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July 2015

 

Acceptance of Online Shopping in West Bengal: Customer’s Perception

 

 

1)      Indrajit Ghosal

Asst. Professor cum Author

Institute of Management Study (IMS), Kolkata

MCA, B.Sc(IT), EDAST, ACSE(IBM)

 

 

 

 

2)      Debansu Chatterjee

IMS Research Scholar

Faculty of EDI (EDI-Entrepreneurship Development Institute, Govt. of India)

 

3)      Meghdoot Ghosh

Institute of Management Study, Kolkata

Asst. Professor

MBA, UGC (NET), PhD (Enrolled)

                                               

Abstract:

Online shopping is a well-known trend around the world. West Bengal is not so far behind. A good number of online shopping portals are getting launched. The present online market scenario and behaviors among the internet users of West Bengal are presented in the study. The reasons and inhibitions are also analyzed. A proposal to the online shop owners has also been given at the end of this study. This research study investigated the preferences influencing the usage pattern of Online Shopping in West Bengal, India. This research study would also help in understanding various reasons for this resistance (reluctance) and would be useful for organizations in formulating strategies aimed at increasing the overall usage of the technology. From this empirical research, first, we discussed the acceptance of the technology from the consumer perception and then their effect on consumers' buying behavior in online shopping decision-making in west Bengal.

 

Keywords: Online Shopping, E-commerce, E-business, E-consumers, West Bengal.

I. Introduction

 

The whole world has already been converted into a virtual world. People, institutions and organizations; all are doing their work virtually. The most impactful sector was the business sector. For the development of the business in the virtual world, e-commerce was established. E-commerce covers the range of online business activities for products and services, both business-to-business and business-to-consumer, through the internet. The e-commerce has already created massive differences in the whole world. The actual concept of globalization is achieved through e-commerce. People can buy and sell anything from anywhere in this world through e-commerce sites.

According to the internetlivestats.com, 40.4% of the overall population of this world is using internet till July, 2014. In 2013, the percentage was 37.9% [2]. So, it has been clear that the number of internet users is increasing day by day. There is no chance that the growth will decrease. As a matter of fact, the internet users are the ultimate target customers for the online shops.

1.1 Internet in India

The E-commerce Industry in India has come a long way since its early days. The market has matured and new players have entered the market space. In the present dynamic scenario, e-commerce market in the B2C space is growing in demand as well as in the array of services. According to TOI article ("With 243 million," 2013), internet penetration in India may not have crossed 16% of the population, but that’s enough to reach a number which is approximately 10 times the population of Australia. The report published by Internet and Mobile Association of India (IMAI) and Indian Market Research Bureau (IMRB) estimates 243 million internet users in the country by June 2014, overtaking the US as the world's second largest internet base after China.

In the beginning of the e-commerce in India, payment issue was a big impediment for the consumers to shop online. The only valid and trustworthy option was Cash-on-delivery option. A payment gateway is an e-commerce application service provider service that authorizes credit card payments for e-businesses, online retailers, bricks and clicks, or traditional brick and mortar. A online payment gateway that provided different facilities like RTG, IFSC for online transaction and VISA, MasterCard ,Secure Code and J/Secure by JCB along with Card Verification Value, and It is the equivalent of a physical point of sale terminal located in most retail outlets. Payment gateways protect credit card details by encrypting sensitive information, such as credit card numbers, to ensure that information is passed securely between the customer and the merchant and also between merchant and the payment processor. A payment gateway facilitates the transfer of information between a payment portal (such as a website, mobile phone or interactive voice response service) and the Front End Processor or acquiring bank.

Now the consumers who are shopping online or getting involved in any kinds of online transaction can use their debit/credit card. As one can say that the online transaction scenario has been improved in West Bengal, India in recent times.

All the researchers have pointed out to the direction that what measures should be taken to make things convenient for the consumers. Online sellers have been trying to make things easier for the consumers. Various e-commerce sites are launched. The product lines are getting rich. Based on primary data and previous studies, major dimensions are identified and those which have significant impact on consumers' decision-making are empirically tested and proposed, what risk factors from the overall process of B2C may really cause consumers' perceived risks are examined and identified the dimensions of perceived risks which significantly influenced consumers' buying behavior in the overall process of B2C.

