Ch5 final Mod-Final-109-133 - Information and Library …shodhganga.inflibnet.ac.in/bitstream/10603/7328/13/13... · · 2015-12-04Fieldwork or Data collection Data Preparation and

Research Methodology

CHAPTER-5

CHAPTER 5 Research Methodology

PhD Thesis Sunita Guru Page Number 110

5.1 Introduction

Research is any organized inquiry carried out to provide information for solving

problems. Marketing research is a systematic inquiry that provides information to

guide marketing decisions. The American Marketing Association defines

marketing research as “Marketing research is the function that links the consumer,

customer and public to the marketer through information – information used to

identify and define marketing opportunities and problems –generate , refine and

evaluate marketing actions ; monitor marketing performance ; and improve

understanding of marketing as a process”. Marketing research specifies the

information required to address these issues, designs the method for collecting

information, manage and implements the data collection process, analyzes the

results and communicates the findings and their implications1.

In other words, marketing research is the systematic and objective identification,

collection, analysis, dissemination and use of information for the purpose of

improving decision making related to the identification and solution of problems

and opportunities in marketing. Thus marketing research links the consumers to

marketers by providing information that can be used in making marketing

decisions. As marketing research is a systematic inquiry, it involves systematic

planning at all the stages. Each stage of the procedure is methodologically sound,



well documented and as much as possible planned. Thus the following six steps of

marketing research process have been carried out in this study which is systematic

and conceptually sound:

Problem Identification

Approach to the problem

Research Design

Fieldwork or Data collection

Data Preparation and Analysis

Report preparation and presentation 2

5.2 Problem Identification

The growth of Internet and its user base in recent years has been truly

phenomenal. Despite the phenomenal growth of the Internet over the past few

years, the vast potential of conducting business over the Internet remains

largely untapped. This study is designed to provide suggestions to online

marketers and e-vendors regarding barriers to online shopping. There are

several questions that need to be answered so that internet users do online

shopping without any risk fear or lack of trust. Moreover demographic

characteristics like income and education are also anticipated to influence

online purchase decision. This study was undertaken to provide solution to

the above mentioned problems.



5.3 Development of an approach to the problem

Development of an approach to the problem includes formulating an objective or

theoretical framework, analytical models, research questions and hypothesis and

identifying the information needed3.

Present study basically focuses on trust and risk factor acting as barriers to online

shopping. The study also aims to explore the product categories people intend to

spend, risk perceptions in conventional shopping versus online shopping and other

reasons for reluctance to online shopping apart from perceived risk and lack of

trust.

5.3.1 Rational of the study

The literature review has revealed that most of the studies have mainly

concentrated on trust and risk independently. There have been hardly any

studies which take into account the relationship between perceived risk and

trust. Since the concept of trust is intimately related to (and often confused

with) the concept of risk, an understanding of trust that does not examine its

relationships with risk is incomplete. Whether and how trust affects perceived

risk (or vice versa) in the Internet shopping context is still very much an open

issue.



Moreover, on detailed search the researchers have not found any substantial

literature available in the Indian context delving on perceived risk and the various

components of the same. From literature study it can be seen that all these studies

have been done in non –Indian context. Through this research, the researchers

expect to find the different ways in which shoppers perceive risk, which is

understood as a function of culture, in Indian context. Moreover the relationship

between intension to shop and perceived risk will also be studied i.e. in what

product categories people intend to spend more and how much amount they intend

to spend.

Under the above context, I realize the need for an extensive and intensive

study to analysis the study of relationship between perceived risk and trust

and their interactions.

5.3.2 Objectives of the study

To explore whether and how trust affects perceived risk in the online

shopping context and vice versa.

To determine the different perceived risks involved in online shopping in

Indian context.

To understand elements of each perceived risk in online shopping.



To understand risk perceptions in conventional shopping versus online

shopping.

To determine in what product categories people intend to spend more in

case of online shopping.

To find out reasons for reluctance to online shopping.

5.3.3 Hypothesis of the study

Considering the above objectives the following hypothesis was tested

There is no relationship between Income level of people and trust in

online shopping.

Trust in online shopping is independent of Education level of

customers.

Shopping convenience in online shopping does not attract younger and

older customers.

The nature of product does not affect the acceptance of online

shopping.

5.3.4 Area of Information

With the above objectives in mind the following information was soughted.



