Gunawan, D. and Huarng, K. (2015). Viral effects of social network and media on consumers’ purchase intention. Journal of Business Research, 68(11), pp.2237-2241.
Keywords: Viral marketing, eWOM, SEM, fsQCA
Main idea: This article is based on a study that explains how SNM influences people to make purchases. The research they conducted is surveys completed by people who use three SNM platforms.
The SEM results proved that SNM has no correlation with consumer’s purchasing, whereas fsQCA shows the opposite.
Development:
SNM sites are growing, and affect their user’s lives by forming connections among these users. SNM Viral marketing is often used as an electronic WOM, since a lot of people are connected and state their opinions and tastes online. The messages are transmitted way faster than they once were, which benefits the market as well as the consumers.
The study is based on three theories that make sense when put together (TRA, IAM and perceived risk). The first one is used to understand and predict behavior. The second one basically explains how one adopts to a new model, or technology. The latter clarifies the overall risk a consumer feels before and after purchasing a particular item.
The study gathered data taken from users who completed surveys they got online via these SNM sites. Based on the results, the researches would define if the theories can still apply. The findings prove that social influence is, indeed, the first leading impact.
Conclusion:
To conclude, the SEM results indicates that social influence and the source credibility is very important and showing in consumer’s attitude toward receiving and trusting an information. Consumers are more comfortable in listening to opinions from credible sources rather than trusting arguments written with quality.
References:
Ajzen, I. (2005). Attitudes, personality, and behavior (2nd ed.). Milton-Keynes, England:
Open University Press / McGraw-Hill.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior.
Englewood Cliffs, NJ: Prentice-Hall.
Bauer, R.A. (1960). Consumer behavior as risk taking. In D.F. Cox (Ed.), Risk taking and information handling in consumer behavior (pp. 23–33). Boston: Harvard UniversityPress.
Beldad, A., Jong, M.D., & Steehouder, M. (2010). How shall I trust the faceless and the intangible A literature review on the antecedents of online trust. Computers in HumanBehavior, 26, 857–869.
Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance:An elaboration likelihood model. MIS Quarterly, 30(4), 805–825.
Camarero, C., & San José, R. (2011). Social and attitudinal determinants of viral marketing dynamics. Computers in Human Behavior, 27, 2292–2300.
Cheung, C.M.K., Lee, M.K.O., & Rabjohn, N. (2008). The impact of electronic word-ofmouth.Internet Research, 18(3), 229.
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Farooq, F., & Jan, Z. (2012). The impact of social networking to influence marketing through product reviews. International Journal of Information and Communication Technology Research, 2(8), 627–637.
Fiss, P.C. (2011). Building better causal theories: A fuzzy set approach to typologies in organization research. Academy of Management Journal, 54(2), 393–420.
Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Hair, Jr, Anderson, J.F., Tatham, R.L., & Black, W.C. (1998). Multivariate data analysis (Fifthed.). Upper Saddle River, NJ: Prentice-Hall.
Hennig-Thurau, T., Gwinner, K.P., Walsh, G., & Gremler, D.D. (2004). Electronic word-ofmouth via consumer opinion platforms: What motivates consumers to articulate themselves on the internet? Journal of Interactive Marketing, 18, 38–52.
Ho, J.Y.C., & Dempsey, M. (2010). Viral marketing: Motivations to forward online content. Journal of Business Research, 63(9), 1000–1006.
Hsu, C. -L., & Lin, J.C.-. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence, and knowledge sharing motivation. Information & Management, 45, 65–74.
Huarng, K. -H. (2014). Configural theory for ICT development. Journal of Business Research, 68, 748–756.
Kempe, D., Kleinberg, J., & Tardos, E. (2003). Maximizing the spread of influence through a social network. Proceedings of the Ninth ACM SIGKDD International Conference on
Knowledge Discovery and Data Mining (SIGKDD’03) (pp. 137–146).
Lin, H. -F. (2007). Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research and Applications, 6(4), 433–442.
Nunally, J. (1967). Psychometric theory. New York: Mc-Graw Hill.
Oden, N., & Larsson, R.S. (2011). What makes a marketing campaign a viral success? A descriptive model exploring the mechanisms of viral marketing. Universitat UMEA.
Petty, R.E., & Cacioppo, J.T. (1986). Communication and persuasion: Central and peripheral routes to attitude change. New York, NY: Springer-Verlag.
Petty, R.E., Cacioppo, J.T., & Goldman, R. (1981). Personal involvement as a determinant of argument-based persuasion. Journal of Personality and Social Psychology, 41, 847–855.
Pitta, D.A., & Fowler, D. (2005). Online consumer communities and their value to new product developers. Journal of Product & Brand Management, 14(15), 283–291.
Qiu, L., & Benbasat, I. (2005). An investigation into the effects of text-to-speech voice and 3d avatars on the perception of presence and flow of live help in electronic commerce. ACM Transactions on Computer-Human Interaction, 12(4), 329–355.
Ragin, C.C. (1987). The comparative method: Moving beyond qualitative and quantitative strategies. Berkeley: University of California Press.
Ragin, C.C. (2008). Redesigning social inquiry: Fuzzy sets and beyond. Chicago: University of Chicago Press.
Rihoux, B., & Ragin, C.C. (2009). Configurational comparative methods: Qualitative Comparative Analysis (QCA) and related techniques. Thousand Oaks, CA: Sage.
Rubin, M., Watt, S.E., & Ramelli, M. (2012). Immigrants’ social integration as a function of approach-avoidance orientation and problem-solving style. International Journal of Intercultural Relations, 36, 498–505.
Smith, D., Menon, S., & Sivakumar, K. (2005). Online peer and editorial recommendations, trust, and choice in virtual markets. Journal of Interactive Marketing, 19(3), 15–37.
Stromer-Galley, J. (2004). Interactivity-as-product and interactivity-as-process. The Information Society, 20(5), 391–394.
Sussman, S.W., & Siegal, W.S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Informational System Research, 14(1), 47–65.
Vilpponen, A., Winter, S., & Sundqvist, S. (2006). Electronic word-of-mouth in online environments: Exploring referral network structure and adoption behavior. Journal of Interactive Advertising, 6(2) (http://www.jiad.org/article82).
Wang, X., Yu, C.L., & Wei, Y.J. (2012). Social media peer communication and impacts on purchase intentions: A consumer socialization framework. Journal of Interactive Marketing, 26, 198–208.
Weber, M. (1947). The theory of social and economic organization. NY: The Free Press.
Woodside, A.G., Eunju, K., & Tzung, C.H. (2012). The new logic in building isomorphic theory of management decision realities. Management Decision, 50(5), 765–777.
Wu, C. -W., Huarng, K.-. H., Fiegantara, S., & Pai, C.W. (2012). The impact of online customer satisfaction on the yahoo auction in Taiwan. Service Business, 6, 473–487.
Yang, H., Liu, H., & Zhou, L. (2011). Predicting young Chinese consumers’ mobile viral attitudes,intents, and behavior. Asia Pacific Journal of Marketing and Logistics, 24(1),59–77.
Zhang, Y., & Hiltz, S.R. (2003). Factors that influence online relationship development in aknowledge sharing community. Proceedings of the Ninth American Conference on InformationSystems (pp. 410–417).
Zhaveri, H. (2013). Social networking site for marketing. Proceedings of National Conference on New Horizons in IT (pp. 215–218).