Dissertation Final

“Understanding Undergraduate students'

Purchasing Behaviour and Satisfaction towards

Quality low-input and Organic foods”

Tiezheng Yuan

Newcastle University

BA Honours Marketing and Management

1st May 2014

“Understanding Undergraduate students'

Purchasing Behaviour and Satisfaction towards

Quality low-input and Organic foods”

Dissertation submitted in partial fulfilment for the Degree of


Tiezheng Yuan

Newcastle University


1st May 2014

Confirmation

I confirm that this report is my own work and that all sources are fully referenced and

acknowledged.

Word count: 10316

Signature Date: 1st May 2014

i

Acknowledgements

I would like to thank my dissertation tutor, Dr Mitchell Ness, for his guidance and

encouragement throughout this academic year. I would also like to thank him for his patience

in answering all my questions. I would certainly miss the early morning appointments which

forces me to wake up early and start working.

I would like to thank my parents for giving me the opportunity to study abroad and helping

me in achieving my goals. I would also like to thank my sisters for their care and love

throughout my academic years.

I would like to thank my girlfriend, Angeline Tjandra, for her feedbacks and ideas. I would

also like to thank her for her support throughout my university studies.

Lastly, I would like to thank all questionnaire respondents for their help in completing the

questionnaire.

ii

Table of Contents

Acknowledgements i

Table of Contents ii

List of Figures vi

List of Tables vi

Abstract vii

I. Chapter 1. Introduction 1

1.1. Introduction 1

1.2. Background 1

1.2.1. Background of the UK Organic Market and Student Population 1

1.3. Aims and Objectives 3

1.4. Research Methodology 4

1.4.1. Research Objective and Research Methodology 5

1.5. Anticipated Contribution of Study 6

1.6. Structure of Study 6

1.7. Summary 7

II. Chapter 2. Literature Review – Organic Foods and Student Market 8

2.1. Introduction 8

2.2. The Organic Market 8

2.2.1. The UK Organic Market Environment 8

2.2.2. The UK Organic Consumer Environment 10

2.3. Overview of Student Population 12

2.3.1. UK Student Demographics 13

2.3.2. UK Student Food and Cooking 14

2.4. Summary 15

III. Chapter 3. Literature Review – The Theoretical framework 16

3.1. Introduction 16

3.2. Models of Purchase Behaviour 16

3.2.1. The Total Food Quality Model 16

3.2.2. Theory of Planned Behaviour 18

iii

3.2.3. Influence, Attributes and Satisfaction Model 19

3.2.3.1 Demographics 20

3.2.3.2 Motivations 21

3.2.3.3 Attributes 23

3.2.3.4 Overall satisfaction from quality low-input and organic foods 24

3.2.3.5 Perceived risk 25

3.3. Summary 25

IV. Chapter 4. Methodology 26


4.2. Secondary Data Collection 26

4.3. Primary Data Collection 26

4.3.1. Quantitative Data Collection 26

4.3.2. Questionnaire Design 27

4.3.3. Pre-testing and Development 27

4.3.4. Survey and Sampling Method 28

4.4. Reliability Analysis 28

4.5. Data Analysis 29

4.5.1. Exploratory Factor Analysis 29

4.6. Ethical Issues 30

4.7. Summary 30

V. Chapter 5. Results 31

5.1 Introduction 31

5.2. Sample Characteristics 31

5.3. Food Shopping Behaviour 32

5.3.1. Multiple Response Analysis 32

5.3.1.1 Place of food shopping 32

5.3.1.2 Ways of food shopping 33

5.3.2. Frequency Analysis 34

5.4. Attitudes to Food 35

5.4.1. Descriptive Analysis 35

5.4.1.1 Importance of food attributes 35

5.4.1.2 Perceived risk on food production process 36

iv

5.4.2. Factor Analysis 37

5.4.2.1 Importance of food attributes 37

5.4.2.2 Perceived risk on food production method 39

5.5. Attitudes to Organic Food 41

5.5.1. Frequency Analysis 41

5.5.1.1 Purchased organic categories 41

5.5.1.2 Future purchase likelihood of organic categories 41

5.5.2. Descriptive Analysis 42

5.5.2.1 Satisfaction level obtained from various organic attributes 42

5.5.2.2 Influences of benefits on decision to purchase 43

5.5.3. Factor Analysis 44

5.5.3.1 Satisfaction level obtained from different organic features 44

5.5.3.2 Effect of benefits on decision to purchase 46

5.6. Regression and Moderated Regression Analysis 48

5.6.1. Determinants of Purchase Likelihood 48

5.6.2. Determinants of Satisfaction 48

5.6.3. Purchase Likelihood and Satisfaction 48

5.6.4. Moderating effect of Gender on Purchase Likelihood 48

5.7. Summary 49

VI. Chapter 6. Discussion 50


6.2. Demographics 50

6.3. Food Shopping Behaviour 50

6.4. Attitudes to Food 51

6.5. Attitudes to Organic Food 51

6.5.1. Purchased Organic Categories 51

6.5.2. Motivations to Purchase 51

6.5.3. Satisfaction 52

6.6. Summary 52

v

VII. Chapter 7. Conclusion 53


7.1.1. Re-statement of Aims and Objectives 53

7.2. Summary of Key Findings 54

7.3. Marketing Implications 55

7.4. Limitations 56

7.5. Future Research 56

7.6. Summary 56

References 57

Appendices

Appendix 1. Questionnaire 63

Appendix 2. Reliability Analysis Output 72

Appendix 3. Importance of Food Attributes 81

Appendix 4. Perceived Risk on Food Production Process 82

Appendix 5. Importance of Food Attributes 82

Appendix 6. Perceived Risk on Food Production Method 88

Appendix 7. Purchased Organic Categories 90

Appendix 8. Likelihood Organic Categories 93

Appendix 9. Obtained from various Organic Attributes 96

Appendix 10.Influences of Benefits on Decision to Purchase 97

Appendix 11. Satisfaction Level Obtained from Different Organic Features 98

Appendix 12. Effect of Benefits on Decision to Purchase 103

Appendix 13. Determinants of Purchase Likelihood 108

Appendix 14. Determinants of Satisfaction 110

Appendix 15. Purchase Likelihood and Satisfaction 112

Appendix 16. Moderating Effect of Gender on Purchase Likelihood 114

Appendix 17. Ethical Form 118

vi

List of Figures

Figure 1. Research Methodology 4

Figure 2. UK Sales of Organic Products 1995–2013 8

Figure 3. Product Shares of the UK Organic Market 2012 9

Figure 4. Organic Sales by Social Grouping 2012 11

Figure 5. Total Number of Undergraduates from 2007 – 2012 12

Figure 6. Percentage of Undergraduate by Gender 13

Figure 7. Living Cost in Percentage among Full-time Undergraduate 14

Figure 8.The Total Food Quality Model (TFQM) 16

Figure 9.Theory of Planned Behaviour 18

Figure 10. Influences, Attributes and Satisfaction model 19

List of Tables

Table 1. Research Objectives 3

Table 2. Research Objective and Research Methodology 5

Table 3. Ranking Based on Market Share of Organic Sales 10

Table 4. Attributes of Organic Food 23

Table 5. Summary of Reliability Analysis 28

Table 6. Quantitative Technique used for Data Analysis 29

Table 7. Sample Characteristics 31

Table 8. Places of Food Shopping 32

Table 9. Ways of Food Shopping 33

Table 10. Frequency Analysis Food Shopping Behaviour 34

Table 11. Rotated Factor Matrix for Importance of Food Features 38

Table 12. Factor Matrix for Perceived Risk to Food Production Method 40

Table 13. Rotated Factor Matrix for Satisfaction Level Obtained 45

Table 14. Rotated Factor Matrix for Effect of Benefits on Decision to Purchase 47

Table 15. Re-statement of Aims and Objectives 53

Table 16. Summary of Key Findings 54

Table 17. Implications 55

vii

Abstract

The purpose of this study is to explore undergraduate students' purchasing behaviour and

satisfaction towards quality low-input and organic foods.

The study adopts an empirical approach which employs the usage of web-based

questionnaires. A total of 352 valid samples were gathered from full-time undergraduates

studying in Newcastle University.

The results indicated three similar dimensions for all three scales measuring importance of

food attributes, expected satisfaction level obtained from various organic features and effects

of benefits on decision to purchase respectively. The dimensions identified were Quality,

Support small and local producers, and Environment and animal welfare. The result also

revealed that undergraduate organic consumers are most concerned with usage of drugs,

fertilisers and pesticides in food production.

This research contributes to the academic literature as prior research concerning

understanding students' purchasing behaviour and satisfaction towards quality low-input and

organic foods is very limited. Secondly, this study seeks to segment and profile

undergraduates according to their attitude towards quality low-input and organic foods.

Practitioners can develop effective marketing strategies according to the dimensions

identified thus capturing more student audience.

1

Chapter 1. Introduction

1.1 Introduction

The aim of this research is to explore undergraduate students' purchasing behaviour and


This chapter is intended to present a brief outline of the study. It begins with Section 1.2

where it will provide the background of study. Next, Section 1.3 will identify the aims and

objectives of the study. This is followed by Section 1.4 where the research methodology will

be displayed in a logical sequence. Section 1.5 will identify the anticipated contributions of

the study. Section 1.6 will provide an overall outline of the structure of the study. Lastly,

Section 1.7 will summarise Chapter 1.

1.2 Background of Study

This section will provide the background of the UK organic market and student population.

1.2.1 Background of the UK Organic Market and Student Population

Wright (1990) noted that the UK public were increasingly aware of the health implications of

their chosen diets; as the demand for healthy food started to be recognised. In 21st century,

UK food consumers started to increase their awareness towards the quality issues concerning

taste, environment and ethics, besides health (Makatouni, 2002; Padel and Foster, 2005;

Bertil and Martine, 2006). In UK, this development is characterised by the fact that the

organic market increased by almost nine times between 1995 to 2013, £140 million to £1200

million (Clifford, 2013), while there is also evidence of the emergence of the demand for

quality low-input foods (Stolz et al., 2011). Confronted by these market conditions, organic

food marketers and retailers are required to formulate strategies that differentiate the products

that they offer, in order to gain a larger market share and ensure survival and prosperity in the

long run (Anderson et al., 1994; Laverty, 2001; Kristensen et al., 2001; Boddy, 2011; Baines

et al., 2011; Rego et al., 2013).

Attracting more student consumers could be a viable solution for marketers in the current

situation. The business potential of the graduate market has been recognised by some

marketers as graduates are more likely to be employed and enjoy higher income compared to

non-graduates (Murray and Robinson, 2001; Grundy and Jamieson, 2002; Helyer and Lee,

2012). Hence, they have become the primary interest to commercial marketers because of

2

their future potential, an aspect that has attracted the attention of the e–commerce sector

(Teach and Schwartz, 2003). However, the business potential of student segment has been

overlooked by both academic and commercial marketers over the years (Knutson, 2000; Ness

et al., 2002, Zopiatis and Pribic, 2007). Evidence of commercial potential of the student

segment can be identified from the total number of undergraduates (full and part-time) in the

academic year of 2010/2011. It was estimated at 1.9million, studying in 189 institutions

across UK (National Statistic, 2013; Euromonitor, 2013). The student population has

increased by 7.1% between 2007 and 2011, it is forecasted that this number will continue to

grow (Mintel, 2011). It is estimated that universities in UK contributed £3.3billion to the

economy in 2010-11 alone (Higher Education Funding Council England, 2012).

3

1.3 Aims and Objectives

The aim of the research is to explore undergraduate students' purchasing behaviour and


Research objectives are defined in Table 1.

Table 1. Research Objectives

Objective

Label

Objective Defined

Objective 1 To provide an overview of the quality low-input foods and organic foods

market

Objective 2 To provide an overview of the UK student population

Objective 3 To investigate the demography of student consumers of quality low-input

and organic foods

Objective 4 To investigate the food shopping behaviours of undergraduates

Objective 5 To measure the importance of food features that undergraduates attach

Objective 6 To identify underlying dimensions of students’ attitude to food features in

general

Objective 7 To measure undergraduates’ perceived risk concerning food production

methods

Objective 8 To identify underlying dimensions of undergraduates’ perceived risk to

food production methods

Objective 9 To identify the driving features of customer satisfaction towards quality

low-input and organic foods

Objective 10 To identify underlying dimensions of student satisfaction level obtained

from various organic features

Objective 11 To investigate the future purchase likelihood of organic categories

Objective 12 To measure the effect of benefits of different organic features on decision

to purchase

Objective 13 To identify the underlying dimensions of effect of benefits on decision to

purchase

4

1.4 Research Methodology

Figure 1 displays an overview of the research methodology for this dissertation. Elements of

secondary and primary research aim to investigate the objectives previously mentioned, thus

achieving the overall aim.

Figure 1. Research Methodology

To explore undergraduate students' purchasing behaviour and


Empirical research setting

Market review on organic and quality

low-input foods

Market review on the UK student

population

Theoretical Perspective

Critical review on the models of

purchase behaviour

In-depth discussion on Influences,

Attributes and Satisfaction model

Quantitative Methodology

Quantitative elements of the questionnaire

Results

Analysis of questionnaire through SPSS

Discussion

Combine and discuss results from both primary and secondary data

Conclusion

Identify practical implications, limitations and suggestions

5

1.4.1 Research Objective and Research Methodology

Table 2 explains the research methodology used to achieve each objective.

Table 2. Research Objective and Research Methodology

Objective

Label

Objective Defined Research Methodology

Objective 1 To provide an overview of the quality low-

input foods and organic foods market

Literature review

Objective 2 To provide an overview of the UK student

population

Literature review

Objective 3 To investigate the demography of student

consumers of quality low-input and organic

foods

Literature review

Frequency analysis

Objective 4 To investigate the food shopping behaviours

of undergraduates

Literature review

Frequency analysis

Multiple response

Objective 5 To measure the importance of food features

that undergraduates attach

Descriptive analysis

Objective 6 To identify underlying dimensions of

students’ attitude to food features in general

Literature review

Reliability analysis

Factor analysis

Objective 7 To measure undergraduates’ perceived risk

concerning food production methods


Objective 8 To identify underlying dimensions of

undergraduates’ perceived risk to food

production methods

Literature review


Factor analysis

Objective 9 To identify the driving features of customer

satisfaction towards quality low-input and

organic foods


Regression

Objective 10 To identify underlying dimensions of student

satisfaction level obtained from various

organic features

Literature review


Factor analysis

Objective 11 To investigate the future purchase likelihood

of organic categories

Frequency analysis

Regression

Moderated regression

Objective 12 To measure the effect of benefits of different

organic features on decision to purchase


Objective 13 To identify the underlying dimensions of

effect of benefits on decision to purchase


Factor analysis

6

1.5 Anticipated Contribution of Study

This research is of value to both academics and practitioners. Firstly, this research contributes

to the academic literature as prior research with regards to understanding students' purchasing

behaviour and satisfaction towards quality low-input and organic foods has been inadequate.

Secondly, this study seeks to segment and profile undergraduates according to their attitude

towards quality low-input and organic foods. Practitioners can develop effective marketing

strategies according to the dimensions identified thus capturing more student audience.

1.6 Structure of Study

Chapter 2 will outline the empirical setting of the study. Firstly, it will provide an in-depth

overview of the quality low-input and organic foods market. Secondly, an overview of the

student population will also be provided, so readers are able to have a better

comprehension towards the student market situation.

Chapter 3 will provide the literature review; this comprises secondary literature relating to

various theoretical frameworks. It will therefore begin with a review of Total Food

Quality Model (TFQM). This is followed by Theory of Planned Behaviour and lastly

Influence, Attributes and Satisfaction model.

Chapter 4 as the research methodology section is going to provide an explanation of the

methodology used in this research. The primary data collection employs web-based

questionnaire. The analysing methods are introduced in this chapter as well.

Chapter 5 will introduce the ensuing quantitative data results, aiming to answer the

respective research objectives.

Chapter 6 will combine and discuss these research findings from both primary and

secondary data gathered.

Chapter 7 will identify the practical implications of the results, expose the study’s

limitations, and suggest areas for future research.