Demographics:

Age

Gender

Occupation

Marital status

Income

Family type

Ownership of durables, computer and internet line at home

Internet usage

Place of using Internet:

At a cyber cafe

Office

Home

School/College/Institute

Friends / Relatives/Neighbor’s

Through Mobile

Purpose of Internet Usage:

Communications

Interactive communication

Information search



Online bill payment

On-line shopping

Pattern of internet usage

Average per day hours for which internet is used

Types of sites visited

Frequency of online visit

Online shopping – usage

Category of products/ services purchased through online shopping

Highest amount ever spent on online shopping

Average per month amount spent on online shopping

Online shopping – purchase behavior

o From information gathering to final purchase

Places from where online shopping is done

Benefits derived from online shopping

Different Perceived Risk

Financial risk

Time risk

Social risk

Physical risk



Psychological risk

Source risk

Privacy risk

Intention to purchase

Intention to purchase

o Type of product/brand

o Intention to recommend

5.4 Research Design

A research design is a framework or blueprint for conducting the scientific

inquiry. It details the procedures necessary for obtaining the information needed to

structured or solve marketing research problem4 . The purpose of the research

design is to provide the plan for answering the research question or testing the

hypothesis. In other words, a basic aspect of research design is to set up the

research so as to allow logical inferences to be drawn. Research design may be

broadly classified as exploratory or conclusive (Descriptive research and Causal

research).

The research design for this study is descriptive in nature and both qualitative and

quantitative research methodologies are used. In this two stage research design,



first stage of the research design is exploratory. Output of the exploratory is used

in the second stage of the research. Qualitative output was used for the

formulation of questionnaire especially for item construction for the scale to

measure risk and trust. Semi structured questionnaire was used for the second

stage quantitative research. A semi structured questionnaire was designed and was

pre-tested before using as a final instrument for collecting the data.

5.4.1 Scope of the Study

The study was confined to Gujarat state which has 5 geographic regions namely

North Gujarat, South Gujarat, Central Gujarat, Saurashtra and Kutch. Since they

are geographically distant, they are also socio-economic difference. A pilot study

was conducted in Ahmedabad (Central Gujarat), Mehasana (North Gujarat), South

Gujarat (Vapi), Jamnagar (Saurashtra), and Kutch (Gandhidham) for the

formulation of questionnaire for item construction for the scale to measure risk

and trust. Data through survey was collected for this study from Ahmedabad and

Anand (Central Gujarat), Mehasana and Patan (North Gujarat), Surat and Vapi

(South Gujarat), Rajkot, Bhavnagar and Jamanager (Saurashtra) and Bhuj and

Adipur (Kutch) during the period of June 2010-to December -2010



5.4.2 Primary and Secondary Data

Secondary data was collected in form of literature reviewed from various national

and international Journals, Websites, Books, Online Databases and Reports. The

Major International Journals reviewed are Journal of Advertising Research,

Marketing Management Journal, Journal of Consumer Research, Journal of

Management Information Systems, Journal of Interactive Marketing, Journal of

Service Industry Management, Marketing Intelligence and Planning, International

Journal of Retail & Distribution Management, TQM and Business Excellence,

Journal of Fashion Marketing and Management, International Journal of Research

in Marketing, Industrial Management & Data Systems, Journal of Internet

Commerce, Communication World, Journal of Marketing Research, Journal of

Business Research, Marketing and Technology, Journal of Interactive Marketing,

European Journal of Marketing, Journal of Organizational and End User

Computing, Journal of Marketing Management, International Journal of

Information Management, Journal of Marketing, Service Journal, Marketing

Management Journal, Business and Society Review, Communications of the

ACM, Journal of Marketing, Journal of Consumer Behavior, International Journal

of Bank Marketing, Journal of Computer Mediated Communication, Information

Technology and Management, Journal of Applied Psychology, Journal of

Consumer Marketing, Journal of services marketing, Family and Consumer

Sciences Research Journal, Journal of Business ethics, International Marketing



Review, International Journal of Electronic Commerce, Information Management

& Computer Security, Journal of Food Products Marketing, Academy of

Management Review, Information Systems Research, Management Decision,

Journal of Consumer Affairs, International Journal of Service Industry

Management, Journal of Computer Mediated Communication, Human Systems

and Management, American Psychologist, Journal of Internet Commerce, Journal

of Personality and Social Psychology, Journal of International Consumer

Marketing, Journal of International Consumer Marketing, Journal of the Academy

of Marketing Science, Multinational Business Review, Sloan Management

Review, Marketing Health Services, Journal of Interactive Marketing, Journal of

the Association for Information Systems. Primary data was collected using a semi

structured questionnaire. After scanning various secondary data sources, primary

data was collected to meet the objectives of the present study.

