literature review for online shopping system

Comunicação Pública

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 14 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]

Artigos do mesmo autor

• Música na publicidade: compondo a relação entre marca e consumidor [Texto integral] Music in advertising: composing the relationship between brand and consumer Publicado em Comunicação Pública , Vol.11 nº 20 | 2016
• Patrocínio e influência na atitude relativamente à marca e intenção de compra: caso Nike e Selecção Portuguesa de Futebol [Texto integral] Sponsorship and its influence on attitude towards the brand and purchase intention: Nike and Portuguese Soccer Team case study Publicado em Comunicação Pública , Vol.9 n15 | 2014

Direitos de autor

Apenas o texto pode ser utilizado sob licença CC BY-NC 4.0 . Outros elementos (ilustrações, anexos importados) são "Todos os direitos reservados", à exceção de indicação em contrário.

• Palavras-chave

Números em texto integral

• 2021 Vol.16 nº 30
• 2020 Vol.15 nº 28  | Vol.15 nº 29
• 2019 Vol.14 nº 26  | Vol.14 nº 27
• 2018 Vol.13 nº 24  | Vol.13 nº 25
• 2017 Vol.12 nº 22  | Vol.12 nº 23
• 2016 Vol.11 nº 20  | Vol.11 nº 21
• 2015 Vol.10 nº17  | vol.10 nº 18  | Vol.10 nº 19
• 2014 Vol.9 n15  | Vol.9 nº16
• 2013 vol.8 n13  | vol.8 n14
• 2012 vol.7 n11  | vol.7 n12
• 2011 vol.6 n10  | Especial 01E
• 2010 Vol.5 nº 9
• 2009 Vol.4 nº8 / nº7
• 2008 Vol.3 nº 6
• 2007 vol.3 nº5
• 2006 Vol.2 nº4 / nº3
• 2005 Vol.1 nº1  | Vol.1 nº2

Todos os números

Apresentação.

• Projeto Editorial
• Equipa Editorial
• Comissão Editorial
• Comissão Científica
• Revisores 2009-2020
• Normas de publicação
• Declaração de normas éticas de publicação e boas-práticas editoriais

Informações

• Menções legais e creditos

Chamadas para contribuições

• Chamadas fechadas
• Chamadas abertas

Newsletter informativa

• Newsletter da OpenEdition

Filiações/parceiros

ISSN electrónico 2183-2269

Consultar a ficha no catálogo OpenEdition  

Mapa do site  – Feed RSS

Privacy Policy  – About Cookies  – Assinalar um problema

Subscrevemos OpenEdition  – Editado com Lodel  – Acesso reservado

Você sera redirecionado para OpenEdition Search

Exploring Key Factors for Customer Satisfaction in Online Shopping: A Systematic Literature Review

• January 2020
• 6(1):163-190

• University of Sri Jayewardenepura

Abstract and Figures

Discover the world's research

• 25+ million members
• 160+ million publication pages
• 2.3+ billion citations
• Meth Eur J Res Meth Behav Soc Sci

• Maryam Heydari
• Haliyana Khalid
• Laura Lončarić
• Matej Višnjić

• mohammad shaykhzade

• Lis Tatin Herdinadiatin
• Ario Purdianto
• Nadhira Azzahra
• Nebojša Vasić
• Milorad Kilibarda
• Tanja Kaurin

• Ghanya Khamies Al Kalbani

• J PLAN EDUC RES

• Hasina Mumtaz

• Anayet Karim
• Saeed Fathi

• Urvashi Tandon

• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

A Systematic Review and Meta-Analysis of the Latest Evidence on Online Shopping Intensity

17 Pages Posted: 24 Apr 2023

Omed Rafiq Fatah

Cihan university Sulaymaniyah

Nameer Hashim Qasim

Computer Science department, Cihan University

Natalia Bodnar

Al-Rafidain University College

Aqeel Mahmood Jawad Abu-Alshaeer

Omar saad ahmed.

Al-Turath University College

Date Written: April 11, 2023

Information and communication technologies have had an upward trend over the past decades. Online shopping provides flexibility in the place and time of shopping activities. The current study applies the concepts and guidelines of the systematic review and meta-analysis to the most recent evidence on the intensity of online shopping, intending to resolve the controversies arising from past research in this area. Preferred Reporting Items for Systematic Reviews Meta-Analyses and Meta-analyses of Observational Studies in Epidemiology (PRISMA and MOOSE, respectively) were used to conduct this review. To evaluate the association between online shopping intensity and various influencing factors, we systematically searched the electronic database, including Scopus, Medline/PubMed, EMBASE, and the Web of Sciences (WOS), "online buying," "online purchasing," "online shopping" until Jan 2023. There is no constraint on period or language, and more publications were found by manually searching the citations list of chosen articles. Overall, 5708 studies were collected. After removing duplicated studies (274), 5434 studies have remained. During screening titles and abstracts, 250 studies were considered potentially eligible. Subsequently, 152 studies were excluded in full-text screening, including 98 in the evidence synthesis. The results related to the combined effect size of the variables showed that the satisfaction variable, followed by perceived value and shopping experience, have the most significant effect on online shopping intention. Also, the results showed that the effect sizes of other variables with low, medium, and high impact intensity were substantial and acceptable.

Keywords: Online shopping, Shopping intention, Combination of results, Meta-analysis

JEL Classification: Z00

Suggested Citation: Suggested Citation

Cihan university Sulaymaniyah ( email )

Bakrajo Department of Law Sulaymaniyah, Sulaymaniyah 46001 Iraq

Computer Science department, Cihan University ( email )

Sulaimaniya campus 46001 Suleymanieh, 46001 Iraq

Natalia Bodnar (Contact Author)

Al-rafidain university college ( email ), al-turath university college ( email ), do you have a job opening that you would like to promote on ssrn, paper statistics, related ejournals, advertising, marketing & strategic communication ejournal.

Subscribe to this fee journal for more curated articles on this topic

Information Systems eJournal

Consumers’ rational attitudes toward online shopping improve their satisfaction through trust in online shopping platforms

• Published: 02 September 2024

Cite this article

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

11 Accesses

Explore all metrics

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Consumer Product Evaluation Updating: The Impact of Online and Interpersonal Social Influence on Evaluation Certainty

Factors affecting customer intention to return in online shopping: the roles of expectation disconfirmation and post-purchase dissonance

Online Consumer Perceptions of Retailer Familiarity and Price Discrimination

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

Download references

Acknowledgements

The data and analysis procedure can be obtained from the corresponding author.

Author information

Authors and affiliations.

School of Economics and Management, Shanghai Maritime University, No.1550 HaiGang Avenue, Pudong New Area, Shanghai, 201306, China

Yaxing Lan & Guofang Liu

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Guofang Liu .

Ethics declarations

This study complied with APA ethical standards.

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

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

Download citation

Accepted : 23 August 2024

Published : 02 September 2024

DOI : https://doi.org/10.1007/s12144-024-06622-0

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Rational attitude
• Online shopping
• Consumer satisfaction
• Electronic commerce
• Find a journal
• Publish with us
• Track your research

To read this content please select one of the options below:

Please note you do not have access to teaching notes, what drives consumers to shop online a literature review.

International Journal of Service Industry Management

ISSN : 0956-4233

Article publication date: 1 February 2004

While a large number of consumers in the US and Europe frequently shop on the Internet, research on what drives consumers to shop online has typically been fragmented. This paper therefore proposes a framework to increase researchers’ understanding of consumers’ attitudes toward online shopping and their intention to shop on the Internet. The framework uses the constructs of the Technology Acceptance Model (TAM) as a basis, extended by exogenous factors and applies it to the online shopping context. The review shows that attitudes toward online shopping and intention to shop online are not only affected by ease of use, usefulness, and enjoyment, but also by exogenous factors like consumer traits, situational factors, product characteristics, previous online shopping experiences, and trust in online shopping.

