60

Chapter 3

Research Methodology

This research work aims to assess the land record information system and develop an

effective model for its e-Enablement using Mobile commerce. However, a logical and

systematic approach is required for the purpose. The present chapter discusses not only the

steps involved in conducting this research, but also justifies the selection of various

methods. These are described as under.

3.1 Preparation of Respondents’ Database and Scope of Study

Digitization of land records has become a major talk out of all the e-Governance initiatives

of the Government of Punjab. It has aroused a new hope, especially among the rural

masses as they can easily access the required land record, and find a quick solution to their

problems without much difficulty and delay. The State of Punjab has been selected for the

purpose of this study because of the reform initiatives taken by the Government in the

revenue department through automation of land records under the e-Governance program.

Punjab being an agrarian State has majority of its population residing in rural areas and

their main source of livelihood is agriculture. Fard Centres (Fard Kendras) have been

established for the successful implementation of land records. The establishment of Fard

Centres has helped to remove corruption and unusual delays in such matters to a great

extent. The stakeholders for any e-Governance initiative project are the citizens and the

Government officials. It has led to win the confidence of the general public in the

Government services being provided to them. The common citizens have been the main

beneficiary of this initiative as it has resulted in more transparency of the revenue records

and reduction in the procedural intricacies related to the land records.

61

A number of sub-objectives and correlated factors have been highlighted so as

to meet the objectives of this research. The need of the hour is the integration of

automation of land records with mobile technologies and other e-Government services,

which will further result in making e-Governance initiatives available at the doorstep of the

common citizens.

3.2 Current Scenario of Land Records: State of Punjab

The digitization of land records is an e-Governance initiative of the Government of Punjab

and is seen as a revolutionary step to improve the overall depleting state of the revenue

records of the State. There are total of 13,001 villages in the State of Punjab and the land

records of nearly 12,683 villages have been already digitized (as available on:

http://articles.timesofindia.indiatimes.com). The Fard Kendras (land record information

centres) have been established all over the State at the various Tehsils and sub-Tehsils.

These Fard Kendras have been connected to the Fard Centres at the District headquarters,

which are in turn further connected to PLRS (Punjab Land Record Society) headquarters

located at Jalandhar district. The information about land records at various districts is thus

interconnected with the central information web server maintained at PLRS. The up-to-

date land record at Fard Centres is further provided to the PLRS headquarters. Thus, PLRS

headquarter acts as repository of information for all the land records of the Fard Centres in

the State of Punjab. The land records of remaining few villages and those belonging to

urban area are being automated in a phased manner. Currently, the computerization of

Jamabandi (record of the land updated after every 4 years) and the digitization work of

Mutations (Intkal) is also going on in a phased manner.

Patwaris (revenue record officers) are officially available twice a week at the Fard

Centres for updating and correction of land records. The land records need to be updated

62

because of the sale transactions of the land or due to the death of land owner or transfer to

legal owner or for mortgage reasons, etc. Since the land records are dynamic in nature, the

change of the ownership or title of the land can happen anytime. Hence, the updating of the

records is a must for maintaining the legal inheritance and defining the legal right of the

land owners. Thus, there will be more accuracy of information and lesser chances of errors

pertaining to the land records. It has resulted in saving time and resources of the common

citizens, especially those residing in rural areas. The website http://www.plrs.org.in gives

complete digitized online information related with land records of the State and is used for

updating all the land records of the common citizens resulting in more transparency of the

revenue records. The land record is available at the Fard Centres and can be accessed

online (24x7) through PLRS (Punjab Land Record Society) website as shown below in

Figure 3.1.

Figure 3.1: Snapshot of the PLRS website (http://www.plrs.org.in)

63

3.3 Benefits of Computerisation of Land Records

The computerization of land records is seen as a revolutionary step, as part of the

administrative reforms, to mitigate corruption from the public dealing seats in various

Government departments. It has resulted in the following benefits for the common citizens

of the State.