5.4.3 Sampling Plan

Sampling is defined as the selection of some part of an aggregate or totality on the

basis of which a judgment or inference about the aggregate or totality is made5. In

other words, it is the process of obtaining information about an entire population

by examining only a part of it. A sampling design is a definite plan for obtaining a

sample from the sampling frame. It refers to the technique or the procedure the

researcher would adopt in selecting some sampling units from which inferences



about the population is drawn6. Sampling design incorporates population and

sampling unit, determining the sampling techniques and sampling size.

The Population

A population is the aggregate of all the elements that share some common set of

characteristics and that comprise the universe for the purpose of the marketing

research problem. In other words, population represents the total set of things

under consideration about which some information is desired7.

The state of Gujarat has 5 geography regions namely North Gujarat, South

Gujarat, Central Gujarat, Saurashtra and Kutch. The study is carried out in ten

cities in the state of Gujarat from different cultural regions. Moreover only urban

dwellers are covered here as the internet penetration in rural area is almost

negligible. Thus the population for the present study is all the urban internet users

of the ten selected cities.

Sampling Unit

A sampling unit is an element, or a unit containing the element, that is available

for selection at some stage of the sampling process8. From the above population,

all the internet users who are either aware of online shopping or have done online



shopping were identified as sampling unit for the purpose of the study. Those

internet users who had no idea or were not aware of online shopping were

excluded from the study.

Sampling techniques

Sampling techniques may be broadly classified as non-probability and probability.

Non-probability relies on the personal judgment of the researcher rather than

chance to select sample elements. In probability sampling, sampling units are

selected by chance. Commonly used non-probability sampling techniques are

Convenience Sampling, Judgment Sampling, Quota Sampling, and Snowball

Sampling. Probability sampling includes simple random sampling, Systematic

Sampling, Stratified Sampling, Cluster Sampling, and other sampling techniques9.

In the present study, Quota sampling has been adopted. Quota sampling may be

viewed as two-stage restricted judgmental sampling. The first stage consists of

developing control categories, of population elements. To develop these quotas

the researcher lists relevant control characteristics and determines the distribution

of these characteristics in the target population10. In the second stage, sample

elements are selected based on convenience and judgment.

The sample of the present study, represented the population with respect to



demographic dimensions i.e. gender, age, income, and education. Care was taken

to make the sample representative of the actual population.

Size of the Sample

The five cities selected for the exploratory study are Ahmedabad, Mehsana, Vapi,

Jamnagar and Adipur. From each of these cities, four online shoppers’ were

selected for in-depth interviews. In all, 20 in-depth interviews were conducted for

the study.

Table 5.1: City –wise Sample size for in-depth interviews

Region City Number of

DIs (Men)

Number of DIs

(Women)

Central Gujarat Ahmedabad 2 2

North Gujarat Mehasana 2 2

South Gujarat Vapi 2 2

Saurashtra Jamnagar 2 2

Kutch Gandhidham 2 2

The in-depth interview was conducted with the help of guideline. During the

interview, the following themes were explored through open-ended discussion:

Motivations for online shopping

Barriers to online shopping- especially risk associated with online shopping



Amount spent in online shopping

Products purchased through online shopping

The in-depth interviews were recorded, transcribed and content analysed. For

content analysis, each transcript was repeatedly read and a content analysis table

was prepared using Excel sheet. In the Excel sheet, each vertical column

represented one respondent and each horizontal row represented one research

question. The content analysis table helped to map all the respondents

simultaneously, looking for emerging patterns and insights.

From the earlier research work on online marketing and trust in online marketing,

the respondent’s responses were quick and positive. This led to an anticipation of

a sample size of nearly 1520 respondents for the present work. As the work

progressed it was realized that though the initial response rate was net high,

respondents were difficult to come by in numbers and interest to respond. To

avoid poor response due to lack of interest it was decided to limit the sample size

to 650.

