Abstract
The aim of this paper is to study consumers’ purchase intention on web-based and social-based B2C e-commerce platforms. This research is one of the first empirical studies to employ the Stimulus-Organism-Response Model (S-O-R Model) as a main research model. The researchers found six findings which contrast with the previous literature. First, the two-way communication tools provided by the platform are not powerful enough to significantly affect the emotional needs of online consumers. Second, the stimulus that affect user’s interpretation of online information is the two-way communication tools provided by the platform. Third, the risk perceived by a consumer in contemplating a particular purchase action does not significantly affect the emotional needs of consumers. Fourth, the stimulus that affects users’ curiosity aroused while interacting with the platform is the ability of the platform to enhance user participation in the platform’s activities. Fifth, consumers’ emotional needs significantly affect online consumers’ purchase intention. Finally, the degree of users’ attention while using the platform significantly affects consumers’ purchase intention.
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References
Animesh AP, Yang SB, Oh W (2011) An odyssey into virtual words: exploring the impacts of technological and spatial environments on intention to purchase virtual products. MIS Q 35(3):780–810
Arnett DB, German SD, Hunt SD (2003) The identity salience model of relationship marketing success: the case of non-profit marketing. J Mark 67(2):89–105
Bray JP (2008) Consumer behaviour theory: Approaches and models. Discussion paper. (Unpublished)
Clément R, Noels K, Doeneault B (2001) Interethnic contact, identity, and psychological adjustments in the mediating and moderating roles of communication. J Soc Issues 57(3):559–578
Cheung CMK, Lee MKO (2010) A theoretical model of intentional social action in online social networks. Decis Support Syst 49(1):24–30
Electronic Transactions Development Agency (2017). Value of e-Commerce Survey in Thailand 2017. Bangkok: Thailand Ministry of Digital Economy and Society. Retrieved January 4, 2017 from https://www.etda.or.th/publishing-detail/value-of-e-commerce-survey-2017.html
Eroglu SA, Machleit KA, Davis LM (2003) Empirical testing of a model of online store atmospherics and shopper responses. Psychol Mark 20(2):139–150
Hoffman DL, Novak TP (1996) Marketing in hypermedia computer-mediated environments: conceptual foundations. J Mark 60(3):50–68
Huang E (2012) Online experiences and virtual goods purchase intention. Internet Res 22(3):252–274
Huang Z, Benyoucef M (2013) From e-commerce to social commerce: A close look at design features. Electron Commer Res Appl 12(4):246–259
Jacoby J (2002) Stimulus-organism-response reconsidered: an evolutionary step in modeling (consumer) behavior. J Consum Psychol 12(1):51–57
Jiang Z, Chan J, Tan BCY, Chua WS (2010) Effects of interactivity on web site involvement and purchase intention. J Assoc Inf Syst 11(1):34–59
Kim J, Lennon S (2013) Effects of reputation and website quality on online consumers’ emotion, perceived risk and purchase intention. Journal of Research in Interactive Marketing 7(1):33–56
Koufaris M (2002) Applying the technology acceptance model and flow theory to online consumer behavior. Inf Syst Res 13(2):205–223
Kwon O, Wen Y (2010) An empirical study of the factors affecting social network service use. Comput Hum Behav 26(2):254–263
Lim N (2003) Consumer’s perceived risk: source versus consequences. Electron Commer Res Appl 2(3):216–238
Lu Y, Zhou T, Wang B (2010) Exploring Chinese user’s acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Comput Hum Behav 25(1):29–39
Manganari EE, Siomkos GJ, Rigopoulou ID, Vrechopoulos AP (2011) Virtual store layout effects on consumer behaviour: applying an environmental psychology approach in the online travel industry. Internet Res 21(3):326–346
Mitchell V-W (1999) Consumer perceived risk: conceptualisations and models. Eur J Mark 33(1/2):163–195
Moon JW, Kim YG (2001) Extending the TAM for a world-wide-web context. Inf Manag 38(4):217–230
Novak TP, Hoffman DL, Yung YF (2000) Measuring the customer experience in Online environments: a structural modeling approach. Mark Sci 19(1):22–44
Simon B (2004) Identity in Modern Society: A Social Psychological Perspective. Blackwell, Oxford
Song J, Kim YJ (2006) Social influence process in the acceptance of a virtual community Service. Inf Syst Front 8(3):241–252
Vijayasarathy LR, Jones JM (2000) Intentions to shop using internet catalogues: exploring the effects of product types, shopping orientations, and attitudes towards computers. Electron Mark 10(1):29–38
Wang K, Wang ETG, Farn CK (2009) Influence of web advertising strategies, consumer goal-directedness, and consumer involvement on web advertising effectiveness. Int J Electron Commer 13(4):67–95
Zaichkowsky JL (1986) Conceptualizing involvement. J Advert 15(6):1–14
Zaichkowsky JL (1994) The personal involvement inventory: Reduction, revision, and application to advertising. J Advert 23(4):59–70
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Patanasiri, A., Krairit, D. A Comparative Study of Consumers’ Purchase Intention on Different Internet Platforms. Mobile Netw Appl 24, 145–159 (2019). https://doi.org/10.1007/s11036-018-1139-3
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DOI: https://doi.org/10.1007/s11036-018-1139-3