Publication date: Available online 16 March 2018
Source:Decision Support Systems
Author(s): Bo Xiao, Izak Benbasat
To assist consumers in product search and selection while shopping online, many e-commerce retailers have implemented web-based product recommendation agents (PRAs). However, consumers are empowered to the extent that the PRAs provide true personalization by recommending products based solely on, and thus best representing, consumers' preferences. This study constructs and empirically tests a theoretical model that examines how biased recommendations from PRAs influence consumers' decision quality and decision effort . The results of an online experiment show that consumers are extremely vulnerable to biased personalized recommendations from online PRAs. In addition, our results extend prior research by identifying perceived personalization as a critical mechanism driving the influence of biased PRA on consumers' decision quality and decision effort. This study fills a void in the literature and calls attention to an insidious form of manipulation made possible by innovative technologies supporting e-commerce.
Source:Decision Support Systems
Author(s): Bo Xiao, Izak Benbasat