6533b7d2fe1ef96bd125ebfc

RESEARCH PRODUCT

When more is less: The other side of artificial intelligence recommendation

Yuyu HanSihua ChenShifei ZhaoHan QiuHua XiaoWei HeJian MouMikko T. Siponen

subject

verkkokauppabusiness.industryStrategy and Managementconsumer decision qualitysuosittelujärjestelmätDecision qualityinformation cocoonGeneral Decision ScienceskuluttajakäyttäytyminentekoälyostopäätöksetAI recommendationGeneralLiterature_MISCELLANEOUSManagement Information SystemsVariety (cybernetics)ComputingMethodologies_PATTERNRECOGNITIONControl and Systems EngineeringManagement of Technology and Innovationconsumers' preferencesLower costArtificial intelligenceBusiness and International ManagementEmpirical evidencebusinessEngineering (miscellaneous)

description

Based on consumers' preferences, AI (artificial intelligence) recommendation automatically filters information, which provokes scholars' debate. Supporters believe that by analyzing the consumers' preferences, AI recommendation enables consumers to choose products more quickly and with lower cost. Critics deem that consumers are more easily trapped in information cocoons because of the use of AI recommendation. This reduces the possibility of consumers contacting with a variety of commodities, thus lowering the consumer decision quality. Based on experiments, this paper discusses the moderating role of AI recommendation on the relationship of consumers' preferences and information cocoons. Moreover, it examines the relationship between information cocoons and consumer decision quality. The findings are: AI recommendation strengthens consumers' preferences; consumers' preferences are positively correlated with information cocoons and further leads to the decline of consumers’ decision quality. In the AI era, this paper contributes to revealing the dark sides of AI recommendation and provides empirical evidence for the regulation of AI behaviors. peerReviewed

https://doi.org/10.1016/j.jmse.2021.08.001