Total 650 questionnaires were received out of which 23 were rejected due to

incomplete responses. Thus final valid respondents for the study were 627. The

sample consisted of respondents from the cities selected for the study. City wise

break of respondents are as follows-



Table 5.2: City –wise Sample size for Survey

City Frequency Percent Valid

Percent

Cumulative

Percent

Adipur 100 15.9 15.9 15.9

Ahmed 68 10.8 10.8 26.8

Anand 80 12.8 12.8 39.6

Bhavnag 73 11.6 11.6 51.2

Jamnagar 49 7.8 7.8 59.0

Mehsana 52 8.3 8.3 67.3

Patan 73 11.6 11.6 78.9

Rajkot 26 4.1 4.1 83.1

Surat 77 12.3 12.3 95.4

Vapi 29 4.6 4.6 100.0

Total 627 100.0 100.0

(Source: Data collected from the study)

Adjustments were made in sample size of every city to make it representative of

other demographic dimensions like Gender and Age-groups.



5.4.4 Instrument for data collection

Exploratory research through pilot study was conducted in selected cities. The

objective of the exploratory research is to explore or search through a problem or

situation to provide insights and understanding11. Output of the exploratory is used

for the formulation of questionnaire for item construction for the scale to measure

risk and trust. Survey as an approach to study has advantage of coverage of large

number of dimensions pertaining to the study. For data collection a survey using a

structured questionnaire was used to collect data from respondents. For getting

qualitative information a few open-ended questions were also included in the

questionnaire.

5.5 Fieldwork and Data Collection

Data was collected from ten cities of Gujarat during the period of Jun 2010 to Dec

2010. Data was collected after checking the respondent’s awareness of online

shopping.

5.6 Data Analysis

Data preparation included the editing, coding, transcription, and verification of

data. After editing the data, a number code was assigned to each response to each



question. A data sheet was prepared containing all the variables and responses for

each question in a code form with the help of datasheets.

Analysis of data is the process by which data is converted into useful information.

Raw data as collected from questionnaires cannot be used unless it is processed in

some way to make it amenable to drawing conclusions. For the purpose of

advanced statistical analysis different datasheets were used. The collected data

was then subjected to suitable statistical analysis including

One Way ANOVA - multiple comparison tests

ANOVA or Analysis of Variance is used to compare the means of more than two

populations12. It uncovers the main and interaction effects of classification or

independent variables on one or more dependent variables. ANOVA uses

the F-statistic, which tests if the means of the groups, formed by one independent

variables or a combination of independent variables, are significantly different13.

An F-ratio equal to or less than one indicates that there is no significant difference

between groups and the null hypothesis is correct. If the null hypothesis is correct,

then we conclude that the independent variables did not have an effect on the

dependent variable. However, if the F-test proves the null hypothesis to be wrong,

multiple comparison tests are used to further explore the specific relationships

among different groups.



The criterion that is used for accepting or rejecting a null hypothesis is called

significance of p-value14. A p-value of 0.05 means that there is only 5% chance

that you would be wrong in concluding that the populations are different or 95%

confident of making a right decision. Rejection of the null hypothesis in ANOVA

only tells us that all population means are not equal. Multiple comparison are used

to assess which group means differ from which other, once the overall F-test

shows that at least one difference exists 15. Many tests are listed under “Post Hoc”

in SPSS. Post Hoc analysis involves hunting through data for some significance16.

Tukey HSD (honestly significant difference) test is one of the most conservative

and commonly used tests17.

Here ANOVA is used to find significant relations between

Perceived reasons of purchasing online by online buyers and their

demographic characteristics.

Criteria for choosing product online by online buyers and their

demographic characteristics.

Trust in online shopping by online buyers and their demographic

characteristics.



Chi-square test

Chi Square is one of the very popular methods for testing hypotheses on discrete

data18. Chi-square is used for finding significant relations19.It is used to determine

if categorical data shows dependency or the two classifications are independent.

This test can also be used to make comparisons between theoretical populations

and actual data when categories are used. A small chi-square statistic indicates

that the null hypothesis is correct and that the two variables are independent of

each other20.

Here Chi-Square is used to find significant relations between

Products/Services bought online by online buyers and their demographic

characteristics

Normally adopted payment mode and their demographic characteristics

Types of online buyers and their demographic characteristics

Factor Analysis

Factor analysis is a statistical approach that can be used to analyze

interrelationships among a large number of variables and to explain these

variables in terms of their common underlying dimensions (factors)21. The

objective is to find a way of condensing the information contained in a number of



original variables into a smaller set of variables (factors) with a minimal loss of

information22.

