IMPACT OF DEMOGRAPHIC FACTORS OF CONSUMERS ON ONLINE SHOPPING BEHAVIOUR: A STUDY OF CONSUMERS IN INDIA

-Dahiya Richa Associate Professor cum Director (o/c), JK Business School, Damdama Lake road, Gurgaon

INTRODUCTION

On-line shopping is a late marvel in the field of E-Commerce and is most likely going to be the fate of shopping on the planet. The top two of the top 10 products bought on the Net by online buyers in India are train tickets (53 per cent) and air tickets (45 per cent). Although India is underpinned by a paid pace of urbanization, a robust economic expansion and rising spending power hold huge potential in this field. The bigger part of the organizations are running their on-line entries to offer their items/administrations on-line. In spite of the fact that internet shopping is exceptionally normal outside India, its development in Indian Market, which is a substantial and key customer business, is still not in accordance with the worldwide business sector.

Early studies showed Internet buyers behaviour to be influenced by gender, marital status, residential location, age, education, and household income were frequently found to be important predictors of Internet purchasing (Fram & Grady, 1997; Kunz, 1997; Mehta & Sivadas, 1995; Sultan & Henrichs, 2000). The research in hand uses Qualitative and Quantitative examination routines to concentrate on the effect of Demographic elements of buyers on-line shopping parameters like fulfilment of their shopping needs and makes an attempt to study the impact of a customer’ demographic factors on its customer satisfaction which he derives shopping online.

OBJECTIVE

Consumer behaviour is the study of the processes involved when an individual selects, purchases, uses or disposes of products, services, ideas, or experiences to satisfy needs and desires (Solomon, 1998). All together for the Internet to extend as a retail channel, it is critical to comprehend the consumer’s attitude, intent and behaviour in light of the online buying experience. The objective of the study is to uncover that on-line shopping in India is altogether influenced by different Demographic variables like age, sexual orientation, conjugal status, family size and pay. The findings of the study could be further utilized by the scientists and professionals for leading future studies in the comparative range.

DATA COLLECTION

A survey among 150 internet users, including both users and non-users of online shopping, was carried out to understand why some purchase online while others do not. The results suggested that convenience and saving of time drive Indian consumers to shop online; while security and privacy concerns dissuade them from doing so.

The developed hypothesis studies the impact of the considered demographic variables on the customer satisfaction. However rather than checking the impact of one independent variable on one dependent variable, we can also do a comparative analysis like-

H2: Males are more satisfied with online shopping as compared to females.

The same can be done between married/unmarried etcetera.

RESEARCH HYPOTHESES

H1: Demographics factors of consumers significantly impact the online shopping behaviour of the consumers.

H1.1: Age of consumer significantly impacts online shopping parameters of consumer.

H1.2: Gender of consumer significantly impacts online shopping parameters of consumer.

H1.3: Marital Status of consumer significantly impacts online shopping parameters of consumer.

H1.4: Income of consumer significantly impacts online shopping parameters of consumer.

H1.5: Family Size of consumer significantly impacts online shopping parameters of consumer.

H1.6: Education of consumer significantly impacts online shopping parameters of consumer.

H1.7: Ability to use internet of consumer significantly impacts online shopping parameters of consumer

MAJOR LEARNINGS

STATISTICAL

Moreover the study being exploratory gave insights about-:

1. Importance of reviewing existing literature which helps in validation and extraction of the important variables and factors and helps in formulation of hypotheses.

2. A Cross-sectional (at a point of time) survey of respondents was done using a structured questionnaire for descriptive phase.

3. The use of judgemental and snowball sampling although at prima facie was to have a convenience in the data collection but the study being done in 2012 where the total e-commerce market stood at 40,300 Crore Rs(approx. one-third of current market cap.) and collecting data from credit card users involved using some references and hence judgemental sampling. However such sampling method involves higher chances of bias on part of researcher and also reduces the applicability of collected data further studies.

4. Data was collected from primary as well as secondary sources. Primary sources were in-depth interviews and questionnaires whereas secondary sources were journals, newspapers, national and international publications, internet, personal books and libraries. This highlights the importance of both of such data. While primary data was used in collecting the sample and test the hypotheses, secondary data was used in formulating such hypotheses and understanding the traits of population better.

Some more insights about the tests used are as follows-:

SAMPLE SIZE The sample size for questionnaire was 598. 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. The sample for questionnaire was collected from Delhi, Mumbai, Chennai, Hyderabad and

Bangalore. The sample was mainly collected from metros and big cities assuming the high Internet diffusion rate. TABLE 1- SAMPLE SIZE FOR QUESTIONNAIRE

Survey Respondents

City No. of Respondents

Delhi 137

Mumbai 123

Chennai 104

Bangalore 119 Hyderabad 115 Total 598

SAMPLINGTECHNIQUE Judgmental and snowball sampling were used. 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). Judgemental 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.

STATISTICAL TOOL To meet the research objectives and to test proposed hypotheses, the data analysis technique used in the study was ANOVA.

INFERENCES & LEARNINGS (NON-STATISTICAL)

The findings of the study can be used by specialists in relooking or redesigning their strategies for online-shopping. Some of the major practical implications being-

1. Online sites ought to give careful consideration to the female portions as results demonstrate that females shop more in web shopping when contrasted with men. So organizations ought to devise the approaches and procedures to draw in more number of females in this fragment in future moreover.

2. The existing online sites like Amazon, Flipkart needn’t explicitly have a separate advertisement for people of different age groups(say teen vs adults) as age doesn’t has any significant impact on the overall intention to shop online. They can be targeted with a single advertisement leading in cost savings.

3. The findings show that marital status does not influence any of online shopping parameters. Such a finding can be because of the nascent stage of online shopping in India, due to which single/married people are mainly using Internet for their specific needs. Other researches have shown different patterns of shopping by single and married people and the evolution of online shopping in the future might witness the same trend.

4. The earlier studies found Income to be significant factor affecting a customer’ online shopping behaviour, however the same doesn’t holds true as the present study shows that income doesn’t affects the online shopping behaviour. Such a change shows the willingness on customer’ side towards online shopping over the traditional medium.

5. Family size and ability to use internet are some of the factors directly related to the online shopping behaviour and the study doesn’t contributes, rather affirms the behaviour of such variables.

However the above stated has to be taken with a pinch of salt, the results hold true predominantly for metropolitan cities, and on a sample having specific traits. So if the target group for a manager is a segment belonging to this population then the findings of this paper can be applied. In case such findings are applied to any target group of tier II and III cities, the results may not hold true.

LIMITATIONS

1. The study considers only those people who have credit cards while nearly 60 % of all online shopping done in India is via Cash on Delivery or COD and 28% by debit card mode and there might be a significant difference in the behaviour of these persons who form majority of the population.

2. The sample comprises of people whose minimum qualification was at least Graduation, however the % of graduated population in tier II and III cities stands between 7-11%. The behaviour depicted by comparatively less educated population might significantly vary.

3. The primary cities considered into study are metropolitan, however with more internet penetration in Tier II and III cities, the findings of this study might not be directly applicable in such areas and a fresh research needs to be undertaken.

Moreover the extensive use of judgement and snowball sampling makes the data collection extensively convenient and the sample focus on very specific traits making it less applicable if customers having one or more different traits are targeted.

ALTERNATIVE TOOL SUGGESTION

FINDING FROM THE SUGGESTED TOOL

DISCUSSION ON FINDINGS

LESSON LEARNT