Artificial intelligence or human: when and why consumers prefer AI recommendations

IF 4.9 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
Fei Jin, Xiaodan Zhang
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引用次数: 0

Abstract

Purpose Artificial intelligence (AI) is revolutionizing product recommendations, but little is known about consumer acceptance of AI recommendations. This study examines how to improve consumers' acceptance of AI recommendations from the perspective of product type (material vs experiential). Design/methodology/approach Four studies, including a field experiment and three online experiments, tested how consumers' preference for AI-based (vs human) recommendations differs between material and experiential product purchases. Findings Results show that people perceive AI recommendations as more competent than human recommendations for material products, whereas they believe human recommendations are more competent than AI recommendations for experiential products. Therefore, people are more (less) likely to choose AI recommendations when buying material (vs experiential) products. However, this effect is eliminated when is used as an assistant to rather than a replacement for a human recommendation. Originality/value This study is the first to focus on how products' material and experiential attributes influence people's attitudes toward AI recommendations. The authors also identify under what circumstances resistance to algorithmic advice is attenuated. These findings contribute to the research on the psychology of artificial intelligence and on human–technology interaction by investigating how experiential and material attributes influence preference for or resistance to AI recommenders.
人工智能还是人类:消费者何时以及为何更喜欢人工智能推荐
人工智能(AI)正在彻底改变产品推荐,但消费者对人工智能推荐的接受程度却知之甚少。本研究从产品类型(物质vs体验)的角度探讨如何提高消费者对人工智能推荐的接受度。设计/方法/方法四项研究,包括一个现场实验和三个在线实验,测试了消费者对基于人工智能(与人类)的推荐的偏好在物质和体验式产品购买之间的差异。结果表明,人们认为人工智能推荐比人类推荐的物质产品更有能力,而他们认为人工推荐比人工推荐的体验产品更有能力。因此,人们在购买实物(而不是体验式)产品时更有可能(或更少)选择人工智能推荐。然而,当它被用作辅助而不是替代人工推荐时,这种影响就会消除。独创性/价值这项研究首次关注产品的材料和体验属性如何影响人们对人工智能推荐的态度。作者还指出,在什么情况下,对算法建议的抵制会减弱。这些发现通过调查经验和物质属性如何影响对人工智能推荐的偏好或抵制,有助于人工智能心理学和人类技术互动的研究。
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 Technology & People
Information Technology & People INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
8.20
自引率
13.60%
发文量
121
期刊介绍: Information Technology & People publishes work that is dedicated to understanding the implications of information technology as a tool, resource and format for people in their daily work in organizations. Impact on performance is part of this, since it is essential to the well being of employees and organizations alike. Contributions to the journal include case studies, comparative theory, and quantitative research, as well as inquiries into systems development methods and practice.
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