Meanings of terminologies related with factor analysis are given below:

Bartlett’s test of sphericity is significant if its associated probability is less

than 0.05.

Kaiser-Meyer-Olkin (KMO) measures the sampling adequacy which

should be greater than 0.5 for a statistical factor analysis to proceed.

Screen plot are used to decide the number of underlying factors after

extraction. Screen plot is a graphical presentation of eigenvalues of all of

the factors initially considered for extraction23.

Community gives the variance accounted for a particular variable by all the

factors24.

Varimax is the most commonly used rotation technique.

The Cronbach alpha coefficient is an indicator of internal consistency of

the scale25. A high value of Cronback alpha above 0.70 can be used as a

reasonable test of scale reliability.

Factor analysis is used here for the reduction of elements of online risk into the

factors.



5.7 Report Preparation and Presentation

Reports help to present the study in a systematic manner. Research problem,

current scenario and future directions can be effectively presented in form of

report. A Research reports typically contain Literature Survey and identification

of knowledge Gaps, Nature and Scope of study, Methodology, analysis of data,

findings and conclusion. This report is also organized on a similar framework. The

report is organized in eight chapters.



References

1. Naresh K. Malhotra,, Marketing Research – An Applied Orientation, Pearson Education

Asia, 2001, p.83 2. K.R. Sharma, Research Methodology national Publishing House, New Delhi, p.40. 3. C.R. Kothari, Research Methodology – Methods & Techniques, New Age International

Publishers, New Delhi, 2004, p.54. 4. Naresh K. Malhotra,, Marketing Research – An Applied Orientation, Pearson Education

Asia, 2001, p.328

5. K.R. Sharma, Research Methodology national Publishing House, New Delhi, p.40 6. Naresh K. Malhotra,, Marketing Research – An Applied Orientation, Pearson Education

Asia, 2001, p.330 7. Naresh K. Malhotra,, Marketing Research – An Applied Orientation, Pearson Education

Asia, 2001, p.334

8. Naresh K. Malhotra,, Marketing Research – An Applied Orientation, Pearson Education Asia, 2001, p.336

9. Alvin C. Burns and Ronald F. Bush, Marketing Research, Prentice-Hall International,

INC, New Jersey, 1998, p.379 10. Naresh K. Malhotra,, Marketing Research – An Applied Orientation, Pearson Education

Asia, 2001, p.336 11. K.R. Sharma, Research Methodology national Publishing House, New Delhi, p.40 12. Gaur A.S and Gaur S.S (2006) , Statistical Methods for Practice and Research : A guide

to data analysis using SPSS, Sage Publications 13. Ibid, 68 14. Ibid, 35 15. Ibid, 70 16. Gupta, S.L. and Gupta, H (2011). , SPSS 17.0 for researchers, International Book

House Pvt. Ltd 17. Gaur A.S and Gaur S.S (2006) , Statistical Methods for Practice and Research : A guide

to data analysis using SPSS, Sage Publications



18. Ibid 19. Gupta, S.L. and Gupta, H (2011). , SPSS 17.0 for researchers, International Book

House Pvt. Ltd 20. Gaur A.S and Gaur S.S (2006) , Statistical Methods for Practice and Research : A guide

to data analysis using SPSS, Sage Publications, 92 21. Gupta, S.L. and Gupta, H (2011). , SPSS 17.0 for researchers, International Book

House Pvt. Ltd 22. Gupta, S.L. and Gupta, H (2011). , SPSS 17.0 for researchers, International Book

House Pvt. Ltd, 142 23. Gaur A.S and Gaur S.S (2006) , Statistical Methods for Practice and Research : A guide

to data analysis using SPSS, Sage Publications, 92 24. Gaur A.S and Gaur S.S (2006) , Statistical Methods for Practice and Research : A guide

to data analysis using SPSS, Sage Publications,, 133 25. Ibid, 92

Documents

Ch5 final Mod-Final-109-133 - Information and Library …shodhganga.inflibnet.ac.in/bitstream/10603/7328/13/13... · · 2015-12-04Fieldwork or Data collection Data Preparation and