7

1.7 Summary

This introductory chapter has provided a brief overview of the contents of the study, while

also clearly presented its aims and objectives. This research attempts to bridge the existing

gap in the literature with regards to understanding undergraduates' purchasing behaviour

and satisfaction towards quality low-input and organic foods. The following chapter

acquaints the reader with the market situation of the organic food industry and the student

population.

8

Chapter 2. Organic Foods and Student Market

2.1 Introduction

Chapter 2 aims to provide the empirical setting, within which the research has been

conducted. Firstly, Section 2.2 will provide an overview of the UK organic market from

two dimensions, the market environment and consumer environment. Next, Section 2.3

will provide an overview of the UK student population. Finally, the empirical research

setting is summarised in Section 2.4.

2.2 The Organic Market

This section displays an overview of the UK organic market from two dimensions, the

market environment and consumer environment.

2.2.1 The UK Organic Market Environment

The organic food sector has traditionally been very much a specialist niche market, and it

is now becoming an increasingly visible element in the major food retailers' offer (Jones

et al., 2001). In UK, this development is characterised by the fact that the organic market

(Figure 2) has grown from £140 million in 1995 to £1200 million in 2013 (Clifford, 2013;

Soil Association, 2013).

Figure 2. UK Sales of Organic Products 1995–2013

Source: Adapted from Soil Association (2013)

0

500

1000

1500

2000

2500

1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Sa

les

£ M

illi

on

Year

UK Sales of Organic Products 1995–2013

9

Online sales have been on the raise, representing 10.1% of major retailers’ sales and this

leads to the fact that organic shoppers are currently spending £4.1 million online every

week (Soil Association, 2013).

In the large retailer stores the most popular organic purchases (Figure 3) are dairy and

‘chilled convenience’ products (31%) and fresh fruit and vegetables (23%).

Figure 3. Product Shares of the UK Organic Market 2012

Source: Soil Association (2013)

Dairy/chilled

convenience, 30.8

Fruit, vegetables

and salad, 22.8

Baby food, 13.9

Beverages, 6

Fresh

meat, 5

Fresh poultry and

game, 1.6 Fresh fish, 0.6

Product Shares of the UK Organic Market 2012

10

Tesco and Sainsbury (Table 3) are the market leaders in terms of organic sales. However,

Ocado (online grocer) experienced the fastest growth in sales (6.4%). It jumped two

positions up to number 4 overtaking Asda and Morrisons. In addition, their sales were

anticipated to grow 10-15% in 2013 for Ocado (Soil Association, 2013).

Table 3. Ranking Based on Market Share of Organic Sales

Rank Company Name

1 Tesco

2 Sainsbury’s

3 Waitrose

4 Ocado

5 Asda

6 Morrisons

7 Co-operative

8 Marks & Spencer


2.2.2 The UK Organic Consumer Environment

Compared to 2011 young organic shoppers (below-28s) now are spending more on

organic products. Retired people and ‘empty nesters’ are still the majority of all UK

spending on organic products (48.6%) but the ‘Jamie Generation’ of ethically aware

under-35s (16% of sales) significantly increased their average spending in 2012 (Soil

Association, 2013; Mintel, 2013). Planet Organic (2013), a leading London organic

retailer, mentioned that students became an increasingly important part of its customer

base, accounting for 10% of all sales in its five stores and student purchases increased by

15% in 2012.

11

The socio-demographic class of ABs (38%) is the largest consumer segment of organic

foods, shown in Figure 4. Followed by C1 constituting 32% and lastly C2, D and E

constituting 29.8% (Soil Association, 2013).

Figure 4. Organic Sales by Social Grouping 2012


AB

38%

C1

32%

C2, D, E

30%

Organic Sales by Social Grouping 2012

12

2.3 Overview of UK Student Population

Euromonitor (2013) put the total number of undergraduates (Figure 5) in 2012 at 2 million,

studying in 189 institutions across UK. The student population increased by 7.1% between

2007 and 2011, it was forecasted that this number would continue to grow (Mintel, 2011).

This increase was partially driven by the rise in number of foreign students, who

accounted for 16.8% of students in 2012, up from 14.9% in 2007 (Euromonitor, 2013).

Figure 5. Total Number of Undergraduates from 2007 - 2012

Source: Euromonitor (2013)

1550

1600

1650

1700

1750

1800

1850

1900

1950

2000

2050

2100

2007 2008 2009 2010 2011 2012

Un

der

gra

du

ate

s in

00

0

Year

Undergraduate Total

13

2.3.1 UK Student Demographics

The number of female students continues to outnumber males over the years (Figure 6).

Furthermore, in 1980/81, there were 56.6% male and 41.4% female students, whereas, by

2009/10 there were 44.7% male and 55.3% female undergraduates in total.

Figure 6. Percentage of Undergraduate by Gender

Source: Higher Education Statistics Agency (2013)

0

10

20

30

40

50

60

70

1980/81 1990/91 2005/06 2007/08 2009/10

Per

cen

tag

e

Year

Percentage of Undergraduate by Gender

Men

Women

14

2.3.2 UK Student Food and Cooking

According to Student Income and Expenditure Survey (2013), food accounted for over a

quarter of student expenditure (Figure 7). This survey also estimated that on average

student spent about £1,884 per academic year on food (Student Income and Expenditure

Survey, 2013).

Figure 7. Living Cost in Percentage among Full-time Undergraduate

Source: Student Income and Expenditure Survey (2013)

According to Mintel (2010), 57% of undergraduates preferred cooking food from scratch

rather than consuming convenience foods. Within this group, 62% are females and 38%

are males. Mintel (2010) also mentioned that there are more second and third year

undergraduates who knows/prefer to cook compared to year one undergraduate.

Other

1% Household goods

5%

Entertainment

16%

Travel

23%

Personal item

27%

Food

28%

Living Cost in Percentage among Full-time Undergraduate

15

2.4 Summary

This chapter has outlined the empirical setting of the research. Firstly, it provided an

overview of the UK organic market from two dimensions, the market environment and

consumer environment. Next, an overview of the UK student population has also been

presented. In the following chapter, this study will continue on to review the theoretical

literature with the most relevance to the study.

16

Chapter 3. The Theoretical Framework

3.1 Introduction

Chapter 3 aims to provide the theoretical setting, within which the research has been

conducted. Firstly, Section 3.2 will review on the models of purchase behaviour which

includes the review of the Total Food Quality Model in Section 3.2.1, Theory of Planned

Behaviour in Section 3.2.2 and lastly Influences, Attributes and Satisfaction model in

Section 3.2.3. Finally, the theoretical research setting is summarised in Section 3.3.

3.2 Models of Purchase Behaviour

Since the 1940s, models of purchase behaviour have been developed to satisfy the

objectives of describing and predicting consumer behaviour, so that a better understanding

of consumers, both present and prospective, is achieved (Chisnall, 1995).

3.2.1 The Total Food Quality Model

The Total Food Quality Model (TFQM) of Grunert et al. (1997) depicted in Figure 8

emphasises the distinction between pre and post purchase evaluations.

Figure 8. The Total Food Quality Model (TFQM)

Source: Grunert (1997)

17

The pre-purchase component of the model illustrates how quality expectations are formed

based on the availability of quality cues. The intrinsic quality can be measured objectively

and is related to the product’s technical specifications. All other characteristics, such as

brand name, price and packaging represent extrinsic quality cues. Grunert et al. (2004)

explain that of all the cues consumers are exposed to, only those which are perceived will

have an influence on the expected quality.

Consumers will often have an experience which deviates from the expected quality after

the purchase. The product itself, especially its sensory characteristics will influence the

experienced quality. According to Grunert et al. (2004), the relationship between quality

expectation and quality experience is commonly believed to determine product

satisfaction and, consequently, the probability of repeat purchase.

18

3.2.2 Theory of Planned Behaviour

The Theory of Planned Behaviour of Ajzen (1991) depicted in Figure 9 is a model that

correlates a person’s attitudes and behaviours. Ajzen (1991) specifies that a person’s

behaviour is determined by their intentions and perceived behavioural control. In turn, the

individual’s attitude toward the behaviour, subjective norm and the perceived control of

the behaviour all contribute towards the prediction of the individual’s behaviour (Ajzen ,

1991).

Figure 9. Theory of Planned Behaviour

Source: Adapted from Ajzen (1991)

Researchers frequently implement the Theory of Planned Behaviour to predict behaviour

patterns ranging from shoplifting (Tonglet, 2002) to attending demonstration rallies

(Louis et al., 2004). Furthermore, the theory of planned behaviour has also been applied in

the domain of eating behaviours. Godin and KoK (1996) applied the model in their study

to test the efficiency of the theory concerning health related behaviours. More recently,

Louis et al. (2007) applied the model to a research identifying what embodies a student’s

decisions to eat healthily or unhealthily.

19

3.2.3 Influences, Attributes and Satisfaction Model

Figure 10. Influences, Attributes and Satisfaction model

Source: Adapted from Paul and Rana (2012)

The Influences, Attributes and Satisfaction model depicted in Figure 10 will be the main

model used in this study as this study focuses on understanding the factors influencing the

intention of undergraduates to purchase organic food. Specifically, four factors were

identified as most relevant and they are influences, attributes, satisfaction and perceived

risk.

Influences Demographics

Motivations

Intention to

Purchase

Overall

satisfaction

from quality

low-input and

organic foods

Attributes Benefits

Attitudes to food

Perceived Risk

to food

production

20

3.2.3.1 Demographics

Many studies focused on profiling the demographics of organic consumers based on age,

gender and other socio-demographic and socio-economic factors (Whitehead, 1991;

Cameron and Englin, 1997; Blomquist and Whitehead, 1998; Engel and Potschke, 1998;

Witzke and Urfei, 2001; Dupont, 2004; Israel and Levinson, 2004; Hidano et al., 2005).

Predominantly, studies are consistent to identify that the purchasers of organic foods are

primarily female (Davies et al., 1995; Fotopoulos and Krystallis, 2002). A study

conducted by Sriram and Forman (1993) discovered that the percentage of female organic

consumers were higher than male. The findings of Sriram and Forman (1993) were

supported by the work of Connor and Bord (1997). Connor and Bord (1997) reviewed 19

studies administered in the decades of the 1980s and the 1990s that explored gender

differences in 'risk-related environmental issues' such as food preservatives and irradiated

food, women express greater concern in 95% of the study. This trend is also proven to be

consistent in modern day research. The studies conducted by Doorn and Verhoef (2011)

identified that women consider organic food more important and include it in their

purchase.

However, modern day organic food researchers are noticing a gradual change in gender

composition of organic consumers. An empirical study conducted by Paul and Rana (2012)

discovered that there is no significant difference in gender composition of organic

consumers. Moreover, a research conducted by Mintel (2013) discovered that men are

more likely than women to choose organic because it tastes better. Therefore, there are

some inconsistencies in modern day literature and that is one aspect this study will

investigate.

High disposable income is another characteristic of organic consumers that many previous

studies had identified. Clifford (2013) mentioned that purchasers of organic foods and

drinks are typically affluent ABs and consumers living in London. Earlier studies by

Davies et al. (1995) claims that there appears to be a relationship between the amount of

disposable income available and corresponding extent of purchase of organic food. Davies

et al. (1995) also mentioned that those in the lowest income bracket are least regular

purchasers of organic produce. This argument is further supported by other two authors

who mentioned that higher income households purchase organic produce more frequently

(Govidnasamy and Italia, 1990; Loureiro et al., 2001).

21

On the contrary, some marketers of organic foods dispute the claim that high disposable

income is one characteristic of organic consumers. Fotopoulos and Krystallis (2002) argue

that despite high price premiums for organic food, higher household incomes do not

necessarily indicate higher likelihood of organic purchases. Some lower income segments

seem to be more entrenched buyers. This is supported by the research conducted by Paul

and Rana (2012), where they found household income is not significant in profiling the

characteristics of organic consumers. Therefore, this would be another aspect in

demographics that this study will investigate.

3.2.3.2 Motivations

Many authors have attempted to examine consumers’ motivation towards purchasing organic

foods (Roddy et al., 1994; Davies et al., 1995; Grunert and Juhl, 1995; Hutchins and

Greenhalg, 1997; Lohmann and Foster, 1997; Makatouni, 1999; Soil Association, 2000).

Consumers purchase organic food mainly for health reasons (Tregear et al., 1994; Davies et

al., 1995; Morris, 1996; Lohmann and Foster, 1997; Makatouni, 1999; Soil Association,

2000). This is supported by House of Lords select Committee on European Communities

(1999) report which concludes that healthiness is the prime factor contributing to the

willingness of the public to pay premium prices for organic food. Besides that, the effects of

health scares have played an important role in motivating consumers to purchase organic

foods (Davies et al., 1995; Jones et al., 2001; Clifford, 2013). For example, Lacey (1992)

mentioned 12 important cases in the UK in a period of three years 1988-1991; it began with

the Salmonella outbreak in eggs in 1988, which attracted significant media attention. Other

food items such as soft cheese, pate, margarine, seafood and liver were issued public safety

warnings. Warnings also covered means of cooking such as the use of microwave ovens and

cook-chill techniques (Davies et al., 1995). Furthermore, the horsemeat scandal in 2013 also

benefited the market to a certain extent, by encouraging more shoppers to choose products

which promise a higher level of sourcing integrity such as organic (Clifford, 2013). These

types of food scares have resulted in an apparent lack of consumer confidence in

manufacturers, with supermarkets and farmers being deemed more trustworthy than food

manufacturers (Davies et al., 1995; Fotopoulos and Krystallis, 2002). This distrust also

contributes to the move towards organically produced food.

22

Taste is another motive identified by scholars however there is little consensus in the view

that organic produce tastes better than non-organic produce (Fotopoulos and Krystallis, 2002).

The perception of improved taste in organically grown fruit and vegetables is more likely

linked to the use of varieties that give lower yields, but improved flavour. According to

Mintel (2013) approximately 31% of organic consumers provided improved taste as the

reason of purchase.

Environmental and animal welfare are also one important motive identified by scholars.

According to experts, soil fertility can be improved by the addition of organic matters. In

addition, the natural fixation of nitrogen will reduce the pollution of watercourses and

therefore biodiversity is encouraged (Jones et al., 2001). Onozaka et al. (2010) further

emphasised that pollution and high levels of carbon footprint were negatively valued by most

organic shoppers. Animal welfare benefits are said to include treating animals with respect,

reduction in injury and disease resulting from less intensive production and the practice of

natural feeding (Jones et al., 2001; Shepherd et al., 2005; Euromonitor, 2008; Bezawada and

Pauwels, 2013). According to a research conducted by Wandel and Bugge (1997), they

discovered that the age group (15 to 24 years) named consideration for the environment and

animal welfare as key reasons for purchasing organic food, whereas in the older age groups

concern for their own health was the most important reason.

Economic consideration is one motive that some consumers have (Shepherd et al., 2005;

Onozaka et al., 2010). These consumers support locally produced products and regard the

interest of local businesses as highly important. Besides that, employment and job creation

are also a part of their economic motivation to purchase organic products (Shepherd et al.,

2005). According to Mintel (2013) research, British origin is the most important factor

influencing purchasing decision concerning food in UK.

Lastly, Euromonitor (2008) identified premium indulgence as one motive that some organic

consumers have. These buyers are attracted by organic product's premium positioning and

through the purchase of organic products they wish to display their character and socio status

(Euromonitor, 2008). Therefore, it can be seen that there are many motivations influencing

the purchase of organic foods and this study is interested in investigating the relative

importance of each motivation.

23

3.2.3.3 Attributes

Most researchers and practitioners agree that customer satisfaction depends on a number of

determinants at a product attribute level and attribute performance plays a significant role in

customer satisfaction formation (Yi, 1990; Oliver, 2010). In order to achieve a strong

customer satisfaction-profit connection, organic retailers should put an emphasis on attributes

that maximises customer satisfaction (Knutson et al., 2003; Yoo et al., 2011). Therefore, the

attributes of organic foods (Table 4) are identified.

