• Corpus ID: 228174061

E-commerce and Online Consumer Behavior in India: A Literature Review

  • Ms Baljinder Kaur
  • Published 2016
  • Business, Economics, Computer Science

11 References

An study of factors affecting on online shopping behavior of consumers, e-shopping: an analysis of the technology acceptance model, journal of internet banking and commerce e-satisfaction and e-loyalty of consumers shopping online, consumer buying behaviour and e-commerce - an indian perspective, the google story, related papers.

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Início Números Vol.2 nº4 / nº3 Nº3 Artigos Drivers of shopping online: a lit...

Drivers of shopping online: a literature review

Consumers are increasingly adopting electronic channels for purchasing. Explaining online consumer behavior is still a major issue as studies available focus on a multiple set of variables and relied on different approaches and theoretical foundations. Based on previous research two main drivers of online behavior are identified: perceived benefits of online shopping related to utilitarian and hedonic characteristics and perceived risk. Additionally, exogenous factors are presented as moderating variables of the relationship between perceived advantages and disadvantages of internet shopping and online consumer behavior.

Entradas no índice

Keywords: , texto integral, 1. introduction.

1 The increasing dependence of firms on e-commerce activities and the recent failure of a large number of dot-com companies stresses the challenges of operating through virtual channels and also highlights the need to better understand consumer behavior in online market channels in order to attract and retain consumers.

2 While performing all the functions of a traditional consumer, in Internet shopping the consumer is simultaneously a computer user as he or she interacts with a system, i.e., a commercial Web site. On the other hand, the physical store has been transformed into Web-based stores that use networks and Internet technology for communications and transactions.

3 In this sense, there seems to be an understanding that online shopping behavior is fundamentally different from that in conventional retail environment, (Peterson et al ., 1997) as e-commerce relies on hypertext Computer Mediated Environments (CMEs) and the interaction customer-supplier is ruled by totally different principles.

4 Understanding the factors that explain how consumers interact with technology, their purchase behavior in electronic channels and their preferences to transact with an electronic vendor on a repeated basis is crucial to identify the main drivers of consumer behavior in online market channels.

5 Online consumer behavior research is a young and dynamic academic domain that is characterized by a diverse set of variables studied from multiple theoretical perspectives.

6 Researchers have relied on the Technology Acceptance Model (Davis, 1989: Davis et al ., 1989), the Theory of Reasoned Action (Fisbein and Ajzen, 1975), the Theory of Planned Behavior (Ajzen, 1991), Innovation Diffusion Theory (Rogers, 1995), Flow Theory (Czikszentmihalyi, 1998), Marketing, Information Systems and Human Computer Interaction Literature in investigating consumer’s adoption and use of electronic commerce.

7 While these studies individually provide meaningful insights on online consumer behavior, the empirical research in this area is sparse and the lack of a comprehensive understanding of online consumer behavior is still a major issue (Saeed et al ., 2003).

8 Previous research on consumer adoption of Internet shopping (Childers et al ., 2001; Dabholkar and Bagozzi, 2002; Doolin et al ., 2005; Monsuwé et al .; 2004; O´Cass and Fenech, 2002) suggests that consumers’ attitude toward Internet shopping and intention to shop online depends primarily on the perceived features of online shopping and on the perceived risk associated with online purchase. These relationships are moderated by exogenous factors like “consumer traits”, “situational factors”, “product characteristics” and “previous online shopping experiences”.

9 The outline of this paper is as follow. In the next section an assessment of the basic determinants that positively affect consumers’ intention to buy on the Internet is carried out. Second, the main perceived risks of shopping online are identified as factors that have a negative impact on the intention to buy from Internet vendors. Third, since it has been argued that the relationship between consumers’ attitude and intentions to buy online is moderated by independent factors, an examination of the influence of these factors is presented. Finally, the main findings, the importance to professionals and researchers and limitations are summarized.

2. Perceived benefits in online shopping

10 According to several authors (Childers et al ., 2001; Mathwick et al ., 2001; Menon and Kahn, 2002;) online shopping features can be either consumers’ perceptions of functional or utilitarian dimensions, or their perceptions of emotional and hedonic dimensions.

11 Functional or utilitarian perceptions relate to how effective shopping on the Internet is in helping consumers to accomplish their task, and how easy the Internet as a shopping medium is to use. Implicit to these perceptions is the perceived convenience offered by Internet vendor whereas convenience includes the time and effort saved by consumers when engaging in online shopping (Doolin, 2005; Monsuwé, 2004).

12 Emotional or hedonic dimensions reflect consumers’ perceptions regarding the potential enjoyment or entertainment of Internet shopping (Doolin, 2005; Monsuwé, 2004).

13 Venkatesh (2000) reported that perceived convenience offered by Internet Vendors has a positive impact on consumers’ attitude towards online shopping, as they perceive Internet as a medium that enhances the outcome of their shopping experience in an easy way.

14 Childers et al . (2001) found “enjoyment” to be a consistent and strong predictor of attitude toward online shopping. If consumers enjoy their online shopping experience, they have a more positive attitude toward online shop ping, and are more likely to adopt the Internet as a shopping medium.

15 Vijayasarathy and Jones (2000) showed that Internet shopping convenience, lifestyle compatibility and fun positively influence attitude towards Internet shopping and intention to shop online.

16 Despite the perceived benefits in online shopping mainly associated with convenience and enjoyment, there are a number of possible negative factors associated with the Internet shopping experience. These include the loss of sensory shopping or the loss of social benefits associated with shopping (Vijayasarathy and Jones, 2000).

17 In their research, Swaminathan et al . (1999) found that the lack of social interaction in Internet shopping deterred consumers from online purchase who preferred dealing with people or who treated shopping as a social ex perience.

3. Perceived risk in online shopping

18 Although most of the purchase decisions are perceived with some degree of risk, Internet shopping is associated with higher ri sk by consumers due to its newness and intrinsic characteristics associated to virtual stores where there is no human contact and consumers cannot physically check the quality of a product or monitor the safety and security of sending sensitive personal and financial information while shopping on the Internet (Lee and Turban, 2001).

19 Several studies reported similar findings that perceived risk negatively influenced consumers’ attitude or intention to purchase online (Doolin, 2005; Liu and Wei, 2003; Van der Heidjen et al ., 2003).

20 Opposing results were reported in two studies (Corbitt et al ., 2003; Jar venpaa et al ., 1999). The authors found that perceived risk of Internet shopping did not affect willingness to buy from an online store. One of the reasons for this contradictory conclusion might be due to the countries analyzed, respectively New Zealand and Australia, where individuals could be more risk- taken or more Internet heavy-users.

21 In examining the influences on the perceived risk of purchasing online, Pires at al. (2004) stated that no association was found between the fre quency of online purchasing and perceived risk, although satisfaction with prior Internet purchases was negatively associated with the perceived risk of intended purchases, but only for low-involvement products. Differences in perceived risk were associated with whether the intended purchase was a good or service and whether it was a high or low-involvement product. The perceived risk of purchasing goods through the Internet is higher than for services. Perceived risk was found to be higher for high-involvement than for low-involvement-products, be they goods or services.

22 Various types of risk are perceived in purchase decisions, including prod uct risk, security risk and privacy risk.

23 Product risk is the risk of making a poor or inappropriate purchase deci sion. Aspects involving product risk can be an inability to compare prices, being unable to return a product, not receiving a product paid for and product not performing as expected (Bhatnagar et al ., 2000; Jarvenpaa and Todd, 1997; Tan, 1999; Vijayasarathy and Jones, 2000).

24 Bhatnagar et al . (2000) suggest that the likelihood of purchasing on the Internet decreases with increases in product risk.

25 Other dimensions of perceived risk related to consumers’ perceptions on the Internet as a trustworthy shopping medium. For example, a common perception among consumers is that communicating credit card information over the Internet is inherently risky, due to the possibility of credit card fraud (Bhatnagar et al ., 2000; George, 2002; Hoffman et al ., (1999); Jarvenpaa and Todd, 1997; Liebermann and Stashevsky, 2002).

26 Previous studies found that beliefs about trustworthiness of the Internet were associated with positive attitudes toward Internet purchasing (George, 2002; Hoffman et al ., (1999); Liebermann and Stashevsky, 2002).

27 Privacy risk includes the unauthorized acquisition of personal information during Internet use or the provision of personal information collected by companies to third parties.

28 Perceived privacy risk causes consumers to be reluctant in exchanging personal information with Web providers (Hoffman et al ., 1999). The same authors suggest that with increasing privacy concerns, the likelihood of purchasing online decreases. Similarly, George (2002) found that a belief in the privacy of personal information was associated with negative attitudes toward Internet purchasing.

4. Exogenous factors

29 Based on the previous literature review, four exogenous factors were reported to be key drivers in moving consumers to ultim ately adopt the Internet as a shopping medium.

4.1. Consumer traits

30 Studies on online shopping behavior have focus mainly on demographic, psychographics and personality characteristics.

31 Bellman et al . (1999) cautioned that demographic variables alone explain a very low percentage of variance in the purchase decision.

32 According to Burke (2002) four relevant demographic factors – age, gen der, education, and income have a significant moderating effect on consum ers’ attitude toward online shopping.

33 In studying these variables several studies arrived to some contradictory results.

34 Concerning age, it was found that younger people are more interested in using new technologies, like the Internet, to search for comparative information on products (Wood, 2002). Older consumers avoid shopping online as the potential benefits from shopping online are offset by the perceived cost in skill needed to do it (Ratchford et al ., 2001).

35 On the other hand as younger people are associated with less income it was found that the higher a person’s income and age, the higher the propen sity to buy online (Bellman et al ., 1999; Liao and Cheung, 2001).

36 Gender differences are also related to different attitudes towards online shopping. Although men are more positive about using Internet as a shop ping medium, female shoppers that prefer to shop online, do it more frequently than male (Burke, 2002; Li et al ., 1999).

37 Furthermore Slyke et al . (2002) reported that as women view shopping as a social activity they were found to be less oriented to shop online than men.

38 Regarding education, higher educated consumers have a higher propen sity to use no-store channels, like the Internet to shop (Burke, 2002). This fact can be justified as education has been positively associated with individ ual’s level of Internet literacy (Li et al ., 1999).

39 Higher household income is often positively correlated with possession of computers, Internet access and higher education levels of consumers and consequently with a higher intention to shop online (Lohse et al ., 2000).

