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Conceptualization of privacy concerns and their influence on consumers' resistance to AI-based recommender systems in e-commerce
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DOI：10.1108/IMDS-03-2024-0251.png)
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Abstract
En 中文
Purpose-The artificial intelligence-based recommender system (AIRS) provides personalization and convenience for enhancing customer experience but triggers customers' resistance arising from privacy concerns. Few studies have investigated what privacy concerns arise from the AIRS in e-commerce as well as how these privacy concerns influence consumers' resistance to the AIRS in e-commerce. This study aims to conceptualize privacy concerns and explore their influence on consumers' resistance to the AIRS in e-commerce. Design/methodology/approach-A mixed-methods approach is used. Study 1 identifies the context-specific privacy concerns related to the AIRS in e-commerce by interviewing 23 consumers. Study 2 examines the influence of context-specific privacy concerns on consumers' resistance to the AIRS in e-commerce by surveying 557 consumers. Findings-Study 1 reveals that privacy concerns related to the AIRS in e-commerce manifest in perceived surveillance, perceived identity theft and perceived unauthorized secondary use. Study 2 finds that three privacy concerns have three effects on resistance intention: direct, completely mediated by resistance attitude and partially mediated by resistance attitude. Additionally, prior privacy invasion experience strengthens the positive attitude-intention relationship. Originality/value-This study contributes to the literature in three key aspects. Firstly, this study advances the knowledge about privacy concerns by identifying context-specific privacy concerns related to AIRSs in e-commerce. Secondly, this study extends the belief-attitude-intention framework to explain the linkage among the privacy concerns related to AIRSs in e-commerce, resistance attitude and resistance intention. Thirdly, this study adds new insight to the literature on user resistance by examining consumers' resistance to e-commerce AIRSs from a privacy perspective.
Keywords:
Artificial intelligence
Mixed methods
Privacy concern
User resistance
E-commerce
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