Table 4. Attributes of Organic Food

Categories Attributes Descriptions

Organic Farming No artificial chemical

fertilisers

Use of healthy and fertile soil by planting

and rotating a variety of crops, use of

natural fertilisers and using clover to fix

nitrogen from the atmosphere

No pesticides Use of wildlife to control pests and disease

Animal welfare Free-range life for farm animals

Diversity of crops and

animals

A variety of crops and animals are raised to

encourage diversity. Crops are rotated over

several seasons and allowed to fallow. This

improves the fertility of soil and also helps

break cycles of pests and disease

No drugs, antibiotics and

wormers

Preventative methods such as keeping

smaller herd sizes and moving animals to

fresh pasture are used

No genetically modified

elements

No Genetically modified (GM) crops and

ingredients are used

Organic Animals Must have access to fields Truly free range

Must have plenty of space Helps to reduce stress and disease

Natural diet A truly natural diet and free from

genetically modified ingredients

Limited drug use Usages of drugs are only allowed to treat an

illness. Routine use of antibiotics is

prohibited

No growth hormones Growth hormones are strictly prohibited

No cloning Must not be produced from cloned animals

24

3.2.3.4 Overall satisfaction from quality low-input and organic foods

Consumers have different satisfaction level from different types of food, organic as well as

inorganic. Researches have shown that, overall satisfaction from organic food can be more

than inorganic food. This is partially due to the difference perception between organic

products and inorganic products within the consumers (Paul and Rana, 2012). They are being

differentiated with respect to their attributes together with taste, visual appeal or freshness.

Consumers do not solely differentiate based on the process but also on the quality and safety

characteristics of organic food also. Organic products are purchased because of its superior

perception, due to these unique attributes. This claim is supported by Boorn and Prescott

(2002) who highlighted the nutritive, sensory and food safety as the points of comparison

between organic and conventional food in their study. Some consumers choose organic food

due to its improved taste, freshness and appearance (Beharrell and MacFie, 1991). On the

other hand, others choose organic products due to its environmental conservation practices

(Slevitch et al., 2013). Many consumers also think that additives are an undesirable

component in food products and therefore organic food is a better choice (Wright, 1990).

Besides that, consumers are also concerned about the production method where chemical

fertilisers and pesticides were used.

On the other hand, some consumers did not find further difference between organic and

inorganic foods (Jolly and Norris, 1991; Sparling et al., 1992). Some contrasting conclusions

have been drawn regarding the contents of organic products (Slanina, 1995). Williams (2002)

who conducted a study comparing the nutritional aspects of organic and inorganic foods

concluded that few differences could be demonstrated and where differences were detected

they were very small. There seems to be a continuous debate about whether consumers are

more satisfied with organic or inorganic foods (Paul and Rana, 2012). In addition, which

attribute of organic products satisfy consumers the most is also a point of discussion.

Therefore, this research is interested in testing this phenomenon.

25

3.2.3.5 Perceived risk

The theory of perceived risk was first proposed by Bauer (1960). Bauer (1967) suggested that

consumer behaviour involves risk and any action will produce consequences which are

difficult to anticipate and some of which at least likely to be unpleasant. The underlying

principles of perceived risk were uncertainty and consequences. The consequences

component was subdivided into various losses. Jacoby and Kaplan (1972) classified four

types of loss: financial, time, physical and psychosocial loss. Due to the many health issues

related to food consumption, authors generally expect physical loss to be the most important

loss for food products. Physical loss is the physical harm done to the purchaser as a result of

product or service failure (Mitchell and Greatorex, 1992). In a research conducted by

Mitchell and Greatorex (1992) on 75 undergraduate students, the study confirmed that

physical loss was of greater importance than other losses. An example of physical loss would

be food poisoning. Food Standards Agency (2014) estimated that there were 460000 cases of

food poisoning each year in the UK.

Food scares have the biggest influence on perceived risk. For example, in 1988, the then

Junior Health Minister, Edwina Currie made an infamous remake that, ‘Most of the egg

production in this country, sadly, is now infected with salmonella’. Being misinterpreted and

misreported, headlines read, ‘Most eggs are infected with salmonella’. This increases the

perceived risk of egg consumption and egg consumption plummeted. By April 1989, egg

sales were still about 25% below pre-December levels (Mitchell and Greatorex, 1992).

3.3 Summary

This chapter has outlined the theoretical setting of the research and it had conducted a review

on the models of purchase behaviour which includes Total Food Quality Model, Theory of

Planned Behaviour and Influences, Attributes and Satisfaction model. In the following

chapter, this study will explain the methodology of the study.

26

Chapter 4. Methodology

4.1 Introduction

Chapter 4 explains the methodology used to examine undergraduates’ purchasing behaviour

and satisfaction towards quality low-input and organic foods. Section 4.2 will explain how

secondary data was collected and informed the primary research. This is followed by Section

4.3 where primary data collection is explained. Next, Section 4.4 will explain the theory of

reliability analysis and it will also present the results. Next, Section 4.5 will explain the

techniques used for data analysis. Section 4.6 will deal with the ethical issues of the research.

Lastly, Section 4.7 will summarise this chapter.

4.2 Secondary Data Collection

Secondary research is conducted before primary research and it provides insights on

influences, attributes, customer satisfaction and perceived risk. The data is collected from

books, databases and academic journal articles to build a theoretical background for

subsequent research. The secondary data collected helps to provide information and guideline

in designing the primary research.

4.3 Primary Data Collection

This study employs a quantitative primary data collection technique which quantifies data

from a large sample to then apply statistical analysis (Malhotra and Birks, 2007). Many

researchers indicate that statistical information derived from numerical data analysis can be

more objective and unbiased compared to qualitative research (Pride et al., 2008).

4.3.1 Quantitative Data Collection

Electronic questionnaire was applied as a data-collection instrument, which gathers numerical

data from a wide range of respondents. There are several advantages of using electronic

questionnaire: firstly, it provides better representativeness; secondly, it is inexpensive and

easy to administer; thirdly, respondents can answer at their own convenience (Sekaran and

Bougie, 2009; Sincero, 2012). Qualtrics.com was used to construct and host the questionnaire

online. The objective of the questionnaire is to understand undergraduates’ purchasing

behaviour and satisfaction towards quality low-input and organic foods.

27

4.3.2 Questionnaire Design

The questionnaire was organised in four thematic sections: food shopping behaviour;

attitudes to food; attitudes to organic food; and, students’ characteristics. The theme of food

shopping behaviour was drawn from previous work by Ness et al. (2010) and was concerned

with nominal measures of shopping behaviour, outlet where the product is obtained, the

frequency of food shopping, the use of a store card, the use of a food budget, weekly food

expenditure category, ways of food shopping and influences by cultural or religious beliefs.

The second section concerned food in general. It consists of a 21-item scale designed to

measure the importance of food attributes that are related to the wider implications of food

choice (1= Not at all important, 5= Very important). It also consists of an 8-item scale

designed to measure perceived risk concerning food production methods (1= Not at all

concerned, 5= Very concerned). The measures were adapted from the study by Ness et al.

(2010). The third section deals with organic food. It consist of measures relating to the

frequency of organic food purchase for eight product categories and future purchase

intentions for the same product categories. A 21-item scale was also used to measure

expected satisfaction level obtained from various organic features (1= Very low, 5= Very

high). A further 23-item scale was used to measure effect of benefits on decision to purchase

(1= Very low, 5= Very high). The scales were adapted from the study by Ness et al. (2010).

The final section focused on student characteristics and employed nominal measures of

gender, year of study, ethnic origin, religion and household income. The questionnaire is

presented in Appendix 1.

4.3.3 Pre-testing and Development

The initial version of the questionnaire was developed from the literature (Ness et al., 2010)

and refined through consultation with the original author. A paper copy of the questionnaire

was pre-tested using a student sample. Minor modifications to question wording were made,

in response to feedback. The final version of the questionnaire was evaluated in terms of

instructions, ease of use, reading level, clarity, item wording, and response formats and was

judged to possess face and context validity (De Vellis, 2003; Saunders et al., 2009).

28

4.3.4 Survey and Sampling Method

The study employed a Web-based survey. Invitations to complete the questionnaire were

included in an Email forwarded to 900 undergraduate students. Screening questions specified

that respondents should be full-time undergraduates who were responsible for buying their

own food. The advantages of using web-based survey are firstly, it can be sent to many

respondents in a short time at a low cost. Secondly, the data gathered can be automatically

transferred into the computer and processed using statistical software thus, it is beneficial for

making quick online tabulation of results (Rubin and Babbie, 2010). Qualtrics.com was used

to construct and host the questionnaire online. The study employed a convenience sample of

undergraduate students of Newcastle University, United Kingdom. A convenience sample

was judged to be the most effective way to recruit a student sample. The survey yielded a

total of 352 useable responses.

4.4 Reliability Analysis

Scale reliability is evaluated using Cronbach's alpha coefficient on SPSS (SPSS, 2012), a

measure of how well a set of manifest indicators measure the scale (De Vellis, 2003, p.47).

There is no universal convention with respect to the minimum acceptable threshold value.

Nunally (1978) recommends an alpha value of 0.7, while Robinson et al., (1991, in Hair et al.,

2006, p.137) suggest that a value of 0.6 is acceptable for exploratory research. However, De

Vellis (2003, p. 95) notes that it is not unconventional for researchers to use scales with lower

reliability coefficients. The criterion adopted in the study was to apply a minimum threshold

level of 0.7 for the alpha coefficient. The results of reliability analysis are presented in Table

5 and the full SPSS output is to be found in Appendix 2.

Table 5. Summary of Reliability Analysis

Construct Number of items Cronbach's alpha

Attitudes to food 21 0.945

Perceived risk 8 0.944

Satisfaction 21 0.955

Benefits 23 0.961

29

4.5 Data Analysis

Analyses were conducted using SPSS (2012). Table 6 presents the quantitative techniques

used for data analysis.

Table 6. Quantitative Technique used for Data Analysis

Data Quantitative Technique

Sample characteristics Frequency distributions

Food shopping behaviour Multiple response and frequency

analysis

General attitudes to food Descriptive analysis and factor analysis

Attitudes to organic food Frequency, descriptive and factor

analysis

Purchase likelihood Regression analysis

Satisfaction Regression analysis

Purchase likelihood and satisfaction Regression analysis

Effect of gender on purchase

likelihood

Moderated regression

4.5.1 Exploratory Factor Analysis

Exploratory factor analysis is a technique that identifies the underlying dimensions of metric

correlated data. Besides that it also achieves data reduction so that original set of variables are

replaced by smaller set of factors. The factors are derived in descending order of importance

in terms of their contributions to the explanation of the total variance of the scale. The broad

aims of the analysis are to identify the number of factors and interpret what they represent.

The theoretical framework is the factor model that explains the observation on the original

variable, its variance and the covariance between pairs of variables. According to the model

the original variables are determined by a linear combination of common factors and the

influence of a unique factor. The model is based upon a series of assumptions. The original

variables and the common factors are standardised to have zero mean and unit variance. The

co-variances between common factors, unique factors and between pairs of common factors

and unique factors are zero.

In this study factor analysis is applied to four scales; a 21-item scale designed to measure the

importance of food attributes that are related to the wider implications of food choice (1= Not

at all important, 5= Very important); a 8-item scale designed to measure perceived risk

30

concerning food production methods (1= Not at all concerned, 5= Very concerned); a 21-item

scale used to measure expected satisfaction level obtained from various organic features (1=

Very low, 5= Very high) and lastly a 23-item scale was used to measure effect of benefits on

decision to purchase (1= Very low, 5= Very high).

The analysis employs principal components analysis and extracts factors with eigenvalues

greater than unity with Varimax rotation. Confirmation that the data are correlated is

evaluated using Bartlett’s test for sphericity, adopting a significance level of five per cent.

Goodness of fit is reported and evaluated using communalities and total variance explained.

4.6 Ethical Issues

The data was collected in accordance with the Data Protection Act 1998. Participants were

informed that their involvement was completely voluntary and the questionnaire should

require no offensive or sensitive information. Participants were also informed that they are

free to withdraw at any stage and their responses would remain anonymous and confidential.

Ethical approval application was submitted and granted by Newcastle University for the

research (see Appendix 17).

4.7 Summary

This chapter has explained how secondary and primary data were collected. It has also

explained the theory of reliability analysis and the results are also presented. In addition, this

chapter also explained the analytical techniques used in the study. Lastly, the ethical issues

concerning the study are also explained. In the following chapter, the results of the analysis

will be presented.

31

Chapter 5. Results

5.1 Introduction

Chapter 5 will present the results of analysis. Section 5.2 will provide a summary of the

sample characteristics. Next, Section 5.3 will present the results of food shopping behaviour.

This is followed by Section 5.4 which deals with attitudes to food in general. Section 5.5 will

present the results on attitudes to organic food. Section 5.6 will touch on regression and

moderated regression analysis. Lastly, Section 5.7 will summarise this chapter.

5.2 Sample Characteristics

Table 7. Sample Characteristics

Sample characteristics Count/Percentage

Valid response 352

Gender

Male 46.9%

Female 53.1%

Stage of degree

1st year 10.7%

2nd year 21.6%

3rd year or higher 67.7%

Place of birth

Asia 56.3%

Europe 41.5%

others 2.2%

Religion

Buddhist 20.0%

Christian 68.5%

others 11.5%

Annual household income

Less than £10000 25.9%

£10000 - £15000 13.1%

£15000 - £20000 27.8%

more than £20000 33.2%

There were a total of 352 valid responses (Table 7), the majority of student organic shoppers

are females (53.1%) born in Asia (56.3%) or Europe (41.5%) studying in third year or higher

32

(67.7%). Most of them are Christians (68.5%) or Buddhist (20.0%) with annual household

income more than £15000 (27.8% + 33.2% = 61%).

5.3 Food Shopping Behaviour

The questionnaire generates a total of 352 valid responses however there were 79 participants

who were not responsible for providing their own meal. Therefore, only 273 responses were

used to analyse food shopping behaviour. The analytical techniques used were multiple

response and frequency analysis.

5.3.1 Multiple Response Analysis

Multiple response analysis was used to analyse place and ways of food shopping.

5.3.1.1 Place of food shopping

Table 8. Places of Food Shopping

Places of food shopping Cases (student) percentagea Response percentage

b

Multiple retailer

(Hypermarket/supermarket) 96.7% 30.7%

From a market 67.0% 21.3%

Butcher 50.5% 16.0%

Delicatessen 42.5% 13.5%

Independent grocery store 33.0% 10.5%

Greengrocer 15.8% 5.0%

From a farm shop 4.8% 1.5%

Home produced 4.4% 1.4%

Other 0.4% 0.1% a. Percentage calculated based on 273 students

b. Percentage calculated based on 860 responses

Of the 273 respondents (Table 8), 96.7% (30.7% of the responses) shopped for food at

multiple retailers (hypermarket/supermarket), 67.0% (21.3% of the responses) shopped at a

markets, 50.5% (16.0% of the responses) shopped at butchers, 42.5% (13.5% of the responses)

shopped at delicatessens, 33.0% (10.5% of the responses) shopped at independent grocery

stores, 15.8% (5.0% of the responses) shopped at greengrocers, 4.8% (1.5% of the responses)

shopped at farm shops, 4.4% (1.4% of the responses) from home produced and 0.4% (0.1%

of the responses) shopped at other sources.

33

5.3.1.2 Ways of food shopping

Table 9. Ways of Food Shopping

Ways of food

shopping Cases (student) percentagea Response percentage

b

Visit a store 94.1% 38.4%

Shop with friends 72.2% 29.4%

Shop online 46.5% 19.0%

Shop with parents 15.8% 6.4%

Parents shop you 8.8% 3.6%

Friends shop for you 8.1% 3.3% a. Percentage calculated based on 273 students

b. Percentage calculated based on 670 responses

Of the 273 respondents (Table 9), 94.1% (38.4% of the responses) shop for food by visiting a

store, 72.2% (29.4% of the responses) shop with friends, 46.5% (19.0% of the responses)

shop online, 15.8% (6.4% of the responses) shop with parents, 8.8% (3.6% of the responses)

parents shop for them and 8.1% (3.3% of the responses) friends shop for them.