• Information media

Perea y Monsuwé, T. , Dellaert, B.G.C. and de Ruyter, K. (2004), "What drives consumers to shop online? A literature review", International Journal of Service Industry Management , Vol. 15 No. 1, pp. 102-121. https://doi.org/10.1108/09564230410523358

Emerald Group Publishing Limited

Copyright © 2004, Emerald Group Publishing Limited

Related articles

All feedback is valuable.

Please share your general feedback

Report an issue or find answers to frequently asked questions

Contact Customer Support

TechRepublic

Status and scope of online shopping: an interactive analysis through literature review.

Online shopping is a current phenomenon which has developed a great importance in the modern business environment. The evolution of online shopping has opened the door of opportunity to exploit and provide a competitive advantage over firms. This paper analyzed the different issue of online shopping. The paper aims to provide theoretical contribution in understanding the present status of online shopping and explores the factors that affecting the online shopping. The paper provides insights into consumers’ online shopping behaviors and preferences. Moreover, paper also identify the hurdles that customers’ face when they want to adopt internet shopping as their main shopping medium.

Subscribe to the Cybersecurity Insider Newsletter

Strengthen your organization's IT security defenses by keeping abreast of the latest cybersecurity news, solutions, and best practices. Delivered every Monday, Tuesday and Thursday

Resource Details

Create a techrepublic account.

Get the web's best business technology news, tutorials, reviews, trends, and analysis—in your inbox. Let's start with the basics.

* - indicates required fields

Sign in to TechRepublic

Lost your password? Request a new password

Reset Password

Please enter your email adress. You will receive an email message with instructions on how to reset your password.

Check your email for a password reset link. If you didn't receive an email don't forgot to check your spam folder, otherwise contact support .

Welcome. Tell us a little bit about you.

This will help us provide you with customized content.

Want to receive more TechRepublic news?

You're all set.

Thanks for signing up! Keep an eye out for a confirmation email from our team. To ensure any newsletters you subscribed to hit your inbox, make sure to add [email protected] to your contacts list.

IEEE Account

• Change Username/Password
• Update Address

Purchase Details

• Payment Options
• Order History
• View Purchased Documents

Profile Information

• Communications Preferences
• Profession and Education
• Technical Interests
• US & Canada: +1 800 678 4333
• Worldwide: +1 732 981 0060
• Contact & Support
• About IEEE Xplore
• Accessibility
• Terms of Use
• Nondiscrimination Policy
• Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2024 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

BioResources

• About the Journal
• Authors & Reviewers
• How to Self-Register
• Full Site Navigation
• Editorial Board
• Meet the Staff
• Editorial Policies
• General Instructions
• Ethics & Responsibilities
• Article Preparation
• Submission Instructions
• Acknowledgment of your Peer-Reviewing
• Writing Style Suggestions
• Reviewer Guidelines
• Back and Current Issues
• Scholarly Reviews
• Special Conference Collection Issues
• Competition Print Edition
• FRC: Pulp and Paper Fundamental Research Symposia Proceedings
• Paper Manufacturing Chemistry
• BioResources Early Career Investigator Award
• Distance Education: Online Masters Degree & Individual Courses
• Upcoming Conferences
• Hands-On Courses
• Affiliate Journal

Furniture online consumer experience: A literature review

In recent years, people’s acceptance of online shopping has increased markedly with the gradual maturing of e-commerce. The furniture industry in China, along with many other countries, is paying increased attention to the online retail business. The furniture online consumption experience has attracted attention both in academic and industrial fields. The purpose of this paper is to provide a literature review of the furniture online consumption with an aim to extend the concept of consumer experience to the context of online furniture consumption. The paper offers three important contributions for both academics and practitioners. First, it analyzes the main influencing factors of the consumer experience concerning wood furniture online consumption in China. And secondly, it proposes a conceptual framework of furniture online consumer experience (FOCE), which divides online consumption experience into three dimensions: perceived risk experience, emotional experience, and new technology interactive experience. Finally, from a managerial perspective, the authors put forward constructive strategies in terms of furniture online sales. The findings of this study afford practical implications for the improvement of the online shopping experience of consumers for furniture companies.

Full Article

Furniture Online Consumer Experience: A Literature Review

Shuangjie Zhang, Jiangang Zhu,* Guokun Wang, Shuangyue Reng,and Huan Yan

DOI: 10.15376/biores.17.1.1627-1642

Keywords: Furniture consumption; Online shopping; Consumer experience; Interactive experience

Contact information: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China; *Corresponding author: [email protected]

INTRODUCTION

Since the advent of e-commerce, China’s online retail industry has developed rapidly, and consumers have a greater interest in online shopping. The “Internet Plus” policy announced by Chinese government in 2015, encourages people to use network information technology (IT) to promote innovations in e-commerce and online shopping (Xiong et al. 2017). The proportion of furniture companies that choose to sell furniture online is higher than before; as of 2020, the market share of online Chinese brands in the furniture industry has reached more than 80% (Alibaba Research Institute 2020). According to the China National Bureau of Statistics, the number of furniture markets in China has gradually decreased, from 179 in 2016 to 149 in 2020 (China National Bureau of Statistics). The scale of furniture e-commerce is becoming increasingly larger (Qianzhan Industry Research Institute 2018), from 49.47 billion in 2011 to 165.06 billion in 2017. The scale of Chinese furniture e-commerce market is shown in Fig. 1. E-commerce in China’s furniture industry is mainly based on the business-to-customer (B2C) model. The following three main approaches have emerged in the online retail market under this model.

The first approach is the furniture brands’ self-built electronic mall and self-developed mobile application. In this mode, consumers can complete the transaction by browsing the product information on the website or application, selecting the product and the delivery address, and completing the payment. In the context of sustainability and customers’ demand on green consumption, the transition towards green manufacturing of furniture industry increasingly urgent than ever. (Xiong et al. 2020 and Wang et al. 2020). This way makes the process of furniture retailing and purchasing informatized and networked, saves a certain amount of manpower and material costs, and brings consumers a unique and complete consumer experience. But the subsequent development and post-maintenance of the website and application costs also discourage most small businesses, since there is a need for continuous investment in labor and material costs related to networking.

Fig. 1. China Furniture E-Commerce Market Scale

The second approach is to integrate sales on e-commerce platforms such as Taobao and JD.com. Alibaba and JD account for more than 90% of China’s online retail market share (China Internet Information Center 2015). E-commerce platforms provide commodity information a display space and transaction methods for the settled stores. At the same time, the e-commerce platform has gradually standardized the management of furniture stores, which has made the service offering by various furniture brands online stores become more comprehensive and standardized, reducing the psychological risks of consumers buying furniture online. However, it has also caused the service promised by the retailers on the product display page to become more uniform with higher homogeneity.

The third approach is mobile commerce platform sales. With the vigorous development of new media technology, new media platforms, such as Weibo, WeChat Mini Programs, and TikTok, have launched commodity retail functions. In particular, the more intuitive way of displaying goods, such as live broadcast selling, which is an emerging marketing method that uses Internet platforms to introduce and display products to be sold in real time (Liu and Shi 2020). Furniture companies in China are actively participating in this new marketing method. According to Xiao and Yu (2017), although there are various forms of new media, it is found that the most suitable for information spreading in the furniture industry is still graphic, live broadcast, followed by short video.