It has resulted into a hassle-free system in which the common citizen is no longer

required to shuttle between the various offices of the revenue officials.

It has led to corruption-free environment as common citizens do not require shelling

out extra money to grease palms of revenue officials, resulting in bringing an end to

such malpractices. Computerized copies of the land records are available to farmers

and landowners with the payment of official nominal fees of Rs. 20/- per page of land

record.

Records have been accessible online for the public for any-time, any-where

transactions through the land record website.

The total mutations in the State being running into lacs; most of the land records

related with Fard Centre services such as Jamabandi, Girdavari and Mutation have

been put online on the Punjab land record society (PLRS) website. There is ready

availability of the land records in connection with Jamabandi (Fard), Girdavari

(possession) and mutation (transfer of property) besides searching records according

to Khewat and Khatauni number. The details of the revenue records can be easily

fetched on the basis of the name and the land record number associated with the

citizens.

64

Any farmer or client can check the authenticity of the revenue records (Fard, etc.) and

can avail the soft copy of the record from anywhere around the world, thus leading to

greater transparency of land records.

It has also resulted in quick sale and purchase of land due to high authenticity and

reliability of land records. Anyone who wants to go for sale or purchase of the land

can access the record in a transparent manner to find the genuine owner of the land.

The availability of land records in digital form has also led to the reduction in the

overall land-related litigation in courts. Thus this automation of land records has

resulted in authentic land holders and helped in minimizing the tampering of land

records.

The automation of land records has led to ease in administration of other land related

departments for acquisition and grant purposes, etc. to the authentic land holders.

Land record digitization has helped in increasing awareness amongst the common

citizens regarding e-Governance projects.

Automation of land records has been successfully implemented with the establishment

of Fard Centres by the Government. It has led to the creation of jobs such as data

entry, updating of land records and various other jobs related with the maintenance of

land records for the citizens of the State.

The revenue department has also benefitted from this e-Governance initiative by the

Government of State of Punjab as this computerization of land records has resulted in

streamlining of operations for Jamabandi which need to be prepared and updated after

gap of every 4 years.

On the administration side, it has led to easy monitoring and shifting of the land

records to the concerned officials in case there is transfer of Patwari or Kanungo

(revenue officials).

65

3.4 Existing System - Issues (Challenges)

The Fard Centres have been established at various district Tehsils and sub-Tehsils of the

various States in India so as to provide automated computerization of the revenue records

and better e-Governance to the common citizens of the country. Still many deficiencies

(issues) that exist in the current system have been detailed below.

Distant location of the Fard Centre (as most of Fard Centres are located in urban and

semi-urban areas).

Lack of awareness about the e-Governance initiative of State Government for

establishment of Fard Centres for accessing of land records by the citizens.

Time-consuming process (citizens need to stand and wait in queues).

Power (electricity) supply problems at the Fard Centres.

Lack of support, training or guidance to the citizens.

Staff and operator problems at the Fard Centres.

Procedural hassles.

Illiteracy problem (lack of knowledge).

Malpractices by officials.

Non-availability of kiosks (self-operated system).

Revenue officials still like to pursue with traditional methods.

Problems in availing loan from the bank: The authenticated land records need to be

presented to the bank officials. As both bank and Fard Centres are located distantly in

urban or semi-urban areas, the loan transaction and approval process results in sheer

time-wastage and unnecessary harassment of the client.

66

Unexpected delay in delivery of land records: The frequent power cuts (electricity

problems), technical problems related to database updating and lack of infrastructure in

some districts/Tehsils result in inconvenience and harassment of the citizens.

