Thesis PPT

A Study of Consumer Behavior Patterns in On-line Shopping

Thesis Submitted ByRicha Malik Under the supervision ofDr. (Mrs.) SudeshProfessor, University school of management,Kurukshetra.

Roadmap to Presentation

• Introduction

• Research objectives

• Research methodology

• Data analysis and interpretation

• Discussion and Conclusions

Introduction

• On-line shopping is the process consumers go through to

purchase products or services over the Internet.

• Online shopping behaviour (Internet shopping or buying

behaviour) refers to the process of purchasing products or

services via the Internet. The process consists of five

steps similar to those associated with traditional shopping

behaviour (Liang and Lai 2000).

Objectives of the study

Objectives of the study

1. To identify the variables influencing behaviour of consumers towards on-line shopping

2. To identify the factors influencing behaviour of consumers towards on-line shopping

3. To study the impact of identified variables under each category of factors on the on-line shopping

4. To study the impact of factors identified on the on-line shopping

5. To develop a comprehensive model that incorporates all the relevant variables and factors and their impact on online shopping

Research methodology

Research design

• Exploratory

- Review of existing literature

- In-depth interview • Descriptive

-Questionnaires

Data collection methods

• Primary sources

- In-depth interviews

- Questionnaires

• Secondary sources

- Literature review

SAMPLING DESIGN

• Sample size for – In-depth interview - 41 – Questionnaire - 598.

• Final questionnaire was pilot-tested on a sample of 35 to ensure the validity of the survey instrument. However, post elimination of incomplete responses, unreturned questionnaire and invalid answers, the final sample size used for analysis was 580.

Sampling Technique

• In the present study non-probabilistic sampling technique was used. Judgmental and snowball sampling technique were used in respondent selection for in-depth interviews and questionnaire.

• Initial set of respondents was selected on the basis of judgemental sampling. Subsequently additional units were obtained on the basis of information given by initial sample units and then further referrals were taken from those selected in the sample. In this way sample was grown by adding more and more referral-based respondents until it reached the limiting number (150/city).

CONTD…

• In the present study Judgement sampling was based on the following parameters:– The sample comprised of people who have done online

shopping– Only those people having credit cards were part of the

sample– The sample comprised of people whose minimum

qualification was at least Graduation– The sample was taken from metropolitan cities

assuming high internet diffusion rate

QUESTIONNAIRE DESIGN

• The questionnaire design was mainly based on the review of literature and the results of in-depth interviews and pilot study.

• The questionnaire was further checked for the convergent and discriminant validity and reliability.

Data analysis techniques

• Factor analysis• One –way ANOVA• Correlation• Multiple regressions

Data analysis and Interpretation

Categories Of Factors And Variables Under Each Factor Category Identified From Exploratory Study

S# Category of factor Variables under factor category

1 Demographic factor Age, Gender, marital status, income/salary, family size, education, ability to use internet

2 Psychographics factor Innovative, enjoyment, convenience, interaction with people, touch and feel

3 Online shopping feature and policies

Promotion, delivery policy, product return policy, detailed information of product, option of comparison,

4 Technological factor Quality, representative ness of product, value for money

5 Security factor Safety, privacy

Analysis And Interpretation For Descriptive Phase

S# Category Percentage

1 Airline/train reservations 81%

2 Banking & other financial

services

63%

3 Books/Magazines/

membership of library, news

dailies

33%

4 Software/Hardware/DVD/CD 16%

5 Dresses/Apparels/

Footwear/Jewellery

3%

6 Electronics/Mobile phones 30%

LIST OF CATEGORIES SHOPPED ONLINE

Consumers’ Response Variations For Online Shopping Across Gender

HYPOTHESIS

NO.

OUTPUT

VARIABLE

MEAN VALUE Mean Value (Total)

ANOVA RESULT

F (Sig.)

Male

(N=331)

Female

(N=249)

H3.2.1 Satisfaction with online shopping

3.71 3.75 3.72 .007 (.936)

H3.2.2 Future purchase on Internet shopping

3.8 3.5 3.67 .759 (.397)

H3.2.3 Frequency of online shopping

1.43 2.25 1.78 3.3 (.08)

H3.2.4 Number of items purchased on Internet shopping

2.43 2.5 2.46 .020 (.888)

H3.2.5 Overall spend on Internet shopping

2.57 3.5 2.97 1.411 (.252)

Consumers’ Response Variations For Online Shopping Across Different Family Sizes

HYPOTHESISNO.

OUTPUTVARIABLE

MEAN VALUE Mean Total

ANOVA RESULTF (Significance)

Nuclear family(N=193)

Family with two children(N=257)

ExtendedFamily(N=130)


3.66 3.62 4 3.72 .328 (.725)


3.66 3.75 3.75 3.72 .037 (.963)


1.5 1.375 2.25 1.61 1.595 (.236)


2 2.75 2.5 2.44 1.389 (.280)


1.83 3.5 2.75 2.77 3.030 (.078)

Relationship Between Online Shopping Variables And Enjoyment As One Of The Variables Of Psychographics Factor

Hypothesis

No.

Output variable Correlation coefficient

Significance Hypothesis testing results


.284 .253 Hypothesis rejected








.508 .031 Hypothesis not rejected

Relationship Between Online Shopping Variables And Convenience As One Of The Variables Of Psychographics Factor

Hypothesis

No.













