Designing Warning Messages for Detecting Biased Online Product Recommendations: An Empirical Investigation

Bo Xiao () and Izak Benbasat ()
Additional contact information
Bo Xiao: Information Technology Management Department, Shidler College of Business, University of Hawai’i at Mānoa, Honolulu, Hawaii 96822
Izak Benbasat: Sauder School of Business, University of British Columbia, Vancouver, British Columbia V6T 1Z2, Canada

Information Systems Research, 2015, vol. 26, issue 4, 793-811

Abstract: The increasing adoption of product recommendation agents (PRAs) by e-commerce merchants makes it an important area of study for information systems researchers. PRAs are a type of Web personalization technology that provides individual consumers with product recommendations based on their product-related needs and preferences expressed explicitly or implicitly. Whereas extant research mainly assumes that such recommendation technologies are designed to benefit consumers and focuses on the positive impact of PRAs on consumers’ decision quality and decision effort, this study represents an early effort to examine PRAs that are designed to produce their recommendations on the basis of benefiting e-commerce merchants (rather than benefiting consumers) and to investigate how the availability and the design of warning messages (a potential detection support mechanism) can enhance consumers’ performance in detecting such biased PRAs. Drawing on signal detection theory, the literature on warning messages, and the literature on message framing, we identified two content design characteristics of warning messages—the inclusion of risk-handling advice and the framing of risk-handling advice—and investigated how they influence consumers’ detection performance. The results of an online experiment reveal that a simple warning message without accompanying advice on how to detect bias is a double-edged sword, because it increases correct detection of biased PRAs ( hits ) at the cost of increased incorrect detection ( false alarms ). By contrast, including in warning messages risk-handling advice about how to check for bias (particularly when the advice is framed to emphasize the loss from not following the advice) increases correct detection and, more importantly, also decreases incorrect detection. The patterns of findings are in line with the predictions of signal detection theory. With an enriched understanding of how the availability and the content design of warning messages can assist consumers in the context of PRA-assisted online shopping, the results of this study serve as a basis for future theoretical development and yield valuable insights that can guide practice and the design of effective warning messages.

Keywords: electronic commerce; product recommendation agent; personalization; bias; signal detection theory; manipulative practices; warning; message framing; online experiment (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://dx.doi.org/10.1287/isre.2015.0592 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:orisre:v:26:y:2015:i:4:p:793-811

Access Statistics for this article

More articles in Information Systems Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().