There have been many studies that have demonstrated the influence of consumer experience on consumer satisfaction and repurchase intentions (George 2002; Rose et al . 2011). In a saturated and highly competitive market, improving the online shopping experience is important for companies to provide more special and differentiated products and services (Rose et al . 2011). The research of Janda and Ybarra (2005) purports that excellent consumer experience has a positive impact on consumer satisfaction. Khalifa and Liu (2007) defined repurchase intention as “using online channels to buy goods from specific retailers”. After investigation, it was found that positive online consumer satisfaction is positively correlated with repurchase willingness (Khalifa and Liu 2007). In the context of the fierce competition in the Chinese furniture industry and the highly saturated market, the current article analyzes the components of online consumer experience and their impact and provides some suggestions for furniture companies to optimize customer service.

The aim of this paper is to provide a comprehensive review of contemporary literature that informs our understanding of the antecedents and consequences of consumer experience (CE) in the furniture online consumption context. The review is undertaken in hope of highlighting the importance of this emerging area of interest. This paper expects to carry out several explorations. The first is adding the knowledge of the subject of CE in the furniture online consumption context. The paper extends the understanding of the factors related to online consumer experience from the perspective of the furniture consumption. The second is to propose a theoretical framework for furniture online consumer experience (FOCE) through a summary of the literature on furniture online consumption. Third, the theoretical framework proposed in the thesis puts forward many suggestions to improve furniture online consumption experience for retailers in the Chinese furniture industry.

The structure of the paper is as follows. The first section presents the research method used for this literature review. A literature review of the concept of FOCE is then provided, and the proposed conceptual framework is presented. The following section provides the substantive literature review, structured according to the framework. Finally, the paper ends with a summary of the conclusions that can be drawn from the review and makes proposals for further research.

LITERATURE REVIEW

A systematic review of the literature was undertaken using the following method. A review question was identified by the research team: What is the role of consumer experience in the furniture online consumption environment? Then search keywords were drawn up by the team, which included: furniture consumption; furniture industry; furniture online consumption; consumer experience; online consumer experience; interactive experience; and augmented reality. References came from Google Scholar, Web of Science, and China National Knowledge Infrastructure (CNKI).

The articles were screened according to the topics expressed in the title and abstract of the paper. The content analysis of selected papers was done manually, and data extraction forms were used to summarize key data, such as key findings and methodological characteristics. This enables researchers to identify the overall nature, epistemological assumptions, and methodological characteristics of existing research. Furthermore, the team created a list to categorize the content of the forms according to the research direction.

This paper focuses on the consumer experience in furniture online purchase environment and the features of furniture consumption in China. Therefore, the authors paid equal attention on the concept of consumer experience, OCE, and furniture retail in China to propose a theoretical framework to systematically answer the review questions mentioned above.

The Concept of FOCE

There have been many studies on the concept of consumer experience (CE) in the fields of consumer marketing, service delivery, tourism, and retail before the advent of the Internet. With the rapid development of e-commerce, research on retail consumer experience has gradually shifted from offline to online. However, people’s attitudes towards the online shopping experience are often related to the types of goods, i.e. , people are more likely to perceive the shape and weight of electronic products, and they have a higher tactile demand for clothes (Li et al . 2001). Because of the large volume and price of furniture products, people rely much on consumer experience (Lin et al . 2019) to perceive the spatial and tactile elements of furniture during the consumption process.

Many studies have recognized the importance of CE in the retail market (Grewal et al . 2009). Furniture products are suitable for China’s e-commerce platform, as large-scale durable products, under certain conditions (Li et al . 2020). However, CE is still an unfamiliar concept for online furniture retail, which is not conducive to the establishment of a theoretical framework. Next in this paper, a certain literature review and summary of the concepts of CE and OCE is given, and the theoretical framework of FOCE is proposed.

Consumer Experience

Meyer and Schwager (2007) defined consumer experience as the customer’s internal and subjective response to any direct or indirect contact with the company. Similarly, Gentile et al . (2007) argued that consumer experience comes from a series of interactions between consumers and services, products, companies, or their organizations. The above literature analyzes the source of consumer experience from the perspective of the consumption process.

In terms of the dimensions of consumer experience, Babin et al . (1994) proposed that consumer experience is composed of utilitarian elements and hedonic elements. They further demonstrated the rational combination of the two elements of the consumer experience under specific circumstances. Berry et al. (2006) made important contributions. According to Berry et al . (2006), consumers often evaluate their consumption experience through functional clues (meeting customer expectations), mechanic clues (influencing first impressions, expectations, and value creation), and humanic clues (exceeding customer expectations) in the process of interacting with organizations. The importance of this classification is to classify the consumer experience as different aspects of the contact between consumers and organizations.

Based on the above literature review, the overall consumer experience can be defined as: customer experience is the internal and subjective reaction of any direct or indirect contact between customers and the company. Direct contact usually occurs during purchase, use, and maintenance, a process usually initiated by the customer. The most common way of indirect contact is contact with the company’s products, services, or brands, in the form of word-of-mouth recommendations or advertisements, news reports, reviews, etc . The process of generating consumer experience includes the first impression generated by indirect contact, consumer expectations, to functional satisfaction generated by direct contact, and finally the consumer’s evaluation of the consumer behavior after using the product and service (whether it meets or exceeds the consumer’s expectations).

Online Consumer Experience

With the rapid development of commerce online, increased attention is being paid to the research of consumers’ online experience. Consumer experience in the context of e-commerce is an important factor restricting the development of Chinese furniture e-commerce (Niu and Liu 2017). Therefore, online consumer experience has become an important concept, especially in the context of online shopping. It is believed that the offline context can provide a richer information display method than online. The online environment can only display the brand through an audio-visual way, but a range of visible devices can be used to present the brand in an offline environment.

Long (2004) believes that the online consumer experience is mainly affected by the trustworthiness of the website, convenience, customer autonomy, and the relationship between the website and the customer. Constantinides and Geurts (2005) believe that online consumer experience is related to website interactivity, aesthetics, trust, convenience, and marketing. Although the above authors put forward the factors affecting online consumer experience, these works did not propose a reliable conceptual model of online consumer experience. Frow and Payne (2007) proposed that the rational, cognitive process, and the perceptual and emotional process are all part of the formation of consumer experience. Similarly, Hansen (2005) argued that cognitive and emotional identification, as well as the interaction of these, is an appropriate method to understand consumer experience. With the recent rapid development of the internet, more authors have shifted their research focus from offline to online. Many authors have proposed their own online consumer experience models with reference to the Frow and Payne (2007) model. The table below summarizes some of them.

Table 1. Dimensions of Online Consumer Experience

Compared with the offline environment, the online consumer experience places more emphasis on considering the enterprise’s application of data and technology to the consumer level, such as convenience, interactivity, process experience, technical experience, etc . (Tan 2019).

A CONCEPTUAL FRAMEWORK OF FOCE

Previous reviews of the literature mainly have focused on consumer experience and online consumer experience, while the focus of this article is on the particularity of online consumer experience in furniture consumption. Furniture products have the following characteristics due to their high prices: low standardization, high transportation costs, and many additional services.

The online consumption of furniture has the following characteristics. First, consumers are more cautious when buying furniture products online, hoping to obtain more product information. Online consumers want to check the material, workmanship, style, and shape of furniture in offline physical stores (Cao et al . 2014).