Relationship Between Online Shopping Variables And Interaction With Others As One Of The Variables Of Psychographics Factor

Hypothesis

No.




-.161 .525 Hypothesis rejected






-.468 .050 Hypothesis not rejected

H1.4.5 Overall spend on net shopping


Relationship Between Online Shopping Variables And Touch And Feel As One Of The Variables Of Psychographics Factor

Hypothesis

No.













Relationship Between Online Shopping Variables And Comparability Of Product As One Of The Variables Of Online Shopping Features

Hypothesis

No.













Relationship Between Online Shopping Variables And Quality Of Product As One Of The Variables Of Technological Factor

Hypothesis

No.













Relationship Between Online Shopping Variables And Representative ness Of Pictures And Colours As One Of The Variables Of Technological Factor

Hypothesis

No.













Relationship Between Online Shopping Variables And Security As One Of The Variables Of Safety Factor

Hypothesis

No.













Relationship Between Online Shopping Variables And Privacy As One Of The Variables Of Safety Factor

Hypothesis

No.













Analysis Results

Dependent variable Independent variable Direction/relationCustomer satisfaction with online shopping

a) Securityb) Qualityc) Touch and feel factord) Option of comparisone) Privacy

PositivePositiveNegativePositivePositive

Future online purchase a) Customer satisfactionb) Qualityc) Touch and feel factor

PositivePositiveNegative

Frequency of online purchase None ---------

Number of Products/Items purchased

a) Convenienceb) Representative of pictures

and colours c) Interaction with people

PositivePositiveNegative

Total Spend on online purchase

a) Enjoymentb) Touch and feel factor

PositiveNegative

Results Of Regression Analysis

Dependent variable Independent variable Beta value (Significance) R2

Customer satisfaction with online shopping

a) Securityb) Touch and feel

factor

.646(.001)-.490(.009)

.606

Future online purchase

a) Customer satisfaction

.764(.000) .584

Frequency of online purchase

------

------ -------

Quantity of products/Items purchased

a) Convenienceb) Representative of

pictures and colours

c) Interaction with people

.577(.012)-.331(.139)-.137(.532)

.454

Total Spend on online purchase -------- -------- --------

Comprehensive model

Safety Factor

Security Customer satisfaction with online shopping

Psychographic Factor

Touch and feel factor

Interaction with people

Convenience

Technological Factor

Representative of quality

Future online purchase

Number of items purchased in online shopping

Final model

Online Shopping

Security Touch and feel factor

Interaction with people

Representative of pictures and colorsConvenience

If we assume all the output variables to be converging into one broad factor of online shopping, the final model could be interpreted as following:

PRACTICAL/ MANAGERIAL IMPLICATIONS

• Online retailers should focus on better positioning and representation of their products in online shopping.

• Websites/e-tailors should also ensure that all the relevant details regarding the quality and features should be provided to the online shoppers on the website.

• Customer shop through online shopping because of time and effort saving, hence the online retailers should design their website in such a way that the customers can reach out to his/her desired product in the minimum time.

• To save time and effort of the customers the online retailers should also give an option to the customers to store and compare their choices before the actual purchase.

• Online website should pay more attention to the female segments as results prove that females shop more in online shopping as compared to men. So companies should devise the policies and strategies to attract more number of people in this segment in future also.

• Online website need to ensure that security and privacy policies are appropriately defined, implemented, and communicated to the relevant stakeholder.

• Online shopping companies could also look into the possibility of spreading and promoting security and privacy related information on the Internet.

• Delivery policy of the online product should also include a defined trial period to assure that the customer doesn’t miss the touch and feel experience.

• Online retailers should also look into the possibility of running call centres which could ensure that the customer get a chance to formally interact with the other party before the actual purchase.

Continued…………

THEORETICAL IMPLICATIONS

• The study fills the literature gap between the past studies and present research by building a comprehensive model for online shopping.

• The study defines measurement parameters for online shopping.

• This is a unique study as it studied actual as well as post-purchase behaviour of the online shoppers.

• This is one of the initial studies done on online shopping in India as the concept of online shopping is quite new in India and none of the studies on online shopping are done so far on such a large scale in India.

• This is one of the important studies on online shopping in Indian context because it has included people from diverse backgrounds from different cities in India. It includes the random sample of individuals from major cities of India, which are representatives of whole population of India.

• This study finds unanimity amongst diversity by including people of different age groups falling under different income segments with difference in attitude and buying behaviour.

LIMITATIONS

• The study has few limitations like few Indian studies were available in Indian context so literature review pertains to foreign countries.

• Data has been collected from metro cities assuming high internet diffusion rate. And small cities and rural areas were not a part of sample.

• A cross-sectional study was done on the selected sample. Therefore results need to be tested over the time to check whether the same variables affect the online shopping in future or not.

• Judgemental sampling was used in the study. Therefore care must be taken while projecting the results of the study.

• Time and resources were also one of the limiting factors.

• Questionnaire technique was used. some hidden behavioural perspectives remained untouched and unnoticed in that case.

FUTURE RESEARCH DIRECTIONS

• Replication in Other Settings (Generalization)

• Need to Study Other Types of online shopping

• Need to Study Other Concepts and Relationships

Documents

Thesis PPT