3.5 Questionnaire Design

The focus of this work is the detailed study and analysis of the data collected from 400

respondents; in this case the citizens availing e-Governance services at land record

information centres (Fard Centres) at the randomly selected Districts and Tehsils/Sub-

Tehsils of Punjab. A detailed analysis of the citizen’s expectations and technical viability

has been developed based upon their opinion. The questionnaire has been designed on the

basis of comprehensive review of the existing relevant literature besides discussions and

brainstorming sessions with researchers, experts and academicians. White papers, State

projects implementation reports, bulletins, journal publications, relevant Government

websites and various books of concern form the source of data collection for the research.

A five-point (1-5) Likert scale has been used to record the responses (opinions)

of the citizens where 5=Strongly Agree, 4=Agree, 3=Neutral, 2=Disagree and 1=Strongly

Disagree. Likert scale is considered more reliable and is easy to construct (Shahjahan,

2005). The questionnaire-cum-interview method has been deployed to collect the primary

data of the selected respondents. Personal discussions and in-depth interviews have been

conducted so as to get a deep insight into the functioning of Fard Centres established for

the convenience of land records for the common citizens of the State. This also highlighted

the opinions of the citizens about the various benefits and problems related with the land

record services available at the Fard Centres. The random stratified sampling techniques

have been used for the collection of data and further processed by deploying various

statistical and analytical methods so as to result in relevance to the objectives of the study.

67

Most of the questionnaires have been filled by the respondents themselves. The illiterate

respondents have been dictated the questionnaire for collecting their responses. The

citizens visiting Fard Centres for availing the land record services at various Districts and

Tehsil/Sub-Tehsil level were approached personally and convinced to be part of this

research, emphasizing its benefits. The primary data was collected using self-structured

close-ended questionnaires. Questionnaire (as given in Appendix-I) constitutes Part-A and

Part-B (I, II and III). Part-A (Primary Part) relates to the detailed demographic profile of

the respondents of the study. Part B (I) comprises the citizen’s response regarding the

study of existing mobile commerce practices, Part B (II) includes the citizen’s response

regarding the assessment of the current scenario of land record information system

whereas Part B (III) involves the citizen’s response for the requirements of land record

information system using M-commerce methods.

3.6 Testing of the Questionnaire (for Reliability, Consistency and Validity)

Cronbach’s alpha reliability has been used to test the reliability of the questionnaire. It is

regarded as the degree of accuracy of the collected data and is a measure of internal

consistency. Cronbach’s alpha reliability index value for all the variables indicated

goodness of the scale. A pilot study for the survey in the form of questionnaire has also

been conducted before finally administering to the respondents in order to ensure clarity,

relevance, validity and effectiveness of the questionnaire. Testing of the questionnaire

included its relevance with the research objectives of the study, the existing scenario and

its comprehensiveness. The questionnaire designed has then been modified based upon the

feedback and suggestions of the respondents. The relevant and vital suggestions for the

improvement and modification of the questionnaire have been incorporated in the light of

inconsistencies found during the pilot study so as to enhance usefulness for the

68

respondents. Responses were studied by test administering the questionnaire. It was found

that on an average 20-25 minutes were required for each respondent whereas as a whole,

full conversation with the respondents required about 30-35 minutes. The sensitivity of the

questionnaire was ensured by adding multiple questions related to the specific objective

regarding the domain of the study.

3.7 Mapping of Objectives to the Questionnaire

Figure 3.2 below depicts the mapping of the objectives to the questionnaire.

Figure 3.2: Mapping of Objectives to the Questionnaire

Objective 1

To Study the Existing Mobile

Commerce Practices

Questionnaire

(Appendix I: Part B-I)

Objective 2

To Assess the Current Scenario of

Land Record Information System

Questionnaire

(Appendix I: Part B-II)

)

Objective 3

To Seek the Requirements of Land

Record Information System Using

M-Commerce Methods

Questionnaire

(Appendix I: Part B-III)

)

Objective 4

To Design and Evolve M-

Commerce Based Model of Land

Record Information System

Presented through UML

Diagrams and Model

Implementation via M-

commerce Application

(Presented in Chapter - 7)

Objective 5 To Test the M-Commerce Model

Proposed Model on the basis

of PCA and Regression

(Presented in Chapter - 8)

69

The questionnaire has been mapped to the research objectives before data collection phase

so that the adequacy and comprehensiveness of the questionnaire can be matched with the

stated objectives.

