The effects of robot anthropomorphic characteristics on employees’ anti-robot sabotage
Abstract Robot anthropomorphic characteristics have not only been widely manifested in production practices, but their positive effects on human–robot interaction have also been investigated and validated in academic research. Nonetheless, existing research has not adequately addressed the potential...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-05405-2 |
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| Summary: | Abstract Robot anthropomorphic characteristics have not only been widely manifested in production practices, but their positive effects on human–robot interaction have also been investigated and validated in academic research. Nonetheless, existing research has not adequately addressed the potential adverse effects of robot anthropomorphic characteristics. To gain a more comprehensive understanding of their influence, this study introduces a dual-edged sword effect model based on cognitive-experiential self-theory. Specifically, we posit that robot anthropomorphic characteristics can empower employees with perceived relational energy, thereby reducing anti-robot sabotage. However, they may also heighten employees’ perceived job threat, potentially resulting in more anti-robot sabotage. Furthermore, we argue that employee openness to experience amplifies the indirect effects of these characteristics on employees’ anti-robot sabotage through perceived relational energy, while mitigating those mediated by perceived job threat. Empirical evidence supporting our hypotheses was gathered through a paired field study involving 622 employees and their store managers, illustrating how robot anthropomorphic characteristics shape employee perceptions and subsequent actions. This research contributes to a deeper understanding of robot anthropomorphic characteristics and holds significant practical implications for anthropomorphic robot implementation. |
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| ISSN: | 2045-2322 |