Abstract
Recent research on the use of robots in retail settings presents a wide-spread concern among consumers regarding privacy risks and malfunctions in service experiences. This research speculates that such apprehensions likely prevent consumers from sharing information with AI robots, which negatively affects fashion retailers’ abilities to gauge their consumers’ desires. Consumers’ willingness to share (WTS) information helps fashion businesses make strategic marketing decisions. This study identifies seven factors that may lead to high and low WTS information with AI robots through a literature review and implementing interviews. We then build a decision tree predictive model to identify important motivational factors of WTS with AI fashion robots. Our findings indicate that the service quality, enjoyment, usefulness, and trust predict the WTS information with AI robots. Thus, ensuring that consumers understand the benefits AI robot use, including easier and more enjoyable shopping experiences, will increase their interactions with robots. <br>
Highlights
Retailers have traditionally employed AI robots solely in service settings and to expedite the manufacturing processes
Theoretical framework: The foundation of this study is based on Constant et al.’s (1994) information sharing theory, which states that consumers’ willingness to share (WTS) is driven by their rational selfinterest or reciprocity and the social determinants of information sharing
We used decision tree modeling with empirical data using R statistical software
Summary
Retailers have traditionally employed AI robots solely in service settings and to expedite the manufacturing processes. Theoretical framework: The foundation of this study is based on Constant et al.’s (1994) information sharing theory, which states that consumers’ WTS is driven by their rational selfinterest or reciprocity and the social determinants of information sharing. Our qualitative methods included conducting a literature review and implementing 13 personal interviews and a focus group interview (n = 12) to identify the influential factors in WTS.
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