the service processes employed in service delivery. Although

airline passengers may hold certain expectations prior to their impending travel

5

(Coye, 2004), research indicates a number of causes leading to service failures in the

airline industry, including flight cancellations, diversions or delays, attitudes of

ground and cabin staff, strikes, reservation problems and overbooking of flights

(Bamford & Xystouri, 2005). At present, there are number of carriers operating in

domestic sectors of India and many new airlines are ready to join the carnival because

of open sky policy and deregulation of aviation industry. Carriers operating in

domestic sectors of India can be categorized in to many ways like government and

private airlines, high budget and low cost carriers, value and regional carriers etc. for

example govt. domestic carriers operating in India are Air India where as private

domestic carriers include Jet Airways, Jetlite, Spice Jet, Go Air, Kingfisher Airlines,

Indigo, Paramount Airways etc.

The main aim of this study is to analyze the service failures encountered by customers

(passengers) of airlines and thus create a basis for quality improvement. Although it is

highly unlikely that organisations can eliminate service failures, they can learn to deal

with these failures effectively (through service recovery) in an attempt to maintain

and even enhance customer satisfaction (Bamford & Xystouri, 2005; Maxham 2001;

Miller, Craighead & Karwan, 2000). This study is not limited to the service

encounters of Jammu and Delhi sectors only but for the collection of incidents the

respondents were approached from both the cities only.

The present chapter highlights the concept of service, model of service consumption,

attribution theory, perceived justice and present and future scenario of global aviation

industry.

6

1.4 CONCEPT OF SERVICE

Services refer to all economic activities whose output is not a physical product or

construction, is generally consumed at the time it is produced, and provides added

value in forms (such as convenience, amusement, timeliness, comfort or health) that

are essentially intangible concerns of its first purchase. Features like intangibility,

perishability, variability and inseparability distinguish the services from other

physical goods. The concept of service defined by Heskette (1986) as the way in

which the organisation would like to have its services perceived by its customers,

employees, shareholders and lenders i.e. the organisation’s business proposition. In

the words of Edvardsson et al (2000) service concept as a detailed description of the

customer needs to be satisfied, how they are to be satisfied, what is to be done for the

customer and how this is to be achieved.

Customer service has a direct impact on the customer’s level of satisfaction, which in

turn, ultimately reflects on the service provider’s bottom line. Although, it is difficult

to measure the true impact of customer service, quality customer service has been

cited as a means for improving a variety of aspects of a business. The following are

the several objectives of services like:-

• The key to getting closer to one’s customers is making it easier for them to do

business with the service provider, better known as convenience (Anton,

1996).

• The number and quality of services offered, establishes the image of the

service provider.

7

• Multiple services reinforce customer’s sense of security. Protective services

such as security staff, emergency medical facilities, clearly marked exits instil

confidence in customers.

• Quality customer service has the potential to generate increased traffic for the

service provider. Further, the delivery of quality service and customer

satisfaction has been clearly linked with profits, cost savings and market share

(Sager, 1994).

• Service providers who extend their services beyond minimal expectations

have a far better chance of satisfying their customers. The critical differences

in customer/guest service are what often separate hospitality industry leaders

from industry followers.

Service industries and companies include those industries and companies typically

classified with in the service sector whose core product is a service like lodging,

transportation, insurance and financial services, health care services etc. certain

services require customers to enter the service factory and stay there until service

delivery is complete (Zeithaml et al, 2008).

The size of the service sector is increasing around the world, in both developed and

emerging countries. The Indian economy is the second fastest growing economy in

the world with the growth rate of the GDP at 8.5% in 2006-07. The economy of India

is the 12th largest in the world (GDP of US $ 1.09 trillion in 2007). India ranks 15th in

the services output and it provides employment to around 23% of the total workforce

in the country. The various services under this sector are construction, trade,

hospitality, food & beverage services, communication, social and personal services,

insurance, financing and other business services. The service sector contributes the

8

most to the Indian GDP, only 15% in 1950 increased from 43.695% in 1990-1991 to

around 51.16% in 1998-1999. In 2005, it was 53.8% and now the contribution reaches

to 57% (2010).

Burkart and Medlik (1974) had rightly said that tourism is about being elsewhere and

a major component of any tourist activity must necessarily be an element of

transportation. Transport industry provides services for all and sundry, it is not

possible to provide exclusive transport facility for the tourists except the provision of

special coaches, fare concessions and other incentives.

A well known and co-ordinated system of transport plays an important role in the

sustained economic growth of a country. The present transport system of India

comprises several modes of transport including rail, road, coastal shipping, air

transport, etc. Transportation in India has recorded a substantial growth over the years

both in spread of network and in output of the system. The Ministry of Civil Aviation

is responsible for the formulation of national policies and programmes for

development and regulation of civil aviation and for devising and implementing

schemes for orderly growth and expansion of civil air transport. Its functions also

extend to overseeing the provision for airport facilities, air traffic services, carriage of

passengers and goods by air, safeguarding civil aviations operations, regulations of air

transport services, licensing of aerodromes, air carriers, pilots and aircrafts

maintenance engineers.

An airline is a significant component which provides air transport services for

travelling passengers and/or freight. Airlines lease or own their aircraft with which to

supply these services and may form partnerships or alliances with other airlines for

mutual benefit. Generally, airline companies are recognized with an air operating

certificate or license issued by a governmental aviation body. Airlines vary from those

9

with a single aircraft carrying mail or cargo, through full-service international airlines

operating hundreds of aircraft. Airline services can be categorized as being

intercontinental, intra-continental, domestic, regional, or international, and may be

operated as scheduled services or charters. (Airline-www.en.wikipedia.org)

An airline company provides services to its passengers at the airport (check-in, during

boarding and on arrivals), F/C class lounge services, ground staff service, cabin staff

service, services at the airline website and onboard products offered to the passengers.

India is expected to be the fastest growing civil aviation market in the world by 2020

with about 420 million passengers being handled by the Indian airport system,

according to the Economic survey 2010-11. The number of passengers carried by the

domestic airlines during Jan-Feb 2011 was 9.51 million as against 7.95 million in the

corresponding period in 2010, thereby registering a growth of 19.6%, according to the

data released by DGCA. The domestic airlines registered a growth of almost 16 %

year-on-year (y-o-y), carrying a record 5.2 million passengers in Dec. 2009. The

domestic air passenger traffic grew by 19% in 2010, registering 51.53 million

passengers as compared to 43.3 million in 2009, according to economic survey 2010-

11. (Aviation, March 2011)

In today’s scenario, around 12 domestic airlines and above 60 international airlines

are operating in India. The growth of airlines traffic in aviation industry in India is

almost four times above international average. Aviation industry in India holds around

69% of the total share of the airlines traffic in the region of South Asia.

(business.mapsofindia.com)

10

1.5 MODEL OF SERVICE CONSUMPTION

Consumption of services is different from the consumption of products. In the context

of transportation sector for consumption of services, customers are required to enter

the service factory (transportation modes like cars, coaches, cruises, airlines etc.) and

stay there until service delivery is complete. According to Lovelock et al (2010),

service consumption can be divided into three principal stages:

1.5.1 Prepurchase Stage

1.5.2 Service Encounter Stage

1.5.3 Post-encounter Stage

1.5.1 THE PREPURCHASE STAGE: This stage begins with need arousal and

continues through information search and evaluation of alternatives to a decision on

whether to make a service purchase. Like a person wants to go to a destination, for

this, first he searches the various modes of transportation (cars, coaches, railways,

cruise and airline) available to reach that destination and then evaluate each mode

according to the budget and time availability with him and finally he decides to go by

that airline.

1.5.2 THE SERVICE ENCOUNTER STAGE: After making a purchase decision,

customers move on to the core of the service experience – the service encounter stage.

A service encounter is a period of time during which a customer interacts directly

with a service provider (Shostack, 1985). Irrespective of the nature and length of the

contact, each ‘encounter’ represents an important ‘moment of truth’ for the customer.

The later term, originally used by Normann has more recently been termed the

11

‘bullfight metaphor’ by Mattsson as it underlines strongly “the uniqueness and the

importance of every encounter between the customer and the service provider’.

In some instances, the entire service experience can be reduced to a single encounter,

involving ordering, payment and execution of service delivery on the spot. In other

cases, the customer’s experience includes a sequence of encounters. This can mean an

extended process that may be spread out over a period of time, involving a variety of

employees, and even taking place in different locations. It is from these service

encounters that customers build their perceptions. Service processes usually consist of

a series of encounters such as experience with a flight, from making a reservation to

checking in, taking the flight and retrieving bags on arrival (Lovelock et al, 2010). It

is in these encounters that customers receive a snapshot of the airline’s service quality

and each encounter contributes to the customer’s overall satisfaction and willingness

to do business with the airline again. From the airline’s point of view, each encounter,

thus, represents an opportunity to prove its potential as a quality service provider and

to increase customer loyalty.

Although some researchers use the term “encounter” simply to describe personal

interactions between customers and employees (Suprenant and Solomon, 1987),

realistically encounters also involve interactions between customers and self-service

equipment (Meuter and Bitner, 1998).

Services can be grouped into three levels of customer contact, representing the extent

of interaction with service personnel, physical service elements, or both.

a. High Contact Services tend to be those in which customers visit the service

facility in person. It also involves significant interaction among customers,

service personnel, equipment and facilities. Customers are actively involved

12

with the service organization and its personnel throughout service delivery e.g.

medical services or airline services. There are also examples of services that

have traditionally been high contact but can be low contact today because of

technology and include retail banking, purchase of retail goods and higher

education.

b. Medium Contact Services- It involves a limited amount of contact between

customers and elements of the service organization. The purpose of such

contacts is often limited to:

(a) establishing a relationship and defining a service need;

(b) dropping off and picking up a physical possession that is being serviced, or

(c) trying to resolve a problem.

c. Low Contact Services- It involves minimal or no direct contact between

customers and the service organization. Both mental stimulus-processing (e.g.

radio, television) and information processing services (e.g. insurance) fall into

this category.

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Fig 1.1 Levels of Customer Contact with Service Organizations

Source: Principles of Services Marketing and Management- Second Edition- Christopher Lovelock, Lauren Wright, Prentice Hall, 2002

Service encounters are critical in all industries, including those that have not been

traditionally defined as service industries. These are critical moments of truth in

which customers often develop indelible impressions of a firm. In fact, the encounter

frequently is the service from the customer’s point of view (Bitner, 1990). Service

encounters have been defined as the moment of interaction between a customer and a

firm (Shostack, 1985; Keaveney, 1995; Winstead, 1997). Encounters may take place

face-to-face in an actual service setting, over the phone, through the mail, or even

over the internet. Each encounter is an opportunity for a firm to sell it, to reinforce its

offerings, and to satisfy the customer. However, each encounter is also an opportunity

to disappoint.

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Previous research illustrates how important individual service encounters are for

business success. Encounters have been shown to affect critical outcomes such as

customer satisfaction (Bitner, Booms and Tetreault, 1990; Bitner et al, 1994;

Parasuraman, Zeithaml, and Berry, 1988, 1994; Smith and Bolton, 1998, Kivela and

Chu, 2001; Holloway and Beatty, 2008), intention to repurchase (Bitner, 1990;

Keaveney, 1995; Meuter, Ostrom, Roundtree, and Bitner, 2000; Smith and Bolton,

1998, Petrick, Tonner and Quinn, 2006), word-of-mouth communications (Bitner,

1990; Keaveney, 1995; Meuter et al, 2000; Tax, Brown, and Chandrashekaran, 1998);

relationship quality (Czeipiel, 1990), and loyalty (Gremler and Brown, 1999).

Ineffective or unsuccessful service encounters can result in significant costs to the

firm such as performing the service again, compensating customers for poor

performance, lost customers and negative word of mouth (Bitner et al, 1994,

Keaveney, 1995; Tax and Brown, 1998; Tax et al, 1998). Empirical research also

affirms the importance of service encounters in the global assessment of service

quality (Parasuraman et al, 1994). “in most services, quality occurs during service

delivery, usually in an interaction between the customer and contact personnel of the

service firm”. (Zeithaml, Berry and Parasuraman, 1998).

Service quality researchers have suggested that “the proof of service (quality) is in its

flawless performance” (Berry and Parasuraman, 1991), a concept akin to the notion of

“zero defects” in manufacturing. Others have noted that “breakthrough” service

managers pursue the goal of 100% defect-free service (Heskett, Sasser and Hart,

1990). From the customer’s point of view, the most immediate evidence of service

occurs in the service encounter or the “moment of truth” when the customer interacts

with the firm. Thus one central goal in the pursuit of “zero defects” in service is to

work toward 100% flawless performance in service encounters. Here, flawless

15

performance is not meant to imply rigid standardization, but rather 100% satisfying

performance from the customer’s point of view. The cost of not achieving flawless

performance is the “cost of quality” which includes the costs associated with redoing

the service or compensating for poor service, lost customers, negative word of mouth,

and decreasing employee morale.

Situations arise in which quality is low and the problem is recognized by both the firm

(i.e. employees) and the customer, but there may be disagreement on the causes of the

problem and the appropriate solutions. In service encounters such disagreements, are

sure to diminish customer satisfaction; underscore the importance of understanding

the types of events and behaviors that cause customers to be satisfied or dissatisfied.

Because the service encounter involves at least two people, it is important to

understand the encounter from multiple perspectives. Armed with such understanding,

firms are better able to design processes and educate both employees and customers to

achieve quality in service encounters (Berry and Parasuraman, 1991).

Types of Service Encounters: - There are three general types of service encounters:

a.) Remote Encounters- It can occur without any direct human contact such as when

customer interacts with a bank through the ATM system, with ticketron through an

automated ticketing machine, with a retailer through its internet website, or with a

mail-order service through automated touch-tone phone ordering. Remote encounters

also occur when the firm sends its billing statements or communicates other types of

information to customers by mail. Although there is no direct human contact in these

remote encounters, each represents an opportunity for the firm to reinforce or

establish quality perceptions in the customer. In remote encounters the tangible

evidence of the service and the quality of the technical processes and systems become

the primary basis for judging quality. More and more services are being delivered

16

through technology, particularly with the advent of internet applications. Retail

purchases, airline ticketing, repair and maintenance, troubleshooting, and package and

shipment tracking are just a few examples of services available via the internet.

b.) Phone Encounters- In many organizations (such as insurance companies, utilities,

and telecommunications), the most frequent type of encounter between an end

customer and a firm occurs over the telephone. Almost all firms (whether goods

manufacturers or service businesses) rely on phone encounters to some extent for

customer service, general inquiry, or order-taking functions. The judgement of quality

in phone encounters is different from remote encounters because there is great

potential variability in the interaction. Tone of voice, employee knowledge, and

effectiveness/efficiency in handling customer issues become important criteria for

judging quality in these encounters.

c.) Face-to-face Encounters- It occurs between an employee and a customer in direct

contact. At Disney theme parks, face-to-face encounters occurs between customers

and ticket takers, maintenance personnel, actors in Disney character costumes, ride

personnel, food and beverage servers, and others. For a company such as IBM, in a

business-to-business setting direct encounters occur between the business customer

and sales people, delivery personnel, maintenance representatives, and professional

consultants. Determining and understanding service quality issues in face-to-face

contexts is the most complex of all. Both verbal and non verbal behaviours are

determinants of quality, as are tangible cues such as employee dress and other

symbols of service (equipment, information brochures, physical setting). In face-to-

face encounters, the customer also plays a role in creating quality service for

herself/himself through her/his own behaviour during the interaction.

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Characteristics of Service Encounters: - (customer-employee service encounters)

a. Service encounters are purposeful.

b. Service providers for their past are not generally altruistic.

c. In a service encounter, prior acquaintance between participants is not required.

d. In most encounters, task related information exchange dominates.

e. Service encounters are limited in scope, with the scope of interchange being

restricted by the nature and content of the service to be delivered.

f. The roles played by a service provider and a client, in an encounter, are

generally well defined and understood by both parties.

g. A temporary suspension of the normal social status of participants often

occurs in service encounters (Baron and Harris, 2007).

1.5.3 THE POST-ENCOUNTER STAGE: In this stage, customers evaluate the

service performance they have received and compare it with their prior expectations.

The terms ‘quality’ and ‘satisfaction’ are sometimes used interchangeably. It is

believed that perceived service quality is just one component of customer satisfaction,

which also reflects price/quality trade-offs, and personal and situational factors.

Consumer satisfaction and service quality has each been the subject of extensive, but

separate research, although many studies of consumer satisfaction have been

conducted in service settings. Most researchers in the services domain have

maintained that these two constructs are distinct (Bitner, 1990; Parasuraman, Zeithaml

& Berry, 1988). Customers perceive services in terms of the quality of the service and

how satisfied they are overall with their experiences.

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Satisfaction is generally viewed as a broader concept, where as service quality focuses

specifically on dimensions of service. Service quality is a focused evaluation that

reflects the customer’s perceptions of: reliability, assurance, responsiveness, empathy

and tangibles. Satisfaction, on the other hand, is more inclusive. It is influenced by

perceptions of service quality, product quality and price as well as situational factors

and personal factors.

Both satisfaction and service quality literatures have emphasized the idea that

consumers make a comparison between the performance of the product or service and

some standard. The service quality literature has maintained that the distinction

between perceived service quality and satisfaction is that they use different standards

of comparison (Bitner, 1990; Zeithaml et al, 1993). These authors have argued that

the standard of comparison in forming satisfaction is predictive expectations, or what

the consumer believes will happen, while perceived service quality is the result of a

comparison of performance and what the consumer feels a firm should provide.

The success of service firms depends greatly on their ability to deliver consistent,

satisfying consumption experiences to their customers. However, even the companies

with the best strategic plans and the tightest quality control procedures cannot avoid

mistakes in all interactions with customers. Recognizing that completely eliminating

service mistakes or failures is an insurmountable task, service firms should learn to do

the next best thing- rectify the service delivery mistakes (Webster and Sundaram,

1998).

A customer may or may not report these service failures to the organisation. A service

failure is reported to a firm in the form of complaints. A complaint to an airline

company is any type of formal complaint filed by an airline customer either to an

airline responsible for the grievance or a government office responsible for overseeing

19

the airlines national industry. Airline complaints generally arise out of problems

experienced during air travel that were left unresolved.

And service failures are specific events that lead to dissatisfying service encounters

from the customer’s point of view (Bitner et al, 1990). It is the efficiency of an airline

company to immediately identify and rectify the service failures encountered by a

customer which termed as service recovery, defined as:

……..the actions of a service provider to mitigate and/or repair the damage to a

customer that results from the provider’s failure to deliver a service as is designed

(Johnston and Hewa, 1997)

Service failure can occur in several ways, such as when customer requested service is

unavailable, when the service is unreasonably delayed, or when the core service is

delivered below a minimum acceptable level (Bitner, Booms, and Tetreault, 1990).

Whether the initial reaction to service failure is one of mere disappointment or one of

anger, a customer’s negative attitude can become much stronger if the firms fail to

resolve the service failure. Fortunately, the use of appropriate service failure recovery

efforts can convert a problematic situation into a favourable service encounter, thus

enhancing repurchase intentions and positive word-of-mouth communications

(Spreng, Harrell, and Mackoy, 1995) and restoring or even enhancing customer

loyalty (Kelley, Hoffman, and Davis, 1993). Responding to service failure tends to

result in secondary satisfaction which helps the firm build strong, long-standing and

beneficial relations with customers. (Etzel and Silverman, 1981; Gilly, 1987;

Westbrook, 1987)

Past research reveals a linkage between customer satisfaction and two specific

activities performed by a firm, customer complaint handling procedures and the

20

nature of compensation. For example, providing an opportunity for customers to

express their feelings and then listening conscientiously to customers’ complaints has

been found to increase customers’ perceptions of fairness and satisfaction (Goodwin

and Ross, 1992). Further offering customers a marginal discount and an apology as

compensation for service failure, as compared to a mere apology, results in greater

customer satisfaction and perceived fairness. The monetary amount of restitution (i.e.

percentage of initial service charge) and prior usage experience were found to also

influence perceptions of satisfaction, appropriateness of compensation, reputation of a

firm, and intention to return. Unsurprisingly, a greater monetary compensation was

considered to be more appropriate by customers and consequently resulted in

heightened customer satisfaction (Goodwin and Ross, 1992; Meghee, 1994).

1.6 ATTRIBUTION THEORY

Attribution theory has been introduced in consumer research since the beginning of

1970s. Consumer researchers adopt attribution theory in many different areas. For

example, attribution theory has been adopted to explain consumer product purchase or

selection (Scott and Yalch, 1980; Tybout and Scott, 1983), the consequences of

product failure or success (Curren and Folkes, 1987; Richins, 1983), the reasons that

consumers switch brands (Mazursky et al, 1987), the endorser’s credibility

(Sparkman, 1982; Wiener and Mowen, 1986), and consumer responses to research

mail surveys (Allen et al, 1980; Furse et al, 1981; Hansen and Robinson, 1980).

Buyer, seller, and environmental situation can all contribute to a product/service

failure. Folkes (1984) suggested that the locus of causality influenced consumer

equity reactions and beliefs about who should solve problems. Consumers generally

21

hold that problems arising from consumer actions should be solved by consumers,

whereas problems arising from firms’ actions should be solved by firms.

According to Heider’s people perception, consumers in a service failure encounter

may reach a causal inference of the failure based on their observation of the service

delivery and their experience with the firm. Consumers can attribute the failure to any

entities involved in the service delivery process such as firms, themselves, and/or

environmental situations. The environmental situation factor may include anybody

who is responsible for the failure except firms and consumers. For example, weather

can cause a flight delay, a noisy customer in the restaurant can cause an unpleasant

service experience, and a power outage can cause the interruption of a surgery. All of

these factors listed can be classified as environmental situation factors.

When the delivery of a service does not match customers’ prior expectations or

normative standards, customers may engage in attribution processes to make sense of

what has occurred (Bitner, 1990). According to attribution theory (Hewstone, 1989;

Weiner, 1982), causes may be of two types-internal and external. Internal causes

include factors inherent to the service provider, such as the amount of effort put into

the delivery of a service, the strategies used to deal with service situations, and the

skill level demonstrated. External causes include factors outside the service

encounter; include the activities of other people such as suppliers, or bad luck.

Research into the fundamental attribution error (Heider, 1958) indicates that in

general, customers will attribute causes for service breakdowns to features that are

internal to the service provider (for example, the provider’s inexperience or the

organization’s poor training programs) rather than to luck or -organizational policy

past research indicates that the value of customer attribution depends upon the range

of information available regarding the cause of the problem including the frequency

22

of the problem, perception of whether the problem is preventable or due to bad luck

and the extent to which the service providers try to solve the problem (Bitner, 1990;

Folkes, 1984).

When the causal agent is anchored on the firm, consumers expect the firm to recover

service failures. How much consumers want to redress from the firm is based on the

norm of perceived justice governing the exchange relationship.

1.7 PERCEIVED JUSTICE

Another framework used to evaluate the service recovery process is that of justice.

What is perceived to be fair and reasonable in the circumstances will influence the

level of customer satisfaction. Service and organizational research studies (Bies and

Moag, 1986; Goodwin and Ross, 1990; Sparks and Callan, 1995; Tyler, 1994) have

confirmed that customer satisfaction is not merely based upon the ultimate outcome of

the service recovery but also upon the procedures used to reach an outcome, as well as

the interactions along the way. Clemmer and Schneider (1996) make the point that in

services marketing, what is important is the need to focus on processes and

relationships rather than outcomes, due to the intangible nature of services and the key

role played by service personnel. Hence, the effectiveness of service recovery

techniques used by tourism and hospitality firms may rely upon customers’

evaluations of both the intervention process and the outcomes of this exchange.

Structure of Perceived Justice

Justice is first conceptualized as a social and personal device designed to facilitate the

acquisition of other desired resources (Lerner, 1981). Justice is meaningful only when

23

it is defined in contrast with injustice (Karniol and Miller, 1981). Individuals can

perceive an injustice occurring along different dimensions.

a.) Distributive Justice- The first dimension of perceived justice is related to the

allocation of benefits and rewards which is called distributive justice. Adams (1965)

stated that social behaviour was affected by beliefs that the allocation of benefits and

costs within a group should be equitable. When an individual perceives that benefits

have not been allocated equitably, he/she experiences distress (Walster et al, 1973),

which in turn motivates him/her to restore the distributive justice.

Distributive justice is closely related to the outcome of service delivery. Consumers

make an exchange with a firm expecting to receive benefits that are equivalent to the

cost to the consumer (Goodwin and Ross, 1992). When a service failure occurs, the

customer does not receive equivalent benefits, and will perceive distributive injustice

that further leads to customer dissatisfaction. For example, airline passengers pay

tickets to exchange the transportation service from one place to another. If an airline

cancels a flight for some reason, the airline is supposed to arrange another flight for

all passengers. Otherwise, the outcome of the service delivery will be considered

unfairly distributed.

The violation of distributive justice indicates that the outcome of service delivery is

not the same as what consumers expect. Distributive justice only explains one aspect

of perceived justice in the social exchange relations. In many situations, even though

outcomes are perceived as just, individuals may still experience perceived injustice if

the procedure that reaches the outcome is unjust.

b.) Procedural Justice- The systematic study of procedural justice begins with the

work of Thibaut and Walker (1975). Procedural justice refers to the fairness judgment

24

of a decision making procedure. The initial study of procedural justice focuses on

dispute resolution procedures and legal procedures (Thibaut and Walker, 1975). Later

on, many of the explanations and prescriptions are extended to social decision-making

procedures in other contexts. Lind and Tyler (1988) reviewed procedural justice in

law, in the political arena, and in organizations. In general, individuals evaluate

procedural justice based on agreed-upon rules (Leventhal, 1980).

These rules can have a wide variety of manifestations in any given procedural

situation. Leventhal (1980) found that individuals evaluated procedures based on the

following rules: consistency, bias suppression, accuracy of information, correctability,

representativeness, and ethicality. Consistency requires that a fair procedure be

applied consistently across person and time. In other words, all individuals affected by

the procedure should have the same rights and be treated similarly. Meanwhile, the

procedure should be enacted the same way each time it is used. Bias suppression

refers to the concept that the decision makers should be unbiased. There are two

possible sources of bias. First, decision makers may have an interest in a specific

decision. Second, prior beliefs of decision makers may influence the decision making

process. The bias suppression rule requires a decision maker to avoid both types of

bias when making a decision. The rule of accuracy of information requires that a

decision be based on accurate information and on well-informed or expert opinion.

Correctability requires a fair procedure to include provisions for correcting bad

decisions. Representativeness ‘dictates that all phases of allocation process must

reflect the basic concerns, values, and outlook of important subgroups in the

population of individuals affected by the allocation process’ (Thibaut and Walker,

1975). Finally, ethicality requires a procedure to conform to personal standards of

ethics and morality. These rules guide an individual’s evaluation of procedural justice.

25

Studies in procedural justice generally find that the procedure used to allocate

outcomes has an influence on people’s judgement of the fairness of a decision that

was independent of outcome favourability (Folger and Greenberg, 1985). In other

words, given the same unfavourable outcome, individuals feel less dissatisfied when

they perceive the procedure to be fair than when they perceive the procedure to be

unfair.

c.) Interactional Justice Although the decision-making procedure is important in

understanding peoples’ reactions to the fairness of a decision, there is a growing

interest focusing on the enactment of a procedure. Bies and Moag (1986) referred the

fairness judgment of the enactment of a procedure as interactional justice which

concerns the decision makers’ behaviours during the enactment of procedures. For

example, people expect to be treated with truthfulness and respect in communication

(Bies and Moag, 1986). In addition to the two communication criteria (truthfulness

and respect) identified by Bies and Moag (1986), providing explanation or

justification for a decision can influence individuals’ interactional justice. Providing

reasons and information for a decision makes the decision understandable and

acceptable and enhances the perceived justice among parties. The distinction between

procedural justice and interactional justice is not clear-cut. The degree of perceptual

overlap between interactional and procedural fairness judgement has been articulated

by Bies and Moag (1986) as follows:

“Procedures become meaningful only when they are experienced by someone. That is,

people do not really know the procedure until it is implemented. Once the procedure

is enacted, people may make inferences about the fairness of the procedure from the

actions of decision makers. According to this reasoning, procedural fairness

26

judgements are based, in part, on people’s attributions regarding some action or

outcome.

Interactional fairness evaluations will generalize to the procedure itself only when a

person attributes the responsibility for the actions to an organization, a systemic

attribution, rather than a decision maker. For example, if a person believes that

deception and rudeness by recruiters are not isolated occurrences, but condoned by

the organization, then he or she will more likely to assume the decision-making

procedures are unfair. On the other hand, if a person attributes the deception and

rudeness solely to a decision maker and not an organization, then there should be less

implication for the procedure itself.”

1.8 GLOBAL AVIATION INDUSTRY

Air transport markets and the airline industry have been transformed over the last 40

years. The number of passengers has risen tenfold and cargo volumes have grown

fourteen fold, despite repeated shocks from recessions, terrorism and disease. Demand

is volatile but consistently returns to a rapidly growing trend. Supply has also changed

significantly. Having been a highly regulated industry during the first three post-war

decades, market access was increasingly liberalized starting with US domestic

markets in the late 1970s, followed by US ‘Open Skies’ policy on international

markets from the early 1990s, and the European single aviation market in the mid-

1990s. There have been many new entrant airlines in the past three decades, while exit

has been limited. As a result, the number of commercial airlines, flying Western-built

jets, has risen to over 1,000. Consumers and the wider economy have reaped the

benefits of a substantial increase in the choice of travel options by destinations,

27

frequencies, and business models available at lower cost, higher safety, and a smaller

environmental footprint per passenger mile travelled than ever before. Airline owners

have, however, not even been able to recover their cost of capital (Porter, 2011).

In the 66th IATA Annual General Meeting and World Air Transport Summit Berlin,

Germany, Director General and CEO of IATA Giovanni Bisignani submitted about

the global air transport industry- 2.4 billion passengers, 43 million tonnes of cargo, 32

million jobs, just 1 accident for every 1.4 million flights, 2% of global carbon

emissions, $545 billion in revenue and $217 billion in debt (State of the Air Transport

Industry, 2010).

The airline industry in 2050

An industry that carried 2.4 billion passengers and shipped 40 million tonnes of goods

in 2010 carried 16 billion passengers and shipped 400 million tonnes of goods this

year. Air transport has grown at almost twice the rate of GDP expansion, meaning that

more people are travelling than ever before and more frequently than ever before.

Global advances in general technology have been mirrored in the airline industry,

which has made the sector unrecognizable from what it was in 2035. Travelling by air

is faster (when desired), safer and more seamless than ever before.

Unsurprisingly, mobile technology available to air transport consumers is also

affecting their behaviour when they travel. LIMPs mean that they have the ability to

effortlessly and seamlessly change itineraries as and when they see fit. Passenger

information and transfer offices are a thing of the past. And fortunately so are queues.

In-flight entertainment systems are also no longer present on most aircrafts, because

passengers have all of their personal audio, video or virtual entertainment needs to

28

hand and available to take on board, downloaded directly from Internet 8, which

automatically charges them the correct amount.

Customers in 2050- The general aging of the world population has resulted in airline

customers being on average older than ever before. However, healthcare advances

mean that even though our customers are older, they are not necessarily less mobile.

Younger travellers are significantly more aware of air travel and more worldly-wise

than previous generations. Many are frequent fliers by the time they have learned to

talk. As a result, most 4-5 year olds have already established preferences about air

travel, including brand loyalty.

Increased access to advance communication tools and the widespread use of social

media has resulted in individuals and businesses having increasing networks of global

friends or business contacts. But no technology has been able to replace the human-to-

human contact facilitated by air travel.

Forty years ago the industry’s two largest markets were still the United States and

Europe. But this has not been the case for a long time. The shift eastward started early

in the century supported by strong growth in China and India. When Indians started

travelling with the same propensity as North Americans, that market alone jumped to

four billion passengers. A similar leap has already happened in the likes of Brazil,

Russia, and Mexico. It is starting to happen with Indonesia, the Philippines, Vietnam,

Iran, Turkey, Chile, and South Africa. The result is an increasingly socially,

culturally, and ethnically diverse pool of customers, with increasingly diverse

demands based on their culture, social background, or ethnicity that wish to visit an

increasingly diverse range of destinations. In turn, operators have made their product

29

offerings equally diverse to cater to such an array of demands. This has been best

achieved by the truly global operators with highly developed loyalty programs.

Increased access to information has also led to our customers being better informed

than ever before. And better informed customers are more demanding customers.

Customers’ priorities in 2050- In 2050, safety and security are still top priorities for

passengers, but the increasingly rare nature of safety and security incidents means that

these priorities are less frequently reinforced. Safety in particular is less of a concern,

as automation and new technology have continued to revolutionize safety standards.

The same technology has meant that reliability is also something that plays a

decreasing role in consumer choice, given that flights are almost always on time and

are almost never cancelled. There are still sporadic security threats regarding air

transport, but these threats have gradually decreased over the past 40 years, again due

in most part to technological advances that have improved the screening and tracking

of passengers and cargo.

Price is still a key driver of consumer choice, but access to information has made

price transparency almost absolute, which has made price differences between

comparable products almost extinct. As such, price has become more of a driver when

choosing between different product types, and operators have learned to offer a wider

array of products to cater to every need. Whether distinguishing between business and

leisure travellers, or between older and younger travellers, today pricing is more

reflective of what has become the most precious of commodities: time.

• Business people still value their time above all else and are, therefore, willing

to pay a premium for the fastest available transport options.

30

• Amongst leisure passengers, technological advances and the elimination of

security, customs, and immigration delays have fuelled a large increase in the

demand for international and cross-cultural travel.

• Older travellers are seeking greater comfort and convenience, as well as a

slower pace or travel. As pension ages have steadily climbed, some retirees

have had to become more price conscious than others, but many view the

journey as part of the experience as opposed to just a means of getting to their

final destination. And for this they are prepared to pay extra.

• For pre-adolescent travellers, priorities have not changed substantially over the

past 40 years. The method and the medium may have changed, but these

consumers still basically just want to be entertained. Many air carriers have

already moved away from investing in in-flight entertainment systems because

the majority of pre-adolescents have all of the entertainment they need on their

LIMPs.

• For adolescents, entertainment is also still a high priority, but entertainment

that is more about being social than individual. For these adolescents, this is

continuing the shift away from air travel just being a means of getting to their

destination; it is making the travel itself an important part of the whole trip.

• This trend is also the case for young adults, as more and more operators offer

the opportunity for them to use their journey to meet and socialize with

members of the opposite sex. This has become particularly popular amongst

young adults who are travelling in a group, as they are now able to ‘get the

party started’ on the aircraft instead of having to wait until they reach their

destination.

31

• Customers from what used to be called developing economies are trying air

transport services for the first time in ever-increasing numbers. Often, their

first trips are for VFR purposes, but rising living standards normally lead them

into the tourism market, some faster than others. These customers tend to seek

the lowest cost transport options.

• Those customers from developed economies are demanding more and more

authenticity and customization. For them, just travelling by air is not enough,

they want a personal and unique experience. Having visited every continent

and scores of different countries, these passengers are increasingly looking for

something ‘extra’, something ‘special’. Week-long ‘Aircations’ (cruises in the

sky) have become popular. Space travel is becoming more reasonably priced,

although stays in ‘Spatels’ (space hotels) are still reserved for the relatively

well off and week-long stays in Space Spas are only for the truly wealthy.

• One demand that has become consistently high among every type of traveller

is customer service. With almost no price differentials between comparable

products, operators have been forced to achieve ever greater levels of

customer service. In fact, customer service has become effectively ‘atomized’,

from mass to niche to individual.

• Ethical consumerism continues to be a growing trend. Once upon a time,

environmental concerns had an increasing influence over consumer choices.

Whilst aviation’s contribution to climate change has largely been addressed,

this kind of ethical consumerism was the start of the trend that now focuses on

such issues as the preservation of local cultures and livelihoods. In addition,

with widespread economic development across the planet, the definition of

32

‘rights’ has been expanded to include things like annual vacations and

minimum lifestyle standards (IATA Vision 2050, 2011).

33

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3

2.1 INTRODUCTION

India, the second largest economy in the world is a magnificent mix of authentic and

modern culture. It is the world’s second largest growing economy and the world’s

most populous democracy. India is a mix of so many different religions and over four

hundred different languages are spoken throughout the country. India consists of

seven union territories and twenty eight states. India is home to Indus valley

civilization and four of world’s major religions namely Jainism, Hinduism, Buddhism

and Sikhism originated here. India is world’s fourth largest economy by purchasing

power parity and eleventh largest economy in the world with GDP of over $1.3

trillion. India attracts an FDI of over twenty billion dollars on an annual basis. Over

the years India has witnessed a continuous increase in inflow of funds by the foreign

institutional investors who are very bullish on India’s long term growth story. It is

estimated that India will be world’s third largest economy after USA and China by

2020 (Vivek, 2011). The sub- continent of India is a wonder that attracts people from

around the world. The seventh largest country in the world, The Republic of India

comprises of 28 states. Different states in the country connected by the network of

railways, roads and air routes. With globalization and the emergence of economy

airlines, air transport has emerged as a popular mode of transport. (Anjali, 2011)

The aviation industry in India is one of those sectors that saw a constant pace of

growth among the other industries in the world over the past many years. Research

indicates the global aviation industry is poised to grow at a 5.6% CAGR (Compound

CHAPTER-2

INDIAN AVIATION SECTOR

44

Annual Growth Rate) over the next 15 years. While major conventional mature

markets such as the US and Europe will witness a significant fall in market share from

61% to 52%. Emerging markets such as India, China and the Middle East, offer a

great growth potential (Overview, 2008).

With the rise in the economy of the country and followed by liberalization in the

aviation sector, the aviation industry in India went through a complete transformation

in the recent period. The growth in the Indian economy has increased the GDP above

8% and this high growth rate will be sustained for a good number of years. The

growth of airlines traffic in aviation industry in India is almost four times above

international average (Role of aviation industry in India GDP, 2008). It has grown

enormously and expected to have a growth which would be above 25% in the travel

segment. This industry holds around 69% of the total share of the airlines traffic in the

region of South Asia. The liberalization of aviation industry in India has precipitated

the boom for domestic and international passenger carriers. The number of passengers

carried by the domestic airlines in the year 2011 (Jan-Dec) were 606.63 lakhs as

against 520.21 lakhs in the year 2010 there by registering a growth of +16.6%,

according to the latest data released by the Directorate General of Civil Aviation

(passengerdata/dgca, 2012). The domestic air passenger traffic grew by 19 percent in

2010, registering 51.53 million passengers as compared to 43.3 million in 2009,

according to the Economic Survey 2010-11 (Aviation, March 2011).

In India, the aviation sector continues to look promising. There was, and continues to

be a strong surge in demand by domestic passengers, primarily due to the burgeoning

middle class with its massive purchasing power, attractive low fares offered by the

low cost carriers, the growth of domestic tourism in India and increasing outbound

travel from India. In addition, the government has also focused on modernizing non

45

metro airports, opening up new international routes, establishing new airports and

renovating existing ones. According to Kapil Kaul, CEO India and Middle East,

Centre for Asia Pacific Aviation (CAPA), India’s civil aviation passenger growth is

among the highest in the world. “This sector is slated to cruise far ahead of other

Asian giants like China or even strong economies like France and Australia. The

number of passengers who will be airborne by 2020 is a whopping 400 million.” To

keep pace with this accelerated demand, existing players have been trying to increase

fleets and widen their footprint to regional destinations as well. There has also been

increasing attention from international low cost airlines such as Air Asia (Malaysian)

and JetStar Asia (Australian) to capture part of this lucrative opportunity (Overview,

2008).

2.2 A BRIEF HISTORY OF AVIATION INDUSTRY IN INDIA

The history of civil aviation in India dates back to 1912, when the first domestic flight

operated between Karachi and Delhi, by the Indian State Air Services in collaboration

with the Imperial Airways of United Kingdom. Since then, till the time of Indian

independence, in 1947, there were nine air carrier companies operating in India

(including both passenger and cargo). These were as follows:

• Tata Airlines

• Indian National Airways

• Air service of India

• Deccan Airways

• Ambica Airways

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• Bharat Airways

• Mistry Airways

• Orient Airways

However, following partition, one of the airlines i.e. Orient Airways shifted to

Pakistan, leaving independent India with eight airlines. In early 1950s, the

government took to nationalize the airline industry in India. All airlines existing at the

time were merged into either Air India or Indian Airline; all aspect of Indian aviation

was under the control of the government. With the establishment of the Air

Corporation Act of 1953, this monopoly of the Indian Government existed for almost

four decades.

It was not until the early nineties, when the Indian economy experienced a boom and

started growing tremendously, that a need was felt for a more comprehensive air

transport system in order to complement the growing economy, that this monopoly of

the government was brought to an end, and the Air Corporation Act revoked. It was

after this, the private domestic airlines started operating in India once again. However,

even then, in case of foreign airlines, there were many restrictions as regards to the

number of flights they could operate, the types of aircraft they could fly in the

country, their point of call, capacity etc. India becoming a popular tourist destination,

such policies created major problems during the tourist seasons when it was difficult

for tourists to fly in and out of the country. It was then, that India started signing

bilateral agreements with many countries and came up with mutual agreements

regarding ownership, number of seats, ports of call, and number of flights etc. of

scheduled carriers from foreign countries. Now, India has signed more than 180

bilateral agreements with different countries (Pasari, 2005-06).

47

Small window of change was opened in 1986 when the air taxi scheme was

introduced, under which other airlines could run charter flights without fixed time

schedule and issue of the tickets. This state of affairs continued till 1993, when the

Air Corporation Act, 1953 was withdrawn (Gupta, 2008). In April 1990, India

introduced the Open Sky Policy. According to this policy, an air taxi operator could

operate flights, both chartered and non-chartered, from any airport. They were also

allowed discretion on matters relating to flight schedules as well as fares they charged

for passengers (or cargo). However, all such operators were required to conform to

some prescribed rules. They were also required to use airplanes with a minimum

capacity of 15 persons.

Prior to December 2004, any other airlines except Indian Airlines and Air India were

prohibited to fly to international destinations i.e. no private carriers could operate to

foreign countries. In December 2004, the Indian government changed its policy and

granted permission to those private carriers which had completed five years of

domestic operation, to operate flights to any destination worldwide (except the Gulf

Region and West Asia) (Pasari, 2005-06). Today, apart from Indian Airlines and Air

India, Jet Airways, Kingfisher Airline, IndiGo are also operating on international

routes.

At present, private airlines account for around 75% portion of the domestic aviation

market. The 9th largest aviation market in the world is India. The prediction stated

that international passengers will touch 50 million by 2015. More opportunities in the

aviation industry in India are likely to make way for about 69 foreign airlines from 49

countries (Role of aviation industry in India GDP, 2008).

48

2.3 CIVIL AVIATION IN INDIA

2.3.1 MINISTRY OF CIVIL AVIATION

Mission

To maintain a competitive civil aviation environment which ensures safety and

security in accordance with international standards, promotes efficient, cost-effective

and orderly growth of air transport and contributes to social and economic

development of the country.

Strategic Objectives

The objectives of this policy are the creation and continued facilitation of a

competitive and service-oriented civil aviation environment in which:

i. The interests of the users of civil aviation are the guiding force behind all

decisions, systems and arrangements,

ii. Safe, efficient, reliable and widespread quality air transport services are

provided at reasonable prices,

iii. There exists a well-defined regulatory framework catering to changing needs

and circumstances,

iv. All players and stakeholders are assured of a level playing field;

v. Private participation is encouraged and opportunities created for investors to

realize adequate returns on their investments;

vi. Recognizing that aviation today is an important element of infrastructure,

rapid upgradation of airport infrastructure to world class standards with

priority to the busiest airports and those handling international flights;

49

vii. Recognizing that transportation of air cargo is vital to the economic growth of

the country, creation and development of specific infrastructure for air

transportation of cargo and express cargo is encouraged;

viii. "Airline operations and acquisition of Aircraft" is conferred "infrastructure"

status for overall growth of civil aviation sector in the country.

ix. Domestic and international aviation in the country are encouraged to grow at

par with world aviation industry;

x. Inter-linkages with other modes of transport are encouraged and stimulated;

xi. Trade, tourism and overall economic activity and growth is encouraged;

xii. International cooperation in aviation and development in tune with

international trends and best practices, consistent with airspace sovereignty is

promoted;

xiii. Indigenous development of aircraft, components and aviation products is

encouraged;

xiv. Security of civil aviation operations is ensured through appropriate systems,

policies, and practices, and;

xv. Effective systems are put in place for timely crisis and disaster management,

including investigation of incidents/accidents.

