Abstract
Understanding privacy needs has become paramount in the evolving landscape of social robots in the hospitality industry. Traditional privacy concerns, dominated by transactional interactions, fail to encapsulate the complexities of human-social robot interaction on service frontlines. Drawing from the communication management theory and the media equation theory, this study conceptualized "Social Robot Privacy Concerns" (SRPC) and discovered its multidimensionality. The SRPC construct is characterized by three key dimensions: (1) Information Privacy Concern, addressing data management and collection; (2) Interpersonal Privacy Concern, focusing on the robot's physical presence; and (3) Environmental Privacy Concern, encompassing broader contexts of government regulations, media influence, and surveillance mechanisms. The findings unveil that these dimensions are pivotal in navigating the challenges posed by service robots implemented in the hospitality industry, necessitating a nuanced approach to understanding and addressing emergent privacy needs. This study also empirically validated the scale to measure the SRPC construct, providing a foundational tool for future research.
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