Secondly, delivery restricts online sales of furniture. This is because furniture products have the characteristics of larger size, heavier weight, and relatively higher value. Moreover, furniture e-commerce companies in China are mainly small and medium-sized enterprises. Most of them complete the logistics process through third-party logistics companies or joint distribution. The logistics links are prone to differences in reliability and response. It is difficult for consumers to obtain the fast and convenient logistics services they want (Zhang and Xu 2019).

Finally, spiritual connotation of furniture consumption can bring users a consumption experience similar to luxury goods. It is believed that furniture consumption tends to become symbolic (Dou and Chen 2014). As China enters the consumer society, more consumers are purchasing furniture to show their social status and lifestyle, and furniture consumption is increasingly showing a trend of pursuing spirit demand rather than material demand.

The importance of consumption experience lies in the fact that in a highly competitive and saturated market, enterprises hope to provide differentiated products by enriching basic products and services (Rose et al . 2011). It is useful to understand the dimension of consumption experience from the perspective of the relationship between enterprises and consumers, because the concept of consumption experience comes from this. De Keyser et al . (2015) think that consumers are active participants in the shopping experience, and they pursue cognitive and emotional goals in online and offline shopping (Kawaf and Tagg 2017).

The consumer’s cognitive experience is related to the perceived value of consumers. Wang (2008) define the consumer’s perceived value as the overall evaluation of the trade-off between the perceived quality of the received product or service and the total cost of obtaining the product or service. Many scholars define perceived value separately as perceived advantage and perceived risk. Forsythe et al . (2006) define perceived advantage as the sum of consumer needs or desires and online shopping advantage or satisfaction. Perceived advantages include advantages related to online shopping experience, including convenience, price comparison, time saving, return policies, shopping convenience, entertainment, and enhanced consumer-retailer relations (Elwalda et al . 2016). With regard to the elements of perceived risk, Wang et al . (2006) pointed out that the quality of products or services, personal privacy, and security are frequent risk elements. The basic concerns of consumers are those of conducting online financial transactions. When the authors discuss online furniture consumption, the boundary between the two concepts does not seem to exist. Online furniture consumption is different from other products; consumers pay more attention to the cognitive experience, such as the shape, size, and quality of the furniture (Dai 2013). These factors are often the premise for consumers to determine whether goods are available or not to avoid economic losses and the failure of return services. Therefore, this paper refines the cognitive experience in online furniture consumption into a low-risk experience perceived by consumers.

The emotional experience is more personal and subjective, and shopping experience during shopping relies on entertainment and escapism (De Keyser et al . 2015). These aspects bring more entertainment to customers. Jeong et al. (2009) tested four experience areas (entertainment, educational, escapist, and aesthetic experiences) of Pine and Gilmore (1999) in the online shopping environment. In the online sales of furniture in China, the best-selling of various styles of furniture demonstrates the consumers’ demand for the aesthetic experience of furniture. The major e-commerce platforms hold a variety of furniture purchase experience activities every year to meet consumers’ demand for shopping and entertainment.

Most previous research divided online consumption experience into cognitive experience and emotional experience. This paper argues that the experience brought by new technology cannot be ignored; the application of high-end technology is the inevitable way to meet the needs of consumers (Chen and Wu 2018). According to the degree of interaction between consumers and goods, Li et al . (2001) divides consumer experience into direct experience, indirect experience, and virtual experience, in which the experience brought to consumers by virtual experience often combines cognitive experience and emotional experience. The virtual fitting technology defined as VTO (virtual try-on) has both use value and hedonic value (Zhang et al . 2019), which means that the virtual experience involves both cognitive and emotional experience. Similarly, another virtual technology defined as AR (augmented reality) has similar characteristics. Poushneh and Vasquez-Parraga (2017) pointed out that AR can reflect four product characteristics: aesthetic quality, pragmatic quality, stimulating hedonistic quality, and identifying hedonistic quality. As augmented reality technology becomes more affordable, many retailers, such as IKEA, have implemented augmented reality in their experiential retail channels. Therefore, this paper takes the new technology interactive experience as the third part of the online furniture consumption experience.

Based on the above literature review on the characteristics of online furniture consumption, this paper proposes the theoretical framework of furniture online consumption experience in Fig. 2 based on the theoretical structure of Frow and Payne (2007). This framework divides the furniture online consumption experience into three parts: perceived low-risk experience, emotional experience, and new technology interactive experience. There are several influencing elements in each experience.

Fig. 2. A conceptual framework of FOCE

Perceived Low-risk Experience

Bhatnagar et al. (2000) and Lim (2003) put forward the concept of risk perception when shopping online. They believe that it has an important influence on consumers’ willingness to interact online. Perceived risk of online shopping is primarily the uncertainty of product information, followed by the severity of the consequences of purchase (Cases 2002). In China, online furniture consumers are mainly concerned about the product inconsistency with the description and quality issues (Li et al. 2016). This paper combines various viewpoints in the literature and divides the perceived risk experience into three aspects: the reliability of product information, logistics and delivery, and after-sales service (repair and return). The reasons for selecting these three factors will be discussed separately below.

When shopping online, the reliability of furniture product information is important, because furniture products have larger size, their materials are highly relevant to people’s daily life, and it is important that the product matches the home environment when placed in the domestic environment after purchase. Patro and Katta (2020) found that among perceived risks, the greatest impact on consumers is psychological risk, and an important part of psychological risk is whether the retailer’s commitment is consistent with the facts (Zhang et al . 2011). Therefore, for online furniture consumption, the reliability of product information provided by online retailers is crucial.

Another factor that can bring lower perceived risk to consumers is on-time delivery. Delivery has the greatest impact on consumers’ perceived benefits online (Patro and Katta 2020), which means that excellent delivery can reduce consumer perceptions risk. On the contrary, any failure or delay in delivery will leave a bad evaluation for online consumers and reduce repurchases (Reichheld and Schefter 2000). Similarly, Rao et al . (2011) identified that the delay in the delivery of goods will reduce the frequency of online purchases by consumers in the future. In other words, online retailers can improve the consumer experience and repurchase rate by promising a shorter delivery time on the website and fulfilling these promises.

The last factor that affects consumers’ perceived risks is the after-sales experience, including returns and installation, maintenance services, etc . Furniture products (such as beds, wardrobes, etc .) often require professionals to complete the installation work. After consumers purchase furniture online, if retailers can provide door-to-door installation services, it will increase consumer satisfaction and repurchase rates (Zhang and Xu 2019). In addition, after purchasing furniture online, if consumers are not satisfied with the product after receiving the goods, they often will not choose to return the goods because of the inconvenience of returning the goods (Dai 2013). This also leads to a bad online consumer experience.

The above discussion of perceived risk experience mainly involves the cognitive part of online consumer experience, and the research of Barari et al . (2020) shows that consumers tend to pursue emotional experience when sufficient cognitive value has been obtained during their consumption experience. Next the emotional experience part of the furniture online consumer experience is discussed.

Emotional Experience

Emotional experience depends on entertainment and escapism in the shopping process (De Keyser et al . 2015). The emotional experience is personalized and subjective, bringing fun and pleasure to customers (Holbrook and Hirschman 1982). Users’ different preferences for furniture products are related to the positive, neutral, or negative state of their emotions (Yang et al . 2019). When people are engaged in entertainment activities, such as the popular online celebrity live broadcasts in China, it is easy for this to become an incentive for consumers to buy goods.

Another factor related to emotional experience is online trust. Many studies have pointed out that due to more unknowns, compared with face-to-face retail, the online environment requires a higher degree of trust (Corbitt et al . 2003; Van der Heijden et al. 2003). Van der Heijden et al . (2003) shows that a high degree of trust can reduce consumers’ concerns about product performance and retailer policies.