3.8 Sampling Plan

The present study focuses to analyze the citizen’s perceptions at the Fard Centres

established in the State of Punjab. The random samples of the respondents have been

collected in the form of questionnaire. The details of the research methodology adopted for

this research work is as detailed below.

I. For the State of Punjab

a) Universe of the Study: All the districts of the State of Punjab. Three main

regions of Punjab – Majha, Doaba and Malwa constituting various Districts as

mentioned below:

i) Majha - Amritsar, Gurdaspur and Tarn-Taran.

ii) Doaba - Jalandhar, Hoshiarpur, Kapurthala and S.B.S. Nagar (Nawanshahr).

iii) Malwa - Barnala, Bathinda, Faridkot, Fatehgarh Sahib, Ferozepur, Ludhiana,

Mansa, Moga, Muktsar, Patiala, Rupnagar, S.A.S. Nagar and Sangrur.

b) Sample Selection: The study analyses the working and job execution at the Fard

Information Centres (Fard Centres) established by the Government of Punjab for

updating and maintenance of land records. On random basis, following Districts and

Tehsils/sub-Tehsils have been chosen region-wise for this study: Fatehgarh Sahib

and Patiala represents Malwa region, Amritsar and Gurdaspur led the Majha region

70

whereas Jalandhar and S.B.S. Nagar (Nawanshahr) represents Doaba region (as

shown below in Table 3.1).

II. For Respondents

a) Universe of the Study: All the common citizens of the State of Punjab.

b) Sample Selection: The sample selection consists of the primary data

collected from randomly chosen 400 common citizens of the selected Tehsils/Sub-

Tehsils of Punjab, out of which 200 samples each have been collected at the

District level and Tehsil/sub-Tehsil level. The stratified random sampling

technique has been deployed on the citizens’ data in terms of the sample size

selection and the total number of respondents.

Table 3.1: Sampling Plan for Citizens

*Web Source for population: http://censusindia.gov.in/PopulationFinder/Population_Finder.aspx

As shown in Table 3.1 above, sample size (at District and Tehsil/sub-Tehsil level) has been

worked out by doubling percentages (%). Region-wise total for Majha region is 96, Doaba

S.No.

Region

Districts

Population

*

%

Sample

Size

(District

Level)

Sample

Size

(Tehsil/

Sub-

Tehsil

Level)

Region-

wise

Total

1.

MAJHA

Amritsar 24,90,891 25 50 50

96

2. Gurdaspur 22,99,026 23 46 46

3.

DOABA

Jalandhar 21,81,753 21 42 42

54

4. S.B.S.

Nagar 6,14,362 6 12 12

5.

MALWA

Fatehgarh

Sahib 5,99,814 6 12 12

50

6. Patiala 18,92,282 19 38 38

TOTAL 1,00,78,128 100 200 200 200

71

region is 54 and for Malwa region is 50. It varies according to the population strength of

the specific cities in relation to the cumulative strength of all cities of three regions. The

population statistics for the State of Punjab currently stood at 2,77,04,236 and have been

considered on the basis of population data conducted in India as part of Census-2011.

3.9 Demographic Profile of the Respondents

This part deals with the details of demographical profile of respondents (citizens). The

randomly selected respondents have been classified into several categories based on the

classifiers of gender, area, qualification, income, age group and profession as detailed

below. The sample profile of the respondents (citizens) is showcased in Table 3.2 below.

