Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots

Yong Liu; Jiajun Sun; Yanqing Lin; Virpi Kristiina Tuunainen

doi:10.1007/978-3-031-94184-9_5

Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots

Yong Liu^*
, Jiajun Sun
, Yanqing Lin
, Virpi Kristiina Tuunainen

^*Huvudförfattare för detta arbete

Informationsbehandling, Helsingfors

Aalto University

Forskningsoutput: Kapitel i bok/rapport/konferenshandling › Konferensbidrag › Vetenskaplig › Peer review

Sammanfattning

Numerous studies have explored human preferences for male versus female robots, producing inconsistent findings and varied explanations for the manifestation of gender bias towards robots. This study contributes to understanding how user gender and robot gender interact to influence users’ evaluations of robots by analyzing over 1100 survey responses on 23 robots, distinguished by their male and female appearances. The findings refute the existence of the same-gender or cross-gender effect. Specifically, we found a general preference for female robots over male robots. In addition, female users report the highest likeability scores for female robots compared to other human-robot gender combinations.

Originalspråk	Engelska
Titel på värdpublikation	E-Business. Generative Artificial Intelligence and Management Transformation : 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings
Redaktörer	Yiliu Paul Tu, Maomao Chi
Antal sidor	10
Förlag	Springer
Utgivningsdatum	08.06.2025
Sidor	52-61
ISBN (tryckt)	978-3-031-94183-2
ISBN (elektroniskt)	978-3-031-94184-9
DOI	https://doi.org/10.1007/978-3-031-94184-9_5
Status	Publicerad - 08.06.2025
MoE-publikationstyp	A4 Artikel i en konferenspublikation
Evenemang	Wuhan International Conference on E-Business, WHICEB 2025 - Guangzhou, Kina Varaktighet: 06.06.2025 → 08.06.2025 Konferensnummer: 24

Publikationsserier

Namn	Lecture Notes in Business Information Processing
Volym	549 LNBIP
ISSN (tryckt)	1865-1348
ISSN (elektroniskt)	1865-1356

Nyckelord

512 Företagsekonomi

Åtkomst av dokument

10.1007/978-3-031-94184-9_5

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Liu, Y., Sun, J., Lin, Y., & Tuunainen, V. K. (2025). Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots. I Y. P. Tu, & M. Chi (Red.), E-Business. Generative Artificial Intelligence and Management Transformation: 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings (s. 52-61). (Lecture Notes in Business Information Processing; Vol. 549 LNBIP). Springer. https://doi.org/10.1007/978-3-031-94184-9_5

Liu, Yong ; Sun, Jiajun ; Lin, Yanqing et al. / Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots. E-Business. Generative Artificial Intelligence and Management Transformation: 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings. redaktör / Yiliu Paul Tu ; Maomao Chi. Springer, 2025. s. 52-61 (Lecture Notes in Business Information Processing).

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title = "Exploring the Impacts of Human-Robot Gender Match on Users{\textquoteright} Perceptions of Robots",

abstract = "Numerous studies have explored human preferences for male versus female robots, producing inconsistent findings and varied explanations for the manifestation of gender bias towards robots. This study contributes to understanding how user gender and robot gender interact to influence users{\textquoteright} evaluations of robots by analyzing over 1100 survey responses on 23 robots, distinguished by their male and female appearances. The findings refute the existence of the same-gender or cross-gender effect. Specifically, we found a general preference for female robots over male robots. In addition, female users report the highest likeability scores for female robots compared to other human-robot gender combinations.",

keywords = "512 Business and Management, Adoption, Bias, Gender, Gender-Match, Human-Robot-Interaction",

author = "Yong Liu and Jiajun Sun and Yanqing Lin and Tuunainen, \{Virpi Kristiina\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; Wuhan International Conference on E-Business, WHICEB 2025, WHICEB ; Conference date: 06-06-2025 Through 08-06-2025",

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doi = "10.1007/978-3-031-94184-9\_5",

language = "English",

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Liu, Y, Sun, J, Lin, Y & Tuunainen, VK 2025, Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots. i YP Tu & M Chi (red), E-Business. Generative Artificial Intelligence and Management Transformation: 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings. Lecture Notes in Business Information Processing, vol. 549 LNBIP, Springer, s. 52-61, Wuhan International Conference on E-Business, WHICEB 2025, Guangzhou, Kina, 06.06.2025. https://doi.org/10.1007/978-3-031-94184-9_5

Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots. / Liu, Yong; Sun, Jiajun; Lin, Yanqing et al.
E-Business. Generative Artificial Intelligence and Management Transformation: 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings. red. / Yiliu Paul Tu; Maomao Chi. Springer, 2025. s. 52-61 (Lecture Notes in Business Information Processing; Vol. 549 LNBIP).

Forskningsoutput: Kapitel i bok/rapport/konferenshandling › Konferensbidrag › Vetenskaplig › Peer review

TY - GEN

T1 - Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots

AU - Liu, Yong

AU - Sun, Jiajun

AU - Lin, Yanqing

AU - Tuunainen, Virpi Kristiina

N1 - Conference code: 24

PY - 2025/6/8

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AB - Numerous studies have explored human preferences for male versus female robots, producing inconsistent findings and varied explanations for the manifestation of gender bias towards robots. This study contributes to understanding how user gender and robot gender interact to influence users’ evaluations of robots by analyzing over 1100 survey responses on 23 robots, distinguished by their male and female appearances. The findings refute the existence of the same-gender or cross-gender effect. Specifically, we found a general preference for female robots over male robots. In addition, female users report the highest likeability scores for female robots compared to other human-robot gender combinations.

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KW - Adoption

KW - Bias

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BT - E-Business. Generative Artificial Intelligence and Management Transformation

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T2 - Wuhan International Conference on E-Business, WHICEB 2025

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Liu Y, Sun J, Lin Y, Tuunainen VK. Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots. I Tu YP, Chi M, redaktörer, E-Business. Generative Artificial Intelligence and Management Transformation: 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings. Springer. 2025. s. 52-61. (Lecture Notes in Business Information Processing). doi: 10.1007/978-3-031-94184-9_5

Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots

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