顾客在实体零售店使用人工智能的准备程度因素:消费者态度与性别差异的相互作用

Information Pub Date : 2024-06-12 DOI:10.3390/info15060346
Nina Kolar, B. Milfelner, Aleksandra Pisnik
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摘要

为了解决实体零售店中消费者态度与人工智能(AI)使用准备之间微妙的相互作用问题,本研究的主要目的是测试先前经验的影响、人工智能技术的感知风险、消费者管理人工智能技术能力的自我评估以及性别在这一关系中的调节作用。本研究使用结构方程建模(SEM)方法,对 243 名熟悉人工智能技术的消费者的数据进行了定量横截面调查分析,以探讨实体零售店背景下的这些动态变化。此外,在对两个性别群体进行不变量分析后,还测试了调节作用。主要研究结果表明,先前对人工智能技术的积极体验会对实体零售店的人工智能使用准备程度产生积极影响,而人工智能技术的感知风险则会起到阻碍作用。性别差异在很大程度上缓和了这些影响,人工智能技术的风险感知对女性的人工智能使用准备程度产生了更大的负面影响,而对管理人工智能技术能力的自我评估则对男性的人工智能使用准备程度产生了更大的积极影响。研究得出结论,零售商必须考虑这些不同性别对人工智能的看法和态度,以制定更有效的技术整合战略。我们的研究还强调,在采用人工智能技术时,有必要消除性别障碍和偏见。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors for Customers’ AI Use Readiness in Physical Retail Stores: The Interplay of Consumer Attitudes and Gender Differences
In addressing the nuanced interplay between consumer attitudes and Artificial Intelligence (AI) use readiness in physical retail stores, the main objective of this study is to test the impacts of prior experience, as well as perceived risks with AI technologies, self-assessment of consumers’ ability to manage AI technologies, and the moderator role of gender in this relationship. Using a quantitative cross-sectional survey, data from 243 consumers familiar with AI technologies were analyzed using structural equation modeling (SEM) methods to explore these dynamics in the context of physical retail stores. Additionally, the moderating impacts were tested after the invariance analysis across both gender groups. Key findings indicate that positive prior experience with AI technologies positively influences AI use readiness in physical retail stores, while perceived risks with AI technologies serve as a deterrent. Gender differences significantly moderate these effects, with perceived risks with AI technologies more negatively impacting women’s AI use readiness and self-assessment of the ability to manage AI technologies showing a stronger positive impact on men’s AI use readiness. The study concludes that retailers must consider these gender-specific perceptions and attitudes toward AI to develop more effective strategies for technology integration. Our research also highlights the need to address gender-specific barriers and biases when adopting AI technology.
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