There have been many academic studies on the source of online trust. Lv et al . (2016) argues that real-time communication between buyers and sellers through online chat services reduces the uncertainty of buyers in making purchasing decisions. Similarly, Mero (2018) proved the positive impact of two-way communication on trust through empirical research.

Perceived interaction is the premise of trust based on interpersonal relationships. Online consumers form online trust in websites through the three aspects of perceptual interaction (perceived interactivity, perceptual reactivity, and perceptual personalization) (Wu et al . 2010). The rise of the internet has brought the need for interactivity in digital media and digital technology researching background. A review of the new contributions of some new interactive technologies to the online consumer experience will be discussed next.

New Technology Interactive Experience

Liu and Shrum (2002) define interactivity as “the degree to which two or more communicating parties can interact, their role on the communication medium, the role of messages, and the degree to which this influence is synchronized.” They also proposed three aspects of interaction: active control (user’s ability to voluntarily participate in and influence communication with tools); two-way communication (two-way information flow); and synchronization (the speed of interaction). Chinese customers’ cognitions around products have changed from store + facade to reality + VR, which gives consumers a different experience via VR (Xiong et al. 2017). Traditional product information acquisition is often passive and single (only through sound and video acquisition), but the augmented reality technology that has gradually attracted the attention of academia recently seems to be suitable for online sales: shopping in the context of enhanced interactive technology can arouse consumers’ greater purchase intentions than passively accepting product information display (Kim and Forsythe 2008).

To understand more concretely, the current authors will use AR as an example to describe the innovation of new technologies in online consumer experience. Poushneh and Vasquez-Parraga (2017) proposed that AR is an interactive technology that can overlay virtual 3D models into the real environment. Users can rotate, move, and zoom in and out in the 3D model to change its state in the real environment.

On the one hand, AR does have some similarities with the risk perception experience and emotional experience. In terms of risk perception experience, the virtual try-on application can provide clues about the physical properties of the product to help consumers evaluate the product more completely (Dennis et al . 2010). Some previous studies have found evidence that virtual try-on may reduce the likelihood that consumers may perceive clothes purchased online as ill-fitting (Shim and Lee 2011; Kim 2016). In terms of emotional experience, Watson et al . (2020) argue that AR seems to provide a happier experience rather than a utilitarian experience. It is also believed that AR creates a rich sensory experience and thus closer emotional responses. Both those with strong or weak hedonistic motives can have fun from AR shopping applications, and those with strong hedonistic motives are more obvious.

In contrast, AR technology seems to explore some new forms of experience, and virtual try-on applications can further enhance the shopping experience. Users can share the results of fittings with friends and family easily (Dennis et al . 2010). Therefore, it can become a social channel, especially when combined with social media applications, to provide online consumers a pleasant shopping experience by meeting their social needs.

In the furniture industry, the furniture brand IKEA has developed the AR application IKEA Place, which can automatically scan the floor in the scene through the mobile phone camera and place the desired product model in the real scene captured by the camera, effectively enhancing the reality sense. The goods added to the scene can be directly clicked to view the product information and purchase, which greatly reduces the process of collecting information, evaluating purchase risks, purchasing and installing, and evaluating purchase results in the consumer process. It brings consumers a new and fast experience. When using the IKEA Place application, users will feel greater confidence and greater purchasing convenience (Alves and Luís Reis 2020).

CONCLUSIONS

• A review of key literature is presented with an aim to give insight and direction to an understanding of the online furniture purchases and online consumption experience in China. The three main influencing factors of the consumer experience on Chinese furniture product line can be drawn: (1) Consumers hope to access more furniture information such as materials, style, and size before buying furniture; (2) Consumers want to get a better delivery service and after-sales return service; and (3) Consumers have gradually enhanced demand for entertaining furniture products. This paper addresses the adaptability of the online consumer experience model in the Chinese furniture industry by expanding the theoretical structure of Frow and Payne (2007).
• A conceptual model of furniture online customer experience (FOCE) has been proposed in this work. According to FOCE, the furniture online consumer experience can be divided into three parts: (1) perceived low-risk experience, (2) emotional experience, and (3) new technology interactive experience. In the context of the fast-growing Chinese furniture e-commerce market, consumers have a strong demand for new consumer experiences. The new technology interactive experience is considered as a new consumption experience type due to its scarcity in online consumption experience in research, although the new technologies interactive experience often combines a perceived experience and emotional experience, and these are often difficult to segment.
• Furniture companies in China should take solid measures in online product display, size customization, logistics, door-to-door installation, after-sales, and other online value-added services. The offline store appointment experiences also are helpful to minimize consumers’ psychological expectations of risks associated with online shopping. Furthermore, surveying consumers’ furniture style preferences and organizing brand-related entertainment activities can be more conducive to meeting consumers’ emotional needs. Finally, the new technologies, such as AR, have revolutionary advantages in improving the high-level experience brought by the existing services and brands of e-commerce platforms. Furniture companies in China should therefore pay more attention to improvement of the user consumption experience brought by related new technologies.
• This article has attempted to discuss the essence of consumer experience in furniture online consumption by proposing a theoretical framework. There is no denying that the proposed framework is only conceptual; thus, subsequent development and empirical tests are required to establish more systemic understanding.

ACKNOWLEDGMENTS

The authors are grateful the support of the Joint Research program of Nanjing Forestry University, Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, and Sino-foreign Cooperation in Running Schools of Jiangsu Province, Jiangsu, China.

REFERENCES CITED

Alibaba Research Institute (2020). “2020 China consumer brand development report,” (https://file.01caijing.com/attachment/202005/1215D966F6CC4F3.pdf), Accessed 31 May 2020.

Alves, C., and Luís Reis, J. (2020). “The intention to use e-commerce using augmented reality – The case of IKEA Place,” in: Information Technology and Systems . ICITS 2020. Advances in Intelligent Systems and Computing (Vol. 1137), Á. Rocha, C. Ferrás, C. Montenegro Marin, and V. Medina García (eds.), Springer, Cham, Switzerland, pp. 114-123. DOI: 10.1007/978-3-030-40690-5_12

Babin, B. J., Darden, W. R., and Griffin, M. (1994). “Work and/or fun: Measuring hedonic and utilitarian shopping value,” Journal of Consumer Research 20(4), 644-656. DOI: 10.1086/209376

Barari, M., Ross, M., and Surachartkumtonkun, J. (2020). “Negative and positive customer shopping experience in an online context,” Journal of Retailing and Consumer Services 53(1), Article ID 101985. DOI: 10.1016/j.jretconser.2019.101985

Berry, L. L., Wall, E. A., and Carbone, L. P. (2006). “Service clues and customer assessment of the service experience: Lessons from marketing,” Academy of Management Perspectives 20(2), 43-57. DOI: 10.5465/amp.2006.20591004

Bhatnagar, A., Misra, S., and Rao, R. (2000). “On risk, convenience, and internet shopping behaviour,” Communications of the ACM 43(11), 98-105. DOI: 10.1145/353360.353371

Bi, D., and Qiu, C. (2014). “Research on the influence mechanism of e-commerce business-customer interaction on customer experience,” China Software Science 2014(12), 124-135. DOI: 10.3969/j.issn.1002-9753.2014.12.012

Cao, Y., Wu, Z., Yang, B., Li, X., and Li, X. (2014). “Research of status quo and promotion programs of Hongmu furniture e-commerce,” Furniture 35(5), 8-14. DOI: 10.16610/j.cnki.jiaju.2014.05.014

Cases, A. (2002). “Perceived risk and risk-reduction strategies in internet shopping,” International Review of Retail Distribution and Consumer Research 12(4), 375-394. DOI: 10.1080/09593960210151162

Chen, Y., and Wu, Z. (2018). “Study on the application of particle swarm optimization in the virtual reality of the modified wood furniture,” Journal of Intelligent and Fuzzy Systems 35(3), 2741-2747. DOI: 10.3233/JIFS-169626

China National Bureau of Statistics(2021). “The number of China’s furniture market in the past five years,” (https://data.stats.gov.cn/easyquery.htm?cn= C01&zb=A0I0901&sj=2020), Accessed 19 December 2021.