34

5.3.2 Frequency Analysis

Table 10. Frequency Analysis Food Shopping Behaviour

Frequency of food shopping

Once per month or less often 4.0%

Two to three times per month 12.8%

Once per week 64.8%

More often than once per week 18.3%

Loyalty card ownership

Yes 69.6%

No 30.4%

Budget

Yes 69.6%

No 30.4%

Weekly food expenditure

Up to £20 per week 19.0%

£21-30 per week 19.0%

£31-40 per week 17.6%

More than £40 44.3%

Cultural or religious influences on food purchase

Never 62.6%

Rarely 18.3%

Occasionally 12.1%

Often 2.9%

Always 4.0%

Of the 273 respondent (Table 10), most student shoppers have a loyalty card (69.6%) and

have a fixed budget in mind (69.6%) while shopping. Majority shop for food once per week

(64.8%), spending more than £40 (44.3%) and purchases were not influenced by cultural or

religious beliefs (62.6%).

35

5.4 Attitudes to Food

Attitudes to food were analysed using descriptive and factor analysis.

5.4.1 Descriptive Analysis

Descriptive analysis was used to measure the importance of food attributes and perceived risk.

5.4.1.1 Importance of food attributes

The mean importance score for all food attributes range from 3 (moderately important) to 5

(very important).

The top 5 attributes that respondents find it most important were freshness (4.58),

hygienically produced (4.57), taste (4.52), quality assured (4.50) and nutrition (4.45).

The bottom 5 attributes that respondents rated least important were support local producers

(3.01), production process that were animal welfare friendly (3.00), support small producers

(2.93), production process that have little or no impact on the environment (2.80) and not

transported a great distance (2.59).

The distinguishing characteristics between the top 5 and bottom 5 food attributes were that

the respondents rated the quality and nutrition aspect of food as more important but rated

environment and animal welfare as least important.

Judging from the low standard deviation (0.739-0.836), there is a convergence of opinion of

those food attributes that respondents rated as most important. However, the bottom 5

attributes have a slightly higher standard deviation (0.897-1.193). Therefore, there is a

divergence of opinions (See Appendix 3).

36

5.4.1.2 Perceived risk on food production process

The mean score for perceived risk on food production process range from 3 (moderately

concerned) to 5 (very concerned).

The top 3 attributes that respondents were most concerned with were hygiene standards in

food production (4.44), use of pesticides (4.18) and use of permitted drugs in meat production

(4.16).

The bottom 3 attributes that respondents least concerned with were animal welfare standards

(3.78), use of genetically modified ingredients (3.55) and intensive farming methods (3.48).

The distinguishing characteristics between the top 3 and bottom 3 attributes were that the

respondents were more concerned with factors that would have an implication on their

physical health but less concerned about animal welfare.

Judging from the low standard deviation across all categories, there is a convergence of

opinion concerning perceived risk on food production process (See Appendix 4).

37

5.4.2 Factor Analysis

Factor analysis was applied to 2 scales, measuring importance of food attributes and

perceived risk on food production method respectively.

5.4.2.1 Importance of food attributes

Factor analysis was applied to a 21-item scale designed to measure the importance of food

attributes that are related to the wider implications of food choice (1= Not at all important, 5=

Very important). However, one measure (sold by reputable seller) did not load significantly

on any factor. Subsequently, analysis was conducted on 20 measures.

In order to confirm that the data are correlated, Bartlett’s Test for Sphericity is conducted

based on the following hypotheses:

H0: None of the variables are correlated

H1: The Variables are correlated

Confirmation that the test variable are inter-correlated is indicated by a KMO index of .928,

categorised by Kaiser (1974) as ‘Marvellous’ , while Bartlett’s Test of Sphericity results in

the rejection of the null hypothesis at the five percent significance level (χ2(190) = 6022.149,

Sig = .000).

The analysis using SPSS 21.0 (2012) employed principal components analysis with Varimax

rotation and the extraction criterion was to derive factors with eigenvalues greater than unity.

Goodness of fit was evaluated using total variance explained and communalities. The

minimum acceptable value for communalities was set at 0.5 (Hair et al., 2006: p 149).

Following Hair et al. (2006: p128) the cut-off point for the inclusion of factor loadings

consistent with a sample size of 352 was set as .300. The analysis resulted in a solution of 3

factors. Factor scores were saved for subsequent analysis (See Appendix 5).

38

Table 11. Rotated Factor Matrix for Importance of Food Features

Food Features Factor Number

1 2 3 h2

Are produced by processes that have

little or no impact on the environment

.074 .337 .830 .807

Are produced by processes that are

animal welfare friendly

.092 .175 .854 .769

Are not transported a great distance .087 .591 .500 .607

Support local producers .217 .831 .328 .846

Support producers in your country .225 .793 .331 .789

Support small producers .208 .852 .310 .865

Are available from producers who

receive a fair price

.146 .647 .484 .675

Are subject to strict government food

standards regulations

.619 .268 .346 .574

Have been produced and supplied in

an energy efficient way

.391 .667 .414 .770

Can be traced back to the original

supplier

.489 .491 .374 .619

Are available to consumers at a fair

price

.739 .158 .081 .578

Are good for consumers Health .730 .206 .298 .665

Taste .752 .276 -.176 .672

Nutrition .784 .242 .141 .693

Are quality assured .870 .145 .111 .791

Are fresh .852 .157 .042 .752

Are naturally produced .568 .536 .139 .629

Have good appearance .595 .563 -.025 .672

Have long shelf life .375 .708 -.205 .683

Are hygienically produced .806 .135 .077 .674

Eigenvalue 6.167 5.086 2.875

Variance % 30.836 25.432 14.376

Cumulative variance % 30.836 56.269 70.644

Goodness of fit is evaluated from total variance explained and communalities (Table 11).

Total variance explained is combined contribution to total variance of the set of all 3 derived

factors. Total variance explained is 71%. This is regarded as acceptable for social science

data. Communality is the proportion of the variance of a specific variable explained by all the

derived factors. The communalities are generally respectable apart from ‘Are subject to strict

government food standards regulations’ and ‘Are available to consumers at a fair price’. In

summary 8 communalities were strong, 10 were respectable and 2 were acceptable.

Therefore, goodness of fit was regarded as respectable.

39

The interpretation of factors (Table 11) is established through the strength of correlations

between each factor and the original scale items. Factor 1 is most strongly associated, in

descending order of importance, with ‘Quality assured’ (.870), ‘Fresh’ (.852) and

‘Hygienically produced’ (.806). It is therefore interpreted as Quality.

Factor 2 is most strongly associated, in descending order of importance, with ‘Support small

producers’ (.852) and ‘Support local producers (.831). It is therefore interpreted as Support

small and local producers.

Factor 3 is most strongly associated, in descending order of importance, with ‘Are produced

by processes that are animal welfare friendly’ (.854) and ‘Are produced by processes that

have little or no impact on the environment’ (.830). It is therefore interpreted as Animal

welfare and environment.

Next, factor analysis was applied to the scale of perceived risk on food production method.

5.4.2.2 Perceived risk on food production method

Factor analysis was applied to an 8-item scale designed to measure perceived risk concerning

food production methods (1= Not at all concerned, 5= Very concerned).





Confirmation that the test variables are inter-correlated is indicated by a KMO index of .906,



Sig = .000).






40


factor. Factor scores were saved for subsequent analysis (See Appendix 6).

Table 12. Factor Matrix for Perceived Risk to Food Production Method

Food Features Factor

Number

1 h2

Animal welfare standards .824 .679

Use of pesticides in food production .905 .819

Use of fertilisers in food production .906 .820

Intensive farming methods .833 .695

Use of genetically modified

ingredients

.789 .623

Use of permitted drugs in meat

production

.915 .837

Hygiene standards in food production .762 .580

Use of artificial ingredients in food

production

.857 .734

Eigenvalue 5.788

Variance % 72.344

Cumulative variance % 72.344


Total variance explained is combined contribution to total variance of the single derived

factor. Total variance explained is 72%. This is regarded as acceptable for social science data.

Communality is the proportion of the variance of a specific variable explained by all the

derived factors. The communalities are generally respectable apart from ‘Hygiene standards

in food production’. In summary 4 communalities were strong, 3 were respectable and 1 was

acceptable. In summary, goodness of fit was regarded as respectable.



descending order of importance, with ‘Use of permitted drugs in meat production’ (.915),

‘Use of fertilisers in food production’ (.906) and ‘Use of pesticides in food production’

(.905). It is therefore interpreted as Usage of drugs, fertilisers and pesticides.

41

5.5 Attitudes to Organic Food

Attitudes to organic food were analysed using frequency, descriptive and factor analysis.

5.5.1 Frequency Analysis

Frequency analysis was used to measure purchased organic categories and future purchase

likelihood of the same categories.

5.5.1.1 Purchased organic categories

Product categories that majority of respondents answered ‘Nearly always’ are Dairy products

(40.3%) and Organic vegetables (43.5%). Majority of respondents answered ‘Often’ for

Bakery products (46.6%), Organic fruits (50.9%) and Organic fresh meat and poultry (46.6%).

Majority of respondents answered ‘Occasionally’ for Organic beverages (42.6%) and Other

categories (52.6%). Lastly, majority answered ‘Rarely’ for Organic alcoholic drink (50.3%)

(See Appendix 7).

5.5.1.2 Future purchase likelihood of organic categories

Product categories that majority of respondents answered ‘Very likely’ are Dairy products

(42.9%), Organic fruits (46.3%) and Organic vegetables (45.7%). Majority of respondents

answered ‘Likely’ for Organic fresh meat and poultry (60.5%). Majority of respondents

answered ‘Not sure’ for Organic bakery products (51.4%), Organic beverages (52.6%) and

Other categories (62.8%). Lastly, majority answered ‘Unlikely’ for Organic alcoholic drink

(46.3%) (See Appendix 8).

42

5.5.2 Descriptive Analysis

Descriptive analysis was implemented to measure satisfaction level obtained from various

organic attributes and influences of benefits on purchase decision.

5.5.2.1 Satisfaction level obtained from various organic attributes

The mean importance score for satisfaction level obtained from various organic attributes

range from 3 (moderate) to 5 (very high).

The top 5 attributes that respondents obtained the highest satisfaction level were freshness

(4.49), good for consumers’ health (4.47), quality assured (4.46), hygienically produced (4.45)

and nutrition content (4.43).

The bottom 5 attributes that respondents obtained the lowest satisfaction level were

production processes that have little or no impact on the environment (3.64), support

producers in your country (3.40), support local producers (3.39), support small producers

(3.35) and not transported a great distance (3.10).

The distinguishing characteristics between the top 5 and bottom 5 food attributes were that

the respondents rated the quality and nutrition aspects of organic foods as more satisfying but

rated environment and support of producers not as satisfying.

Judging from the low standard deviation (0.792-0.848), there is a convergence of opinions of

those organic food attributes that respondents rated as most satisfying. Similarly, the bottom

5 attributes also have a low standard deviation (0.873-0.994). Therefore, there is a

convergence of opinions (See Appendix 9).

43

5.5.2.2 Influences of benefits on decision to purchase

The mean importance score for measuring influences of benefits on decision to purchase

organic food range from 3 (moderate) to 5 (very high).

The top 5 benefits that respondents rated as most influential were quality assured (4.47),

freshness (4.47), nutrition (4.45), hygienically produced (4.44) and good for consumers’

health (4.41).

The bottom 5 benefits that respondents rated as least influential were production processes

that have little or no impact on the environment (3.50), support local producers (3.36),

support producers in your country (3.33), support small producers (3.32) and not transported

a great distance (3.04).

The distinguishing characteristics between the top 5 and bottom 5 benefits were that the

respondents rated the quality and nutritional benefits as more influential but rated

environment and support of producers not as influential.

Judging from the low standard deviation (0.791-0.870), there is a convergence of opinions of

those benefits that respondents rated as most influential. However, the bottom 5 benefits have

slightly higher standard deviation (0.865-1.029). Therefore, there is a divergence of opinions

(See Appendix 10).

44

5.5.3 Factor Analysis

Factor analysis was applied to 2 scales, measuring satisfaction level obtained from different

organic features and effect of benefits on purchase decision.

5.5.3.1 Satisfaction level obtained from different organic features

Factor analysis was applied to a 21-item scale used to measure expected satisfaction level

obtained from various organic features (1= Very low, 5= Very high).








Sig = .000).








45

Table 13. Rotated Factor Matrix for Satisfaction Level Obtained


1 2 3 h2

Are produced by processes that have little

or no impact on the environment

.304 .808 .174 .776



.313 .809 .112 .764

Are not transported a great distance .032 .727 .153 .552






.297 .650 .407 .677



.683 .345 .301 .676

Have been produced and supplied in an

energy efficient way

.421 .497 .524 .699


supplier

.539 .412 .406 .625

Are available to consumers at a fair price .656 .210 -.016 .475

Are good for consumers’ Health .871 .183 .181 .826

Taste .803 .083 .319 .754

Nutritional content .837 .143 .283 .801


Are fresh .869 .154 .169 .808


Have good appearance .637 .042 .551 .712

Are sold by reputable seller .638 .349 .036 .530

Have long shelf life .399 .025 .721 .680


Eigenvalue 7.579 4.095 3.542

Variance % 36.089 19.498 16.868






derived factors. The communalities are generally respectable apart from ‘Are not transported

a great distance’, ‘Are available to consumers at a fair price’ and ‘Are sold by reputable

seller’. In summary 12 communalities were strong, 6 were respectable, 2 were acceptable and

1 were weak. In conclusion, goodness of fit was regarded as strong.



46

descending order of importance, with ‘Quality assured’ (.896), ‘Good for consumers’ health’

(.871), ‘Are fresh’ (.869) and ‘Hygienically produced’ (.849). It is therefore interpreted as

Quality.

Factor 2 is most strongly associated, in descending order of importance, with ‘Animal

welfare friendly’ (.809) and ‘Little or no impact on the environment’ (.808). It is therefore

interpreted as Environment and animal welfare.

Factor 3 is most strongly associated, in descending order of importance, with ‘Support small

producers’ (.770), ‘Have long shelf life’ (.721) and ‘Support local producers’ (.704). It is

therefore interpreted as Support of small and local producers.

Next, factor analysis was applied to the scale measuring effect of benefits on decision to

purchase.

5.5.3.2 Effect of benefits on decision to purchase

Factor analysis was applied to a 23-item scale used to measure effect of benefits on decision

to purchase (1= Very low, 5= Very high).








Sig = .000).








47

Table 14. Rotated Factor Matrix for Effect of Benefits on Decision to Purchase


1 2 3 h2

Little or no impact on the environment .289 .827 .021 .767

Are animal welfare friendly .330 .806 -.007 .759

Are not transported a great distance .073 .775 -.083 .612






.321 .720 .088 .629



.680 .484 .068 .701



.402 .731 .263 .765


supplier

.512 .599 .239 .679

Are available to consumers at a fair price .732 .178 -.289 .650

Are good for consumers’ Health .846 .249 .190 .815

Taste .735 .079 .412 .716

Nutrition .841 .236 .238 .820


Are fresh .860 .166 .240 .825


Have good appearance .684 .163 .468 .713

Are sold by reputable seller .670 .200 .131 .506

Have long shelf life .405 .200 .731 .739


Recommendation from people who are

important to you

.650 .276 .437 .690

To give yourself a special treat .435 .316 .665 .731

Eigenvalue 8.242 6.156 2.680

Variance % 35.833 26.765 11.654






derived factors. The communalities are generally respectable apart from Are sold by

reputable seller. In summary 17 communalities were strong, 5 were respectable, 1 was

acceptable. In conclusion, goodness of fit was regarded as strong.



48

descending order of importance, with ‘Quality assured’ (.903), ‘Are fresh’ (.860), ‘Good for

consumers’ health’ (.846), ‘Nutrition’ (.841) and ‘Hygienically produced’ (.838). It is

therefore interpreted as Quality and health.

Factor 2 is most strongly associated, in descending order of importance, with ‘Little or no

impact on the environment’ (.877), ‘Support small producers’ (.818), ‘Support local

producers’ (.815) and ‘Animal welfare friendly’ (.806) and. It is therefore interpreted as

Environment and support of small and local producers.

Factor 3 is most strongly associated with ‘Have long shelf life’ (.731). It is therefore

interpreted as Perishability.

5.6 Regression and Moderated Regression Analysis

Regression analysis was conducted to evaluate determinants of purchase likelihood;

satisfaction and both purchase likelihood and satisfaction.

Moderated regression was conducted to evaluate moderating effect of gender on purchase

likelihood and income on purchase likelihood.