Responsibility

• Formulation of National Policies and programmes for development and regulation

of Civil Aviation.

• Devising and implementing schemes for orderly growth and expansion of civil air

transport.

50

• Oversee the provision of airport facilities, air traffic services and carriage of

passengers and goods by air.

• Administratively responsible also for the Commission of Railway Safety, a

statutory body set up under the Railway Act (Civil Aviation Policy (Draft), 2000).

2.3.2 ORGANIZATIONS UNDER MINISTRY OF CIVIL AVIATION

• Attached Offices

� Directorate General of Civil Aviation

� Bureau of Civil Aviation Security

� Commission of Railway Safety

• Public Sector Undertakings

� Airports Authority of India

� National Aviation Company of India Ltd. and its subsidiaries

� Pawan Hans Helicopters Ltd.

• Autonomous Organization

� Indira Gandhi Rashtriya Uran Akademi

(Latest developments and policy initiatives in Civil Aviation in India, 2007)

2.4 CIVIL AVIATION POLICY IN INDIA

The Civil Aviation Ministry is evolving a draft Civil Aviation Policy that would

increase foreign direct investment, ceiling, liberalize bilateral and move towards an

51

`Open Sky,' encourage the promotion of Regional Airlines, lower fares to make

aviation affordable and remove price monopolies in respect of Aviation Turbine Fuel

(ATF).

Mission of Civil Aviation Policy

The main aim of the Civil Aviation Policy is to maintain a competitive Civil Aviation

Environment which ensures safety and security in accordance with international

standards, promotes efficient, cost-effective and orderly growth of air transport and

contributes to social and economic development of the country.

Strategic Objectives of Civil Aviation Policy

The objectives of this Civil Aviation Policy are the creation and continued facilitation

of a competitive and service-oriented Civil Aviation Environment in which:

• The interests of the users of civil aviation are the guiding force behind all

decisions, systems and arrangements

• Safe, efficient, reliable and widespread quality air transport services are

provided at reasonable prices

• There exists a well-defined regulatory framework catering to changing needs

and circumstances

• All players and stakeholders are assured of a level playing field

• Private participation is encouraged and opportunities created for investors to

realize adequate returns on their investments

Regulatory Framework

In the context of a multiplicity of airlines, airport operators (including private sector),

and the possibility of oligopolistic practices, there is need for an autonomous

52

regulatory authority which could work as a watchdog, as well as a facilitator for the

sector, prescribe and enforce minimum standards for all agencies, settle disputes with

regard to abuse of monopoly and ensure level playing field for all agencies.

Therefore, a statutory autonomous Civil Aviation Authority (CAA) will be

constituted. The basic objectives of setting up of the Authority will be to ensure

aviation safety, security and effective regulation of air transport in the country in a

liberalized environment.

Airport Infrastructure

The Government will aim at ensuring adequate world class Airport Infrastructure

capacity in accordance with demand, ensuring maximum utilization of available

capacities and efficiently managing the Airport Infrastructure by increasing

involvement of private sector.

Aviation Support Services

The role of Aviation Support Services like human resource development, maintenance

facilities and manufacture of aircraft is very important, as these are the backbone of

Civil Aviation Services. These services should be available in state-of-art condition in

adequate supply in accordance with demand. For this, the role of private sector needs

to be emphasized.

Co-ordination

• A number of department/ agencies are involved in the development of Civil

Aviation Infrastructure and facilitating the convenience of the travelling

public. Inter-linkages with other modes of transport for travel and trade need

to be emphasised.

53

• An Inter-Ministerial Standing Committee will be constituted for coordination

with Ministries of Commerce, Tourism, Industry, Railways, Surface

Transport, Defence, Home Affairs (Immigration and Security), Finance

(Customs) and External Affairs. (Civil Aviation Policy, 2011)

In 1990, the private air taxi-operators carried 15,000 passengers which rose to 4.1

lakhs, 29.2 lakhs, 36 lakhs and 48.9 lakhs in 1992, 1993, 1994 and 1995 respectively.

The Air Corporation Act 1956 was modified on 1st March, 1994 which enabled

private operators to provide air transport services. Six operators were given the status

of scheduled operators on 1 February, 1995. In 1996, private air taxi operators carried

49.08 lakhs passengers which amounted to 41.14 percent share in domestic air

passenger traffic. The task of managing airports in India vest with Airport Authority

of India which at present looks after 15 international airports, 8 custom airport, 25

civil enclaves and 80 domestic airports.

54

Fig 2.1 Location of Domestic Airports in India

Source: www.mapsofindia.com

55

Fig. 2.2 Location of International Airports in India

Source: www.mapsofindia.com

56

2.5 REASONS FOR BOOM IN INDIAN AVIATION INDUSTRY

The unprecedented boom in airlines and flyers is the result of following factors:

a. Foreign equity allowed- The RBI announced that foreign institutional

investors might have shareholdings more than the limited 49% in the domestic

sector. Foreign equity up to 100% is allowed by the means of automatic

approvals pertaining to establishment of Greenfield airports. Up to 49% of

foreign equity and up to 100% of NRI investment is allowed by the means of

automatic approvals pertaining to the domestic air transport services.

However, the government policy bars foreign airlines from taking a stake in a

domestic airline company.

b. Low entry barriers- Now a days, venture capital of $10 million or less is

enough to launch an airline. Private airlines are known to hire foreign pilots,

get expatriates or retired personnel from the Air Force or PSU airlines in

senior management positions. Further, they outsource such functions as

ground handling, check-in, reservation, aircraft maintenance, catering,

training, revenue accounting, IT infrastructure, loyalty and programme

management. Airlines are known to take on contract employees such as cabin

crew, ticketing and check-in agents.

c. Attraction of foreign shores- Kingfisher airline and Jet Airways have gone

international by starting operations, first to SAARC countries, and then to

South-East Asia, the UK and the US. After five years of domestic operations,

many domestic airlines too will be entitled to fly overseas by using unutilised

bilateral entitlements to Indian carriers.

57

d. Rising income levels and demographic profile- Though India’s GDP (per

capita) at $3,100 is still very low as compared to the developed country

standards, India is shining at least in metro cities and urban centres, where IT

and BPO industries have made the younger generation prosperous.

Demographically, India has the highest percentage of people in age group of

20-50 among its 50 million strong middle class, with high earning potential.

All this contributes for the boost in domestic air travel, particularly from a low

base of 18 million passengers.

e. Untapped potential of India’s tourism- Currently, India attracts more than 5.11

million tourists every year, while China gets 10 times the number. Tourist

arrivals in India are expected to grow exponentially, especially due to open

sky policy between India and SAARC countries and the increase in bilateral

entitlements with European countries and the US.

f. Glamour of the airlines- No industry other than film-making is as glamorous

as the airlines. Airline tycoons from the last century, like J.R.D. Tata, Howard

Hughes, Sir Richard Branson and Dr. Vijaya Mallaya today have been

idolized. Airlines have an aura of glamour around them and high net worth

individuals can always toy with the idea of owning an airline. All the above

factors seem to have resulted in a “me too” rush to launch domestic airlines in

India.

58

2.6 FUTURE OF AVIATION INDUSTRY IN INDIA

The challenges of the Indian aviation industry are cited below:

• Passenger traffic is estimated to grow at a CAGR of over 15% in the coming

few years.

• The Ministry of Civil Aviation would handle around 280 million passengers

by 2020.

• US$ 110 billion investment is envisaged till 2020 with US$ 80 billion solely

for new aircraft and US$ 30 billion for developing the airport infrastructure.

Airports

• Foreign equity up to 100% is allowed by the means of automatic approvals

pertaining to establishment of Greenfield airports

• Foreign equity up to 74% is allowed by the means of automatic approvals

pertaining to the existing airports

• Foreign equity up to 100% is allowed by the means of special permission from

Foreign Investment Promotion Board, Ministry of Finance, pertaining to the

existing airports

Air Transport Services

• Up to 49% of foreign equity is allowed by the means of automatic approvals

pertaining to the domestic air transport services.

• Up to 100% of NRI investment is allowed by the means of automatic

approvals pertaining to the domestic air transport services.

(business.mapsofindia.com)

59

Role of Aviation Industry in India’s GDP-Future Challenges

• Initializing privatization in the airport activities

• Modernization of the airlines fleet to handle the pressure of competition in the

aviation industry

• Rapid expansion plans for the major airports for the increased flow of air

traffic

• Immense development for the growing Regional Airports

Role of Aviation Industry in India’s GDP-FDI Policy

• The Reserve Bank of India (RBI) announced that foreign institutional

investors might have shareholdings more than the limited 49% in the domestic

sector. (Gupta, 2008)

60

Source: IBM Institute for Business Value analysis

Figure 2.3 Forc

es Shaping the Futu

re of th

e Airline In

dustry

.

61

2.7 NATURE OF AIRLINES

An airline provides air transport services for passengers and/or freight. Airlines lease

or own their aircraft with which to supply these services and may form partnerships or

alliances with other airlines for mutual benefit. Generally, airline companies are

recognized with an air operating certificate or license issued by a governmental

aviation body. (Airline, 2010)

Airlines operations can be categorized into two heads:

a.) Domestic airlines

b.) International airlines

List of Airlines in India

a) Domestic Airlines- Kingfisher Airlines, Kingfisher Red (previously Air Deccan),

Jet Airways, Jetlite (previously Air Sahara), Air India, Indian (previously India

Airline), IndiGo, SpiceJet, GoAir, Paramount Airways, Air India Express,

Alliance.

b) International Airlines- Aeroflot Airline, Air Astana, Air Canada, Air France, Air

Mauritius, Alitalia, Ariana Afghan Airline, Asiana Airlines, British Airways,

Cathay Pacific Airways, China Airlines, China Eastern Airlines, Delta Airlines,

Druk Air, Egypt Air, El Al Airline, Emirates Airline, Ethiopian Airlines, Etihad

Airways, Gulf Air, Iran Air, Japan Airline (JAL), Kenya Airways, KLM, Korean

Air, Kuwait Airways, Lufthansa, Mahan Air, Malaysia Airlines, Northwest

Airlines, Oman Air, Pakistan Airlines, Qantas Airways, Qatar airways, Royal

Jordanian Airline, Royal Nepal Airlines, Saudi Arabian Airline, Singapore

Airlines, South African Airways, SriLankan Airlines, Swiss International Airlines,

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Syrian Arab Airlines, Thai Airways International, Turkish Airlines, Uzbekistan

Airways.

Full service Vs Low cost Airlines

Airlines are divided under two sub heads: Full service (FSA) and Low cost service

(LCA) depending upon the nature of services they provide.

The concept of low cost airlines (LCA) was coined in 1971 by the Southwest Airlines

in the United States and has been profitable every year since 1973. Though the

concept became very popular in Europe after the deregulation of aviation and the

most notable success being the Irish Ryan Air founded in 1985, its spread has been

slow in Asia baring few countries. The first to start low cost airlines in Asia was Air

Asia of Malaysia in 2003.

A typical low cost airline’s business model is based on:

a. A single passenger class so as to ensure maximum number of seats.

b. A single type of aircraft thereby reducing training and servicing cost.

c. A simple fare scheme.

d. Open seating which encourages passengers to board early.

e. Direct point to point flights.

f. Flying to less congested airports.

g. Short flights and fast turnaround times allowing maximum utilisation of planes.

h. No catering and complimentary services.

i. No frequent flier or other promotional schemes and;

j. Direct distribution.

63

The low cost carriers have captured the imagination of air travellers and most of these

airlines are showing robust growth. It is estimated that in the next 10 years, low cost

airlines will capture at least 50% market share in Europe, 25% in the US and 25% in

Asia.

In India, there are eight low cost carriers, while other nine are waiting for their

permission to penetrate the aviation sector. Air Deccan, a unit of Deccan Aviation

Private Limited, was the first low cost carrier in India. All low cost carrier operating

in India is following the above proposed business model.

DELAG was the world’s first full service airline. It was founded on November 16,

1909 with government assistance, and operated airship manufactured by Zepelin

Corporation. Its headquarters was in Frankfurt. The other four oldest operative full

service airlines are Netherlands’s KLM, Colombia’s Avianca, Auatralia’s Qantas and

Mexico’s Mexicana. A full service airline’s business model is based on:

a. A dual passenger class.

b. A large and technically advanced fleet.

c. Facilities of connected flights.

d. Flying to almost all airports of country.

e. Star catering and complimentary services and

f. Provision of frequent flier or other promotional schemes.

Rising of low cost airlines have threatened the market share of full service carrier. It is

estimated that in coming few years, large chunk of share of full service carrier will be

captured by low cost airlines. At present, there are 8 low cost carriers and 3 full cost

carriers operating in India. (Gupta, 2008)

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Table 2.1 Sources of Non-Ticket Revenue for LCA and FSC Airlines

Non-ticket and other ancillary revenues

(In-flight services related)

Ancillary revenues

(Frequent Flyer related)

• Onboard sales of food and beverages

• Checking of baggage or excess

baggage

• Assigned seats or better seats such as

aisle seats

• Fees charged for purchases made with

credit cards

• Commissions from the sale of hotel

accommodations, car rentals and

shuttle bus transfer reserved at the

airline website

• Commissions from the sale of travel

insurance and airport lounge access

• Advertising tied to passenger travel

such as onboard magazines and in-

cabin media.

• Miles or points sold to banks

issuing co-branded credit cards

• Travel partners such as hotel

chains and car rental companies

• Other partners such as online

malls, retailers and

communication services

Source: Gupta, 2008 (Source: www.airdeccan.net)

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2.8 AIRLINES IN INDIA

As of 30 October 2007, the total fleet size of commercial airlines in India was 439. In

1994 the Air Corporation Act of 1953 was repealed with a view to remove monopoly

of air corporations on scheduled services, enable private airlines to operate scheduled

service, convert Indian Airlines and Air India to limited company and enable private

participation in the national carriers. However, at the beginning of 1990, private

airline companies were allowed to operate air taxi services, resulting in the

establishment of Jet Airways and Air Sahara. These changes in the Indian aviation

policies resulted in the increase of the share of private airline operators in domestic

passenger carriage to 68.5% in 2005 from 0.4 of 1991. (Airline, 2010)

Table 2.2 Operational Airlines- List of Airlines Today in the Market

AIRLINE ICAO IATA Call Sign Commenced

Operations

Headquarters

Air India AIC AI AIRINDIA October 1932 Mumbai

Air India

Express

AXB IX EXPRESS

INDIA

April 2005 Mumbai

Air India

Regional

LLR CD ALLIED 1996

(As Alliance Air)

Mumbai

GoAir GOW G8 GOAIR June 2004 Mumbai

Indian IAC IC INDAIR May 1953 Mumbai

IndiGo IGO 6E IFLY August 2006 Gurgaon

Jagson JGN JA JAGSON November 1991 Delhi

66

Airlines

Jet Airways JAI 9W JET AIRWAYS May 1993 Mumbai

JetLite JLL S2 LITE JET 1991

(As Air Sahara)

Mumbai

Kingfisher

Airlines

KFR IT KINGFISHER May 2005 Mumbai

Kingfisher

Red

KFR IT KINGFISHER August 2003

(As Air Deccan.

Merged and

made

a low-cost brand

of Kingfisher)

Mumbai

SpiceJet SEJ SG SPICEJET May 2005 Gurgaon

Market Share of Scheduled Domestic Airlines (Dec, 2011)

Airline Share (%)

Air India (Dom) 17.4%

IndiGo 20.4%

Kingfisher Airline 12.1%

Go Air 5.7%

Jet Airways 20.5%

Jetlite 7.1%

Spice Jet 16.8%

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Market Share of Scheduled Domestic Airlines (Dec, 2011)

17%

20%

12%6%

21%

7%

17%

Air India (Dom) IndiGo Kingfisher Airline Go Air

Jet Airways Jetlite Spice Jet

Figure 2.4 Market Share of Scheduled Domestic Airlines (Dec, 2011)

Source: Statistics from DGCA website (www.dgca.org)

68

69

2.8.1 AIR INDIA

Air India is a state-owned flag carrier, the oldest and the largest airline of India. It is a

part of the Indian government-owned Air India Limited (AIL) which is renamed as

Air India Ltd. The airline operates a fleet of Airbus and Boeing aircrafts serving Asia,

Australia, Europe and North America. Its corporate office is located at the Air India

Building at Nariman Point in South Mumbai. It is the 16th largest airline in Asia.

Following its merger with Indian, Air India has faced multiple problems, including

escalating financial losses and discontent among employees. Between September

2007 and May 2011, Air India's domestic market share declined from 19.2% to 14%,

primarily due to stiff competition from private Indian carriers. In 2007, the

Government of India announced that Air India would be merged with Indian. As part

of the merger process, a new company called the National Aviation Company of India

Limited (NACIL) was established, into which both Air India (along with Air India

Express) and Indian (along with Alliance Air) would be merged. On 27 February

2011, Air India and Indian Airlines merged along with their subsidiaries to form Air

India Limited. In August 2011, Air India's invitation to join Star Alliance was

suspended due to its failure to meet the minimum standards for the membership. In

October 2011, talks between the airline and Star Alliance have resumed.

Subsidiaries

Air India Cargo

In 1954, Air India Cargo started its freighter operations with a Douglas DC-3 Dakota

aircraft, giving Air India the distinction of being the first Asian airline to operate

freighters. The airline operates cargo flights to many destinations. The airline also has

ground truck-transportation arrangements on select destinations.

70

Air India Express

Air India Express is the airline's low-cost subsidiary which was established in 2005

during the aviation boom in India. It operates scheduled passenger services primarily

to the Persian Gulf and South East Asia. Air India Express is currently the only airline

in Air India Limited which posts profits. It operates a fleet of Next Generation Boeing

737-800 aircraft. Cochin International Airport is the main hub of the airline from

which it has connections to almost all the Gulf countries.

Air India Regional

Air India Regional (formerly known as Alliance Air) serves mainly on regional

routes. Its main hub is Delhi's Indira Gandhi International Airport.

Destinations:

Air India serves 49 domestic destinations and 26 international destinations in 19

countries across Asia, Europe and North America.

Short-haul routes

Air India's short-haul routes mainly include domestic cities and cities in South East

Asia and South West Asia. For short-haul routes, its Airbus A310, Airbus A330,

Boeing 747-400 and Boeing 777-200LR are used apart from Airbus A320 family

aircraft of Indian which are operated with Air India call sign and code.

Long-haul routes

The airline has long-haul destinations in East Asia, Europe and North America which

are served using Boeing 777-200LR and -300ER aircraft.

Code share agreements- Air India has code sharing agreements with the following

airlines:

71

Aeroflot *, Adria Airways^^, Air India Regional, Air Mauritius, Austrian Airlines^^,

BMI ^^, GMG Airlines, Gulf Air, Ethiopian Airlines, Kuwait Airways, Lufthansa^^,

Singapore Airlines^^, South African Airways^^, Turkish Airlines^^, Uzbekistan

Airways (* SkyTeam member, ^^ Star Alliance members)

Services

Frequent flyer programme- Flying Returns is Air India's frequent flyer programme.

The programme is also shared by all other Air India Limited carriers.

Premium lounges- The Maharaja Lounge (English: "Emperor's Lounge") is offered

to First and Business class passengers. Air India shares lounges with other

international airlines at international airports that do not have a Maharaja Lounge

available. There are five Maharaja Lounges, one at each of the five major destinations

of Air India, which are as following:

International

Air India's Maharaja Lounge at New York City's John F. Kennedy International

Airport London Heathrow Airport

John F. Kennedy International Airport (New York)

India

Bengaluru International Airport (Bangalore)

Chhatrapati Shivaji International Airport (Mumbai)

Indira Gandhi International Airport (Delhi)

Rajiv Gandhi International Airport (Hyderabad)

In-flight entertainment Air India's Boeing 777-200LR/-300ER as well as some

refurbished Boeing 747-400 aircraft uses the Thales Top Series IFE systems for

72

onboard in-flight entertainment. Airbus A310s do not have personal LCD screens.

Airbus A330s have widescreen displays in Business and Economy classes but no

personal IFEs. (en.wikipedia.org/wiki/Air_India)

73

74

2.8.2 JET AIRWAYS

Jet Airways is a major Indian airline based in Mumbai, Maharashtra. It is India's

largest airline and the market leader in the domestic sector. It operates over 400

flights daily to 67 destinations worldwide. Its main hub is Chhatrapati Shivaji

International Airport.

Early years, Jet Airways was incorporated as an air taxi operator on 1 April 1992. It

started Indian commercial airline operations on 5 May 1993 with a fleet of four leased

Boeing 737-300 aircrafts. In January 1994, a change in the law enabled Jet Airways to

apply for scheduled airline status, which was granted on 4 January 1995. It began

international operations to Sri Lanka in March 2004. The company is listed on the

Bombay Stock Exchange, but 80% of its stock is controlled by Naresh Goyal (through

his ownership of Jet’s parent company, Tailwinds). It has 10,017 employees (as at

March 2007).

In October 2008, Jet Airways and rival Kingfisher Airlines announced an alliance

which primarily includes an agreement on code-sharing on both domestic and

international flights, joint fuel management to reduce expenses, common ground

handling, and joint utilisation of crew and sharing of similar frequent flier

programmes.

Subsidiaries

JetLite- JetLite was established as Sahara Airlines on 20 September 1991 and began

operations on 3rd December 1993 with two Boeing 737-200 aircrafts. Initially,

services were primarily concentrated in the northern sectors of India, keeping Delhi as

its base, and then operations were extended to cover all the country. Sahara Airlines

was rebranded as Air Sahara on 2nd October 2000. On 12th April 2007, Jet Airways

75

took over Air Sahara and on 16th April 2007 Air Sahara was renamed as JetLite.

JetLite operates a fleet of mixed owned–leased Boeing 737 Next Generation aircraft

and Bombardier CRJ-200ER.

Jet Konnect- Jet Konnect is the low-cost brand of India-based Jet Airways. It was

launched on 8th May 2009, and shares the same airline code and call sign as Jet

Airways. It operates a mixed fleet of ATR 72-500s and Boeing 737-800s.

Services

Cabin-

Domestic & international short haul

Boeing 737 Next Generation aircrafts are configured in Economy Classes. Some

Boeing 737s have and all Economy Class cabin layout. The ATR 72-500 have

Economy class configuration only.

Première

The Première features 40-inch extra-wide seats with a personal Widescreen LCD

attached to each seat. The Première cabin is configured in a 2-2 abreast pattern.

Economy Class

Jet Airways Economy class on its Boeing 737 Next Generation features 30-inch seat

pitch with personal Widescreen LCD behind each seat. Jet Airways was the World's

first airline to introduce in-flight entertainment systems on the Boeing 737 aircraft.

The Economy class cabin is configured in a 3-3 abreast pattern on the Boeing 737

Next Generation and 2-2 abreast pattern on the ATR 72-500.

76

International long haul

With the arrival of its new Airbus A330-200 and Boeing 777-300ER aircraft, Jet

Airways has introduced a new cabin with upgraded seats in all classes. The Airbus

A330-200 aircraft have two classes: Première and Economy. The Boeing 777-300ER

aircraft has three classes of service: First, Première (Business), and Economy. Jet

Airways has a three-star rated First and Business Class, and is in the top twenty-five

business classes reviewed by Skytrax. Economy class has been reviewed as a three-

star product by Skytrax. Being a Full Service Airline, meals are served on all classes

of travel.

First Class

First class is available on all Boeing 777-300ER aircraft. All seats convert to a fully-

flat bed, similar to Singapore Airlines first class seat but much smaller. It was the

twenty-second airline in the world to have private suites. All seats in First have a 23-

inch widescreen LCD monitor with audio-video on-demand systems (AVOD), BOSE

noise cancelling headphones, in seat power supply, and USB ports etc. Jet Airways is

the first Indian airline to offer fully-enclosed suites on its aircraft; each suite has a

closable door, making for a private compartment. Skytrax consumer airline reviewers

recently rated Jet Airways First Class as being 14th best in the world.

Première

Première on board the Boeing 777-300ERPremière (Business Class) on the Airbus

A330-200 and Boeing 777-300ER international fleet has a fully-flat bed with AVOD

entertainment. Seats are configured in a herringbone pattern (1-2-1 on the Boeing

777-300ER, and 1-1-1 on the Airbus A330-200), with each seat offering direct access

to the aisle. Première seats on the A330-200s leased from ILFC are configured

77

differently in a 2-2-2 non-herringbone pattern. Each Première Seat has a 15.4-inch flat

screen LCD TV with AVOD. USB ports and in-seat laptop power are provided. All

seats are standard recliner business-class seats with a few newer aircraft with

electronic recline and massager.

Economy Class

Economy class on Jet's A330-200/777-300ER aircraft has 32-inch seat pitch. Seats on

the A330-200/777-300ER have a "hammock-style" net footrest. Each Economy seat

on the A330-200/777-300ER has a personal 10.6-inch touch screen LCD TV with

AVOD. All three classes feature Mood lighting on the Airbus A330-200 and Boeing

777-300ER, with light schemes corresponding to the time of day and flight position.

In-flight entertainment- Jet Airways' Panasonic eFX IFE system on-board the

Boeing 737-700/800 and Panasonic eX2 IFE system on-board the Airbus A330-

200/Boeing 777-300ER, called "JetScreen", offers audio video on-demand

programming (passengers can start, stop, rewind, and fast-forward as desired). It has

over 100 movies, 80 TV programmes, 11 audio channels and a CD library of 125

titles.

Airport lounges- Jet Airways Lounges are offered to First and Première Class

passengers, along with JetPrivilege Platinum, Gold or Silver card members. The

international lounge at Brussels has showers, business centre, entertainment facilities

and children's play areas. Lounges are located in: Bangalore, Brussels, Chennai,

Cochin, Delhi, Hyderabad, Jaipur, Kolkata, Mumbai.

Frequent-flyer program- JetPrivilege is Jet Airways’ frequent-flyer program.

(en.wikipedia.org/wiki/Jet_Airways)

78

79

2.8.3 KINGFISHER AIRLINE

Kingfisher Airlines is an airline group based in India. Its head office is The Qube in

Andheri (East), Mumbai and Registered Office in UB City, Bangalore. Kingfisher

Airlines, through its parent company United Breweries Group, has a 50% stake in

low-cost carrier Kingfisher Red.

Kingfisher Airlines is one of the seven airlines to be ranked as a 5-star airline by the

independent research consultancy firm Skytrax. Kingfisher operates more than 375

daily flights to 71 destinations, with regional and long-haul international services. In

May 2009, Kingfisher Airlines carried more than a million passengers, giving it the

highest market share among airlines in India. Kingfisher also owns the Skytrax award

for India's best airline of the year 2011.

Kingfisher Airlines is also the sponsor of F1 racing outfit, Force India, which Vijay

Mallya also owns.

History

Kingfisher Airlines was established in 2003. It is owned by the Bengaluru based

United Breweries Group. The airline started commercial operations on 9th May 2005,

with a fleet of four new Airbus A320-200s operating a flight from Mumbai to Delhi.

It started its international operations on 3rd September 2008, by connecting Bengaluru

with London.

On 7th June 2010, Kingfisher became a member elect of the Oneworld airline alliance

when it signed a formal membership agreement.

80

Services

Cabin classes

Domestic

Kingfisher First

The domestic Kingfisher First seats have a 48 inch seat pitch and a 126 degree seat

recline. There are laptop and mobile phone chargers on every seat. Passengers can

avail of the latest international newspapers and magazines. There is also a steam

ironing service on board Kingfisher First cabins. Every seat is equipped with a

personalised IFE system with AVOD which offers a wide range of Hollywood and

Bollywood movies, English and Hindi TV programmes, 16 live TV channels and 10

channels of Kingfisher Radio. Passengers also get BOSE noise cancellation

headphones.

Domestic Kingfisher First is only available on selected Airbus A320 family aircraft.

Kingfisher Class

The domestic Kingfisher Class has 32-34 inch seat pitch.

Every seat is equipped with personal IFE systems with AVOD on-board the Airbus

A320 family aircraft. As in Kingfisher First, passengers can access the movies,

English and Hindi TV programmes, a few live TV channels powered by Dish TV and

Kingfisher Radio. The screen is controlled by a controller-console on the seat armrest.

Earcup headphones are provided free of cost to all passengers. The default channel

shows, alternating every few seconds, The aeroplane's ground speed, outside

temperature, altitude, distance and time to destination; the position of the aircraft on a

graphical map and one or more advertisements.

81

Passengers are served meals on most flights. Before take-off, passengers are served

bottled Lemonade.

On-board the ATR 72-500s, there are 17 colour LCD drop-down screens mounted

along with loudspeakers for audio in the cabin overhead, a head-end unit to handle

CDs and DVDs, and a crew control panel. The screens measure 12.7 cm by 9.3 cm,

weigh 0.2 kg each and are spaced every two or three seat rows along both sides of the

cabin.

Kingfisher Red

After Kingfisher Airlines acquired Air Deccan, its name was changed to Simplifly

Deccan and subsequently to Kingfisher Red. Kingfisher Red is Kingfisher Airline's

low-cost class on domestic routes. Passengers are given complimentary in-flight

meals and bottled water. A special edition of Cine Blitz magazine is the only reading

material provided.

Kingfisher Airlines is the first airline in India to extend its King Club frequent flyer

program to its low-cost carrier as well. Passengers can earn King Miles even when

they fly Kingfisher Red, which they can redeem for free tickets to travel on

Kingfisher Airlines or partner airlines.

International

Kingfisher First- The international Kingfisher First has full flat-bed seats with a 180

degree recline, with a seat pitch of 78 inches, and a seat width of 20-24.54 inches.

Passengers are given Merino wool blankets, a Salvatore Ferragamo toiletry kit, a

pyjama to change into, five-course meals and alcoholic beverages. Also available are

in-seat massagers, chargers and USB connectors.

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Every Kingfisher First seat has a 17 inch widescreen personal television with AVOD

touch screen controls and offers 357 hours of programming content spread over 36

channels, including Hollywood and Bollywood movies along with 16 channels of live

TV, so passengers can watch their favorite TV programmes live. There is also a

collection of interactive games, a jukebox with customisable playlists and Kingfisher

Radio. Passengers are given BOSE noise cancellation headphones.

The service on board the Kingfisher First cabins includes a social area comprising a

full-fledged bar staffed with a bartender, a break-out seating area just nearby fitted

with two couches and bar stools, a full-fledged chef on board the aircraft and any-time

dining. A turn-down service includes the conversion of the seat into a fully-flat bed

and an air-hostess making the bed when the passenger is ready to sleep.

Both Kingfisher First and Kingfisher classes feature mood lighting on the Airbus

A330-200 with light schemes corresponding to the time of day and flight position.

Kingfisher Class

The international Kingfisher Class seats offer a seat pitch of 34 inches, a seat width of

18 inches and a seat recline of 25 degrees (6 inches). Passengers get full length

blankets, full size pillows and business class meals.

Each Kingfisher Class seat has a 10.6 inch widescreen personal television with

AVOD touch screen controls. The IFE is similar to that of the international Kingfisher

First class. It can also be controlled by a detachable remote-control console fitted in

the armrest. This device can be used to control the IFE, reading-lights, play games

and even has a credit-card swipe for shopping on Kingfisher's 'Air Boutique'. It also

has a facility for sending text-messages, though the service isn't provided by

Kingfisher.

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In-flight entertainment

Kingfisher's IFE system is the Thales Top Series i3000/i4000 on-board the Airbus

A320 family aircraft, and Thales Top Series i5000 on-board the Airbus A330 family

aircraft provided by the France-based Thales Group.

Kingfisher was the first Indian airline to have in-flight entertainment (IFE) systems on

every seat even on domestic flights. All passengers were given a "welcome kit"

consisting goodies such as a pen, facial tissue and headphones to use with the IFE

system. Now, passengers of kingfisher class are not given "welcome kits" but as

mentioned earlier, a complimentary bottle of lemonade and earphones for use with the

IFE are still given. Initially, passengers were able to watch only recorded TV

programming on the IFE system, but later an alliance was formed with Dish TV to

provide live TV in-flight. And in a marked departure from tradition, Kingfisher

Airlines decided to have an on-screen safety demonstration using the IFE system,

however the conventional safety briefing by the flight attendants still exists on many

flights.

King Club

The Frequent-flyer program of Kingfisher Airlines is called the King Club in which

members earn King Miles every time they fly with Kingfisher or its partner airlines,

hotels, car rental, finance and lifestyle businesses. There are four levels in the scheme:

Red, Silver, Gold and Platinum levels. Members can redeem points for over a number

of schemes. Platinum, Gold and Silver members enjoy access to the Kingfisher

Lounge, priority check-in, excess baggage allowance, bonus miles, and 3 Kingfisher

First upgrade vouchers for Gold membership. Platinum members get 5 upgrade

vouchers.

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Kingfisher Lounge

Kingfisher Lounges are offered to Kingfisher First passengers, along with King Club

Silver and King Club Gold members. Lounges are located in:

• Bengaluru International Airport

• Chennai International Airport

• Chhatrapati Shivaji International Airport (Mumbai)

• Cochin International Airport (Kochi)

• Indira Gandhi International Airport (Delhi)

• London Heathrow Airport

• Netaji Subhash Chandra Bose International Airport (Kolkata)

• Rajiv Gandhi International Airport (Hyderabad)

(en.wikipedia.org/wiki/Kingfisher_Airline)

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2.8.4 INDIGO

IndiGo is a private domestic low-cost airline based in Gurgaon, Haryana, India. It

operates domestic services linking 31 destinations. Its main base is Delhi's Indira

Gandhi International Airport. It was awarded the title of the Best Domestic Low Cost

Carrier in India for 2008. IndiGo has the second largest share in India's domestic air

travel market, only behind Jet Airways and as of October 2011 it is the only airline in

India making profit.

Following Indian regulations, IndiGo received its license to operate international

flights upon completing five years of operations. Its main operational hub is New

Delhi's Indira Gandhi International Airport. IndiGo has been awarded numerous

airline and travel industry awards. IndiGo won the Skytrax Central Asia's best low-

cost airline award in 2011.

History

IndiGo commenced operation on 4th August, 2006 from Delhi to Imphal via

Guwahati. Rakesh Gangwal and Rahul Bhatia are the two founders of Indigo airlines.

The airline is owned by the Gurgaon-based InterGlobe Enterprises. It took delivery of

its first Airbus A320-200 aircraft on 28th July 2006 and received six aircraft during

2006. Nine more aircraft were delivered in 2007 taking the total to 15. Former US

Airways Executive, vice-President, Marketing and Planning Bruce Ashby joined

IndiGo as its Chief Executive Officer. The airline has also acquired three parking

spots at Indira Gandhi International Airport and Chhatrapati Shivaji International

Airport. Recently, IndiGo changed the outfits for their crew members on occasion of

its 4th anniversary.

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In-flight service

Being a low-cost carrier, IndiGo does not offer complimentary meal services to its

passengers. However, it does offer buy-on-board food services where items such as

sandwiches, parathas, cookies, nuts, soft drinks and mineral water can be purchased.

Purified drinking water is provided free of charge. (en.wikipedia.org/wiki/IndiGo)

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2.8.5 GOAIR

GoAir is an Indian low-cost airline based in Mumbai, Maharashtra. It operates

domestic passenger services to 21 cities with 156 daily flights and approximately

1092 weekly flights. Its main base is Chhatrapati Shivaji International Airport,

Mumbai.

Go Airlines (India) Ltd. is the aviation foray of the Wadia Group. The airline operates

its services under the brand GoAir. The airline's theme, 'Fly Smart', aims to offer

passengers a consistent, quality-assured and time-efficient service with low fares. The

airline uses Airbus A320 aircraft.

GoAir's business model is based on punctuality, affordability and convenience. The

airline has partnered with Radix International, a technology provider of automated

aviation and travel related software solutions, for the use of its Air Enterprise. The

adoption of such technology solutions enables GoAir to achieve higher process

efficiency, giving passengers increased time savings

History

The airline was established in 2005. It launched commercial operations in November

2005. It is now wholly owned by the Wadia Group, Mumbai based and majority

owners of Bombay Dyeing and Britannia Industries.

Service

Being a no-frills airline, Go does not offer any complimentary meal service to its

passengers. However, it does offer a buy-on-board food service, where items such as

sandwiches, parathas, cookies, nuts, soft drinks and Mineral water can be purchased.

But from 9th April 2009, Go has started a new premium service known as Go

Business in which the passengers, at a slightly higher fare, are assured of seats in the

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first two rows of the aircraft and the middle seat is always empty. Go provides free

meals on board to passengers travelling on Go Business.

(en.wikipedia.org/wiki/GoAir)

91

92

2.8.6 SPICE JET

SpiceJet is a low-cost airline headquartered in Gurgaon, India. It began service in

May 2005 and by 2008, it was India's second-largest low-cost airline in terms of

market share. SpiceJet was voted as the best low-cost airline in South Asia and

Central Asia region by Skytrax in 2007. Following the acquisition by Kalanithi

Maran, SpiceJet went to be part of Kal Airways, Sun Group in 2010.

History

SpiceJet, India's leading low cost airline, is a reincarnation of ModiLuft. It is

promoted by Ajay Singh and the Kansagra family. SpiceJet marked its entry in the

Indian skies with 99 fares for the first 99 days, with 9,000 seats available at this rate.

This deal was followed up with a 999 promotional scheme on select routes. Their

marketing themes are "offering low 'everyday spicy fares' and great guest services to

price conscious travellers. SpiceJet now competes with IndiGo and the Indian

Railways. As India's economy and businesses are growing, the dream for flying has

become common and SpiceJet's mission is to ensure that flying is for everyone.

Destinations

SpiceJet operates over 264 flights daily to 32 Indian cities viz. Agartala, Ahmedabad,

Aurangabad, Bangalore, Bagdogra, Bhopal, Chennai, Coimbatore, Delhi, Guwahati,

Goa, Indore, Hyderabad, Jammu, Jaipur, Kochi, Kolkata, Madurai, Mumbai,

Mangalore, Nagpur, Pune, Rajahmundry, Srinagar, Surat, Trichy, Tirupati,

Trivandrum, Tuticorin, Varanasi, Vijaywada and Visakhapatnam. On the international

front, SpiceJet operates flights to Kathmandu and Colombo. Services

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Services

In order to keep the fares low and affordable, SpiceJet offers an assortment of

vegetarian/non-vegetarian sandwiches, cookies, flavoured nuts, soft drinks and juices

as a buy-on-board option. As a low-cost carrier, SpiceJet offers only complimentary

mineral water to passengers on board its flights. SpiceJet also allows food to be

carried on board. However, the food should be cold snacks, non-alcoholic drinks,

snack bars and biscuits. Messy, oily or smelly food items are not allowed on board.

Per Spicejet Baggage rules, a maximum of 20 kg of baggage is allowed per paying

passenger. However, international passengers can carry 2 bags weighing nothing more

than 23 kilograms each. The cost of carrying excess baggage is Rs 100 per kg for a

one-way trip. Also, the weight of the cabin baggage should not be exceeding 10 kg.

The size of the cabin baggage is as of now, 55 cm + 35 cm + 25 cm. Cabin baggage is

not allowed in flights connecting the Indian state of Jammu and Kashmir. SpiceJet

allows customers to earn reward points and cash back offers as they book using their

SpiceJet State Bank of India Master Card which was recently introduced by SpiceJet

in collaboration with the State Bank of India and Mastercard. They also provide

Insurances Air Accident Insurance, Delayed Flight Insurance, and Lost Baggage

Insurance. Despite no in-flight entertainment, SpiceJet provides an in-flight magazine

named SpiceRoute. Since August 2009, Maxposure Media Group has been printing

and publishing the magazine. (en.wikipedia.org/wiki/SpiceJet)

94

95

2.8.7 JAGSON AIRLINES

Jagson Airlines is an airline based in Delhi, founded in 1991. It operates scheduled

and charter services within India and to Bhutan and Nepal.

History

The airline was established and started operations in November 1991. It began charter

operations with two 18-seat Dornier 228-201 aircraft and later operated regular

services from Delhi. It is wholly owned by Jagson International. In 2006 they

announced plans to expand their services to 9 cities, using leased Airbus A321-200

aircraft. Jagson have withdrawn plans to launch a nationwide scheduled low-cost

airline by mid-2006 and plan to continue as a regional airline.

Jagson has recently taken deliveries of RJ 80s / BAe 146-200s Avro Regional Jets.

They will be starting operations to all their previous routes shortly. Efforts are on to

merge the erstwhile MDLR, which operated the same type of aircraft, and form a 5

aircraft airline.

Besides a seat to travel, the above mentioned airlines offering service products to

domestic air travellers. There are equal chances that a traveller gets satisfied or

dissatisfied after consuming these services. But there are some other airline

performance areas with which the traveller is encountered and which also determines

the air traveller’s satisfaction or dissatisfaction like on-time arrival and departure,

baggage handling, handling of complaints, right and timely information to the

customers, security services, interaction with the crew and ground staff members etc.

(en.wikipedia.org/wiki/Jagson_Airline)

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2.8.8 PARAMOUNT AIRWAYS

Paramount Airways was an airline based in Chennai, India. It was a national licensed

airline. It operated scheduled services, mainly targeting business travellers. Its hub

was Chennai International Airport. It was the first airline in India to launch the New

Generation Embraer 170/190 Family series aircraft.

History- The airline started operations in October 2005 and the company was

originally headquartered in Madurai, where they also operate Paramount Textiles.

Destinations- Since the withdrawal of its license, the operations of the airline are

currently suspended. The airline has stated that it intends to resume operations in

December 2010 following their successful case in the Madras High Court. As of

January 2010 the average age of the Paramount Airways fleet was 8 years. On 20th

June, 2009, Paramount Airways signed a MoU to buy ten Airbus A321-200 aircrafts

with an option for an additional ten. The agreement was concluded at the 48th Paris

Air Show. The deal is being funded by the European Central Bank.

The airline evaluated two turboprop aircraft, the ATR 72-600 and the Bombardier

Dash 8 Q400 at the 2009 Dubai Air show. It had plans to buy up to eight turboprop

aircrafts which would be deployed to connect smaller Indian cities. It however settled

for 6 Bombardier Dash 8 Q400s.

Legal issue and cancellation of licence- In early 2010, legal issues between

Paramount Airways and the lessors of their Embraer aircraft led to the de-registration

of their fleet. This caused a gradual termination of all services as their fleet was

grounded and then, subsequently, seized by the leasing companies.

Court victory and resumption of services - In November, 2010, it was announced

that Paramount Airways have won their legal battle and are all set to resume services

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with a fleet based on Airbus and Bombardier aircraft. Normalisation of the route

network should be successful by December, 2010.

(en.wikipedia.org/wiki/Paramount_Airways)

2.9 AIR TRAFFIC TRENDS

Table 2.3 Air traffic trends: World vs India 2000-2010

E-Estimated

F –Forecast

Source: ICAO data to 2008, IATA 2009 estimates and 2010 forecasts and Airport Authority of India traffic forecasts

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Fig 2.5 Worldwide Passenger Traffic: % Growth Total 2000 to 2010F

Fig 2.6 India Passenger Traffic: % Growth Total 2000 to 2010F

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Fig 2.7 Strong Domestic Passenger Traffic Growth

Fig 2.8 Load Factor at the Highest Level in a Decade

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Table 2.4 Monthly Traffic and Operating Statistics of All Indian Carriers on

Scheduled Domestic Services During 2009-2010

Source: DGCA

102

Table 2.5 Comparative Statement of Domestic Traffic on Scheduled Services of

All Indian Carriers During 2009-10

Source: ICAO Form-A Furnished by Scheduled Indian Carriers

103

Table 2.6 Comparative Statement of Total Traffic on Scheduled Services of All

Indian Carriers During 2009-2010

Source: ICAO Form-A Furnished by Scheduled Indian Carriers

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REFERENCES

Airline. (2010). Retrieved June 23, 2011 from http://en.wikipedia.org/wiki/Airline.