In online shopping because of existence of countless Internet vendors globally, the importance of dimensions of consumers' perceived risk to B2C e-commerce further increases. Such a perception is likely to become a decisive factor in affecting consumers' behavior. This is because consumers perceive higher levels of risk toward B2C e-commerce when they consider security to be insufficient.

Consumer purchasing behavior in study, researcher analyzed all the risk variables related to the overall process of B2C E-Commerce, especially in the phases of searching information before purchasing and after-sale services considering the risk source from the overall process of B2C and current research purposes. So, this paper investigates the present acceptance level of the online consumers of West Bengal. How the consumers are responding to the boom of various online shops? What are the adopters and non-adopters for the online shopping from a buyer’s or consumer’s point of view?

Customer’s Preferences on Online shopping in West Bengal:

Women, particularly women workforce are vital part of buying behavior. It has been found hat Working women are more involved with the purchasing activities. They are more price conscious as compared to the non working married women. It has also been found that working women are more Store loyal than non working married women. In case working women are more quality conscious than non working married women. But non-working unmarried women are quality conscious. This study also prevails that there is a significant difference in buying behavior of working women depending on what type of organization they work. Women are apt to be more involved with purchasing than men, since women have traditionally been the family purchasing agents (Davis 1971, Wilkes 1975) and perceive purchasing as being associated with their role in the family. Woman's role as the family purchasing agent, however, seems to be changing, due primarily to the large increase in the number of working women in recent decades. Therefore, working women has developed as an important segment for the marketers.

Therefore, marketers should consider them with utmost importance.

2. Literature Review

Online shopping is a way of shopping where the buyer can order a product or service by using internet. Virtual world is showing its impact as the days are passing by. We are literally living on the virtual world. As this article is about the acceptance of online shopping in West Bengal, India, some prior researches done on the subject of Online Shopping will be discussed in this segment. A significant amount of research work has been done on Online Shopping. A large group of researchers has pointed out the possibilities of Online Shopping. Others pointed out on the drawbacks and at the same time they provided necessary suggestion to make Online Shopping more useful for the online consumers.

Liu and Arnett (2000) mentioned that the success of the e-commerce site depends on several factors such as Information, service quality, system use, playfulness and system design quality[15]. Online shopping offers to consumers which include ability to shop round the clock at anywhere, to search and browse products, to compare prices, and to make flexible electronic payments (Hoffman et al., 1995; Alba et al., 1997; Peterson et al., 1997; Strauss and Frost, 1999; Shim et al., 2001). According to Ranganathan and Ganapathy (2002), several key dimensions to B2C websites are - Design functionality, Security, Privacy and Information quality [19]. According to Kau, Tang, and Ghose (2003), there are six kinds of online shoppers. They are on-off shopper, comparison shopper, traditional shopper, dual shopper, e-laggard and info surfers. Koo & Ju (2010) suggested that the intention of the consumer’s online shopping depends on their pleasure arousal. Pleasure arousal is occurred by the graphics, color and links of the websites [20]. ‘Customer Satisfaction’ is also one of the prime targets of the online shops. To achieve customer satisfaction, several researches have been done. In those researches, some models have been proposed by the researchers. Alam &Yasin (2010) suggested in their article that website design, reliability, product variety and performances are the antecedents of customer satisfaction [22]. In recent times even used computers are being purchased online. (Bhattacharjee Sarathi Partha,.et al., 2012;) Zhang Lingying, Tan Wojie, Xu yingcong,Tan Genlue (2012) searched the consumers' perceived risk exists in every phase of the overall process of B2C electronic commerce while buying online, so it should be considered, because it influences e-consumers buying behavior. (Kumari Renu,.2013;) Use of technology has opened new doors and opportunities that enable for a more convenient lifestyle today. Variety of products, quicker services and reduced price are the three significant ways in which online shopping influenced people in India and world as a whole. Patna(2013), investigates the relationship between globalization, ecommerce adoption or acceptance that lead to business performance and effectiveness. Through privacy and security policies, developers are doing their best to put an end to this unethical practice. That will pay the way for its success.

