The Influence of Social Presence on Customer Intention to Reuse Online Recommender Systems: The Roles of Personalization and Product Type

Providing recommendations is acknowledged to be an important feature of a business-to-consumer online storefront. Although many studies have examined the algorithms and operational procedures relevant to personalized recommender systems, empirical evidence demonstrating relationships between social presence and two important outcomes of evaluating recommender systems—reuse intention and trust—remains lacking. To test the existence of a causal link between social presence and reuse intention, and the mediating role of trust between these two variables, this study conducted experiments varying the level of social presence while providing personalized recommendations to users based on their explicit preferences. This study also compared these effects in two different product contexts: hedonic and utilitarian. The results show that greater social presence increases both reuse intention and trust in the recommender systems. Moreover, the influence of social presence on reuse intention with respect to utilitarian products is less than that with respect to hedonic products.

[1]  Paul A. Pavlou,et al.  Understanding and Mitigating Uncertainty in Online Exchange Relationships: A Principal-Agent Perspective , 2007, MIS Q..

[2]  Hong Joo Lee,et al.  Mobile push personalization and user experience , 2008, AI Commun..

[3]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[4]  D. Gefen,et al.  E-commerce: the role of familiarity and trust , 2000 .

[5]  Shuk Ying Ho,et al.  Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective , 2005, Inf. Syst. Res..

[6]  Izak Benbasat,et al.  The Effects of Process and Outcome Similarity on Users' Evaluations of Decision Aids , 2008, Decis. Sci..

[7]  Shankar Ganesan.  Determinants of Long-Term Orientation in Buyer-Seller Relationships , 1994 .

[8]  Izak Benbasat,et al.  E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact , 2007, MIS Q..

[9]  Jagdip Singh,et al.  Agency and trust mechanisms in consumer satisfaction and loyalty judgments , 2000 .

[10]  Hans van der Heijden,et al.  User Acceptance of Hedonic Information Systems , 2004, MIS Q..

[11]  Sylvain Sénécal,et al.  Consumers' decision-making process and their online shopping behavior: a clickstream analysis , 2005 .

[12]  David Gefen,et al.  Managing User Trust in B2C e-Services , 2003 .

[13]  Wynne W. Chin.  The partial least squares approach for structural equation modeling. , 1998 .

[14]  D. Gefen,et al.  Consumer trust in B2C e-Commerce and the importance of social presence: experiments in e-Products and e-Services , 2004 .

[15]  Jaeki Song,et al.  An Exploratory Study of Social Factors Influencing Virtual Community Members' Satisfaction with Avatars , 2007, Commun. Assoc. Inf. Syst..

[16]  Yi-Cheng Ku,et al.  Personalized Content Recommendation and User Satisfaction: Theoretical Synthesis and Empirical Findings , 2006, J. Manag. Inf. Syst..

[17]  Mark S. Johnson,et al.  The Different Roles of Satisfaction, Trust, and Commitment in Customer Relationships , 1999 .

[18]  Izak Benbasat,et al.  Online Consumer Trust and Live Help Interfaces: The Effects of Text-to-Speech Voice and Three-Dimensional Avatars , 2005, Int. J. Hum. Comput. Interact..

[19]  Hong Joo Lee,et al.  Effects of Product Recommendations on Customer Behavior in e-Commerce , 2008 .

[20]  E. Hirschman,et al.  Hedonic Consumption: Emerging Concepts, Methods and Propositions , 1982 .

[21]  Daniel L. Sherrell,et al.  Communications of the Association for Information Systems , 1999 .

[22]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[23]  Wynne W. Chin,et al.  A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic - Mail Emotion/Adoption Study , 2003, Inf. Syst. Res..

[24]  Sijun Wang,et al.  Signaling the trustworthiness of small online retailers , 2004 .

[25]  Richard P. Bagozzi,et al.  Assessing Construct Validity in Organizational Research , 1991 .

[26]  Sophie Ahrens,et al.  Recommender Systems , 2012 .

[27]  Shuk Ying Ho,et al.  The attraction of personalized service for users in mobile commerce: an empirical study , 2002, SECO.

[28]  Jacob Cohen.  Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[29]  Shuk Ying Ho,et al.  Understanding the Impact of Web Personalization on User Information Processing and Decision Outcomes , 2006, MIS Q..

[30]  Shuk Ho,et al.  An Empirical Examination of the Effects of Web Personalization at Different Stages of Decision Making , 2005, Int. J. Hum. Comput. Interact..

[31]  Thomas Kramer,et al.  The Effect of Cultural Orientation on Consumer Responses to Personalization , 2007 .

[32]  John Riedl,et al.  GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.

[33]  J. Bettman.  An information processing theory of consumer choice , 1979 .

[34]  Izak Benbasat,et al.  Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs , 2007, J. Manag. Inf. Syst..

[35]  Izak Benbasat,et al.  The Effects of Personalizaion and Familiarity on Trust and Adoption of Recommendation Agents , 2006, MIS Q..

[36]  Kirk L. Wakefield,et al.  Can A Retail Web Site be Social? , 2007 .

[37]  Sirkka L. Jarvenpaa,et al.  Consumer trust in an Internet store , 2000, Inf. Technol. Manag..

[38]  Sui Meng Poon,et al.  Factors influencing the types of products and services purchased over the Internet , 2000, Internet Res..

[39]  Izak Benbasat,et al.  Research Note: The Influence of Recommendations and Consumer Reviews on Evaluations of Websites , 2006, Inf. Syst. Res..

[40]  Pattie Maes,et al.  Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.

[41]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[42]  Izak Benbasat,et al.  A Two-Process View of Trust and Distrust Building in Recommendation Agents: A Process-Tracing Study , 2008, J. Assoc. Inf. Syst..

[43]  Shelly Rodgers,et al.  Development of an Instrument to Measure Web Site Personality , 2006 .

[44]  Milena M. Head,et al.  The Impact of Infusing Social Presence in the Web Interface: An Investigation Across Product Types , 2005, Int. J. Electron. Commer..

[45]  Mayuram S. Krishnan,et al.  The Personalization Privacy Paradox: An Empirical Evaluation of Information Transparency and the Willingness to be Profiled Online for Personalization , 2006, MIS Q..