5.6.1 Determinants of Purchase Likelihood

Results of regression analysis show that the stronger the influence of benefits and food

features is, the higher the likelihood of purchase (See Appendix 13 for full analysis).

5.6.2 Determinants of Satisfaction

Results of regression analysis indicate that, the stronger the influence of benefits and food

features the higher the satisfaction (See Appendix 14 for full analysis).

5.6.3 Purchase Likelihood and Satisfaction

Results of regression analysis indicate that higher satisfaction level leads to increase purchase

likelihood (See Appendix 15 for full analysis).

5.6.4 Moderating effect of Gender on Purchase Likelihood

Since the gender majority is female, results of moderated regression indicate that the increase

in number of females leads to an increase in purchase likelihood (see Appendix 16 for full

analysis).

49

5.7 Summary

This chapter has presented the results on sample characteristics, food shopping behaviour,

attitudes to food in general, attitudes to organic food and regression and moderated regression

analysis. In the following chapter, the results will be discussed.

50

Chapter 6. Discussion

6.1 Introduction

Chapter 6 will provide a discussion on the results. Firstly, Section 6.2 will discuss on

demographics. Secondly, Section 6.3 will discuss on food shopping behaviour. Next, Section

6.4 will discuss on attitudes to food. This followed by Section 6.5 which will discuss on

attitudes to organic food. Lastly, Section 6.6 will summarise the chapter.

6.2 Demographics

Findings from quantitative data analysis revealed that females tend to be more interested in

organic food. This mirrors the findings of Sriram and Forman (1993) who discovered that the

percentage of female organic consumers were higher than male. This also means that the

quantitative analysis contradicts the findings of Paul and Rana (2012) who found no

significant differences in gender composition of organic consumers.

Furthermore, according to quantitative data analysis, 61% of organic consumers have an

annual household income of more than £15000. This suggest that, majority of organic

consumers come from socio-demographic class of ABs and C1. The result confirms the

findings of Davies et al. (1995) who argue that higher income households purchase organic

produce more frequently. The result also therefore rejects the findings of Fotopoulos and

Krystallis (2002) who argue that higher household incomes do not necessarily indicate

frequent organic purchase.

6.3 Food Shopping Behaviour

Findings from Soil Association (2013) indicated that majority of organic consumers shop at

multiple retailers. This finding is confirmed by quantitative analysis which concluded that

96.7% of undergraduate organic consumers shopped for food at multiple retailers. Besides

that, Soil Association (2013) also indicated that there is an increase of online organic

shopping. This is also bolstered by quantitative analysis which discovered that 46.5% of

organic consumers shop online.

According to quantitative analysis, a significant proportion of undergraduates (44.3%) spent

more than £40 per week on food shopping. This mirrors the findings of Student Income and

51

Expenditure Survey (2013) which estimated that, on average, students spent about £1884 per

academic year (£47.1 per week for 40 weeks).

6.4 Attitudes to Food

Findings from Mitchell and Greatorex (1992) mentioned that physical loss was of greater

importance compared to other losses. This is confirmed by the quantitative analysis which

found that undergraduate organic consumers were more concerned with factors that affect

their physical health. The top 3 attributes that consumers were most concerned with were

hygiene standards, pesticides and use of drugs. Besides that, Factor analysis was applied to an

8-item scale designed to measure perceived risk concerning food production and it resulted in

a single factor solution. The factor is most strongly associated to usage of drugs, fertilisers

and pesticides. The factor analysis therefore also supports the findings of Mitchell and

Greatorex (1992).

6.5 Attitudes to Organic Food

This section will discuss on purchased organic categories, motivations and satisfaction.

6.5.1 Purchased Organic Categories

Findings from Soil Association (2013) indicated that dairy products and fruits were the two

most popular organic categories. This indication is supported by quantitative analysis which

found that majority of undergraduate organic consumers either often or nearly always

purchase products from these two categories. However, there were some contradictions

between the findings of Soil Association (2013) and quantitative analysis on the product

category fresh meat and poultry. Soil Association (2013) claims that few organic consumers

purchase fresh meat and poultry. On the other hand, quantitative analysis indicated that a

high percentage (46.6%) of organic consumers often purchase fresh meat and poultry.

6.5.2 Motivations to Purchase

According to Tregear et al. (1994), consumers purchase organic food mainly for health

reasons. This statement is upheld to a large extent by quantitative research. Factor analysis

was applied to a 23-item scale used to measure effect of benefits on decision to purchase (1=

Very low, 5= Very high). The analysis produced a solution of three factors and they are

namely Quality and health (factor 1), Environment and support of small and local producers

52

(factor 2), and Perishability (factor 3). Factor 1 was most strongly associated to ‘Good for

consumers’ health’ and ‘Nutrition’. Therefore, the quantitative analysis supports the findings

of Tregear et al. (1994). However, to a small extent, the quantitative analysis also contradicts

the findings of Tregear et al. (1994). Factor 1 was also strongly associated to ‘Quality assured’

and ‘Hygienically produced’ which jointly interpreted as quality. Tregear et al. (1994) did not

mention quality as a factor for organic purchase. Hence, there were some contradictions.

Factor 2 was strongly associated with ‘Little impact on the environment’ and ‘Animal

welfare friendly’. This result is consistent with the findings of Onozaka et al. (2001) who

emphasised that pollution and high levels of carbon footprint were negatively valued by most

organic shoppers. This result also supports the work of Wandel and Bugge (1997), which

discovered that age group (15 to 24 years old) consider environment and animal welfare as

the key reason for organic purchase.

Factor 3 (perishability) does not support any of the literature reviewed in this study. None of

the authors identified perishability as a factor for organic purchase.

6.5.3 Satisfaction

Factor analysis was applied to a 21-item scale used to measure expected satisfaction level

obtained from various organic features (1= Very low, 5= Very high). The analysis produced a

solution of three factors and they are namely Quality (factor 1), Environment and animal

welfare (factor 2) and Support of small and local producers (factor 3). The result supports the

argument of Boorn and Prescott (2002) that highlighted unique attributes of organic products

as points of comparison between organic and conventional food. The result also therefore

rejects the argument of Jolly and Norris (1991) who argue that some consumers did not

encounter any differences between organic and inorganic foods.

6.6 Summary

This chapter has discussed and triangulated the results with secondary research. The areas

discussed were demographics, food shopping behaviour, attitudes to food and attitudes to

organic food. Next chapter will conclude this study.

53

Chapter 7. Conclusion

7.1 Introduction

Chapter 7 will conclude the study. Firstly, Section 7.2 will summarise the key findings.

Secondly, Section 7.3 will provide the marketing implications of the study. Next, Section 7.4

will address the limitations of the study. This is followed by Section 7.5, where areas of

future research are proposed. Lastly, Section 7.6 will conclude chapter 7.

7.1.1 Re-statement of Aims and Objectives

The aim of the research is to explore undergraduate students' purchasing behaviour and

satisfaction towards quality low-input and organic foods. The aim has been explored using a

quantitative approach and the objectives (Table 15) have been addressed (See Table 16).

Table 15. Re-statement of Objectives

Objective

Label

Objective Defined

Objective 1 To provide an overview of the quality low-input foods and organic foods

market

Objective 2 To provide an overview of the UK student population

Objective 3 To investigate the demography of student consumers of quality low-input

and organic foods

Objective 4 To investigate the food shopping behaviours of undergraduates

Objective 5 To measure the importance of food features that undergraduates attach

Objective 6 To identify underlying dimensions of students’ attitude to food features in

general

Objective 7 To measure undergraduates’ perceived risk concerning food production

methods

Objective 8 To identify underlying dimensions of undergraduates’ perceived risk to

food production methods

Objective 9 To identify the driving features of customer satisfaction towards quality

low-input and organic foods

Objective 10 To identify underlying dimensions of student satisfaction level obtained

from various organic features

Objective 11 To investigate the future purchase likelihood of organic categories

Objective 12 To measure the effect of benefits of different organic features on decision

to purchase

Objective 13 To identify the underlying dimensions of effect of benefits on decision to

purchase

54

7.2 Summary of Key Findings

Table 16. Summary of Key Findings

Objective Label Key Findings

Objective 1 The organic market has grown from £140 million in 1995 to £1200 million in

2013. Online sales are on the raise, representing 10.1% of major retailers’ sales.

Students are becoming an important customer base for retailers. Most popular

organic purchases are dairy and chilled convenience products. Majority of organic

consumers come from the socio-demographic class of ABs and C1.

Objective 2 There were 2 million undergraduates in 2012 and the number is still increasing.

Females tend to be the majority in universities. Besides that, there were also more

females compared to males who prefer to cook.

Objective 3 Majority of student organic shoppers are females born in Asia or Europe studying

in third year or higher. Most of them are Christians or Buddhist with annual

household income more than £15000.

Objective 4 Majority of students shop for food at multiple retailers and there is also a

significant proportion that shop online. Most student shoppers have a loyalty card

and have a fixed budget in mind while shopping. Majority shop for food once per

week, spending more than £40 and purchases were not influenced by cultural or

religious beliefs.

Objective 5 The top 5 food attributes that student consumers find it most important were

freshness, hygienically produced, taste, quality assured and nutrition.

Objective 6 Three dimensions were identified from factor analysis and they were interpreted

as Quality (factor 1), Support small and local producers (factor 2) and Animal

welfare and environment (factor 3).

Objective 7 The top 3 food production process that student consumers most concerned with

were hygiene standards, use of pesticides and use of drugs in meat production.

Objective 8 A single dimension was identified from factor analysis and it was interpreted as

usage of drugs, fertilisers and pesticides.

Objective 9 The top 5 organic attributes that student consumers obtained the highest

satisfaction level were freshness, good for consumers’ health, quality assured,

hygienically produced and nutrition content. Stronger influences of benefits and

food features increase satisfaction.


as Quality (factor 1), Environment and animal welfare (factor 2) and Support of

small and local producers (factor 3).

Objective 11 Majority of student organic shoppers indicated the likelihood of purchasing dairy

products, organic fruits, organic vegetables and organic meat and poultry in the

future. Stronger influence of benefits, food features and higher satisfaction leads

to increase purchase likelihood.

Objective 12 The top 5 organic benefits that consumers rated as most influential were quality

assured, freshness, nutrition, hygienically produced and good for consumers’

health.


as Quality and health (factor1), Environment and support of small and local

producers (factor 2) and Perishability (factor 3).

Table 16 has provided a summary of key findings, answering the objectives of the research.

55

7.3 Marketing Implications

Table 17. Implications

Marketing mix Implications

Product Organic retailers could focus on ensuring the quality of its products as

quality is the most important dimension identified. Retailers could also

engage more in purchasing well-known brands from suppliers which have

good reputation in product quality. Besides that, retailers could

communicate clearly with its suppliers regarding quality standards. Special

attention could be given to quality aspects such as freshness, hygienic

production, taste and nutrition. These features were most important to

consumers. Furthermore, customer feedback on quality could be conducted

by supermarkets as a way to monitor quality and satisfaction. In addition,

internal (employee) feedback on quality could also be encouraged.

Organic retailers could give more attention on product categories of dairy

products, fruits, vegetables, meat and poultry as consumers indicated a

likelihood of future purchase in these categories.

Price Since majority of student shoppers have a fixed budget while shopping,

organic retailers could find out the budget range and set reasonable prices

within the range. Package deals could be introduced as students shop in

bulks weekly.

Place Organic products could be sold at multiple retailer stores as most students

purchase food at supermarkets. Organic products could also be sold online

as there are a significant proportion of students who shop for food online.

Promotion Promotion efforts could focus on 3 aspects and they are quality,

environment and animal welfare and support of small and local producers.

Organic retailers could also promote on the good qualities of organic

products such as no usage of drugs, chemical fertilisers and pesticides.

Rewards for frequent usage of loyalty cards could also be adopted.

Promotional efforts could be more female orientated as female tend to be

more interested in organic products. Retailers could use both above and

below the line promotion methods. For example advertise through internet,

social media, radio and magazines.

Physical

evidence

The layout and design of the store could be aesthetically appealing to

indicate quality and class. Besides that, posters showing commitment

towards quality assurance, environmental friendly and animal welfare and

support of small and local producers could be displayed. This information

could also be displayed on the packaging of the products.

Table 17 has explained the marketing implications using marketing mix 7ps framework.

However, process and people were not included as they were not relevant.

56

7.4 Limitations

More samples could be gathered for this study. There were only 352 valid samples, which

may not provide adequate representation for UK undergraduates. Besides that, the use of

convenience sampling technique may not provide an unbiased representation of population.

As a result, objective statistical inferences are difficult to make when non-probability

sampling technique is used.

7.5 Further Research

In future research, the study could be conducted using mixed method approaches. For

example, focus group could be conducted before statistical analysis. Such a way, the data

gathered is triangulated and therefore would improve the credibility and validity of result. In

addition, more information could be gathered using mixed method approaches. Participants

might be willing to provide more information in a focus group compared to online

questionnaire as they feel more comfortable answering questions in a group. Therefore enable

the researcher to gather more information.

More samples could be gathered for future research to provide better representation to UK

undergraduates. Probability sampling technique could also be applied in future research to

provide an unbiased representation of the population.

7.6 Summary

This chapter has concluded the study. The research aim and objectives have been achieved

and key findings have been outlined. Marketing implications based on quantitative analysis

have been reported. Limitations of study have been identified and further research has been

suggested.

57

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63

Appendix 1. Questionnaire

Survey of Student Food Shopping Behaviour

Hello. I am a third-year student in Newcastle University studying Marketing and Management.

I am conducting a questionnaire regarding UK university students' attitude towards quality low-input

and organic foods for my final-year dissertation.

Please kindly spend a maximum 10 minutes to complete the questionnaire about quality low-input and

organic foods.

Your involvement is completely voluntary. The questionnaire should require no offensive or sensitive

information. You are free to withdraw at any stage. All answers remain anonymous and confidential

in accordance with the Data protection Act 1998 for academic use only.

Thank you very much for your time and your great help for my dissertation.

Should you have any enquiries about the study, please do not hesitate to contact me:

[email protected]

Best wishes,

Tiezheng Yuan

Screening Question

S1. Are you an undergraduate studying in a UK university?

Tick one box

(1) Go to Question S2

(2) Go to Question 8

S2.Are you responsible for providing your own meals while you are at university?

Tick one box

Yes (1) Go to Question 1

No (2) Go to Question 8

Yes

No

64

Food Shopping Behaviour

In this section I would like you to answer some questions about your food shopping behaviour

Q1. Where do you usually shop for your food? (Multiple responses permitted)

Multiple retailer (Hypermarket/supermarket) (1=yes,blank=no)

Independent grocery store

Butcher

Greengrocer

Delicatessen

From a market

From a farm shop

Home produced

Other

Q2. How often do you usually shop for food? Tick one box

Once per month or less often (1)

Two to three times per month (2)

Once per week (3)

More often than once per week (4)

Q3. Do you have a store loyalty card? (e.g. ASDA Club, Tesco Club)

Tick one box

Yes (1)

No (2)

Q4. When you usually shop for food, do you have in mind a fixed sum of money (i.e. a budget) that you

plan to spend? Tick one box

Yes (1)

No (2)

Q5. On average, how much do you spend on food shopping per week? Tick one box

Up to £20 per week (1)

£21-30 per week (2)

£31-40 per week (3)

More than £40 (4)

65

Q6. How do you shop for food? (Tick as appropriate, multiple responses)

Visit a store (1) (1=yes,blank=no)

Shop online (2)

Shop with friends (3)

Shop with parents (4)

Friends shop for you (5)

Parents shop for you (6)

Q7. Are decisions about the food you buy influenced by your cultural or religious beliefs?