3. Objective:

 To study the customer preferences of online shopping in West Bengal.

4. Research Methodology

The study is based on the primary data the author collected from the internet users of West Bengal. A questionnaire was given to the respondents. 100 respondents filled up the questionnaire. On the basis of those responses, the whole analysis has been made. SPSS was used to analyze the data. Descriptive statistics and one sample t-test have been used for the analysis.

4.1 Data Collection Methodology

Data collection methodology involves both secondary and primary data. Primary data is collected using structured undisguised questionnaire. Responses are rated using 5 point Likert Scale, ranging from Totally Disagree (1) to Totally Agree (5). Secondary Data is collected from relevant journals, books, magazines, blogs, and conference proceedings. Depth interviews and focus groups are also conducted for qualitative study.

4.1.1 Sampling Plan

4.1.1a Population:  Customers who use internet across all demographic characteristics.

4.1.1b Sampling Frame: Customer List(s) of selected user who prefers online shopping.

4.1.1c Sample Unit: Customers registered by local internet users.

4.1.1d Sampling Method: Multistage sampling technique (where the different stage units are states/district/divisions/blocks etc) to be used.

4.1.1e Sample Size: 100

4.2 Data Analysis Methodology

The data collected from the survey will be subjected to data cleaning in order to identify missing value, sample characteristics and meet the assumptions of normality. After this, the descriptive analysis will be used to summarize the respondents’ demography.  Factor  analysis will also be employed  in  this  regard  to help  in  reducing the number of  variables  that do not measure  the  constructs  in  this study as perceived by the respondents.  In this case, the component  factor analysis with varimax rotation will therefore be conducted on all the variables to extract factors from the scales of each construct. The researchers will ensure that all items meet the acceptable limit level. Therefore, in this study, all items below 0.50 will not be  retained  and  those having  a  loading  factor  limit of  above 0.50 will  all be  retained. The validity of the instrument will be determined by content  and construct validity. The  construct validity will be determined  through  the  factor  analysis  in which  the Kaiser- Meyer  (KMO)  index  of  sampling  adequacy  and  Bartlett’s  test  of  sphericity  will equally  be  determined. All variables with KMO above .6 will be regarded as valid for this proposed study. 

4.2.1 Empirics

The demographics of the respondent is presented under the 5 attributes i.e. age, gender, qualification, profession, income level. The following table(s) depicts the respondent’s profile and the type of company they have selected for patronizing. As  far  as  age  is  concerned,  almost  50%  of  the  respondents were between  25-34  years  old  (50%) followed by the age group of 35-44 years (25%) . On the other hand, 15 respondents (15%) were 45-54 years of age and 10 respondents (10%) were in the 55-64 years age group. Gender-wise, 56% of the respondents were male and only 44% were female. 50% of the respondents were Graduates followed by 32% higher secondary, Post graduates (12%) and PhD(s) only 6%.

Table 1: Parameter: Age

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

25-34

50

50.0

50.0

50.0

35-44

25

25.0

25.0

75.0

45-54

15

15.0

15.0

90.0

55-64

10

10.0

10.0

100.0

Total

100

100.0

100.0

 

 

Table 2: Parameter: Gender

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Male

56

56.0

56.0

56.0

Female

44

44.0

44.0

100.0

Total

100

100.0

100.0

 

 

 

Table 3: Parameter: Education Qualification

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Higher Secondary

32

32.0

32.0

32.0

Graduate

50

50.0

50.0

82.0

Post Graduate

12

12.0

12.0

94.0

PhD

6

6.0

6.0

100.0

Total

100

100.0

100.0

 

 

Table 4: Parameter: Annual Income

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

< 1,00,000

20

20.0

20.0

20.0

1,00,000-3,00,000

34

34.0

34.0

54.0

3,00,000-6,00,000

28

28.0

28.0

82.0

>6,00,000

18

18.0

18.0

100.0

Total

100

100.0

100.0

 

 

