Issues and opinion on structural equation modeling
MIS Quarterly
Automatic personalization based on Web usage mining
Communications of the ACM
Personalization in business-to-customer interaction
Communications of the ACM - The Adaptive Web
Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization
Data Mining and Knowledge Discovery
Trust and Distrust Definitions: One Bite at a Time
Proceedings of the workshop on Deception, Fraud, and Trust in Agent Societies held during the Autonomous Agents Conference: Trust in Cyber-societies, Integrating the Human and Artificial Perspectives
Trust Transfer on the World Wide Web
Organization Science
Developing and Validating Trust Measures for e-Commerce: An Integrative Typology
Information Systems Research
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 06
Distrust and trust in B2C e-commerce: do they differ?
ICEC '06 Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet
Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective
Information Systems Research
Journal of Management Information Systems
Individual Trust in Online Firms: Scale Development and Initial Test
Journal of Management Information Systems
Data mining for web personalization
The adaptive web
Trust and TAM in online shopping: an integrated model
MIS Quarterly
Timing of Adaptive Web Personalization and Its Effects on Online Consumer Behavior
Information Systems Research
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Merchants adopt web personalization technologies to offer product recommendations in the hope of influencing online users' decision making in a shopping process. Although there is a large body of research on the favorable effects of web personalization on influencing online users' decision making, it is often assumed that web personalization functions well. Only scant research examines the adverse outcomes of web personalization on online users' perceptions and behavior when the personalized services malfunction. This research aims to fill this gap. Specifically, we examine malfunctioning personalized services that produce irrelevant and biased product recommendations in online shopping. Irrelevant recommendations are offerings not matched to online users' preferences, whereas biased recommendations are offerings generated for the merchant's interests. When online users encounter such malfunctioning personalized services, they may distrust the personalization agent, which influences their interactions with the agent. We drew on distrust theories to develop six hypotheses. To test the hypotheses, 245 participants were recruited for a field experiment in which they were tasked to download free music tracks from a personalized music download website. Our findings indicate that both irrelevant and biased recommendations lead to high distrust in a personalization agent's competence and integrity. Competence distrust, but not integrity distrust, in a personalization agent negatively influences online users' interactions with the agent.