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As social robots are becoming more prevalent in our society, it is beneficial to understand how people form first impressions of them and eventually come to trust and accept them. A literature review provides an overview of user acceptance models, stereotype content model theory and trustworthiness characteristics. An online user study with 236 participants evaluates people’s first impressions along the dimensions of warmth and competence, their perceptions of a robot’s trustworthiness and their intention to interact with it. Multiple regression identifies significant predictors of use intention and hierarchical regression determines that a regression model including trustworthiness variables alongside classic UTAUT model constructs explains significantly more variance than the original model. Warmth and competence significantly predict trustworthiness. The implications of the findings are discussed. This study contributes to human-robot interaction research by uncovering new variables that determine people’s propensity to accept social robots.

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What Makes People Use Social Robots? Integrating Trustworthiness Into the UTAUT Model

  • 会议论文

  • 发表日期：

    2025年

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  • Katrin Fischer,
  • Donggyu Kim,
  • Joo-Wha Hong

摘要

As social robots are becoming more prevalent in our society, it is beneficial to understand how people form first impressions of them and eventually come to trust and accept them. A literature review provides an overview of user acceptance models, stereotype content model theory and trustworthiness characteristics. An online user study with 236 participants evaluates people’s first impressions along the dimensions of warmth and competence, their perceptions of a robot’s trustworthiness and their intention to interact with it. Multiple regression identifies significant predictors of use intention and hierarchical regression determines that a regression model including trustworthiness variables alongside classic UTAUT model constructs explains significantly more variance than the original model. Warmth and competence significantly predict trustworthiness. The implications of the findings are discussed. This study contributes to human-robot interaction research by uncovering new variables that determine people’s propensity to accept social robots.