40 In terms of psychographics characteristics, Bellman et al . (1999) stated that consumers that are more likely to buy on the Internet have a “wired life” and are “starving of time”. Such consumers use the Internet for a long time for a multiple of purposes such as communicating through e-mail, reading news and search for information.

41 A personality characteristic closely associated with Internet adoption for shopping is innovativeness defined as the relative willingness of a person to try a new product or service (Goldsmith and Hokafer, 1991).

42 Innovativeness seems to influence more than frequency of online purchasing. It relates to the variety of product classes bought online, both in regard to purchasing and to visiting Web sites seeking information. (Blake et al ., 2003). In this sense innovativeness might be a fundamental factor determining the quantity and quality of online shopping.

4.2. Situational factors

43 Situational factors are found to be factors that affect significantly the choice between different retail store formats when consumers are faced with a shopping decision (Gehrt and Yan, 2004). According to this study, the time pressure and purpose of the shopping (for a gift or for themselves) can change the consumers’ shopping habits. Results showed that traditional stores were preferred for self-purchase situations rather than for gift occasions as in this case other store formats (catalog and Internet) performed better in terms of expedition. As for time pressure it was found that it was not a significantly predictor of online shopping as consumers when faced with scarcity of time responded to temporal issues related to whether there is a lag of time between the purchase transaction and receipt of goods rather than whether shopping can take place anytime.

44 Contradictory results were reported by Wolfinbarger and Gilly (2001). According to this study important attributes of online shopping are convenience and accessibility. When faced with time pressure situations, consumers engaged in online shopping but no conclusions should be taken on the effect of this factor on the attitude toward Internet shopping.

45 Lack of mobility and geographical distance has also been addressed has drivers of online shopping as Internet medium offers a viable solution to overcome these barriers (Monsuwé et al ., 2004). According to the same au thors the physical proximity of a traditional store that sells the same prod ucts available online, can lead consumers to shop in the “brick and mortar” alternative due to its perceived attractiveness despite consumers’ positive attitude toward shopping on the Internet.

46 The need for special items difficult to find in traditional retail stores has been reported a situational factor that attenuates the relationship between attitude and consumers’ intention to shop online (Wolfinbarger and Gilly, 2001).

4.3. Product characteristics

47 Consumers' decisions whether or not to shop online are also influenced by the type of product or service under consideration.

48 The lack of physical contact and assistance as well as the need to “feel” somehow the product differentiates products according to their suitability for online shopping.

49 Relying on product categories conceptualized by information economists, Gehrt and Yan (2004), reported that it is more likely that search goods (i.e. books) can be adequately assessed within a Web than experience goods (i.e. clothing), which usually require closer scrutiny.

50 Grewal et al . (2002) and Reibstein (1999) referred to standardized and fa miliar products as those in which quality uncertainty is almost absent and do not need physical assistance or pre-trial. These products such as groceries, books, CDs, videotapes have a high potential to be considered when shopping online.

51 Furthermore in case of certain sensitive products there is high potential to shop online to ensure adequate levels of privacy and anonymity (Grewal et al ., 2002). Some of these products like medicine and pornographic movies are raising legal and ethical issues among international community.

52 On the other hand, personal-care products like perfume or products that required personal knowledge and experience like cars or computers, are less likely to be considered when shopping online (Elliot and Fowell, 2000).

4.4. Previous online shopping experiences

53 Past research suggests that prior online shopping experiences have a direct impact on Internet shopping intentions. Satisfactory previous experiences decreases consumers’ perceived risk levels associated with online shopping but only across low-involvement goods and services (Monsuwé et al ., 2004).

54 Consumers that evaluate positively the previous online experience are motivated to continue shopping on the Internet (Eastlick and Lotz, 1999; Shim et al ., 2001; Weber and Roehl, 1999).

5. Conclusion

55 Relying on an extensive literature review, this paper aims to identify the main drivers of online shopping and thus to give further insights in explaining consumer behavior when adopting the Internet for buying as this issue is still in its infancy stage despite its major importance for academic and professionals.

56 This literature review shows that attitude toward online shopping and in- tention to shop online are not only affected by perceived benefits and perceived risks, but also by exogenous factors like consumer traits, situations factors, product characteristics, previous online shopping experiences.

57 Understanding consumers’ motivations and limitations to shop online is of major importance in e-business for making adequate strategic options and guiding technological and marketing decisions in order to increase customer satisfaction. As reported before consumers´ attitude toward online shopping is influenced by both utilitarian and hedonic factors. Therefore, e-marketers should emphasize the enjoyable feature of their sites as they promote the convenience of shopping online. As personal characteristics also affect buyers´ attitudes and intentions to engage in Internet shopping e-tailers should customize customers´ treatment. Furthermore, the e-vendor should assure a trust-building relationship with its customers to minimize perceived risk associated to online shopping. Adopting and communicating a clear privacy policy, using a third party seal and offering guarantees are mechanisms that can help in creating a reliable environment.

58 Some limitations of this paper must be pointed out as avenues for future. The factors identified as main drives of shopping online are the result of a literature review and there can always be factors of influence on consumers´ intentions to shop on the Internet that are not included because they are addressed in other studies not included in this review. However there are methodological reasons to believe that the most relevant factors were identified in this context. A second limitation is that this paper is the result of a literature review and has never been tested in its entirety using empirical evidence. This implies that some caution should be taken in applying the findings that can be derived from this paper Further research is also needed to determine which of the factors have the most significant effect on behavioral intention to shop on the Internet.

Bibliografia

Ajzen, I. (1991) The theory of planned behavior: some unresolved issues. Organizational Behavior and Human Decisions Processes , 50 (2), pp. 179-211.

Bellman, S., Lohse, G., and Johnson, E. (1999) Predictors of online buying behavior. Communica tions of the Association for the Comptuting Machinery , 42 (12), pp. 32-38.

Bhatnagar, A., Misra, S., and Rao, H. R. (2000) On risk, convenience and internet shopping behavior. Communications of the Association for Computing Machinery , pp. 43 (11), 98-105.

Blake, B. F., Kimberly, A. N., and Colin, M. V. (2003) Innovativeness and variety of internet shopping. Internet Research , 13 (3), pp. 156-169.

Burke, R. R. (2002) Technology and the customer interface: what consumers want in the physical and virtual store. Journal of the Academy of Marketing Science , 30 (4), pp. 411-432.

Childers, T. L., Carr, C. L., Peck, J., and Carson, S. (2001) Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing , 77 (4), pp. 511-535.

Corbitt, B. J., Thanasanki, T., and Yi, H. (2003) Trust and e-commerce: a study of consumer perceptions. Electronic Commerce Research and Applications , 2, pp. 203-215.

Csikszentmihalyi, M. (1988) Optimal experience: psychological studies of flow in cousciousness . U.K, Cambridge University Press.

Dabholkar, P. A. and Bagozzi R. P. (2002) An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. Journal of the Academy of Marketing Science , 30 (3), pp. 184-201.

Davis, F. D. (1989) Perceived usefulness, perceived ease of use and user acceptance of information techonology. MIS Quaterly , 13 (4), pp. 319-340.

Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. (1989) User acceptance of computer technology: a comparation of two theoretical models. Management Science , 35 (8), pp. 982-1002.

Doolin, B., Dillon, S., Thompson, F., and Corner, J. L. (2005) Perceived risk, the internet shopping experience and online purchasing behavior: a New Zeland perspective. Journal of Global Information Management , 13 (2), pp. 66-88.

Eastlick, M. A. and Lotz, S. L. (1999) Profiling potential adopters of an interactive shopping medium. International Journal of Retail and Distribution Management, pp. 27 (6/7), 209-223.

Elliot, S. and Fowell, S. (2000) Expectations versus reality: a snapshot of consumer experiences with internet retailing. International Journal of Information Management, 20 (5), pp. 323- 336.

Fishbein, M., and Ajzen, I. (1975) Belief, attitude, intention and behavior: an introduction to theory and research . Reading, MA, Addison-Wesley.

Gehrt, K. C. and Yan, R-N. (2004) Situational, consumer, and retail factors affecting internet, catalog, and store shopping. International Journal of Retail and Distribution Management , 32 (1), pp. 5-18.

George, J. F. (2002) Influences on the intent to make internet purchases. Internet Research , 12 (2), pp. 165-180.

Goldsmith, R. E. and Hofacker, C. F. (1991) Measuring consumer innovativeness. Journal of the Academy of Marketing Science , 19 (3), pp. 209-221.

Grewal, D., Iyer, G. R., and Levy, M. (2002) Internet retailing: enablers, limiters and market con sequences. Journal of Business Research .

Hoffman, D. L., Novak, T. P., and Peralta, M. (1999) Building consumer trust online. Communica tion of the Association of Computing Machinery , 42 (4), pp. 80-85.

Jarvenpaa, S. and Todd, P. (1997) Consumer reactions to electronic shopping on the world wide web. International Journal of Electronic Commerce , 1 (2), pp. 59-88.

Jarvenpaa, S., Tractinsky, N., and Vitale, M. (1999) Consumer trust in an internet store. Informa tion Technology and Managemet , 1 (1/2), pp. 45-72.

Lee, M. K.-O. and Turban, E. (2001). A trust model for consumer internet shopping. International Journal of Electronic Commerce , 6 (1), 75-91.

Li, H., Kuo, C., and Russel, M. G. (1999) The impact of perceived channel utilities, shopping orientations, and demographics on the consumer’s online buying behavior. Journal of Com- puter-Mediated Communications , 5 (2).

Liao, Z. and Cheung, M. T. (2001) Internet based e-shopping and consumer attitudes: an empirical study. Information and Management , 38 (5), pp. 299-306.

Liebermann, Y. and Stashevsky, S. (2002) Perceived risks as barriers to internet and e-commerce usage. Qualitative Market Research , 5 (4), pp. 291-300.

Liu, X. and Wei, K. K. (2003) An empirical study of product differences in consumers’ e-commerce adoption behavior. Electronic Commerce Research and Applications , 2, pp. 229-239.

Lohse, G. L., Bellman, S., and Johnson, E. J. (2000) Consumer buying behavior on the internet: findings from panel data. Journal of Interactive Marketing , 14 (1), pp. 15-29.

Mathwick, C., Malhotra, N. K. and Rigdon, E. (2001) Experiential value: conceptualisation, measurement and application in the catalog and internet shopping environment. Journal of Re- tailing , 77 (1), pp. 39-56.

