System- vs. consumer-generated recommendations: affective and social-psychological effects on purchase intention

ABSTRACT Although online product recommendation (OPR) is important in e-commerce transactions, there is a little understanding about differential impact of different recommendations. This study aims to examine the distinct effects of system-generated recommendation (SGR) and consumer-generated recommendation (CGR) on affective and social-psychological beliefs of OPR evaluation and to assess how they mediate the impact of OPR usage on purchase intentions. Results of a cross-sectional survey with 482 Amazon consumers showed that users of CGR express significantly higher trusting beliefs than users of SGR, while users of SGR elicit greater perceived enjoyment than users of CGR, resulting in mediating effect on purchase intentions. Moreover, CGRs were found to elicit greater trusting beliefs for experience products, while SGRs were found to unfold greater perceived enjoyment for search products.

[1]  M. Sujan,et al.  Consumer Knowledge: Effects on Evaluation Strategies Mediating Consumer Judgments , 1985 .

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

[3]  H. Cheong,et al.  Consumers’ Reliance on Product Information and Recommendations Found in UGC , 2008 .

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

[5]  M. Sarstedt,et al.  A new criterion for assessing discriminant validity in variance-based structural equation modeling , 2015 .

[6]  Ainin Sulaiman,et al.  Impact of instrumental and social-psychological beliefs on customer satisfaction with online product recommendations , 2016 .

[7]  Ping Zhang,et al.  Toward a positive design theory: Principles for designing motivating information and communication technology , 2008 .

[8]  Etta Y. I. Chen,et al.  Consumers' Online Information Search Behavior and the Phenomenon of Search vs. Experience Products , 2004 .

[9]  BenbasatIzak,et al.  E-commerce product recommendation agents , 2007 .

[10]  Valerie J. Trifts,et al.  Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids , 2000 .

[11]  Kar Yan Tam,et al.  The Effects of Post-Adoption Beliefs on the Expectation-Confirmation Model for Information Technology Continuance , 2006, Int. J. Hum. Comput. Stud..

[12]  S. Sénécal,et al.  The influence of online product recommendations on consumers' online choices , 2004 .

[13]  Matthew K. O. Lee,et al.  The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities , 2008, Internet Res..

[14]  Ram D. Gopal,et al.  Empirical Analysis of the Impact of Recommender Systems on Sales , 2010, J. Manag. Inf. Syst..

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

[16]  Arun Sundararajan,et al.  The Visible Hand? Demand Effects of Recommendation Networks in Electronic Markets , 2012, Manag. Sci..

[17]  Nada Nasr Bechwati,et al.  Word of Mouse , 2008 .

[18]  Tong Bao,et al.  Why Amazon Uses Both the New York Times Best Seller List and Customer Reviews: An Empirical Study of Multiplier Effects on Product Sales from Multiple Earned Media , 2014, Decis. Support Syst..

[19]  Sylvain Senecal,et al.  Using Recommendation Agents to Cope with Information Overload , 2012, Int. J. Electron. Commer..

[20]  David L. Mothersbaugh,et al.  Information content and consumer readership of print ads: A comparison of search and experience products , 2004 .

[21]  James C. Ward,et al.  Virtual Community: a Sociocognitive Analysis , 1996 .

[22]  Joseph S. Valacich,et al.  The Influence of Website Characteristics on a Consumer's Urge to Buy Impulsively , 2009, Inf. Syst. Res..

[23]  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..

[24]  K. Barriball,et al.  Non-response in survey research: a methodological discussion and development of an explanatory model. , 1999, Journal of advanced nursing.

[25]  Peter C. Neijens,et al.  "Highly Recommended!" The Content Characteristics and Perceived Usefulness of Online Consumer Reviews , 2011, J. Comput. Mediat. Commun..

[26]  Terry S. Overton,et al.  Estimating Nonresponse Bias in Mail Surveys , 1977 .

[27]  Andrew Whinston,et al.  The Dynamics of Online Word-of-Mouth and Product Sales: An Empirical Investigation of the Movie Industry , 2008 .

[28]  Rajiv Vaidyanathan,et al.  Eliciting Online Customers’ Preferences: Conjoint vs Self-Explicated Attribute-Level Measurements , 2003 .

[29]  Izak Benbasat,et al.  The Nature and Consequences of Trade-Off Transparency in the Context of Recommendation Agents , 2014, MIS Q..

[30]  G. Häubl,et al.  Preference Construction and Persistence in Digital Marketplaces: The Role of Electronic Recommendation Agents , 2003 .

[31]  Zhijie Lin,et al.  An empirical investigation of user and system recommendations in e-commerce , 2014, Decis. Support Syst..

[32]  Vladimir Zwass,et al.  Co-Creation: Toward a Taxonomy and an Integrated Research Perspective , 2010, Int. J. Electron. Commer..

[33]  Haiyang Yang,et al.  Consumer Decision Making , 2015 .

[34]  Dwayne D. Gremler,et al.  Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? , 2004 .

[35]  Do-Hyung Park,et al.  eWOM overload and its effect on consumer behavioral intention depending on consumer involvement , 2008, Electron. Commer. Res. Appl..