Constantinides, E., and Geurts, P. (2005). “The impacts of web experience on virtual buying behavior: An empirical study,” Journal of Customer Behavior 4(3), 307-336. DOI: 10.1362/147539205775181249

Corbitt, B. J., Thanasankit, T., and Yi, H. (2003). “Trust and e-commerce: A study of consumer perceptions,” Electronic Commerce Research and Applications 2(3), 203-215. DOI: 10.1016/S1567-4223(03)00024-3

Dai, L. (2013). “The present and the future of the electronic commerce of Chinese furniture industry,” Furniture 34(1), 68-78. DOI: 10.16610/j.cnki.jiaju.2013.01.007

De Keyser, A., Lemon, K. N., Klaus, P., and Keiningham, T. L. (2015). A Framework for Understanding and Managing the Customer Experience (Report No. 15-121), Marketing Science Institute, Cambridge, MA, USA.

Dennis, C., Morgan, A., Wright, L. T., and Jayawardhena, C. (2010). “The influences of social e-shopping in enhancing young women’s online shopping behaviour,” Journal of Customer Behaviour 9(2), 151-174. DOI: 10.1362/147539210X511353

Dou, L., and Chen, Y. (2014). “Review on Chinese furniture’s symbolic consumer behavior,” Furniture and Interior Design 2014(1), 82-83. DOI: 10.16771/j.cnki.cn43-1247/ts.2014.01.029

Elwalda, A., Lü, K., and Ali, M. (2016). “Perceived derived attributes of online consumer reviews,” Computers in Human Behavior 56, 306-319. DOI: 10.1016/j.chb.2015.11.051

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 20(2), 55-75. DOI: 10.1002/dir.20061

Frow, P., and Payne, A. (2007). “Towards the ‘perfect’ customer experience,” Journal of Brand Management 15(2), 89-101. DOI: 10.1057/palgrave.bm.2550120

Gentile, C., Spiller, N., and Noci, G. (2007). “How to sustain the customer experience: An overview of experience components that co-create value with the customer,” European Management Journal 25(5), 395-410. DOI: 10.1016/j.emj.2007.08.005

George, J. F. (2002). “Influences on the intent to make internet purchases,” Internet Research 12(2), 165-180. DOI: 10.1108/10662240210422521

Grewal, D., Levy, M., and Kumar, V. (2009). “Customer experience management in retailing: An organizing framework,” Journal of Retailing 85(1), 1-14. DOI: 10.1016/j.jretai.2009.01.001

Guo, H., and Wang, J. (2013). “The study of B2C customer experience model based on Tam model,” Science and Technology Management Research 33(19)184-188. DOI: 10.3969/j.issn.1000-7695.2013.19.042

Hansen, T. (2005). “Perspectives on consumer decision-making: An integrated approach,” Journal of Consumer Behaviour 4(6), 420-437. DOI: 10.1002/cb.33

Holbrook, M. B., and Hirschman, E. C. (1982). “The experiential aspects of consumption: Consumer fantasies, feelings, and fun,” Journal of Consumer Research 9(2), 132-140. DOI: 10.1086/208906

Janda, S., and Ybarra, A. (2005). “Do product and consumer characteristics affect the relationship between online experience and customer satisfaction?,” Journal of Internet Commerce 4(4), 133-151. DOI: 10.1300/J179v04n04_09

Jeong, S. W., Fiore, A. M., Niehm, L. S., and Lorenz, F. O. (2009). “The role of experiential value in online shopping: The impacts of product presentation on consumer responses towards an apparel web site,” Internet Research 19(1), 105-124. DOI: 10.1108/10662240910927858

Long, K. (2004). “Customer loyalty and experience design in e-business,” Design Management Review 22(16), 60-67. DOI: 10.1111/j.1948-7169.2004.tb00163.x

Kawaf, F., and Tagg, S. (2017). “The construction of online shopping experience: A repertory grid approach,” Computers in Human Behavior 72, 222-232. DOI: 10.1016/j.chb.2017.02.055

Khalifa, M., and Liu, V. (2007). “Online consumer retention: Contingent effects of online shopping habit and online shopping experience,” European Journal of Information Systems 16(6), 780-792. DOI: 10.1057/palgrave.ejis.3000711

Kim, D. (2016). “Psychophysical testing of garment size variation using three-dimensional virtual try-on technology,” Textile Research Journal 86(4), 365-379. DOI: 10.1177/0040517515591782

Kim, J., and Forsythe, S. (2008). “Adoption of virtual try-on technology for online apparel shopping,” Journal of Interactive Marketing 22(2), 45-59. DOI: 10.1002/dir.20113

Li, H., Daugherty, T., and Biocca, T. (2001). “Characteristics of virtual experience in electronic commerce: A protocol analysis,” Journal of Interactive Marketing 15(3), 13-30. DOI: 10.1002/dir.1013

Li, Y, Gong, M., Li, X., and Zhao, S. (2016). “Research on the Development Strategy of Electronic Commerce of Furniture – The comparative analysis of the furniture buying of entity shop and online shop,” Issues of Forestry Economics 36(03), 268-275 DOI:10.16832/j.cnki.1005-9709.2016.03.014

Li, Y., Li, X., Zhang, Z., Zhang, G., and Gong, M. (2020). “Understanding consumers online furniture purchase behavior: An updated UTAUT perspective,” Journal of Forest Economics 35(4), 267-303. DOI: 10.1561/112.00000516

Lim, N. (2003). “Consumers’ perceived risk: Sources versus consequences,” Electronic Commerce Research and Applications 2(3), 216-228. DOI: 10.1016/s1567-4223(03)00025-5

Lin, M., Wang, Z., Zhang, Z., and Cao, Y. (2019). “Research on consumers’ attitudes in china about using online-to-offline mode for purchasing wooden furniture,” Forest Products Journal 69(2), 159-172. DOI: 10.13073/FPJ-D-18-00039

Liu, P., and Shi, Y. (2020). “Research on the influencing mechanism of live broadcasting marketing pattern on consumers’ purchase decision,” China Business and Market (10), 38-47. DOI:10.14089/j.cnki.cn11-3664/f.2020.10.004.

Liu, Y., and Shrum, L. J. (2002). “What is interactivity and is it always such a good thing? Implications of definition, person, and situation for the influence of interactivity on advertising effectiveness,” Journal of Advertising 31(4), 53-64. DOI: 10.1080/00913367.2002.10673685

Luo, G. (2011). “Comprehensive evaluation of B2C E-commerce website service quality based on user experience,” Market Modernization 2011(1), 100-102. DOI: 10.3969/j.issn.1006-3102.2011.01.063

Mero, J. (2018). “The effects of two-way communication and chat service usage on consumer attitudes in the e-commerce retailing sector,” Electronic Markets 28(2), 205-217. DOI: 10.1007/s12525-017-0281-2

Meyer, C., and Schwager, A. (2007). “Understanding customer experience,” Harvard Business Review 85(2), 116-126.