Menon, S. and Kahn, P. (2002) Cross-category effects of induced arousal and pleasure on the internet shopping experience. Journal of Retailing , 78 (1), pp. 31-40.

Monsuwé, T. P., Dellaert, G. C.and de Ruyter, K. (2004) What drives consumers to shop online? A literature review. International Journal of Service Industry Management , 15 (1), pp. 102-121.

O’Cass, A. and Fenech, T. (2002) Web retailing adotion: exploring the nature of Internet users web retailing behavior. Journal of Retailing and Consumer Services , 13 (2), pp. 151-167.

Peterson, R. A., Balasubramaniam, S., and Bronnenberg, B. J. (1997) Exploring the implications of the internet for consumer marketing. Journal of the Academy of Marketing Science , 25 (4), pp. 329-346.

Pires, G., Staton, J., and Eckford, A. (2004) Influences of the perceived risk of purchasing online. Journal of Consumer Behavior , 4 (2), pp. 118-131.

Ranganathan, C. and Ganapathy, S. (2002) Key dimensions of business-to-consumer web sites. Information and Management , 39 (6), pp. 457-465.

Ratchford, B. T., Talukdar, D., and Lee, M.-S. (2001) A model of consumer choice of the internet as an information source. International Journal of Electronic Commerce , 5 (3), pp. 7-21.

Reibstein, D. J. (1999) Who is buying on the Internet, 1999? Working Paper, The Wharton School, University of Philadelphia, PA.

Rogers, E. M. (1985) Diffusion of innovations . New York: Free Press.

Saeed, K. A., Hwang, Y., and Yi, M. Y. (2003) Toward an integrative framework for online con sumer behavior research: a meta-analysis approach. Journal of End User Computing , 15 (4), pp. 1-26.

Shim, S., Eastlick, M. A., Lotz, S. L., and Warrington, P. (2001) An online prepurchase intentions model: the role of intention to saerch. Journal of Retailing , 77 (3), pp. 397-416.

Slyke, C. V., Comunale, C. L., and Belanger, F. (2002). Gender differences in perceptions of web-based shoping. Communications of the Association for Computing Machinery , 45 (7), 82-86.

Swaminathan, V., Lepkowska-White, E., and Rao, B. P. (1999) Browsers or buyers in cyberspace? An investigation of factors influencing electronic exchanges. Journal of Computer-Mediated Communication , 5 (2).

Tan, S. J. (1999) Strategies for reducing consumers’ risk aversion in internet shopping. Journal of Consumer Marketing , 16 (2), pp. 163-180.

van der Heidjen, H., Verhagen, T., and Creemers, M. (2003) Understanding online purchase intentions: Contributions from technology and trust perspectives. European Journal of Infor- mation Systems , 12, pp. 41-48.

Vijayasarathy, L. R. and Jones, J. M. (2000) Print and internet catalog shopping: assessing atti tudes and intentions. Internet Research , 10 (3), pp. 191-202.

Weber, K. and Roehl, W. S. (1999). Profiling people searching for and purchasing travel products on the world wide web. Journal of Travel Research , 37, 291-298.

Wolfinbarger, M. and Gilly, M. C. (2001) Shopping online for freedom, control, and fun. California Management Review , 43 (2), pp. 34-55.

Wood, S. L. (2002) Future fantasies: a social change perspective of retailing in the 21 st century. Journal of Retailing , 78 (1), pp. 77-83.

Para citar este artigo

Referência do documento impresso.

Ana Teresa Machado , «Drivers of shopping online: a literature review» ,  Comunicação Pública , Vol.2 nº4 / nº3 | 2006, 39-50.

Referência eletrónica

Ana Teresa Machado , «Drivers of shopping online: a literature review» ,  Comunicação Pública [Online], Vol.2 nº4 / nº3 | 2006, posto online no dia 30 outubro 2020 , consultado o 07 setembro 2024 . URL : http://journals.openedition.org/cp/8402; DOI : https://doi.org/10.4000/cp.8402

Ana Teresa Machado

Escola Superior de Comunicação Social Instituto Politécnico de Lisboa

[email protected]

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A Study on Consumer Behaviour towards online shopping in India -A Review of Literature

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The present article is an attempt that has been made to study the customer perception towards online shopping at Salem district. In this study an attempt has been made customer perception on online shoppers has been playing a vital role in these scenarios day to day activities in the mind of customers. Customer perception is typically affected in the way of broadly such as advertising, reviews, public relations, social media and personal experiences etc.,. Today we say that customers are mind blowing while go for an online shopping because the wide range of internet facilities in the era. The questionnaire was prepared through the inputs taken from the past researches and also from the feedback of the pilot study. Thus the validated final questionnaire was used to collect data from 150 respondents. The researchers have adopted random convenient sampling technique to gather the data. The data are analyzed using the simple percentage analysis and ANOVA (analysis of variances) methods. The result of this study reveals that customers are intake in the future online shopping in the way of intention for getting a products through internet websites such as EBay, Flipkart etc.,. The study suggested that the advertisers need to focus on their every customer’s effort to ticket the market assuming that the influence of the television ads in the online shopping behavior.

Iam Elvie Ü

Consumer behaviors are influenced by different factors such as culture, social class, relation, family, salary level and salary independency, age, gender etc. And so they show different customer behaviors. On-line shopping is a recent phenomenon in the field of E-Business. Most of the companies are selling their products/services on-line through online portals. Though online shopping is very common outside India, its growth in Indian Market, is still not in line with the global market. Companies are using the internet to put across and communicate the information. The main objective is to understand the behavior of consumers on online shopping in India. The results of study reveal that on-line shopping in India is affected by various factors like age, gender, marital status, family size and income. The results of the study could be further used by the researchers and practitioners for conducting future studies in the similar area.

isha aggarwal

Shyam Sundar

PAGE \* MERGEFORMAT 10 Modern retailing offers an ideal shopping experience through excellent ambience, merchandise choice and consumer preference analysis. Strong income growth, changing lifestyle and favourable demographics are the key factors for the rapid development of this sector. Education, global exposure, enhancing income level, acceptance of credit and smart cards might have effect on the shopping habits of Indian consumer (Baseer & Laxmi Prabha, 2007).Therefore it is essential for retailers to understand the motivational level of customer in order to attract them. Since consumers are attracted with more and more choices and this makes them to confuse ultimately on what to purchase. This in turn directs the consumer to deal with variety of seekers rather than brand loyalty. This leads the consumer to move from one brand to other or even to alternative product. In recent, this change has been mostly observed in Karnataka where the shoppers are exposed to several shopping formats that range from local Kirana's shop, supermarkets, convenience stores to hypermarkets (Anon, n.d.). The aim of this research paper was to investigate the impact of various individual factors on shoppers' behaviour in modern retail formats viz. hypermarkets and malls in Mangalore. Four independent variables viz. personality, pre-purchase information, shopping enjoyment tendency and buying intention are determined to examine the influence for the study. The data were collected from 210 valid responses. The outcome shows that pre-purchase information and shopping enjoyment tendency positively relate to shoppers' buying behaviour in modern retail formats in Mangalore. The study shows that the respondents are aware of modern retail formats; they prefer to shop, because they were getting pleasure while shopping. The study also reveals that both hypermarkets and malls were preferred by the respondents for shoppertainment.

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The purpose of these paper is to identify the attributes of online grocery shopping which has been the motivational factors of customers buying groceries online. To meet the objectives of the study, semi structured formal interviews were conducted with online grocery consumers, who are aware and purchase grocery products from online stores in and around Bangalore City in Karnataka. Convenience sampling techniques was used to collect primary data from online grocery consumers who were happened to be the employees, who are aware, use and purchase grocery products from online grocery stores, working in seven software companies by administering a structured non-disguised questionnaire to online grocery consumers. The data analysis and results were based on 183 usable questionnaires duly filled up by the online retail grocery consumers who actively participated in marketing survey. Descriptive statistical tools (Mean, Standard Deviations and cross tabulations), exploratory factor analysis and inferential statistical techniques such as Chi-square analysis, Correlation, multiple Regression were applied to test the formulated hypotheses from conceptual framework. The seven determinants are convenience, security, trust, service support, flexible transaction, personalized attention, price promotions are having significant influence on consumers online grocery buying behavior.

The aim of this study is to understand the consumer buying behavior via website versus mobile application. There are millions of people online at any point of time and all of them are potential customer for some or other retailer. With the advent of technology, many portals have been developed online, for the ease of customers as per their convenience like – websites, mobile applications. Since there are many portals and so many providers of services, it is vital to understand what customers are buying, form where they are buying, how they are buying and the reason behind buying from that particular place/portal. Customer behaviors are influenced by the advantages and disadvantages of these portals (websites and mobile applications) and also the demographics due to which they show varying behaviours. To understand the consumer behaviour, a questionnaire was designed and distributed online to 156 respondents and the sample consisted of people from Bengaluru. The result of this study would contribute to enhancement of knowledge and help analyze why one portal is working more than the other for the same retailer. It will help identify the major product/service categories that are availed via website and sectors availed via mobile application so that providers of different services/products can develop marketing strategies to generate more traffic and sales.

Due to the sharp growth in the number of people using internet, online shopping in India also has taken a sharp shoot with increasing trend. Educated people specially who are working in the private sector and are time scarce; prefer to shop online for various reasons. A study conducted by BCG suggests that during the year 2013; out of 1220 million Indians, 169 million Indians were active internet users. The study indicates that by the year 2018 this figure of internet users will shoot up and reach up to 583 million. The popularity of the online shopping trend gave an idea of undertaking this research work to know the preference of people to shop from the three popular shopping websites i.e. Amazon.com, Flipkart.com, Snapdeal.com; one Global Company and two Indian Companies. Wherein, the ‘convenience’ sample of 100 internet users in the age group of 18 to 40 years from Ahmedabad city was chosen. A structured questionnaire was given to each one of them to know the preference of website in the city of Ahmedabad along-with the personal interviews. Descriptive research design was used to know the preferences. The findings revealed that majority of the male as well as female internet users preferred Amazon.com (55%) following Flipkart.com (32%) on the various attributes, factors or services offered by these websites. Amazon topped among the three, on variables like: best payment options for all the products, wide range of products, quality products, variety of products. Flipkart was considered as having the best customer care services among the three and Snapdeal was considered as offering the good packaging. The suggestions from the respondents were that all the companies should display original products, offer better product return policies and provide full and actual product description.

