Designing for Diagnosticity and Serendipity: An Investigation of Social Product-Search Mechanisms

• 成果类型: Article
• 署名作者: Yi, Cheng; Jiang, Zhenhui (Jack); Benbasat, Izak
• 署名单位: Tsinghua University; Tsinghua University; National University of Singapore; University of British Columbia
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2017.0695
• 发表日期: 2017
• 页码: 413-429
• 关键词: information-seeking; recommender systems; decision-making; online; MODEL; environments; integration; PERSONALIZATION; generation; BEHAVIOR

摘要

Users are increasingly sharing their product interests and experiences with others on e-commercewebsites. For example, users can tag products using their ownwords, and these product tags then serve as navigation cues for other users who want to search for products. Also, socially endorsed information contributors are sometimes highlighted on websites and serve as direct information sources. This study examines the effects of these two distinct social product search cues, product tags and socially endorsed people, on users' perceived diagnosticity and serendipity of their product search experience. While product tags support product navigation via a variety of product features tagged by the community, access to socially endorsed people enables users to browse diverse and high-quality alternatives favored by these individuals. We constructed an experimental website using real data from one of the largest social-network-based product-search websites in China to conduct an empirical study. The results of this study show that product tags help users to locate and evaluate relevant alternatives, thus enhancing the perceived diagnosticity of product search, whereas the integration of product tags and access to socially endorsed people enables users to conduct even more serendipitous searches. In addition, both perceived diagnosticity and perceived serendipity of a search experience positively affect users' decision satisfaction.