Factor Analysis Results

A total of 100 respondents were surveyed using the questionnaire. The raw data was analyzed using SPSS 17.0 and factor analysis in order to summarize the 15 variables (as each question in Part - 2 (Consumer opinion) of survey questionnaire represent one variable) into smaller sets. Then data was subjected to principal component analysis. Hence,  these  15  variables  were  reduced  to  four  principal  components  through varimax rotation  (Table  6).  Items  with  factor  loadings  of  0.40  or  higher  were  clustered  together  to  form separate constructs,  as  recommended  by Hair  et  al.  (2006). Here, the researcher had considered only those factors whose eigen-values is more than one, as significant. Table 5 indicates that, in the present  test  the Kaiser-Meyer-Olkin  (KMO) measure was  0.671.  Bartlett’s  sphericity  test  also  found  highly significant; Chi-Square = 428.383 with a significance of 0.000 it provide support for validity of the factor analysis of the data set and indicates that, factor analysis is appropriate. 

Table 5: KMO and Bartlett's Test

 

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

.671

Bartlett's Test of Sphericity

Approx. Chi-Square

428.383

 

 

Sig.

.000

 

                                   Table 6: Rotated Component Matrix

 

 

Component

1

2

3

4

1.Online Shopping is compatible with my shopping needs

.906

.108

.154

.145

2.Online Shopping is compatible with my lifestyle

.736

-.095

-.121

-.177

3.I am concerned about the security of Online Shopping

-.086

-.015

.856

-.147

4.I shop online as I can shop according to my convenience

-.085

.831

.171

.119

5.I am concerned about the privacy of Online Shopping

-.062

-.014

.691

.256

6.Using Online Shopping is a sign of modernity

.812

.098

-.155

.144

7.I feel that my credit-card details may be compromised and misused if I shop online

.263

-.133

.798

-.123

8.Online Shopping is easy to use

.648

-.043

.118

.482

9.My friends are using Online Shopping

.837

-.131

.048

-.180

10.Online Shopping is compatible with my lifestyle

.872

.157

.097

.082

11.I shop online as I can save myself from market crowd

-.195

.731

.139

.274

12.I shop online as I can take as much time as I want to decide

.052

.042

-.061

.794

13.I might not get what I ordered through online shopping

.021

.899

-.173

-.066

14.It is hard to judge the quality of merchandise over Internet

.147

.881

-.209

-.055

15.Getting good after sales service is time taking and difficult for online purchase

.323

.570

-.184

-.202

Extraction Method: Principal Component Analysis.

 Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 5 iterations.

 

In the Rotated Component  Matrix table, each number represents the partial correlation coefficient between variable and rotated component. All the variables having factor loadings of greater than .50 for a given component define the component. The following (Table 7) displays the variables constituting the 4 components.

                                                              

Table 7: Components

Sl

Factors

Eigen Value

Variance

Cumulative Variance

1

Shopping Needs

4.217

27.704

27.704

 

Online Shopping is compatible with my shopping needs

 

.906

 

 

Online Shopping is compatible with my lifestyle

 

.736

 

 

Using Online Shopping is a sign of modernity

 

.812

 

 

Online Shopping is easy to use

 

.648

 

 

My friends are using Online Shopping

 

.837

 

 

Online Shopping is compatible with my lifestyle

 

.872

 

2

Convenience & Trust

3.285

21.538

49.243

 

I shop online as I can shop according to my convenience

 

.831

 

 

I shop online as I can save myself from market crowd

 

.731

 

 

I might not get what I ordered through online shopping

 

.899

 

 

It is hard to judge the quality of merchandise over Internet

 

.881

 

3

Security & Risk

2.025

13.959

63.201

 

I am concerned about the security of Online Shopping

 

.856

 

 

I am concerned about the security of Online Shopping

 

.856

 

 

I am concerned about the privacy of Online Shopping

 

.691

 

 

I feel that my credit-card details may be compromised and misused if I shop online

 

.798

 

4

Flexibility

1.197

8.093

71.295

 

I shop online as I can take as much time as I want to decide

 

.794

 

 

5. Conclusion

The derived factors represent different elements of Online Shopping which form the underlying factors from the original 15 scale response items given. Referring to Table 7, it is evident that people associate the use of online shopping with the following factors:

 

(i) Shopping Needs (ii) Convenience & Trust (iii) Security & Risk (iv) Flexibility

 

Thus the companies looking forward to transact online and the existing companies already providing e-shopping facilities have to focus on all the above factors. The most prominent and vital characteristic for adoption of any new technology, is generating awareness among the customers and educating them about that specific technology. Hence, if the consumers of West Bengal are not adopting Online Shopping, it may be because they are not aware about such a service being available and the added value that it offers. They should simplify the initial setup process and also provide troubleshooting.