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A study on factors limiting online shopping behaviour of consumers

Rajagiri Management Journal

ISSN : 0972-9968

Article publication date: 4 March 2021

Issue publication date: 12 April 2021

This study aims to investigate consumer behaviour towards online shopping, which further examines various factors limiting consumers for online shopping behaviour. The purpose of the research was to find out the problems that consumers face during their shopping through online stores.

Design/methodology/approach

A quantitative research method was adopted for this research in which a survey was conducted among the users of online shopping sites.

As per the results total six factors came out from the study that restrains consumers to buy from online sites – fear of bank transaction and faith, traditional shopping more convenient than online shopping, reputation and services provided, experience, insecurity and insufficient product information and lack of trust.

Research limitations/implications

This study is beneficial for e-tailers involved in e-commerce activities that may be customer-to-customer or customer-to-the business. Managerial implications are suggested for improving marketing strategies for generating consumer trust in online shopping.

Originality/value

In contrast to previous research, this study aims to focus on identifying those factors that restrict consumers from online shopping.

  • Online shopping

Daroch, B. , Nagrath, G. and Gupta, A. (2021), "A study on factors limiting online shopping behaviour of consumers", Rajagiri Management Journal , Vol. 15 No. 1, pp. 39-52. https://doi.org/10.1108/RAMJ-07-2020-0038

Emerald Publishing Limited

Copyright © 2020, Bindia Daroch, Gitika Nagrath and Ashutosh Gupta.

Published in Rajagiri Management Journal . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

Today, people are living in the digital environment. Earlier, internet was used as the source for information sharing, but now life is somewhat impossible without it. Everything is linked with the World Wide Web, whether it is business, social interaction or shopping. Moreover, the changed lifestyle of individuals has changed their way of doing things from traditional to the digital way in which shopping is also being shifted to online shopping.

Online shopping is the process of purchasing goods directly from a seller without any intermediary, or it can be referred to as the activity of buying and selling goods over the internet. Online shopping deals provide the customer with a variety of products and services, wherein customers can compare them with deals of other intermediaries also and choose one of the best deals for them ( Sivanesan, 2017 ).

As per Statista-The Statistics Portal, the digital population worldwide as of April 2020 is almost 4.57 billion people who are active internet users, and 3.81 billion are social media users. In terms of internet usage, China, India and the USA are ahead of all other countries ( Clement, 2020 ).

The number of consumers buying online and the amount of time people spend online has risen ( Monsuwe et al. , 2004 ). It has become more popular among customers to buy online, as it is handier and time-saving ( Huseynov and Yildirim, 2016 ; Mittal, 2013 ). Convenience, fun and quickness are the prominent factors that have increased the consumer’s interest in online shopping ( Lennon et al. , 2008 ). Moreover, busy lifestyles and long working hours also make online shopping a convenient and time-saving solution over traditional shopping. Consumers have the comfort of shopping from home, reduced traveling time and cost and easy payment ( Akroush and Al-Debei, 2015 ). Furthermore, price comparisons can be easily done while shopping through online mode ( Aziz and Wahid, 2018 ; Martin et al. , 2015 ). According to another study, the main influencing factors for online shopping are availability, low prices, promotions, comparisons, customer service, user friendly, time and variety to choose from ( Jadhav and Khanna, 2016 ). Moreover, website design and features also encourage shoppers to shop on a particular website that excite them to make the purchase.

Online retailers have started giving plenty of offers that have increased the online traffic to much extent. Regularly online giants like Amazon, Flipkart, AliExpress, etc. are advertising huge discounts and offers that are luring a large number of customers to shop from their websites. Companies like Nykaa, MakeMyTrip, Snapdeal, Jabong, etc. are offering attractive promotional deals that are enticing the customers.

Despite so many advantages, some customers may feel online shopping risky and not trustworthy. The research proposed that there is a strong relationship between trust and loyalty, and most often, customers trust brands far more than a retailer selling that brand ( Bilgihan, 2016 ; Chaturvedi et al. , 2016 ). In the case of online shopping, there is no face-to-face interaction between seller and buyer, which makes it non-socialize, and the buyer is sometimes unable to develop the trust ( George et al. , 2015 ). Trust in the e-commerce retailer is crucial to convert potential customer to actual customer. However, the internet provides unlimited products and services, but along with those unlimited services, there is perceived risk in digital shopping such as mobile application shopping, catalogue or mail order ( Tsiakis, 2012 ; Forsythe et al. , 2006 ; Aziz and Wahid, 2018 ).

Literature review

A marketer has to look for different approaches to sell their products and in the current scenario, e-commerce has become the popular way of selling the goods. Whether it is durable or non-durable, everything is available from A to Z on websites. Some websites are specifically designed for specific product categories only, and some are selling everything.

The prominent factors like detailed information, comfort and relaxed shopping, less time consumption and easy price comparison influence consumers towards online shopping ( Agift et al. , 2014 ). Furthermore, factors like variety, quick service and discounted prices, feedback from previous customers make customers prefer online shopping over traditional shopping ( Jayasubramanian et al. , 2015 ). It is more preferred by youth, as during festival and holiday season online retailers give ample offers and discounts, which increases the online traffic to a great extent ( Karthikeyan, 2016 ). Moreover, services like free shipping, cash on delivery, exchange and returns are also luring customers towards online purchases.

More and more people are preferring online shopping over traditional shopping because of their ease and comfort. A customer may have both positive and negative experiences while using an online medium for their purchase. Some of the past studies have shown that although there are so many benefits still some customers do not prefer online as their basic medium of shopping.

While making online purchase, customers cannot see, touch, feel, smell or try the products that they want to purchase ( Katawetawaraks and Wang, 2011 ; Al-Debei et al. , 2015 ), due to which product is difficult to examine, and it becomes hard for customers to make purchase decision. In addition, some products are required to be tried like apparels and shoes, but in case of online shopping, it is not possible to examine and feel the goods and assess its quality before making a purchase due to which customers are hesitant to buy ( Katawetawaraks and Wang, 2011 ; Comegys et al. , 2009 ). Alam and Elaasi (2016) in their study found product quality is the main factor, which worries consumer to make online purchase. Moreover, some customers have reported fake products and imitated items in their delivered orders ( Jun and Jaafar, 2011 ). A low quality of merchandise never generates consumer trust on online vendor. A consumer’s lack of trust on the online vendor is the most common reason to avoid e-commerce transactions ( Lee and Turban, 2001 ). Fear of online theft and non-reliability is another reason to escape from online shopping ( Karthikeyan, 2016 ). Likewise, there is a risk of incorrect information on the website, which may lead to a wrong purchase, or in some cases, the information is incomplete for the customer to make a purchase decision ( Liu and Guo, 2008 ). Moreover, in some cases, the return and exchange policies are also not clear on the website. According to Wei et al. (2010) , the reliability and credibility of e-retailer have direct impact on consumer decision with regards to online shopping.

Limbu et al. (2011) revealed that when it comes to online retailers, some websites provide very little information about their companies and sellers, due to which consumers feel insecure to purchase from these sites. According to other research, consumers are hesitant, due to scams and feel anxious to share their personal information with online vendors ( Miyazaki and Fernandez, 2001 ; Limbu et al. , 2011 ). Online buyers expect websites to provide secure payment and maintain privacy. Consumers avoid online purchases because of the various risks involved with it and do not find internet shopping secured ( Cheung and Lee, 2003 ; George et al. , 2015 ; Banerjee et al. , 2010 ). Consumers perceive the internet as an unsecured channel to share their personal information like emails, phone and mailing address, debit card or credit card numbers, etc. because of the possibility of misuse of that information by other vendors or any other person ( Lim and Yazdanifard, 2014 ; Kumar, 2016 ; Alam and Yasin, 2010 ; Nazir et al. , 2012 ). Some sites make it vital and important to share personal details of shoppers before shopping, due to which people abandon their shopping carts (Yazdanifard and Godwin, 2011). About 75% of online shoppers leave their shopping carts before they make their final decision to purchase or sometimes just before making the payments ( Cho et al. , 2006 ; Gong et al. , 2013 ).

Moreover, some of the customers who have used online shopping confronted with issues like damaged products and fake deliveries, delivery problems or products not received ( Karthikeyan, 2016 ; Kuriachan, 2014 ). Sometimes consumers face problems while making the return or exchange the product that they have purchased from online vendors ( Liang and Lai, 2002 ), as some sites gave an option of picking from where it was delivered, but some online retailers do not give such services to consumer and consumer him/herself has to courier the product for return or exchange, which becomes inopportune. Furthermore, shoppers had also faced issues with unnecessary delays ( Muthumani et al. , 2017 ). Sometimes, slow websites, improper navigations or fear of viruses may drop the customer’s willingness to purchase from online stores ( Katawetawaraks and Wang, 2011 ). As per an empirical study done by Liang and Lai (2002) , design of the e-store or website navigation has an impact on the purchase decision of the consumer. An online shopping experience that a consumer may have and consumer skills that consumers may use while purchasing such as website knowledge, product knowledge or functioning of online shopping influences consumer behaviour ( Laudon and Traver, 2009 ).

From the various findings and viewpoints of the previous researchers, the present study identifies the complications online shoppers face during online transactions, as shown in Figure 1 . Consumers do not have faith, and there is lack of confidence on online retailers due to incomplete information on website related to product and service, which they wish to purchase. Buyers are hesitant due to fear of online theft of their personal and financial information, which makes them feel there will be insecure transaction and uncertain errors may occur while making online payment. Some shoppers are reluctant due to the little internet knowledge. Furthermore, as per the study done by Nikhashem et al. (2011), consumers unwilling to use internet for their shopping prefer traditional mode of shopping, as it gives roaming experience and involves outgoing activity.

Several studies have been conducted earlier that identify the factors influencing consumer towards online shopping but few have concluded the factors that restricts the consumers from online shopping. The current study is concerned with the factors that may lead to hesitation by the customer to purchase from e-retailers. This knowledge will be useful for online retailers to develop customer driven strategies and to add more value product and services and further will change their ways of promoting and advertising the goods and enhance services for customers.