Niu, Q., and Liu, H. (2017). “Research progress of e-commerce in furniture industry,” Issues of Forestry Economics 37(01), 68-73+108. DOI: 10.16832/j.cnki.1005-9709.2017.01.012.

Patro, C. S., and Katta, R. M. R. (2020). “Consumers’ perceived value in internet shopping: An empirical study,” International Journal of Customer Relationship Marketing and Management 11(2), 17-36. DOI: 10.4018/IJCRMM.2020040102

Poushneh, A., and Vasquez-Parraga, A. Z. (2017). “Discernible impact of augmented reality on retail customer’s experience, satisfaction and willingness to buy,” Journal and Consumer Services 34, 229-234. DOI: 10.1016/j.jretconser.2016.10.005

Qianzhan Industry Research Institute (2018). “Report of forward and investment strategic planning analysis on China furniture manufacturing industry,” (https://bg.qianzhan.com/report/detail/459/181129-adfe1b7d.html), Accessed 23 May 2021.

Rao, S., Griffis, S. E., and Goldsby, T. J. (2011). “Failure to deliver? Linking online order fulfillment glitches with future purchase behavior,” Journal of Operations Management 29(7-8), 692-703. DOI: 10.1016/j.jom.2011.04.001

Reichheld, F. F., and Schefter, P. (2000). “E-loyalty: Your secret weapon on the web,” Harvard Business Review 78(4), 105-113.

Rose, S., Hair, N., and Clark, M. (2011). “Online customer experience: A review of the business-to-consumer online purchase context,” International Journal of Management Reviews 13(1), 24-39. DOI: 10.1111/j.1468-2370.2010.00280.x

Shim, S. I., and Lee, Y. (2011). “Consumer’s perceived risk reduction by 3D virtual model,” International Journal of Retail & Distribution Management 39(12), 945-959. DOI: 10.1108/09590551111183326

Song, W. (2012). A Study of Customer Experience’s Effect on Customer Loyalty of B2C Electronic Commerce , Master’s Thesis, Shandong University, Shandong, China.

Tan, H. (2019). Research on the Influence of E-commerce Offline Store Experience on Consumers’ Online Purchase Intention , Master’s Thesis, Chongqing University of Posts and Telecommunications, Chongqing, China.

Van der Heijden, H., Verhagen, T., and Creemers, M. (2003). “Understanding online purchase intentions: Contributions from technology and trust perspectives,” European Journal of Information Systems 12(1), 41-48. DOI: 10.1057/palgrave.ejis.3000445

Wang, G., Zhu, J., Cai, W., Liu, B., Tian, Y., and Meng, F. (2021). “Research on packaging optimization in customized panel furniture enterprises,” Bioresources , 16(1), 1186-1206. DOI: 10.15376/biores.16.1.1186-1206

Wang, J., Ashleigh, M., and Meyer, E. (2006). “Knowledge sharing and team trustworthiness: It’s all about social ties!,” Knowledge Management Research & Practice 4(3), 175-186. DOI: 10.1057/palgrave.kmrp.8500098

Wang, Y. (2008). “Assessing e-commerce systems success: A respecification and validation of the DeLone and McLean model of IS success,” Information Systems Journal 18(5), 529-557. DOI: 10.1111/j.1365-2575.2007.00268.x

Watson, A., Alexander, B., and Salavati, L. (2018). “The impact of experiential augmented reality applications on fashion purchase intention,” International Journal of Retail & Distribution Management 48(5), 433-451. DOI: 10.1108/IJRDM-06-2017-0117

Wu, G., Hu, X., and Wu, Y. (2010). “Effects of perceived interactivity, perceived web assurance and disposition to trust on initial online trust,” Journal of Computer-Mediated Communication 16(1), 1-26. DOI: 10.1111/j.1083-6101.2010.01528.x

Xiao, C., and Yu, S. (2017). “Status survey of furniture information dissemination in new medium enviroment,” Furniture 38(3), 13-16, +49. DOI: 10.16610/j.cnki.jiaju.2017.03.003

Xiong, X., Guo, W., Fang, L., Zhang, M., Wu, Z., Lu, R., and Miyakoshi, T. (2017). “Current state and development trend of Chinese furniture industry,” Journal of Wood Science 63(5), 433-444. DOI: 10.1007/s10086-017-1643-2

Xiong, X., Ma, Q., Yuan, Y, Wu, Z., and Zhang, M. (2020). “Current situation and key

manufacturing considerations of green furniture in China: A review,” Journal of Cleaner Production , DOI:10.1016/j.jclepro.2020.121957.

Yang, Y., Liu, W., and Li, G. (2019). “Research on users’cognition of different preferences based on ERPs,” Journal of Forestry Engineering 4(05), 152-158. DOI:10.13360/j.issn.2096-1359.2019.05.022

Zhang, L., Tan, W., Xu, Y., and Tan, G. (2011). “Dimensions of perceived risk and their influence on consumers’ purchasing behavior in the overall process of B2C,” Engineering Education and Management 111, 1-10. DOI: 10.1007/978-3-642-24823-8_1

Zhang, T., Wang, W. Y. C., Cao, L., and Wang, Y. (2019). “The role of virtual try-on technology in online purchase decision from consumers’ aspect,” Internet Research 29(3), 529-551. DOI: 10.1108/IntR-12-2017-0540

Zhang, Z., and Xu, B. (2019). “Research on e-commerce logistics service quality problem based on electronic word-of-mouth data mining,” China Business and Market 2019(1), 43-55. DOI: 10.14089/j.cnki.cn11-3664/f.2019.01.005

Article submitted: August 16, 2021; Peer review completed: November 14, 2021; Revised version received and accepted: January 3, 2022; Published: January 18, 2022.

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

REVIEW OF LITERATURE: ONLINE AND OFFLINE CONSUMER BUYING BEHAVIOR

Related Papers

GhanShyam Sharma

IJRAR JOURNAL I J R A R IJRAR

The main objectives of this research report are to find out if Social Media has any impact in Tourism, to determine what tourists' perceived benefits of using social media when taking trips are, and to ascertain if there is any strategic opportunity for value creation for the tourist. A Social Media value-creation model is created in order to find out if any of the functionalities applied to tourism and any of the perceived benefits of using Social Media in tourism contribute in any way to the tourist's value-creation or if it has an influence on tourists when planning and taking trips. Through a survey answered by 600 respondents, the most influential attributes of the usage of Social Media in tourism are ascertained, the travellers' perception of social media is analysed, the important functionalities and benefits are determined and an analysis of the strategic impact of Social Media in tourism is conducted. It can even be used as a source of sustainable competitive advantage if tourism firms develop a positive reputation and focus on the personalization of their services as the key element for their value-creating strategy.

International Journal of Research and Analytical Reviews

KWADWO BOATENG

This piece of research work aims at understanding the preferred emerging media options used for marketing by start-ups in India and Ghana. A start-up is a temporal organization that is searching for a scalable, and repeatable profitable business model, which can be a partnership, a company, or temporal organization. There is an evidential proves to suggest that any business venture, be it an MNC or a growing organization in this era of information communication technology can never survive the test of time if it fails to leverage on the booming ICT to announce its presence. However, the question that arises is through which media type can this be possible? It is based on the above question that this research work is being carried out to ascertain the most used emerging media by start-ups for their marketing purposes in India and Ghana. A total of 30 start-up owners comprising of 15 from each country were sampled for the study through convenience and snowball sampling techniques. The data collected was analysed using charts, graphs, and tables. It was found that startups prefer electronic media to the traditional media for the marketing of its products and services. Among the electronic media, social media is used more by startups. Facebook, WhatsApp, LinkedIn, Twitter, Instagram, YouTube and Google+ were the most used.