Tick one box

Never

(1)

Rarely

(2)

Occasionally

(3)

Often

(4)

Always

(5)

66

Your Attitudes to Food that you Buy

Q8. How important is it that the foods you buy have the following features: (Tick for each feature)

Features Not at all

important

(1)

Somewhat

important

(2)

Moderately

important

(3)

Important

(4)

Very

important

(5)

Are produced by

processes that have little

or no impact on the

environment

Are produced by

processes that are animal

welfare friendly

Are not transported a

great distance

Support local producers

Support producers in

your country

Support small producers

Are available from

producers who receive a

fair price

Are subject to strict

government food


Have been produced and

supplied in an energy

efficient way

Can be traced back to

the original supplier

Are available to

consumers at a fair price

Are good for consumers

Health

Taste

Nutrition

Are quality assured

Are fresh

Are naturally produced

Have good appearance

Are sold by reputable

seller

Have long shelf life

Are hygienically

produced

67

Q9. To what extent are you concerned that the following aspects which might be associated with food

production could be a risk to your health? (Tick for each feature)

Features Not at all

concerned

(1)

Somewhat

concerned

(2)

Moderately

concerned

(3)

Fairly

Concerned

(4)

Very

Concerned

(5)

Animal welfare standards

Use of pesticides in food

production

Use of fertilizers in food

production

Intensive farming methods

Use of genetically modified

ingredients

Use of permitted drugs in

meat production

Hygiene standards in food

production

Use of artificial ingredients

in food production

68

Organic Food

In this section I would like you to answer some questions about organic food

Q10. How often have you purchased organic versions of the following foods if at all?

(Tick for each category)

Product category Never

(1)

Rarely

(2)

Occasionally

(3)

Often

(4)

Nearly

always

(5)

Bakery products

Dairy products (cheese,

milk, yoghurt)

Fruits

Vegetables

Fresh meat and poultry

Alcoholic drink (beer,

wine)

Beverages

Others

69

Q11. If you bought organic food on a regular basis what level of satisfaction would you expect to

obtain from the following features? (Tick for each feature)

Feature Very

low

Low Moderate

High

Very

high

Are produced by processes that have

little or no impact on the environment



Are not transported a great distance


Support producers in your country









supplier


price

Are good for consumers Health

Taste

Nutritional content

Are quality assured

Are fresh



Are sold by reputable seller


Are hygienically produced

70

Q12. What is the likelihood that you will buy organic foods in these categories in the future?


Category Not at all

likely

(1)

Unlikely

(2)

Not sure

(3)

Likely

(4)

Very likely

(5)

Bakery products

Dairy products (cheese,

milk, yoghurt)

Fruits

Vegetables


Alcoholic drink (beer,

wine)

Beverages

Others

Q13. What effect would the following benefits or influences have on your decision to buy organic

food?


Features No effect Little

effect

Moderate

Some

effect

Big

effect

Little or no impact on the

environment

Are animal welfare friendly

Are not transported a great distance


Support producers in your country






Have been produced and supplied in

an energy efficient way


supplier


price

Are good for consumers Health

Taste

Nutrition

Are quality assured

Are fresh



Are sold by reputable seller


Are hygienically produced

Recommendation from people who

are important to you

To give yourself a special treat

71

Questions about Yourself

In this section I would like you to answer some questions about yourself

Q14. Your gender (Tick one box)

Female

Male

Q15. What stage of study are you (Tick one box)

1st year

2nd

year

3rd

year or higher +

Q16. In which geographical area were you born (Tick one box)

Africa

Asia

Australia and Oceania

Europe

North America

Central America, Caribbean and South America

Middle East

Q17. What is your religion (Tick one box)

Buddhist

Christian (2)

Hindu

Judaism

Muslim

Sikh

Other religion

None

Q18. Which of the following categories best describes your annual household income before taxes?

(Tick one box)

Less than £10000

£10000-15000

£15000-20000

More than £20000

72

Appendix 2. Reliability Analysis Output

Scale: Attitude to food

Case Processing Summary

N %

Cases

Valid 352 82.4

Excluded 75 17.6

Total 427 100.0

Reliability Statistics

Cronbach's

Alpha

N of

Items

.945 21

73

Item-Total Statistics

Scale Mean if Item

Deleted

Scale Variance if Item

Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if Item

Deleted

Are produced by processes that have little or no impact on

the environment 76.56 207.176 .542 .944

Are produced by processes that are animal welfare friendly 76.36 208.493 .451 .945

Are not transported a great distance 76.77 204.344 .591 .943

Support local producers 76.34 195.496 .778 .940

Support producers in your country 76.33 195.269 .755 .941

Support small producers 76.43 194.724 .776 .940

Are available from producers who receive a fair price 76.07 199.966 .662 .942

Are subject to strict government food standards regulations 75.18 198.835 .677 .942

Have been produced and supplied in an energy efficient way 75.84 188.493 .823 .939

Can be traced back to the original supplier 75.54 192.158 .745 .941

Are available to consumers at a fair price 74.96 206.921 .578 .943

Are good for consumers Health 74.97 203.022 .681 .942

Taste 74.84 209.270 .569 .944

Nutrition 74.91 204.860 .687 .942

Are quality assured 74.86 205.746 .671 .942

Are fresh 74.77 207.931 .634 .943

Are naturally produced 75.27 198.803 .738 .941

Have good appearance 75.24 200.508 .727 .941

Are sold by reputable seller 75.56 210.065 .440 .945

Have long shelf life 75.52 200.233 .595 .943

Are hygienically produced 74.79 207.625 .610 .943

74

ANOVA Sum of

Squares

df Mean Square F Sig

Between People 3710.315 351 10.571

Within People

Between Items 3187.996 20 159.400 273.387 .000

Residual 4093.052 7020 .583

Total 7281.048 7040 1.034

Total 10991.362 7391 1.487

In the case of attitudes to food, the alpha coefficient (0.945) exceeds the minimum threshold

value. Examination of CITC values reveals that all values are greater than the minimum

threshold and range from 0.440-0.823. Examination of the impact of deleting items from the

scale indicates that there is no support for the deletion of items .The ANOVA test for the

equality of scores results in a rejection of the null hypothesis at the 5 percent significance

level (F (351, 20) = 273.387, p < .001). Consequently, the construct is judged to have

acceptable qualities of reliability.

Scale: Perceived risk


N %

Cases

Valid 352 82.4

Excluded 75 17.6

Total 427 100.0


Cronbach's

Alpha

N of

Items

.944 8

75


Scale Mean if Item

Deleted


Deleted


Correlation


Deleted

Animal welfare standards 27.86 42.684 .767 .940

Use of pesticides in food production 27.45 42.807 .869 .932

Use of fertilizers in food production 27.66 41.571 .869 .932

Intensive farming methods 28.16 44.960 .784 .938

Use of genetically modified ingredients 28.09 44.444 .726 .942

Use of permitted drugs in meat production 27.47 42.108 .882 .931

Hygiene standards in food production 27.20 47.178 .696 .944

Use of artificial ingredients in food

production

27.58 43.025 .810 .936

ANOVA

Sum of Squares df Mean Square F Sig

Between People 2478.647 351 7.062

Within People

Between Items 271.474 7 38.782 98.524 .000

Residual 967.151 2457 .394

Total 1238.625 2464 .503

Total 3717.272 2815 1.321

In the case of perceived risk, the alpha coefficient (0.944) exceeds the minimum threshold value. Examination of CITC values reveals that all

values are greater than the minimum threshold and range from 0.696-0.882. Examination of the impact of deleting items from the scale indicates

that there is no support for the deletion of items .The ANOVA test for the equality of scores results in a rejection of the null hypothesis at the 5

percent significance level (F (351, 7) = 98.524, p < .001). Consequently, the construct is judged to have acceptable qualities of reliability.

76

Scale: Satisfaction


N %

Cases

Valid 352 82.4

Excluded 75 17.6

Total 427 100.0


Cronbach's

Alpha

N of

Items

.955 21

77


Scale Mean if Item

Deleted


Deleted


Correlation


Deleted

Are produced by processes that have little or no impact on

the environment

79.91 183.499 .676 .953

Are produced by processes that are animal welfare friendly 79.88 184.167 .648 .954











Taste 79.15 183.082 .739 .953

Nutritional content 79.12 182.271 .779 .952


Are fresh 79.06 184.150 .747 .953






78

ANOVA


Between People 3356.623 351 9.563

Within People

Between Items 1335.384 20 66.769 155.793 .000

Residual 3008.616 7020 .429

Total 4344.000 7040 .617

Total 7700.623 7391 1.042

In the case of satisfaction, the alpha coefficient (0.955) exceeds the minimum threshold value.

Examination of CITC values reveals that all values are greater than the minimum threshold

and range from 0.423-0.782. Examination of the impact of deleting items from the scale

indicates that there is no support for the deletion of items .The ANOVA test for the equality

of scores results in a rejection of the null hypothesis at the 5 percent significance level (F

(351, 20) = 155.793, p < .001). Consequently, the construct is judged to have acceptable

qualities of reliability.

Scale: Benefits


N %

Cases

Valid 352 82.4

Excluded 75 17.6

Total 427 100.0


Cronbach's

Alpha

N of

Items

.961 23

79


Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted

Little or no impact on the environment 87.28 237.799 .686 .959

Are animal welfare friendly 87.24 236.812 .690 .959











Taste 86.43 237.768 .682 .959

Nutrition 86.33 235.938 .799 .958


Are fresh 86.32 238.034 .768 .959






Recommendation from people who are important to you 86.55 234.180 .761 .958

To give yourself a special treat 86.73 231.856 .711 .959

80

ANOVA


Between People 3928.417 351 11.192

Within People

Between Items 1480.891 22 67.313 153.057 .000

Residual 3396.066 7722 .440

Total 4876.957 7744 .630

Total 8805.374 8095 1.088

In the case of benefits, the alpha coefficient (0.961) exceeds the minimum threshold value.

Examination of CITC values reveals that all values are greater than the minimum threshold

and range from 0.458-0.800. Examination of the impact of deleting items from the scale

indicates that there is no support for the deletion of items .The ANOVA test for the equality

of scores results in a rejection of the null hypothesis at the 5 percent significance level (F

(351, 22) = 153.057, p < .001). Consequently, the construct is judged to have acceptable

qualities of reliability.

81

Appendix 3. Importance of Food Attributes

Descriptive Statistics Importance of Food Attributes

N Minimum Maximum Mean Std.

Deviation

Are fresh 352 1 5 4.58 .739

Are hygienically produced 352 1 5 4.57 .782

Taste 352 1 5 4.52 .739

Are quality assured 352 1 5 4.50 .809

Nutrition 352 1 5 4.45 .836

Are available to consumers at a fair price 352 1 5 4.39 .861

Are good for consumers Health 352 1 5 4.38 .932

Are subject to strict government food standards regulations 352 1 5 4.17 1.145

Have good appearance 352 1 5 4.11 .995

Are naturally produced 352 1 5 4.08 1.060

Have long shelf life 352 1 5 3.84 1.205

Can be traced back to the original supplier 352 1 5 3.82 1.356

Are sold by reputable seller 352 1 5 3.80 .875

Have been produced and supplied in an energy efficient way 352 1 5 3.51 1.396

Are available from producers who receive a fair price 352 1 5 3.28 1.111

Support producers in your country 352 1 5 3.03 1.198

Support local producers 352 1 5 3.01 1.156

Are produced by processes that are animal welfare friendly 352 1 5 3.00 .965

Support small producers 352 1 5 2.93 1.193

Are produced by processes that have little or no impact on the

environment

352 1 5 2.80 .897

Are not transported a great distance 352 1 5 2.59 .986

Valid N (listwise) 352

82

Appendix 4. Perceived Risk on Food Production Process

Descriptive Statistics Perceived Risk on Food Production Process

N Minimum Maximum Mean Std.

Deviation

Hygiene standards in food production 352 1 5 4.44 .891

Use of pesticides in food production 352 1 5 4.18 1.098

Use of permitted drugs in meat production 352 1 5 4.16 1.143

Use of artificial ingredients in food production 352 1 5 4.06 1.144

Use of fertilizers in food production 352 1 5 3.98 1.203

To what extent are you concerned that the following

aspects Animal welfare standards

352 1 5 3.78 1.227

Use of genetically modified ingredients 352 1 5 3.55 1.116

Intensive farming methods 352 1 5 3.48 1.001


Appendix 5. Importance of Food Attributes

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy.

.928

Bartlett's Test of

Sphericity

Approx. Chi-Square 6022.149

df 190

Sig. .000

83

Communalities

Initial Extraction

Are produced by processes that have little or

no impact on the environment

1.000 .807

Are produced by processes that are animal

welfare friendly

1.000 .769

Are not transported a great distance 1.000 .607

Support local producers 1.000 .846

Support producers in your country 1.000 .789

Support small producers 1.000 .865

Are available from producers who receive a

fair price

1.000 .675



1.000 .574

Have been produced and supplied in an energy

efficient way

1.000 .770

Can be traced back to the original supplier 1.000 .619

Are available to consumers at a fair price 1.000 .578

Are good for consumers Health 1.000 .665

Taste 1.000 .672

Nutrition 1.000 .693

Are quality assured 1.000 .791

Are fresh 1.000 .752

Are naturally produced 1.000 .629

Have good appearance 1.000 .672

Have long shelf life 1.000 .683

Are hygienically produced 1.000 .674

Extraction Method: Principal Component Analysis.

84

Total Variance Explained

Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %

1 10.008 50.038 50.038 10.008 50.038 50.038 6.167 30.836 30.836

2 2.904 14.522 64.560 2.904 14.522 64.560 5.086 25.432 56.269

3 1.217 6.085 70.644 1.217 6.085 70.644 2.875 14.376 70.644

4 .909 4.546 75.191

5 .602 3.008 78.199

6 .538 2.689 80.888

7 .492 2.462 83.350

8 .451 2.256 85.606

9 .401 2.005 87.611

10 .383 1.914 89.525

11 .338 1.688 91.213

12 .322 1.610 92.822

13 .283 1.414 94.237

14 .262 1.312 95.549

15 .203 1.016 96.565

16 .191 .957 97.522

17 .158 .790 98.312

18 .129 .645 98.957

19 .117 .584 99.542

20 .092 .458 100.000


86

Component Matrixa

Component

1 2 3



.559 .570 .413


welfare friendly

.477 .501 .538

Are not transported a great distance .612 .481 .010

Support local producers .794 .395 -.244

Support producers in your country .776 .375 -.216

Support small producers .794 .400 -.272


fair price

.683 .456 -.026



.717 -.117 .215


efficient way

.840 .253 -.038

Can be traced back to the original supplier .780 .086 .066

Are available to consumers at a fair price .636 -.400 .115

Are good for consumers Health .737 -.249 .244

Taste .628 -.506 -.147

Nutrition .741 -.360 .115

Are quality assured .728 -.480 .174

Are fresh .699 -.501 .111

Are naturally produced .779 -.084 -.120

Have good appearance .757 -.186 -.253

Have long shelf life .634 -.073 -.525

Are hygienically produced .666 -.459 .142


a. 3 components extracted.

87

Rotated Component Matrixa

Component

1 2 3



.074 .337 .830


welfare friendly

.092 .175 .854


Support local producers .217 .831 .328

Support producers in your country .225 .793 .331

Support small producers .208 .852 .310


fair price

.146 .647 .484



.619 .268 .346


efficient way

.391 .667 .414


Are available to consumers at a fair price .739 .158 .081

Are good for consumers Health .730 .206 .298

Taste .752 .276 -.176

Nutrition .784 .242 .141

Are quality assured .870 .145 .111

Are fresh .852 .157 .042

Are naturally produced .568 .536 .139

Have good appearance .595 .563 -.025

Have long shelf life .375 .708 -.205

Are hygienically produced .806 .135 .077


Rotation Method: Varimax with Kaiser Normalization.a

a. Rotation converged in 6 iterations.

88

Appendix 6. Perceived Risk on Food Production Method



Adequacy.