Research methodology

This study aimed to find out the problems that are generally faced by a customer during online purchase and the relevant factors due to which customers do not prefer online shopping. Descriptive research design has been used for the study. Descriptive research studies are those that are concerned with describing the characteristics of a particular individual or group. This study targets the population drawn from customers who have purchased from online stores. Most of the respondents participated were post graduate students and and educators. The total population size was indefinite and the sample size used for the study was 158. A total of 170 questionnaires were distributed among various online users, out of which 12 questionnaires were received with incomplete responses and were excluded from the analysis. The respondents were selected based on the convenient sampling technique. The primary data were collected from Surveys with the help of self-administered questionnaires. The close-ended questionnaire was used for data collection so as to reduce the non-response rate and errors. The questionnaire consists of two different sections, in which the first section consists of the introductory questions that gives the details of socio-economic profile of the consumers as well as their behaviour towards usage of internet, time spent on the Web, shopping sites preferred while making the purchase, and the second section consist of the questions related to the research question. To investigate the factors restraining consumer purchase, five-point Likert scale with response ranges from “Strongly agree” to “Strongly disagree”, with following equivalencies, “strongly disagree” = 1, “disagree” = 2, “neutral” = 3, “agree” = 4 and “strongly agree” = 5 was used in the questionnaire with total of 28 items. After collecting the data, it was manually recorded on the Excel sheet. For analysis socio-economic profile descriptive statistics was used and factors analysis was performed on SPSS for factor reduction.

Data analysis and interpretation

The primary data collected from the questionnaires was completely quantified and analysed by using Statistical Package for Social Science (SPSS) version 20. This statistical program enables accuracy and makes it relatively easy to interpret data. A descriptive and inferential analysis was performed. Table 1 represents the results of socio-economic status of the respondents along with some introductory questions related to usage of internet, shopping sites used by the respondents, amount of money spent by the respondents and products mostly purchased through online shopping sites.

According to the results, most (68.4%) of the respondents were belonging to the age between 21 and 30 years followed by respondents who were below the age of 20 years (16.4%) and the elderly people above 50 were very few (2.6%) only. Most of the respondents who participated in the study were females (65.8)% who shop online as compared to males (34.2%). The respondents who participated in the study were students (71.5%), and some of them were private as well as government employees. As per the results, most (50.5%) of the people having income below INR15,000 per month who spend on e-commerce websites. The results also showed that most of the respondents (30.9%) spent less than 5 h per week on internet, but up to (30.3%) spend 6–10 h per week on internet either on online shopping or social media. Majority (97.5%) of them have shopped through online websites and had both positive and negative experiences, whereas 38% of the people shopped 2–5 times and 36.7% shopped more than ten times. Very few people (12%), shopped only once. Most of the respondents spent between INR1,000–INR5,000 for online shopping, and few have spent more than INR5,000 also.

As per the results, the most visited online shopping sites was amazon.com (71.5%), followed by flipkart.com (53.2%). Few respondents have also visited other e-commerce sites like eBay, makemytrip.com and myntra.com. Most (46.2%) of the time people purchase apparels followed by electronics and daily need items from the ecommerce platform. Some of the respondents have purchased books as well as cosmetics, and some were preferring online sites for travel tickets, movie tickets, hotel bookings and payments also.

Factor analysis

To explore the factors that restrict consumers from using e-commerce websites factor analysis was done, as shown in Table 3 . A total of 28 items were used to find out the factors that may restrain consumers to buy from online shopping sites, and the results were six factors. The Kaiser–Meyer–Olkin (KMO) measure, as shown in Table 2 , in this study was 0.862 (>0.60), which states that values are adequate, and factor analysis can be proceeded. The Bartlett’s test of sphericity is related to the significance of the study and the significant value is 0.000 (<0.05) as shown in Table 2 .

The analysis produced six factors with eigenvalue more than 1, and factor loadings that exceeded 0.30. Moreover, reliability test of the scale was performed through Cronbach’s α test. The range of Cronbach’s α test came out to be between 0.747 and 0.825, as shown in Table 3 , which means ( α > 0.7) the high level of internal consistency of the items used in survey ( Table 4 ).

Factor 1 – The results revealed that the “fear of bank transaction and faith” was the most significant factor, with 29.431% of the total variance and higher eigenvalue, i.e. 8.241. The six statements loaded on Factor 1 highly correlate with each other. The analysis shows that some people do not prefer online shopping because they are scared to pay online through credit or debit cards, and they do not have faith over online vendors.

Factor 2 – “Traditional shopping is convenient than online shopping” has emerged as a second factor which explicates 9.958% of total variance. It has five statements and clearly specifies that most of the people prefer traditional shopping than online shopping because online shopping is complex and time-consuming.

Factor 3 – Third crucial factor emerged in the factor analysis was “reputation and service provided”. It was found that 7.013% of variations described for the factor. Five statements have been found on this factor, all of which were interlinked. It clearly depicts that people only buy from reputed online stores after comparing prices and who provide guarantee or warrantee on goods.

Factor 4 – “Experience” was another vital factor, with 4.640% of the total variance. It has three statements that clearly specifies that people do not go for online shopping due to lack of knowledge and their past experience was not good and some online stores do not provide EMI facilities.

Factor 5 – Fifth important factor arisen in the factor analysis was “Insecurity and Insufficient Product Information” with 4.251% of the total variance, and it has laden five statements, which were closely intertwined. This factor explored that online shopping is not secure as traditional shopping. The information of products provided on online stores is not sufficient to make the buying decision.

Factor 6 – “Lack of trust” occurred as the last factor of the study, which clarifies 3.920% of the total variance. It has four statements that clearly state that some people hesitate to give their personal information, as they believe online shopping is risky than traditional shopping. Without touching the product, people hesitate to shop from online stores.

The study aimed to determine the problems faced by consumers during online purchase. The result showed that most of the respondents have both positive and negative experience while shopping online. There were many problems or issues that consumer’s face while using e-commerce platform. Total six factors came out from the study that limits consumers to buy from online sites like fear of bank transaction and no faith, traditional shopping more convenient than online shopping, reputation and services provided, experience, insecurity and insufficient product information and lack of trust.

The research might be useful for the e-tailers to plan out future strategies so as to serve customer as per their needs and generate customer loyalty. As per the investigation done by Casalo et al. (2008) , there is strong relationship between reputation and satisfaction, which further is linked to customer loyalty. If the online retailer has built his brand name, or image of the company, the customer is more likely to prefer that retailer as compared to new entrant. The online retailer that seeks less information from customers are more preferred as compared to those require complete personal information ( Lawler, 2003 ).

Online retailers can adopt various strategies to persuade those who hesitate to shop online such that retailer need to find those negative aspects to solve the problems of customers so that non-online shopper or irregular online consumer may become regular customer. An online vendor has to pay attention to product quality, variety, design and brands they are offering. Firstly, the retailer must enhance product quality so as to generate consumer trust. For this, they can provide complete seller information and history of the seller, which will preferably enhance consumer trust towards that seller.

Furthermore, they can adopt marketing strategies such as user-friendly and secure website, which can enhance customers’ shopping experience and easy product search and proper navigation system on website. Moreover, complete product and service information such as feature and usage information, description and dimensions of items can help consumer decide which product to purchase. The experience can be enhanced by adding more pictures, product videos and three-dimensional (3D), images which will further help consumer in the decision-making process. Moreover, user-friendly payment systems like cash on deliveries, return and exchange facilities as per customer needs, fast and speedy deliveries, etc. ( Chaturvedi et al. , 2016 ; Muthumani et al. , 2017 ) will also enhance the probability of purchase from e-commerce platform. Customers are concerned about not sharing their financial details on any website ( Roman, 2007 ; Limbu et al. , 2011 ). Online retailers can ensure payment security by offering numerous payment options such as cash on delivery, delivery after inspection, Google Pay or Paytm or other payment gateways, etc. so as to increase consumer trust towards website, and customer will not hesitate for financial transaction during shopping. Customers can trust any website depending upon its privacy policy, so retailers can provide customers with transparent security policy, privacy policy and secure transaction server so that customers will not feel anxious while making online payments ( Pan and Zinkhan, 2006 ). Moreover, customers not only purchase basic goods from the online stores but also heed augmented level of goods. Therefore, if vendors can provide quick and necessary support, answer all their queries within 24-hour service availability, customers may find it convenient to buy from those websites ( Martin et al. , 2015 ). Sellers must ensure to provide products and services that are suitable for internet. Retailers can consider risk lessening strategies such as easy return and exchange policies to influence consumers ( Bianchi and Andrews, 2012 ). Furthermore, sellers can offer after-sales services as given by traditional shoppers to attract more customers and generate unique shopping experience.

Although nowadays, most of the vendors do give plenty of offers in form of discounts, gifts and cashbacks, but most of them are as per the needs of e-retailers and not customers. Beside this, trust needs to be generated in the customer’s mind, which can be done by modifying privacy and security policies. By adopting such practices, the marketer can generate customers’ interest towards online shopping.

Conceptual framework of the study

Socioeconomic status of respondents

Variables Frequency (%)
Gender Male 100 34.2
Female 52 65.8
Age
Below 20 25 16.4
21–30 104 68.4
31–40 15 9.9
41–50 4 2.6
Above 50 4 2.6
Occupation
Government employee 2 1.3
Private employee 23 15.2
Self employed 14 9.3
Student 108 71.5
Other 4 2.6
Income (per month)
Less than 15,000 53 50.5
15,001–30,000 17 16.2
30,001–60,000 23 21.9
Above 60,000 12 11.4
Hours spent by respondents on the internet per week
Less than 5 h 47 30.9
6–10 h 46 30.3
11–15 h 22 14.5
More than 15 h 37 24.3
No. of times respondents shopped online
Once 19 12
2–5 times 60 38
6–10 times 21 13.3
More than 10 19 36.7
Highest amount spent by respondents on online shopping
Less than INR500 9 5.7
INR500–INR1,000 38 24.1
INR1,000–INR5,000 69 43.7
More than INR5,000 42 26.6
E-commerce sites mostly preferred
Flipkart 84 53.2
eBay 14 8.9
Amazon 113 71.5
MakeMyTrip 20 12.7
Other 23 14.6
Products purchased by respondents
Daily need items 52 32.9
Apparels 73 46.2
Travel tickets 29 18.4
Movie tickets 46 29.1
Books 34 21.5
Electronics 68 43
Other 10 6.3

KMO and Bartlett’s test

KMO measure of sampling adequacy 0.862
Bartlett’s test of sphericity Approximate 1,812.156
df 378
Sig 0.000

