Reducing perceived deceptiveness of e-commerce product recommendation agents: An empirical examination of the relative impact of transparency and verifiability and the moderating role of gender

Bo Sophia XIAO, Chee Wee Tan

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

Product Recommendations Agents (PRAs) are software applications that augment consumers' purchasing decisions by offering product recommendations based on consumers' preferences that are elicited either explicitly or implicitly. The underlying premise of PRAs is often grounded on the assumption that PRAs seek to optimize consumers' utility with the recommendations provided. However, since a majority of commercial PRAs are implemented by parties with vested interests in product sales, it is highly probable that recommendations are biased in favor of their providers and do not reflect consumers' interests. This in turn may possibly induce a deceptiveness perception among consumers. As such, this study theorizes and empirically demonstrates that the induction of IT-mediated components in PRAs, which induce high levels of perceived transparency and perceived verifiability, could be useful in mitigating consumers' perceived deceptiveness of PRAs. This study also explores the moderating role of gender in the relationship between transparency/verifiability perception and deceptiveness perception.

Original languageEnglish
Title of host publication18th Americas Conference on Information Systems 2012, AMCIS 2012
Pages3801-3810
Number of pages10
Publication statusPublished - 2012
Event18th Americas Conference on Information Systems 2012, AMCIS 2012 - Seattle, WA, United States
Duration: 9 Aug 201212 Aug 2012

Publication series

Name18th Americas Conference on Information Systems 2012, AMCIS 2012
Volume5

Conference

Conference18th Americas Conference on Information Systems 2012, AMCIS 2012
Country/TerritoryUnited States
CitySeattle, WA
Period9/08/1212/08/12

Scopus Subject Areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Library and Information Sciences

User-Defined Keywords

  • Deception
  • Electronic commerce
  • Gender
  • Product recommendation agents
  • Transparency
  • Verifiability

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