The performance of recommender systems in online shopping: A user-centric study

Abstract This research investigates the effects of preference relaxation on decision-making performance of users in online preference-based product search contexts. We compare four recommender systems based on different preference relaxation methods in extensive user experiments with 111 subjects that use two real-world datasets: 1818 digital cameras and 45,278 used car advertisements gathered from popular e-commerce websites. Our results provide new insights into the positive impact of the Soft-Boundary Preference Relaxation methods on decision-making quality and effort. The paper extends previous studies on this topic and demonstrates that decision aids based on preference relaxation techniques can effectively enhance preference-based product search in online product catalogues and help alleviate common disadvantages of form-based filtering mechanisms.

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

[2]  Lotte Sangstad Sørensen,et al.  The mobile decision maker , 2009 .

[3]  M. F. Luce,et al.  Correlation, conflict, and choice. , 1993 .

[4]  Sean M. McNee,et al.  Interfaces for Eliciting New User Preferences in Recommender Systems , 2003, User Modeling.

[5]  L. K. Branting.  Optimizing return-set size for requirements satisfaction and cognitive load , 2002, Proceedings. Third International Symposium on Electronic Commerce,.

[6]  Francesco Ricci,et al.  COOPERATIVE QUERY REWRITING FOR DECISION MAKING SUPPORT AND RECOMMENDER SYSTEMS , 2007, Appl. Artif. Intell..

[7]  W. Steven Perkins,et al.  Deriving Attribute Utilities From Consideration Sets: an Alternative to Self-Explicated Utilities , 1992 .

[8]  Ralph Bergmann,et al.  Intelligent Customer Support for Product Selection with Case-Based Reasoning , 2002 .

[9]  Philippe Aurier,et al.  Consideration Set Size and Familiarity With Usage Context , 2000 .

[10]  John Roberts,et al.  Development and Testing of a Model of Consideration Set Composition , 1991 .

[11]  Maciej Dabrowski,et al.  Modelling preference relaxation in e-commerce , 2010, International Conference on Fuzzy Systems.

[12]  R. L. Keeney,et al.  Decisions with Multiple Objectives: Preferences and Value Trade-Offs , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[13]  Greg M. Allenby,et al.  A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules , 2004 .

[14]  P. Chandler,et al.  Cognitive load as a factor in the structuring of technical material. , 1990 .

[15]  Maciej Dabrowski,et al.  Comparing Techniques for Preference Relaxation: A Decision Theory Perspective , 2010, EC-Web.

[16]  Izak Benbasat,et al.  Evaluating the Impact of DSS, Cognitive Effort, and Incentives on Strategy Selection , 1999, Inf. Syst. Res..

[17]  P. Nedungadi.  Recall and Consumer Consideration Sets: Influencing Choice without Altering Brand Evaluations , 1990 .

[18]  John W. Payne,et al.  Effort and Accuracy in Choice , 1985 .

[19]  Patrick Bosc,et al.  Incremental controlled relaxation of failing flexible queries , 2009, Journal of Intelligent Information Systems.

[20]  Chih-Hung Liu,et al.  Intelligent agent-based systems for personalized recommendations in Internet commerce , 2002, Expert Syst. Appl..

[21]  Boi Faltings,et al.  Increasing user decision accuracy using suggestions , 2006, CHI.

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

[23]  Sarah Spiekermann.  Online information search with electronic agents , 2001 .

[24]  Ronaldo C. Prati,et al.  An Integrated Environment for Data Mining , 2004 .

[25]  Robert S. Moore,et al.  An Investigation of Agent Assisted Consumer Information Search: Are Consumers Better Off? , 2001 .

[26]  Izak Benbasat,et al.  An Experimental Investigation Of The Relationship Between Decision Makers, Decision Aids and Decision Making Effort , 1993 .

[27]  Markus Stolze,et al.  Soft Navigation in Product Catalogs , 1998, ECDL.

[28]  Gerald Häubl,et al.  "Double Agents": Assessing the Role of Electronic Product Recommendation Systems , 2005 .

[29]  Donald Kossmann,et al.  The Skyline operator , 2001, Proceedings 17th International Conference on Data Engineering.

[30]  Rex Eugene Pereira,et al.  Influence of Query-Based Decision Aids on Consumer Decision Making in Electronic Commerce , 2001, Inf. Resour. Manag. J..

[31]  J. Payne,et al.  Measuring Constructed Preferences: Towards a Building Code , 1999 .

[32]  Boi Faltings,et al.  Enriching buyers' experiences: the SmartClient approach , 2000, CHI.

[33]  Gerhard Friedrich,et al.  An Integrated Environment for the Development of Knowledge-Based Recommender Applications , 2006, Int. J. Electron. Commer..