Air India. Retrieved Feb 10, 2012 from http://en.wikipedia.org/wiki/Air_India.

Anjali. (2011). Find cheap domestic flights in India with a click of mouse. Retrieved

June 18, 2011 from http://www.articlesalley.com/article.detail.php.

Aviation. (March, 2011). Retrieved June 23, 2011 from

http://www.ibef.org/sector/Aviation.

Civil Aviation Policy. (2011). Retrieved June 23, 2011 from

http://www.businessmapsofindia.com/indiapolicy.

Civil Aviation Policy (Draft). (April, 2000).Retrieved June 25, 2011 from

http://www.gidb.org.

Domestic airports in India. Retrieved June 23, 2011 from http://mapsofindia.com/air-

network/domestic-airport-map.htm.

Go Air. Retrieved Feb 10, 2012 from http://en.wikipedia.org/wiki/GoAir.

Gupta, Sanjana. (2008). Service Quality in Airlines. A Dissertation submitted to The

University of Jammu.

IndiGo. Retrieved Feb 10, 2012 from http://en.wikipedia.org/wiki/IndiGo.

International airports in India. Retrieved June 23, 2011 from

http://mapsofindia.com/air-network/international-airport-map.htm.

Jagson Airline. Retrieved June 25, 2011 from

http://en.wikipedia.org/wiki/Jagson_Airline.

Jet Airways. Retrieved June 23, 2011 from http://en.wikipedia.org/wiki/Jet_Airways.

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Kingfisher Airline. Retrieved Feb 10, 2012 from

http://en.wikipedia.org/wiki/Kingfisher_Airlines.

Latest developments and policy initiatives in Civil Aviation in India (March, 2007),

Retrieved June 23, 2011 from

http://www.inrnews.com/realestateproperty/india/infrastructure.

Overview. (2008). Retrieved June 22, 2011 from http://www.info.shine.com/Industry-

Information/Aviation.

Paramount Airways. Retrieved June 23, 2011 from

http://en.wikipedia.org/wiki/Paramount_Airways.

Passenger data. (2012). Retrieved Feb. 10, 2012 from

http://www.dgca.nic.in/reports/pass_data.pdf.

Pasari Nitika. (2005-06). Low Cost Airlines in a Developing Economy- The Case of

India. A Dissertation submitted to The University of Nottingham.

Role of Aviation Industry in India GDP. (2008). Retrieved June 23, 2011 from

http://www.businessmapsofindia.com/indiagdp/industries.

SpiceJet. Retrieved June 23, 2011 from http://en.wikipedia.org/wiki/SpiceJet.

Vivek. (2011). Travelling between the cities with the cheapest flights in India.

Retrieved June 18, 2011 from

http://www.articlesalley.com/article.detail.php.

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–

During the past three decades, a growing number of researchers and marketing

practitioners have undertaken systematic efforts to understand the effect of

consumption of services on the customer’s satisfaction. The increasing attention given

to the subject has been manifested in various ways. In the service consumption

process, service encounter stage and post encounter stage is very critical to build the

relationship between a service provider and a customer. A negative evaluation of

service encounter by a customer leads to service failure which effects the satisfaction

of a customer. After a service failure occurs, the service provider has the opportunity

to take a variety of recovery actions to re-establish the customer satisfaction. A lot of

research work has been done in the areas of effect of service encounter, service

failures and recovery strategies on customer satisfaction. In this context, it becomes

imperative to undertake a synoptic view of research conducted on effect of service

encounter, service failures and recovery strategies on customer satisfaction in various

service sectors (like restaurant, hotels, airlines, medical, self-service technologies,

online environment etc.). This will indicate the areas in which researcher could

concentrate more, though, it may be necessary but not possible to give a detailed

review of existing literature, yet an attempt has been made to provide a

comprehensive account of the findings of various studies and identify research gaps

there in. Further with the help of review of literature, an outline of the research design

to be adopted by the researcher in the present study has been developed.

CHAPTER-3

REVIEW OF LITERATURE

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The review of literature has been divided into two sections; separately dealing with

the topics of service encounters and service failure and recovery strategies. The

literature review includes findings of studies in the related subject done in the recent

past. However, research by Bitner, Booms and Tetreault (1990) form the basis of

present research. Since the time of Bitner et al’s work, several studies have been

published that attempt to study the effect of service failures and recovery strategies on

customer satisfaction.

3.1 SERVICE ENCOUNTER

For the success of marketing efforts, there is increased recognition of the significance

of the person to person encounter i.e. between the service provider and the customer

and the effect of this encounter on the customer. The concept of Service Encounter

i.e. a period of time during which a customer interact directly with service provider

(Shostack, 1985). The concept of service encounter and its effect on the person

involved has attracted the attention of researchers in the last few years.

Surprenant and Solomon (1987) in the paper “Predictability and Personalization in

the Service Encounter” investigate the soundness of the conventional wisdom that

personalized service is better service. The findings of the study confirm that service

personalization is a multidimensional construct and all forms of personalization do

not necessarily result in more positive evaluations of the service offering by

consumers. Personalized service is not without cost to the service establishment or to

consumers, and its degree of “value added” should be assessed carefully.

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Bitner (1990) in her research paper “Evaluating Service Encounters: The Effects of

Physical Surroundings and Employee Responses” presents a model for understanding

service encounter evaluation that synthesizes consumer satisfaction, services

marketing and attribution theories and provides a framework for programmatic

research on service encounter evaluations. A controlled experiment was conducted to

test a portion of the model focusing on the relationships between attributions and

satisfaction and between selected elements of the services marketing mix and

attributions. The results of the study showed that when customers perceive the cause

of service failure to be with in the control of the firm and likely to occur again, they

will be more dissatisfied than when opposite conditions hold. The controllable

variables such as employee explanations, offers to compensate and the appearance of

the physical environment can influence how customers perceive the causes of service

failure. The framework and study results reinforce the idea that elements of the

expanded marketing mix should be included in strategies for improving service

encounter satisfaction.

Bitner, Booms and Tetreault (1990) in their study “The Service Encounter:

Diagnosing Favorable and Unfavorable Incidents” applied the Critical Incident

Method, collected 700 incidents from customers of airlines, hotels and restaurants,

resulted in three major groups of employee behaviours that could account for all

satisfactory and dissatisfactory incidents. The three major groups are – Group 1:

Employee response to service delivery system failures: When the service delivery

system fails, contact employees are required to respond to consumer complaints or

disappointments. The content or form of the employee response determines

customer’s perceived satisfaction or dissatisfaction. Group 2: Employee Response to

Customer Needs and Requests: When a customer requires the contact employee to

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adapt the service delivery system to suit his or her unique needs, the contact

employee’s response determines customer’s dis/satisfaction. In this group incidents

are required to contain either an explicit or inferred request for customized service

and Group 3: Unprompted and Unsolicited Employee Actions: Events and

employee behaviours that are truly unexpected from the customer’s point of view are

included in this group. Satisfactory incidents represent very pleasant surprises (special

attention, being treated like royalty, something nice but not requested) where as

dissatisfactory incidents comprise negative and unacceptable employee behaviours

(rudeness, stealing, discrimination, ignoring the customer).

With in three major groups, there are 12 categories under which various incident

outcomes were defined. Group1 includes three categories –

G1A: Response to Unavailable Service: Services normally available are lacking or

absent like the airplane is overbooked or the reserved table is occupied. The way in

which non availability is handled influences the customer’s perception of the service.

G1B: Response to Unreasonably Slow Service: This category reflects incidents in

which services or employee performances are perceived as inordinately slow.

Employee reaction to such delays determines the customer’s satisfaction level.

G1C: Response to other Core Service Failures: It includes incidents in which other

aspects of the core service do not meet basic performance standards for the industry

(e.g. the hotel room is not clean, the baggage arrives damaged). How the employee

responds to these failures determines the customer’s perceptions of the encounter.

Group2 includes four categories – G2A: Response to Special Needs Customers:

This category involves customers who have special medical, dietary, psychological,

language or sociological difficulties. Failure to recognize the seriousness of the

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customer’s need and/or inappropriate or inadequate treatment of the problem can

result in a very dissatisfactory incident.

G2B: Response to Customer Preferences: This category includes incidents when

from the customer’s perspective, special requests are made. These requests reflect

personal preferences unrelated to the customer’s sociological, physical or

demographic characteristics. However, customers can be very dissatisfied when their

preferences are not accommodated, especially if the employee shows no interest and

exerts no effort to be responsive, is unwilling to consider ‘bending the rules’, or

promises to do something and then fails to follow through.

G2C: Response to Admitted Customer Error: In this category the triggering event

is a customer error that strains the service encounter (e.g. lost tickets, missed

reservations). Dissatisfactory employee responses include laughing at and

embarrassing the customer for his or her mistake, avoiding any responsibility and

demonstrating an unwillingness to assist the customer in solving the problem.

G2D: Response to Potentially Disruptive Others: With in the environment of the

service encounter, other customers’ behaviours can strain the encounter (e.g.

intoxication, rudeness, social deviance). The contact employee either does or does not

cope with the disruptive person(s) to the satisfaction of other customers present.

Group3 includes five categories – G3A: Attention paid to Customers: This category

includes incidents in which the level of attention paid to the customer is viewed very

favourably or negatively. Dissatisfactory encounters occur when contact employees

demonstrate poor attitudes toward the customer, ignore the customer or treat the

customer impersonally.

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G3B: Truly out-of-ordinary employee behaviour: In this category are incidents in

which the employee does some small thing that for the customer translates into a

highly satisfactory or dissatisfactory encounter. In case of dissatisfactory encounters,

extraordinary employee behaviour may consist of profanity, yelling, inappropriate

touching or rudeness.

G3C: Employee behaviours in the context of Cultural norms: Incidents in this

category reflect employee behaviours relating to cultural norms such as equality,

honesty and fairness. Dissatisfactory encounters are associated with employee

behaviours that clearly violate cultural norms (discrimination against female/young

customers, employee theft, bribery or lying).

G3D: Gestalt evaluation: For dissatisfactory incidents in this category, customers

are unable to attribute dis/satisfaction to any single feature of the service encounter.

Instead the service encounter is evaluated holistically, either ‘everything went right’

or ‘everything went wrong’.

G3E: Performance under adverse circumstances: This category includes incidents

in which the customer is particularly impressed / displeased with the way a contact

employee handles a stressful situation.

The incidents were categorized to isolate the particular events and related behaviours

of contact employees that cause customers to distinguish very satisfactory service

encounters from very dissatisfactory ones. The study has various implications like the

Critical Incident Method is a useful tool for assessing customer dis/satisfaction in

service encounters and the classification system that emerged from the data can be

used to other high-contact transaction-based service industries as well. The CIT

enables managers to identify what knowledge is needed and what control is required

112

as well as providing a basis for determining which is more important for a given type

of encounter. The results of this study suggest that the CIT is also an appropriate and

useful method for studying marketing questions and for assessing customer

perceptions.

Table 3.1 Bitner et al’s (1990) Group and Category Classification by Type of

Incident Outcome

Group & Category Type of Incident Outcome

Group 1 Employee Response to Service Delivery System Failures

G1A Response to unavailable service

G1B Response to unreasonably slow service

G1C Response to other core service failures

Group 2 Employee Response to Customer Needs and Requests

G2A Response to special needs customers

G2B Response to customer preferences

G2C Response to admitted customer error

G2D Response to potentially disruptive others

Group 3 Unprompted and Unsolicited Employee Actions

G3A Attention paid to customers

G3B Truly out-of-the ordinary employee behaviour

G3C Employee behaviours in the context of cultural norms

G3D Gestalt evaluation

G3E Performance under adverse circumstances

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Bitner, Booms and Mohr (1994) in their study “Critical Service Encounters: The

Employee’s Viewpoint” collected critical service encounters reported by employees

of the hotel, restaurant and airline industries. The purpose of the study is to evaluate

the soundness of the classification scheme developed by Bitner et al, 1990 in a

distinctive context. Drawing on insights from role, script and attribution theories

critical service encounters were analyzed and compared with previous research. The

results indicated that all the categories found in the original customer-perspective

study (Bitner et al, 1990) were also found when employees were asked to report

and also identify an additional source of customer dissatisfaction i.e. their own

misbehaviour. The addition of this new group 4, problematic customer behaviour

provides a more complete classification system that can be further examined in other

contexts. It is suggested that many frontline employees do have a true customer

orientation and do identify with and understand customer needs in service encounter

situations. It is also derived that customers can be the source of their own

dissatisfaction through inappropriate behaviour or being unreasonably demanding.

Mohr and Bitner (1995) in their empirical study “The Role of Employee Effort in

Satisfaction with Service Transactions” examined how one aspect of service

encounter i.e. perceived employee effort affects customer satisfaction with service

transactions. The results of the study indicated that perceived effort has a strong

positive impact on transaction satisfaction, and this effect is not eliminated when the

perceived success of the service outcome is statistically controlled. They also

concluded that effort is perceived by consumers through a variety of behavioural and

attitudinal cues. The study results suggest implications for motivation, attribution, and

customer satisfaction theories, as well as for managing the service encounter.

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Price, Arnould and Tierney (1995) in the paper “Going to Extremes: Managing

Service Encounters and Assessing Provider Performance” provided a framework for

analysis and comparison of service encounters using three dimensions- duration,

affective content and spatial proximity. They also develop measures of service

provider performance and test a structural model of the relationships among service

provider performance, affective response and service satisfaction for EAI encounters.

The results supported that EAI encounters provider performance strongly influences

positive affect, and affect both negative and positive, in turn influences encounter

satisfaction. It is found that emotional fatigue, role stress, role conflict and the

problem of negotiating relationship boundaries pose important managerial challenges

for EAI services.

Bejou, Edvardsson and Rakowski (1996) in their empirical study “A Critical

Incident Approach to Examining the Effects of Service Failures on Customer

Relationships: The Case of Swedish and U.S. Airlines” analyze negative critical

incidents from the customers’ point of view and thus create a basis for crisis

management and quality improvement. The study describe and analyze negative

critical incidents from 320 customers and 80 airline employees in Sweden and 241

customers and 100 employees in the United States. The results indicate how important

it is to collect data about lapses in quality directly from the customer in order to gain

an understanding of quality defects and to develop quality in the right areas. It is

drawn from the study that the airline should train its staff in the techniques of

communication and how to relate to customers when critical incidents occur. The

study showed that the critical incident technique is a useful tool and that it provides

interesting and meaningful information about customers.

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Grove and Fisk (1997) conducted a study “The Impact of Other Customers on

Service Experiences : A Critical Incident Examination of ‘Getting Along” using the

critical incident technique, data were gathered from 486 customers regarding

satisfying or dissatisfying episodes with service organizations that were the result of

other customer’s presence. The findings of this study are (a) Extended waits that often

accompany many service encounters can put people in a bad mood, tempers can flare

and disruptive behavior can result, (b) apparently satisfying all customers with the

same service delivery is virtually impossible, (c) tendency of people to be less

inhibited when they are “out-of-town” or among strangers has long been observed, (d)

methods for improving customer-to-customer relationships are apparently needed.

The study suggested that before means of enhancing customer-to-customer

relationships or controlling against negative incidents can occur, organizations need to

develop an appreciation for the importance of managing other customers.

Callan (1998) in the paper “The critical incident technique in hospitality research: an

illustration from the UK lodge sector” studied the strengths and weaknesses of the cri

tical incident technique to compare the criteria used in the grading of UK budget

hotel lodges with the needs of customers and the hotel managers’ view of customers’

perceived needs. As the study was concerned with the adequacy of the grading

scheme for lodges, the incidents were first subdivided into three major categories.

Under each of these categories, ten sub categories were developed. In turn, a number

of attributes were identified under each of the sub categories. This broader application

of CIT allows not only comparisons between sub categories, but also judgements to

be made about the relative importance of a range of tangible and intangible attributes.

It is suggested that CIT is an appropriate and useful technique for studying service

quality questions and assessing customers’ perceptions.

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Chell and Pittaway (1998) in their research paper “A study of entrepreneurship in

the restaurant and café industry: exploratory work using the critical incident technique

as a methodology” study the Critical Incident Technique as a methodology and show

the technique can be used to research development in the hospitality industry. This

technique has been used in the paper to analyse the behaviors associated with

entrepreneurship in the restaurant and café industry. The CIT has been shown to be a

versatile and useful tool for gathering primary data of a subjective nature from

participants. It can, through careful coding, reveal both quantifiable data, and

descriptions of a qualitative kind. In the study concluded that CIT is a powerful tool

which is theoretically sound, capable of facilitating considerable depth of analysis and

can help produce important insights into the nature of entrepreneurship in the

hospitality industry.

Smith, Bolton and Wagner (1999) executed the research in the context of two

different service settings, restaurants and hotels in their study “A Model of Customer

Satisfaction with Service Encounters Involving Failure and Recovery” They

developed a model of customer satisfaction with service failure/recovery encounters

based on an exchange framework that integrates concepts from both the consumer

satisfaction and social justice literature, using principles of resource exchange, mental

accounting and prospect theory. The results show that customers prefer to receive

recovery resources that ‘match’ the type of failure they experience in ‘amounts’ that

are commensurate with the magnitude of the failure that occurs. The study also

provided organizations with guidelines for developing service recovery procedures

that improve customer service and enhance customer relationships. These guidelines

can be used to implement service delivery systems that include provisions for

appropriate recovery efforts, allocate recovery resources to maximize returns in terms

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of satisfaction, and train employees to recognize failures and reduce their effects on

customers.

Bitner, Brown and Meuter (2000) in their research paper “Technology Infusion in

Service Encounters” examined the ability of technology to effectively-customize

service offerings, recover from service failure, and spontaneously delight customers.

The infusion of technology is examined as an enabler of both employees and

customers in efforts to achieve these three goals. The challenges of successfully

incorporating technology must be recognized. Firms that consider the implementation

of technology should closely involve customers in the design process. Satisfying

specific customers’ needs and creating an open dialogue to address concerns are

important ways of overcoming some of the negative repercussions of technology

infusion. They suggested that management must carefully address the impact of

technology on encounter costs and customer satisfaction and loyalty. In moving

toward enabling technology use in service encounters, it is important to retain the

traditional low-tech, high-touch approach as a viable option for customers.

Meuter, Ostron, Roundtre and Bitner (2000) described in their study “Self-Service

Technologies: Understanding Customer Satisfaction with Technology –Based Service

Encounters” the CIT involving self-service technologies (SSTs) solicited from

customers through a web-based survey. The incidents are categorized to discern the

sources of satisfaction and dissatisfaction with SSTs. They categorized the incidents

into seven groups (solved intensified need, better than the alternative, did its job,

technology failure, process failure, poor design and customer driven failure) to

discern the sources of satisfaction and dissatisfaction with SSTs. By including a series

of quantitative measures to elicit additional information related to the incident, the

study linked the qualitative categories to other consumer evaluations and behaviors. In

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the study, the researchers related the critical incident categories with customer

attributions, complaining behavior, word of mouth and repeat purchase intentions.

They also studied the sources of customer satisfaction with SST encounters similar to

or different from the sources of customer satisfaction and dissatisfaction with

interpersonal encounters.

Dolen, Lemmink, Mattsson and Rhoen, (2001) in their research paper “Affective

consumer responses in service encounters: The emotional content in narratives of

critical incidents” explores the effect of emotion on satisfaction with after sales

services. It is concluded that critical incidents evoke emotional responses in a

customer. The emotional content is classified according to three levels of

inclusiveness: the super ordinate, the basic and the subordinate level. It is found that

the subordinate level is responsible for explaining most of the service satisfaction.

Positive emotions like positive surprise, pleasure and contentment contribute

positively to satisfaction, while negative emotions, such as irritation and

disappointment have a negative influence. Also, more intense emotions have a greater

impact on customer satisfaction than less intense emotions. By analyzing and

classifying content from respondents’ written answers to the critical incident question,

seem to be a valid way to isolate the particular emotions that cause customers to

distinguish satisfactory service encounters from less satisfactory ones. It is suggested

that training, motivating and rewarding service employees to evoke positive emotions

in the customers raise the potential for imposing a significant positive impact on the

overall customer satisfaction.

Friman, Edvardsson, Garling (2001) in their study “Frequency of negative critical

incidents and satisfaction with public transport services I” investigated whether

cumulative overall and attribute-specific satisfaction with public transport services are

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related to the remembered frequency of negative critical incidents. A model of these

relationships was proposed and estimated for survey data obtained from public

transport users. In this model overall cumulative satisfaction is positively related to

attribute-specific cumulative satisfaction which in turn is negatively related to the

remembered frequency of negative critical incidents. In addition, measurement

models indicated that both attribute-specific satisfaction and the frequency of negative

critical incidents are related to treatment by employee, reliability of service, simplicity

of information and design.

Kivela and Chu (2001) in their empirical study “Delivering Quality Service:

Diagnosing Favorable and Unfavorable Service Encounters in Restaurants” found

linkages between customer feedback and employee performance and the possible

integration of feedback into the overall management of service delivery in restaurants.

By using CIT 1294 favorable and unfavorable responses were collected from the

customers of restaurants. The results of this study concur with and confirm Bitner

et al’s 1990 findings and suggest that classifications and sub classifications are

more critical contributory factors of favorable and unfavorable service

encounters in restaurants. It is suggested that the CIT has the potential to provide

appropriate qualitative data as a foundation for restaurants’ service quality assurance

strategies to their customers. The findings of this study is that service encounters in

restaurants appeared to moderate the relationship between employees and customers

as well as customers’ overall dining experiences. This study also suggested that the

quality of customer-service provider encounters might have a greater impact on how

customers feel about restaurants than the quality of food and the ambience.

Ofir and Simonson (2001) in their experimental study “In Search of Negative

Customer Feedback: The Effect of Expecting to Evaluate on Satisfaction Evaluations”

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demonstrated that expecting to evaluate leads to less favorable quality and satisfaction

evaluations and reduces customers’ willingness to purchase and recommend the

evaluated services. Systematic bias can be possible through three ways referred as

negativity enhancement, role expectation, and vigilant processing. The findings of the

study are most consistent with the negativity enhancement account indicating that

unless buyers begin the evaluation task with low expectations, they tend to focus

during consumption primarily on negative aspects of product /service quality.

Turley and Hoffman (2001) in their paper “The Role of the Environment in Self-

service Encounters” explores a type of encounter that occurs between customers and

inanimate service environment. Also find strategic differences that differentiate

environmentally-based service encounters from those that are primarily based on

interactions between providers and customers. The level of technology needed for

delivering self-service need not be extremely high, low level technology is used in

some cases.

Dolen, Lemmink, Ruyter and Jong (2002) in their research paper “Customer-sales

employee encounters: a dyadic perspective” found that the perceptions of employee

performance and satisfaction do not only reflect the unique interaction between the

customer and the employee, but also relatively stable characteristics of the employee.

It is the unique experience of the customer and the employee during the interaction

that is important in creating satisfaction for both parties. It is suggested that hiring and

training policies for employees focusing on task and social competence profiles could

be valuable for the sake of customer and employee satisfaction, contributing thereby

to sales and employee success.

Hoffman and Turley (2002) examined in their study “Atmospherics, service

encounters and consumer decision-making: An integrative perspective” the impact of

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the environment on the consumer’s service experience and the potential role of

atmospherics throughout the service consumer decision process. It is found that

creating an atmosphere that enhances the delivery of a product can have a tremendous

effect on how consumers perceive that product. Managers should review the

atmosphere in which these encounters occur to make sure that information sought out

during the prepurchase stage is present, that the atmosphere supports and encourages

consumers to interact with service personnel during the consumption stage, and that

the environment will contribute to meeting consumer expectations and leading to

satisfaction.

Aksoy, Atilgan and Akinci (2003) found in their paper “Airline services marketing

by domestic and foreign firms: difference from the customers’ view point” that

significant differences exist between the foreign and domestic airline passenger

groups on the same flight destinations with respect to their demographic profiles,

behavioral characteristics, and understanding of airline service dimensions. They also

suggested that a firm’s competitive advantage is established by its ability to satisfy

customers’ present and future needs. The primary purpose of this paper is to look at

the profiles and service expectations of airline customers of domestic and foreign

carriers, and to provide valuable clues to improve services.

Hoffman, Kelly, and Chung (2003) in their research paper “A CIT investigation of

servicescape failures and associated recovery strategies” investigated service failures

relating to problems with the management of the servicescape with the help of CIT.

Of the 1370 failure critical incidents collected, 123 were identified as servicescape

failures. The three primary types of servicescape failure identified are - cleanliness

issues, mechanical problems and facility design issues. The study also identifies eight

servicescape sub failure type categories and discusses failure ratings, recovery

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strategies, recovery ratings and customer retention rates. They suggested that the

design of facilities is important; their impact on customers is only as good as how

well these facilities are maintained over time.

Chung-Herrera, Goldschmidt and Hoffman (2004) examined perceptual

similarities and differences between customers and employees in terms of critical

service incidents in the research paper “Customer and employee views of critical

service incidents”. The Critical Incident Technique was used to collect 1512

customer-reported incidents and 390 employee-reported incidents. Each critical

incident through a deductive sorting process systematically categorized into three

major failure groups developed by Bitner et al (1990). The results showed that

overall customers and employees were fairly similar in their perceptions regarding

failures that ultimately resulted in a good recovery effort. They concluded that

employee perceptions tended to be more aligned with customer perceptions when the

overall outcome was good. Conversely, employees tended to diverge from customer

views when the overall outcome was poor. During the service encounter, it is

important that employees have a better understanding of exactly how customers

perceive failure events.

Friman (2004) in the paper “The structure of affective reactions to critical incidents”

examines affective reactions to positive and negative scenarios describing critical

incidents in public transport and their impact on satisfaction. It is concluded that

satisfaction depended on the nature and type of the critical incidents. The mood

people experience when using public transport services may be influenced by

critical incidents, as the difference between positive critical incident, negative

critical incident and neutral incidents gives witness to. Also, unpleasantness -

pleasantness rather than deactivation – activation appeared to determine satisfaction.

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The results of the study indicated that respondents rated satisfaction lower after

having encountered a negative critical incident and higher after having encountered a

positive critical incident.

Poon, Hui and Au (2004) in their study “Attributions on dissatisfying service

encounters : A cross-cultural comparison between Canadian and PRC consumers”

explores the variations in the stage of economic development and the cultural

dimension of long-term versus short-term orientation affect consumers’ perceived

level of control in and attributions of dissatisfying service encounters, and the relative

effects of various attribution dimensions (including locus, controllable-by-

organization, and stability) on consumers’ switching intentions. The results indicated

that compared to PRC consumers, Canadian consumers experience more deprivation

of control in dissatisfying service encounters and exhibit stronger self-serving biases

in forming attributions about their dissatisfying service experiences. Also, the

controllable-by-organization dimension is found to have a stronger effect on the

switching intentions of Canadian consumers than that of PRC consumers, while the

opposite is found for the stability dimension. The results suggested that switching

intentions are affected by the three casual attributions (locus, controllable-by-

organization, stability). The service companies or employees should understand that

service failure is inevitable and it is important to carry out appropriate service

recovery (such as apology, explanation and offer to compensate) so as to alleviate the

negative effect of the casual attributions on post consumption behavioral intentions.

Petrick, Tonner and Quinn (2006) in their study “The Utilization of Critical

Incident Technique to Examine Cruise Passengers’ Repurchase Intentions” use CIT to

identify both positive and negative incidents and examine the differences among the

established CIT categories (both positive and negative) and their overall satisfaction,

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perceived value, WOM and repurchase intentions. The results of the CIT analysis

revealed eight themes related to moments of truth that are positively related to cruise

passengers’ cruise experiences and ten themes related to negative cruise experiences.

These identified themes can be used by cruise management to examine areas in which

critical incidents are assisting and/or hindering their interactive marketing efforts.

Results imply that analyzing critical incidents can be an effective management tool

for cruise line management and that these “moments of truth” are relevant to visitor

retention. Also, found that negative incidents have a much greater effect on cruise

passengers’ post hoc cruise evaluations than positive incidents.

Holloway and Beatty (2008) in their study “Satisfiers and Dissatisfiers in the Online

Environment A Critical Incident Assessment” examines the factors driving customer

dis (satisfaction) in the online service environment using critical incident technique

and content analysis. They identify the critical drivers reported by consumers to

produce particularly satisfactory or dissatisfactory online service encounters in three

industry groups (hard goods, soft goods and services). The results found how

satisfiers and dissatisfiers vary both overall and across industry classifications,

providing an assessment of the differences between the factors producing online

success versus those preventing failure.

Lundberg (2011) in the research paper “Critical Service Encounters in Hotel

Restaurants: The Personnel’s Perspective” explores the frontline hotel restaurant

workers’ experiences of satisfactory and dissatisfactory face to face critical service

encounters. A critical incident technique was employed to collect experiences of

critical service encounters together with projective techniques. The findings of the

study showed that a large proportion of the dissatisfactory incidents are related to

problematic customer behaviour.

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3.2 SERVICE FAILURE AND SERVICE RECOVERY

Service failures, recovery strategies and their effect on customer have attracted a lot

of attention from researchers. Various research studies have been conducted on

various issues related to this area of service marketing. A brief account of the

researchers carried out in the area has been discussed.

Singh (1988) in the study “Consumer Complaint Intentions and Behavior:

Definitional and Taxonomical Issues” assesses the validity of the three current

operationalizations and taxonomies of consumer complaint behavior (CCB) using

intentions data from four different and independent CCB situations. The findings

indicate that the currently available taxonomies and operational definitions cannot be

accepted as satisfactory representations of observed CCB responses. It is showed that

CCB is a three-faceted phenomenon consisting of voice, third party and private

actions; are distinct, have discriminant validity and warrant additional research

attention. The findings suggest that researchers may find it advantageous to

operationalize the CCB construct at the level of its individual dimensions.

Hart, Heskett and Sasser (1990) explained in their article “The Profitable Art of

Service Recovery” that service recovery is a significant management philosophy, one

that embraces customer satisfaction as a primary goal of business. Service companies

shift the emphasis from the cost of pleasing a customer to the value of doing so and it

entrusts front line employees with using their judgment. In the article it is emphasized

that a good service recovery can turn angry, frustrated customers into loyal ones and it

can create more goodwill than if things had gone smoothly in the first place. They

suggested that companies that want to build the capability of recovering from service

problems should do these things: measure the costs of effective service recovery,

break customer silence and listen closely for complaints, anticipate needs for

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recovery, act fast, train employees, empower the front line and close the customer

feedback loop.

Bitner (1992) in the paper “Servicescape: The Impact of Physical Surroundings on

Customers and Employees” provide a theoretical framework that describes how the

built environment (i.e. the manmade, physical surroundings) or what is referred to as

the servicescape affects both consumers and employees in service organizations. The

overall conclusion is that through careful and creative management of the

servicescape, firms may be able to contribute to the achievement of both external

marketing goals and internal organizational goals. Decisions about the physical

facility can have an impact on human resource goals (e.g. worker retention, worker

productivity), operations goals (e.g. efficiency, cost reduction) and marketing goals

(e.g. consumer attraction, consumer satisfaction). The typology of service

organizations combined with the theoretical framework suggests that the physical

environment assume a variety of strategic roles in services marketing and

management.

Kelly, Hoffman and Davis (1993) in their research work “A Typology of Retail

Failures and Recoveries” provides an initial investigation of the failures and

subsequent recoveries experienced by retail customers using the CIT methodology.

The work of Bitner and her colleagues (Bitner, Booms, Tetreault, 1990; Gremler

and Bitner, 1992) served as a starting point for the content analysis of the critical

incidents collected for this research. They identified nine categories of service

failures in group1- employee response in service delivery system failures, two

categories of service failures in group2- employee response to customer needs and

requests and four categories of service failures in group 3- unprompted and

unsolicited employee actions. Total fifteen types of retail failures and twelve types

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of recovery strategies were identified in this study. The study demonstrates the

importance of recovery in the retail industry whenever a retail customer experiences a

failure.

Kelly and Davis (1994) proposed model in the paper “Antecedents to Customer

Expectations for Service Recovery” in which customer perceptions of service quality ,

customer satisfaction and customer organizational commitment function as

antecedents to service recovery expectations. The proposed model was tested with

covariance structure analysis. The results of the study indicated that perceived service

quality and customer satisfaction are directly related to customer organizational

commitment. Committed customers are also likely to hold elevated expectations for

recovery. The results suggested that service quality and customer organizational

commitment have direct effects on customer service recovery expectations and that

customer satisfaction has an indirect effect on service recovery expectations.

Taylor (1994) in the paper “Waiting for Service: The Relationship Between Delays

and Evaluations of Service” concluded that delays can affect service evaluations in a

negative fashion. An empirical test of the model with delayed airline passengers

reveals that delays do affect service evaluations; however this impact is mediated

negative affective reactions to the delay. Service providers should attempt to either

shorten or eliminate delays for service (by operations management), or change the

consumer’s wait service (by perceptions management) so that it results in less

uncertainty and anger. The affective reactions of anger and uncertainty play a key role

in mediating the delay’s effects on service evaluations.

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Blodgett, Wakefield and Barnes (1995) conducted a study “The effects of customer

service on consumer complaining behavior” to determine why some dissatisfied

consumers seek redress while others do not approach the seller with their complaint.

The study also presents a dynamic model of the complaining behavior process. The

results indicated that the pay-off gained from retaining a dissatisfied customer is many

times greater than the cost of remedying the complaint. It is also implied that

dissatisfied customers expect not only to receive a fair settlement but, more

importantly, they also to be expect treated with courtesy and respect. It is suggested

that retailers and other service providers can view the complaining behavior process

as an opportunity to solidify and strengthen their relationships with their customers.

Sellers can implement complaint-handling policies and procedures that are designed

to maximize customer satisfaction and can train their employees to implement these

policies and procedures effectively.

Hoffman, Kelly and Rotalsky (1995) in their research article “Tracking service

failures and employee recovery efforts” identify and classify failures with in the

restaurant industry, assess customer perceptions regarding the magnitude of each

failure, identify and classify recovery strategies utilized by restaurants to correct

failures, assess customer perceptions of the effectiveness of each recovery strategy

and assess subsequent patronage behaviors. The CIT is applied to describe a

typology of service failures and recoveries and three main categories previously

identified by Bitner et al (1990) was used to classify the service failures. The

results of the study suggest the importance of employee training as these failures were

difficult to effectively recover. Also, suggest service managers to effectively design

their service delivery systems and procedures.

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Spreng, Harrell and Mackoy (1995) in their paper “Service Recovery: impact on

satisfaction and intentions” using data from 410 customers who reported damage

following a move of their household goods examined the relative importance of

service recovery activities in determining overall satisfaction and consequent

behavioral intentions. The results indicate that the service recovery process variables

have a relatively greater effect on overall satisfaction and behavioral intentions than

does the customer’s satisfaction with original service outcomes. It is suggested that

the companies should develop an excellent service recovery program then companies

should actively encourage complaining behavior and it should reevaluate their relative

budget allocations to these two activities. Also provides evidence of the importance of

service recovery in producing satisfied customers who intend to use the firm’s

services in the future and would provide positive word of mouth.

Brown, Cowles and Tuten (1996) in their study “Service recovery: its value and

limitations as a retail strategy” examines the impact of service recovery as a

relationship tool; in addition to its well accepted role as a means to enhance customer

satisfaction at the transaction-specific level. A comparison of the concept of service

consistency and reliability with the concept of service recovery leads to a statement of

hypothesis tested in an experimental setting. The implications of service recovery as a

means to create and retain satisfied customers as well as its potential role in the

continual improvement of a service delivery system by providing employees both the

resources and the authority to recovery and inspiring them to participate in the process

of continual improvement.

Boshoff and Leong (1998) in their study “Empowerment, attribution and apologizing

as dimensions of service recovery – An experimental study” addresses the question of

relative importance of service recovery dimensions from a customer’s point-of-view

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by considering three dimensions- taking ownership of the problem; apologizing for

the inconvenience and empowering employees to solve customer complaints- that

could influence customer satisfaction. It is implied from the results that once a service

failure has occurred, customers expect the service firm to accept responsibility for the

problem; they prefer to deal with staff that are fully empowered to solve their problem

relatively quickly. An apology in person or, alternatively, by telephone is preferable.

Hocut and Stone (1998) in their experimental study “The Impact of Employee

Empowerment on the Quality of a Service Recovery Effort” investigate the effects of

frontline employee empowerment in a service recovery situation. The study1 showed

that giving employees’ autonomy to handle a service recovery situation would

significantly enhance their levels of satisfaction on the job. Additionally, providing

training in how to handle service recovery problems further improved employee

satisfaction. In study 2, an interaction effect was found between empathy/courtesy and

responsiveness. The effect revealed that satisfaction was maximized when high levels

of both empathy/courtesy and responsiveness occurred. It is indicated that employee

empowerment components (autonomy and training) influence employee job facet

satisfaction which in turn influences the perceived fairness of the service recovery

effort, thus leading to higher customer satisfaction. The study suggested that a service

recovery policy to empower frontline employees to “do whatever it takes to satisfy a

customer” must be combined with training on a set of guidelines to help employees

determine what would be reasonable to do under different service failure situations.

Tax and Brown (1998) in their article “Recovering and Learning from Service

Failure” used a survey designed to assess customers’ evaluations of their most recent

service complaint. More than 30 different types of services were the subjects of

respondent complaints, the most frequently identified were restaurants, automobile

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repair, banks, doctors and dentists, airlines, hotels and motels. The results of the

research shows that the majority of customers are dissatisfied with the way companies

resolve there complaints and there are vast majority of customers who do not take

advantage of the learning opportunities afforded by service failures. To guide

managers in designing an effective strategy, the researchers provide a four-stage

approach to service recovery- identifying service failures, resolving customer

problems, communicating and classifying service failures and integrating data and

improving overall service. The results of the study indicates that the successful

service recovery strategy has a strong effect on customer loyalty, employee

satisfaction and, ultimately, firm performance and profitability.

Webster and Sundaram (1998) in their research work “Service Consumption

Criticality in Failure Recovery” examined the effects of various service failure

recovery efforts – an apology, different levels of monetary compensations and an

offer to reperform the service- on customer satisfaction and loyalty across varying

levels of criticality for different service industries. An experimental design was used

to determine the effects of level of criticality, type of recovery effort and type of

service on customer satisfaction and loyalty. The findings of this study indicate that

both type of service failure recovery effort and criticality of service consumption have

a significant effect on customers’ perceived level of satisfaction and extent of loyalty

toward the firm. Also, there is a negative relationship between perceived criticality of

service consumption and customers’ attitudes once service failure occurs. It is

suggested that when service firm managers are deciding how to recover once service

failure occurs, they should consider the level of criticality the customer places on

successful delivery of that particular service. It means a recovery effort strategy must

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be based on the specifics of the situation; a firm cannot assume that standardized

recovery measures will be appropriate across all service failure situations.

Boshoff (1999) conducted a study “Recovsat : An instrument to Measure Satisfaction

with Transaction-Specific Service Recovery” to identify the dimensions of

transaction-specific service recovery satisfaction by analyzing consumer expectations

and to develop a validated measuring instrument to measure satisfaction with

transaction-specific service recovery based on those dimensions. It led to the

conclusion that the use of RECOVSAT instrument to evaluate how effectively service

recovery is performed from a customer’s point of view but it will also permit an

investigation of the organizational antecedents of satisfactory service recovery. This

tool can be adapted to be used as a service recovery performance evaluation measure

of frontline staff.

Johnston and Fern (1999) in their exploratory study “Service Recovery Strategies

for Single and Double Deviation Scenarios” contribute to the growing body of

knowledge on service recovery by identifying effective recovery strategies from a

customer’s point of view. It was found that customers have clear expectations of

service recovery for different levels of failure. Furthermore, service recovery can

restore the customer to a satisfied state or to a delighted state. Getting the customer

‘back to neutral’ appears to require one set of ingredients, where as an enhanced set is

required to delight the customer. The study also distinguishes between the actions

required in dealing with service failures (single deviation) and the situations where

there was an inappropriate or inadequate response to the failure (double deviation).

Mc Dougall and Levesque (1999) in their experimental study “Waiting for service:

the effectiveness of service recovery strategies” examined the effectiveness of service

recovery strategies in situations where the service firm made customers wait even

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though they had made a reservation. The recovery strategies –apology only,

assistance, compensation, assistance plus compensation- which reflected industry

practices, did not lead to positive future intentions towards the service firm. The

results of the study are customers held negative future intentions towards the service

provider regardless of the recovery strategy offered including assistance plus

compensation. Customers do not like pre-process, post-schedule waits. The best

strategy a service firm can pursue is to eliminate these waits, which they can do.

Levesque and Mc Dougall (2000) in their experimental study “Service Problems and

Recovery Strategies: An Experiment” examines the effectiveness of recovery

strategies after a service failure on customer complaint and complaint intentions. The

results of the study suggest that effectiveness of service recovery strategies (assistance

and/or compensation) varied depending on the type of service, problem severity, and

criticality levels. Also to improve the probability of retaining new customers, the firm

needs to reduce core failure rates. “Getting it right the first time” optimizes value for

both the customer and the firm.

Mack, Mueller, Crotts and Broderick (2000) examined in their study “Perceptions,

corrections and defections: implications for service recovery in the restaurant

industry” customer perceptions of their personal service failures experienced in the

restaurant industry. This study found customers to be very specific about, and

involved in, failures they experienced in the restaurant industry. Identifying failures

points in the service delivery process and identifying methods to prevent these failures

help to prevent negative customer perceptions. The effectiveness of simpler recovery

strategies such as discount, partial free food or replacement or a coupon as compared

to “overkill” recovery methods can be used in structuring appropriate recovery

strategies.

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Miller, Craighead and Karwan (2000) in their empirical research “Service

recovery: a framework and empirical investigation” provides a framework for

examining the service recovery process. In the service recovery framework, the

various elements include- outcome measures related to customer satisfaction and

retention, antecedents to successful/unsuccessful recovery, the phases of recovery,

types of recovery activities and the delivery of service recovery. The study used the

Critical Incident Technology for research methodology. It is concluded from

empirical analysis that (a) successful and unsuccessful service recoveries are

characterized by very different customer outcome measures, mixes of psychological

and tangible recovery efforts and attention to operational details, and (b) the factors

that seem to matter the most (fair restitution and value-added) are very much

operational in nature.

Lewis and Clacher (2001) in their study “Service failure and recovery in UK theme

parks: the employees’ perspective” focused on the perspective of customer contact-

employees on service failure and service recovery. It is concluded that formal

understanding of service failure and recovery varied amongst the managers, but all

referred to exceptional communication and “people” skills, and they had a desire to

investigate service failures and recovery and take positive actions in the parks.

Critical incident technique was used to describe service failures and subsequent

service recoveries, both satisfactory and dissatisfactory, which were categorized in

relation to employee response to service delivery system failures, employee response

to customer needs and requests, unprompted employee actions and problem

customers. The critical incidents that were collected were subjected to the method

of sorting and analysis developed by Bitner et al (1990). It is suggested the

applicability of the critical incident method to identify service failures and associated

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recovery strategies in other service industries that involve substantive customer-

employee interaction and subjective judgement.

Lewis and Spyrakopoulos (2001) in their empirical study “Service failures and

recovery in retail banking: the customers’ perspective” assess the significance of

service failures and recovery strategies in financial services from the customers’ point

of view. The researchers identified various types of service failure and recovery

strategies with the help of critical incident technique. These were investigated further

through a survey questionnaire, to discover customer perceptions of the importance of

particular failures and the effectiveness of the service recovery strategies. The results

of the study indicated that service failures were found to be of varying importance and

different service recovery strategies more effective for particular failures. Further,

customers with long relationships with their banks were more demanding with respect

to service recovery.

