Does Bot Gender Matter? Theory and Evidence From a High-Tension Service Context

Despite the increasing use of AI-powered voicebots, our understanding of how the choice of bot gender may impact service outcomes in high-tension service contexts, such as debt collection, remains limited. To address this gap, we drew on the tensions-based view of customer relationships and gender stereotype theory to hypothesize how and when voicebot gender matters in high-tension service contexts. We tested our hypotheses using a proprietary dataset of debt collection calls made by AI voicebots. We found that female voicebots increase the odds of a positive repayment intention by 28.3%. This gender effect is more pronounced when service encounters begin with higher tension, such as during weekdays or with initially uncooperative customers. We further show that the gender effect can be explained by the advantages of female voicebots in reducing behavioral and emotional tension during service interactions.

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Publication Details

Journal
MIS Quarterly
Published
2025-09-18
DOI
https://doi.org/10.25300/misq/2025/17909
Citations
1
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
3.25
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article

Does Bot Gender Matter? Theory and Evidence From a High-Tension Service Context

Ximing Yin, Sean Xin Xu, Liu De, Yiting Guo
1 citations
MIS Quarterly
Spam and Phishing Detection
3.25
article

Does Bot Gender Matter? Theory and Evidence From a High-Tension Service Context

Ximing Yin, Sean Xin Xu, Liu De, Yiting Guo
article en
1 citations

Abstract

Despite the increasing use of AI-powered voicebots, our understanding of how the choice of bot gender may impact service outcomes in high-tension service contexts, such as debt collection, remains limited. To address this gap, we drew on the tensions-based view of customer relationships and gender stereotype theory to hypothesize how and when voicebot gender matters in high-tension service contexts. We tested our hypotheses using a proprietary dataset of debt collection calls made by AI voicebots. We found that female voicebots increase the odds of a positive repayment intention by 28.3%. This gender effect is more pronounced when service encounters begin with higher tension, such as during weekdays or with initially uncooperative customers. We further show that the gender effect can be explained by the advantages of female voicebots in reducing behavioral and emotional tension during service interactions.

MIS QuarterlyVol. 49(4)
Beijing Institute of Technology (CN), University of Minnesota (US), Xiamen University (CN), Xiamen University of Technology (CN), Chinese Academy of Governance (CN), China Institutes of Contemporary International Relations (CN), Tsinghua University (CN)
Openalex Percentile: Top 6%
Spam and Phishing Detection
3.25
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Does Bot Gender Matter? Theory and Evidence From a High-Tension Service Context — Ximing Yin, Sean Xin Xu, et al. · MIS Quarterly (2025) | TGRS Research Map | TGRS