[36]  Izak Benbasat,et al.  Investigating the Influence of the Functional Mechanisms of Online Product Presentations , 2007 .

[37]  Chuan-Hoo Tan,et al.  Comprehension and Assessment of Product Reviews: A Review-Product Congruity Proposition , 2013, J. Manag. Inf. Syst..

[38]  Ming-Chi Lee,et al.  Explaining and predicting users' continuance intention toward e-learning: An extension of the expectation-confirmation model , 2010, Comput. Educ..

[39]  Ann E. Schlosser.  Experiencing Products in the Virtual World: The Role of Goal and Imagery in Influencing Attitudes versus Purchase Intentions , 2003 .

[40]  Thomas Hess,et al.  Differential Effects of Provider Recommendations and Consumer Reviews in E-Commerce Transactions: An Experimental Study , 2012, J. Manag. Inf. Syst..

[41]  Izak Benbasat,et al.  Virtual Product Experience: Effects of Visual and Functional Control of Products on Perceived Diagnosticity and Flow in Electronic Shopping , 2004, J. Manag. Inf. Syst..

[42]  W. Kintsch,et al.  Reading comprehension and readability in educational practice and psychological theory , 1979 .

[43]  Gianfranco Walsh,et al.  Electronic Word-of-Mouth: Motives for and Consequences of Reading Customer Articulations on the Internet , 2003, Int. J. Electron. Commer..

[44]  Huaping Chen,et al.  Credibility of Electronic Word-of-Mouth: Informational and Normative Determinants of On-line Consumer Recommendations , 2009, Int. J. Electron. Commer..

[45]  Jing Li,et al.  Information self-efficacy and information channels: Decision quality and online shopping satisfaction , 2013, Online Inf. Rev..

[46]  Ronnie Silverblatt,et al.  Influence of Product Class on Preference for Shopping on the Internet , 2006, J. Comput. Mediat. Commun..

[47]  Subhash Sharma,et al.  Effects of online communication practices on consumer perceptions of performance uncertainty for search and experience goods , 2007 .

[48]  Martin Spann,et al.  The Interplay Between Online Consumer Reviews and Recommender Systems: An Experimental Analysis , 2014, Int. J. Electron. Commer..

[49]  M. Sobel.  Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models , 1982 .

[50]  BenbasatIzak,et al.  The effects of personalizaion and familiarity on trust and adoption of recommendation agents , 2006 .

[51]  Marko Sarstedt,et al.  PLS-SEM: Indeed a Silver Bullet , 2011 .

[52]  Detmar W. Straub,et al.  Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs , 1999, MIS Q..

[53]  C. Dennis,et al.  Determinants of Customer Continuance Intention of Online Shopping , 2011 .

[54]  Ainin Sulaiman,et al.  Effects of Post-Adoption Beliefs on the Online Product Recommendation continuance: an Extension of is continuance Model , 2016, PACIS.

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

[56]  Izak Benbasat,et al.  Trust In and Adoption of Online Recommendation Agents , 2005, J. Assoc. Inf. Syst..

[57]  F. Kardes,et al.  The Role of Direction of Comparison, Attribute-Based Processing, and Attitude-Based Processing in Consumer Preference , 1999 .

[58]  Ling Ma,et al.  What Makes a Helpful Online Review for Healthcare Services? An Empirical Analysis of Haodaifu Website , 2019 .

[59]  James R. Marsden,et al.  Consumer Search and Retailer Strategies in the Presence of Online Music Sharing , 2006, J. Manag. Inf. Syst..

[60]  P. Nelson.  Information and Consumer Behavior , 1970, Journal of Political Economy.

[61]  Yong Liu.  Word-of-Mouth for Movies: Its Dynamics and Impact on Box Office Revenue , 2006 .

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

[63]  Prasad A. Naik,et al.  Understanding the Impact of Synergy in Multimedia Communications , 2003 .

[64]  Scott D. Johnson,et al.  Influences on consumer use of word-of-mouth recommendation sources , 1997 .

[65]  Marko Sarstedt,et al.  Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research , 2014 .

[66]  N. Etcoff,et al.  Beauty and the beholder , 1994, Nature.

[67]  Yong-Soon Kang,et al.  Beauty and the Beholder: Toward an Integrative Model of Communication Source Effects , 2006 .

[68]  David Schuff,et al.  What Makes a Helpful Review? A Study of Customer Reviews on Amazon.com , 2010 .

[69]  Nicholas H. Lurie,et al.  Searching for Experience on the Web: An Empirical Examination of Consumer Behavior for Search and Experience Goods , 2009 .

[70]  V. Swaminathan.  The Impact of Recommendation Agents on Consumer Evaluation and Choice: The Moderating Role of Category Risk, Product Complexity, and Consumer Knowledge , 2003 .

[71]  R. Briggs,et al.  Association for Information Systems , 2009 .

[72]  Ian Linton,et al.  Integrated marketing communications , 2018 .

[73]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[74]  David A. Griffith,et al.  The Role of Interface in Electronic Commerce: Consumer Involvement with Print Versus On-Line Catalogs , 2001, Int. J. Electron. Commer..