Abstract
Purpose: In response to calls to reduce the gender gap in the salesforce, this study aims to examine the effect of candidate gender, manager gender and industry to explain gender bias in salesperson recruitment during screening and skill assessment. Design/methodology/approach: This paper tested the hypotheses using observational data from a national sales competition in the USA, where managers evaluated student candidates for entry-level sales positions. Findings: This research finds gender bias during screening using the dyadic perspective. Specifically, female managers evaluate male candidates more favorably than male managers do during screening. Further, managers of service companies evaluate female candidates more favorably than managers of goods companies during screening. However, this paper finds no such effects during candidates’ skill assessment. Research limitations/implications: The findings indicate the importance of using dyadic research techniques to assess gender bias. Practical implications: Managers should not use short interactions to screen candidates. Social implications: Implicit bias exists when candidates and managers interact during screening. To reduce gender bias in recruitment the candidates and managers should interact for a longer duration. Originality/value: This study draws upon a unique setting, where the candidates interact with the managers for screening and skill assessment. Implicit bias exists when candidates and managers interact for screening under time pressure. This paper finds no evidence of gender bias in skill assessment. This study finds that female managers are more prone to bias when evaluating male candidates than male managers. Prior work has not examined industry-based bias; this paper provides evidence of such bias in candidate screening.
| Original language | English |
|---|---|
| Pages (from-to) | 1335-1344 |
| Number of pages | 10 |
| Journal | Journal of Business & Industrial Marketing |
| Volume | 35 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 25 Sept 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 5 Gender Equality
Keywords
- Recruitment
- Salesforce
- Equal opportunities
- Regression analysis
- Hiring
- Gender bias
- Industry effect
- Implicit bias
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