Maxham III (2001) in the research paper “Service recovery‘s influence on customer

satisfaction, positive word-of –mouth, and purchase intentions” examined the effects

of service recovery on key purchase perception variables in both experimental and

field study analyses. The results of the study suggest that effective service recoveries

can enhance consumer perceptions of satisfaction, purchase intent and positive word

of mouth. Also there is not a significant difference in satisfaction and purchase intent

between groups receiving high and moderate service recoveries. The results do not

support a recovery paradox, where by post recovery satisfaction is greater that that

satisfaction prior to the service failure. It is suggested that poor service recovery

efforts may influence consumers to discontinue service with such organizations and it

may also increase a firm’s sales and administration costs associated with recruiting

new customers.

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Matillaa (2001) in the study “The effectiveness in service recovery in a multi-industry

setting” examined how two situational factors, the service type and magnitude of

failure, moderate customer responses to service failures. A 3(service type) X

2(compensation) X 2(magnitude of failure) between subjects design was used to test

the hypothesis. Subjects were exposed to a written scenario describing a service

failure with in the context of one of three service types (restaurant, hair stylist or dry-

cleaning). The findings indicated that the relative importance of the fairness

dimensions in driving service recovery satisfaction might depend on the type of

service or the failure context. It is suggested that service managers should tailor their

recovery efforts to match the customer’s perceptions of the seriousness of failure.

Customer perceptions of the magnitude of failure should then guide employee actions

in resolving the problem to the customer’s satisfaction.

Mattilab (2001) in the experimental study “The Impact of Relationship Type on

Customer Loyalty in a Context of Service Failures” examines the impact of

relationship type (true service relationship, pseudorelationship, and service encounter)

on customers’ behavioral intentions in a context of service failures. It is concluded

that customers might feel equally dissatisfied about poorly handled service recovery

regardless of the relationship type, yet their behavioral intentions might differ

depending on the closeness of the customer-provider bond. The results from the two

experiments suggest that building and maintaining close relationships with customers

are critical in case of a failed service recovery.

Michel (2001) in his research study “Analyzing service failures and recoveries: a

process approach” suggested a process approach by which not only dissatisfied or

complaining customers are surveyed but due attention is paid to a representative

sample of both satisfied and dissatisfied customers. A service blueprint approach was

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used to track the path of the customer’s service experience before asked for specific

negative incidents. A large proportion of the failure incidents reported by the

respondents did not meet the restrictive criteria of ‘critical incidents’ suggested

by Bitner et al (1990). However, the reported failure incidents were critical regarding

their impact on satisfaction, an open coding procedure was applied. He found that

process-by-process analysis reveals specific service problems and therefore helps

to manage service recoveries accordingly. An analysis of the effect of good

recoveries resulted in the recovery paradox being found in all but one process type. It

is suggested that service recovery not only involves the costs of redressing failures but

is also a powerful tool for increasing customer satisfaction.

Maxhama III and Netemeyer (2002) examined in their study “A Longitudinal Study

of Complaining Customers’ Evaluations of Multiple Service Failures and Recovery

Efforts” complaining customers’ perceptions of two service failures and recovery

efforts. The findings indicate customers reporting an unsatisfactory recovery followed

by a satisfactory recovery reported significantly higher ratings at the second post

recovery period than did customers reporting the opposite recovery sequence. The

outcome of the second recovery also demonstrated a significant influence on customer

ratings (positively if the recovery was satisfactory, negatively if the recovery was

unsatisfactory), regardless of whether the customer found the first recovery

satisfactory or unsatisfactory.

De Witt and Brady (2003) in their empirical study “Rethinking Service Recovery

Strategies-The Effect of Rapport on Consumer Responses to Service Failure”

examines the recovery benefits of fostering rapport between the service provider and

customer by conducting four independent studies test. The first study employed a

scenario based experimental design and a student sample. The second study was

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intended to assess the external validity of the Study1. The third and fourth studies

were designed to further explore some of the results found in studies 1 and 2. The

third study was intended to uncover strategies that can be used to encourage

complaint behavior under conditions of high rapport, where as the fourth study tested

whether the strategies uncovered in study 3 were viable. The findings indicate that in

addition to enhancing perceptions of service quality and customer satisfaction, rapport

can have a positive effect on the negative outcomes often associated with service

failures. For managers focused on rapport, the findings indicate that in addition to

enhancing perceptions of service quality and customer satisfaction, rapport can have a

positive effect on the negative outcomes often associated with service failures. Also,

the results suggest that consumers who have developed rapport with the service

provider are less likely to complain because they are empathic toward the situations

these individuals work under and are unwilling to possibly damage their relationship

by complaining.

Hessa Jr., Ganesan and Klein (2003) in their empirical study “Service Failure and

Recovery: The Impact of Relationship Factors on Customer Satisfaction” examined

how customer relationships either buffer or magnify the impact of service failures on

customer satisfaction. Also, how the quality of past service performance, number of

past encounters with the organization, and the customers’ expectations of relationship

continuity affect consumers’ responses to failures and recoveries. It is concluded that

customers with higher expectations of relationship continuity had lower service

recovery expectations after a service failure to a less stable cause. Both the lower

recovery expectations and the lower stability attributions were associated with greater

satisfaction with the service performance after the recovery. It is also showed that

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customer-organization relationships can help to shield a service organization from the

negative effects of failures on customer satisfaction.

Holloway and Beatty (2003) in their two research studies “Service Failure in Online

Retailing-A Recovery Opportunity” employing both qualitative and quantitative

methods with samples of online shoppers to provide an initial examination of the

service recovery management of online retailers. The results provide a typology of

online service failures and demonstrate a number of areas in which online retailers are

failing to effectively manage their service recoveries. The typology of service

failures share some consistency with Bitner et al’s classification but they mostly

differ due to the lack of human interaction, the influence of technology and other

factors unique to the online environment. It is concluded that the online retailers

are largely failing in their service recovery efforts. These ineffective service

recoveries are negatively affecting important consumer behaviors, particularly

retention.

Leal and Pereira (2003) in their empirical research “Service recovery at financial

institution” focusing the main aspects of the service recovery process after a

complaint has occurred. A specific methodology is proposed to analyse the failures

and corresponding complaints in service delivery, with the ultimate goal of

articulating internal and external measures of performance. The methodology

provides a better knowledge of the impact caused by operational factors (internal

measures) on customer perceptions (external measures), so that management

decisions can be objectively taken.

Lidén and Skålén (2003) in their research paper “The effect of service guarantees on

service recovery” focused on the risk-reducing effect of service guarantees and how

guarantees influence employee service recovery behavior. Critical incident data were

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collected using the critical incident interview technique with customers of hotels. It is

proved that the implicit guarantee may serve as a risk reducer, which contradicts and

adds to previous research because the previous research states that only the explicit

guarantee has these benefits. The results of the study suggested that service

guarantees can impact the behavior of front-line employees in the service recovery

process. Also it is indicated that the service guarantee may actually lower customer

satisfaction after an incident if the employee relies too heavily on the possibility of

compensating the customer with economic means.

Mueller, Palmer, Mack and Mc Mullan (2003) in their research paper “Service in

the restaurant industry: an American and Irish comparison of service failures and

recovery strategies” determine the most prevalent service failures and recovery

strategies used in each country. This study compares the effects of failure and

recovery strategies in the restaurant sector of two countries with very different dining

traditions- the United States and Ireland. Analysis of over 700 personal interviews

with restaurant customers shows that there is much commonality with regard to

service failures but significant differences in recovery efforts. This study also used

the same classification system of service failures as given by Bitner et al (1990)

and also used by Hoffman et al (1995). It is found that twice as many service

failures were attributed to service delivery system failures than in the studies of

Bitner et al and Hoffman et al (1995). In both countries, overcompensation methods

do not appear to influence customer repeat patronage intentions, nor do they have

significant influence on the rating of recovery effort. This study supported that simple

apologies are not enough, successful recovery strategies should be used in conjunction

with some sort of compensation- regardless of nationality and some recovery action is

much more likely to result in repeat business than no action.

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Warden, Liu, Huang and Lee (2003) extended in the Stauss and Mang model in

their study “Service failures away from home: benefits in intercultural service

encounters” by including the importance of recovery strategies, and the benefit gained

by any recovery attempt with in an intercultural service setting. A pretest, employing

the CIT, established descriptions of common service failures and recovery strategies

for the sample frame. A total of thirteen service failure incident categories and nine

categories of recovery strategies were found. They suggested to service providers that

often have contact with customers of foreign cultures need to build into their

corporate cultures not only an atmosphere of tolerance, but also a proactive behavior

towards solving service problems. When a service failure does occur, a positive

attempt at recovery will trigger a positive reaction from the consumer that has

increased benefit, surpassing intra-culture recoveries.

Craighead, Karwan and Miller (2004) in the paper “The Effects of Severity of

Failure and Customer Loyalty on Service Recovery Strategies” creates and analyzes

empirical types of service failures by using the hierarchical and non-hierarchical

cluster analysis and to gain some insight into how the failure types may require

differential treatment. The CIT was used to generate the service failures. The results

found the differences among the failures which fit together to form common

encounters and indeed the service recovery techniques varied in their effectiveness

relative to the failure types. The creation of meaningful failure types from pre-

encounter factors serves as another way to verify the importance of other studies

which have identified and studied the antecedents to service recovery but, more

importantly, offers a mechanism which then allows for a theory of “strategic fit” in

the determination of service recovery strategies.

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Cranage (2004) in the paper “Plan to do it right: and plan for recovery” presents

research results and implications in the literature for the last 15 years, and suggests

guidelines on how to make the best use of the information to develop strategies that

‘fit’ a service operation. There are numerous benefits of customer satisfaction, loyalty

and increased profits from developing strategies to prevent service failures and

strategies to successfully implement service recovery. The researcher suggested three

steps to prevent service failure are- talk to the customer; truly analyze the operation

and analyze the staff. All of this is to try to get it right the first time. If the service

failure still occurs then management should consider some pre-emptive strategies to

mitigate the negative effects of service failure.

Lewis and Mc Cann (2004) in their study “Service failure and recovery: evidence

from the hotel industry” focused on service failure and recovery in the hotel industry

in the UK. They assess the quality attributes which are important to guests when

staying in three-or-four- star hotels; the types and magnitude of service failures

experienced; the different recovery strategies used to satisfy the guests; and the

effectiveness of these strategies.

Magnini and Ford (2004) in their research paper “Service failure recovery in China”

found that in the hotel industry, exceptional service failure recovery is a key

determinant of customer satisfaction and loyalty; even across cultures. Excellent

recovery requires employees to decode emotional cues and to be empowered to offer

a customized recovery effort; these skills should be taught through service training.

Teaching these skills to Chinese hotel associates is different than teaching these skills

to associates in other countries. Service recovery training has been shown to be

effective and is a strategic necessity for guest retention and hotel profitability, but

western training programs do not take into consideration cultural differences and

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sensitivities. Hoteliers with properties in China must consider adapting their programs

to reflect Chinese cultural issues and requirements.

Mattila (2004) in the research paper “The impact of service failures on customer

loyalty: The moderating role of affective commitment” examined the moderating role

of affective commitment on post failure attitudes and loyalty intentions under two

service failure conditions: a successful and poor service recovery. The findings

indicate that emotionally – bonded customers might feel betrayed when a service

failure occurs, thus resulting in sharp decrease in post-recovery attitudes. The results

suggest that affective commitment might produce the spill-over effects of service

failures to future loyalty behaviours.

Robbins and Miller (2004) in the research paper “Considering Customer Loyalty In

Developing Service Recovery Strategies” analyze the potential for customer loyalty to

play an antecedent role in service recovery by interacting with perceptions of

unfairness to influence post-failure reactions. The Critical Incident Technique was

used to collect the data for this study. The respondents were asked about the two

service failure incidents; for the first failure they described a successful resolution and

for the second an unsuccessful resolution. They described the company, the service

failure, provided their evaluations of service recovery management and perceptions of

the fairness of interactions and outcomes for both incidents. Pre-failure variables (i.e.

customer loyalty) as well as post-failure reactions (e.g. loyalty, repatronage intentions

etc.) were also assessed. The results of the study suggested that both procedural and

distributive fairness in recovery had stronger influences on subsequent reactions of

customers with higher levels of loyalty prior to the service failure. It is found that the

effectiveness of service recovery had the strongest influence on loyal customers. It is

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also suggested that business strategies and training programs should stress the

importance of managing the fairness perceptions of loyal customers in particular.

Weber and Sparks (2004) in their study “Consumer attributions and behavioral

responses to service failures in strategic airline alliance settings” suggested that

potential problems for airlines in an alliance where their image can be negatively

affected by a service failure of a partner airline in terms of negative evaluations

leading to customer dissatisfaction, negative word-of-mouth and reduced loyalty. This

suggests that airlines involved in alliance structures need to take cognizance of the

service quality being offered by their partners. Interviews were used to determine

airline passengers’ attributions and behavior towards the various alliance entities

following a service failure and recovery.

Weun, Beatty and Jones, (2004) in their research paper “The impact of service

failure severity on service recovery evaluations and post-recovery relationships” focus

on customer reaction to a service organization’s service recovery efforts under

varying levels of service failure severity. The present paper investigated the main and

interactive effects of the severity of the service failure, along with perceptions of

interactive and distributive justice, on satisfaction with the service recovery with the

help of experimental design and stimuli. The results indicate that service failure

severity has a significant influence on satisfaction, trust, commitment and negative

word-of-mouth. In terms of interactional justice, the severity of the service failure did

not moderate the interactional justice/satisfaction relationship. In terms of the key

outcome relationship variables, the severity of the service failure moderated the

satisfaction/commitment relationship.

Bamford and Xystouri (2005) in their research paper “A case study of service failure

and recovery with in an international airline” concluded that service quality

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excellence can only be achieved through employee satisfaction, commitment and

loyalty as a result of senior management commitment, focus and drive. Also, found

that for service recovery to be effective, it must be external (to the customer) as well

as (to the organization) so that internal improvement can be ensured. Periodic review

of performances and reward schemes are considered of vital importance, to aid the co-

evolution of mutual understanding between managers and employees, and hence the

development of superior service quality.

Forbes, Kelly and Hoffman (2005) in their research paper “Typologies of e-

commerce retail failures and recovery strategies” applied CIT using 377 customer

responses to present ten e-tail failures and eleven e-tail recovery strategies used by e-

commerce service firms. The present study took the guidance from the Bitner et al,

1990 (favorable and unfavorable service encounters) and Kelly et al, 1993 (retail

failures and recoveries) for analyzing and sorting the content of the critical

incidents. It is derived that major group 3, unprompted and unsolicited action

failures did not occur in the data collected may be because of the non-human

element of the service encounter. It is concluded that the analysis of failures and

recovery strategies is beneficial to organizations as it allows management to identify

the areas of improvement valued by customers. This information can in turn be used

to minimize future mistakes, and improve the recovery efforts of the organization

through improved technology, revised policies and employee training programs

focusing on these issues.

Reynolds and Harris (2005) in their study “When service failure is not service

failure: an exploration of the forms and motives of “illegitimate” customer

complaining” explore the service encounters where in customers knowingly, and

incorrectly report service failures and their motives behind it. The qualitative method

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i.e. critical incident technique was applied in the study. It was found that (a) coding

procedures revealed four distinct forms of customer complainants –one-off

complainants, opportunistic complainants, conditioned complainants and professional

complainants. (b) six main motives for articulating fraudulent complaints –

freeloaders, fraudulent returners, fault transferors, solitary ego gains, peer-induced

esteem seekers and disruptive gains. The results of the study suggested that managers

should enforce mechanisms wherein customer complaints are monitored and tracked

in a manner that assists in the identification and challenging of re-offending

fraudulent complainers.

Youjae and Lee (2005) in their empirical research work “An Empirical Study on the

Customer Responses to Service Recovery in the context of Service Failure” examined

how customers respond to various service recoveries by investigating the moderate

role of service failure severity. The results show that under the core service failure,

high recoveries are more effective than low recoveries, where as low recoveries are as

effective as high recoveries under the peripheral service failure. The effects were

assessed in terms of customers’ intentions such as repurchase intention and word-of-

mouth communication.

Harris, Grewal, Mohr and Bernhardt (2006) in their empirical study “Consumer

responses to service recovery strategies: The moderating role of online versus offline

environment” examine the affects of on/offline medium on customer satisfaction with

service failure recovery and post purchase intentions in two different service contexts.

The data were gathered using a scenario-based experiment, constructed the scenarios

to manipulate the service medium (online versus offline) and the remedy for the

service failure (high versus low level) across the two service industries i.e. airlines

and banks. The results indicated that recovery levels have positive effects on

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satisfaction and intentions in both online and offline settings and that the on-/offline

medium moderates the relationship between the recovery level and both satisfaction

and post purchase intentions. In low recovery situations, online customers are more

satisfied and have more positive intentions than do their offline counterparts. Airline

customers were more satisfied and had more positive post purchase intentions than

did bank customers. Also, in low recovery situations, airline customers were more

satisfied and more inclined towards repurchase and positive word-of-mouth behaviors

than were bank customers.

Gupta Anil (2006) explained in his article “Regaining Customer Confidence” about

different incidents of service delivery failures, how customers react to service failure,

and regaining customer share through service recovery and how service providing

firms can build customer-driven service recovery competencies. The researcher

emphasized if firms plan service recovery mechanism, it could lead to even higher

customer satisfaction levels and have a positive influence on customer commitment,

trust, word-of-mouth and repurchase intentions.

Patterson, Cowley and Prasongsukarn (2006) in their research article “Service

failure recovery: The moderating impact of individual-level cultural value orientation

on perceptions of justice” examined the influence of customers’ cultural value

orientation (i.e. cultural values measured at the individual level, not national level)

and service recovery processes on the perception of fairness (justice) and post

recovery satisfaction in a medium contact service. To test the hypothesis three single

factor experimental designs was used. The results reveal that cultural values of

individual power distance, uncertainity avoidance and collectivism do indeed interact

with a firm’s recovery tactics to influence perceptions of fairness (justice). Finally, all

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three forms of justice (distributive, procedural, interactional) impact on overall service

recovery satisfaction.

Gountas, Ewing and Gountas (2007) conducted a study “Testing airline passengers’

responses to flight attendants’ expressive displays: The effects of positive affect”

collected 1160 useable questionnaires from the national airline passengers. They

measure the influence of service providers’ positive expressive displays on life

satisfaction, overall consumption satisfaction and intention to purchase. The findings

indicate a strong positive relationship between and with in affective displays, overall

service satisfaction and life satisfaction. The results of the study found a strong

relationship between ‘sincere or authentic’ smiles and the perception of genuine care

for the consumer. There is no significant direct, relationship between life satisfaction

and service satisfaction.

Lin, Lin and Lin (2007) investigated in their study “The Relationship between

Service Failures, Service Recovery Strategies and Behavioral Intentions in Hotel

Industry” the impact of hotel guests’ sociodemographic characteristics and their

perceptions of service recovery strategies, in explaining behavioral intentions of hotel

guests in Orlando, Florida. The results of the study showed that three dimensions of

service failure-facilities, procedure, and provider’s behaviour- were significant

explanatory variables of behavioral intentions. Also all dimensions of service

recovery strategies- correction, exceptional treatment, explanation, apologies,

redirection, and compensation and did nothing- were significant explanatory variables

of behavioral intention.

Ringberg, Odekerken – Schroder, and Christensen (2007) in their paper “A

Cultural Models Approach to Service Recovery” empirically identify three embodied

cultural models – relational, oppositional and utilitarian –that consumers apply to

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goods or service failures. They suggested that the more successful the provider is at

creating a self – relevant connection between the service and the consumer,

paradoxically, the less flexibility and control the firm has in managing consumers

during failures.

Choi and Matilla (2008) in the research paper “Perceived controllability and service

expectations: Influences on customer reactions following service failure” examines

the impact of perceived controllability over service failures and service quality

expectations on customer reactions to those failures. The experimental design method

was used to test the hypothesis. The study’s findings show that customers’ perception

of a service firm’s controllability over a service failure influences their reaction after

the incident. Customers holding higher service expectations are more likely to be

more tolerant with the service failure and that their overall satisfaction, return intent

and positive word-of-mouth are significantly higher than their counterparts with low

expectations. The findings of the study implied that when a failure is outside a firm’s

control, it is crucial to let customers know what circumstances led to the failure;

letting the customer know that the firm has taken actions to prevent a failure can

mitigate the negative effects of poor service and to reduce the potential negative

impact of inevitable service failures on business outcomes, service firms need to

enhance customer expectations.

Luria, Gal and Yagil (2009) in their research article “Employees’ Willingness to

Report Service Complaints” conducted two qualitative and a quantitative study to

examine frontline workers’ discretion about reporting customer complaints. The

qualitative studies based on critical incident technique and interviews with service

providers and reveal that service providers practice much discretion in their decision

to report formal and informal complaints and also conceptualize willingness to report

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service complaints (WRC). The quantitative study examines a preliminary WRC scale

and shows that WRC levels are associated with measures of organizational citizenship

behaviour, service climate and empowerment.

Mc Collough (2009) in the paper “The Recovery Paradox: The effect of Recovery

Performance and Service Failure severity on post-recovery customer satisfaction”

investigates the recovery paradox, the proposition that superior recovery can leave the

customer as satisfied, if not more satisfied, than if nothing had gone wrong by

examining the impact of service failure severity and the recovery performance on

post-recovery satisfaction. The findings of the study showed that for a recovery

paradox to emerge the service failure severity must be very modest and the recovery

effort superior. The relative low level of harm caused by the failure and the relatively

high recovery performance necessary is surprising and indicates that the recovery

paradox may be rather limited phenomenon.

Mostert, Meyer and Rensburg (2009) in their study “The influence of service

failure and service recovery on airline passengers’ relationships with domestic

airlines: an exploratory study” investigates the effect of service failures and an

airline’s service recovery efforts on their customer relationships and future patronage

of the airline. A non-probability convenience sampling method was used to survey

passengers of domestic airlines in South Africa. A self-administered questionnaire

was randomly distributed by trained fieldworkers to passengers at the check-in

counters of the various domestic airlines at airport. The findings indicate that

customer satisfaction with an airline’s service recovery efforts significantly influences

their relationship with the airline as well as their future patronage of the airline.

Dissatisfied respondents indicated that their relationship with the airline was

weakened or broken and that they would fly less frequently or never again with the

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airline following the service failure. Satisfied respondents’ relationships with the

airline were unchanged or strengthened, and they flew with the airline all the time or

as frequently as before the service failure.

Malhotra and Malhotra (2011) attempts to study in their paper “Evaluating

Customer Information Breaches as Service Failures: An Event Study Approach”

associated breach reports with the decline in market value of firms using an event

study. Due to the greater potential of customer backlash, negative publicity and

liability risk, managers must view customer information breaches as service failures

rather than as information system failures. Employing established service failure

recovery strategies may allow firms to quickly and proactively address customer

privacy concerns and thereby mitigate negative market reaction to information

breaches.

3.2.1 PERCEIVED JUSTICE

Spreng and Mackoy (1996) in their exploratory study “An Empirical Examination of

a Model of Perceived Service Quality and Satisfaction” assess the distinction between

perceived service quality and satisfaction and examine the impact of different

standards of comparison. The results of the study indicated that service quality and

satisfaction, in a confirmatory factor analysis, are distinct and structural equations

modeling showed that they have different antecedents. They also noted that

expectations have a negative effect on satisfaction, through disconfirmation, but a

positive effect on both satisfaction and perceived service quality, through perceived

performance. A key determinant of both satisfaction and service quality is meeting

customers’ desires.

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Blodgett, Hill and Tax (1997) in their experimental study “The Effects of

Distributive, Procedural, and Interactional Justice on Post complaint Behavior”

examined the effects of distributive, interactional and procedural justice on

complainants’ subsequent repatronage and negative word of mouth intentions. The

results indicated that complainants who experience higher levels of distributive and

interactional justice are more likely to repatronize the retailer and are less likely to

engage in negative word-of-mouth behavior (and vice-versa). On the other hand,

procedural justice or timeliness had no effect on subjects’ repatronage intentions

or on their negative word-of-mouth intentions. Also, the higher levels of

interactional justice can compensate for lower levels of distributive justice. The

findings of the study points to the importance of training retail employees how to

respond to customer complaints and retailers that focus on interactional issues will

have the greatest chances of building long-term relationships with their customers.

Maxhamb III and Netemeyer (2002) in their paper “Modeling customer perceptions

of complaint handling overtime: the effects of perceived justice on satisfaction and

intent” suggested that procedural and interactional justice are more influential in

forming overall firm satisfaction than distributive justice. Retailers offering refunds

and discounts (i.e. distributive justice) following product or service failures can likely

increase satisfaction with recoveries and indirectly affect WOM intent. Also, retailers

offering procedural and interactional justice following failures may increase overall

firm satisfaction and indirectly affect purchase intent. It is also suggested that

distributive justice is more pronounced in forming satisfaction with recovery

perceptions among durable good complainants than service complainants, and

interactional justice is more influential in forming satisfaction with recovery

perceptions among service complainants than durable good complainants.

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Mc Coll-Kennedy and Sparks (2003) in their study “Application of Fairness Theory

to Service Failures and Service Recovery” to understand customer responses to

service failures and recovery presented a theoretical framework for studying and

managing service recovery and provided demonstrated support for the conceptual

framework through the results of the five focus groups. It is concluded that service

failures can be triggered by events from a range of sources, including the following

four major areas: (a) problems with the service itself, (b) problems associated with the

service provider, (c) problems outside the service provider’s control, and (d) problems

related to the customer. Also it is clear from the focus groups that when customers

experience a negative event (service failure), they commence an assessment of the

situation, making attributions as to whether the service provider could (in terms of

conduct) and should (in terms of moral principles) have done something more to

remedy the situation. The key managerial implication is that to manage service failure

situations, service organizations need to have knowledge of the range of solutions that

(a) possible, (b) practical, (c) fair, and (d) understood by customers to be all three of

these things.

Maxham III and Netemeyer (2003) in the research paper “Firms Reap What They

Sow: The Effects of Shared Values and Perceived Organizational Justice on

Customers’ Evaluations of Complaint Handling” examined how employees’

perceptions of shared values and organizational justice can stimulate customer-

directed extra-role behaviors when handling complaints and also investigated how

these extra-role behaviors affect customers’ perceptions of justice, satisfaction, word

of mouth and purchase intent. The results of the study are- customer-directed extra-

role behaviors had strong effects on customers’ perceptions of interactional

justice, procedural justice and distributive justice, customer ratings of

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distributive justice affected all outcome variables (i.e. satisfaction with recovery,

overall firm satisfaction, purchase intent and word of mouth), procedural justice

affected satisfaction with recovery, overall firm satisfaction and word of mouth

and interactional justice affected overall firm satisfaction and purchase intent.

Extra-role behaviors affected all dimensions of customer justice which shows that

extra-role behaviors indirectly and significantly affect customer outcomes.

Yim, Gu, Chan, and Tse (2003) in their empirical study “Justice-Based Service

Recovery Expectations: Measurement and Antecedents” examine the measurement

properties of an equity-based expectancy-disconfirmation framework in service

recovery evaluation and to test hypothesis regarding potential antecedents to

consumer normative recovery expectations. The results showed that customers form

justice-based normative recovery expectations and use them as reference standards in

evaluating recovery performance of the service provider. Also, recovery

expectations of distributive justice are more strongly related to the recovery

disconfirmation judgment than that of procedural/interactional justice. All three

tested antecedents-magnitude of service failure, switching cost, and length of the

customer-organization relationship- are found to have either a direct or an interactive

effect on expectations of distributive justice and procedural/interactional justice. The

results of the study confirm the important role of normative equity-based expectations

in service recovery evaluation. To institute effective programs of service recovery,

managers need to know what customers expect in order to be satisfied. They should

strive to offer high recovery performance that meets or exceeds customer

expectations.

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Mattila and Patterson (2004) in their experimental study “Service Recovery and

Fairness Perceptions in Collectivist and Individualistic Contexts” contrasts the impact

of two recovery attributes (compensation and exceptional) on customers’ post

recovery perceptions in a cross-cultural context (East-Asia versus United States).

They suggested that offering compensation is particularly effective in restoring the

sense of justice among American consumers. Offering an explanation for the failure

had a positive impact on the customer perceptions regardless of the customers’

cultural orientation. It is also found that perceived fairness is directly linked to post

recovery satisfaction. The results clearly showed that firms (domestic and

international) should consider ways to restore consumers’ sense of justice

considerations- distributive and interactional, as each affects post recovery

satisfaction, irrespective of culture.

Kau and Wan-Yiun Loh (2006) in the study “The effects of service recovery on

consumer satisfaction: a comparison between complainants and non-complainants”

examines the perception of “justice” in service recovery and how it affects the level of

satisfaction and behavioral outcomes. Also explores whether the “recovery paradox”

exists. The researchers proposed model in which customers in a service setting can be

broadly divide into two distinct classes: those who complain (complainants) and those

who do not complain (non-complainants). Of the non-complainants, they are either

satisfied with the service or dissatisfied with the service provider but did not lodge a

complaint. Of the complainants, they are either satisfied with the service recovery

provided or dissatisfied. These four types of consumers may experience different

service encounters and would be expected to display different levels of satisfaction

with the service provider. This satisfaction or dissatisfaction would lead to different

behavioral outcomes. The findings of the study indicated that distributive justice is

156

significantly related to satisfaction with service recovery. Similarly, procedural

justice also played a significant role in influencing the level of satisfaction with

service recovery. It is suggested that service recovery should not be neglected and

bad service recovery efforts might lead to more detrimental consequences such as loss

of trust and bad publicity through negative word-of-mouth communications. Finally,

the lack of support of the “recovery paradox” effect suggests that successful service

recovery alone could not bring customer satisfaction to pre-service failure types.

Thus, it is imperative for service providers to examine their service operations to

identify potential pitfalls with the objective of providing fail-proof service at the first

instant.

157

Fig 3.1 The Research Model

158

Shapiro and Nieman-Gonder (2006) in their scenario-based experimental study

“Effect of communication mode in justice-based service recovery” investigate the

effects of organizational justice-based recovery strategies and the mode of

communication used following a service failure on key organizational variables

including customer satisfaction, loyalty and complaining behavior. The scenario

manipulated the type of organizational justice-based recovery strategy (distributive,

interactional, both) and the mode of communication (in-person, toll-free number, e-

mail) used during the recovery process. The findings of the study suggest no

difference between the effect of justice-based strategies on overall customer

satisfaction or loyalty. Customers were more likely to engage in informal negative

word-of-mouth behaviour than formally complaining to the company. It is suggested

that employees close to the customer are vital to service recovery because they are

often the first to know about problems. These employees must be trained in

communication, creative thinking and decision-making skills that allow them to deal

with customer complaints.

Hessb Jr., Ganesan and Klein (2007) in their research paper “Interactional service

failures in a pseudorelationship: The role of organizational attributions” investigates

interactional service failures with in a pseudorelationship, a context in which

customers interact with different frontline employees in multiple settings across

service encounters. The study establishes the globality attributions after a service

failure in a pseudorelationship are a major element of dissatisfaction with the

organization. The results show a strong relationship between dissatisfaction with the

employee and organization, as expected, but that customers in a pseudorelationship

distinguish between the employee and the organization in their responses to

interactional failures. Managers might consider communications intended to reduce

159

those attributions following a failure. They should note the crossover effect, in which

a good record of core service helps to mitigate the effects of an interactional failure.

Excellent service on one dimension may contribute to the organization’s stereotype as

a high quality service provider, creating some synergy between the core and

interactional elements of service.

Kim, Kim and Kim (2009) in their study “ The effects of perceived justice on

recovery satisfaction, trust, word of mouth and revisit intention in upscale hotels”

assesses the relative influences of justices on customer satisfaction with service

recovery and to examine the relationship between recovery satisfaction and

subsequent customer relationships; trust, word of mouth and revisit intention. The

results showed that the effect of Distributive Justice (DJ) on satisfaction with

service recovery was stronger than those of Procedural Justice (PJ) and

Interactional Justice (IJ). Since DJ, PJ and IJ have significant effects on trust,

word of mouth and revisit intention through recovery satisfaction, recovery

satisfaction was found to be an important mediating variable.

Chang and Chang (2010) in their paper “Does service recovery affect satisfaction

and customer loyalty? An empirical study of airline services” investigates the

relationships among service recovery, recovery satisfaction, overall customer

satisfaction and customer loyalty in airline services using structural equation models.

It is found that both interactional and procedural justice have a significant effect

on recovery satisfaction. Overall satisfaction mediates the relationship between

recovery satisfaction and loyalty.

160

Nikbin, Ismail, Marimuthu and Jalalkamali (2010) in their research paper

“Perceived Justice in Service Recovery and Recovery Satisfaction: The Moderating

Role of Corporate Image” assess the influence of perceived justice on recovery

satisfaction and to examine the moderating role of corporate image in the relationship

between perceived justice and recovery satisfaction. Data was gathered by means of

survey from Iran Air customers who experienced a service failure with in last year. It

was found that distributive and interactional justices have significant effects on

recovery satisfaction. The effects of distributive justice on recovery satisfaction

were stronger than interactional justice. Also, corporate image plays a moderating

role between perceived justice and recovery satisfaction in the distributive and

interactional justice dimensions.

DISSERTATION

McCollough (1995) in his dissertation “The Recovery paradox: A conceptual model

and empirical investigation of customer satisfaction and service quality attitudes after

service failure and recovery” explores the nature of post-recovery customer

satisfaction and service quality evaluations (where recovery refers to the efforts of the

service provider to turn customer dissatisfaction into satisfaction by addressing the

customer’s service problem). The researcher develops a general model of customer

satisfaction after recovery which incorporates the disconfirmation, service quality,

attribution and the justice literatures. A scenario-based experimental approach was

used to test hypothesis and data was collected by surveying airline passengers in an

airport. This research also demonstrated that recovery can partially mitigate the

dissatisfaction which results from service failures. The results of this research provide

overall support for the general model of recovery, with a few notable exceptions. The

results indicated that given failure, satisfaction was very strongly related to the

161

superiority of the recovery effort. All three experiments in this study showed that the

higher the recovery, the higher the satisfaction evaluation and service quality

attitudes. The general model of recovery predicted that distribution justice would

have a greater effect on satisfaction, while procedural justice would have a

greater effect on service quality. The findings show that procedural justice was the

most important predictor of satisfaction might be due, in part, to the inability of

the service provider to fully recover in the situation depicted. It is suggested that

service providers will find that the most direct and least problematic way for them to

enhance satisfaction judgements, service quality attitudes and repurchase intentions is

through improving service reliability.

Ma, Jun (2007) in his study “Attribution, Expectation, and Recovery: An Integrated

Model of Service Failure and Recovery” integrated attribution theory, expectancy-

disconfirmation paradigm, and justice theory into a model of customer satisfaction

with failure and recovery encounters. Also, the relationship between attribution,

recovery expectations and perceived justice toward service encounters is empirically

tested. It provides answers for questions regarding how consumers make a causal

attribution, how their causal attributions influence their reactions to service failures,

and how their causal attributions affect the effect of recoveries on perceived justice

and service encounter satisfaction. The results of the study reveal that between the

two dimensions of perceived justice (distributive justice and procedural justice)

distributive justice plays a salient role in the formation of recovery expectations. It is

derived that when a procedural justice is violated, it leads to a low level of distributive

justice and further a high level of recovery expectations. Further, the results suggest

that the more attributes a recovery strategy contained, the higher the evaluation of

procedural justice and service encounter satisfaction will be. The significant

162

implication of this study is that offering consumers more than what they expect can

delight consumers and make them more satisfied. Matching consumer needs both

economically and psychologically elevates consumer perceived justice and service

encounter satisfaction.

Weng, Hua-Hung (Robin) (2009) in the dissertation “Service Recovery: Trend, Path

Model, and Cultural Comparison” studies the trends of service recovery practice over

the past decade, establishes a service recovery model, and compares the cultural

differences using it. Comparing the results from 2000 and 2008, the study finds

decreased impact on customer satisfaction and loyalty over time, suggesting that the

recovery practice has changed from order winner to order qualifier. Based on Justice

Theory, a new service recovery model is established in this study. This new model

suggests two insights on service recovery. First, process and outcome satisfactions are

considered separately. Second, Interactional Justice, regarded as service encounter,

has a direct impact on the other two justice measure and influences satisfaction

indirectly through them.

163

3.3 HIGHLIGHTS OF THE PRESENT STUDY

The main issues addressed in the present study are:-

1. It attempts to clarify the concept of service encounter, service failure and

service recovery by surveying the available literature.

2. It makes the use of CIT to identify the service failures that happened with

airline passengers while travelling in domestic sectors of India.

3. It also tries to identify the recovery actions taken by the airline companies

after service failure and their effect on satisfaction of passengers.

4. It makes use of survey technique to study the airline passenger’s complaint

intentions and perceived justice and their effect on satisfaction.

5. It also studies the level of seriousness of airline passenger’s towards service

failures, their frequency of encountering these failures and the effect of service

failures on their satisfaction.

6. It further, consolidates the research available in the field of service failures

and recoveries.

164

RESEARCH GAP

From the detailed review of literature it is found that researchers study the service

failures and recovery strategies from the customer’s perspective (Bitner et al, 1990;

Bejou et al, 1996; Smith et al, 1999; Lewis et al, 2001; Ofir et al, 2001; Mueller et al,

2003; Chung-Herrera, 2004; Bamford et al, 2005; Harris et al, 2006; Gountas et al,

2007; Choi et al, 2008) in various service sectors (airlines, hotels, restaurants, public

transport services, cruises, theme parks, retail banking), employees’ perspective

(Bitner, 1990; Bitner et al, 1994; Mohr et al, 1995; Hocutt et al, 1998; Lewis and

Clacher,2001; Chung-Herrera, 2004; Luria et al, 2009 ), other customers’ perspective

(Grove, 1997); servicescape failures (Bitner, 1992; Hoffman et al, 2003), self-service

technology failures (Meuter at al, 2000), e-commerce failures and online failures

(Tyrrell, 2004, Forbes et al, 2005, Holloway et al, 2003, 2008; Harris et al, 2006),

retail failures and recoveries (Kelly et al, 1993). It is derived from the literature that

till date their exists no study that attempts to study the customer’s perspective of

service failures and recovery actions undertaken by the airlines operating in domestic

sectors of India and their effect on customer satisfaction indicating the gap in existing

literature. The findings of the study shall fill the gap in the existing literature. Airline

companies shall be able to use the findings by knowing the passenger’s perspective of

service failure and recovery issues. The findings would help managers to improve the

quality of services to customers.

165

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4.1 RESEARCH PURPOSE

The primary focus of this research is to study the service failures and recovery

strategies made by the airlines, providing services in domestic sectors of India, to

overcome the various failures and their effect on the customer’s overall satisfaction.

The analysis of service failures and service recoveries is beneficial to service

organizations as it allows management to identify and rectify common failure

situations (Hoffman, Kelly and Rotalsky, 1995).

Previous research has also supported that when consumers are offered an apology or

are provided with the opportunity to express their concerns to a service representative

those perceptions of satisfaction and fairness are enhanced, particularly when

recovery outcomes are favourable. There has been consistently found a relationship

between satisfaction and repurchase intentions, satisfaction and word of mouth

(Spreng, Harrell and Mackoy, 1995).

4.2 RESEARCH OBJECTIVES

CHAPTER-4

RESEARCH DESIGN AND METHODOLOGY

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The main objectives of the study are:

O1: To study the various types of service failures and their effect on customer’s

satisfaction in aviation industry.

O2: To study the various coping strategies undertaken by the airlines to overcome

the service failures.

O3: To make an impact assessment of recovery efforts in enhancing the customer’s

satisfaction.

4.3 RESEARCH HYPOTHESIS

H1: Service failures have negative effect on customer’s overall satisfaction.

H2: Recovery efforts have a positive role in enhancing customer’s satisfaction

levels.

4.4 RESEARCH DESIGN

It specifies the methods and procedures for conducting a particular study. According

to Green and Tull (1970), a research design is the specification of methods and

procedures for acquiring the information needed. It is the overall operational pattern

or framework of the project that stipulates what information is to be collected, from

which sources and by what procedures.

In simple terms research design is the detailed blueprint used to guide a research study

towards its objectives (Aaker, Kumar and Day, 2001). One of the most significant

decision as a part of research design is the choice of research approach, because it

determines how the information will be obtained. In the present study personal

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interviews were conducted with the help of a questionnaire for Study I and Survey

Research Approach was used for Study II to meet the objectives of the research.

4.5 RESEARCH METHODS

The research uses primary data to address the research objectives. This study uses

both the qualitative and quantitative methods of primary data collection. Two pilot

studies were conducted for Study1 and Study2. The first pilot study was conducted to

collect satisfying or dissatisfying incidents that were encountered with the airline

passengers regarding the services provided by airlines in the domestic sectors in India.

A set of six questions was framed in the form of questionnaire to describe the whole

incident in case the respondent missed some information to narrate. A total of 20

respondents were approached and 28 incidents were collected using personal

interview method. Initially, a voice recorder was used to record the incident described

by the respondents for getting original data that saves time of the respondent and the

researcher, then the incident was written on the paper to derive the information from

the dissatisfying incidents. But this method of collecting incident is not convenient to

the respondents because of privacy issue, as such, only personal interviews were

conducted and the information shared by the respondent was written on the paper.

Finally, Study 1 was conducted and 338 dissatisfying incidents were collected using

critical incident technique.

After sorting these incidents, twenty-six service failures were identified that had

happened with airline customers (passengers). Second pilot study was conducted with

20 respondents using a questionnaire to insure that there were no errors in the

questionnaire and to prevent misinterpretation of questions and to find out time taken

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by the respondent to fill a questionnaire and whether filling up the questionnaire was

easy or not? It was found that the respondents were comfortable to fill up the

questionnaire and it took approximately fifteen minutes to fill the questionnaire.

4.5.1 SAMPLING

The process of sampling forms a very important part of the research process. The

basic idea behind sampling is that by selecting some of the elements in a population,

conclusions can be drawn about the entire population. In other words, the process of

sampling involves any procedure using a small number of items or parts of the whole

population to make conclusions regarding the whole population (Zikmund, 2007). The

sampling methods are broadly classified as either probability sampling or non-

probability sampling.

In the first part of the study where the objective was to identify the various types of

service failures encountered, random sampling method was used. Previous studies like

Bitner, Booms and Tetreault (1990) collected 700 incidents (satisfactory and

unsatisfactory) from customers of airlines (163), restaurant (356) and hotel (180);

Hoffman, Kelly and Rotalsky (1995) collected 373 incidents from customers of

restaurants; Kivela and Chu (2001) collected favourable and unfavourable service

encounters from 417 customers of restaurants; Chung-Herrera, Goldschmidt and

Hoffman (2004) collected customer-reported incidents and employee-reported

incidents; Forbes, Kelly and Hoffman (2005) applied CIT using 377 customer

responses to present ten e-tail failures and eleven e-tail recovery strategies used by e-

commerce service firms. Keeping in view the previous studies, the present study

collected 338 dissatisfying incidents from 200 respondents and derived the twenty-six

service failures from these incidents and classified according to Bitner, Booms and

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Tetreault (1990) classification by type of incident outcome which became the base for

Study II.

In Study II, the stratified sampling method was employed. This data collection

method, a process of segregating a population into relevant mutually exclusive groups

followed by random selection of subjects from within each stratum, ensured a good

cross-section of the population with adequate representation for strata with fewer

members.

The population is stratified on the basis of type of carrier. Accordingly, in Apr-Jun,

2008, the market share (domestic) of full service carrier and low cost carrier was

36.5% and 63.5% and in the year 2010, it was 34.8% and 65.1% respectively. For

data collection, the market share of the airlines is considered (irrespective of the

airline) through survey method. A total of 305 (or 61%) of the 500 distributed

questionnaires were sufficiently completed and returned by respondents. Out of which

20.98% (64) of the respondents didn’t mention the name of the airline. The response

percentage of respondents is 26.89% (82) and 52.13% (159) of full service carrier and

low cost carrier respectively.