Cronbach’s α

Research variables Cronbach’s
Fear of bank transaction and no faith 0.747
Traditional shopping is convenient than online shopping 0.797
Reputation and service provided 0.825
Bad experience 0.816
Insecurity and insufficient product information 0.784
Lack of trust 0.760
Factors Name of the factor Statements Eigenvalue % of variance Loadings
1 Fear of bank transaction and faith − The fact that only those with a credit card or bank account can shop on the internet is a drawback 29.431 0.789
−While shopping online, I hesitate to give my credit card number 0.642
−I do not prefer online shopping because of lack of trust over vendors 8.241 0.601
−I do not prefer to buy online because of bad returning policy 0.580
−The fear of wrong product delivery stops me to buy through online 0.552
−I do not prefer to purchase from online stores if they do not provide cash on delivery facilities 0.394
2 Traditional shopping is convenient than online shopping − I think shopping on the internet takes lot of time 2.788 9.958 0.713
−Online shopping is complex as compared to traditional shopping 0.706
−It is more difficult to shop on the internet 0.698
−I believe online shopping cannot overtake the traditional shopping 0.658
−I prefer traditional shopping than online shopping 0.614
3 Reputation and service provided −I prefer to purchase from reputed online websites 1.964 7.013 0.775
−I generally prefer to buy after comparing prices with all other websites 0.732
−I prefer to purchase online if website is secure and genuine 0.726
−I prefer those websites only that deliver the goods as soon as possible 0.638
−If there is no guarantee and warrantee of the product, I will never prefer to buy through online stores 0.550
4 Experience −I do not prefer to purchase from online stores if they do not provide every month instalment (EMI) facilities 1.299 4.640 0.776
−I hesitate to shop online because my past experience was not good 0.663
−I do not prefer to buy online because of little knowledge of internet 0.606
5 Insecurity and insufficient product information −I will not prefer online shopping if the description of products shown on the online websites are not accurate 1.190 4.251 0.665
−I will not prefer online shopping if online prices are high 0.614
−The information given about the products and services on the internet is not sufficient to make purchase 0.548
−If variety of goods available on the online stores are less, I will not prefer online shopping 0.539
−Online shopping is not secure as traditional shopping 0.416
6 Lack of trust − I hesitate to give my personal information on online websites 1.098 3.920 0.552
−Without touching products, it is difficult to make buying decision 0.521
−Shopping online is risky 0.511
−I would be frustrated about what to do if I am dissatisfied with a purchase made from the internet 0.488

Agift , A. , Rekha , V. and Nisha , C. ( 2014 ), “ Consumers attitude towards online shopping ”, Research Journal of Family, Community and Consumer Sciences , Vol. 2 No. 8 , pp. 4 - 7 , available at: www.isca.in/FAMILY_SCI/Archive/v2/i8/2.ISCA-RJFCCS-2014-017.php

Akroush , M.N. and Al-Debei , M.M. ( 2015 ), “ An integrated model of factors affecting consumer attitudes towards online shopping ”, Business Process Management Journal , Vol. 21 No. 6 , pp. 1353 - 1376 , doi: 10.1108/BPMJ-02-2015-0022 .

Alam , M.Z. and Elaasi , S. ( 2016 ), “ A study on consumer perception towards e-shopping in KSA ”, International Journal of Business and Management , Vol. 11 No. 7 , p. 202 .

Alam , S. and Yasin , N.M. ( 2010 ), “ What factors influence online brand trust: evidence from online tickets buyers in Malaysia ”, Journal of Theoretical and Applied Electronic Commerce Research , Vol. 5 No. 3 , pp. 78 - 89 , doi: 10.4067/S0718-18762010000300008 .

Al-Debei , M.M. , Akroush , M.N. and Ashouri , M.I. ( 2015 ), “ Consumer attitudes towards online shopping: the effects of trust, perceived benefits, and perceived web quality ”, Internet Research , Vol. 25 No. 5 , pp. 707 - 733 , doi: 10.1108/IntR-05-2014-0146 .

Aziz , N.N.A. and Wahid , N.A. ( 2018 ), “ Factors influencing online purchase intention among university students ”, International Journal of Academic Research in Business and Social Sciences , Vol. 8 No. 7 , pp. 702 - 717 , doi: 10.6007/IJARBSS/v8-i7/4413 .

Banerjee , N. , Dutta , A. and Dasgupta , T. ( 2010 ), “ A study on customers’ attitude towards online shopping-An Indian perspective ”, Indian Journal of Marketing , Vol. 40 No. 11 , pp. 36 - 42 .

Bianchi , C. and Andrews , L. ( 2012 ), “ Risk, trust, and consumer online purchasing behaviour: a Chilean perspective ”, International Marketing Review , Vol. 29 No. 3 , pp. 253 - 275 , doi: 10.1108/02651331211229750 .

Bilgihan , A. ( 2016 ), “ Gen Y customer loyalty in online shopping: an integrated model of trust, user experience and branding ”, Computers in Human Behavior , Vol. 61 , pp. 103 - 113 , doi: 10.1016/j.chb.2016.03.014 .

Casalo , L. , Flavián , C. and Guinalíu , M. ( 2008 ), “ The role of perceived usability, reputation, satisfaction and consumer familiarity on the website loyalty formation process ”, Computers in Human Behavior , Vol. 24 No. 2 , pp. 325 - 345 , doi: 10.1016/j.chb.2007.01.017 .

Chaturvedi , D. , Gupta , D. and Singh Hada , D. ( 2016 ), “ Perceived risk, trust and information seeking behavior as antecedents of online apparel buying behavior in India: an exploratory study in context of Rajasthan ”, International Review of Management and Marketing , Vol. 6 No. 4 , pp. 935 - 943 , doi: 10.2139/ssrn.3204971 .

Cheung , C.M. and Lee , M.K. ( 2003 ), “ An integrative model of consumer trust in internet shopping ”, ECIS 2003 Proceedings , p. 48 .

Cho , C.H. , Kang , J. and Cheon , H.J. ( 2006 ), “ Online shopping hesitation ”, Cyberpsychology and Behavior , Vol. 9 No. 3 , pp. 261 - 274 , doi: 10.1089/cpb.2006.9.261 .

Clement , J. ( 2020 ), “ Worldwide digital population as of April 2020 ”, available at: www.statista.com/statistics/617136/digital-population-worldwide/ ( accessed 18 June 2020 ).

Comegys , C. , Hannula , M. and Váisánen , J. ( 2009 ), “ Effects of consumer trust and risk on online purchase decision-making: a comparison of Finnish and United States students ”, International Journal of Management , Vol. 26 No. 2 , available at: www.questia.com/library/journal/1P3-1874986651/effects-of-consumer-trust-and-risk-on-online-purchase

Forsythe , S. , Liu , C. , Shannon , D. and Gardner , L.C. ( 2006 ), “ Development of a scale to measure the perceived benefits and risks of online shopping ”, Journal of Interactive Marketing , Vol. 20 No. 2 , pp. 55 - 75 , doi: 10.1002/dir.20061 .

George , O.J. , Ogunkoya , O.A. , Lasisi , J.O. and Elumah , L.O. ( 2015 ), “ Risk and trust in online shopping: experience from Nigeria ”, International Journal of African and Asian Studies , Vol. 11 , pp. 71 - 78 , available at: https://iiste.org/Journals/index.php/JAAS/article/view/23937

Gong , W. , Stump , R.L. and Maddox , L.M. ( 2013 ), “ Factors influencing consumers’ online shopping in China ”, Journal of Asia Business Studies , Vol. 7 No. 3 , pp. 214 - 230 , doi: 10.1108/JABS-02-2013-0006 .

Huseynov , F. and Yildirim , S.O. ( 2016 ), “ Internet users’ attitudes toward business-to-consumer online shopping: a survey ”, Information Development , Vol. 32 No. 3 , pp. 452 - 465 , doi: 10.1177/0266666914554812 .

Jadhav , V. and Khanna , M. ( 2016 ), “ Factors influencing online buying behavior of college students: a qualitative analysis ”, The Qualitative Report , Vol. 21 No. 1 , pp. 1 - 15 , available at: https://nsuworks.nova.edu/tqr/vol21/iss1/1

Jayasubramanian , P. , Sivasakthi , D. and Ananthi , P.K. ( 2015 ), “ A study on customer satisfaction towards online shopping ”, International Journal of Applied Research , Vol. 1 No. 8 , pp. 489 - 495 , available at: www.academia.edu/download/54009715/1-7-136.pdf

Jun , G. and Jaafar , N.I. ( 2011 ), “ A study on consumers’ attitude towards online shopping in China ”, International Journal of Business and Social Science , Vol. 2 No. 22 , pp. 122 - 132 .

Karthikeyan ( 2016 ), “ Problems faced by online customers ”, International Journal of Current Research and Modern Education (IJCRME) , Vol. 1 No. 1 , pp. 166 - 169 , available at: http://ijcrme.rdmodernresearch.com/wp-content/uploads/2015/06/23.pdf

Katawetawaraks , C. and Wang , C.L. ( 2011 ), “ Online shopper behavior: influences of online shopping decision ”, Asian Journal of Business Research , Vol. 1 No. 2 , pp. 66 - 74 , available at: https://ssrn.com/abstract=2345198

Kumar , M. ( 2016 ), “ Consumer behavior and satisfaction in e-commerce: a comparative study based on online shopping of some electronic gadgets ”, International Journal of Research in Commerce and Management , Vol. 7 No. 7 , pp. 62 - 67 , available at: https://ijrcm.org.in/article_info.php?article_id=6785

Kuriachan , J.K. ( 2014 ), “ Online shopping problems and solutions ”, New Media and Mass Communication , Vol. 23 No. 1 , pp. 1 - 4 , available at: www.academia.edu/download/34229456/Online_shopping_problems_and_solutions

Laudon , K.C. and Traver , C.G. ( 2009 ), E-Commerce Business. Technology. Society , 5th ed ., Prentice Hall .

Lawler , J.P. ( 2003 ), “ Customer loyalty and privacy on the web ”, Journal of Internet Commerce , Vol. 2 No. 1 , pp. 89 - 105 , doi: 10.1300/J179v02n01_07 .

Lee , M.K. and Turban , E. ( 2001 ), “ A trust model for consumer internet shopping ”, International Journal of Electronic Commerce , Vol. 6 No. 1 , pp. 75 - 91 , doi: 10.1080/10864415.2001.11044227 .

