Should Recommendation Agents Think Like People?

Journal of Service Research, Vol. 8, pp. 297-315, 2006

19 Pages Posted: 18 Jul 2006 Last revised: 19 Nov 2012

See all articles by Lerzan Aksoy

Lerzan Aksoy

Koc University

Paul N. Bloom

Duke University - Center for the Advancement of Social Entrepreneurship (CASE)

Nicholas H. Lurie

University of Connecticut School of Business

Bruce Cooil

Vanderbilt University - Statistics

Abstract

Electronic recommendation agents have the potential to increase the level of service provided by firms operating in the online environment. Recommendation agents assist consumers in making product decisions by generating rank ordered alternative lists based on consumer preferences. However, many of the online agents currently in use rank options in different ways than the consumers they are designed to help. Two experiments examine the role of similarity between an electronic agent and a consumer, in terms of actual similarity of attribute weights and perceived similarity of decision strategies, on the quality of consumer choices. Results indicate that it helps consumers to use a recommendation agent that thinks like them, either in terms of attribute weights or decision strategies. When agents are completely dissimilar, consumers may be no better, and sometimes worse off, using an agent's ordered list than if they simply used a randomly-ordered list of options.

Keywords: Decision-Making, Electronic Commerce, Recommendation Agents, Personalization, Information Search, Latent Class Model

Suggested Citation

Aksoy, Lerzan and Bloom, Paul N. and Lurie, Nicholas H. and Cooil, Bruce, Should Recommendation Agents Think Like People?. Journal of Service Research, Vol. 8, pp. 297-315, 2006. Available at SSRN: https://ssrn.com/abstract=916607

Lerzan Aksoy (Contact Author)

Koc University ( email )

Cayir Cad. No: 5 Istinye
Sariyer 80910, Istanbul, 34450
Turkey

Paul N. Bloom

Duke University - Center for the Advancement of Social Entrepreneurship (CASE) ( email )

Box 90120
Durham, NC 27708-0120
United States
919-660-7914 (Phone)
919-660-8038 (Fax)

Nicholas H. Lurie

University of Connecticut School of Business ( email )

Storrs, CT CT - Connecticut 06269
United States

HOME PAGE: http://www.business.uconn.edu/person/nicholas-lurie/

Bruce Cooil

Vanderbilt University - Statistics ( email )

Nashville, TN 37203
United States

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