Table 3.2: Sample Profile of the Respondents (Citizens)

Categories Count* Percentage

(%)

(400)

Area

Urban 113 28

Semi-urban 91 23

Rural 196 49

Qualification

Graduate 125 31

Matriculation/10+2 184 46

Illiterate 91 23

Income (Annual)

Not income tax-payer 299 75

(BPL/not BPL)

Income tax-payer 101 25

72

Age Group (in years)

Above 60 46 11

18-60 351 88

Below 18 3 1

Profession

Employed (Government service/private) 66 16

Businessman 29 7

Student 6 2

Farmer 292 73

Unemployed / Non-working 7 2

Gender

Male 376 94

Female 24 6

Region

Malwa 103 26

Majha 188 47

Doaba 109 27

*Here, Count represents the number of respondents.

Table 3.2 above indicates the sample profile of the respondents (citizens) where categories

constitute various demographic group profiles and percentage (%) indicates the percentage

response size of the respondents. Out of the total of 400 sample size, most of the

respondents are found to be males or belonging to the 18-60 years of age group. This is so

because males predominantly manage agricultural lands and avail land record services at

the Fard centres in comparison to the females. Almost half of the total respondents are

from rural area as more than 60% of the citizens reside in rural areas in the State of Punjab

(India Census-2011) and their livelihood being largely dependent on agriculture. A

majority of the citizens are non income-tax payers whereas BPL respondents have been

73

found to be negligible since they do not avail land record services as they are deprived of

land holdings through hereditary or financial means. The demographic profiles of

respondents (citizens) consist of various professions such as unemployed, farmers and

students. The distinguishing feature of this study is the majority of the respondents being

farmers (73%) as they often visit Fard Centres for availing land record services.

3.9.1 Sample Frame

Demographic Profile: The sample distribution of the demographic profile of the

respondent citizens with respect to gender, area, region, qualification, income, age group

and profession is as detailed below. Count represents the sample (number) of respondent

citizens (total=400).

A. Sample Distribution: Gender-wise Proportion

Table 3.3 below represents the distribution of respondents (gender-wise). It shows that

94% respondents are males and 6% are females in the present study.

Table 3.3: Sample Distribution: Gender-wise Proportion

Gender Count Percent (%)

Male 376 94

Female 24 6

The sample distribution based on gender is shown in Figure 3.3.

74

Figure 3.3: Sample Distribution: Gender-wise Proportion

B. Sample distribution: Area-wise proportion

Table 3.4 represents the distribution of respondents (area-wise). It depicts that 28% of

citizens belong to urban area whereas 23% and 49% of citizens belong to semi-urban area

and rural area respectively.

Table 3.4: Sample Distribution: Area-wise Proportion

Area Count Percent (%)

Urban 113 28

Semi-urban 91 23

Rural 196 49

The sample distribution based on area is shown below in Figure 3.4.

Figure 3.4: Sample Distribution: Area-wise Proportion

Male

94%

Female

6%

Urban

28%

Semi-Urban

23%

Rural

49%

75

C. Sample Distribution: Qualification-wise Proportion

Table 3.5 below represents the distribution of qualification-wise profiles of respondents. It

shows that 46% respondents are having qualification as Matric/10+2 whereas 31% and

23% are graduates and illiterates respectively.

Table 3.5: Sample Distribution: Qualification-wise Proportion

Qualification Count Percent (%)

Graduate 125 31

Matriculation/10+2 184 46

Illiterate 91 23

Their sample distribution based on qualification is shown below in Figure 3.5.

Figure 3.5: Sample Distribution: Qualification-wise Proportion

D. Sample Distribution: Income-wise Proportion

Table 3.6 below represents the distribution of income-wise profiles of respondents. It

shows that 75% are not income tax-payers (BPL/not BPL) whereas 25% are income tax-

payers.

Graduate

31%

Matric/10+2

46% Illiterate

23%

76

Table 3.6: Sample Distribution: Income-wise Proportion

Income Count Percent (%)

Not income tax-payer

(BPL/not BPL) 299 75

Income tax-payer 101 25

The sample distribution based on income is shown below in Figure 3.6.