Dr.S.Palani

A.senthil Raja

In this competitive world, branded garments are occupying a very vital role in the market. Before the selection of garments, the consumers should have awareness of its features. The consumer's desire, need, and the expectation is not unique from customer to customer and so many factors are the determining criterion for the selection of brand. By analyzing these factors, firms can formulate the strategies in accordance with the customer's needs and deliver them the products which consumer wants from the firms, which should be profitable for the firm. The relationship between consumer's decision-making styles and their choice between branded items are investigated using a sample of consumers of Madurai city. The purpose of the research project is to investigate the consumers of Madurai city to_ examine if any factor dominates in their buying behavior of apparel. In addition, consumer behaviors and personal characteristics were investigated separately in relation to the purchase behavior of consumers. A total of 316 sample consumers have been randomly selected for the study. Using descriptive statistics, chi-square and garretrankingtechniquesthecollecteddatawasinterpreted.

Sudipta Sen Gupta , deepti wadera

This paper investigates the awareness and understanding about CSR among Indian consumers, using Carroll’s pyramid model of CSR dimensions viz. economic, legal, ethical and philanthropic, as the conceptual framework. The empirical study used online survey method, from 934 consumers,from six major cities in India, across different demographics. The results indicate that Indian consumers are aware of CSR; older and more educated Indian consumers, from privileged socioeconomic classes are more aware than others. Their understanding is that CSR is pre-eminently about following laws, followed by ethical responsibilities towards the environment and regarding human rights while economic and philanthropic dimensions are considered to be relatively less important. The findings will help corporate India, with its historical association with philanthropy, to note the consumer perspective and reap the benefits of strategic CSR. The study sheds light on the way forward for CSR practices in the large and growing consumer market of India, for multinational and domestic companies which are mandatorily required to spend on CSR under the Companies Act (2013). It adds to the body of literature on the applicability of Carroll’s pyramid model across global markets, being one of the very few studies in India to do so. Index Terms: CSR pyramid model, Indian consumers, CSR awareness, understanding of CSR, CSR dimensions, economic responsibility, ethical responsibility, legal responsibility, philanthropy, mandatory CSR

vijayalakshmi R.

The aim of the study is to investigate the consumer behavior towards Fast Moving Consumer Goods. Consumer behavior consists of the activities people engage in when selecting purchasing and using products so as to satisfy needs and desires. The sample respondent of 200 FMCG products users has been selected under the non-probability convenience sampling method. This study is start with objective of buying decision process of Fast Moving Consumer Goods. The collected data were analyzed by using descriptive statistics and Chi-Square. The study intends to buy decision process of FMCG products. Consumer motive relates to a wide spectrum of wants and needs. Consumer inspiration is an internal state that drives people to classify and buy products or services that accomplish conscious and unconscious needs or desires. The implementation of those needs can then stimulate them to make a repeat purchase or to find special goods and services to better fulfill those needs.

Dr.Mugesh kannan Reguraman

Dr.J.Solomon Thangadurai

Organic products are considered as healthy by most of the buyers as these are made up of natural substances. Organic products are grownup without the harmful substance and grown natural quality. The Indian organic food market although in its infant stage, has started growing faster. Consumers choose organic food in the interest of safety, human health, and environmental concern. The result also presented the factors that benefits organic food consumption and the barriers that limit the growth of organic profit. To achieve the research objectives, primary and secondary data collection methods used. The main sources of secondary data were collected from different online sources such as reports, surveys, and websites of Research Institutes, published books, online journals and papers. The primary data was gained by utilizing structured questionnaire that was collected from consumers.

nternational Journal of Research and Analytical Reviews (IJRAR)

sreenivasa B R , Dr.Nirmala C R

The e-Commerce industries require efficient recommendation model to maximize the profit and user satisfaction. Recommendation system assists consumers to find their relevant items of interest. The state-of-art models are designed by considering long-term consumer context. However, in the current application dynamic, such long-context does not exist and recommendation must be made based on user present behavior of an ongoing session. Many session based approaches have been presented in recent times to forecast user's next item requirement. However, these models consider modeling a single behavior with long-context. As a result, the state-of-art model finds difficulty in revealing the correlation between the items and behaviors. To overcome the above-mentioned research challenge the research work presents a multi-behavioral trait based on consumer location-centric prediction (LCP) model using an optimized recurrent neural network (ORNN). LCP model can learn both short and long-context efficiently. Experiment outcome shows LCP attain significant performance over the existing model in terms of Recall, F1-Score, Mean reciprocal rate (MMR) and Hit rate (HR).

Dr. Ashutosh Kumar , Dr. Anupma Mahajan , shikha sharma

The main aim of the study was to explore customers' inclination towards eco-friendly hotels in Northern India. Eco-friendly hotels are the ones that use various sustainable strategies towards addressing the environmental issues as well as improving the awareness of the customers and tourists towards environmental contribution. The current study used an empirical quantitative study that comprised of 138 customers from different eco-friendly hotels in Northern India. Data were collected using closed ended questionnaires and analyzed using SPSS v23. Statistical findings implicated that factors of customer beliefs and attitudes towards importance of eco-hotels were sustainable and cost efficient, green hotels area responsible for reducing carbon footprint and environmental pollution, green hotels use sustainable and organic products to support environmental issues, green hotels reduces the amount of waste generated, green tourism involves awareness programmes on environmental conservation, and green hotels support environmental conservation. Similarly, customer intentions of features of eco-hotels such as recycles it waste products and water, reducing paper usage, bans the use of plastic and other toxic elements, and products and utilities that are made sustainably motivates the customers to choose eco-friendly hotels. However, the study has some limitations presented in the concluding section of the study along with future scope.

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED PAPERS

Dr. Sandipkumar G Prajapati

Seema Sambargi

Publisher ijmra.us UGC Approved

Ankit Choudhary

Assoc. Prof. Dr. Rashad Yazdanifard

Arafatur Rahaman

INTERNATIONAL JOURNAL OF RESEARCH AND ANALYTICAL REVIEWS (IJRAR)

Dr. SUJITH T S

Dr. Prafulla K U M A R Padhi , SUBASH CHANDRA NATH

IJRAR | www.ijrar.org | E-ISSN 2348-1269, P- ISSN 2349-5138

Ifrah Bukhari

UNANZA gulzar

Research in Mark ch in Mark ch in Mark ch …

ANAND AGRAWAL

International Journal of Latest Technology in Engineering, Management & Applied Science -IJLTEMAS (www.ijltemas.in)

International Journal of Electronic Marketing and Retailing

narendra sharma

TJPRC Publication

MAMTA CHAWLA

Emon K Chowdhury , Rupam Chowdhury

IOSR Journals

Dr Samantha Lynch

UGC Approved Journal of Marketing Strategy(JMS)

International Journal of Analytical Research and Reviews

Dr. Prafulla K U M A R Padhi

Journal of Marketing Vistas

praveen pandey , prashant pandey

International Journal of Scientific Research in Science and Technology

Dr. Raja Sarkar

Journal of Retailing

Mary Wolfinbarger

North Asian International Research Journal Consortium

RA A Rather

hemath weerasinghe

2012 International Conference on Innovation Management and Technology Research

Lennora Putit

M Bilgehan Aytaç

Tengku Amin

Ms. Syeda Nazneen Waseem Lecturer (KUBS)

Journal of Computer Science IJCSIS

Sajad Rezaei , Tengku Amin

International Journal

Irfan Iftekhar

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024