The Influence of Online Product Recommendations on Consumers' Online Choices

Journal of Retailing 80 (2004) 159–169

The influence of online product recommendations on consumers’ online choices
Sylvain Senecal a,∗ , Jacques Nantel a,1 a HEC Montreal, University of Montreal, 3000 Chemin de la Cote-Sainte-Catherine, Montreal, Que., Canada H3T 2A7

Abstract This study investigates consumers’ usage of online recommendation sources and their influence on online product choices. A 3 (websites) × 4 (recommendation sources) × 2 (products) online experiment was conducted with 487 subjects. Results indicate that subjects who consulted product recommendations selected recommended products twice as often as subjects who did not consult recommendations. The online recommendation source labeled “recommender system,” typical of the personalization possibilities offered by online retailing, was more influential than more traditional recommendation sources such as “human experts” and “other consumers”. The type of product also had a significant influence on the propensity to follow product recommendations. Theoretical and managerial implications of these findings are provided. © 2004 by New York University. Published by Elsevier. All rights reserved.
Keywords: Online product; Recommendation; Consumers

Introduction Among all possible advantages offered by electronic commerce to retailers, the capacity to offer consumers a flexible and personalized relationship is probably one of the most important (Wind & Rangaswamy, 2001). Online personalization offers retailers two major benefits. It allows them to provide accurate and timely information to customers which, in turn, often generates additional sales (Postma & Brokke, 2002). Personalization has also been shown to increase the level of loyalty consumers hold toward a retailer (Cyber Dialogue, 2001; Srinivasan, Anderson, & Ponnavolu, 2002). While there are several ways to personalize an online relationship, the capacity for an online retailer to make recommendations is certainly among the most promising