4.6 INSTRUMENT DEVELOPMENT

The whole study is divided into two- Study I and Study II. The study I became the

basis for study II.

STUDY I

The first questionnaire developed was used to identify the various types of service

failures encountered by the customers (passengers) of airlines operating in domestic

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sectors of India only by using Critical Incident Technique (CIT) (Flangan, 1954 and

Booms, Bitner and Tetreault, 1990).

The survey instrument is self-administered and consists of two sections. The questions

in the first section are about demographic profile of the respondents like gender, age,

income, occupation and belong to city & state. In the second section, respondents

were asked about an incident that stands out in their mind as either satisfying/positive

or dissatisfying/negative experience with the airline in domestic sectors of India

during the last five years of their travel in domestic sectors of India only. The

following questions were asked to all the respondents and answers were written down

on the paper attached with the questionnaire as:

• Was this a satisfying/dissatisfying experience?

• Please describe the circumstances leading up to this incident.

• Describe what happened during the incident. What specific details do you

recall that made this experience memorable for you?

• What was the outcome of the incident?

• How could this experience have been improved (if at all)?

• Did you complain to the organization about this incident? If yes, how did you

complain? If not, why not?

Critical Incident Technique (CIT) – Critical Incident Technique is a qualitative

interview procedure in which customers are asked to provide verbatim stories about

satisfying and dissatisfying service encounters they have experienced. The critical

incident technique (CIT) in its original conception consisted of “….a set of

procedures for collecting direct observations of human behaviour in such a way as to

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facilitate their potential usefulness in solving practical problems and developing broad

psychological principles” (Flanagan, 1954, pp. 327-358). The use of this technique in

various services like hotels, restaurants, airlines, amusement parks, automotive

repairs, retailing, banking, cable television, public transportation and education has

been reported. The primary research objectives of using this technique are-

1. To identify ‘best practices’ at transaction level.

2. To identify customer requirements as input for quantitative studies.

3. To identify common service failure points.

4. To identify systematic strengths and weaknesses in customer-contact services.

(Zeithaml, Gremler, Bitner and Pandit, 2008).

STUDY II

Study II consists of two parts. Part I of the study includes demographic profile of the

respondents like gender, age (in years), Income (in Rupees, approx. per year), Travel

frequency by air (in a year), Travel purpose and preference of the carrier. On the basis

of study I, 26 service failures were identified and also defined under the classification

by type of incident outcome given by Bitner, Booms and Tetreault (1990). Bitner et al

classified the incident outcomes into three major groups - Group1 is Employee

Response to Service Delivery System Failures, Group 2 is Employee Response to

Customer Needs and Requests and Group 3 is Unprompted and Unsolicited Employee

Actions. With in three major groups, a total of 12 categories were developed- three in

Group1, four in Group 2 and five in Group 3. The present study defined the twenty-

six identified service failures into sub- groups.

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Six service failures are included in sub group G1A, Response to unavailable service,

four service failures are included in sub group G1B, Response to unreasonably slow

service, six service failures are in sub group G1C Response to other core service

failures, one service failure in sub group G2A, Response to special need customers,

two service failures are included in sub group G2B, Response to customer

preferences, one service failure in sub group G2C, Response to admitted customer

error, one service failure in sub group G2D, Response to potentially disruptive others,

one service failure included in sub group G3A, Attention paid to customer, two

service failures are included in sub group G3B, Truly out-of-the-ordinary employee

behaviour, one service failure in sub group G3C, Employee behaviour in the context

of cultural norms and one service failure is included in sub group G3D Gestalt

Evaluation. There is no service failure incident outcome that falls in sub group G3E,

Performance under Adverse Circumstances.

Respondents were asked about the level of seriousness of these 26 service failures

(rated on 5-point Likert scale i.e. 1 being not at all serious and 5 being very serious),

how often they encountered with these failures in domestic sectors (after 2000) (rated

on 5- point Likert scale i.e. 1 being never and 5 being always) and whether these 26

service failures effect their satisfaction level (rated on 5- point Likert scale i.e. 1 being

strongly disagree and 5 being strongly agree).

The part II of the questionnaire consists of a precise description about the

respondents’ latest dissatisfying /negative domestic air travel experience. Then, 10-

items of consumer complaint behaviour intentions were measured on 6-point scale 1

being least likely to 6 being most likely taken from Singh, 1988. Respondent’s

opinion about the 10 recovery actions were taken, what recovery actions were taken

by the airline (Lewis and Mc Cann, 2004) and what they were expecting from the

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airline. 4-items of distributive justice, 4-items of procedural justice and 4-items of

interactional justice were asked to the respondents rated on 7-point Likert scale i.e. 1

being very strongly disagree and 7 being very strongly agree (Maxham III and

Netemeyer, 2003). 2-items of overall airline satisfaction and 3-items of satisfaction

with recovery were rated by the respondents on 7-point scale i.e. 1 being very strongly

disagree and 7 being very strongly agree (Maxham III and Netemeyer, 2002). Finally

the respondents were asked about the satisfaction with the overall quality of the

airline rated on 7-point Likert scale i.e. 1 being very dissatisfied and 7 being very

satisfied.

4.7 STATISTICAL TECHNIQUES USED

Research uses primary data to address the research objectives and test the hypothesis

developed. Study uses both the qualitative and quantitative methods for primary data

collection.

4.7.1 CRITICAL INCIDENT TECHNIQUE

A critical incident is defined as the confrontation of a group leader with one or more

members, in which an explicit or implicit opinion, decision or action is demanded of

him. The word critical incident probably communicates a common meaning to a great

many people. One would expect them to have occurred quite often in psychological

literature, particularly in those situations where selective observations were involved.

The only systematic use of the critical – incident technique was developed by John C.

Flanagan and first reported in the Psychological Bulletin (1954). The summary and

conclusions from his review article follow.

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This review has described the development of a method of studying activity

requirements called the critical incident technique. The technique grew out of studies

carried out in the Aviation Psychology Program of the Army Air Force in World War

II. The success of the method in analysing such activities as combat leadership and

disorientation in pilots resulted in its extension and further development after the war.

This developmental work has been carried out primarily at the American Institute for

Research and the University of Pittsburgh. The reports of this work are previewed

briefly.

The five steps included in the critical incident procedure that are most commonly used

at present are as under-

a.) Determination of the general aim of the activity. This general aim should be a

brief statement obtained from the authorities in the field which expresses in

simple terms those objectives to which most people would agree.

b.) Development of plans and specifications for collecting factual incidents

regarding the activity. The instructions to the persons are to report their

observations, need to be specific as possible with respect to the standards to be

used in evaluating and classifying the behaviour observed.

c.) Collection of the data. The incident may be reported in an interview or written

by the observer himself. In either case it is essential that the reporting be

objective and includes all relevant details.

d.) Analysis of the data. The purpose of this analysis is to summarize and describe

the data in an efficient manner so that it can be effectively used for various

practical purposes. It is not usually possible to obtain as much objectivity in

this step as in the preceding one.

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e.) Interpretation and reporting of the statement of the requirements of the

activity. The possible biases and implications of decisions and procedures

made in each of the four previous steps should be clearly reported. The

researcher is responsible for pointing out not only the limitations but also the

degree of credibility and the value of the final results obtained.

It should be noted that the critical incident technique is very flexible and the

principles underlying it have many types of applications. Its two basic principles may

be summarized as follows-

a.) reporting of facts regarding behaviour is preferable to the collection of

interpretations, ratings and opinions based on general impressions;

b.) reporting should be limited to those behaviours which, according to competent

observers, make a significant contribution to the activity.

It should be emphasized that critical incidents represent only raw data and do not

automatically provide solutions to problems. However, a procedure which assists in

collecting representative samples of data that are directly relevant to important

problems such as establishing standards, determining requirements, or evaluating

results should have wide applicability.

The applications of the critical incident technique which have been made to date are

discussed under the following headings: a.) measures of typical performance

(criteria); b.) measures of proficiency (standard samples); c.) training; d.) selection

and classification; e.) job design and purification; f.) operating procedures; g.)

equipment design; h.) motivation and leadership (attitudes); i.) counselling and

psychotherapy.

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In summary, the critical incident technique, rather than collecting opinions, and

estimates, obtains a record of specific behaviours from those in the best position to

make the necessary observations and evaluations. The collection and tabulation of

these observations make it possible to formulate the critical requirements of an

activity. A list of critical behaviours provides a sound basis for making inferences as

to requirements in terms of aptitudes, training, and other characteristics. It is believed

that progress has been made in the development of procedures for determining

activity requirements with objectivity and precision in terms of well defined and

general psychological categories. Much remains to be done. It is hoped that the

critical incident technique and related developments will provide a stable foundation

for procedures in many areas of psychology. (pp. 354-355).

Since 1954, no additional review has been made of the critical incident technique as

Flanagan developed it. Its use has been primarily in military-related studies.

Pigors and Pigors (1965) developed the Incident Process, a five step method for the

purpose of improving decision making and leadership skills in industrial relations.

The five steps or phases are : 1.) Studying an incident; 2.) Getting information about

facts; 3.) Stating the Immediate Issue- or hub of a problem; 4.) Deciding this issue;

and 5.) Thinking about the case as a whole, to answer the practical questions: What

Can We Learn From It? (pp. 2-3)

The data collected through the measurement instruments was subjected to a number of

statistical tools and techniques. In the first stage, a detailed descriptive analysis has

been done. Descriptive analysis refers to the transformation of raw data into a form

that will make them easy to understand and interpret. In addition to the descriptive

analysis, this research uses statistical techniques as suggested by Zikmund (2007)

keeping in view

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1. Type of question to be answered

2. Number of variables

3. Scale of Measurement

This research uses a combination of univariate, bivariate and multivariate data

analysis techniques. The following bivariate analysis technique has been used-

4.7.2 ANALYSIS OF VARIANCE (ANOVA)

Analysis of Variance is a statistical method used to compare two or more means. It is

used to test general rather than specific differences among means. This section shows

how ANOVA can be used to analyze a one-factor between subjects design. The null

hypothesis tested by ANOVA is that the population means for all conditions are the

same. This can be expressed as follows:

H0: µ1= µ2=….. µk

Where H0 is the null hypothesis and k is the number of conditions.

If the null hypothesis is rejected, then it can be concluded that at least one of the

population means is different from at least one other population means.

Analysis of Variance is a method for testing differences among means by analyzing

variance. The test is based on two estimates of the population variance (σ2). One

estimate is called the Mean Square Error (MSE) and is based on differences among

scores within the groups. MSE estimates σ2 regardless of whether the null hypothesis

is true (the population means are equal). The second estimate is called the Mean

Square Between (MSB) and is based on differences among the sample means. MSB

only estimates σ2 if the population means are equal. If the population means are not

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equal, then MSB estimates a quantity larger than σ2. Therefore, if the MSB is much

larger than the MSE, then the population means are unlikely to be equal. On the other

hand, if the MSB is about the same as MSE, then the data are consistent with the

hypothesis that the population means are equal.

Before proceeding with the calculation of MSE and MSB, it is important to consider

the assumptions made by ANOVA:

1. The populations have the same variance. This assumption is called the

assumption of homogeneity of variance.

2. The populations are normally distributed.

3. Each value is sampled independently from each other value. This

assumption requires that each subject provide only one value. If a

subject provides two scores, then the value are not independent.

These assumptions are the same as for a t test of differences between groups except

that it applies to two or more groups, not just to two groups.

Computing MSE

Recall that the assumption of homogeneity of variance states that the variance with in

each of the populations (σ2) is the same. This variance, σ2, is the quantity estimated by

MSE and is computed as the mean of the sample variances.

Computing MSB

The formula for MSB is based on the fact that the variance of the sampling

distribution of the mean is

σ2

σ2M = ―

n

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where n is the sample size. Rearranging this formula we have

σ2 = n σ2M

therefore, if we knew the variance of the sampling distribution of the mean, we could

compute σ2 by multiplying by n, although, we do not know the variance of the

sampling distribution of the mean, we can estimate it with the variance of the sample

means.

To sum up these steps:

1. Compute the means.

2. Compute the variance of the means.

3. Multiply by the variance of the means by n.

Comparing MSE and MSB

The critical step in an ANOVA is comparing MSE and MSB. Since MSB estimates a

larger quantity than MSE only when the population means are not equal, a finding of

a larger MSB than an MSE is a sign that the population means are not equal. But since

MSB could be larger than MSE by chance even if the population means are equal,

MSB must be much larger than MSE in order to justify the conclusion that the

population means differ. But how larger must MSB be? Is that difference big enough?

To answer, we would need to know the probability of getting this big a difference or a

bigger difference between if the population means were all equal. The mathematics

necessary to answer this question were worked out by the statistician R. Fisher.

Although Fisher’s original formulation took a slightly different form, the standard

method for determining the probability is based on the ratio of MSB to MSE. This

ratio is named after Fisher and is called the F ratio.

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The shape of the F distribution depends on the sample size. More precisely, it depends

on two degrees of freedom (df) parameters: one for the numerator (MSB) and one for

the denominator (MSE). Recall that the degree of freedom for an estimate of variance

is equal to the number of scores minus one. Since the MSB is the variance of k means,

it has k-1 df. The MSE is an average of k variances each with n-1 df. Therefore the df

for MSE is k(n-1)= N-k where N is the total number of scores, n is the number in each

group and k is the number of groups. To summarize:

dfnumerator = k-1

dfdenominator = N-k

Tukey Honestly Significant Difference (HSD) Test

Many experiments are designed to compare more than two conditions. An obvious

way to proceed would be to do a t-test of the difference between each group mean and

each other group mean. The problem with this approach is that the possibility of

making a Type I error increases. Therefore, if one were using the 0.05 significance

level, the probability that one would make a Type I error on at least one of these

comparisons is greater than 0.05. the more means that are compared, the more the

Type I error rate is inflated.

The type I error rate can be controlled using a test called the Tukey Honestly

Significant Difference test or Tukey HSD for short. The Tukey HSD is based on a

variation of the t distribution that takes into account the number of means being

compared. This distribution is called the studentized range distribution.

Tukey’s test calculates a new critical value that can be used to evaluate whether

differences between any two pairs of means are significant. The critical value is a

little different because it involves the mean difference that has to be exceeded to

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achieve significance. So, one simply calculates one critical value and then the

difference between all possible pairs of means. Each difference is then compared to

the Tukey critical value. If the difference is larger than the Tukey value, the

comparison is significant. The formula for the critical value is as follows:

‾dT = qT√MSs/A

‾‾‾‾‾‾

n

qT is the studentized range statistic (similar to the t-critical values, but different),

MSs/A is the mean square error from the overall F-test, and n is the sample size for

each group.

This the test usually recommend, because studies show it has greater power than the

other tests under most circumstances and it is readily available in computer packages.

It is important to note that the power advantage of the Tukey test depends on the

assumption that all possible pairwise comparisons are being made.

Tukey HSD is calculated as per the steps are outlined below:

1. Compute the means and variances of each group.

2. Compute MSE which is simply the mean of the variances.

3. Compute:

Mi – Mj

Q = ‾‾‾‾‾‾‾

√MSE/n

for each pair of means where Mi is one mean, Mj is the other mean and n is the

number of scores in each group.

The following multivariate analysis techniques have been used

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4.7.3 MULTIPLE REGRESSION

The general purpose of multiple regression (the term was first used by Pearson, 1908)

is to learn more about the relationship between several independent or predictor

variables and a dependent or criterion variable.

The Regression Equation- A line in a two dimensional or two-variable space is

defined by the equation Y= a + b*X; in full text: the Y variable can be expressed in

terms of a constant (a) and a slope (b) times the X variable. The constant is also

referred to as the intercept, and the slope as the regression coefficient or β coefficient.

In the multivariate case, when there is more than one independent variable, the

regression line cannot be visualized in the two dimensional space, but can be

computed just as easily. In general then, multiple regression procedures will estimate

a linear equation of the form:

Y = a + b1*X1 + b2*X2 + …..+ bp*Xp

Beta (standardised regression coefficients)

The beta value is a measure of how strongly each predictor variable influences the

criterion variable. The beta is measured in units of standard deviation. For example, a

beta value of 2.5 indicates that a change of one standard deviation in the predictor

variable will result in a change of 2.5 standard deviations in the criterion variable.

Thus, the higher the beta value the greater the impact of the predictor variable on the

criterion variable.

When we have only one predictor variable in the model, then beta is equivalent to the

correlation coefficient between the predictor and the criterion variable. This

equivalence makes sense, as this situation is a correlation between two variables.

When we have more than two predictor variable, we cannot compare the contribution

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of each predictor variable by simply comparing the correlation coefficients. The beta

regression coefficient is computed to allow you to make such comparisons and to

assess the strength of the relationship between each predictor variable to the criterion

variable.

Predicted and Residual Scores

The regression line expresses the best prediction of the dependent variable (Y), given

the independent variables (X). However, nature is rarely (if ever) perfectly

predictable, and usually there is substantial variation of the observed points around

the fitted regression line. The deviation of a particular point from the regression line

(its predicted value) is called the residual value.

Residual Variance and R-square

The smaller the variability of the residual values around the regression line relative to

the overall variability, the better is our prediction. For example, if there is no

relationship between the X and Y variables, then the ratio of the residual variability of

the Y variable to the original variance is equal to 1.0. If X and Y are perfectly related

then there is no residual variance and the ratio of variance would be 0.0. In most

cases, the ratio would fall somewhere between these extremes, that is, between 0.0

and 1.0. 1.0 minus this ratio is referred to as R-square or the coefficient of

determination. This value is immediately interpretable in the following manner. If we

have an R square of 0.4 then we know that the variability of the Y values around the

regression line is 1–0.4 times the original variance; in other words we have explained

40% of the original variability, and are left with 60% residual variability. Ideally, we

would like to explain most if not all of the original variability. The R-square value is

an indicator of how well the model fits the data (e.g. an R square close to 1.0 indicates

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that we have accounted for almost all of the variability with the variables specified in

the model).

Interpreting the Correlation Coefficient R

Customarily, the degree to which two or more predictors (independent or X variables)

are related to the dependent (Y) variable is expressed in the correlation coefficient R,

which is the square root of R-square. In multiple regression, R can assume values

between 0 and 1. To interpret the direction of relationship between variables, one

looks at the signs (plus or minus) of the regression or B coefficients. If a B coefficient

is positive, then the relationship of this variable with the dependent variable is

positive; if the B coefficient is negative then the relationship is negative. Of course, if

the B coefficient is equal to 0 then there is no relationship between the variables.

R, R Square, Adjusted R Square

R is a measure of the correlation between the observed value and the predicted value

of the criterion variable. R Square (R2) is the square of this measure of correlation and

indicates the proportion of the variance in the criterion variable which is accounted

for by our model. In essence, this is a measure of how good a prediction of the

criterion variable we can make by knowing the predictor variables. However, R

Square, tends to somewhat overestimate the success of the model when applied to the

real world, so an adjusted R Square value is calculated which takes into account the

number of variables in the model and the number of observations (participants) our

model is based on. This Adjusted R Square value gives the most useful measure of the

success of our model. If, for example, we have an adjusted R Square value of 0.75 we

can say that our model has accounted for 75% of the variance in the criterion.

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4.7.4 FACTOR ANALYSIS

Factor analysis is used to uncover the latent structure (dimensions) of a set of

variables. It reduces attribute space from a larger number of variables to a smaller

number of factors and as such is a “non-dependent” procedure (that is, it does not

assume a dependent variable is specified). Factor analysis could be used for any of the

following purposes:

• To reduce a large number of variables to a small number of factors for

modelling purposes, where the large number of variables precludes modelling

all the measures individually.

• To select a subset of variables from a larger set, based on which original

variables have the highest correlations with the principal component factors.

• To create a set of factors to be treated as uncorrelated variables as one

approach to handling multicollinearity in such procedures as multiple

regression.

• To validate a scale or index by demonstrating that its constituent items load on

the same factor, and to drop proposed scale items which cross load on more

than one factor.

Steps in Factor Analysis

Step 1: Compute a k by k intercorrelation matrix. Compute the factorability of the

matrix.

There are two ways to determine the Factorability of an intercorrelation matrix.

(1) Bartlett’s Test of Sphericity- Calculates the determinate of the matrix of the

sums of products and cross-products (S) from which the intercorrelation matrix is

200

derived. The determinant of the matrix S is converted to a chi-square statistic and

tested for significance. The null hypothesis is that the intercorrelation matrix comes

from a population in which the variables are noncollinear (i.e an identity matrix). And

that the non-zero correlations in the sample matrix are due to sampling error.

(2) Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO)- If two variables

share a common factor with other variables, their partial correlation will be small,

indicating a unique variance they share. Interpretation of the KMO as characterized

by Kaiser, Meyer and Olkin….

KMO Value Degree of Common Variance

0.90 to 1.00 Marvelous

0.80 to 0.89 Meritorious

0.70 to 0.79 Middling

0.60 to 0.69 Mediocre

0.50 to 0.59 Miserable

0.00 to 0.49 Don’t Factor

Step 2: Extract an initial solution

A variety of methods have been developed to extract factors from an intercorrelation

matrix. SPSS offers the following methods-

� Principal component method (probably the most commonly used method)

� Maximum likelihood method (a commonly used method)

� Principal axis method also known as common factor analysis

� Unweighted least squares method

201

� Generalized least squares method

� Alpha method

� Image factoring

There are several different types of factor analysis, with the most common being

principal component analysis (PCA). Principal Component Analysis seeks a linear

combination of variables such that the maximum variance is extracted from the

variables. It then removes this variance and seeks a second linear combination which

explains the maximum proportion of the remaining variance, and so on. This is called

the principal axis method and results in orthogonal (uncorrelated) factors. PCA

analyzes total (common and unique) variance.

Step 3: From the initial solution, determine the appropriate number of factors to be

extracted in the final solution

In the initial solution, each variable is standardized to have a mean of 0.0 and a

standard deviation of +_1.0. Thus the variance of each variable = 1.0. Since a single

variable can count for 1.0 unit of variance, a useful factor must account for more than

1.0 unit of variance, or have an eigen value λ > 1.0, otherwise the factor extracted

explains no more variance than a single variable.

Eigen Values: Also called Characteristic roots. The eigen value for a given factor

measures the variance in all the variables which is accounted for by that factor. The

ratio of eigen values is the ratio of explanatory importance of the factors with respect

to the variables. If a factor has a low eigen value, then it is contributing little to the

explanation of variances in the variables and may be ignored as redundant with more

important factors.

Interpretation. Eigen values measure the amount of variation in the total sample

202

REFERENCES

Aaker, D.A., Kumar, V. Day, G.S. (2001). Marketing Research. (7th ed.). John Wiley

and Sons, New York, NY.

Bitner, Mary Jo, Booms, Bernard H. & Tetreault, M. S. (1990). The Service

Encounter: Diagnosing Favorable and Unfavorable Incidents. Journal of

Marketing, 54 (January), 71-84.

Chung-Herrera, Beth G., Goldschimdt, Nadav & Hoffman, K. Doug. (2004).

Customer and employee views of critical service incidents. Journal of

Services Marketing, 18 (4), 241-254.

Cohen, Arthur M. & Smith, R. Douglas (1976), Chapter 4, The Critical-Incident

Model: Its Use and Application, The Critical Incident in Growth Groups:

Theory and Technique, University Associates Publishers and Consultants.

Flanagan, John C. (1954). The Critical Incident Technique. Psychological Bulletin. 51

(July), 327-57.

Forbes, Lukas P., Kelley, Scott W. & Hoffman, K. Douglas. (2005). Typologies of e-

commerce retail failures and recovery strategies. Journal of Services

Marketing, 19(5), 280-292.

George, Darren & Mallery, Paul. (2009). SPSS for Windows Step By Step- A Simple

Guide and Reference 15.0 Update. (8th ed.). Pearson Education, Inc.,

Dorling Kindersley (India) Pvt. Ltd.

Green, PE & Tull, DS. (1970). Research for Marketing Decisions, Englewood Cliffs,

NJ: Prentice –Hall, Inc.

203

Gupta, S.P. (2009). Statistical Methods. (37th revised ed.). Sultan Chand and Sons,

New Delhi.

Hoffman, Douglas K., Kelly, Scott, W. & Rotalsky, Holly, M. (1995). Tracking

Service Failures and Employee Recovery Efforts. Journal of Services

Marketing, 9 (2).

Kivela, Jaksa, J. & Chu, Carmen Yiu Ha. (2001). Delivering Quality Service:

Diagnosing Favorable And Unfavorable Service Encounters in

Restaurants. Journal of Hospitality and Tourism Research, 25 (3), August,

251-271.

Lewis, Barbara R. & Mc Cann, Pamela. (2004). Service failure and recovery:

evidence from the hotel industry. International Journal of Contemporary

Hospitality Management, 16 (1), 6-17.

Malhotra, Naresh, K. & Dash, Satyabhusan. (2009). Marketing Research An Applied

Orientation, (5th ed.). Dorling Kindersley (India) Pvt. Ltd.

Maxham III, James G. & Netemeyer, Richard G. (2002). A Longitudinal Study of

Complaining Customers’ Evaluations of Multiple Service Failures and

Recovery Efforts. Journal of Marketing, 66, (October). 57-71.

Maxham III, James G. & Netemeyer, Richard G. (2003). Firms Reap What They Sow:

The Effects of Shared Values and Perceived Organizational Justice on

Customers’ Evaluations of Complaint Handling. Journal of Marketing, 67,

(January), 46-62.

Pigors & Pigors. (1965). The Pigors Incident Process Case Studies for Management

Development. BNA Incorporated.

204

Singh, Jagdip. (1988). Consumer Complaint Intentions and Behavior: Definitional and

Taxonomical Issues. Journal of Marketing, 52, (January), 93-107.

Spreng, Richard A., Harrell, Gilbert D. & Mackoy, Robert, D. (1995). Service

Recovery: Impact on Satisfaction and Intentions. Journal of Services

Marketing, 9 (1), 15-23.

Zeithaml, Valarie A., Gremler, Dwayne D., Bitner, Mary Jo & Pandit, Ajay. (2008).

Services Marketing Integrating Customer Focus Across the Firm (4th ed.).

Tata McGraw Hill.

Zikmund, William G. (2007). Business Research Methods, Cincinnati, Ohio.

Thomson/South-Western.

205

STUDY I

5.1 IDENTIFICATION OF VARIOUS TYPES OF SERVICE FAILURES

To identify the various types of service failures that happened with passengers

travelling in domestic sectors of India, a technique called Critical Incident Technique

(CIT) is used. It is a qualitative interview procedure in which customers are asked to

provide verbatim stories about satisfying and dissatisfying service encounters they

have experienced. The CIT in its original conception consisted of “….a set of

procedures for collecting direct observations of human behaviour in such a way as to

facilitate their potential usefulness in solving practical problems and developing broad

psychological principles” (Flanagan, 1954, pp. 327-357). The use of this technique in

various services like hotels, restaurants, airlines, amusement parks, automotive

repairs, retailing, banking, cable television, public transportation, self-service

technologies and education has been reported. Bitner et al’s (1990) findings became

the foundation for the future studies in examining the service failure incidents with

the help of critical incident technique and the classification by type of incident

outcome provided guidelines to improve customer satisfaction. Each critical incident

through a deductive sorting process systematically categorized into three major failure

groups developed by Bitner et al (1990).

CHAPTER-5

DATA ANALYSIS AND INTERPRETATION

206

Table 5.1 Bitner et al’s (1990) Group and Category Classification by Type of

Incident Outcome

Group &

Category

Type of Incident Outcome

Group 1 Employee Response to Service Delivery System Failures

G1A Response to unavailable service

G1B Response to unreasonably slow service

G1C Response to other core service failures

Group 2 Employee Response to Customer Needs and Requests

G2A Response to special needs customers

G2B Response to customer preferences

G2C Response to admitted customer error

G2D Response to potentially disruptive others

Group 3 Unprompted and Unsolicited Employee Actions

G3A Attention paid to customers

G3B Truly out-of-the ordinary employee behaviour

G3C Employee behaviours in the context of cultural norms

G3D Gestalt evaluation

G3E Performance under adverse circumstances

207

Group1, Employee response to service delivery system failures- When the service

delivery system fails, contact employees are required to respond to consumer

complaints or disappointments. The content or form of the employee response

determines the customer’s perceived satisfaction or dissatisfaction. All group1

incidents are related directly to failures in the core service (flight delay, overbooking

of passengers, and delay in refund of cancelled ticket) and inevitable system failures

that occur for even the best of firms.

G1A, Response to unavailable service- Services normally available are lacking or

absent: overbooking of passengers, no provision of any refreshment when there is

long delay in flight, non-availability of right information about flight delay. The way

in which unavailability is handled influences the customer’s perception of the service.

Failure to apologize, offer to compensate or give an explanation can result in an

unavailability incident being remembered as very dissatisfactory.

G1B, Response to unreasonably slow service- This category reflects incidents in

which services or employee performances are perceived as inordinately slow. Delay

in refund of cancelled ticket, delay of baggage delivery, rescheduling without prior

notice, employee reactions to such delays determines the customer’s satisfaction

levels. Acting as though nothing is wrong, not explaining the delay and leaving

customers to figure out what to do their own are ways to aggravate the customer.

G1C, Response to other core service failures- Since unavailability (1A) and slow

service (1B) were dominating causes of core service failure, separate categories were

established for each category 1C encompasses incidents in which other aspects of the

core service do not meet basic performance standards for the industry e.g. missing of

baggage, exchange of baggage, inconvenience due to non working of air condition in

208

an aircraft, food and beverage not of high quality. How the employee responds to

these failures determines the customer’s perceptions of the encounter.

G2, Employee response to customer needs and requests- When a customer requires

the contact employee to adapt the service delivery system to suit his or her unique

needs, the contact employee’s response determines the customer’s dis/satisfaction. To

be classified in group2, incidents were required to contain either an explicit or

inferred request for customized service. ‘Customized’ was interpreted from the

customer’s point of view because much of what customers perceive as special

needs/requests may actually be routine from the firm or contact employee’s point of

view. What is important whether or not the customer perceives that his or her special

requests or needs have been accommodated?

G2A, Response to special needs customers- This category involves customers who

have special medical, dietary, psychological difficulties. Failure to recognize the

seriousness of the customer’s need and/or inappropriate or inadequate treatment of the

problem can result in a very dissatisfactory incident.

G2B, Response to customer preferences- This category includes incidents when,

from the customer’s perspective, ‘special’ requests are made. These requests reflect

personal preferences unrelated to the customer’s sociological, physical or

demographic characteristics (2A). This category also includes incidents in which the

customer requests a level of service customization clearly beyond the scope of or in

violation of firm/industry policies or norms. Customers can be very dissatisfied when

their preferences are not accommodated, especially if the employee shows no interest

and exerts no effort to be responsive, is unwilling to consider the ‘bending the rules’,

or promises to do something and then fails to follow through.

209

G2C, Response to admitted customer error- In this category the triggering event is

a customer error that strains the service encounter (e.g. lost ticket, reached late at

check in counter). Dissatisfactory employee responses include laughing at and

embarrassing the customer for his or her mistake, avoiding any responsibility, and

demonstrating unwillingness to assist the customer in solving the problem.

G2D, Response to potentially disruptive others- Within the environment of the

service encounter, other customers’ behaviours can strain the encounter (e.g.

intoxication, rudeness, creating noise). The contact employee or firm either does or

does not cope with the disruptive person to the satisfaction of other customers present.

G3, Unprompted and unsolicited employee actions- Events and employee

behaviours that are truly unexpected from the customer’s point of view are included

in group 3.

G3A, Attention paid to customer- This category includes incidents in which the

level of attention paid the customer is viewed very favourably or very negatively.

Dissatisfactory encounters occur when contact employees demonstrate poor attitudes

toward the customer, ignore the customer, not caring about the customer’s comfort,

and failing to provide information.

G3B, Truly out-of-ordinary employee behaviour- In this category are incidents in

which the employee does some small thing that for the customer translates into a

highly satisfactory or dissatisfactory encounter. In the case of dissatisfactory

encounters, extraordinary employee behaviour may consist of yelling, inappropriate

touching or rudeness.

G3C, Employee behaviours in the context of cultural norms- Incidents in this

category reflect employee behaviours relating to cultural norms such as equality,

210

honesty and fairness. Dissatisfactory encounters are associated with employee

behaviours that clearly violate cultural norms (discrimination against female/young

customers, employee theft, lying)

G3D, Gestalt evaluation- In this category, customers are unable to attribute

dissatisfaction to any single feature of the service encounter. Instead, the service

encounter is evaluated holistically, either everything went right or everything went

wrong.

G3E, Exemplary performance under adverse circumstances- This category

include incidents in which the customer is particularly displeased/ impressed with the

way a contact employee handles a stressful situation. This category emerged only for

satisfactory encounters.

211

Table 5.2 Demographic Profile of Respondents (N=200)

S.No. Variable No. of respondents Percentage

1. Gender

(a.) Male 139 69.5

(b.) Female 61 30.5

2. Age (in years)

(a.) below 20 8 4

(b.) 20-40 117 58.5

(c.) 40-60 61 30.5

(d.) above 60 14 7

3. Income (in Rs.)

(a.) below 10,000 21 10.5

(b.) 10,000-30,000 69 34.5

(c.) 30,000-50,000 69 34.5

(d.) above 50,000 41 20.5

4. Occupation

(a.) service 123 61.5

(b.) business 38 19

(c.) student 8 4

(d.) others 31 15.5

212

Table 5.2 presents the distribution of sample respondents with respect to the

demographics used in the study. From this distribution, it is seen that there are 139

(69.5%) male and 61 (30.5%) female amongst the respondents. The main age group is

20 – 40 years representing 58.5 % of the respondents (below 20 with 4%, 40-60 with

30.5% and above 60 with 7%). Equal percentages of the respondents’ i.e 34.5% have

income between Rs. 10,000 to Rs. 30,000 and Rs. 30,000 to Rs. 50,000 and 61.5% of

the respondents belong to occupation service, 19% belongs to business and 4% of the

respondents are students.

The critical incidents collected were categorized as per the classification given by

Bitner et al, 1990. For the classification of incidents, the procedures used by Bitner et

al, 1990; Kivela and Chu, 2001; Forbes et al, 2005 were considered. The analytic

induction process was used which consists of repeated, careful readings and sorting of

the incidents into groups and categories according to similarities in the reported

experience. Bitner et al classified the incident outcomes into three major groups -

Group1 is Employee Response to Service Delivery System Failures, Group 2 is

Employee Response to Customer Needs and Requests and Group 3 is Unprompted

and Unsolicited Employee Actions. Within three major groups, a total of 12

categories were developed- three in Group1, four in Group 2 and five in Group 3.

There is no service failure incident outcome that falls in category G3E, Performance

under Adverse Circumstances.

213

Table 5.3 Group and Category Classification by Type of Incident Outcome

Group &

Category

Type of Incident Outcome Count Percentage

Group 1 Employee Response to Service Delivery System Failures

G1A Response to unavailable service 53 31.5

G1B Response to unreasonably slow service 48 24

G1C Response to other core service failures 67 33.5

Total (1) 168 49.7

Group 2 Employee Response to Customer Needs and Requests

G2A Response to special needs customers 16 8

G2B Response to customer preferences 21 10.5

G2C Response to admitted customer error 5 2.5

G2D Response to potentially disruptive others 6 3

Total (2) 48 14.2

Group 3 Unprompted and Unsolicited Employee Actions

G3A Attention paid to customers 23 11.5

G3B Truly out-of-the ordinary employee behaviour

36 18

G3C Employee behaviours in the context of cultural norms

29 14.5

G3D Gestalt evaluation 34 17

Total (3) 122 36.1

Total (1+2+3) 338 100

214

Table 5.3 indicated that 49.7% of incidents reported by passengers in domestic sectors

of India occurred due to service delivery system failures i.e. the incidents are related

directly to failures in the core service and inevitable system failures that occur for

even the best of firms, 14.2% of incidents occurred due to employee response to

customer needs and requests i.e. when a customer requires the contact employee to

adapt the service delivery system to suit his or her unique needs, the contact

employee’s response determines the customer’s dis/satisfaction and 36.1% of

incidents reported due to unprompted and unsolicited employee actions i.e. events and

employee behaviours that are truly unexpected from the customer’s point of view.

Examination of Table 5.3 reveals that a large proportion of dissatisfactory encounters

were related to employees’ inability or unwillingness to respond in core service

failure situations (33.5%). These core service failures are related with missing,

exchange and mishandling of baggage, quality of food provided by the airlines and

technology failures like non-working of air condition in the aircraft. After careful and

repeated readings of the incidents indicate that it is not the initial failure to deliver the

core service alone that causes dissatisfaction but rather the employees’ response to the

failure.

Category ‘unavailable service’ accounted for 31.5% of the total failures. It includes

non-availability of seat at departure terminal, no information is provided about flight

delay, after long delay flight cancelled, flight cancelled without any prior notice to the

passengers, no provision of any refreshment when there is long delay in flight and

some passengers suffered due to overbooking.

Incidents classified under category of ‘unreasonably slow service’ made up of 24% of

total incidents collected. These dissatisfactory encounters are delay in baggage

215

delivery and delay in refund of cancelled ticket. Also, food provided in the aircraft is

not on time and rescheduling is not intimated to the passengers.

In all group 1 dissatisfactory incidents, the employee failed to handle the situations in

a way that could have satisfied the passenger.

Group 2 failures involved employee response to customer needs and requests and

accounted for 14.2% of total failures. Incidents classified under category of response

to special needs customers made up of 8% of total incidents. It is mishandling of

carry-on/delicate items by the airlines’ personnel after special request is made by the

passengers. Response to customer preferences accounted for 10.5% of total failures.

Respondents considered inconvenience caused due to less leg space in aircraft and

allow to carry- on items at one sector by the airline personnel and deny the same item

by the same airline personnel at another sector considered dissatisfactory encounters.

Five incidents were reported that fall in the category response to admitted customer

error (2.5%) i.e. airline staff shows unwillingness to assist the customer in solving the

problem arises due to customer error. And failure incidents were identified in the

category response to potentially disruptive others (3%) i.e. co-passengers in the

aircraft caused inconvenience to the other passengers. Thus, failures to accommodate

the need for customized service are relatively infrequent in comparison with other

sources of dissatisfaction.

36.1% of dissatisfactory service encounters in Group 3 are related to passenger’s

negative reactions to unprompted and unsolicited employee behaviours. Twenty-three

service failure incidents were identified that belong to the category attention paid to

customers (11.5%) i.e. inefficiency shown by the staff of the airlines while solving the

problems of the passengers. Thirty-six incidents were identified in category truly out-

of-ordinary employee behaviour (18%), twenty-nine incidents in the category

216

employee behaviour in the context of cultural norms (14.5%) and thirty-four failure

incidents in category gestalt evaluation (17%). In this group of incidents, the assessed

character or attitude of the airline personnel as inferred from particular behaviours

both verbal and non verbal caused dissatisfaction to passengers.

Table 5.4 Group 1 – Sample Incidents: Employee Response to Service Delivery

Failures

Category Dissatisfactory Incident

A. Response to Unavailable

Service

Boarding 5.30 pm, flight departed at 2.30 am

finally flight reached at 4 am. There is no way to

contact my son who is waiting for me at Chennai

airport. There is no place to sit at Delhi airport. If

flight is delayed due to unavoidable circumstances

at least they provide a place to sit comfortably.

(2006)

B. Response to Unreasonably

Slow Service

Scheduled to depart at 12 noon, planned to reach

Delhi around 1 pm and had lunch by 2.30 pm, but

the flight get delayed by 1hr, informed me via

phone. I reached airport after check in wait 1 and a

half hour at airport, boarded flight wait for another

half an hour, finally flight departed at 3 pm. They

don’t ask for water or any refreshment to the

passengers. I didn’t complain for that, especially

Spice Jet provide paid and costly snacks in the

flight. (2008)

C. Response to Other Core

Service Failures

My luggage was lost. I complained to the staff

members at Jammu airport and I also sent mail to

CC, later. But I didn’t get any reply. Till date,

neither had I got my luggage nor did I get any

compensation. (2006)

217

Table 5.5 Group 2– Sample Incidents: Employee Response to Customer Needs

and Requests

Category Dissatisfactory Incident

A. Response

“Special

Needs”

Customers

During flight landing and departing faced problems in ears/ear

pressure, ask for ear buds. They didn’t provide me and they don’t have

such facility. But they should provide some earphone or buds so that

passengers don’t feel pressure. (2008)

B. Response

to Customer

Preferences

Morning flight at 4.20am, reached airport at 4am did not get three

seats together because they already accommodated the passengers

who already check in, uncomfortable atmosphere, huge rush in the

flight, even air hostess didn’t give the breakfast properly or on time,

complained them that I am a frequent flyer, arrange three seats

together when we returned after three days, they noted down my

frequent flyer no. and when we came back after three days to board

the fight, huge rush was their but they upgraded in executive class,

cabin crew staff didn’t provide efficient service. (2007)

C. Response

to Admitted

Customer

Error

I reached at airline counter thirty minutes before the departure of

flight; 3-4 passengers were also late. I got late because of traffic

chaos. But the customer service manager denied us to check in,

without listening any reason of ours. He was least cooperative and

didn’t help at all. He didn’t even try to speak to the captain and wasted

another 10-15 minutes in arguing with us. Ultimately, I purchased

another ticket of next flight. (2009)

D. Response

to Potentially

Disruptive

others

The passenger sitting next to me was drunkard, he showed a very

wrong behaviour towards the passengers, after every ten minutes went

to toilet and came back. His movement caused inconvenience to me

and others and kids were also sitting with me. Asked the crew staff to

change my seat or tell that passenger to sit properly. But no response

from the staff and through out the journey I was uncomfortable and

remained alert for any adverse circumstances. (2008)

218

Table 5.6 Group 3 – Sample Incidents: Unprompted and Unsolicited Employee

Actions

Category Dissatisfactory Incident

A. Attention

Paid to

Customer

Scheduled time 4.15 pm but departed at 9.30 pm, during the whole

period stranded at Delhi airport, time wastage, none of my fault,

boring period, after this period I never travelled with Air Deccan. It

doesn’t look good to ask for tea/coffee, they should give themselves,

like coupons to check-in passengers. There should be tight scheduling

of time. (2004)

B. Truly Out-

of-the-

Ordinary

Employee

Behaviour

I have delicate items and informed the security personnel, they took it

lightly, paste the sticker on the packed items. After taking boarding

pass, I again informed that there are delicate items, handle them

carefully. When I reached Jammu, locked was broken of my suitcase,

flower vase was broken when I saw at home. Go Air staff members

have very careless attitude. Not possible to complain at Srinagar

airport. (2008)

C. Employee

Behaviours in

the context of

Cultural

Norms

I have to go to Mumbai for the cremation of my relative, I booked the

flight through the agent when I reached the airport what I found that

the airline was overbooked, the airline member denied check-in and

offered me to board the next flight of Indian Airline. I told them the

reason that this flight is urgent for me and gave the reason that you

booked the flight on the same day. I don’t understand if it is fully

booked then why they issued the ticket. Finally, I boarded the next

flight and the purpose of my visit was not fulfilled. (2001)

D. Gestalt

Evaluation

The airline issued boarding pass to four passengers as connecting

flight from Mumbai to Delhi, the Rajkot-Mumbai flight landed at 9.05

pm but the airline staff misguided us that our next fight is already left

and contact duty manager at the airport. Actually, our next flight was

delayed by 40 minutes but due to staff negligence they pushed us into

a mess just to avoid a little effort at their part. Finally, they boarded us

in Jet Konnect flight which left Mumbai at 12.20 am, very

inconvenient journey, moreover no food was provided by the staff. It

was a full fledged mess created by the airline staff. (2009)

219

Comparison of Failure Frequency in Percentage

45.5

27.3 27.3

49.7

14.2

36.1

0102030405060

Employee Response toService Delivery System

Failures

Employee Response toCustomer Needs and

Requests

Unprompted andUnsolicited Employee

Actions

G1 G2 G3

Bitner et al (1990) Failure Frequency (Airlines) (%)

Present Study Failure Frequency (%)

Fig 5.1 Shows the Comparison of Failure Frequency in Percentage (Study I)

220

Table 5.7 Comparison of Failure Frequency in Percentage

Bitner et al (1990)

Failure Frequency

(Airlines)

Present Study

Failure Frequency

Group Statements

No. % No. %

Group1 Employee Response to

Service Delivery System

Failures

35 45.5 168 49.7

Group2 Employee Response to

Customer Needs and

Requests

21 27.3 48 14.2

Group3 Unprompted and

Unsolicited Employee

Actions

21 27.3 122 36.1

Total 77 100 338 100

Table 5.7 shows the comparison of failure frequency of incidents in airline sector of

Bitner et al’s (1990) study and present study.