.906

Bartlett's Test of

Sphericity


df 28

Sig. .000

Communalities

Initial Extraction

Animal welfare standards 1.000 .679

Use of pesticides in food production 1.000 .819

Use of fertilizers in food production 1.000 .820

Intensive farming methods 1.000 .695

Use of genetically modified ingredients 1.000 .623

Use of permitted drugs in meat production 1.000 .837

Hygiene standards in food production 1.000 .580

Use of artificial ingredients in food production 1.000 .734



Component Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %

1 5.788 72.344 72.344 5.788 72.344 72.344

2 .533 6.662 79.006

3 .527 6.586 85.593

4 .388 4.855 90.448

5 .306 3.823 94.271

6 .196 2.447 96.718

7 .153 1.907 98.625

8 .110 1.375 100.000


89

Component Matrixa

Component

1

Animal welfare standards .824

Use of pesticides in food production .905

Use of fertilizers in food production .906

Intensive farming methods .833

Use of genetically modified ingredients .789

Use of permitted drugs in meat production .915

Hygiene standards in food production .762

Use of artificial ingredients in food production .857



90

Appendix 7. Purchased Organic Categories

Bakery Products

Frequency Percent Valid Percent Cumulative

Percent

Valid

Never 44 10.3 12.5 12.5

Rarely 73 17.1 20.7 33.2

Occasionally 64 15.0 18.2 51.4

Often 164 38.4 46.6 98.0

Nearly always 7 1.6 2.0 100.0

Total 352 82.4 100.0

Missing System 75 17.6

Total 427 100.0

Dairy products (cheese, milk, yoghurt)


Percent

Valid

Never 34 8.0 9.7 9.7

Rarely 70 16.4 19.9 29.5


Often 40 9.4 11.4 59.7

Nearly always 142 33.3 40.3 100.0

Total 352 82.4 100.0


Total 427 100.0

Fruits


Percent

Valid

Never 21 4.9 6.0 6.0

Rarely 62 14.5 17.6 23.6


Often 179 41.9 50.9 91.2


Total 352 82.4 100.0


Total 427 100.0

91

Vegetables


Percent

Valid

Never 21 4.9 6.0 6.0

Rarely 54 12.6 15.3 21.3


Often 59 13.8 16.8 56.5

Nearly always 153 35.8 43.5 100.0

Total 352 82.4 100.0


Total 427 100.0



Percent

Valid

Never 34 8.0 9.7 9.7

Rarely 60 14.1 17.0 26.7


Often 164 38.4 46.6 93.8


Total 352 82.4 100.0


Total 427 100.0

Alcoholic drink (beer, wine)


Percent

Valid

Never 105 24.6 29.8 29.8

Rarely 177 41.5 50.3 80.1


Often 24 5.6 6.8 98.6


Total 352 82.4 100.0


Total 427 100.0

92

Beverages


Percent

Valid

Never 73 17.1 20.7 20.7

Rarely 78 18.3 22.2 42.9

Occasionally 150 35.1 42.6 85.5

Often 42 9.8 11.9 97.4


Total 352 82.4 100.0


Total 427 100.0

Others


Percent

Valid

Never 69 16.2 19.6 19.6

Rarely 71 16.6 20.2 39.8

Occasionally 185 43.3 52.6 92.3

Often 21 4.9 6.0 98.3


Total 352 82.4 100.0


Total 427 100.0

93

Appendix 8. Future Purchase Likelihood Organic Categories

Bakery products


Percent

Valid

Not at all

likely

20 4.7 5.7 5.7

Unlikely 38 8.9 10.8 16.5

Not sure 181 42.4 51.4 67.9

Likely 93 21.8 26.4 94.3

Very likely 20 4.7 5.7 100.0

Total 352 82.4 100.0


Total 427 100.0

Dairy products (cheese, milk, yoghurt)


Percent

Valid

Not at all

likely

15 3.5 4.3 4.3

Unlikely 30 7.0 8.5 12.8

Not sure 58 13.6 16.5 29.3

Likely 98 23.0 27.8 57.1

Very likely 151 35.4 42.9 100.0

Total 352 82.4 100.0


Total 427 100.0

Fruits


Percent

Valid

Not at all

likely

11 2.6 3.1 3.1

Unlikely 17 4.0 4.8 8.0

Not sure 38 8.9 10.8 18.8

Likely 123 28.8 34.9 53.7

Very likely 163 38.2 46.3 100.0

Total 352 82.4 100.0


Total 427 100.0

94

Vegetables


Percent

Valid

Not at all

likely

10 2.3 2.8 2.8

Unlikely 22 5.2 6.3 9.1

Not sure 38 8.9 10.8 19.9

Likely 121 28.3 34.4 54.3

Very likely 161 37.7 45.7 100.0

Total 352 82.4 100.0


Total 427 100.0



Percent

Valid

Not at all

likely

16 3.7 4.5 4.5

Unlikely 30 7.0 8.5 13.1

Not sure 56 13.1 15.9 29.0

Likely 213 49.9 60.5 89.5

Very likely 37 8.7 10.5 100.0

Total 352 82.4 100.0


Total 427 100.0

Alcoholic drink (beer, wine)


Percent

Valid

Not at all

likely

69 16.2 19.6 19.6

Unlikely 163 38.2 46.3 65.9

Not sure 74 17.3 21.0 86.9

Likely 38 8.9 10.8 97.7

Very likely 8 1.9 2.3 100.0

Total 352 82.4 100.0


Total 427 100.0

95

Beverages


Percent

Valid

Not at all

likely

47 11.0 13.4 13.4

Unlikely 51 11.9 14.5 27.8

Not sure 185 43.3 52.6 80.4

Likely 51 11.9 14.5 94.9

Very likely 18 4.2 5.1 100.0

Total 352 82.4 100.0


Total 427 100.0

Others


Percent

Valid

Not at all

likely

57 13.3 16.2 16.2

Unlikely 32 7.5 9.1 25.3

Not sure 221 51.8 62.8 88.1

Likely 33 7.7 9.4 97.4

Very likely 9 2.1 2.6 100.0

Total 352 82.4 100.0


Total 427 100.0

96

Appendix 9. Satisfaction Level Obtained from various Organic Attributes

Descriptive Statistics Satisfaction Level Obtained from various Organic Attributes

N Mean Std.

Deviation

Are fresh 352 4.49 .792

Are good for consumers Health 352 4.47 .819

Are quality assured 352 4.46 .801

Are hygienically produced 352 4.45 .835

Nutritional content 352 4.43 .848

Taste 352 4.40 .851

Are naturally produced 352 4.37 .887

Are subject to strict government food standards regulations 352 4.28 .982

Have good appearance 352 4.13 .996

Can be traced back to the original supplier 352 4.13 1.099

Are available to consumers at a fair price 352 3.99 .786

Have been produced and supplied in an energy efficient way 352 3.95 1.171

Have long shelf life 352 3.91 1.202

Are sold by reputable seller 352 3.90 .789

Are produced by processes that are animal welfare friendly 352 3.68 .901

Are available from producers who receive a fair price 352 3.64 .904

Are produced by processes that have little or no impact on the

environment

352 3.64 .901

Support producers in your country 352 3.40 .994

Support local producers 352 3.39 .949

Support small producers 352 3.35 .978

Are not transported a great distance 352 3.10 .873


97

Appendix 10. Influences of Benefits on Decision to Purchase

Descriptive Statistics Influences of Benefits on Decision to Purchase

N Mean Std. Deviation

Are quality assured 352 4.47 .813

Are fresh 352 4.47 .791

Nutrition 352 4.45 .846

Are hygienically produced 352 4.44 .839

Are good for consumers Health 352 4.41 .870

Taste 352 4.35 .896

Are naturally produced 352 4.30 .922

Recommendation from people who are important to you 352 4.24 .958

Are subject to strict government food standards regulations 352 4.16 1.033

Have good appearance 352 4.14 .978

To give yourself a special treat 352 4.05 1.122

Are available to consumers at a fair price 352 3.99 .781

Can be traced back to the original supplier 352 3.99 1.128

Have long shelf life 352 3.92 1.183

Have been produced and supplied in an energy efficient way 352 3.88 1.204

Are sold by reputable seller 352 3.87 .804

Are available from producers who receive a fair price 352 3.55 .892

Are animal welfare friendly 352 3.54 .930

Little or no impact on the environment 352 3.50 .890

Support local producers 352 3.36 .980

Support producers in your country 352 3.33 1.029

Support small producers 352 3.32 .979

Are not transported a great distance 352 3.04 .865


98

Appendix 11. Satisfaction Level Obtained from Different Organic Features



Adequacy.

.925

Bartlett's Test of

Sphericity


df 210

Sig. .000

Communalities

Initial Extraction

Are produced by processes that have little or no impact on the environment 1.000 .776

Are produced by processes that are animal welfare friendly 1.000 .764





Are available from producers who receive a fair price 1.000 .677

Are subject to strict government food standards regulations 1.000 .676

Have been produced and supplied in an energy efficient way 1.000 .699




Taste 1.000 .754

Nutritional content 1.000 .801





Are sold by reputable seller 1.000 .530




99




1 11.397 54.270 54.270 11.397 54.270 54.270 7.579 36.089 36.089

2 2.698 12.847 67.117 2.698 12.847 67.117 4.095 19.498 55.587

3 1.121 5.338 72.455 1.121 5.338 72.455 3.542 16.868 72.455

4 .882 4.202 76.657

5 .769 3.664 80.321

6 .656 3.126 83.447

7 .618 2.942 86.389

8 .405 1.927 88.315

9 .396 1.886 90.201

10 .297 1.414 91.615

11 .280 1.334 92.950

12 .269 1.279 94.229

13 .229 1.093 95.322

14 .197 .936 96.258

15 .166 .789 97.047

16 .149 .708 97.755

17 .117 .556 98.312

18 .105 .499 98.811

19 .100 .475 99.286

20 .077 .366 99.653

21 .073 .347 100.000


101

Component Matrixa

Component

1 2 3

Are produced by processes that have little or no impact on the environment .691 .400 .373

Are produced by processes that are animal welfare friendly .669 .370 .424





Are available from producers who receive a fair price .718 .390 .094

Are subject to strict government food standards regulations .815 -.101 .045

Have been produced and supplied in an energy efficient way .793 .255 -.076

Can be traced back to the original supplier .787 .076 -.017

Are available to consumers at a fair price .584 -.294 .216


Taste .789 -.344 -.109

Nutritional content .827 -.341 -.042


Are fresh .803 -.398 .060

Are naturally produced .780 -.188 .081


Are sold by reputable seller .660 -.171 .254

Have long shelf life .644 .034 -.513

Are hygienically produced .826 -.353 -.002



102


Component

1 2 3

Are produced by processes that have little or no impact on the environment .304 .808 .174

Are produced by processes that are animal welfare friendly .313 .809 .112






Are subject to strict government food standards regulations .683 .345 .301

Have been produced and supplied in an energy efficient way .421 .497 .524


Are available to consumers at a fair price .656 .210 -.016


Taste .803 .083 .319

Nutritional content .837 .143 .283


Are fresh .869 .154 .169


Have good appearance .637 .042 .551

Are sold by reputable seller .638 .349 .036

Have long shelf life .399 .025 .721





103

Appendix 12. Effect of Benefits on Decision to Purchase



Adequacy.

.936

Bartlett's Test of

Sphericity


df 253

Sig. .000

Communalities

Initial Extraction

Little or no impact on the environment 1.000 .767

Are animal welfare friendly 1.000 .759





Are available from producers who receive a fair price 1.000 .629

Are subject to strict government food standards regulations 1.000 .701

Have been produced and supplied in an energy efficient way 1.000 .765




Taste 1.000 .716

Nutrition 1.000 .820





Are sold by reputable seller 1.000 .506



Recommendation from people who are important to you 1.000 .690

To give yourself a special treat 1.000 .731


104




1 12.651 55.003 55.003 12.651 55.003 55.003 8.242 35.833 35.833

2 3.130 13.608 68.611 3.130 13.608 68.611 6.156 26.765 62.597

3 1.297 5.640 74.251 1.297 5.640 74.251 2.680 11.654 74.251

4 .842 3.661 77.912

5 .707 3.074 80.985

6 .569 2.474 83.460

7 .461 2.005 85.465

8 .424 1.844 87.309

9 .417 1.812 89.121

10 .371 1.614 90.735

11 .288 1.250 91.985

12 .264 1.146 93.131

13 .232 1.009 94.140

14 .226 .983 95.123

15 .213 .927 96.050

16 .200 .869 96.920

17 .147 .638 97.558

18 .125 .544 98.102

19 .118 .513 98.615

20 .106 .460 99.075

21 .090 .393 99.468

22 .070 .303 99.771

23 .053 .229 100.000


106

Component Matrixa

Component

1 2 3

Little or no impact on the environment .695 .473 .246

Are animal welfare friendly .704 .431 .279






Are subject to strict government food standards regulations .805 -.037 .226



WAre available to consumers at a fair price .544 -.316 .504


Taste .734 -.383 -.174

Nutrition .842 -.329 .053


Are fresh .817 -.395 .040

Are naturally produced .825 -.246 -.020


Are sold by reputable seller .657 -.253 .100

Have long shelf life .670 -.078 -.532

Are hygienically produced .825 -.328 .092

Recommendation from people who are important to you .793 -.175 -.175

To give yourself a special treat .736 -.007 -.435



107


Component

1 2 3

Little or no impact on the environment .289 .827 .021

Are animal welfare friendly .330 .806 -.007

Are not transported a great distance .073 .775 -.083





Are subject to strict government food standards regulations .680 .484 .068



Are available to consumers at a fair price .732 .178 -.289


Taste .735 .079 .412

Nutrition .841 .236 .238


Are fresh .860 .166 .240


Have good appearance .684 .163 .468

Are sold by reputable seller .670 .200 .131

Have long shelf life .405 .200 .731


Recommendation from people who are important to you .650 .276 .437

To give yourself a special treat .435 .316 .665




108

Appendix 13. Determinants of Purchase Likelihood

Model equation:

sumq12 = b0 + b1 sumq8 + b2 sumq9 + b3 sumq11 + b4 sumq13

where

sumq12 = Purchase likelihood

sumq8 = Food features

sumq9 = Perceived risk

sumq11 = Satisfaction obtained from organic features

sumq13 = Influences of benefits on decision to purchase organic food

Based on SPSS (2012) analysis, Adjusted R Square = .416. Approximately 42% of the

variation in the dependent variable is explained by the model. The low Adjusted R Square

means that there are important determinants of the dependent variable that are not included in

the model.

Anova test was conducted to test the whole model. It tests whether the complete set of

coefficients b0, b1 to b4 inclusive are significantly different from zero.

The hypotheses are:

H0: The set of all coefficients is equal to zero

H1: The set of coefficients is not equal to zero

Table 1. Anova Test for Purchase Likelihood

Model Sum of

Squares

df Mean Square F Sig.

Regression

Residual

Total

5001.803 4 1250.451 63.535 .000

6829.422 347 19.681

11831.224 351

The results in Table 1 indicate that the null hypothesis is rejected at the 5 per cent

significance level (F(4, 347) = 1250.451, Sig = .000). Thus, the set of coefficients is not equal

to zero.

The t statistic forms the basis of the test for the significance of the coefficient. The

hypotheses are;

109

H0: The coefficient is zero

H1: The coefficient is not equal to zero

Table 2. Coefficients for Purchase Likelihood

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

(Constant) 6.367 1.501 4.243 .000

Q8 Total Importance Score .063 .031 .160 2.029 .043


Q11 Total Important Score -.046 .026 -.113 -1.760 .079

Q13 Total Important Score .180 .029 .498 6.295 .000

The significant statistic for sumq9 and sumq11 shown in Table 2 are .061 and .079

respectively which is bigger than .05. Therefore, the coefficient is zero.

The most important influences on purchase likelihood are:

Q13 Total Important Score = sumq13 = Influences of benefits on decision to purchase

organic food (.498)

Q8 Total Importance Score = sumq8 = Food features (.160)

Judging from the positive sign of the independent variables, which indicates that, the stronger

the influences of benefits and food features the higher the likelihood of purchase.

110

Appendix 14. Determinants of Satisfaction

Model equation:

sumq11 = b0 + b1 sumq8 + b2 sumq9 + b3 sumq13

where


sumq8 = Food features

sumq9 = Perceived risk

sumq13 = Influences of benefits on decision to purchase organic food




the model.


coefficients b0, b1 to b3 inclusive are significantly different from zero.

The hypotheses are:



Table 3. Anova Test for Satisfaction

Model Sum of

Squares

df Mean

Square

F Sig.

Regression

Residual

Total

42054.874 3 14018.291 171.567 .000

28434.205 348 81.707

70489.080 351


significance level (F(3, 348) = 14018.291, Sig = .000). Thus, the set of coefficients is not

equal to zero.

