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Effects of Gender Matching on Performance in Human-Robot Teams and Acceptance of Robots

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Cross-Cultural Design. Applications in Cultural Heritage, Tourism, Autonomous Vehicles, and Intelligent Agents (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12773))

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Abstract

Robots provide important help in relieving work pressure and reducing workload. This study aimed to explore the impact of robots’ gender on individuals’ performance and their acceptance of robots. This study explored the effects of human-robot gender matching on the performance and the mediating role of acceptance of robots. A questionnaire survey was conducted and 212 valid questionnaires were collected. The results indicated that for the male respondents, their acceptance of opposite-sex robots was higher than the acceptance of same-sex robots and their performance was higher while working with opposite-sex robots. For the female respondents, their acceptance of same-sex robots was higher and their performance wasn’t influenced by robots’ gender. Moreover, the acceptance of robots mediated in the influence of gender matching on performance. Implications were discussed for future work.

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Acknowledgements

This study was funded by a National Natural Science Foundation of China 71942005, a Ministry of Education of Humanities and Social Science project 19YJC840002, a Beijing Social Science Fund 17SRC021 and a Beijing Natural Science Foundation 9184029.

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Authors and Affiliations

  1. Beijing University of Chemical Technology, Beijing, 100055, China

    Yanan Zhai, Na Chen & Jiajia Cao

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  1. Yanan Zhai
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  2. Na Chen
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  3. Jiajia Cao
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Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Pei-Luen Patrick Rau

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Zhai, Y., Chen, N., Cao, J. (2021). Effects of Gender Matching on Performance in Human-Robot Teams and Acceptance of Robots. In: Rau, PL.P. (eds) Cross-Cultural Design. Applications in Cultural Heritage, Tourism, Autonomous Vehicles, and Intelligent Agents. HCII 2021. Lecture Notes in Computer Science(), vol 12773. Springer, Cham. https://doi.org/10.1007/978-3-030-77080-8_32

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  • DOI: https://doi.org/10.1007/978-3-030-77080-8_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77079-2

  • Online ISBN: 978-3-030-77080-8

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