221

STUDY-II

After initial sorting process and classification, twenty-six service failure

categories were identified. All twenty-six service failures classified in to sub

categories of three major groups as per the classification given by Bitner et al (1990).

The present study defined the twenty-six identified service failures into categories.

Table 5.8 Classification of Service Failures in Bitner et al’s (1990) Group and

Category Classification by Type of Incident Outcome

Group &

Category

Type of Incident Outcome Number of

Service

Failures

Group 1 Employee Response to Service Delivery System Failures

G1A Response to unavailable service Six

G1B Response to unreasonably slow service Four

G1C Response to other core service failures Six

Group 2 Employee Response to Customer Needs and Requests

G2A Response to special needs customers One

G2B Response to customer preferences Two

G2C Response to admitted customer error One

G2D Response to potentially disruptive others One

Group 3 Unprompted and Unsolicited Employee Actions

G3A Attention paid to customers One

G3B Truly out-of-the ordinary employee behaviour Two

G3C Employee behaviours in the context of cultural norms One

G3D Gestalt evaluation One

G3E Performance under adverse circumstances Nil

222

Six service failures are included in category G1A Response to unavailable service -

cancelled flight without prior notice, non-availability of seat at departure terminal,

overbooking of passengers, no provision of any refreshment when there is long delay

in flight, flight delay and non-availability of right information about flight delay; four

service failures are included in category G1B Response to unreasonably slow

service- delay in refund of cancelled ticket, rescheduling without prior notice,

provision of food not on time and delay of baggage delivery; six service failures are in

category G1C Response to other core service failures- mishandling of baggage,

food and beverage not of high quality, missing of baggage, exchange of baggage,

inconvenience due to non working of air condition in aircraft and printing mistake on

ticket; one service failure in category G2A Response to special need customers-

mishandling of carry-on items/delicate items; two service failures are included in

category G2B Response to customer preferences- less leg space and allow to carry-

on items at one sector and deny the same at another; one service failure is in category

G2C Response to admitted customer error- staff shows unwillingness to assist the

customer in solving the problem arises due to customer error, one service failure in

category G2D Response to potentially disruptive others- co-passengers show

interrupted behaviour; one service failure included in category G3A Attention paid

to customer- inefficient staff; two service failures are included in category G3B

Truly out-of-the-ordinary employee behaviour- unfriendly and unhelpful attitude

of ground staff members and unfriendly and unhelpful attitude of crew members; one

service failure in category G3C Employee behaviour in the context of cultural

norms- theft of items which are under the scrutiny of airline staff members and one

service failure is included in category G3D Gestalt Evaluation- unfriendly and

223

uncomfortable ambience for the travellers. There is no service failure incident

outcome that falls in category G3E, Performance under Adverse Circumstances.

Table 5.9 Classification of Twenty-six Identified Service Failures into Groups

and Categories

Group and

Category

Statements

G1 Employee Response to Service Delivery System Failures

G1A Response to unavailable service

1 Cancelled flight without prior notice

2 Non-availability of seat at departure terminal

3 Overbooking of passengers

4 No provision of any refreshment when there is long delay in flight

5 Flight delay

6 Non-availability of right information about flight delay

G1B Response to unreasonably slow service

7 Delay in refund of cancelled ticket

8 Rescheduling without prior notice

9 Provision of food not on time

10 Delay of baggage delivery

G1C Response to other core service failures

11 Mishandling of baggage

12 Food & beverage not of high quality

13 Missing of baggage

14 Exchange of baggage

15 Inconvenience due to non working of air condition in aircraft

16 Printing mistake on ticket

G2 Employee Response to Customer Needs and Requests

G2A Response to special needs customers

17 Mishandling of carry-on items/delicate items

G2B Response to customer preferences

18 Less leg space

19 Allow to carry-on items at one sector & deny the same at another

224

G2C Response to admitted customer error

20 Staff shows unwillingness to assist the customer in solving the problem arises due to customer error

G2D Response to potentially disruptive others

21 Co-passengers show interrupted behaviour

G3 Unprompted and Unsolicited Employee Actions

G3A Attention paid to customer

22 Inefficient staff

G3B Truly out-of-the-ordinary employee behaviour

23 Unfriendly & unhelpful attitude of ground staff members

24 Unfriendly & unhelpful attitude of crew members

G3C Employee behaviours in the context of cultural norms

25 Theft of items which are under the scrutiny of airline staff members

G3D Gestalt evaluation

26 Unfriendly & uncomfortable ambience for the travellers

5.2 SECTION I- DEMOGRAPHIC PROFILE OF THE RESPONDENTS

The demographic profile of the respondents is reflected in Table 5.10. It is clear from

the table that out of the 305 total respondents, 201 (65.90 %) are male and 104 (34.10

%) are female.

Majority of the respondents are in the age group 20-40 i.e. 203 constituting 66.56%

followed by 40-60 i.e. 64 (20.98%).

As far as the income of the respondents is concerned, maximum respondents i.e. 98

(32.13%) belong to Rs.20,000 - Rs.40,000, followed by less than Rs.20,000 i.e. 77

(25.25%).

Table 5.10 shows that the travel frequency of respondents by air in a year is 120

(39.34%) who travelled less than 5 times in a year followed by 110 (36.07%)

225

respondents travelled by 5-10 times, 51 (16.72%) respondents travelled by 10-15

times and only 24 (7.87%) respondents travelled above 15 times in a year.

For travel purpose and preference given to full service carrier and low cost carrier,

respondents selected more than two options. 76 and 74 respondents travelled for

vacation and business purpose respectively. 170 respondents preferred low cost

carrier for travel and only 60 respondents preferred full service carrier.

226

Table 5.10 Demographic Profile of the Respondents

N=305

S.No. Variable No. of Respondents Percentage

(%)

1. Gender

(a) Male 201 65.90

(b) Female 104 34.10

2. Age (in years)

(a) less than 20 20 6.56

(b) 20-40 203 66.56

(c) 40-60 64 20.98

(d) above 60 18 5.90

3. Income (in Rs.) (approx. per year)

(a) less than 20,000 77 25.25

(b) 20,000-40,000 98 32.13

(c) 40,000-60,000 68 22.30

(d) above 60,000 62 20.33

4. Travel frequency (by air) ( in a year)

(a) less than 5 120 39.34

(b) 5-10 110 36.07

(c) 10-15 51 16.72

(d) above 15 24 7.87

5.* Travel purpose

(a) Business 74

(b) Visit 47

(c) Vacation 76

(d) Education 23

(e) Others 14

6.* Preference given to

(a) Full Service Carrier 60

(b) Low Cost Carrier 170

• Respondents selected more than one option.

227

5.3 SECTION II- DESCRIPTIVE STATISTICS (MEAN AND STANDARD

DEVIATION) OF LEVEL OF SERIOUSNESS, FREQUENCY OF SERVICE

FAILURES ENCOUNTERED AND EFFECT ON SATISFACTION

The mean and standard deviation were computed to illustrate the central tendency and

dispersion of variables.

The mean is simply the average of each variable. From the mean we can determine

the standard deviation, is a measure of how widely values are dispersed from the

average value (the mean).

Table 5.11 describes the mean scores and standard deviation values of all twenty-six

service failures classified in three major groups as per the classification given by

Bitner et al (1990).

228

Table 5.11 Statement Wise Response (Mean and Standard Deviation) to Level of

Seriousness, Frequency of Failures Encountered and effect on Satisfaction

N=305

A. Level of Seriousness

B. Frequency of failures encountered

C. Effect on Satisfaction

Statements

Mean SD Mean SD Mean SD

G1 Employee Response to Service

Delivery System Failures

G1A Response to unavailable

service

1 Cancelled flight without prior notice

4.35 0.85 1.70 0.76 4.37 0.74

2 Non-availability of seat at departure terminal

3.86 1.03 1.54 0.82 4.15 0.83

3 Overbooking of passengers 4.17 0.84 1.51 0.73 4.29 0.72 4 No provision of any

refreshment when there is long delay in flight

4.15 0.86 1.93 0.99 4.41 0.65

5 Flight delay 4.38 0.77 2.40 1.04 4.51 0.67 6 Non-availability of right

information about flight delay 4.22 0.84 2.21 1.09 4.50 0.67

Grand Mean 4.18 0.54 1.88 0.64 4.37 0.48

G1B Response to unreasonably slow service

7 Delay in refund of cancelled ticket

4.37 0.79 1.69 0.89 4.47 0.71

8 Rescheduling without prior notice

4.50 0.69 1.63 0.84 4.51 0.67

9 Provision of food not on time 4.03 0.91 1.65 0.88 4.36 0.78 10 Delay of baggage delivery 4.30 0.80 1.86 1.07 4.50 0.66 Grand Mean 4.3 0.58 1.71 0.73 4.46 0.52

G1C Response to other core service

failures

11 Mishandling of baggage 4.59 0.69 1.59 0.85 4.54 0.69 12 Food & beverage not of high

quality 4.36 0.74 1.6 0.86 4.50

0.72 13 Missing of baggage 4.68 0.59 1.35 0.67 4.59 0.64 14 Exchange of baggage 4.64 0.70 1.35 0.65 4.6 0.69 15 Inconvenience due to non

working of air condition in aircraft

4.24 0.88 1.36 0.66 4.50 0.72

16 Printing mistake on ticket 4.35 0.72 1.27 0.62 4.49 0.69 Grand Mean 4.48 0.47 1.42 0.50 4.54 0.51

G2 Employee Response to

Customer Needs and Requests

G2A Response to special needs

customers

17 Mishandling of carry-on items/delicate items

4.45 0.67 1.36 0.66 4.47 0.66

229

G2B Response to customer preferences

18 Less leg space 3.71 0.95 1.68 1.04 4.09 0.78 19 Allow to carry-on items at one

sector & deny the same at another

4.35 0.75 1.43 0.76 4.51 0.71

Grand Mean 4.03 0.69 1.56 0.79 4.3 0.62

G2C Response to admitted customer error

20 Staff shows unwillingness to assist the customer in solving the problem arises due to customer error

4.00 0.99 1.43 0.68 4.28 0.85

G2D Response to potentially

disruptive others

21 Co-passengers show interrupted behaviour

3.96 0.83 1.44 0.69 4.2 0.78

G3 Unprompted and Unsolicited

Employee Actions

G3A Attention paid to customer

22 Inefficient staff 4.08 0.88 1.69 0.84 4.38 0.71 G3B Truly out-of-the-ordinary

employee behaviour

23 Unfriendly & unhelpful attitude of ground staff members

4.36 0.76 1.73 0.79 4.48 0.71

24 Unfriendly & unhelpful attitude of crew members

4.42 0.75 1.65 0.81 4.54 0.68

Grand Mean 4.39 0.69 1.69 0.73 4.51 0.63 G3C Employee behaviour in the

context of cultural norms

25 Theft of items which are under the scrutiny of airline staff members

4.61 0.64 1.36 0.59 4.62 0.73

G3D Gestalt evaluation 26 Unfriendly & uncomfortable

ambience for the travellers 4.27 0.88 1.73 0.89 4.57 0.69

It is concluded from the Table 5.11 that the respondents (N= 305) show the highest

level of seriousness towards the service failures that are included in category G3C,

employee behaviour in the context of cultural norms (Mean= 4.61, SD= 0.64) and

also the satisfaction (Mean= 4.62, SD= 0.73) is highly affected by this category of

failures. The most frequently encountered (Mean= 1.88 and SD= 0.64) failures are

included in category G1A, response to unavailable service.

230

Within a group1, employee response to service delivery system failures, the

respondents are considered the other core service failures (Mean= 4.48, SD= 0.47)

highly serious and these failures are highly affected the satisfaction of respondents.

But the failures that are most frequently encountered by respondents are included in

category response to unavailable service (Mean= 1.88, SD= 0.64).

In group2, employee response to customer needs and requests, failures regarding

employee response to special needs customers are considered most serious (Mean=

4.45, SD= 0.67) and these failures highly affected the satisfaction (Mean= 4.47, SD=

0.66) of respondents but the failures regarding customer preferences are more

frequently encountered (Mean= 1.56, SD= 0.79) by respondents.

In group3, unprompted and unsolicited employee actions, the respondents are

considered the failures regarding the employee behaviour in the context of cultural

norms (Mean= 4.61, SD= 0.64) most serious and these failures highly affected the

satisfaction (Mean= 4.62, SD= 0.73). The failures that are most frequently

encountered (Mean= 1.73, SD= 0.89) by respondents are gestalt evaluations.

231

Table 5.12- Statement Wise Response (Mean and Standard Deviation) to Level of

Seriousness, Frequency of Failure Encountered and Effect on Satisfaction on the

basis of gender

Males, N=201, Females, N=104

A-Level of Seriousness B-Frequency of Failures

Encountered

C- Effect on

Satisfaction

S.No

.

Type of Service

Failure

Male

(Mean, SD)

Female

(Mean, SD)

Male

(Mean, SD)

Female

(Mean, SD)

Male

(Mean, SD)

Female

(Mean, SD)

G1 Employee Response to Service Delivery

System Failures

G1A Response to

unavailable service

1. Cancelled flight without prior notice

4.4 (0.90) 4.34 (0.76) 1.72 (0.78) 1.68 (0.71) 4.39 (0.71) 4.33 (0.78)

2. Non-availability of seat at departure terminal

3.86 (1.02) 3.85 (1.02) 1.57 (0.87) 1.47 (0.71) 4.20 (0.83) 4.05 (0.84)

3. Overbooking of passengers

4.18 (0.84) 4.14 (0.83) 1.50 (0.72) 1.55 (0.76) 4.34 (0.71) 4.17 (0.72)

4. No provision of any refreshment when there is long delay in flight

4.10 (0.88) 4.24 (0.81) 1.95 (1.04) 1.88 (0.88) 4.40 (0.65) 4.42 (0.66)

5. Flight delay 4.34 (0.81) 4.45 (0.70) 2.47 (1.01) 2.27 (1.08) 4.47 (0.71) 4.61 (0.60) 6. Non-availability of

right information about flight delay

4.15 (0.90) 4.36 (0.71) 2.21 (1.08) 2.21 (1.12) 4.51 (0.66) 4.49 (0.70)

Grand Mean 4.17 (0.55) 4.23 (0.53) 1.90 (0.67) 1.84 (0.58) 4.39 (0.47) 4.34 (0.50)

G1B Response to

unreasonably slow

service

7. Delay in refund of cancelled ticket

4.38 (0.77) 4.35 (0.84) 1.70 (0.83) 1.69 (1.00) 4.44 (0.73) 4.51 (0.67)

8. Rescheduling without prior notice

4.47 (0.72) 4.56 (0.64) 1.70 (0.87) 1.5 (0.75) 4.52 (0.72) 4.5 (0.57)

9. Provision of food not on time

4.01 (0.95) 4.08 (0.81) 1.66 (0.89) 1.63 (0.86) 4.33 (0.83) 4.42 (0.66)

10. Delay of baggage delivery

4.31 (0.85) 4.28 (0.69) 1.94 (1.13) 1.70 (0.91) 4.50 (0.70) 4.48 (0.59)

Grand Mean 4.29 (0.60) 4.31 (0.55) 1.75 (0.76) 1.63 (0.66) 4.45 (0.54) 4.48 (0.46)

G1C Response to other

core service failures

11. Mishandling of baggage

4.59 (0.70) 4.60 (0.69) 1.62 (0.86) 1.53 (0.82) 4.51 (0.73) 4.60 (0.62)

12. Food & Beverage not of high quality

4.36 (0.76) 4.37 (0.70) 1.69 (0.93) 1.43 (0.71) 4.49 (0.72) 4.51 (0.74)

13. Missing of baggage 4.69 (0.62) 4.65 (0.53) 1.40 (0.71) 1.26 (0.56) 4.58 (0.62) 4.61 (0.69) 14. Exchange of baggage 4.63 (0.72) 4.64 (0.67) 1.38 (0.70) 1.30 (0.56) 4.60 (0.70) 4.60 (0.68) 15. Inconvenience due to

non working of air condition in aircraft

4.22 (0.89) 4.28 (0.85) 1.44 (0.73) 1.21 (0.48) 4.54 (0.67) 4.42 (0.81)

16. Printing mistake in ticket

4.36 (0.71) 4.35 (0.75) 1.31 (0.68) 1.20 (0.49) 4.47 (0.71) 4.54 (0.64)

Grand Mean 4.48 (0.48) 4.48 (0.47) 1.47 (0.55) 1.32 (0.37) 4.53 (0.50) 4.54 (0.53)

232

G2 Employee Response

to Customer Needs

and Requests

G2A Response to special needs customers

17. Mishandling of carry-on items/delicate items

4.42 (0.68) 4.49 (0.64) 1.40 (0.69) 1.29 (0.62) 4.48 (0.68) 4.45 (0.64)

G2B Response to

customer preferences

18. Less leg space 3.71 (0.94) 3.73 (0.99) 1.71 (1.05) 1.62 (1.02) 4.11 (0.79) 4.05 (0.76) 19. Allow to carry-on

items at one sector & deny the same at another

4.37 (0.67) 4.31 (0.89) 1.49 (0.78) 1.32 (0.71) 4.51 (0.71) 4.51 (0.71)

Grand Mean 4.04 (0.66) 4.02 (0.75) 1.60 (0.80) 1.47 (0.76) 4.31 (0.62) 4.28 (0.63)

G2C Response to admitted customer error

20. Staff shows unwillingness to assist the customer in solving the problem arises due to customer error

4.01 (1.00) 3.98 (0.98) 1.46 (0.73) 1.38 (0.56) 4.28 (0.88) 4.27 (0.79)

G2D Response to

potentially disruptive

others

21. Co-passengers show interrupted behaviour

3.93 (0.85) 4.01 (0.79) 1.46 (0.70) 1.40 (0.66) 4.17 (0.78) 4.25 (0.76)

G3 Unprompted and Unsolicited Employee Actions

G3A Attention paid to customer

22. Inefficient staff 4.04 (0.94) 4.16 (0.74) 1.73 (0.86) 1.62 (0.78) 4.36 (0.73) 4.43 (0.68) G3B Truly out-of-the-

ordinary employee

behaviour

23. Unfriendly & unhelpful attitude of ground staff members

4.29 (0.79) 4.51 (0.70) 1.77 (0.82) 1.67 (0.74) 4.48 (0.70) 4.49 (0.73)

24. Unfriendly & unhelpful attitude of crew members

4.39 (0.79) 4.48 (0.68) 1.69 (0.85) 1.57 (0.72) 4.49 (0.70) 4.63 (0.63)

Grand Mean 4.34 (0.72) 4.50 (0.63) 1.73 (0.78) 1.62 (0.64) 4.49 (0.63) 4.56 (0.62)

G3C Employee behaviour

in the context of

cultural norms

25. Theft of items which are under the scrutiny of airline staff members

4.62 (0.65) 4.61 (0.63) 1.36 (0.60) 1.35 (0.57) 4.60 (0.76) 4.66 (0.66)

G3D Gestalt evaluation 26. Unfriendly &

uncomfortable ambience for the travellers

4.25 (0.89) 4.31 (0.85) 1.08 (0.89) 1.69 (0.89) 4.56 (0.68) 4.60 (0.70)

233

Table 5.13- Statement Wise Response (Mean and Standard Deviation) to Level of

Seriousness on the Basis of Travel Frequency

A. Level of Seriousness S. No. Type of Service Failure

a.) less than 5

(Mean & SD)

N= 120

b. ) 5-10

(Mean & SD)

N= 110

c.) 10-15

( Mean & SD)

N= 51

d.) above 15

(Mean & SD)

N= 24

G1 Employee Response to Service Delivery System Failures

G1A Response to unavailable

service

1. Cancelled flight without prior notice

4.29 (0.95) 4.37 (0.80) 4.35 (0.87) 4.58 (0.50)

2. Non-availability of seat at departure terminal

3.85 (0.98) 3.87 (1.04) 3.76 (1.12) 4 (0.98)

3. Overbooking of passengers 4.16 (0.86) 4.21 (0.74) 4.22 (0.86) 3.92 (1.06) 4. No provision of any

refreshment when there is long delay in flight

4.18 (0.82) 4.07 (0.87) 4.16 (1.01) 4.29 (0.62)

5. Flight delay 4.32 (0.73) 4.42 (0.79) 4.43 (0.88) 4.42 (0.65) 6. Non-availability of right

information about flight delay 4.23 (0.85) 4.17 (0.76) 4.25 (0.98) 4.38 (0.88)

Grand Mean 4.17 (0.54) 4.19 (0.54) 4.20 (0.64) 4.26 (0.34)

G1B Response to unreasonably

slow service

7. Delay in refund of cancelled ticket

4.34 (0.84) 4.39 (0.65) 4.29 (0.99) 4.54 (0.72)

8. Rescheduling without prior notice

4.48 (0.73) 4.5 (0.69) 4.51 (0.70) 4.63 (0.49)

9. Provision of food not on time 4.02 (0.86) 4.1 (0.86) 4.06 (0.99) 3.75 (1.15) 10. Delay of baggage delivery 4.28 (0.81) 4.3 (0.77) 4.39 (0.80) 4.25 (0.85)

Grand Mean 4.28 (0.63) 4.32 (0.50) 4.31 (0.65) 4.29 (0.63)

G1C Response to other core service failures

11. Mishandling of baggage 4.53 (0.80) 4.67 (0.53) 4.59 (0.75) 4.5 (0.66) 12. Food & Beverage not of high

quality 4.37 (0.73) 4.41 (0.67) 4.29 (0.90) 4.29 (0.75)

13. Missing of baggage 4.68 (0.63) 4.7 (0.52) 4.63 (0.66) 4.67 (0.56) 14. Exchange of baggage 4.58 (0.80) 4.7 (0.61) 4.65 (0.66) 4.63 (0.65) 15. Inconvenience due to non

working of air condition in aircraft

4.19 (0.95) 4.26 (0.80) 4.22 (0.94) 4.42 (0.72)

16. Printing mistake in ticket 4.35 (0.72) 4.4 (0.72) 4.35 (0.69) 4.29 (0.86) Grand Mean 4.45 (0.53) 4.52 (0.40) 4.45 (0.51) 4.47 (0.41)

G2 Employee Response to

Customer Needs and

Requests

G2A Response to special needs

customers

17. Mishandling of carry-on items/delicate items

4.4 (0.69) 4.43 (0.66) 4.55 (0.64) 4.54 (0.66)

G2B Response to customer

preferences

18. Less leg space 3.7 (0.94) 3.74 (0.90) 3.67 (1.16) 3.79 (0.83) 19. Allow to carry-on items at one 4.26 (0.82) 4.44 (0.70) 4.27 (0.75) 4.54 (0.59)

234

sector & deny the same at another

Grand Mean 4.0 (0.71) 4.09 (0.66) 3.97 (0.78) 4.17 (0.48)

G2C Response to admitted

customer error

20. Staff shows unwillingness to assist the customer in solving the problem arises due to customer error

3.85 (1.00) 4.15 (0.91) 4.08 (1.02) 3.96 (1.16)

G2D Response to potentially

disruptive others

21. Co-passengers show interrupted behaviour

3.86 (0.84) 4.06 (0.77) 4 (0.82) 3.88 (1.03)

G3 Unprompted and Unsolicited

Employee Actions

G3A Attention paid to customer

22. Inefficient staff 3.96 (0.93) 4.29 (0.76) 4.02 (0.86) 3.88 (0.99) G3B Truly out-of-the-ordinary

employee behaviour

23. Unfriendly & unhelpful attitude of ground staff members

4.31 (0.79) 4.47 (0.74) 4.31 (0.76) 4.25 (0.74)

24. Unfriendly & unhelpful attitude of crew members

4.33 (0.77) 4.54 (0.67) 4.49 (0.70) 4.17 (1.01)

Grand Mean 4.32 (0.71) 4.5 (0.65) 4.40 (0.65) 4.21 (0.85)

G3C Employee behaviour in the

context of cultural norms

25. Theft of items which are under the scrutiny of airline staff members

4.62 (0.68) 4.65 (0.61) 4.57 (0.64) 4.5 (0.66)

G3D Gestalt evaluation 26. Unfriendly & uncomfortable

ambience for the travellers 4.09 (0.95) 4.45 (0.81) 4.35 (0.77) 4.17 (0.87)

235

Table 5.14- Statement Wise Response (Mean and Standard Deviation) to

Frequency of Failure Encountered on the Basis of Travel Frequency

B. Frequency of Failures Encountered S.

No.

Type of Service Failure

a.) less than 5

(Mean & SD)

N=120

b. ) 5-10

(Mean & SD)

N= 110

c.) 10-15

(Mean & SD)

N= 51

d.) above 15

(Mean & SD)

N= 24

G1 Employee Response to Service Delivery System Failures

G1A Response to unavailable service 1. Cancelled flight without prior notice 1.51 (0.69) 1.73 (0.68) 1.96 (0.87) 2.04 (0.95) 2. Non-availability of seat at departure

terminal 1.41 (0.76) 1.65 (0.89) 1.55 (0.73) 1.63 (0.88)

3. Overbooking of passengers 1.47 (0.77) 1.57 (0.76) 1.57 (0.67) 1.38 (0.49) 4. No provision of any refreshment

when there is long delay in flight 1.7 (0.88) 1.94 (1.00) 2.29 (0.99) 2.25 (1.15)

5. Flight delay 2.18 (0.95) 2.51 (1.08) 2.61 (1.10) 2.58 (0.97) 6. Non-availability of right

information about flight delay 1.98 (1.02) 2.35 (1.12) 2.37 (1.11) 2.42 (1.14)

Grand Mean 1.71 (0.59) 1.96 (0.65) 2.06 (0.65) 2.05 (0.62)

G1B Response to unreasonably slow

service

7. Delay in refund of cancelled ticket 1.56 (0.88) 1.71 (0.85) 1.86 (0.93) 1.96 (1.00) 8. Rescheduling without prior notice 1.44 (0.81) 1.68 (0.79) 1.76 (0.97) 2.04 (0.69) 9. Provision of food not on time 1.52 (0.83) 1.77 (0.98) 1.61 (0.78) 1.88 (0.74) 10. Delay of baggage delivery 1.56 (0.88) 1.96 (1.03) 2.10 (1.20) 2.33 (1.37) Grand Mean 1.52 (0.66) 1.78 (0.73) 1.82 (0.78) 2.05 (0.73)

G1C Response to other core service failures

11. Mishandling of baggage 1.44 (0.79) 1.63 (0.81) 1.75 (1.02) 1.79 (0.83) 12. Food & Beverage not of high

quality 1.44 (0.81) 1.75 (0.99) 1.59 (0.75) 1.75 (0.61)

13. Missing of baggage 1.31 (0.67) 1.37 (0.65) 1.35 (0.69) 1.46 (0.72) 14. Exchange of baggage 1.36 (0.66) 1.39 (0.66) 1.27 (0.70) 1.29 (0.46) 15. Inconvenience due to non working

of air condition in aircraft 1.31 (0.62) 1.39 (0.72) 1.31 (0.58) 1.63 (0.77)

16. Printing mistake in ticket 1.23 (0.63) 1.3 (0.66) 1.31 (0.62) 1.29 (0.46) Grand Mean 1.35 (0.49) 1.47 (0.53) 1.43 (0.49) 1.53 (0.40)

G2 Employee Response to Customer

Needs and Requests

G2A Response to special needs

customers

17. Mishandling of carry-on items/delicate items

1.24 (0.53) 1.41 (0.68) 1.43 (0.85) 1.58 (0.65)

G2B Response to customer preferences 18. Less leg space 1.56 (0.94) 1.78 (1.17) 1.63 (0.85) 1.92 (1.18) 19. Allow to carry-on items at one

sector & deny the same at another 1.37 (0.73) 1.43 (0.76) 1.45 (0.73) 1.75 (0.90)

Grand Mean 1.46 (0.75) 1.60 (0.83) 1.54 (0.68) 1.83 (0.95)

G2C Response to admitted customer

error

20. Staff shows unwillingness to assist the customer in solving the problem arises due to customer error

1.34 (0.64) 1.45 (0.61) 1.43 (0.67) 1.83 (0.96)

G2D Response to potentially disruptive

others

21. Co-passengers show interrupted 1.4 (0.68) 1.45 (0.67) 1.39 (0.67) 1.67 (0.82)

236

behaviour G3 Unprompted and Unsolicited

Employee Actions

G3A Attention paid to customer

22. Inefficient staff 1.54 (0.81) 1.72 (0.83) 1.86 (0.85) 1.96 (0.91) G3B Truly out-of-the-ordinary

employee behaviour

23. Unfriendly & unhelpful attitude of ground staff members

1.55 (0.73) 1.82 (0.85) 1.90 (0.73) 1.92 (0.83)

24. Unfriendly & unhelpful attitude of crew members

1.46 (0.71) 1.68 (0.81) 1.90 (0.92) 1.88 (0.85)

Grand Mean 1.50 (0.63) 1.75 (0.77) 1.90 (0.76) 1.90 (0.81)

G3C Employee behaviour in the

context of cultural norms

25. Theft of items which are under the scrutiny of airline staff members

1.27 (0.58) 1.45 (0.61) 1.35 (0.56) 1.42 (0.58)

G3D Gestalt evaluation 26. Unfriendly & uncomfortable

ambience for the travellers 1.51 (0.84) 1.8 (0.84) 2.10 ( 0.96) 1.79 (0.88)

237

Table 5.15 Statement Wise Response (Mean and Standard Deviation) to Effect

on Satisfaction on the Basis of Travel Frequency

C. Effect on Satisfaction S.

No.

Type of Service Failure

a.) less than 5

(Mean & SD)

N= 120

b. ) 5-10

(Mean & SD)

N= 110

c.) 10-15

(Mean & SD)

N= 51

d.) above 15

(Mean & SD)

N= 24

G1 Employee Response to Service

Delivery System Failures

G1A Response to unavailable service

1. Cancelled flight without prior notice

4.27 (0.87) 4.55 (0.60) 4.31 (0.81) 4.17 (0.64)

2. Non-availability of seat at departure terminal

4.11 (0.76) 4.25 (0.83) 4.20 (0.85) 3.79 (1.10)

3. Overbooking of passengers 4.21 (0.68) 4.42 (0.63) 4.29 (0.70) 4.04 (1.12) 4. No provision of any refreshment

when there is long delay in flight 4.38 (0.66) 4.47 (0.62) 4.43 (0.64) 4.21 (0.78)

5. Flight delay 4.53 (0.70) 4.51 (0.59) 4.59 (0.67) 4.29 (0.91) 6. Non-availability of right

information about flight delay 4.47 (0.69) 4.5 (0.63) 4.57 (0.70) 4.54 (0.72)

Grand Mean 4.33 (0.47) 4.45 (0.40) 4.40 (0.53) 4.17 (0.66)

G1B Response to unreasonably slow

service

7. Delay in refund of cancelled ticket

4.47 (0.69) 4.51 (0.57) 4.47 (0.78) 4.25 (1.11)

8. Rescheduling without prior notice 4.45 (0.72) 4.61 (0.58) 4.43 (0.76) 4.58 (0.65) 9. Provision of food not on time 4.39 (0.75) 4.49 (0.65) 4.20 (0.89) 3.96 (1.04) 10. Delay of baggage delivery 4.47 (0.67) 4.58 (0.61) 4.43 (0.64) 4.38 (0.88) Grand Mean 4.44 (0.56) 4.55 (0.39) 4.38 (0.57) 4.29 (0.65)

G1C Response to other core service failures

11. Mishandling of baggage 4.53 (0.72) 4.62 (0.54) 4.39 (0.78) 4.54 (0.93) 12. Food & Beverage not of high

quality 4.39 (0.78) 4.72 (0.45) 4.37 (0.80) 4.29 (1.04)

13. Missing of baggage 4.5 (0.73) 4.74 (0.48) 4.47 (0.67) 4.63 (0.65) 14. Exchange of baggage 4.56 (0.71) 4.76 (0.47) 4.37 (0.85) 4.54 (0.93) 15. Inconvenience due to non

working of air condition in aircraft

4.38 (0.79) 4.67 (0.53) 4.41 (0.73) 4.5 (0.98)

16. Printing mistake in ticket 4.43 (0.68) 4.58 (0.56) 4.55 (0.81) 4.29 (0.91) Grand Mean 4.46 (0.53) 4.68 (0.31) 4.43 (0.61) 4.47 (0.76)

G2 Employee Response to

Customer Needs and Requests

G2A Response to special needs customers

17. Mishandling of carry-on items/delicate items

4.38 (0.67) 4.6 (0.55) 4.45 (0.70) 4.38 (0.92)

G2B Response to customer

preferences

18. Less leg space 4 (0.80) 4.17 (0.76) 4.14 (0.75) 4.08 (0.83) 19. Allow to carry-on items at one

sector & deny the same at another 4.41 (0.70) 4.71 (0.51) 4.41 (0.88) 4.29 (0.95)

Grand Mean 4.20 (0.64) 4.44 (0.50) 4.27 (0.70) 4.19 (0.79)

G2C Response to admitted customer

error

20. Staff shows unwillingness to assist the customer in solving the

4.2 (0.82) 4.4 (0.77) 4.18 (1.01) 4.33 (0.96)

238

problem arises due to customer error

G2D Response to potentially

disruptive others

21. Co-passengers show interrupted behaviour

4.12 (0.78) 4.29 (0.71) 4.22 (0.83) 4.17 (0.92)

G3 Unprompted and Unsolicited

Employee Actions

G3A Attention paid to customer

22. Inefficient staff 4.34 (0.70) 4.48 (0.63) 4.29 (0.73) 4.33 (1.01) G3B Truly out-of-the-ordinary

employee behaviour

23. Unfriendly & unhelpful attitude of ground staff members

4.41 (0.80) 4.62 (0.54) 4.43 (0.70) 4.33 (0.87)

24. Unfriendly & unhelpful attitude of crew members

4.45 (0.77) 4.65 (0.52) 4.55 (0.64) 4.46 (0.88)

Grand Mean 4.43 (0.72) 4.63 (0.42) 4.49 (0.60) 4.40 (0.86)

G3C Employee behaviour in the

context of cultural norms

25. Theft of items which are under the scrutiny of airline staff members

4.53 (0.87) 4.76 (0.45) 4.57 (0.70) 4.54 (0.98)

G3D Gestalt evaluation 26. Unfriendly & uncomfortable

ambience for the travellers 4.45 (0.78) 4.74 (0.46) 4.57 (0.76) 4.42 (0.83)

The Tables 5.12 and 5.13, 5.14 and 5.15 provides information about the level of

seriousness, frequency of failures encountered and effect on satisfaction of

respondents on the basis of gender and travel frequency respectively

In category G1A, response to unavailable service, the service failure flight delay is

considered to be highly serious by female (Mean= 4.45, SD= 0.70) as shown in Table

5.12 and to the respondents travelled by air 10 to 15 times in a year (Mean= 4.43,

SD= 0.88) as shown in Table 5.13. But the service failure cancelled flight without

prior notice is considered to be serious by male (Mean= 4.40, SD= 0.90) as shown in

Table 5.12 and to the respondents travelled by air more than 15 times in a year

(Mean= 4.58, SD= 0.50) as shown in Table 5.13.

The highest value of mean score of flight delay indicates that this failure is most

frequently encountered by male (Mean= 2.47, SD= 1.01), female (Mean= 2.27, SD=

1.08) as presented in Table 5.12 and the respondents travelled by air less than 5 times

239

in a year (Mean= 2.18, SD= 0.95), 5 to 10 times in a year (Mean= 2.51, SD= 1.08), 10

to 15 times in a year (Mean= 2.61, SD= 1.10) above 15 times in a year (Mean= 2.58,

SD=0.97) as shown in the Table 5.14.

Non availability of right information about flight delay highly affected the satisfaction

of male (Mean= 4.51, SD= 0.66) as shown in Table 5.12 and to the respondents

travelled by air more than 15 times in a year (Mean= 4.54, SD= 0.72) as presented in

Table 5.15; flight delay highly effected the satisfaction of female (Mean= 4.61, SD=

0.60) as presented in Table 5.12 and the respondents travelled by air less than 5 times

in a year (Mean= 4.53, SD= 0.70) and 10 to 15 times in a year (Mean=4.59, SD=

0.67). The satisfaction of respondents travelled by air 5 to 10 times in a year (Mean=

4.55, SD= 0.60) highly affected by the service failure cancelled flight without prior

notice as shown in Table 5.15.

In category G1B, response to unreasonably slow service, the service failure

rescheduling without prior notice is considered to be highly serious by female (Mean=

4.56, SD= 0.64), male (Mean= 4.47, SD= 0.72) as shown in Table 5.12 and the

respondents travelled by air less than 5 times in a year (Mean= 4.48, SD= 0.73), 5 to

10 times in a year (Mean= 4.5, SD= 4.48), 10 to 15 times in a year (Mean= 4.51, SD=

0.70) and above 15 times in a year (Mean= 4.63, SD= 0.49) as shown in Table 5.13.

The delay of baggage delivery is more frequently encountered by male (Mean= 1.94,

SD= 1.13), female (Mean= 1.70, SD= 0.91) as presented in Table 5.12 and by the

respondents travelled by air less than 5 times in a year (Mean= 1.56, SD= 0.88), 5 to

10 times in a year (Mean= 1.96, SD= 1.03), 10 to 15 times in a year (Mean= 2.10,

SD= 1.20) and above 15 times in a year (Mean= 2.33, SD= 1.37) as presented in

Table 5.14.

240

The satisfaction of male (Mean= 4.52. SD= 0.72) as shown in Table 5.12 and the

respondents travelled by air 5 to 10 times in a year (Mean= 4.61, SD= 0.58) and

above 15 times in a year (Mean= 4.58, SD= 0.65) as shown in Table 5.15 is highly

affected by the service failure rescheduling without prior notice. The delay in refund

of cancelled ticket highly effected the satisfaction of female (Mean= 4.51, SD= 0.67)

as presented in Table 5.12 and the respondents travelled by air less than 5 times in a

year (Mean= 4.47, SD= 0.69) and 10 to 15 times in a year (Mean= 4.47, SD= 0.78) as

shown in Table 5.15.

In category G1C, response to other core service failures, the service failure missing of

baggage (Mean= 4.68, SD= 0.59) is considered to be most serious by male (Mean=

4.69, SD= 0.62), female (Mean= 4.65, SD= 0.53) as shown by Table 5.12,

respondents travelled by air less than 5 times in a year (Mean= 4.68, SD= 0.63), 5 to

10 times in a year (Mean= 4.70, SD= 0.52) and above 15 times in a year (Mean= 4.67,

SD= 0.56). Respondents travelled by air 5 to 10 times in year (Mean= 4.70, SD=

0.60) and 10 to 15 times in a year (Mean= 4.65, SD= 0.66) as presented in Table 5.13

are considered the service failure exchange of goods as most serious.

Mishandling of baggage is most frequently encountered by female (Mean= 1.53, SD=

0.82) as presented by Table 5.12 and the respondents travelled by air less than 5 times

in a year (Mean= 1.44, SD= 0.79), 10 to 15 times in a year (Mean= 1.75, SD= 1.02)

above 15 times in a year (Mean= 1.79, SD= 0.83) as shown in Table 5.14. Male

(Mean= 1.69, SD= 0.93) as shown in Table 5.12 and the respondents travelled by air

less than 5 times in a year (Mean= 1.44, SD= 0.81) and 5 to 10 times in year (Mean=

1.75, SD= 0.99) as shown in Table 5.14 are most frequently encountered the service

failure food and beverage not of high quality.

241

Missing of baggage highly affected the satisfaction of female (Mean= 4.61, SD= 0.69)

as shown in Table 5.12 and the respondents travelled by air above 15 time in a year

(Mean= 4.63, SD= 0.65) as presented in Table 5.15. But the exchange of baggage

highly effected the satisfaction of male (Mean= 4.60, SD= 0.70) as presented in Table

5.12 and the respondents travelled by air less than 5 times in a year (Mean= 4.56, SD=

0.71) and 5 to 10 times in a year (Mean= 4.76, SD= 0.47) as shown in Table 5.15. The

service failure printing mistake on ticket highly effected the satisfaction of

respondents travelled by air 10 to 15 times in a year (Mean= 4.55, SD= 0.81) as

shown in Table 5.15.

In category G2A, response to special needs customers, the female (Mean= 4.49, SD=

0.64) considered the service failure mishandling the carry on items is more serious

than male (Mean= 4.42, SD= 0.68) as presented in Table 5.12. And the respondents

travelled by air 10 to 15 times in a year (Mean= 4.55, SD= 0.64) considered it more

serious than other respondents as presented in Table 5.13.

Male (Mean= 1.40, SD= 0.69) are more frequently encountered and their satisfaction

(Mean= 4.48, SD= 0.68) is highly effected by the service failure mishandling of carry

on items than female as shown in Table 5.12. Respondents travelled by air above 15

times in a year (Mean= 1.58, SD= 0.65), as shown in Table 5.14, are more frequently

encountered the service failure mishandling of carry on items and the failure is highly

effected the satisfaction of the respondents travelled by air 5 to 10 times in a year

(Mean=4.60, SD= 0.55) as shown in Table 5.15.

In category G2B, response to customer preferences, male (Mean= 4.37, SD= 0.67) as

presented in Table 5.12 and the respondents travelled by air above 15 times in a year

(Mean= 4.54, SD= 0.59), as shown in Table 5.13, are considered the service failure

allow to carry-on items at one sector and deny the same at another is very serious.

242

The service failure less leg space in the aircraft is most frequently encountered by

male (Mean= 1.71, SD= 1.05) as shown in Table 5.12 and the respondents travelled

by air above 15 times in a year (Mean= 1.92, SD= 1.18) as shown in Table 5.14.

The equal mean score value of male (Mean= 4.51, SD= 0.71) and female (Mean=

4.51, SD= 0.71) as presented in Table 5.12 indicates that the service failure allow to

carry-on items at one sector and deny the same at another equally effected the

satisfaction of both. And the satisfaction is highly effected by the service failure allow

to carry-on items at one sector and deny the same at another of respondents travelled

by air 5 to 10 times in year (Mean= 4.71, SD= 0.51) as shown in Table 5.15.

In category G2C, response to admitted customer error, male (Mean= 4.01, SD= 3.98)

as shown in table 5.12 and respondents travelled by air 5 to 10 times in a year (Mean=

4.15, SD= 0.91) as shown in Table 5.13 considered the service failure staff shows

unwillingness to assist the customer in solving the problem arises due to customer

error is highly serious. This service failure is more frequently encountered by males

(Mean= 1.46, SD= 0.70) as presented in Table 5.12 and the respondents travelled by

air above 15 times in a year (Mean= 1.83, SD= 0.96) as shown in Table 5.14. The

satisfaction is highly effected by the above mentioned failure of male (Mean= 4.28,

SD= 0.78) as shown in Table 5.12 and the respondents travelled by air 5 to 10 times

in a year (Mean= 4.29, SD= 0.71) as presented in Table 5.15.

In the category G2D, response to potentially disruptive others, for female (Mean=

4.01, SD= 0.79) as shown in Table 5.12 and the respondents travelled by air 5 to 10

times in a year (Mean= 4.06, SD= 0.91) as shown in Table 5.13 considered the service

failure co-passengers show interrupted behaviour to be very serious than other

respondents. Male (Mean= 1.46, SD= 0.70) as presented in Table 5.12 and the

respondents travelled by air above 15 times in a year (Mean= 1.67, SD= 0.82) as

243

shown in Table 5.14 most frequently encountered by this service failures. This failure

is highly effected the satisfaction of female (Mean= 4.25, SD= 0.76) as shown in

Table 5.12 and the respondents travelled by air 5 to 10 times in a year (Mean= 4.29,

SD= 0.71) as presented in Table 5.15 than other respondents.