111


hypotheses are:



Table 4. Coefficient for Satisfaction


Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

(Constant) 19.928 2.865 6.956 .000


Q9 Total Importance Score -.089 .106 -.047 -.838 .403


The significant statistic shown in Table 4 for sumq9 is .403 which is greater than .05.

Therefore, the coefficient is zero.

The most important determinants of satisfaction are:

Q13 Total Important Score = sumq13 = Influences of benefits on decision to purchase

organic food (.641)

Q8 Total Importance Score = sumq8 = Food features (.199)

Judging from the positive sign of the independent variables, which indicates that, the stronger

the influences of benefits and food features the higher the satisfaction.

112

Appendix 15. Purchase Likelihood and Satisfaction

Model equation:

sumq12 = b0 + b1 sumq11

where






the model.


coefficients b0 and b1 are significantly different from zero.

The hypotheses are:



Table 5. Anova Test for Purchase likelihood and Satisfaction

Model Sum of

Squares

df Mean

Square

F Sig.

Regression

Residual

Total

2349.743 1 2349.743 86.739 .000

9481.482 350 27.090

11831.224 351


significance level (F(1, 350) = 2349.743, Sig = .000). Thus, the set of coefficients is not equal

to zero.


hypotheses are:



113

Table 6. Coefficients for Purchase likelihood and Satisfaction


Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

(Constant) 11.674 1.661 7.027 .000


The significant statistic shown in Table 6 for sumq11 is .000 which is smaller than .05.

Therefore, the coefficient is not equal to zero

Judging from the positive sign of the independent variable, which indicates that higher

satisfaction level leads to increase purchase likelihood.

114

Appendix 16. Moderating Effect of Gender on Purchase Likelihood

Model equation 1: sumq12 = b0 + b1 sumq11 + b2 q14

Model equation 2: sumq12 = b0 + b1 sumq11 + b2 q14 + b3isumq11q14

where



q14 = Gender

isumq11q14 = Interactive term between satisfaction and gender

Table 7. Model Summary for Moderated Gender Purchase likelihood

Model R R Square Adjusted R

Square

Std. Error of

the Estimate

Change Statistics

R Square

Change

F Change df1 df2 Sig. F Change

1 .459a .210 .206 5.174 .210 46.503 2 349 .000

2 .475b .226 .219 5.130 .015 6.921 1 348 .009

a. Predictors: (Constant), Your gender (Tick one box), Q11 Total Important Score

b. Predictors: (Constant), Your gender (Tick one box), Q11 Total Important Score, isumq11q14

From Table 7 it is evident that the respective Adjusted R square values for Model 1 (.210)

and Model 2 (.226) are low so that approximately 22% of the variation in the dependent

variable is explained by the models. This suggests that there are important determinants of

behavioural intentions that are not included in the model.

The change in R square of .015 (.225-.210) is statistically significant (ΔF (1, 348) = 6.921,

sig = .009). Hence the significance of the moderator effect is confirmed.


coefficients b0, b1 to b3 are significantly different from zero.

The hypotheses are:



115

Table 8. Anova Test Result for Moderated Gender Purchase likelihood

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression 2489.494 2 1244.747 46.503 .000b

Residual 9341.730 349 26.767

Total 11831.224 351

2

Regression 2671.647 3 890.549 33.835 .000c

Residual 9159.578 348 26.321

Total 11831.224 351

a. Dependent Variable: Q12 Total Important Score

b. Predictors: (Constant), Your gender (Tick one box), Q11 Total Important Score

c. Predictors: (Constant), Your gender (Tick one box), Q11 Total Important Score, isumq11q14

The results in Table 8 indicate that the null hypothesis is rejected for both models at the 5 per

cent significance level. Hence we can conclude that the regression coefficients are not equal

to zero.


hypotheses are:



116

Table 9. Estimated Moderated Regression Coefficients for Purchase likelihood

Coefficientsa


Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 11.297 1.660 6.807 .000

Q11 Total Important

Score

.161 .022 .394 7.490 .000

Your gender (Tick one

box)

1.397 .611 .120 2.285 .023

2

(Constant) 24.646 5.334 4.620 .000

Q11 Total Important

Score

-.002 .066 -.004 -.025 .980

Your gender (Tick one

box)

-8.112 3.665 -.698 -2.213 .028

isumq11q14 .113 .043 1.060 2.631 .009

a. Dependent Variable: Q12 Total Important Score

The results for model 1 (Table 9) indicate that the constant and the regression coefficient are

statistically significant at the 5 per cent level of significance.

The independent variables have a positive sign, which indicates that higher satisfaction level

leads to increase purchase likelihood. This is consistent with a priori expectations.

The equation for the moderator effect is:

Model equation 2: sumq12 = 5.334+ .066 sumq11 + 3.665 q14 + .043 isumq11q14

From Kenny (2013) the total effect of gender on purchase likelihood is:

Effect = .066 + .043 q14

Values for q14 are

1 = Very negative

3 = Neutral

5 = Very positive

117

If q14 = 1 the total effect is

.066 + .043 = .109

If q14 = 3 the effect is

.066 + .043*3 = .195

If q14 = 5 the effect is

.066 + .043*5 = .281

Since the gender majority is female. Hence it is evident that the increase in number of

females leads to an increase in purchase likelihood.

118

Appendix 17. Ethical Form

Application for Approval of NUBS

UG / PGT Research Project

SECTION 1 - to be completed by CANDIDATE

Name:

Tiezheng Yuan

Student No:

110562836

Degree:

NN52

BA (Hons) Marketing and Management

Date:

9th

December 2013

Summary of Proposed Project – typically around 500 words plus supplementary documents if required

Proposed Project Title:

Understanding undergraduates’ attitude towards quality food.

This study aims to understand undergraduates’ attitude towards quality food. Grunert’s Total

Food Quality Model will be used in the study to investigate student perception towards quality

food. After reviewing some journal articles, the researcher found out that there are many

different factors that motivate consumers to purchase quality food. However, not many

researches were conducted on the student population. Besides that, the student segment is

growing rapidly suggesting promising opportunities for marketers. Therefore, this research

seeks to have a thorough understanding of undergraduates’ attitude towards quality food so that

retailers could tap into this lucrative segment.

119

Details of Project Plan - including key milestones

Ethical Issues – and where to get further guidance

(i) Does your research involve NHS PATIENTS OR STAFF, their tissue, organs or data?

Yes ☐ No √

If YES your project will require additional review by a NHS Research Ethics Committee (see

http://www.nres.npsa.nhs.uk). You will also require separate Trust Research & Development Department

(R&D) approval from each NHS Organisation involved in the study (for Newcastle upon Tyne NHS Foundation

Trust (see http://www.newcastle-hospitals.org.uk/about-us/staff-information_research-development.aspx).

When making your application to these bodies, please provide a copy of this project approval form (once it has

been approved) as it will act as your independent peer review.

YES NO

1. Does the project involve human subjects? √

2. Is there any risk of damage to the University’s reputation because of the

sensitivity of the chosen topic?

√

3. Does the project involve risks to the researcher? √

If the answers to all THREE questions above is NO, then there is no need to proceed any further. The supervisor

needs to consider whether the answers are reasonable given the chosen topic.

If the answer to any of the questions above is yes, please answer the remaining questions:

YES NO

4 Does the project involve participants who are particularly vulnerable or unable to give

informed consent? (e.g. children, people with learning disabilities, your own students)

√

5 Does the project require the co-operation of a gatekeeper for initial access to the

subjects? (e.g. students at school, members of a self-help group, residents of a nursing

home)

√

6 Will it be necessary for participants to take part in the study without their knowledge

and consent? (e.g. covert observation of people in non-public places) √

The researcher plans to complete the literature review and methodology by January 2014 when

progress report will be submitted. Qualitative in-depth interviews and subsequent analysis will be

conducted in January-February. A questionnaire will be developed and distributed through online

survey during February-March. Multivariate techniques will be used to analyse the questionnaire

data. Final report will be completed in April 2014.

http://www.nres.npsa.nhs.uk/

http://www.newcastle-hospitals.org.uk/about-us/staff-information_research-development.aspx

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7 Will the study involve deliberately misleading participants in any way? √

8 Will the study involve discussion of sensitive topics (e.g. sexual activity; drug use;

pornography)? √

9 Will participants be offered financial inducements (reasonable expenses are

permissible)? √

10 Will the study involve prolonged and repetitive testing of subjects? √

11 Will the study induce psychological stress or anxiety or cause harm or negative

consequences beyond the risks encountered in normal life? √

12 Will the study involve administering any substances (e.g. food; vitamins) to participants

or any invasive, intrusive or potentially harmful procedures of any kind? √

13 Will the study involve students or staff of this university as participants? √

14 Will the study involve recruitment of staff or patients through the NHS? √

15 Will the study involve any actions which might be regarded as unethical or illegal? √

If one or more of questions 4-15 answers yes, please complete the following sections in as much detail as

possible:

Type of project:

Please indicate the predominant nature of this project (mark one box only):

Questionnaire/Survey

e.g. surveys of members of particular groups / organisations; mail out questionnaires, street surveys √

Experiments

e.g. participants completing tasks under controlled conditions, use of tasks/method other than or in

addition to questionnaires/surveys

Observational

e.g. observing how people behave in a natural setting or in a laboratory

Data-based

e.g. the use of official statistics where individuals could be identified

Other

If you answered ‘Other’

please provide additional

details.

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Proposed Start Date of Research Project: January 2014

Project Outline & Aims: Briefly describe the aims of this research as well as the main tasks (or tests) that participants will be required to

complete or what use will be made of sensitive economic, social or personal data. This description must be in

everyday language, free from jargon, technical terms or discipline-specific phrases. (No more than 700 words)

The aim of this research is to understand undergraduates’ attitude towards quality food. The research objectives

are to understand consumer decision making process when purchasing quality food; to establish the dimensions

underlying undergraduates’ attitudes to quality food; and to profile the student segments using the dimensions

identified.

The outline of this project consists of an overview of the quality food market; analysis on previous studies

regarding consumer motivation when purchasing quality food; investigating consumer decision making process

when making purchase; establishing the underlying dimensions concerning quality food; profiling the segments

using the dimensions identified; and finally, the implications for quality food sector marketing strategies.

In-depth interviews will be conducted with university students in the UK based on Grunert’s Total Food Quality

framework. Laddering technique will be used to elicit attribute-consequence-value associations consumers have

with respect to quality food. Framework may be modified based on the interview results for further research.

Quantitative approach will be used to examine the framework. A questionnaire will be designed based on the in-

depth interview findings and distributed through online survey. Multivariate analysis will be applied to the data

collected and marketing implications will be drawn from the results.

Proposed Research Methods

Please provide an outline, in layman’s terms, of the proposed research methods, including where and how data

will be collected and stored (including steps that will be taken to ensure the confidentiality of personal data) and

all tasks that participants will be asked to complete. Specify if the research will take place outside of the UK or

in collaboration with internationally-based partners, and / or if research will take place using the internet.

Present an outline of the method in a step-by-step chronological order, and avoid using jargon and technical

terms as much as possible. (No more than 700 words)

Qualitative data will be collected using in-depth interview. In-depth interviews will be recorded to aid

transcribing and thematic analysis. The researcher will ensure participants’ confidentially is maintained

throughout the final report by coding the participants’ names into initials or numbers.

Quantitative data will be conducted using an online survey. The data collected will be analysed using SPSS

software. The researcher will ensure participant data is protected under the Data Protection Act 1998.

Participants will not be individually identified in the final report.

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Participant information YES NO

Will you inform participants that their participation is voluntary? √

Will you inform participants that they may withdraw from the research at any time and for

any reason? √

Will you inform participants that their data will be treated with full confidentiality and that,

if published, it will not be identifiable as theirs? √

Will you provide an information sheet that will include the contact details of the

researcher/team? √

Will you obtain written consent for participation? √

Will you debrief participants at the end of their participation (i.e., give them an explanation

of the study and its aims and hypotheses)? √

Will you provide participants with written debriefing (i.e., a sheet that they can keep that

shows your contact details and explanations of the study)? √

If using a questionnaire, will you give participants the option of omitting questions that they

do not want to answer? √

If an experiment, will you describe the main experimental procedures to participants in

advance, so that they are informed about what to expect? N/A

If the research is observational, will you ask participants for their consent to being

observed? N/A

Participant consent

Please describe the arrangements you are making to inform participants, before providing consent, of what is

involved in participating in your study and the use of any identifiable data. (No more than 300 words)

In-depth interview participants will be informed of the project aim and objectives and will be asked for their

verbal consent to participate in the study.

Questionnaire participants will be informed of the project aim and objectives and will be informed that their

participation is voluntary.

Participants should be able to provide written consent. Please describe the arrangements you are making for

participants to provide their full consent before data collection begins OR If you think gaining consent in this

way is inappropriate for your project, then please explain how consent will be obtained and recorded. (No more

than 300 words)

Before the in-depth interview begins, the researcher will ask the participants to sign a written consent form.

In the beginning of the online survey, questionnaire respondents will be informed that by completing and

submitting the survey, they are giving their consent for their responses to be used.

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Participant debriefing

It is a researcher’s obligation to ensure that all participants are fully informed of the aims and methodology of

the project, that they feel respected and appreciated after they leave the study and to ensure that participants do

not experience any levels of stress, discomfort, or unease following a research session. Please describe the

debriefing that participants will receive following the study and the exact point at which they will receive the

debriefing. If you do not plan to provide a written debriefing sheet then please describe your alternative position.

(No more than 300 words)

The researcher will provide a written debriefing sheet to each interview participant upon the completion of the

interview. Participants will also be thanked for their participation through verbal message.

Online survey respondents will be thanked at the end of the survey completion.

Insurance and Risk Considerations

Potential risk to participants and risk management procedures

Identify, as far as possible, all potential risks (small and large) to participants (e.g. physical, psychological, etc.)

that may be associated with the proposed research. Please explain any risk management procedures that will be

put in place and attach any risk assessments or other supporting documents. Please answer as fully as possible,

note ‘None’ / ‘No risk responses’ are not appropriate. (No more than 300 words)

No potential risks to participants beyond those encountered in daily life.

Potential risk to researchers and risk management procedures

What are the potential risks to researchers themselves? For example, personal safety issues such as lone or out

of normal hours working or visiting participants in their homes; travel arrangements, including overseas travel;

and working in unfamiliar environments. Please explain any risk management procedures that will be put in

place and attach any risk assessments or other supporting documents. (No more than 300 words)

No potential risk to researcher beyond those encountered in daily life.

Signature of Candidate:

Date: 9th

December 2013

This form will be passed to your academic supervisor for consideration

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SECTION 2 - to be completed by SUPERVISOR

Proposed Supervisor – Identified in consultation with the Dissertation Co-ordinators in NUBS

Academic Supervisor: Dr Mitchell Ness

☐ X This project has been approved by the Academic supervisor

☐ This project has been submitted to the School Research Ethics Committee

Supporting Statement - to be completed by Supervisor– including information on project funding and any

resource implications. If there are any resource implications for the Library please inform the relevant Library

Liaison Officer for your School.

All aspects of the study are to be conducted according to the Market Research Society Code of

Practice (2010) and the Data Protection Act 1998.

The Market Research Society Code of Practice (2010) includes general rules of professional

conduct (MRS code items A.1-A.10), designing of the research project (MRS code items B.1-

B.2), respondents’ rights to anonymity (MRS code items B.8-B.10), the design of the data

collection process (MRS code item B.14), preparation of fieldwork (MRS code items B.15-B.16),

Fieldwork (MRS code items B.17-B.24), analysis and reporting of findings (MRS code items

B.49-B.61), and data storage (MRS code items B.62-B.64).

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SECTION 3 – to be completed by School Ethics committee

School Ethics Committee Recommendations

☐ The Panel notes Research Ethics Approval is required for this project.

The panel should consider the evidence and make written notes below, or on additional sheets if required. In the

event of concerns the report should indicate the steps necessary to address them. These notes will be made

available to the student and to the supervisory team.

School Ethics Convenor:

Signature: [ ] Date: [ ]

Schools should feedback the recommendations from the Project Approval Panel to the Candidate.

Date return to UG / PG office: [ ]

This form should now be passed to your Graduate School Office

Dean of Postgraduate Studies

Signature: [ ] Date: [ ]

Dissertation Final

Documents

Transcript of Dissertation Final