Figure 3.6: Sample Distribution: Income-wise Proportion

E. Sample Distribution: Age group-wise Proportion

Table 3.7 below represents the distribution of respondents (age group-wise). It shows that

88% respondents are of 18-60 years of age-group whereas 11% and 1% respondents are

above 60 years and below 18 years of age-group respectively.

Table 3.7: Sample Distribution: Age group-wise Proportion

Age group

(in years) Count Percent (%)

Above 60 46 11

18-60 351 88

Below 18 3 1

The sample distribution based on age group is shown in Figure 3.7.

Income tax

payer

25%

Not income

tax payer

75%

77

Figure 3.7: Sample Distribution: Age group-wise Proportion

F. Sample Distribution: Profession-wise Proportion

Table 3.8 below represents the distribution of profession-wise profiles of respondents. It

shows that the percentage on the basis of count (number of respondents) for farmers,

employed, businessman and unemployed is 73%, 16%, 7%, 2% respectively whereas only

2% are students.

Table 3.8: Sample Distribution: Profession-wise Proportion

Profession Count Percent (%)

Employed

(Government service/private) 66 16

Businessman 29 7

Student 6 2

Farmer 292 73

Unemployed /Non-working 7 2

The sample distribution based on profession is as shown below in Figure 3.8.

Figure 3.8: Sample Distribution: Profession-wise Proportion

Below 18 yrs

1%

18-60 yrs

88%

Above 60 yrs

11%

Unemployed

2%

Employed

16%

Bussinessman

7%

Student

2%

Farmer

73%

78

G. Sample Distribution: Region-wise Proportion

Table 3.9 below represents the distribution of region-wise profiles of respondents. It

indicates that the percentage on the basis of count (number of respondents) for Malwa,

Majha and Doaba region is 26%, 47% and 27% respectively.

Table 3.9: Sample Distribution: Region-wise Proportion

Region Count Percent (%)

Malwa 103 26

Majha 188 47

Doaba 109 27

The sample distribution based on region is as shown below in Figure 3.9.

Figure 3.9: Sample Distribution: Region-wise Proportion

3.10 Data Analysis Techniques

The responses of 400 respondents were gathered and recorded on the summating rating

method of five point Likert scale. The valid responses have been coded, tabulated and then

statistically analyzed. The data obtained has been processed and analyzed for citizen’s

data. SPSS has been used for analytical processing of the selected data. The questionnaire

has been divided into the various demographic profiles for the respondents such as gender,

area, qualification, income, age group and profession. The questionnaire as illustrated in

Doaba

28%

Majha

47%

Malwa

26%

79

Appendix-I has been developed on the basis of literature survey and after thorough

discussions with researchers and academicians. Appropriate sample from the common

citizens has been selected on the basis of Statistical Stratified sampling technique. Various

statistical tools have been applied to analyze the secondary data. Mean scores and Rank

methods have been used in order to identify the influence of various factors based on the

opinions of the citizens that have been classified into various demographic profiles. t-test

and ANOVA F-test have been deployed for finding out the mean difference in opinion

between the factors regarding the various demographic profiles except for region. No

significant differences in the mean scores of various sub-groups were observed for the

considered regions in this research concerning the State of Punjab namely; Malwa, Majha

and Doaba regions. Hence, they have not been considered for finding the difference in

opinion of the mean scores of the respondents based on t-test and ANOVA F-test.

The specific methodology of this research study (as illustrated below in

Figure 3.10) follows the concept of Walker’s (1997) model and is based on the literature

review, a survey questionnaire, face-to-face interviews and detailed case studies. Factor

analysis (Principal Component Analysis) has been used to extract the suitable principal

components and then regrouping of the extracted common variables has been conducted

through factor loading. The various factors related with the research objectives have been

hypothesized in order to find the effect on citizen demographic profile responses. The

developed hypothesized relationships have been fully validated in the form of results. The

null hypotheses and alternate hypotheses have been developed to accomplish the

objectives. In order to find the relationship between the research objectives and the citizen

demographic profile responses, various developed hypotheses have been tested using

Correlation analysis. Regression analysis has also been deployed to test the relationship

between the factors of the various objectives and citizen demographic profile responses.