References: Alba, J., Lynch, J., Weitz, B., Janiszewski, C., Lutz, R., Sawyer, A., et al. (1997). Interactive home shopping: Consumer, retailer, and manufacturer incentives to participate in electronic marketplaces. Journal of Marketing, 61(3), 38–53. Andreasen, A. R. (1968). Attitudes and customer behavior: A decision model. In H. H. Kassarjian & T. S. Robertson (Eds.), Perspectives in consumer behavior (pp. 498–510). Glenview, IL: Scott, Foresman and Company. Ansari, A., Essegaier, S., & Kohli, R. (2000). Internet recommendation systems. Journal of Marketing Research, 37(3), 363–375. Ardnt, J. (1967). Role of product-related conversations in the diffusion of a new product. Journal of Marketing Research, 4(3), 291–295. Bakos, Y. J. (1997). Reducing buyer search costs: Implications for electronic marketplaces. Management Science, 43(2), 1676–1692. Bearden, W. O., & Etzel, M. J. (1982). Reference group influence on product and brand purchase decisions. Journal of Consumer Research, 9(2), 183–194. Bearden, W. O., Netemeyer, R. G., & Teel, J. E. (1989). Measurement of consumer susceptibility to interpersonal influence. Journal of Consumer Research, 15(4), 473–481. Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer Research, 14(3), 350–362. Childers, T. L., & Rao, R. (1992). The influence of familial and peer-based reference groups. Journal of Consumer Research, 19(2), 198–212. Cyber Dialogue (2001). The personalization consortium’s online consumer personalization survey. Duhan, D. F., Johnson, S. D., Wilcox, J. B., & Harell, G. D. (1997). Influences on consumer use of word-of-mouth recommendation sources. Journal of the Academy of Marketing Science, 25(4), 283–295. Folkes, V. S. (1988). Recent attribution research in consumer behavior: A review and new directions. Journal of Consumer Research, 14(4), 548–565. Flynn, L. R., & Goldsmith, R. E. (1999). A short, reliable measure of subjective knowledge. Journal of Business Research, 46(1), 57–66. Gilly, M. C., Graham, J. L., Wolfinbarger, M. F., & Yale, L. J. (1998). A dyadic study of personal information search. Journal of the Academy of Marketing Science, 26(2), 83–100. Harmon, R. R., & Coney, K. A. (1982). The persuasive effects of source credibility in buy and lease situations. Journal of Marketing Research, 19(2), 255–260. Häubl, G., & Trifts, V. (2000). Consumer decision-making in online shopping environments: The effects of interactive decision aids. Marketing Science, 19(1), 4–21. Hoffman, D. L., Novak, P. T., & Chatterjee, P. (1995). Commercial scenarios for the web: Opportunities and challenges. Journal of Computer Mediated Communication, 1(1). Kelley, H. H. (1967). Attribution Theory in Social Psychology. In D. Levine (Ed.), Nebraska symposium on motivation (pp. 192–241). Lincoln, NE: University of Nebraska Press. Kelley, H. H. (1973). The process of causal attribution. American Psychologist, 28, 107–128. Kelman, H. C. (1961). Processes of opinion change. Public Opinion Quarterly, 25, 57–78. S. Senecal, J. Nantel / Journal of Retailing 80 (2004) 159–169 King, M. F., & Balasubramanian, S. K. (1994). The effects of expertise, end goal, and product type on adoption of preference formation strategy. Journal of the Academy of Marketing Science, 22(2), 146– 159. Lascu, D.-N., Bearden, W. O., & Rose, R. L. (1995). Norm extremity and personal influences on consumer conformity. Journal of Business Research, 32(3), 201–213. Liang, K.-L., & Zeger, S. L. (1986). Longitudinal data analysis using generalized linear models. Biometrika, 73(1), 13–22. Liang, K.-L., Zeger, S. L., & Qaqish, B. (1992). Multivariate regression analyses for categorical data. Journal of the Royal Statistical Society, 54, 3–40. Lohse, L. G., Bellman, S., & Johnson, E. J. (2000). Consumer behavior on the Internet: Findings from panel data. Journal of Interactive Marketing, 14(1), 15–29. Lynch, J. G., & Ariely, D. (2000). Wine online: Search costs affect competition on price, quality, and distribution. Marketing Science, 19(1), 83–103. Maes, P. (1999). Smart commerce: The future of intelligent agents in cyberspace. Journal of Interactive Marketing, 13(3), 66–76. McGuire, W. J. (1969). The nature of attitudes and attitude change. In G. Lindzey & E. Aronson (Eds.), The handbook of social psychology (pp. 137–314). Reading, MA: Addison-Wesley Publishing Company. Mizerski, R. W., Golden, L. L., & Kernan, J. B. (1979). The attribution process in consumer decision making. Journal of Consumer Research, 6(2), 123–140. Nelson, P. (1970). Information and consumer behavior. Journal of Political Economy, 78(2), 311–329. Nelson, P. (1974). Advertising as information. Journal of Political Economy, 83(4), 729–754. Nosek, B. A., Banaji, M. R., & Greenwald, A. G. (2002). E-research: Ethics, security, design, and control in psychological research on the Internet. Journal of Social Issues, 58(1), 161–176. Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers’ perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39–52. Olshavsky, R. W., & Granbois, D. H. (1979). Consumer decision-making— fact or fiction. Journal of Consumer Research, 6(2), 93–100. Park, C. W., Mothersbaugh, D. L., & Feick, L. (1994). Consumer knowledge assessment. Journal of Consumer Research, 21(2), 71– 82. Perdue, B. C., & Summers, J. O. (1986). Checking the success of manipulations in marketing experiments. Journal of Marketing Research, 23(4), 317–326. 169 Postma, O. J., & Brokke, M. (2002). Personalisation in practice: The proven effects of personalisation. Journal of Database Marketing, 9(2), 137–142. Price, L. L., & Feick, L. F. (1984). The role of recommendation sources in external search: An informational perspective. In T. Kinnear (Ed.), Advances in consumer research (Vol. 11, pp. 250–255). Provo, UT: Association for Consumer Research. Rosen, D. L., & Olshavsky, R. C. (1987). The dual role of informational social influence: Implications for marketing management. Journal of Business Research, 15(2), 123–144. Senecal, S., & Nantel, J. (2002). Online influence of relevant others: A framework (Working Paper). RBC Financial Group Chair of E-Commerce, HEC Montreal, University of Montreal. Simonson, I. (1999). The effect of product assortment on buyer preferences. Journal of Retailing, 75(3), 347–370. Spiller, P., & Lohse, J. (1998). A classification of Internet retail stores. International Journal of Electronic Commerce, 2(2), 29–56. Srinivasan, S. S., Anderson, R., & Ponnavolu, K. (2002). Customer loyalty in E-commerce: An exploration of its antecedents and consequences. Journal of Retailing, 78(1), 41–50. Sternthal, B., Phillips, L. W., & Dholakia, R. (1978). The persuasive effect of source credibility: A situational analysis. Public Opinion Quarterly, 42(3), 285–314. Stokes, M. E., Davis, C. S., & Koch, G. G. (2001). Categorical data analysis using the SAS System. Cary, NC: SAS Institute Inc. Szymanski, D. M., & Hise, R. T. (2000). e-Satisfaction: An initial examination. Journal of Retailing, 76(3), 309–322. The e-tailing Group (2003). 2nd Annual Merchant Survey. Tybout, A. M. (1978). Relative effectiveness of three behavioral influence strategies as supplements to persuasion in a marketing context. Journal of Marketing Research, 15(2), 229–242. Urban, G., Sultan, F., & Qualls, W. (1999). Design and evaluation of a trust based advisor on the Internet (Working Paper 40). e-Commerce Research Forum, MIT. West, P. M., Ariely, D., Bellman, S., Bradlow, E., Huber, J., Johnson, E., et al. (1999). Agents to the rescue? Marketing Letters, 10(3), 285–300. Wind, J., & Rangaswamy, A. (2001). Customerization: The next revolution in mass communication. Journal of Interactive Marketing, 15(1), 13– 32. Wood, S. L. (2002). Future fantasies: A social change perspective of retailing in the 21st century. Journal of Retailing, 78(1), 77–83. Zeger, S. L., Liang, K.-L., & Albert, S. (1988). Models for longitudinal data: A generalized estimating equation approach. Biometrics, 44, 1049–1060.