Lennon , S.J. , et al. ( 2008 ), “ Rural consumers’ online shopping for food and fiber products as a form of outshopping ”, Clothing and Textiles Research Journal , Vol. 27 No. 1 , pp. 3 - 30 , doi: 10.1177/0887302X07313625 .

Liang , T.P. and Lai , H.J. ( 2002 ), “ Effect of store design on consumer purchases: an empirical study of on-line bookstores ”, Information and Management , Vol. 39 No. 6 , pp. 431 - 444 , doi: 10.1016/S0378-7206(01)00129-X .

Lim , P.L. and Yazdanifard , R. ( 2014 ), “ Does gender play a role in online consumer behavior? ”, Global Journal of Management and Business Research , Vol. 14 No. 7 , pp. 48 - 56 , available at: https://journalofbusiness.org/index.php/GJMBR/article/view/1570

Limbu , Y.B. , Wolf , M. and Lunsford , D.L. ( 2011 ), “ Consumers’ perceptions of online ethics and its effects on satisfaction and loyalty ”, Journal of Research in Interactive Marketing , Vol. 5 No. 1 , pp. 71 - 89 , doi: 10.1108/17505931111121534 .

Liu , C. and Guo , Y. ( 2008 ), “ Validating the end-user computing satisfaction instrument for online shopping systems ”, Journal of Organizational and End User Computing , Vol. 20 No. 4 , pp. 74 - 96 , available at: www.igi-global.com/article/journal-organizational-end-user-computing/3849

Martin , J. , Mortimer , G. and Andrews , L. ( 2015 ), “ Re-examining online customer experience to include purchase frequency and perceived risk ”, Journal of Retailing and Consumer Services , Vol. 25 , pp. 81 - 95 , doi: 10.1016/j.jretconser.2015.03.008 .

Mittal , A. ( 2013 ), “ E-commerce: it’s impact on consumer behavior ”, Global Journal of Management and Business Studies , Vol. 3 No. 2 , pp. 131 - 138 , available at: www.ripublication.com/gjmbs_spl/gjmbsv3n2spl_09.pdf

Miyazaki , A.D. and Fernandez , A. ( 2001 ), “ Consumer perceptions of privacy and security risks for online shopping ”, Journal of Consumer Affairs , Vol. 35 No. 1 , pp. 27 - 44 , doi: 10.1111/j.1745-6606.2001.tb00101.x .

Monsuwe , T.P.Y. , Dellaert , B.G.C. and Ruyter , K.D. ( 2004 ), “ What drives consumers to shop online? A literature review ”, International Journal of Service Industry Management , Vol. 15 No. 1 , pp. 102 - 121 , doi: 10.1108/09564230410523358 .

Muthumani , A. , Lavanya , V. and Mahalakshmi , R. ( 2017 ), “ Problems faced by customers on online shopping in Virudhunagar district ”, International Journal of Science Technology and Management (IJSTM) , Vol. 6 No. 2 , pp. 152 - 159 , available at: www.ijstm.com/images/short_pdf/1486214600_S184_IJSTM.pdf .

Nazir , S. , Tayyab , A. , Sajid , A. , Ur Rashid , H. and Javed , I. ( 2012 ), “ How online shopping is affecting consumers buying behavior in Pakistan? ”, International Journal of Computer Science Issues (IJCSI) , Vol. 9 No. 3 , p. 486 .

Nikhashem , S.R. , Yasmin , F. , Haque , A. and Khatibi , A. ( 2011 ), “ Study on customer perception towards online-ticketing in Malaysia ”, In Proceedings For 2011 International Research Conference and Colloquium , Vol. 1 , No. 1 , pp. 320 - 338 .

Pan , Y. and Zinkhan , G.M. ( 2006 ), “ Exploring the impact of online privacy disclosures on consumer trust ”, Journal of Retailing , Vol. 82 No. 4 , pp. 331 - 338 , doi: 10.1016/j.jretai.2006.08.006 .

Roman , S. ( 2007 ), “ The ethics of online retailing: a scale development and validation from the consumers’ perspective ”, Journal of Business Ethics , Vol. 72 No. 2 , pp. 131 - 148 , doi: 10.1007/s10551-006-9161-y .

Sivanesan ( 2017 ), “ A study on problems faced by customers in online shopping with special reference to Kanyakumari district ”, International Journal of Research in Management and Business Studies , Vol. 4 No. 3 , pp. 22 - 25 , available at: http://ijrmbs.com/vol4issue3SPL1/sivanesan.pdf

Tsiakis , T. ( 2012 ), “ Consumers’ issues and concerns of perceived risk of information security in online framework. The marketing strategies ”, Procedia – Social and Behavioral Sciences , Vol. 62 No. 24 , pp. 1265 - 1270 , doi: 10.1016/j.sbspro.2012.09.216 .

Wei , L.H. , Osman , M.A. , Zakaria , N. and Bo , T. ( 2010 ), “ Adoption of e-commerce online shopping in Malaysia ”, In 2010 IEEE 7th International Conference on E-Business Engineering , IEEE , pp. 140 - 143 .

Yazdanifard , R. and Godwin , N.W. ( 2011 ), “ Challenges faced by customers: Highlighting E-shopping problems ”, Paper presented at international Conference on Economics, Business and Marketing Management (CEBMM 2011) , Shanghai, China , available at: http://www.researchgate.net/profile/Assc_Prof_Dr_Rashad_Yazdanifard/publication/268507745_Challenges_faced_by_customers_Highlighting_E-shopping_problems/links/546d4ade0cf26e95bc3cb0a1/Challenges-faced-by-customers-Highlighting-E-shopping-problems.pdf ( accessed 20 March 2020 ).

Further reading

Grabner-Kräuter , S. and Kaluscha , E.A. ( 2003 ), “ Empirical research in on-line trust: a review and critical assessment ”, International Journal of Human-Computer Studies , Vol. 58 No. 6 , pp. 783 - 812 .

Nurfajrinah , M.A. , Nurhadi , Z.F. and Ramdhani , M.A. ( 2017 ), “ Meaning of online shopping for indie model ”, The Social Sciences , Vol. 12 No. 4 , pp. 737 - 742 , available at: https://medwelljournals.com/abstract/?doi=sscience.2017.737.742

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Title: A study of consumer behaviour towards online shopping
Researcher: Meghna Meena
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Keywords: Business
Business Finance
Commerce
Economics
Economics and Business
Industrial management
Management
Social sciences
Social Sciences
University: University of Rajasthan
Completed Date: 2018
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Consumers’ rational attitudes toward online shopping improve their satisfaction through trust in online shopping platforms

  • Published: 02 September 2024

Cite this article

literature review on online shopping behaviour in india

  • Yaxing Lan   ORCID: orcid.org/0009-0001-0275-8451 1 &
  • Guofang Liu   ORCID: orcid.org/0000-0002-2502-2244 1  

Currently, online shopping has become one of the main consumption methods, with online retail sales reaching 13.79 trillion yuan in 2022. However, not all consumers are satisfied with their online shopping experiences. This study proposed that consumers’ rational attitudes toward online shopping were an important influencing factor for their satisfaction. Additionally, consumers’ trust in online shopping platforms is a mediator in the above relationship. Two studies were conducted to investigate this proposition. In Study 1, participants’ rational attitudes were first operationalized by a procedure to approve their decisions. Then, their rationality, trust in online shopping platforms, and consumer satisfaction were measured. It was found that participants’ rational attitudes improved their satisfaction through the mediating role of their trust in online shopping platforms. Study 2 further examined the hypotheses by providing participants with either budget alert information or no information. The results showed that such alert information increased participants’ rationality and supported the findings of Study 1. Based on the results, rational consumers are more likely to be satisfied with their consumption, and trust is a key mechanism. Therefore, online shopping platforms and retailers should make efforts to improve consumers’ rational attitudes and protect their rights and interests to obtain consumers’ trust and a win‒win result between themselves and consumers.

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Ashtar, S., Yom-Tov, G. B., Rafaeli, A., & Wirtz, J. (2023). Affect-as-Information: Customer and employee affective displays as expeditious predictors of customer satisfaction. Journal of Service Research , advance publication online. https://doi.org/10.1177/10946705231194076

Article   Google Scholar  

Ayodeji, Y., Rjoub, H., & Ozgit, H. (2023). Achieving sustainable customer loyalty in airports: The role of waiting time satisfaction and self-service technologies. Technology in Society , 72 , 102–106. https://doi.org/10.1016/j.techsoc.2022.102106

Becker, G. S. (1976). The economic approach to human behavior (Vol. 803). University of Chicago Press.

Book   Google Scholar  

Bolek, S. (2020). Consumer knowledge, attitudes, and judgments about food safety: A consumer analysis. Trends in Food Science & Technology , 102 , 242–248. https://doi.org/10.1016/j.tifs.2020.03.009

Borah, P. S., Dogbe, C. S. K., & Marwa, N. (2024). Generation Z’s green purchase behavior: Do green consumer knowledge, consumer social responsibility, green advertising, and green consumer trust matter for sustainable development?. Business Strategy and the Environment , advance publication online. https://doi.org/10.1002/bse.3714

Bozkurt, S., Welch, E., Gligor, D., Gligor, N., Garg, V., & Pillai, K. G. (2023). Unpacking the experience of individuals engaging in incentivized false (and genuine) positive reviews: The impact on brand satisfaction. Journal of Business Research , 165 , 114077. https://doi.org/10.1016/j.jbusres.2023.114077

China Banking and Insurance Regulatory Commission (2021). Notice on further regulating the supervision and administration of internet consumer loans for college students. http://www.cbirc.gov.cn/cn/view/pages/govermentDetail. html?docId=971269&itemId=4215&generaltype=1

Chinedu, A. H., Haron, S. A., & Osman, S. (2016). Competencies of Mobile Telecommunication Network (MTN) consumers in Nigeria. IOSR Journal of Humanities and Social Science , 21 (11), 61–69. https://doi.org/10.9790/0837-2111046169

Chinelato, F. B., Oliveira, A. S. D., & Souki, G. Q. (2023). Do satisfied customers recommend restaurants? The moderating effect of engagement on social networks on the relationship between satisfaction and eWOM. Asia Pacific Journal of Marketing and Logistics , 35 (11), 2765–2784. https://doi.org/10.1108/APJML-02-2022-0153

Chopdar, P. K., & Balakrishman, J. (2020). Consumers response towards mobile commerce, applications: S-O-R approach. International Journal of Information Management , 53 , 102106. https://doi.org/10.1016/j.ijinfomgt.2020.102106

Delvecchio, D. S., Jae, H., & Ferguson, J. L. (2019). Consumer aliteracy.  Psychology & Marketing , 36(2), 89–101. https://doi.org/10.1002/mar.21160 .