 

Convenience & Trust is the second factor considered for this research study. In order to successfully implement the Online Shopping, companies must ensure that the services are easy, simple, rapid and of sufficiently high quality to ensure consumer satisfaction in order to maintain e-customers. A user friendly website with a good graphical user interface and easy to use navigation tools will certainly help in this regard.

 

Security and Risk is another important factor. The element of risk  in  this context would  relate  to  the  security of  transacting  for  consumers and determine  the  acceptability rate of this alternative delivery channel in the long run. To control the risk factor marketers has to provide consumer reassurance and information. Improve application as well as online payment information security and privacy, train & advise e-customers for following secure online transaction practices and other risk related factors. The payment system still needs to be improved. The most challenging issue would be building the trust among the consumers about the online shops. The people know the positive sides of online shopping. But they do not know whether their privacy or security is there or not. Develop easy & user friendly customer support applications for flexibility.

 

6. Limitations & Scope of future Research

The main objective of this research is to present the current scenario of online shopping in West Bengal. Researchers only used 100 respondents to draw inference on the population which is a very small number compared to the massive population of the research. Future researchers can use the findings of this paper for further research and can extend their studies to other neighboring states like Bihar, Jharkhand etc where the use of the technology is still in the nascent stage.

 

7. References

[1] Liu, C & Arnett K.P. (2000), ‘Exploring the factors associated with website success in the context of electronic commerce’, Information & Management, 38 (2000), pp-23-33.

[2] http://articles.timesofindia.indiatimes.com/2013-11-14/internet/44073307_1_internet-and-mobile-association- internet-penetration-rural-india

[3] Ranganathan, C. &Ganapathy, S. (2002), ‘Key dimensions of Business-to-Consumer websites’, Information and Management, 38 (2002), pp 457-465.

[4] Kau, AK., Tang, YE &Ghose, S. (2003), ‘Typology of Online Shoppers’, Journal of Consumer Marketing, vol.20,no.2, 2003. Pp 139-156.

[5] Koo DM &Ju SH (2010), ‘Interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intentions’, Computers in Human Behavior, 26 (2010), pp 377-388.

[6] Alam S.S &Yasin N.M. (2010), ‘An Investigation into the Antecedents of Customer Satisfaction of Online Shopping’ Journal of Marketing Development and Competitiveness, 5(1), 2010.

[7] Bhattacharjee Sarathi Partha, Saha Kumar Anish, Begum Ara Sahin,. 2012 July. The application of E-commerce in Business Application: Their Problems and Prospects. International Journal of Computer Applications (0975 – 8887), Volume 49– No.10.Retrieved from http://www.euroasiapub.org/IJRESS/Sep2013/4.pdf

[8] Zhang Lingying, Tan Wojie, Xu Yingcong, Tan Genlue, Dimensions of Consumers' Perceived

Risk and Their Influences on Online Consumers' Purchasing Behavior. CISME Vol. 2, Iss. 7,

2012, PP.8-14, www.jcisme.org ? C 2011-2012, World Academic Publishing.

[9]Kumari Renu,. (2013) September. Problem and Prospects of E-commerce in Retailing. IJRESS (ISSN 2249-7382), Volume 3,Issue 9. Retrieved from http://www.euroasiapub.org/IJRESS/Sep2013/4.pdf

[10] Patna, H. C. (2013). Is online shopping booming in india? - an empirical study. Retrieved from http://www.mbaskool.com/business-articles/marketing/7695-is-online-shopping-booming-in-india-an-empirical-study.html

 

 

 

 

 
 

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