[34]  Boi Faltings,et al.  Preference-based search with adaptive recommendations , 2008, AI Commun..

[35]  Eric J. Johnson,et al.  The adaptive decision maker , 1993 .

[36]  Stephen J.S. Holden.  Individual and Situational Influences on Purchase Goal Specification , 1994 .

[37]  Don N. Kleinmuntz,et al.  Anticipations of Effort and Accuracy in Multiattribute Choice , 1995 .

[38]  Noreen M. Klein,et al.  Assessing Unacceptable Attribute Levels in Conjoint Analysis , 1987 .

[39]  Allan D. Shocker,et al.  Consideration set influences on consumer decision-making and choice: Issues, models, and suggestions , 1991 .

[40]  W. Bearden,et al.  Consumer Self‐Confidence: Refinements in Conceptualization and Measurement , 2001 .

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

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

[43]  Eric J. Johnson,et al.  Behavioral decision research: A constructive processing perspective. , 1992 .

[44]  Yoon Ho Cho,et al.  A user-oriented contents recommendation system in peer-to-peer architecture , 2004, Expert Syst. Appl..

[45]  Izak Benbasat,et al.  Understanding Customer Trust in Agent-Mediated Electronic Commerce, Web-Mediated Electronic Commerce, and Traditional Commerce , 2004, Inf. Technol. Manag..

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

[47]  Kirsten Swearingen,et al.  Beyond Algorithms: An HCI Perspective on Recommender Systems , 2001 .

[48]  Donald R. Lehmann,et al.  Consumer Experience and Consideration Sets For Brands and Product Categories , 1997 .

[49]  Boi Faltings,et al.  Conversational recommenders with adaptive suggestions , 2007, RecSys '07.

[50]  I. Benbasat,et al.  The Influence of Decision Aids on Choice Strategies: An Experimental Analysis of the Role of Cognitive Effort , 1994 .

[51]  Katherine N. Lemon,et al.  The Effect of Local Consideration Sets on Global Choice Between Lower Price and Higher Quality , 1993 .

[52]  Ramesh Sharda,et al.  Development of a fisheye-based information search processing aid (FISPA) for managing information overload in the web environment , 2004, Decis. Support Syst..

[53]  A. Rangaswamy,et al.  A Fuzzy Set Model of Search and Consideration with an Application to an Online Market , 2003 .

[54]  Armin Stahl,et al.  Combining Case-Based and Similarity-Based Product Recommendation , 2006, ECCBR.

[55]  Hans van der Heijden,et al.  Intelligent product search with soft-boundary preference relaxation , 2012, Expert Syst. Appl..

[56]  Barry Smyth,et al.  Case-based recommender systems , 2005, The Knowledge Engineering Review.

[57]  Gerald Häubl,et al.  The Fiction of No Friction: A User Skills Approach to Cognitive Lock-In , 2002 .

[58]  Salvador Ruiz,et al.  Consideration sets in online shopping environments: the effects of search tool and information load , 2009, Electron. Commer. Res. Appl..

[59]  Rick L. Andrews,et al.  Studying Consideration Effects in Empirical Choice Models Using Scanner Panel Data , 1995 .

[60]  Robert D. Macredie,et al.  The assessment of usability of electronic shopping: A heuristic evaluation , 2005, Int. J. Inf. Manag..

[61]  David McSherry,et al.  Retrieval Failure and Recovery in Recommender Systems , 2005, Artificial Intelligence Review.

[62]  Tor Guimaraes,et al.  Assessing the impact of internet agent on end users' performance , 2005, Decis. Support Syst..

[63]  Robert E. Widing,et al.  Are interactive decision aids better than passive decision aids? A comparison with implications for information providers on the internet , 2002 .

[64]  Francesco Ricci,et al.  Supporting User Query Relaxation in a Recommender System , 2004, EC-Web.

[65]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[66]  John G. Lynch,et al.  Smart Agents: When Lower Search Costs for Quality Information Increase Price Sensitivity , 2003 .

[67]  Gerald Häubl,et al.  Personalization without Interrogation: Towards more Effective Interactions between Consumers and Feature-Based Recommendation Agents , 2009 .

[68]  Hans van der Heijden.  Mobile decision support for in-store purchase decisions , 2006, Decis. Support Syst..

[69]  Roger Jianxin Jiao,et al.  An associative classification-based recommendation system for personalization in B2C e-commerce applications , 2007, Expert Syst. Appl..

[70]  Ralph L. Keeney,et al.  Decisions with multiple objectives: preferences and value tradeoffs , 1976 .

[71]  Alexander Felfernig,et al.  Utility-Based Repair of Inconsistent Requirements , 2009, IEA/AIE.