Abstract

PurposeThis article aims to develop a new theory that can better explain and predict how and when humans interact with commercial robots. To this end, utility maximization theory (UMT) along with four principles and propositions that may guide how human-to-commercial robot interactions are developed.Design/methodology/approachThis article conceptualizes UMT by drawing from social exchange, conservation of resources, and technology-driven theories.FindingsThis article proposes UMT, which consists of four guiding principles and propositions. First, it is proposed that the human must invest sufficient resources to initiate a human-to-commercial robot interaction. Second, the human forms an expectation of utility gain maximization once a human-to-commercial robot interaction is initiated. Third, the human severs a human-to-commercial robot interaction if the human is unable to witness maximum utility gain upon the interaction. Finally, once the human severs a human-to-commercial robot interaction, the human seeks to reinvest sufficient resources in another human-to-commercial robot interaction with the same expectation of utility maximization.Originality/valueThis article is one of the few studies that offers a theoretical foundation for understanding the interactions between humans and commercial robots. Additionally, this article provides several managerial implications for managing effective human-to-commercial robot interactions.

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