In the category G3A, attention paid to customer, the service failure inefficient staff is

considered most serious by the male (Mean= 4.04, SD= 0.94) as presented in Table

5.12 and the respondents travelled by air 5 to 10 times in a year (Mean=4.29, SD=

0.76) as shown in Table 5.13. It is more frequently encountered by male (Mean= 1.73,

SD= 0.86) as shown in Table 5.12 and the respondents travelled by air above 15 times

in a year (Mean= 1.96, SD= 0.91) as presented in Table 5.14. This failure is highly

effected the satisfaction of female (Mean= 4.43, SD= 0.68) as presented in Table 5.12

and the respondents travelled by air 5 to 10 times in a year (Mean= 4.48, SD= 0.63) as

shown in Table 5.15.

In the category G3B, truly out-of-ordinary employee behaviour, the highest mean

value of female (Mean= 4.51, SD= 0.70) as shown in Table 5.12 and the respondents

travelled by air above 15 times in a year (Mean=4.25, SD= 0.74) as shown in Table

5.13 of service failure unfriendly and unhelpful attitude of ground staff members

showed that they are very serious towards this failure. And male (Mean= 4.39, SD=

0.79) as presented in Table 5.12 and respondents travelled by air less than 5 times in a

year (Mean= 4.33, SD= 0.77), 5 to 10 times in a year (Mean= 4.54, SD= 0.67) and 10

to 15 times in a year (Mean= 4.49, SD= 0.70) are considered the service failure

unfriendly and unhelpful attitude of crew members very serious as presented in Table

5.13.

Male (Mean= 1.77, SD=0.82) as shown in Table 5.12 and the respondents travelled by

air less than 5 times in a year (Mean= 1.55, SD= 0.73), 5 to 10 times in a year (Mean=

244

1.82, SD= 0.85) and above 15 times in a year (Mean= 1.92, SD=0.83) are frequently

encountered the service failure unfriendly and unhelpful attitude of ground staff

members as shown in Table 5.14. Equal value of mean scores of both failures

included in category G3B indicated that respondents travelled by air 10 to 15 times in

a year (Mean=1.90, SD= 0.73 and Mean= 1.90, SD= 0.92) equally encountered by

these failures as shown in Table 5.14.

Unfriendly and unhelpful attitude of crew members highly effected the satisfaction of

male (Mean= 4.49, SD= 0.70), female (Mean= 4.63, SD= 0.63) as presented in Table

5.12 and the respondents travelled by air less than 5 times in a year (Mean= 4.45, SD=

0.77), 5 to 10 times in a year (Mean= 4.65, SD= 0.52), 10 to 15 times in a year

(Mean= 4.55, SD= 0.64) and above 15 times in a year (Mean=4.46, SD= 0.88) as

shown in Table 5.14. The satisfaction of female (Mean= 4.60, SD= 0.70) as shown in

Table 5.12 and the respondents travelled by air 5 to 10 times in a year (Mean= 4.74,

SD= 0.46) is highly effected by the above mentioned failure as shown in Table 5.15.

In the category G3C, employee behaviour in the context of cultural norms, male

(Mean= 4.62, SD= 0.65) as shown in Table 5.12 and the respondents travelled by air 5

to 10 times in a year (Mean= 4.65, SD= 0.61) as shown in Table 5.13 are considered

the failure theft of items which are under the scrutiny of airline staff members very

serious. Male (Mean= 1.36, SD= 0.60) as shown in Table 5.12 and the respondents

travelled by air 5 to 10 times in a year (Mean= 1.45, SD= 0.61) are more frequently

encountered this failure as shown in Table 5.14. This failure is highly effected the

satisfaction of female (Mean= 4.66, SD= 0.66) as shown in Table 5.12 and the

respondents travelled by air 5 to 10 times in a year (Mean=4.74, SD= 0.46) as shown

in Table 5.15.

245

In the category G3D, Gestalt evaluation, female (Mean=4.31, SD= 0.85) as shown in

Table 5.12 and the respondents travelled by air 5 to 10 times in a year as shown in

Table 5.13 (Mean=4.45, SD= 0.81) are considered the failure unfriendly and

uncomfortable ambience for traveller is very serious. The highest mean score of

female (Mean= 1.69, SD= 0.89) as shown in Table 5.12 and the respondents travelled

by air 10 to 15 times in a year (Mean=2.10, SD= 0.96) are more frequently

encountered by this failure as shown in Table 5.14. The satisfaction of female (Mean=

4.60, SD= 0.70) as shown in Table 5.12 and the respondents travelled by 5 to 10 times

in a year as presented in Table 5.15 is highly effected by the failure unfriendly and

uncomfortable ambience for the travellers.

Table 5.16- Descriptive Statistics (Mean and Standard Deviation) of Three

Groups N=305

Group Statements A- Level of

Seriousness

Mean (SD)

B- Failure

Frequency

Mean(SD)

C- Effect on

Satisfaction

Mean (SD)

G1 Employee Response to Service Delivery System Failures

4.32 (0.44) 1.67 (0.54) 4.46 (0.43)

G2 Employee Response to Customer Needs and Requests

4.09 (0.52) 1.47 (0.58) 4.31 (0.53)

G3 Unprompted and Unsolicited Employee Actions

4.35 (0.58) 1.63 (0.59) 4.52 (0.56)

Table 5.16 indicated that respondents are more serious towards the unprompted and

unsolicited employee actions and this also highly effected the satisfaction where as

the service delivery system failures are most frequently encountered by respondents.

246

Comparison of Failure Frequency in Percentage

45.5

27.3 27.3

61.54

19.23 19.23

010203040506070

Employee Response toService Delivery System

Failures

Employee Response toCustomer Needs and

Requests

Unprompted andUnsolicited Employee

Actions

G1 G2 G3

Bitner et al (1990) Failure Frequency (Airlines) (%)

Present Study Failure Frequency (%)

Fig 5.2 Shows the Comparison of Failure Frequency in Percentage (Study II)

247

Table 5.17 Comparison of Failure Frequency in Percentage

Group Statements Bitner et al (1990)

Failure Frequency

(Airlines) (%)

Present Study

Failure Frequency

(%)

G1 Employee Response to

Service Delivery System

Failures

45.5 61.54

G2 Employee Response to

Customer Needs and

Requests

27.3 19.23

G3 Unprompted and

Unsolicited Employee

Actions

27.3 19.23

5.4 DESCRIPTIVE STATISTICS (MEAN AND STANDARD DEVIATION) OF

CONSUMER COMPLAINT BEHAVIOUR (CCB) INTENTIONS OF AIRLINE

PASSENGERS

The demographic composition of complainants (N=201) and non-complainants

(N=104) is show in Table 5.18. It is clear from the table that out of 201 complainants,

134 (66.67%) are male and 67 (33.33%) are female. Majority of the respondents fall

in the age group 20 to 40 i.e 144 constituting 71.64% followed by 40 to 60 i.e. 37

(18.41%), 14 (6.96%) respondents fall in age group less than 20 years and 6

respondents (2.99%) belongs to above 60 years of age group. 68 respondents i.e.

33.83% belongs to the income group Rs. 20,000 to Rs. 40,000, 56 respondents i.e.

27.86% belongs to the income group less than Rs. 20,000, 43 (21.39%) falls in

income group Rs. 40,000 to Rs. 60,000 and 34 respondents (16.92%) have the income

248

above Rs. 60,000. The table presents 79 respondents i.e. 39.30% travelled by air 5 to

10 times in a year, 74 (36.82%) travelled less than 5 times in a year, 34 respondents

(16.92%) travelled by 10 to 15 times in a year and 14 respondents (6.96%) travelled

above 15 times in a year by air.

Table 5.18 Demographic Composition of Complainants and Non-Complainants

S.No. Variable Complainants,

N= 201

Non-Complainants,

N=104

No. of

respondents

Percentage No. of

respondents

Percentage

1. Gender (a.) Male 134 66.67 67 64.42 (b.) Female 67 33.33 37 35.58 2. Age (in years) (a.) less than 20 14 6.96 06 5.77 (b.) 20-40 144 71.64 59 56.73 (c.) 40-60 37 18.41 27 25.96 (d.) above 60 06 2.99 12 11.54 3. Income (in Rs.) (a.) less than

20,000 56 27.86 21 20.19

(b.) 20,000-40,000

68 33.83 30 28.85

(c.) 40,000-60,000 43 21.39 25 24.04 (d.) above 60,000 34 16.92 28 26.92 4. Travel

Frequency

(a.) less than 5 74 36.82 46 44.23 (b.) 5-10 79 39.30 31 29.80 (c.) 10-15 34 16.92 17 16.35 (d.) above 15 14 6.96 10 9.62

To study the airline passenger’s complaint behaviour intentions, a 10-items scale

developed by Singh (1988) to measure CCB intentions categorized into three

dimensions: voice, private and third party is used. The intentions data were obtained

on a most likely/least likely scale (coded 1 through 6).

249

Table 5.19- Statement wise response to Consumer Complaint Behaviour (CCB)

Intentions

N=305

CCB

Intentions

Statements Mean SD

1. Forget about the incident and do nothing 4.12 1.33

2. Definitely complain to the airline staff members

3.85 1.16

VOICE

4. Complain to the airline staff members and ask them to take care of your problem

3.90 1.09

Grand Mean 3.96 0.80

3. Decide not to travel by that airline 3.62 1.16

5. Speak to your friends and relatives about your bad experience

4.02 1.23

PRIVATE

6. Convince your friends and relatives not to travel by that airline

3.54 1.29

Grand Mean 3.73 0.97

7. Complain to a consumer agency and ask them to make the airline take care of your problem

3.07 1.10

8. Write a letter to the local newspaper about your bad experience

2.72 1.06

9. Report to the consumer agency so that they can warn other consumers

2.78 1.09

THIRD

PARTY

10. Take some legal action against the airline

2.55 1.08

Grand Mean 2.78 0.85

250

Table 5.20- Descriptive Statistics (Mean and Standard Deviation) of CCB

Intentions of Complainants and Non-Complainants

CCB

Intentions

Complainants, N=201

Mean (SD)

Non-Complainants, N=104

Mean (SD)

VOICE 4.18 (0.74) 3.54 (0.74)

PRIVATE 3.94 (0.93) 3.31 (0.90)

THIRD

PARTY

2.92 (0.87) 2.51 (0.73)

Table 5.21 Independent t-test Between Complainants and Non Complainants

Complainants N=201 Non-complainants N=104 CCB

Intentions t-value Sig. (2-tailed) t-value Sig. (2-tailed)

VOICE 7.214 .000 7.198 .000

PRIVATE 5.644 .000 5.705 .000

THIRD

PARTY

4.073 .000 4.304 .000

* at 5% level of significance

Table 5.19 describes the descriptive statistics of airline passenger’s complaint

behaviour intentions. The results show that mean value for voice intentions (Mean=

3.96, SD= 0.80) is highest than private (Mean= 3.93, SD= 0.97) and third party

(Mean= 2.78, SD= 0.85) intentions. It means that the respondents are actually

engaged in voice actions.

There are 66% of the respondents complaint to the airline about the service failure and

34% of the respondents did not complaint. The highest mean score of voice intention

251

(Mean=4.18, SD= 0.74) of complainants with respect to other two intentions i.e.

private and third party (Table 5.20) show that complainants preferred voice actions.

Table 5.21 reveals that there is no significant difference between the voice, private

and third party intentions of complainants and non-complainants at 5% level of

significance.

Table 5.22 Comparison of Descriptive Statistics (Mean and Standard Deviation)

of CCB intentions of Complainants on the Basis of Gender Complainants

N=201

Males, N=134 Females, N= 67 Consumer Complaint Behaviour Intentions

Mean SD Mean SD

1. Forget about the incident and do nothing

2.63 1.28 2.66 1.21

2.Definitely complain to the airline staff members

4.10 1.17 4.25 0.89

VOICE

4. Complain to the airline staff members and ask them to take care of your problem

4.18 1.08 4.18 0.82

Grand Mean 3.64 0.75 3.70 0.66

3. Decide not to travel by that airline 3.61 1.18 4.01 0.95

5. Speak to your friends and relatives about your bad experience

4.22 1.19 4.30 1.09

PRIVA

TE

6. Convince your friends and relatives not to travel by that airline

3.75 1.34 3.99 1.13

Grand Mean 3.86 0.97 4.10 0.83

7. Complain to a consumer agency and ask them to make the airline take care of your problem

3.16 1.16 3.27 1.10

8. Write a letter to the local newspaper about your bad experience

2.87 1.16 2.90 0.97

9. Report to the consumer agency so that they can warn other consumers

2.96 1.14 2.96 0.93

10. Take some legal action against the airline

2.62 1.16 2.72 1.08

Grand Mean 2.90 0.92 2.96 0.77

252

Table 5.23 Comparison of Descriptive Statistics (Mean and Standard Deviation)

of CCB Intentions of Complainants On the Basis of Age Complainants, N=201

Age less than 20,

N=14

Age 20 to 40,

N=144

Age 40 to 60,

N=37

Age above 60,

N=6

CCB INTENTIONS

Mean SD Mean SD Mean SD Mean SD

1. Forget about the incident and do nothing

2.43 0.85 2.69 1.31 2.46 1.07 3 1.67

2.Definitely complain to the airline staff members

4.14 0.53 4.12 1.16 4.32 1.00 4 1.10

VOICE

4. Complain to the airline staff members and ask them to take care of your problem

4.21 0.58 4.12 1.04 4.38 0.95 4.33 0.82

Grand Mean 3.60 0.47 3.64 0.78 3.72 0.55 3.78 0.78

3. Decide not to travel by that airline

3.93 0.62 3.76 1.13 3.46 1.19 4.67 0.82

5. Speak to your friends and relatives about your bad experience

4.14 0.86 4.24 1.18 4.24 1.23 4.83 0.75

PRIVATE

6. Convince your friends and relatives not to travel by that airline

3.79 0.97 3.78 1.29 3.95 1.41 4.33 0.82

Grand Mean 3.95 0.61 3.93 0.95 3.88 0.99 4.61 0.49

7. Complain to a consumer agency and ask them to make the airline take care of your problem

3.21 0.80 3.18 1.20 3.16 1.04 3.83 0.98

8. Write a letter to the local newspaper about your bad experience

3.14 0.66 2.77 1.11 3.03 1.14 3.83 0.75

9. Report to the consumer agency so that they can warn other consumers

3 0.88 2.94 1.08 2.92 1.14 3.5 1.05

THIRD

PARTY

10. Take some legal action against the airline

2.93 0.83 2.59 1.11 2.76 1.28 2.83 1.33

Grand Mean 3.07 0.68 2.87 0.88 2.97 0.89 3.5 0.82

253

The Tables 5.22 and 5.23 provides information about the complaint behaviour

intentions of male, female and the respondents divided in four age groups i.e. less

than 20 years, 20 to 40 years and 40 to 60 years and above 60 years among

complainants. It has been seen that female in comparison with male and the

respondents fall in the age group above 60 years got the highest mean score of voice,

private and third party intentions which indicated that these respondents are preferred

to complaint with the specified intentions.

In ‘voice’ behaviour intentions, male (Mean=4.18, SD= 1.08) and the respondents

belongs to the age group 40 to 60 years (Mean=4.38, SD= 0.95) are highly intended to

complain to the airline staff members and ask them to take care of the problem where

as female (Mean= 4.25, SD= 0.89) are highly intended to definitely complaint to the

airline staff members about the service failure.

In ‘private’ behaviour intentions, the highest mean value of male (Mean= 4.22, SD=

1.190), female (Mean= 4.30, SD= 1.09) and the respondents belong to the age group

above 60 years (Mean= 4.83, SD= 0.75) show that they are highly intended to speak

to friends and relatives about their bad experience.

In ‘third party’ behaviour intentions, the highest average values of male (Mean= 3.16,

SD= 1.16), female (Mean= 3.27, SD= 1.10) and the respondents belongs to the age

group above 60 years (Mean= 3.83, SD= 0.98) reveals that they are highly intended to

complain to a consumer agency and ask them to make the airline take care of their

problem.

254

5.5 DESCRIPTIVE STATISTICS (MEAN AND STANDARD DEVIATION)

FOR AIRLINE PASSENGER’S PERCEIVED JUSTICE

To study the airline passenger’s perceived justice after experiencing the service

failure, a 12-item scale taken from Maxham III and Netemeyer, 2003 further divided

into three i.e distributive, procedural and interactional justice. Four-items are included

in each construct. For each item, the respondents used a 7-point Likert scale to

respond to the statements with 1 being “Very Strongly Disagree” to 7 being “Very

Strongly Agree”.

Table 5.24 Statement wise response to Perceived Justice of Complainants

Complainants,

N=201

Customer Perceived Justice

Mean SD a. The incident caused me problems, the airline effort to fix it resulted in a very positive outcome

2.59 1.14

b. The final outcome I received from airline was fair, given the time and hassle

2.86 1.02

c. Inconvenience caused by the problem, the outcome I received from airline was fair

2.99 0.96

Distribution

Justice

d. The service recovery outcome that I received in response to the problem was more than fair

3.00 0.94

Grand Mean 2.86 0.82 a. Despite the hassle caused by the problem, the airline responded fairly and quickly

3.05 1.00

b. I feel airline responded in a timely fashion to the problem

3.10 1.01

c. I believe airline has fair policies & practices to handle problems

3.25 1.00

Procedural

Justice

d. With respect to its policies & procedures, the airline handled the problem in a fair manner

3.11 1.00

Grand Mean 3.13 0.78 a. In dealing with my problem, the airline personnel treated me in a courteous manner

3.40 1.19

b. During their effort to fix my problem, the airline employees showed a real interest in trying to be fair

3.29 1.14

c. The airline employees worked as hard as possible for me during the recovery effort

3.24 0.98

Interactional

Justice

d. The airline employees were honest and ethical in dealing with me during their fixing of my problem

3.28 1.02

Grand Mean 3.30 0.90

It has been seen from the Table 5.24 that there are 65% of the respondents who made

complaint to the airline. The highest mean score value of interactional justice (Mean=

255

3.30, SD= 0.90) reveals that the complainants are strongly agree with the interactional

justice of the airline.

Table 5.25 Statement wise response to Perceived Justice of Complainants on the

Basis of Gender

N= 201

Males, N= 134 Females, N= 67 Customer Perceived Justice

Mean SD Mean SD a. The incident caused me problems, the airline effort to fix it resulted in a very positive outcome

2.70 1.21 2.37 0.95

b. The final outcome I received from airline was fair, given the time and hassle

3.00 1.05 2.57 0.91

c. Inconvenience caused by the problem, the outcome I received from airline was fair

3.04 0.92 2.88 1.04

Distribution

Justice

d. The service recovery outcome that I received in response to the problem was more than fair

3.04 0.96 2.93 0.89

Grand Mean 2.95 0.85 2.69 0.72 a. Despite the hassle caused by the problem, the airline responded fairly and quickly

3.08 1.00 2.99 1.01

b. I feel airline responded in a timely fashion to the problem

3.18 1.03 2.96 0.96

c. I believe airline has fair policies & practices to handle problems

3.28 1.01 3.21 0.99

Procedural

Justice

d. With respect to its policies & procedures, the airline handled the problem in a fair manner

3.16 1.05 3.04 0.91

Grand Mean 3.17 0.81 3.05 0.71 a. In dealing with my problem, the airline personnel treated me in a courteous manner

3.45 1.19 3.31 1.18

b. During their effort to fix my problem, the airline employees showed a real interest in trying to be fair

3.31 1.13 3.27 1.16

c. The airline employees worked as hard as possible for me during the recovery effort

3.29 1.01 3.13 0.92

Interactional

Justice

d. The airline employees were honest and ethical in dealing with me during their fixing of my problem

3.34 1.08 3.18 0.89

Grand Mean 3.35 0.91 3.13 0.66

256

Table 5.26 Statement wise response to Perceived Justice of Complainants on the

Basis of Age

N=201

Age less than 20,

N=14

Age 20 to 40,

N=144

Age 40 to 60,

N=37

Age above 60,

N=6

Consumer Justice

Mean SD Mean SD Mean SD Mean SD

a. The incident caused me problems, the airline effort to fix it resulted in a very positive outcome

2.21 0.89 2.70 1.21 2.35 0.92 2.33 0.52

b. The final outcome I received from airline was fair, given the time and hassle

2.36 1.08 2.92 1.02 2.78 1.00 2.83 0.75

c. Inconvenience caused by the problem, the outcome I received from airline was fair

2.64 1.15 3.03 0.96 2.81 0.81 3.67 1.21

Distributive

Justice

d. The service recovery outcome that I received in response to the problem was more than fair

2.86 0.95 3.09 0.93 2.78 0.92 2.67 1.21

Grand Mean 2.52 0.87 2.94 0.84 2.68 0.68 2.88 0.72

a. Despite the hassle caused by the problem, the airline responded fairly and quickly

3.0 1.11 3.08 0.95 2.84 0.90 3.83 2.04

b. I feel airline responded in a timely fashion to the problem

2.86 1.17 3.16 0.99 3.0 1.03 3.00 1.26

c. I believe airline has fair policies & practices to handle problems

3.07 1.07 3.39 0.99 2.81 0.88 3.17 1.17

Procedural

Justice

d. With respect to its policies & procedures, the airline handled the problem in a fair manner

2.71 1.07 3.20 1.03 3.0 0.88 2.83 0.41

Grand Mean 2.91 0.82 3.21 0.78 2.91 0.71 3.21 0.93

Interactional

Justice

a. In dealing with my problem, the airline personnel treated me in a courteous manner

3.21 1.12 3.44 1.23 3.32 1.13 3.5 0.84

257

b. During their effort to fix my problem, the airline employees showed a real interest in trying to be fair

3.43 1.16 3.35 1.14 2.97 0.90 3.5 2.07

c. The airline employees worked as hard as possible for me during the recovery effort

3.21 0.97 3.33 1.0 2.92 0.89 3.17 0.98

d. The airline employees were honest and ethical in dealing with me during their fixing of my problem

3.21 0.97 3.35 1.0 3.11 1.10 3.00 1.10

Grand Mean 3.27 0.95 3.37. 0.91 3.08 0.78 3.29 1.16

Among the complainants, there are 66.67% of male and 33.33% of female. Both male

(Mean=3.35, SD= 0.91) and female (Mean= 3.13, SD= 0.66) and also respondents

belong to the age group 20 to 40 years are strongly agree with the interactional justice

of airlines (Table 5.25 and Table 5.26). But the equal mean values of procedural

justice of the respondents belong to age group 20 to 40 years (Mean=3.21, SD= 0.78)

and above 60 years (Mean=3.21, SD= 0.93) that they are satisfied with this justice.

258

Recovery Actions

93

25

3212

117

2615 9 8 2

Apology Corrected problem Explanation provided

Immediate Action Did nothing Took responsibility

Followed up Redirected the problem Compensation

Exceptional good treatment

Fig 5.3 Show the Recovery Actions taken by Airlines after Service Failure

259

5.6 DIMENSION RECOVERY STRATEGIES

Table 5.27 Recovery strategies used by airlines after service failure

Recovery Actions Frequency Frequency (%) Ranking of

frequency of use

Apology 93 27.4 2

Corrected problem 25 7.37 5

Explanation provided 32 9.4 3

Immediate Action 12 3.5 6

Did nothing 117 34.5 1

Took responsibility 26 7.7 4

Followed up 15 4.4 7

Redirected the problem 9 2.7 8

Compensation 8 2.4 9

Exceptional good treatment 2 0.6 10

Table 5.27 shows the list of ten recovery actions, the ones that the airline used to

rectify their particular problem, with each respondent (complainant N=201)

mentioning on an average two actions. 34.5% of respondents reported that the airline

did nothing to the problem faced by them, 27.4% of the respondents reported the

apology was made by the airline then explanation provided to the problem (9.4%),

7.7% of the respondents told that the airline took responsibility of the problem and

only 7.37% of the respondents told that the problem was corrected by the airline.

3.5% of the respondents reported that the airline took immediate action to solve the

problem. 2.7% of the respondents told that the airline redirected the problem and

260

2.4% of the respondents get compensation and only 0.6% of the respondents received

exceptional good treatment.

As far as the expectations of the respondents regarding recovery strategies should be

taken by the airline, when the service failure is encountered by them. Generally

respondents mark all the recovery strategies, it is concluded that they did not reply

rationally so the results of that section of the questionnaire is not reported.

5.7 DIMENSION OF PERCEIVED JUSTICE OF AIRLINE PASSENGERS

To study the perceived justice of airline passengers after experiencing service failure,

a 12-items scale of perceived justice of consumers (Maxham III and Netemeyer,

2003) divided into three- Distributive justice (4-items), Procedural justice (4-items)

and Interactional justice (4-items) is taken. For each item, the respondents used a 7-

point Likert scale to respond to the statements with 1 being “Very Strongly Disagree”

to 7 being “Very Strongly Agree”.

RELIABILITY

Reliability is a measure of consistency between multiple measurements of a variable.

The consistency of these measures indicates homogeneity of the variable measuring

the same construct. The items should be highly correlated to obtain a reliable measure

for the construct (Hair et al, 1998). Cronbach’s Alpha is a test designed to measure

this reliability. The correlation is indicated by a score greater than 0.70 (Hair et al,

1998). This research uses Cronbach’s Alpha to test for reliability.

All 12-items, four in each construct i.e. distributive, procedural and interactional

justice reported a high degree of consistency, homogeneity and reliability with

261

Cronbach’s Alpha in excess of 0.70 at 0.820, 0.781 and 0.850 respectively (Table

5.28).

Table 5.28 Reliability of Perceived Justice Construct of Airline Passengers

Construct Cronbach’s Alpha N

Distributive Justice 0.820 201

Procedural Justice 0.781 201

Interactional Justice 0.850 201

ADEQUACY AND SCALE PURIFICATION

The face and content validity of the instrument was duly attested. Kaiser-Meyer-Olkin

(KMO) is a measure of sampling adequacy to test if the distribution of values is

adequate for conducting Factor Analysis. Values between 0.50 and 1.0 indicate that

Factor Analysis is appropriate (Malhotra, 2005). Further, the Bartlett’s Test of

Sphericity also suggests that the intercorrelation matrix is factorable and therefore

factor analysis can be applied to the current data. The Kaiser-Meyer-Olkin values for

the aforesaid variables as depicted in Table 5.29 indicate the high degree of construct

validity.

Table 5.29 Kaiser-Meyer-Olkin and Bartlett's Test of Sphericity

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .869

Bartlett's Test of Sphericity Approx. Chi-Square 1123.056

df 66

Significance .000

262

FACTOR ANALYSIS

A factor analysis was performed to analyse the interrelationships of multiple variables

and to explain these variables in terms of their underlying commonalities as univariate

factors. The goal is to condense the variables into a set of variables for further

analysis with minimal data loss (Hair et al, 1998). Principal component matrix was

used to account for the full variance in the data set. Variables reporting factor

loadings above 0.50 are deemed to be significant (Hair et al, 1998).

Additionally, Eigen values are measured to determine the number of factors to be

retained. Only factors returning an Eigen value over 1 are deemed significant.

In the present study, factor analysis was performed on 12 statements. Table 5.29

summarises the twelve perceived justice variables into three factors that determines

the perceived justice of airline passengers which explains 65.684% of the total

variance. From the analysis of these results, it can be said that the factors returned

from this process have minimum factor loadings of 0.605, with a range between 0.605

and 0.829, demonstrating a high degree of reliability.

The first factor i.e. Distributive Justice, comprises of four statements. Statements ‘The

incident caused me problems, the airline effort to fix it resulted in a very positive

outcome’, ‘The final outcome I received from airline was fair, given the time and

hassle’, ‘Inconvenience caused by the problem, the outcome I received from airline

was fair’, ‘The service recovery outcome that I received in response to the problem

was more than fair’ are most important with factor loading values of 0.703, 0.812,

0.774 and 0.633 respectively. This factor explained 46.298% of variance.

The second factor i.e. Procedural Justice consist of four statements. Statements

‘Despite the hassle caused by the problem, the airline responded fairly and quickly’, ‘I

263

feel airline responded in a timely fashion to the problem’, ‘I believe airline has fair

policies & practices to handle problems’ and ‘With respect to its policies &

procedures, the airline handled the problem in a fair manner’ with factor loading

values of 0.605, 0.713, 0.775 and 0.692 respectively. The factor identified 11.191% of

variance.

The third factor i.e. Interactional Justice comprises of four statements. Statements ‘In

dealing with my problem, the airline personnel treated me in a courteous manner’,

‘During their effort to fix my problem, the airline employees showed a real interest in

trying to be fair’, ‘The airline employees worked as hard as possible for me during the

recovery effort’, ‘The airline employees were honest and ethical in dealing with me

during their fixing of my problem’ with factor loading values of 0.829, 0.814, 0.736

and 0.733 respectively. The factor identified 8.194% of variance.

These results show strong support for perceived justice of airline passengers as a

multidimensional construct consisting of distributive, procedural and interactional

justice.

264

Table 5.30 Summary of Results from Scale Purification

Name of the

Factor

Factor Wise Dimensions Factor

Loading

Values

Communalities Eigen

Values

% of

Variance

a. The incident caused me problems, the airline effort to fix it resulted in a very positive outcome

0.703 0.600

b. The final outcome I received from airline was fair, given the time and hassle

0.812 0.733

c. Inconvenience caused by the problem, the outcome I received from airline was fair

0.774 0.702

1. Distributive Justice

d. The service recovery outcome that I received in response to the problem was more than fair

0.633 0.464

5.556 46.298%

a. Despite the hassle caused by the problem, the airline responded fairly and quickly

0.605 0.566

b. I feel airline responded in a timely fashion to the problem

0.713 0.674

c. I believe airline has fair policies & practices to handle problems

0.775 0.636

2. Procedural

Justice

d. With respect to its policies & procedures, the airline handled the problem in a fair manner

0.692 0.576

1.343 11.191 %

a. In dealing with my problem, the airline personnel treated me in a courteous manner

0.829 0.732

b. During their effort to fix my problem, the airline employees showed a real interest in trying to be fair

0.814 0.732

c. The airline employees worked as hard as possible for me during the recovery effort

0.736 0.701

3. Interactional

Justice

d. The airline employees were honest and ethical in dealing with me during their fixing of my problem

0.733 0.657

0.983 8.194 %

Cumulative percentage of

Variance

65.684%

Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalisation N=201

265

Fig.5.4 Scree Plot Rep

resenting the Factors of Perce

ived

Justice

266

After the systematic evaluation of the contents of data, SPSS was used to simplify the

data through the Scree test/plot under factor analysis (Sharma et al, 2001). Therefore,

the factors finally emerged were put under scree test so as to know which of them are

contributing significantly to the total variance in the results obtained. This test

examines the graph of Eigen values which stop factoring at the point where these

values begin to form a straight line with an almost horizontal slope (Fig. 5.4). The

findings are on the basis of the data gathered with in the domain of perceived justice.

5.8 REGRESSION ANALYSIS

In order to predict the changes on a dependent variable caused by the changes in an

independent variable, the regression analysis is applied. The basic information of the

regression equation is:

Y=a + bX

Where

Y = dependent variable and

X= independent variable

I. Regression output for customer satisfaction and seriousness of the service

failure

Customer Satisfaction = f (Seriousness of the service failure)

267

Table 5.31 Regression Coefficient of Seriousness of the Service Failure

Variable Beta t-value Sig.

Seriousness of the service failure .637 14.39 .000

Table 5.32 Regression Model for Seriousness of the Service Failure (Summary)

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .637(a) .406 .404 .33086

a Predictors: (Constant), Seriousness

The values shown in the Table 5.31 and Table 5.32 suggest that the customer

satisfaction is a function of seriousness of service failure. The dependent variable is

customer satisfaction and independent variable is seriousness of service failure. The

findings are presented by regression model (R Square = 0.406) and the β value

(0.637) of seriousness of service failure is significant as suggested by the t-value.

Thus, higher the seriousness of the service failure, higher is the satisfaction level of

customer affected.

II. Regression output for satisfaction with recovery and perceived justice

In order to predict the difference in the satisfaction with recovery of the complainants

due to distributive justice, procedural justice and interactional justice, the regression

analysis is used. The basic information of the regression equation is:

Y=a + bX

268

Where

Y = dependent variable i.e. satisfaction with recovery of complainants.

X= independent variable i.e. distributive justice, procedural justice and interactional

justice.

This research explores the effect of distributive, procedural and interactional justice

provided by airlines to complainants’ satisfaction. Thus, the dependent variable is

satisfaction with recovery and the independent variable is the justice of airlines.

Satisfaction with recovery = f (Distributive Justice, Procedural Justice and

Interactional Justice)

Table 5.33 Regression Coefficient of Perceived Justice

Variable Beta Value t-value Sig.

Distributive Justice 0.269 3.385 .001

Procedural Justice 0.245 3.042 .003

Interactional Justice 0.128 1.736 .084

Table 5.34 Regression Model for Perceived Justice (Summary)

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .549(a) .302 .291 .45202

a Predictors: (Constant), CIJ, CDJ, CPJ

The values shown in the Table 5.33 and Table 5.34 suggest that the satisfaction with

recovery is a function of distributive justice, procedural justice and interactional

269

justice. The β values of distributive and procedural justice are significant as suggested

by the t-values. The justice construct together explain 30.2% of the total variance in

the satisfaction with recovery as suggested by the R-square value.

III. Regression output for overall airline satisfaction and satisfaction with

recovery

Overall Airline Satisfaction = f (Satisfaction with Recovery)

Table 5.35 Regression Coefficient of Satisfaction with Recovery

Table 5.36 Regression Model for Satisfaction with Recovery (Summary)

Model R R Square

Adjusted R

Square Std. Error of the Estimate

1 .303(a) .092 .087 .53206

a Predictors: (Constant), SR

The values shown in the Table 5.35 and Table 5.36 suggest that the satisfaction with

recovery is a function of overall airline satisfaction. The β value of satisfaction with

recovery is significant as suggested by the t-value.

Variable Beta t-value Sig.

Satisfaction with

recovery

0.303 4.477 .000

270

5.9 DESCRIPTIVE STATISTICS OF DIMENSION OVERALL AIRLINE

SATISFACTION W.R.T. EACH AIRLINE

The mean scores and standard deviation values of dimension overall airline

satisfaction are mentioned in the Table 5.37. Out of 305 respondents, only 241

respondents mentioned the name of the airline with which service failure was

encountered during travel in domestic sectors of India. There are ten airlines

identified- Air Deccan (now its Kingfisher Red), Air India, Air Sahara (the name

changed is JetLite), Go Air, Indian Airline, Indigo, Jet airways, Spice jet, JetLite and

Kingfisher Airline.

Table 5.37 Descriptive Statistics (Mean and Standard Deviation) of Overall

Airline Satisfaction w.r.t Each Airline

N Mean

Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Airline

Lower

Bound

Upper

Bound

Air Deccan 26 4.00 .40 .08 3.84 4.16

Air India 37 3.87 .40 .07 3.73 3.99

Air Sahara 6 4.00 .00 .00 4.00 4.00

Go Air 16 3.75 .89 .22 3.27 4.23

Indian Airline

14 3.96 .50 .13 3.68 4.25

Indigo Airline

15 3.93 .26 .07 3.79 4.08

Jet Airways 25 3.92 .62 .12 3.66 4.18

JetLite

27 4.07 .27 .05 3.97 4.18

Spice Jet 45 3.87 .60 .09 3.69 4.04

Kingfisher Airline

30 3.98 .36 .07 3.85 4.12

Total 241 3.93 .49 .03 3.87 3.99

271

Comparison of mean values as shown in Table 5.37 establishes that the satisfaction

with the overall quality of airlines JetLite, Air Deccan, Air Sahara and Kingfisher

Airline are higher than the rest of the airlines.

Table 5.38 Test of Homogeneity of Variances

Levene Statistic df1 df2 Sig.

3.798 9 231 .000

5.9.1 COMPARISON OF AIRLINES ON THE BASIS OF OVERALL AIRLINE

SATISFACTION

This section was conducted with the null hypotheses that there is no significant

difference between the airlines as far as overall airline satisfaction is concerned.

Using the Analysis of Variance (ANOVA) test the hypotheses were tested, the results

are shown in the Table 5.39. Since the calculated value of F0.05 (0.760) is greater than

the table value (For v1= 9, v2=231, F0.05=0.653), the null hypothesis i.e. there is no

significant difference between the airlines as far as overall airline satisfaction is

concerned, is rejected in this case. It means that there is difference between the

airlines regarding overall airline satisfaction. It is implied that at least one of the

airlines is perceived by the passengers to be significantly different from the rest of the

lot.

Table 5.39 One Way ANOVA Results for Overall Airline Satisfaction

Sum of Squares Df Mean Square F Sig.

Between Groups 1.68 00009 .186 .760 .653

Within Groups 56.62 231 .245

Total 58.30 240

272

Tukey’s Honestly Significant Difference Test for Multiple Comparisons:

This test identifies the airlines that are significantly different from the rest of the lot.

The results of Tukey’s Honestly Significant Difference Test as shown in Table 5.40

for multiple comparisons suggest that all the airlines are significantly different from

the rest of the lot as far as overall airline satisfaction is concerned.

Table 5.40 Tukey HSD Multiple Comparisons Test for Overall Airline

Satisfaction

95% Confidence Interval Airline

Airline (In comparison

with)

Mean Difference

Std. Error

Sig.

Lower Bound

Upper Bound

Air Deccan

Air India .14 .13 .987 -.2697 .5399

Air Sahara .00 .22 1.000 -.7164 .7164 Go Air .25 .16 .852 -.2526 .7526 Indian Airline .04 .16 1.000 -.4887 .5601 Indigo .07 .16 1.000 -.4462 .5795 Jet Airways .08 .14 1.000 -.3631 .5231 JetLite -.07 .14 1.000 -.5087 .3606 Spice jet .13 .12 .985 -.2563 .5230 Kingfisher Airline .02 .13 1.000 -.4072 .4405 Air India Air Deccan -.14 .13 .987 -.5399 .2697 Air Sahara -.14 .22 1.000 -.8313 .5610 Go Air .11 .15 .999 -.3584 .5882 Indian Airline -.10 .16 1.000 -.5958 .3969 Indigo -.07 .15 1.000 -.5527 .4157 Jet Airways -.06 .13 1.000 -.4647 .3544 JetLite -.21 .13 .811 -.6096 .1912 Spice jet -.001 .11 1.000 -.3528 .3492 Kingfisher Airline -.12 .12 .993 -.5071 .2702 Air

Sahara

Air Deccan .00 .22 1.000 -.7164 .7164

Air India .14 .22 1.000 -.5610 .8313 Go Air .25 .24 .988 -.5072 1.0072 Indian Airline .04 .24 1.000 -.7361 .8076 Indigo .07 .24 1.000 -.6974 .8308 Jet Airways .08 .23 1.000 -.6391 .7991 JetLite -.07 .22 1.000 -.7880 .6399 Spice jet .13 .21 1.000 -.5541 .8208 Kingfisher Airline .02 .22 1.000 -.6907 .7241 Go Air Air Deccan -.25 .16 .852 -.7526 .2526

273

Air India -.11 .15 .999 -.5882 .3584 Air Sahara -.25 .24 .988 -1.0072 .5072 Indian Airline -.21 .18 .974 -.7932 .3646 Indigo -.18 .18 .990 -.7518 .3852 Jet Airways -.17 .16 .987 -.6764 .3364 Jetlite -.32 .16 .547 -.8231 .1750 Spice jet -.12 .14 .998 -.5771 .3438 Kingfisher Airline -.23 .15 .882 -.7230 .2563 Indian Airline

Air Deccan -.04 .16 1.000 -.5601 .4887

Air India .09 .16 1.000 -.3969 .5958 Air Sahara -.04 .24 1.000 -.8076 .7361 Go Air .21 .18 .974 -.3646 .7932 Indigo .03 .18 1.000 -.5569 .6188 Jet Airways .04 .17 1.000 -.4837 .5723 JetLite -.11 .16 1.000 -.6307 .4112 Spice jet .10 .15 1.000 -.3865 .5817 Kingfisher Airline -.02 .16 1.000 -.5310 .4929 Indigo Air Deccan -.07 .16 1.000 -.5795 .4462 Air India .07 .15 1.000 -.4157 .5527 Air Sahara -.07 .24 1.000 -.8308 .6974 Go Air .18 .18 .990 -.3852 .7518 Indian Airline -.03 .18 1.000 -.6188 .5569 Jet Airways .01 .16 1.000 -.5033 .5300 JetLite -.14 .16 .997 -.6501 .3687 Spice jet .07 .15 1.000 -.4049 .5383 Kingfisher Airline -.05 .16 1.000 -.5502 .4502 Jet

Airways

Air Deccan -.08 .14 1.000 -.5231 .3631

Air India .06 .13 1.000 -.3544 .4647 Air Sahara -.08 .23 1.000 -.7991 .6391 Go Air .17 .16 .987 -.3364 .6764 Indian Airline -.04 .17 1.000 -.5723 .4837 Indigo -.01 .16 1.000 -.5300 .5033 JetLite -.15 .14 .982 -.5931 .2850 Spice jet .05 .12 1.000 -.3412 .4479 Kingfisher Airline -.06 .13 1.000 -.4917 .3650 Jetlite Air Deccan .07 .14 1.000 -.3606 .5087 Air India .21 .13 .811 -.1912 .6096 Air Sahara .07 .22 1.000 -.6399 .7880 Go Air .32 .16 .547 -.1750 .8231 Indian Airline .11 .16 1.000 -.4112 .6307 Indigo .14 .16 .997 -.3687 .6501 Jet Airways .15 .14 .982 -.2850 .5931 Spice jet .21 .12 .783 -.1777 .5925 Kingfisher Airline .09 .13 1.000 -.3289 .5104 Spice jet Air Deccan -.13 .12 .985 -.5230 .2563 Air India .001 .11 1.000 -.3492 .3528 Air Sahara -.13 .22 1.000 -.8208 .5541

274

Go Air .12 .14 .998 -.3438 .5771 Indian Airline -.10 .15 1.000 -.5817 .3865 Indigo -.07 .15 1.000 -.5383 .4049 Jet Airways -.05 .12 1.000 -.4479 .3412 JetLite -.21 .12 .783 -.5925 .1777 Kingfisher Airline -.12 .12 .992 -.4895 .2562 Kingfishe

r Airline

Air Deccan -.02 .13 1.000 -.4405 .4072

Air India .12 .12 .993 -.2702 .5071 Air Sahara -.02 .22 1.000 -.7241 .6907 Go Air .23 .15 .882 -.2563 .7230 Indian Airline .02 .16 1.000 -.4929 .5310 Indigo .05 .16 1.000 -.4502 .5502 Jet Airways .06 .13 1.000 -.3650 .4917 JetLite -.09 .13 1.000 -.5104 .3289 Spice jet .12 .12 .992 -.2562 .4895

5.10 DESCRIPTIVE STATISTICS OF DIMENSION SATISFACTION WITH

OVERALL QUALITY OF AIRLINE

The mean scores and standard deviation values of dimension satisfaction with overall

quality of airline are mentioned in the Table 5.41. Out of 305 respondents, only 241

respondents mentioned the name of the airline with which service failure was

encountered during travel in domestic sectors of India. There are ten airlines

identified- Air Deccan (now its Kingfisher Red), Air India, Air Sahara (the name

changed is JetLite), Go Air, Indian Airline, Indigo, Jet airways, Spice jet, JetLite and

Kingfisher Airline.

275

Table 5.41 Descriptive Statistics (Mean and Standard Deviation) of Satisfaction

with the Overall Quality of Each Airline

95% Confidence

Interval for Mean

Airline N

Mean

Std.

