Navigating the perceived credibility and adoption of AI-generated review summaries in online shopping: An affordance perspective

IF 6.9 1区管理学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information Processing & Management Pub Date : 2025-09-18 DOI:10.1016/j.ipm.2025.104404

Mingxia Jia , Yuxiang Zhao Chris , Xiaoyu Zhang

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引用次数: 0

Abstract

As generative AI (GenAI) advances, e-commerce platforms increasingly leverage AI-generated review summaries to facilitate consumer decision-making. However, given the experience-driven nature of online review consumption, whether consumers perceive these summaries as credible, useful, and adoptable remains a key challenge to their effective implementation. Therefore, using affordance actualization theory, we conducted a scenario-based experiment and survey to analyze the quantitative data from 713 consumers (N_search product = 356, N_experience product = 357) regarding their perceptions of AI-generated review summaries. The findings show that functional affordances (algorithmic transparency, understandability, and convenience) and symbolic expressions (conveyed values and meanings) toward AI-generated review summaries play important roles in shaping consumers’ perceived credibility. Among them, algorithmic transparency, meaning conveyed, and understandability were identified as strong predictors. Perceived credibility further predicts perceived helpfulness, which, in turn, motivates users’ intentions to adopt AI-generated review summaries and contribute to consumer reviews. Interestingly, these influence pathways differ significantly depending on whether the product is a search or an experience product. This study provides an empirical investigation into the pathway from affordance to actualized belief and behavioral intention in the AI-generated review summaries context and offers practical insights for its effective application in AI-powered marketing.

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在网上购物中导航人工智能生成的评论摘要的感知可信度和采用：一个可视性的角度

随着生成式人工智能（GenAI）的发展，电子商务平台越来越多地利用人工智能生成的评论摘要来促进消费者决策。然而，考虑到在线评论消费的经验驱动性质，消费者是否认为这些摘要是可信的、有用的和可接受的，仍然是它们有效实现的关键挑战。因此，我们利用可视性实现理论，进行了基于场景的实验和调查，分析了713名消费者（N_search产品= 356，N_experience产品= 357）对人工智能生成的评论摘要的看法的定量数据。研究结果表明，对人工智能生成的评论摘要的功能支持（算法透明度、可理解性和便利性）和符号表达（传达的价值和意义）在塑造消费者感知可信度方面发挥着重要作用。其中，算法透明度、所传达的含义和可理解性被认为是强有力的预测因素。感知到的可信度进一步预测了感知到的有用性，这反过来又激励用户采用人工智能生成的评论摘要，并为消费者评论做出贡献。有趣的是，这些影响途径根据产品是搜索产品还是体验产品而有显著差异。本研究对人工智能生成的评论摘要背景下从提供到实现信念和行为意图的途径进行了实证调查，并为其在人工智能驱动的营销中的有效应用提供了实践见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Information Processing & Management 工程技术-计算机：信息系统

CiteScore

17.00

自引率

11.60%

发文量

276

审稿时长

39 days

期刊介绍： Information Processing and Management is dedicated to publishing cutting-edge original research at the convergence of computing and information science. Our scope encompasses theory, methods, and applications across various domains, including advertising, business, health, information science, information technology marketing, and social computing. We aim to cater to the interests of both primary researchers and practitioners by offering an effective platform for the timely dissemination of advanced and topical issues in this interdisciplinary field. The journal places particular emphasis on original research articles, research survey articles, research method articles, and articles addressing critical applications of research. Join us in advancing knowledge and innovation at the intersection of computing and information science.