80

All these factors identified and analyzed, result into M-commerce model for the Land

record information system (LRIS). UML (Unified Modeling Language) has been deployed

for modeling the step-by-step systematic design of the developed model. UML is a general

purpose notational language for specifying and visualizing complex software, especially

large object-oriented projects. The features of the system have been visually mapped by

deploying StarUML, a tool of UML. Various statistical tests have been applied to the data

collected so as to result in the desired proposed model. The positive and negative

estimators (predictors) have been illustrated using Regression Models for the research

objectives.

Figure 3.10: Overall Research Framework for the Research Study

(Walker, 1997)

1. Drawn on knowledge published in literature;

2. Gain experience from experts in the field.

1. Test the factors leading to the

success of a project;

2. Adopt the criteria in assessing the

success of a existing project.

1. Gain an understanding of the

existing practice;

2. Provide information for the

refinement of the pilot questions and

develop research questionnaire.

1. Factor analysis;

2. Multiple regression.

Pilot Study Questionnaire Face-to-face interview

Empirical Research Questionnaire

Data Analysis

Preliminary Conclusions

Final Report

81

Hypothesis testing process chooses between different alternatives, which have to be

mutually exclusive and exhaustive (Gaur and Gaur, 2009). A two-tailed test has been done

for the testing of hypotheses in the form of H0 (null hypothesis) and H1 (alternate

hypothesis) as given by:

H0: µ1 = µ2

H1: µ1 ≠ µ2

The null hypothesis is rejected if the p-value obtained is less than the significance level at

which the hypotheses have been tested and is accepted if it is greater than the significance

level at which the hypotheses have been tested.

Methodological Notes:

The various terms and symbols used in the analysis have been presented below in the

Sample Table (Table 3.10) and described as follows:

Table 3.10: A Sample Table

Facto

rs Gender Age group Area Qualification Income Profession

Mal

e

Fem

ale

Bel

ow

18

18

-60

Ab

ov

e 6

0

Urb

an

Sem

i-U

rban

Ru

ral

Gra

du

ate

Mat

ric/

10

+2

Illi

tera

te

BP

L

No

t in

com

e ta

x-p

ayer

Inco

me

tax

-pay

er

Un

emp

loy

ed

Em

plo

yed

Bu

sin

essm

an

Stu

den

t

Far

mer

F2 -9.35** 5.01** 10.46** 40.99** 17.4** 3.93**

F4 -0.39 33.76** 4.75* 4.53* 11.32** 11.47**

82

I. Likert scale (Summating rating method): 5 point scale (numbered 1-5)

II. Fi denotes the ith factor (i=2 means F2)

III. * denotes 5% significance level

IV. ** denotes 1% significance level

V. t denotes t-test (for Gender)

VI. F denotes ANOVA F-test (for age group, area, qualification, income and

profession)

3.11 Chapter Summary

The chapter highlighted the design of the developed questionnaire and its mapping with the

various research objectives. The sampling plan, sample distribution of the demographic

profile of the respondents and the data collection method has been highlighted. The various

data analysis techniques deployed for analyzing the data related with the citizens have been

detailed in this chapter.

The next chapter discusses the study of the existing Mobile commerce practices.

REFERENCES

Gaur, A.S.; and Gaur, S.S. (2009), “Statistical Methods for Practice and Research: A

Guide to Data Analysis Using SPSS”, 2nd

edition, SAGE publications, India.

Shahjahan, S. (2005), “Research Methods for Management”, 3rd

edition, JAICO Publishing

House, Mumbai, India.

83

Walker, D.H.T (1997), “Choosing an appropriate research methodology”, Construction

Management and Economics, 15(2):149-159.