Deviation

Std.

Error

Lower

Bound

Upper

Bound

Air Deccan 26 2.85 .92 .18138 2.4726 3.2197

Air India 37 3.05 .99 .16415 2.7211 3.3870

Air Sahara 6 3.17 .41 .16667 2.7382 3.5951

Go Air 16 3.75 1.18 .29580 3.1195 4.3805

Indian Airline 14 3.79 1.53 .40841 2.9034 4.6680

Indigo Airline 15 3.07 1.10 .28396 2.4576 3.6757

Jet Airways 25 3.56 1.33 .26508 3.0129 4.1071

JetLite 27 3.37 1.15 .22103 2.9160 3.8247

Spice Jet 45 3.33 1.07 .15891 3.0131 3.6536

Kingfisher

Airline

30 3.87 1.28 .23358 3.3889 4.3444

Total 241 3.37 1.16 .07506 3.2173 3.5130

Comparison of mean values as shown in Table 5.41 establishes that the satisfaction

with the overall quality of Kingfisher Airline, Indian Airline and Go Air are higher

than the Air Deccan, Air India, Air Sahara, Indigo Airline, Jet Airways, JetLite and

Spice Jet.

Table 5.42 - Test of Homogeneity of Variances

Levene Statistic df1 df2 Sig.

2.668 9 231 .006

276

5.10.1 COMPARISON OF AIRLINES ON THE BASIS OF SATISFACTION

WITH THE OVERALL QUALITY OF AIRLINE

This section was conducted with the null hypotheses that there is no significant

difference between the airlines as far as satisfaction with overall quality of airline is

concerned. Using the Analysis of Variance (ANOVA) test the hypotheses were tested,

the results are shown in the Table 5.43. Since the calculated value of F0.05 (2.183) is

greater than the table value (For v1= 9, v2=231, F0.05=0.024), the null hypothesis i.e.

there is no significant difference between the airlines as far as satisfaction with overall

quality of airline is concerned, is rejected in this case. It means that there is difference

between the airlines regarding satisfaction with overall quality of airline. It is implied

that at least one of the airlines is perceived by the passengers to be significantly

different from the rest of the lot.

Table 5.43- One Way ANOVA results for Satisfaction with Overall Quality of

Airline

Sum of

Squares

df Mean

Square

F Sig.

Between Groups 25.54 9 2.84 2.183 .024

Within Groups 300.32 231 1.30

Total 325.87 240

Tukey’s Honestly Significant Difference Test for Multiple Comparisons:

This test identifies the airlines that are significantly different from the rest of the lot.

Since the null hypotheses got rejected, it is necessary to find out as to which airline (s)

is/are significantly different from the rest. The results of Tukey’s HSD Test as shown

in Table 5.44 for multiple comparisons suggest that Kingfisher Airline is significantly

different from Air Deccan as far as satisfaction with overall quality of airline is

concerned.

277

Table 5.44- Tukey HSD Multiple Comparisons Test for Satisfaction with Overall

Quality of Airline

95% Confidence Interval

Airline

Airline (In Comparison with)

Mean Difference

Std. Error

Sig.

Lower Bound

Upper Bound

Air Deccan Air India -.21 .29 .999 -1.1402 .7244 Air Sahara -.32 .52 1.000 -1.9704 1.3294 Go Air -.90 .36 .277 -2.0614 .2537 Indian Airline -.94 .38 .282 -2.1472 .2681 Indigo -.22 .37 1.000 -1.4017 .9607 Jet Airways -.71 .32 .436 -1.7343 .3066 JetLite -.52 .31 .809 -1.5252 .4768 Spice jet -.49 .28 .775 -1.3846 .4102 Kingfisher Airline -1.02(*) .31 .032 -1.9966 -.0444 Air India Air Deccan .21 .29 .999 -.7244 1.1402 Air Sahara -.11 .50 1.000 -1.7159 1.4907 Go Air -.70 .34 .572 -1.7859 .3941 Indian Airline -.73 .36 .568 -1.8747 .4114 Indigo -.01 .35 1.000 -1.1277 1.1025 Jet Airways -.51 .30 .787 -1.4491 .4372 JetLite -.32 .29 .985 -1.2384 .6057 Spice jet -.28 .25 .984 -1.0877 .5292 Kingfisher Airline -.81 .28 .111 -1.7076 .0824 Air Sahara Air Deccan .32 .52 1.000 -1.3294 1.9704 Air India .11 .50 1.000 -1.4907 1.7159 Go Air -.58 .55 .987 -2.3273 1.1606 Indian Airline -.62 .56 .983 -2.3966 1.1585 Indigo .10 .55 1.000 -1.6597 1.8597 Jet Airways -.39 .52 .999 -2.0494 1.2628 JetLite -.20 .51 1.000 -1.8479 1.4405 Spice jet -.17 .50 1.000 -1.7499 1.4166 Kingfisher Airline -.70 .51 .934 -2.3292 .9292 Go Air Air Deccan .90 .36 .277 -.2537 2.0614 Air India .70 .34 .572 -.3941 1.7859 Air Sahara .58 .55 .987 -1.1606 2.3273 Indian Airline -.03 .42 1.000 -1.3689 1.2975 Indigo .68 .41 .812 -.6259 1.9926 Jet Airways .19 .37 1.000 -.9763 1.3563 JetLite .38 .36 .988 -.7697 1.5290 Spice jet .42 .33 .962 -.6437 1.4770 Kingfisher Airline -.12 .35 1.000 -1.2444 1.0111 Indian Airline Air Deccan .94 .38 .282 -.2681 2.1472 Air India .73 .36 .568 -.4114 1.8747 Air Sahara .62 .56 .983 -1.1585 2.3966 Go Air .04 .42 1.000 -1.2975 1.3689 Indigo .72 .42 .796 -.6347 2.0728 Jet Airways .23 .38 1.000 -.9903 1.4418 JetLite .42 .38 .984 -.7844 1.6151

278

Spice jet .45 .35 .954 -.6624 1.5672 Kingfisher Airline -.08 .37 1.000 -1.2601 1.0982 Indigo Air Deccan .22 .37 1.000 -.9607 1.4017 Air India .01 .35 1.000 -1.1025 1.1277 Air Sahara -.10 .55 1.000 -1.8597 1.6597 Go Air -.68 .41 .812 -1.9926 .6259 Indian Airline -.72 .42 .796 -2.0728 .6347 Jet Airways -.49 .37 .947 -1.6831 .6964 JetLite -.30 .37 .998 -1.4768 .8694 Spice jet -.27 .34 .999 -1.3528 .8194 Kingfisher Airline -.80 .36 .447 -1.9520 .3520 Jet Airways Air Deccan .71 .32 .436 -.3066 1.7343 Air India .51 .30 .787 -.4372 1.4491 Air Sahara .39 .52 .999 -1.2628 2.0494 Go Air -.19 .37 1.000 -1.3563 .9763 Indian Airline -.23 .38 1.000 -1.4418 .9903 Indigo .49 .37 .947 -.6964 1.6831 JetLite .19 .32 1.000 -.8215 1.2007 Spice jet .23 .28 .999 -.6820 1.1354 Kingfisher Airline -.31 .31 .992 -1.2932 .6798 JetLite Air Deccan .52 .31 .809 -.4768 1.5252 Air India .32 .29 .985 -.6057 1.2384 Air Sahara .20 .51 1.000 -1.4405 1.8479 Go Air -.38 .36 .988 -1.5290 .7697 Indian Airline -.42 .38 .984 -1.6151 .7844 Indigo .30 .37 .998 -.8694 1.4768 Jet Airways -.19 .32 1.000 -1.2007 .8215 Spice jet .04 .28 1.000 -.8498 .9238 Kingfisher Airline -.50 .30 .827 -1.4627 .4701 Spice Jet Air Deccan .49 .28 .775 -.4102 1.3846 Air India .28 .25 .984 -.5292 1.0877 Air Sahara .17 .50 1.000 -1.4166 1.7499 Go Air -.42 .33 .962 -1.4770 .6437 Indian Airline -.45 .35 .954 -1.5672 .6624 Indigo .27 .34 .999 -.8194 1.3528 Jet Airways -.23 .28 .999 -1.1354 .6820 JetLite -.04 .28 1.000 -.9238 .8498 Kingfisher Airline -.53 .27 .611 -1.3920 .3253 Kingfisher

Airline

Air Deccan 1.02(*) .31 .032 .0444 1.9966

Air India .81 .28 .111 -.0824 1.7076 Air Sahara .70 .51 .934 -.9292 2.3292 Go Air .12 .35 1.000 -1.0111 1.2444 Indian Airline .08 .37 1.000 -1.0982 1.2601 Indigo .80 .36 .447 -.3520 1.9520 Jet Airways .31 .31 .992 -.6798 1.2932 JetLite .50 .30 .827 -.4701 1.4627 Spice jet .53 .27 .611 -.3253 1.3920

* The mean difference is significant at the .05 level.

279

Comparison of Number of Service Failures in Each

Group w.r.t. Airline

32

13

19

29

39

1512

21

4

24

2 1 30

6

1 2 40 1

23

68 8

14

6 69

3

10

0

5

10

15

20

25

30

35

40

45

Air India

Indian A

irline

Jet A

irways

Kingfis

her A

irline

Spice

Jet

Go Air

Indigo

Airline

JetLite

Air Sa

hara

Air Dec

can

Group-1 Service Delivery System Failures Group-2 Customer Needs and Requests

Group-3 Unprompted and Unsolicited Actions

Fig 5.5 Comparison of Number of Service Failures in Each Group w.r.t. Airline

280

Table 5.45- Comparison of Number of Service Failures in Each Group w.r.t.

Airline

Airlines Group-1 Service

Delivery System

Failures

Group-2

Customer

Needs and

Requests

Group-3

Unprompted and

Unsolicited

Actions

Total

Air India 32 02 23 57

Indian Airline 13 01 06 20

Jet Airways 19 03 08 30

Kingfisher

Airline

29 00 08 37

Spice Jet 39 06 14 59

Go Air 15 01 06 22

Indigo Airline 12 02 06 20

JetLite 21 04 09 34

Air Sahara 04 00 03 7

Air Deccan 24 01 10 35

281

REFERENCES

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Encounter: Diagnosing Favorable and Unfavorable Incidents. Journal of

Marketing, 54 (January), 71-84.

Flanagan, John C. (1954). The Critical Incident Technique. Psychological Bulletin. 51

(July), 327-57.

Forbes, Lukas P., Kelley, Scott W. & Hoffman, K. Douglas. (2005). Typologies of e-

commerce retail failures and recovery strategies. Journal of Services

Marketing, 19(5), 280-292.

Hair, J.F. Jr., Anderson, R.E., Taltan, R.L. & Black W.C. (1988). Multivariate Data

Analysis. Prentice-Hall Inc., Englewood Cliffs, NJ.

Kivela, Jaksa, J. & Chu, Carmen Yiu Ha. (2001). Delivering Quality Service:

Diagnosing Favorable And Unfavorable Service Encounters in

Restaurants. Journal of Hospitality and Tourism Research, 25 (3), August,

251-271.

Malhotra, Naresh K. (2005). Marketing Research: An Applied Orientation, Prentice

Hall of India Private Ltd: New Delhi.

Maxham III, James G. & Netemeyer, Richard G. (2003). Firms Reap What They Sow:

The Effects of Shared Values and Perceived Organizational Justice on

Customers’ Evaluations of Complaint Handling. Journal of Marketing, 67

(January), 46-62.

Sharma, R. D., Gurjeet Kaur & Mahesh C. Gupta. (2001). Measurement of Marketing

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Scale: A Case of Jammu Rural Banks. Pranjnan, XXX (1), (April-June).

282

Singh, Jagdip. (1988). Consumer Complaint Intentions and Behavior: Definitional and

Taxonomical Issues. Journal of Marketing, January, 93-107.

283

In this chapter, all the key findings supplemented by the conclusions and the

suggestions are discussed, that can provide useful inputs for companies that are

providing services especially airline companies. The conclusions drawn are based on

the data analysis conducted and presented in the previous chapter.

6.1 OBJECTIVES OF THE STUDY AND THEIR ACHIEVEMENT

The following three objectives were set forth for the present research work. In the

section below, we discuss how the objectives set forth were achieved

Objective 1: To study the various types of service failures and their effect on

customer’s satisfaction in aviation industry.

The first objective was to study the various types of service failures encountered by

the customers (passengers) while using services of airlines, travelling by air in

domestic sectors of India and the effect of these failures on their satisfaction. This

objective was achieved in Study I using the Critical Incident Technique. A total of

338 dissatisfying incidents were collected from the customers (passengers) of airlines.

After initial sorting process and classification, twenty-six service failure categories

were identified and classified into three major groups as per Bitner et al’s (1990)

Group and Category Classification by Type of Incident Outcome discussed in detail in

Chapter 5.

CHAPTER-6

CONCLUSION AND SUGGESTIONS

284

It is evident from the literature that Bitner et al’s (1990) classification by Type of

Incident Outcome is applied by researchers in their studies in various service sectors

like Hoffman, Kelly and Rotalsky (1995) collected 373 incidents from customers of

restaurants; Kivela and Chu (2001) collected favourable and unfavourable service

encounters from 417 customers of restaurants; Chung-Herrera, Goldschmidt and

Hoffman (2004) collected customer-reported incidents and 390 employee-reported

incidents; Forbes, Kelly and Hoffman (2005) applied CIT using 377 customer

responses to present ten e-tail failures and eleven e-tail recovery strategies used by e-

commerce service firms.

The effect of service failures on customer satisfaction is analysed in Study II with the

help of mean and standard deviation as presented in Table 5.11. Among all service

failures, the failures that fall under category of employee behaviour in the context of

cultural norms (Mean= 4.62, SD= 0.73) highly effected the satisfaction of customers

i.e. if employee behaved negatively to cultural norms such as equality, honesty and

fairness it definitely effected the satisfaction of customers.

It is the first study in India which identifies the failures in the airline services from

passenger’s perspective.

Objective 2: To study the various coping strategies undertaken by the airlines

to overcome the service failures.

The objective was to study the various recovery actions taken by the airlines to

overcome the service failures encountered by customers. It is derived from Study I

that, generally, customers did not complain regarding the failure they encountered; the

reason may be- lack of time, doubt on the ability of the airline to rectify the situation,

lengthy procedures to follow etc. Only 3% of the respondents are satisfied with the

285

service failure recovery and the recovery strategies used by the airline are

compensation, timely action and fulfil the needs of customers.

This objective was achieved in Study II using the survey method. It is found that,

despite some recovery efforts by airlines, the majority of respondents who

experienced a service failure with a domestic airline (34.5%) indicated that the airline

did nothing to recover from the failure. This finding is similar to that of a study in the

hotel industry, where only 40% of guests reported that the hotel had not offered them

service recovery, suggesting that hotels are not doing enough to resolve service

failures (Lewis & McCann 2004) and in the South African airline industry where

57.7% of the service failure experienced respondents also agreed that domestic airline

did nothing to recover from the failure (Mostert, Meyer and Rensburg, 2009).

If the customer complained to the airline about the service failure, the most common

recovery action taken by airline is apology. And, only 7% of the respondents told that

the problem was corrected by the airline.

Objective 3: To make an impact assessment of recovery efforts in enhancing the

customer’s satisfaction.

The objective was to find out if recovery actions taken by the airlines enhanced the

satisfaction of customers? This objective was achieved by applying regression

analysis on the perceived justice as independent variable and satisfaction with

recovery of complainants as dependent variable. The findings suggest that distributive

and procedural justice have strong influence on customer’s satisfaction with recovery.

It is indicated that customers are satisfied with the outcome of the service recovery

process adopted by airlines and the fairness of the service recovery to rectify the

problem. But the effect of distributive justice on satisfaction with recovery of

286

respondents is stronger than procedural justice. This finding is consistent with results

of previous studies where distributive justice was found to have the greatest impact on

customer satisfaction (Kim et al, 2009; Kau and Loh, 2006; Mattila, 2001). The

interactional dimension of perceived justice is not significantly affecting the

satisfaction with recovery of respondents. It means that how the airline personnel

treated the customers’ through-out the service recovery process is not affecting the

satisfaction of customers.

It is also measured that satisfaction with recovery significantly effected the overall

airline satisfaction.

6.2 VALIDITY OF HYPOTHESIS TESTED

Two separate hypotheses were set up to be tested. The data generated from the present

research has been used to test the hypotheses and check whether they have been

accepted or not.

H1: Service failures have negative effect on customer’s overall satisfaction.

Twenty-six service failures were derived from StudyI and the mean values of service

failures fall in the category employee behaviour in the context of cultural norms (theft

of items which are under the scrutiny of airline staff members, Mean=4.62, SD=0.73),

gestalt evaluation (unfriendly and uncomfortable ambience for travellers, Mean=4.57,

SD=0.69) and response to core service failures (mishandling, missing and exchange

of baggage, printing mistake on ticket, inconvenience due to non-working of air

condition in aircraft, food and beverage not of high quality, Mean=4.54, SD=0.51)

suggests that service failures have negative effect on customer’s overall satisfaction in

287

the context of airline services provided to its customers (passengers). Hence,

hypothesis 1 is accepted.

In addition, effect of seriousness of service failure on customer satisfaction is also

measured with the help of regression analysis. The dependent variable is customer

satisfaction and independent variable is seriousness of service failure. The findings

are presented by regression model (R Square = 0.406) and the β value (0.637) of

seriousness of service failure is significant as suggested by the t-value. Thus, higher

the seriousness of the service failure, higher is the satisfaction level of customer

affected.

H2: Recovery efforts have a positive role in enhancing customer’s satisfaction

levels.

This hypothesis was tested using regression analysis, the dependent variable is

satisfaction with recovery and the independent variable is perceived justice and the

findings are presented by regression models (R Square=0.302) suggests that recovery

efforts in terms of perceived justice have a positive relationship in customer

satisfaction. It is indicated that customers are satisfied with the outcome of the service

recovery process adopted by airlines and the fairness of the service recovery to rectify

the problem. But the effect of distributive justice on satisfaction with recovery of

respondents is stronger than procedural justice. Hence, hypothesis 2, recovery efforts

have a positive role in enhancing customer’s satisfaction is accepted.

288

6.3 CONCLUSION

The demographic profile of the respondents of Study I point out that out of 200

respondents, 69.5% are male and 58.5% belong to the age group 20-40 years. Equal

percentage of respondents i.e. 34.5% belong to the 10,000 to 30,000 and 30,000 to

50,000 income group. Also, majority of the respondents 61.5% belong to occupation

service.

A total of 338 incidents were collected from 200 respondents, the analytic induction

process was used to classify these incidents into Bitner et al’s (1990) group and

category classification by type of incident outcome. 49.7% of the incidents collected

come under the group1, employee response to service delivery system failures; 14.2%

of the incidents come under the group2, employee response to customer needs and

requests and 36.1% of the incidents collected belong to the group3, unprompted and

unsolicited employee actions.

After initial sorting process and classification, twenty-six service failure categories

were identified in second part of the study. All twenty-six service failures classified

into sub categories of three major groups as per the classification given by Bitner et al

(1990).

The demographic profile of the respondents of Study II points out that out of 305

respondents, 65.90% are male, 66.56% belong to the age group 20-40, and 32.13%

belong to income group 20,000 to 40,000. Majority of the respondents (39.34%)

travelled by air less than 5 times in a year. 76 respondents travelled for vacation

purpose and 170 respondents’ preferred low cost carrier for travel.

It is found that the respondents are most serious towards the service failure like ‘theft

of items which are under the scrutiny of airline staff members (Mean=4.61,

289

SD=0.64)’ and it also effected their satisfaction (Mean=4.62, SD=0.73). The most

frequently encountered failures are ‘delay in flight (Mean=2.40, SD=1.04)’, ‘non

availability of right information about flight delay (Mean=2.21, SD=1.09)’, ‘no

provision of any refreshment when there is long delay in flight (Mean=1.93,

SD=0.99)’, ‘cancelled flight without prior notice (Mean=1.70, SD=0.76)’, ‘non-

availability of seat at departure terminal (Mean=1.54, 0.82)’ and ‘overbooking of

passengers (Mean=1.51, SD=0.73)’.

Both male (Mean=4.69, SD=0.62) and female (Mean=4.65, SD=0.53) considered the

service failure ‘missing of baggage’, most serious. The most frequently encountered

service failure is ‘delay in flight (male, Mean=2.47, SD=1.01 and female, Mean=2.27,

SD=1.08)’ and the service failure ‘theft of items which are under the scrutiny of

airline staff members (male, Mean=4.60, SD=0.76 and female, Mean=4.66,

SD=0.66)’ highly effected the satisfaction.

Respondents who travelled by air less than 5 times in a year (Mean=4.68, SD=0.63),

5 to 10 times in a year (Mean=4.7, SD=0.52) and above 15 times in a year

(Mean=4.67, 0.56) considered ‘missing of baggage’ as the most serious service failure

where as the passengers who travelled 5 to 10 times in a year (Mean=4.7, SD=0.61)

and 10 to 15 times in a year (Mean=4.65, SD=0.66) considered ‘exchange of

baggage’ as most serious service failure.

‘Flight delay’ is most frequently encountered by respondents who travelled less than 5

times in a year (Mean=2.18, SD=0.95), 5 to 10 times in a year (Mean=2.51,

SD=1.08), 10 to 15 times in a year (Mean=2.61, SD=1.10) and above 15 times in a

year (Mean=2.58, SD=0.97) by air.

290

‘Theft of items which are under the scrutiny of airline staff members’ is highly

effected the satisfaction of respondents travelled by air less than 5 times in a year

(Mean=4.53, SD=0.87), 5 to 10 times in a year (Mean=4.76, 0.45), 10 to 15 times in a

year (Mean=4.57, SD=0.70) and above 15 times (Mean=4.54, SD=0.98) in a year.

The demographic composition of complainants (N=201) exhibits that there are

66.67% of male, 71.64% belong to age group 20 to 40 and 33.83% belong to income

group 20,000 to 40,000. Also, 39.30% of respondents (complainants) travelled by air

5 to 10 times in a year.

It is found that the complainants preferred voice action (Mean=4.18, SD=0.74) in

comparison to private (Mean=3.94, SD=0.93) and third party (Mean=2.92, SD=0.87)

actions. The result of the independent t-test shows that there is no significant

difference between the voice, private and third party intentions of complainants and

non-complainants.

In ‘Voice’ behaviour intentions, male (Mean=4.18, SD=1.08) are highly intended to

complain to the airline staff members and ask them to take care of the problem where

as female (Mean=4.25, SD=0.89) are highly intended to complain to the airline staff

members about the service failure.

In ‘Private’ behaviour intentions, both male (Mean=4.22, SD=1.19) and female

(Mean=4.30, SD=1.09) are highly intended to speak to friends and relatives about

their bad experience. In ‘Third Party’ behaviour intentions, both male (Mean=3.16,

SD=1.16) and female (Mean=3.27, SD=1.10) are highly intended to complain to a

consumer agency and ask them to make the airline take care of their problem.

It is supported from the factor analysis that the perceived justice of airline passengers

as a multidimensional construct consisting of distributive, procedural and interactional

291

justice. The highest mean score value of interactional justice (Mean=3.30, SD=0.90)

reveals that the complainants strongly agree with the interactional justice of the

airline.

The result of regression analysis was applied on customer satisfaction and seriousness

of the service failure; perceived justice and satisfaction with recovery; overall airline

satisfaction and satisfaction with recovery.

The findings are presented by regression model (R2 = 0.406) and the β value (0.637)

of seriousness of service failure is significant as suggested by the t-value. Thus,

higher the seriousness of the service failure, highly effected is the satisfaction of

customers.

It is also derived that the perceived justice effected the satisfaction of customers after

recovery. The value of R2=0.302 shows that when perceived justice is increased by

one unit, the satisfaction with recovery increases by 30%. It is also evident from the

value of R2=0.302, that 30% of variation (increase) in satisfaction with recovery is

accounted for by distributive, procedural and interactional justice.

On the other hand, the regression analysis shows that when satisfaction with recovery

is increased by one unit, the overall airline satisfaction increases by 6%. The value of

R2=0.068 shows that only 6% of variation in overall airline satisfaction is accounted

for by satisfaction with recovery. Though the overall airline satisfaction has increased

after satisfaction with recovery, yet the results of regression reflect that satisfaction

with recovery contribute very little (6%) to bring about this change. There might be

other factors which also influenced the customers’ overall airline satisfaction like fare,

past experience etc. Therefore, although satisfaction with recovery leads to an

increase in the overall airline satisfaction, yet it is not the only variable.

292

As far as recovery strategies is concerned, it was established from the literature

review that organisation can use a number of strategies to recover from service

failures, including communicating with customers to provide feedback and offer an

explanation for the failure (Boshoff & Staude, 2003; La & Kandampully 2004) and

that the organisation should apologise for the failure (Boshoff & Leong, 1998; Mattila

& Cranage, 2005; Smith et al, 1999). The findings of this study support these service

recovery strategies in that the majority of the respondents (34.5%) reported that the

airline did nothing to the problem faced by them. The most often recovery action

taken by the airlines is apology (27.4%).

After comparison of mean values of overall airline satisfaction of all the airlines, the

overall airline satisfaction of JetLite (Mean=4.07, SD=0.27), Air Deccan (now it as

Kingfisher Red, Mean=4.00, SD=0.40), Air Sahara (the name changed to JetLite,

Mean=4.00, SD=0.00) and Kingfisher Airline (Mean=3.98, SD=0.36) are higher than

the Indian Airline (X=3.96, SD=0.50), Indigo Airline (Mean=3.93, SD=0.26), Jet

Airways (Mean=3.92, SD=0.62), Spice jet (Mean=3.87, SD=0.60), Air India

(Mean=3.87, SD=0.40), Go Air (Mean=3.75, SD=0.89).

The results of ANOVA (F0.05=0.760) rejected the null hypothesis that there is no

significant difference between the airlines as far as overall airline satisfaction is

concerned. It means that there is difference between the airlines regarding overall

airline satisfaction. It is implied that at least one of the airlines is perceived by the

respondents to be significantly different from the rest of the lot. And the results of

Tukey’s HSD Test for multiple comparisons suggest that all the airlines are

significantly different from the rest of the lot as far as overall airline satisfaction is

concerned.

293

The comparison of the mean score values of satisfaction from the overall quality of

airline showed that satisfaction from Kingfisher Airline (Mean=3.87, SD=1.28),

Indian Airline (Mean=3.79, SD=1.53) and Go Air (Mean=3.75, 1.18) are higher than

the Jet Airways (Mean=3.56, SD=1.33), JetLite (Mean=3.37, SD=1.15), Spice jet

(Mean=3.33, SD=1.07), Air Sahara (Mean=3.17, SD=0.41), Indigo Airline

(Mean=3.07, SD=1.10), Air India (Mean=3.05, SD=0.99), Air Deccan (Mean=2.85,

SD=0.92).

The results of ANOVA (F0.05=2.183) rejected the null hypothesis that there is no

significant difference between the airlines as far as satisfaction with overall quality of

airline is concerned. It means that there is difference between the airlines regarding

satisfaction with overall quality of airline. The results of Tukey’s HSD Test for

multiple comparisons suggest that Kingfisher airline is significantly different from Air

Deccan as far as satisfaction with overall quality of airline is concerned.

6.4 RECOMMENDATIONS

The Critical Incident Technique is a useful tool for gathering primary data of

subjective nature from respondents. It can, through careful coding, reveal both

quantifiable data and bountiful descriptions of a qualitative kind. Analytical

categories derived from such sources increase validity and explanation. Reliability is

also enhanced by defining the service failure categories in the classification given by

Bitner et al (1990).

The results of this study may prove useful to airline companies in a number of

different ways. First, it is revealed from the results that the service failures are

inevitable whether the services are provided by full service airlines like Air India, Jet

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Airways, Kingfisher Airline or low cost carriers like Kingfisher Red, Spice Jet, Go

Air, Indigo, JetLite. The prime motive of a person to travel by air is to save time and

expect efficient services when he spends more on by deciding travel by the costliest

mode of transportation. The results of this study revealed that the service delivery

system failures are the most encountered by passengers. The reason may be a core

service failure (mishandling of baggage, missing and exchange of baggage), a

particular service which is expected by the customers but is unavailable (cancelled

flight without prior notice, no provision of any refreshment when there is long delay

in flight) and unreasonably slow services (delay in refund of cancelled ticket, delay of

baggage delivery).

It is found that all customers didn’t complain (Goodman and Ward, 1993); customer

complaints serve as the main indicator of service failure because complaints provide

an organisation with the opportunity to recover from service failure and prevent

negative behaviours on the part of customers. So, the airline companies should

encourage the customers to complain. Make it easy for them to complain and give

them outlets to complain. A well-implemented recovery has the potential to make a

customer more satisfied than if no service failure had occurred. Make the recovery fit

the failure.

Examining how company policies are perceived is important, previous research has

shown that customers are sensitive to violations of distributive, procedural and

interactional justice (Tax et al, 1998). The results of the study showed that the airline

customers are more sensitive towards distributive and procedural justice as compared

to interactional justice. Invariably, the problem is not in the company policy itself but

in the perception and interpretation of the policy. It may be the case that some

company policies may inhibit the provision of high service quality and good recovery.

295

The importance of service staff in the success of the service encounter and in the

service recovery effort has constantly been cited in the literature. The airline industry

needs satisfied customers to survive in the fierce competition of today. Employees

should be trained to prevent failures in the first place and if failures do occur, to

recover from failures in an appropriate and satisfying manner. Staff training is

essential to be able to reach the above, and training with focus on service recovery is a

special area which could act as a competitive advantage.

Airline management should consider some pre-defined strategies to mitigate the

negative effects of service failure. When analyzing the services offered, management

should identify those areas with in the service encounters where the customer can be

empowered. Customers can be empowered by giving them choices and information to

make good choices, which will improve their service experience. This will reduce the

chance of service failures and if failure occurs, it will reduce customers’ negative

feelings toward the service provider through self-attribution and respect for

disclosure.

The lack of service recovery (or inadequate service recovery) will, therefore, have a

direct influence on the airline’s profitability, since customers will not be retained,

despite the airline’s marketing efforts. Airlines’ service recovery efforts do not

necessarily need to incur considerable costs, as customers may be satisfied by simply

keeping them informed and explaining the reason for the failure or offering an

apology for the failure. Airlines could, through effective service recovery, possibly

retain their customers in their competitive industry.

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6.5 RESEARCH CONTRIBUTIONS

Very limited work has been done on the Indian aviation industry and no research

work has been found in India to study the service failures and recovery actions taken

by the domestic airlines from customer’s perspective and their effect on satisfaction.

This study is an attempt in this direction. The major implications of this study are-

The results obtained in this study have important implications for airline managers

and suggests that they should consider the service failures seriously and take prompt

actions to retain customers and survive in this competitive industry.

The current study has made a meaningful contribution to the service failure and

recovery literature since it deals with the measurement of the influence of service

failure and recovery on customer satisfaction, using critical incident technique and

survey method.

The methodology followed in the present research in identifying the service failures

and recovery actions taken by airline companies strongly supports the classification of

Incident Outcome given by Bitner et al (1990).

6.6 LIMITATIONS/FUTURE RESEARCH DIRECTIONS

Several limitations of this study must be recognised, first owing to the airline-oriented

focus of this study, these results cannot be generalized for other service industries.

Future work should consider the other service providing sectors like restaurant, hotels,

banks etc. Secondly, the incidents collected were from the customer’s perspective i.e

the outcome of the interaction between the customer and services provided by

airlines. Future research should consider the non-human elements (e.g. equipment,

297

facilitating goods) in service encounter-dis/satisfaction. Also, study the incidents from

service provider’s perspective in the same industry or other service industries.

Third, this study classified only dissatisfactory incidents in the classification of

Incident Outcome given by Bitner et al (1990) and it becomes the base for other

studies like Kelly, Hoffman and Davis (1993), Bitner, Booms and Mohr (1994),

Hoffman, Kelly and Rotalsky (1995), Kivela and Chu (2001), Lewis and Clacher

(2001), Hoffman, Kelly and Chung (2003), Mueller, Palmer, Mack and Mc Mullan

(2003), Holloway and Beatty (2003), Chung-Herrera, Goldschmidt and Hoffman

(2004), Forbes, Kelly and Hoffman (2005). Future research can make its own

classification system based on type of incidents.

Fourth, another limitation of this study is that it is limited to study the effect of service

failure on customer satisfaction only but future research can contribute to study the

effect of service failure recovery on repurchase intentions, loyalty, value and word of

mouth publicity. Fifth, the study was further limited by identifying only

dissatisfactory incidents that happened with the passengers from the services provided

by the airlines. Future research can examine not only both satisfying and dissatisfying

incidents that occurred between passengers and airline services but also of the airport

services or of the peer passengers in particular in Indian aviation industry or other

service industries.

It is the limitation of the study to consider the service failures encountered by

passengers due to congestion and crowd in the airports that put pressure on the service

supplier to provide effective service.

Sixth, researchers should also study failures and recoveries using different

methodologies. The CIT method provides an informative starting point for research in

298

this area; future studies might investigate this phenomenon through survey research

methods and experimental methods (e.g. Goodwin and Ross, 1992).

299

REFERENCES

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Encounter: Diagnosing Favorable and Unfavorable Incidents. Journal of

Marketing, 54 (January), 71-84.

Bitner, Mary Jo, Booms, Bernard H. & Mohr, Lois A. (1994). Critical Service

Encounters: The Employee’s Viewpoint. Journal of Marketing, 58

(October), 95-106.

Boshoff, C. & Leong, J. (1998). Empowerment, attribution and apologising as

dimensions of service recovery: an experimental study. International

Journal of Service Industry Management, 9 (1), 24–47.

Boshoff. C. & Staude, G. (2003). Satisfaction with service recovery: its measurement

and its outcomes. South African Journal of Business Management, 34 (3),

9–16.

Chung-Herrera, Beth G., Goldschimdt, Nadav & Hoffman, K. Doug. (2004).

Customer and employee views of critical service incidents. Journal of

Services Marketing, 18 (4), 241-254.

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commerce retail failures and recovery strategies. Journal of Services

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Goodwin, Cathy & Ross, Ivan. (1992). Consumer Responses to Service Failures:

Influence of Procedural and Interactional Fairness Perceptions. Journal of

Business Research 25, 149-163.

Goodman, J.A. & Ward, D.S. (1993). The importance of customer satisfaction. Direct

Marketing, 56, 23-6.

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Hoffman, K. Douglas, Kelly, Scott W. & Rotalsky, Holly M. (1995). Tracking service

failures and employee recovery efforts. Journal of Services Marketing, 9

(2), 49-61.

Hoffman, K. Douglas, Kelley, Scott W. & Chung, Beth C. (2003). A CIT

investigation of servicescape failure and associated recovery strategies.

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A Recovery Opportunity. Journal of Service Research, 6 (1), August, 92-

105.

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on consumer satisfaction: a comparison between complainants and non-

complainants. Journal of Services Marketing, 20 (2), 101-111.

Kelly, Scott W., Hoffman, K. Douglas & Davis, Mark A. (1993). A Typology of

Retail Failures and Recoveries. Journal of Retailing, 69 (4), 429-452.

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perceived justice on recovery satisfaction, trust, word of mouth and revisit

intention in upscale hotels. Tourism Management, 30 (1), February, 51-62.

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Diagnosing Favorable And Unfavorable Service Encounters in

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251-271.

La, K.V. & Kandampully, J. (2004). Market orientated learning and customer value

enhancement through service recovery management. Managing Service

Quality, 14 (5), 390–401.

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Questionnaire (Study I)

Dear Respondent

This research is being conducted as a part of PhD work titled “Service Failures and

Recovery Strategies- A Study of Indian Aviation Industry Since 2000”. The

data/information collected is purely for academic work and shall be kept confidential.

Demographic Profile of Respondents:

Belongs to: City:……………………….. State:……………………………

1. Gender: (a) Male (b) Female

2. Age: (a) below 20 (b) 20-40 (c) 40-60 (d) above 60

3. Income: (a) below Rs.10,000 (b) Rs.10,000-30,000

(monthly) (c) Rs. 30,000-50,000 (d) above Rs.50,000

4. Occupation: (a) service (b) business (c) student (d) others (…………….)

Think of the time when, as a passenger, you came across an incident that stands out in

your mind as either a particularly satisfying/positive or dissatisfying/negative

experience with the airline in domestic sectors of India during the last five years.

1. Demographic Profile

2. Was this a satisfying/dissatisfying experience?

3. Please describe the circumstances leading up to this incident.

4. Describe what happened during the incident. What specific details do you

recall that made this experience memorable for you?

5. What was the outcome of the incident?

6. How could this experience have been improved (if at all)?

7. Did you complain to the organization about this incident? If yes, how did

you complain? If no, why not?

303

Questionnaire (Study II)

Dear Respondent

This research is being conducted as a part of PhD work titled “Service Failures and

Recovery Strategies-A Study of Indian Aviation Industry since 2000”. The

data/information collected is purely for academic work and shall be kept confidential.

Demographic profile of the Respondent:

� Gender: Male Female

� Age (in years): (a) less than 20 (b) 20-40 (c) 40-60 (d) above 60

� Income (in Rupees): (a) less than 20,000 (b) 20,000-40,000

(per month) (c) 40,000-60,000 (d) above 60,000

� Travel Frequency by air: (a) less than 5 (b) 5-10 (c) 10-15 (d) above 15

(in a year)

� Travel purpose: (a) Business (b) Visit (c) Vacation

(d) Education (e) Other

� Do you prefer: (a) Low Cost Airline (b) Full Cost Airline

� Which is your most preferred airline?

(a) Air India (b) Jet Airways (c) Kingfisher Airlines

(d) Go Air (e) Indigo (f) Spice Jet

(g) Jetlite (h) Any other……………..

304

A: Indicate your level of seriousness w.r.t. each service failure by encircling at appropriate column. 1= Not at All Serious (NAS) , 2= Not

Very Serious (NVS), 3= Neutral (N), 4= Serious (S), 5= Very Serious (VS)

B: Indicate how frequently you had encountered the following service failure by encircling at appropriate column. 1= Never (N), 2=

Occasionally (Oc), 3= Sometimes (S), 4= Often (Of), 5= Always (A)

C: Do you think that the following service failure effected your satisfaction, indicate by encircling at appropriate column. 1= Strongly

Disagree (SD), 2= Disagree (D), 3= Neutral (N), 4= Agree (A), 5= Strongly Agree (SA)

A B C 1= Not at All Serious (NAS) , 2= Not Very Serious (NVS), 3= Neutral (N), 4= Serious (S), 5= Very Serious (VS)

1= Never (N), 2= Occasionally (Oc), 3= Sometimes (S), 4= Often (Of), 5= Always (A)

1= Strongly Disagree (SD), 2= Disagree (D), 3= Neutral (N), 4= Agree (A), 5= Strongly Agree (SA)

Type of Service Failure

NAS NVS N S VS N Oc S Of A SD D N A SA 1. Flight Delay 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 2. Non-availability of right information about flight delay

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

3. Mishandling of baggage 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 4. Delay of baggage delivery 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 5. Missing of baggage 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 6. Exchange of baggage 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 7. Unfriendly & unhelpful attitude of ground staff members

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

8. Unfriendly & unhelpful attitude of crew members

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

9. Mishandling of carry-on items/delicate items

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

10. Food & beverage not of high quality 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 11.Provision of food not on time 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 12. Non-availability of seat at departure terminal

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

13. Overbooking of passengers 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 14. Unfriendly & Uncomfortable ambience 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

305

for the travelers 15. Inconvenience due to non working of air condition in aircraft

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

16. No provision of any refreshment when there is long delay in flight

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

17. Less leg space 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 18. Inefficient staff 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 19. Delay in refund of cancelled ticket 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 20. Cancelled flight without prior notice 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 21. Rescheduling without prior notice 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 22. Printing mistake on ticket 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 23. Allow to carry-on items at one sector & deny the same at another sector by the same airline

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

24. Staff shows unwillingness to assist the customer in solving the problem arises due to customer error

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

25. Co-passengers show interrupted behavior

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

26. Theft of items which are under the scrutiny of staff members

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

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Section II

Think back about the latest dissatisfying/negative air travel experience that you came across, please describe it:

………………………………………………………………………………………………………………………………………………………………………

………………………………………………………………………………………………………………………………………………………………………

……………………………………………………………………………………………………………………………….

How likely is it that you would: -

Least Less Not More Most

Likely Likely Likely Likely Likely Likely (1) (2) (3) (4) (5) (6)

1. Forget about the incident and do nothing 1 2 3 4 5 6 2. Definitely complain to the airline staff members 1 2 3 4 5 6 3. Decide not to travel by that airline 1 2 3 4 5 6 4. Complain to the airline staff members and ask them to take care of your problem 1 2 3 4 5 6 5. Speak to your friends and relatives about your bad experience 1 2 3 4 5 6 6. Convince your friends and relatives not to travel by that airline 1 2 3 4 5 6 7. Complain to a consumer agency and ask them to make the airline take care of your problem 1 2 3 4 5 6 8. Write a letter to the local newspaper about your bad experience 1 2 3 4 5 6 9. Report to the consumer agency so that they can warn other consumers 1 2 3 4 5 6 10. Take some legal action against the airline 1 2 3 4 5 6

307

Did you complain to the airline about the service failure incident? YES NO

Please mark at the appropriate recovery strategy: S.No. Recovery Strategy Used by the airline against the

service failure experienced by you

That you think that

airline should do

1. Apologized 2. Corrected problem 3. Explanation provided 4. Immediate action 5. Did nothing 6. Airline took responsibility of the problem 7. Followed up 8. Redirected the problem 9. Compensation provided 10. Exceptional treatment

Indicate by encircling at appropriate column: 1= Very Strongly Disagree (VSD), 2= Strongly Disagree (SD), 3= Disagree (D), 4= Neutral (N), 5= Agree (A), 6= Strongly Agree (SA), 7= Very Strongly Agree (VSA) S.No. Items VSD

(1)

SD

(2)

D

(3)

N

(4)

A

(5)

SA

(6)

VSA

(7)

1. The incident caused me problems, the airline effort to fix it resulted in a very positive outcome for me

2. The final outcome I received from airline was fair, given the time & hassle 3. Inconvenience caused by the problem, the outcome I received from airline was fair 4. The service recovery outcome that I received in response to the problem was more than fair 5. Despite the hassle caused by the problem, the airline responded fairly and quickly 6. I feel airline responded in a timely fashion to the problem 7. I believe airline has fair policies & practices to handle problems 8. With respect to its policies & procedures, the airline handled the problem in a fair manner

308

9. In dealing with my problem, the airline personnel treated me in a courteous manner 10. During their effort to fix my problem, the airline employees showed a real interest in trying to

be fair

11. The airline employees worked as hard as possible for me during the recovery effort 12.

The airline employees were honest and ethical in dealing with me during their fixing of my problem

Indicate by encircling at appropriate column:

1= Very Strongly Disagree (VSD), 2= Strongly Disagree (SD), 3= Disagree (D), 4= Neutral (N), 5= Agree (A), 6= Strongly Agree (SA), 7= Very Strongly Agree (VSA) S.No. Items VSD

(1)

SD

(2)

D

(3)

N

(4)

A

(5)

SA

(6)

VSA

(7)

Overall Firm Satisfaction 1. I am satisfied with my overall experience with airline 2. As a whole, I am not satisfied with airline Satisfaction with Recovery 1. In my opinion, the airline provided a satisfactory resolution to my problem on this particular

incident

2. I am not satisfied with airline’s handling of the problem 3. Regarding the incident that I described above, I am satisfied with the airline

Indicate by encircling at appropriate column: 1= Very Dissatisfied(VD), 2= Somewhat Dissatisfied (SD), 3= Dissatisfied (D), 4= Neutral (N), 5= Satisfied (S), 6= Somewhat Satisfied ( SS), 7= Very Satisfied (VS)

S.No. Item VD (1)

SD (2)

D (3)

N (4)

S (5)

SS (6)

VS (7)

1. How satisfied are you overall with the quality of airline?

309

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