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Do Perceived Values Influence User Identification and Attitudinal Loyalty in Social Robots? The Mediating Role of Active Involvement

Hua Pang, Zhen Wang, Lei Wang

Year
2025
Citations
1
Access
Open access

Abstract

With the rapid advancement of artificial intelligence, the deployment of social robots has significantly broadened, extending into diverse fields such as education, medical services, and business. Despite this expansive growth, there remains a notable scarcity of empirical research addressing the underlying psychological mechanisms that influence human-robot interactions. To address this critical research gap, the present study proposes and empirically tests a theoretical model designed to elucidate how users' multi-dimensional perceived values of social robots influence their attitudinal responses and outcomes. Based on questionnaire data from 569 social robot users, the study reveals that users' perceived utilitarian value, emotional value, and hedonic value all exert significant positive effects on active involvement, thereby fostering their identification and reinforcing attitudinal loyalty. Among these dimensions, emotional value emerged as the strongest predictor, underscoring the pivotal role of emotional orientation in cultivating lasting human-robot relationships. Furthermore, the findings highlight the critical mediating function of active involvement in linking perceived value to users' psychological sense of belonging, thereby elucidating the mechanism through which perceived value enhances engagement and promotes sustained long-term interaction. These findings extend the conceptual boundaries of human-machine interaction, offer a theoretical foundation for future explorations of user psychological mechanisms, and inform strategic design approaches centered on emotional interaction and user-oriented experiences, providing practical guidance for optimizing social robot design in applications.

Keywords

Identification (biology)Value (mathematics)LoyaltyFunction (biology)ScarcityEmpirical researchFoundation (evidence)Conceptual model

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