Doney, P. M., & Cannon, J. P. (1997). An examination of the nature of trust in buyer–seller relationships. Journal of Marketing , 61 (2), 35–51. https://doi.org/10.1177/002224299706100203

Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G * power 3.1: Tests for correlation and regression analyses. Behavior Research Methods , 41 (4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149

Article   PubMed   Google Scholar  

Feng, X. L., Huang, M. X., & Zhang, Y. (2013). Are contradictory consumers’ attitudes more susceptible to external influences: A study of the differences in the composition of different attitudes. Nankai Business Review International , 16 (1), 92–101. https://doi.org/10.3969/j.issn.1008-3448.2013.01.011

Fernandes, J., Segev, S., & Leopold, J. K. (2020). When consumers learn to spot deception in advertising: Testing a literacy intervention to combat greenwashing. International Journal of Advertising , 39 (7), 1115–1149. https://doi.org/10.1080/02650487.2020.1765656

Fiske, S. T., Cuddy, A. J., & Glick, P. (2007). Universal dimensions of social cognition: Warmth and competence. Trends in Cognitive Science , 11 (2), 77–83. https://doi.org/10.1016/j.tics.2006.11.005

Gong, X., Liu, Z., & Wu, T. (2021). Gender differences in the antecedents of trust in mobile social networking services. The Service Industries Journal ,  41 (5 − 6), 400−426. https://doi.org/10.1080/02642069.2018.1497162

Hall, J. A., Dominguez, J., & Mihailova, T. (2023). Interpersonal media and face-to-face communication: Relationship with life satisfaction and loneliness. Journal of Happiness Studies , 24 (1), 331–350. https://doi.org/10.1007/s10902-022-00581-8

Hardin, R. (1992). The street-level epistemology of trust. Politics and Society , 14 (2), 152–176. https://doi.org/10.1177/0032329293021004006

Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Journal of Educational Measurement , 51 (3), 335–337. https://doi.org/10.1111/jedm.12050

Helliwell, J. F., & Putnam, R. D. (2007). Education and social capital. Eastern Economic Journal , 33 (1), 1–19. https://doi.org/10.3386/w7121

Honora, A., Chih, W. H., & Ortiz, J. (2023). What drives customer engagement after a service failure? The moderating role of customer trust. International Journal of Consumer Studies , 47 (5), 1714–1732. https://doi.org/10.1111/ijcs.12939

Jin, L. Y. (2007). The impact of online word of mouth information on consumer purchasing decisions: An experimental study. Economic Management , (22), 36−42. https://doi.org/10.19616/j.cnki.bmj.2007.22.008

Kazemian, A., Hoseinzadeh, M., Banihashem Rad, S. A., Jouya, A., & Tahani, B. (2023). Nudging oral habits; application of behavioral economics in oral health promotion: A critical review. Frontiers in Public Health , 11 , 1243246. https://doi.org/10.3389/fpubh.2023.1243246

Kociatkiewicz, J., & Kostera, M. (2012). Sherlock Holmes and the adventure of the rational manager: Organizational reason and its discontents. Scandinavian Journal of Management , 28 (2), 162–172. https://doi.org/10.1016/j.scaman.2012.01.003

Korotkova, N., Benders, J., Mikalef, P., & Cameron, D. (2023). Maneuvering between skepticism and optimism about hyped technologies: Building trust in digital twins. Information & Management , 60 (4), 103787. https://doi.org/10.1016/j.im.2023.103787

Liu, G. F., & Zhang, M. (2022). A review and prospect of consumer competency. Chinese Journal of Applied Psychology , 28 (2), 147–156. http://www.appliedpsy.cn/CN/Y2022/V28/I2/147

Google Scholar  

Liu, G. F., Li, X., & Meng, Q. X. (2023). How to shop online: The construct and measurement of consumer competency in online shopping. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 17 (2), Article 6. https://doi.org/10.5817/CP2023-2-6

Macready, A. L., Hieke, S., Klimczuk-Kochańska, M., Szumiał, S., Vranken, L., & Grunert, K. G. (2020). Consumer trust in the food value chain and its impact on consumer confidence: A model for assessing consumer trust and evidence from a 5–country study in Europe. Food Policy , 92 , 101880. https://doi.org/10.1016/j.foodpol.2020.101880

Manuela, V. Z., Francisco, J. T. R., & Manuel, P. R. (2019). Towards sustainable consumption: Keys to communication for improving trust in organic foods. Journal of Cleaner Production , 216 , 511–519. https://doi.org/10.1016/j.jclepro.2018.12.129

Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review , 20 (3), 709–734. https://doi.org/10.2307/258792

McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: A trust building model. The Journal of Strategic Information Systems , 11 (3 − 4), 297−323. https://doi.org/10.1016/S0963-8687(02)00020-3

Melović, B., Šehović, D., Karadžić, V., Dabić, M., & Ćirović, D. (2021). Determinants of millennials’ behavior in online shopping–implications on consumers’ satisfaction and e-business development. Technology in Society , 65 , 101561. https://doi.org/10.1016/j.techsoc.2021.101561

Mhlanga, S., & Kotze, T. (2014). Information search, alternatives evaluation, and coping mechanisms of functionally illiterate consumers in retail settings: A developing economy context. Journal of African Business , 15 (2), 136–149. https://doi.org/10.1080/15228916.2014.925363

Min, J., Kim, J., & Yang, K. (2023). CSR attributions and the moderating effect of perceived CSR fit on consumer trust, identification, and loyalty. Journal of Retailing and Consumer Services , 72 , 103274. https://doi.org/10.1016/j.jretconser.2023.103274

Mistry, T. G., Wiitala, J., & Clark, B. S. (2024). Leadership skills and the glass ceiling in event management: A social role theory approach. International Journal of Contemporary Hospitality Management , advance publication online. https://doi.org/10.1108/IJCHM-07-2023-0927

Miyazaki, A. D., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. The Journal of Consumer Affairs , 35 (1), 27–54. https://doi.org/10.1111/j.1745-6606.2001.tb00101.x

Namasivayam, K., & Guchait, P. (2013). The role of contingent self-esteem and trust in consumer satisfaction: Examining perceived control and fairness as predictors. International Journal of Hospitality Management , 33 , 184–195. https://doi.org/10.1016/j.ijhm.2012.08.002

Olya, H., Kim, N., & Kim, M. J. (2023). Climate change and pro-sustainable behaviors: Application of nudge theory. Journal of Sustainable Tourism , advance publication online.   https://doi.org/10.1080/09669582.2023.2201409

Rucker, D. D., Petty, R. E., & Briñol, P. (2008). What’s in a frame anyway? A meta-cognitive analysis of the impact of one versus two sided message framing on attitude certainty. Journal of Consumer Psychology , 18 (2), 137–149. https://doi.org/10.1016/j.jcps.2008.01.008

Saab, A. B., & Botelho, D. (2020). Are organizational buyers rational? Using price heuristics in functional risk judgment. Industrial Marketing Management , 85 , 141–151. https://doi.org/10.1016/j.indmarman.2019.10.001

Sears, D. O., Peplau, L. A., & Taylor, S. E. (1991). Social psychology (7th ed., pp. 188–194). Prentice-Hall, Inc.

Stewart, C. R., & Yap, S. F. (2020). Low literacy, policy and consumer vulnerability: Are we really doing enough? International Journal of Consumer Studies , 44 (4), 343–352. https://doi.org/10.1111/ijcs.12569

Sung, E., Chung, W. Y., & Lee, D. (2023). Factors that affect consumer trust in product quality: A focus on online reviews and shopping platforms. Humanities and Social Sciences Communications , 10 (1), 1–10. https://doi.org/10.1057/s41599-023-02277-7

Sunstein, C. R. (2017). Human agency and behavioral economics: Nudging fast and slow . Springer.

Tahir, M. S., Richards, D. W., & Ahmed, A. D. (2023). The role of financial risk-taking attitude in personal finances and consumer satisfaction: Evidence from Australia. International Journal of Bank Marketing , 41 (4), 787–809. https://doi.org/10.1108/IJBM-09-2022-0431

Tzeng, S. Y., Ertz, M., Jo, M. S., & Sarigöllü, E. (2021). Factors affecting customer satisfaction on online shopping holiday. Marketing Intelligence & Planning , 39 (4), 516–532. https://doi.org/10.1108/MIP-08-2020-0346

Varian, H. R. (2014). Intermediate microeconomics with calculus: A modern approach . W. W. Norton & Company.

Weiss, A., Michels, C., Burgmer, P., Mussweiler, T., Ockenfels, A., & Hofmann, W. (2021). Trust in everyday life. Journal of Personality and Social Psychology , 121 (1), 95–114. https://doi.org/10.1037/pspi0000334

West, T., Butler, D., & Smith, L. (2023). Sludged! Can financial literacy shield against price manipulation at the shops? International Journal of Consumer Studies , 47 (5), 1853–1870. https://doi.org/10.1111/ijcs.12959

Wu, L., Li, Z., Chen, X., & Gong, X. (2020). Dose the compromise effect exist in food consumption behavior? An empirical case study based on pork products. Journal of Agricultural Technology , (09), 102–116. https://doi.org/10.13246/j.cnki.jae.20191205.001

Xin, Z., Liu, G., & Zong, Z. (2023). Feeling and calculation: The impact of the thinking mode on mental budgeting. Current Psychology , 42 , 26514–26526. https://doi.org/10.1007/s12144-022-03689-5

Yoon, J. H., & Kim, H. K. (2023). Why do consumers continue to use OTT services? Electronic Commerce Research and Applications , 60 , 101285. https://doi.org/10.1016/j.elerap.2023.101285

Yuan, X. H., & Xiao, Y. C. (2021). Information accessibility, cognition level and consumer trust of organic agricultural products. Journal of Management , 34 (5), 92–108. https://doi.org/10.19808/j.cnki.41-1408/F.2021.0039

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Lan, Y., Liu, G. Consumers’ rational attitudes toward online shopping improve their satisfaction through trust in online shopping platforms. Curr Psychol (2024). https://doi.org/10.1007/s12144-024-06622-0

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