Abstract
Past choices can influence subsequent choices in employee selection. Previous approaches rather described similar sequential effects with feedback learning or the misperception of randomness. However, in the selection of job candidates also the accumulation of the moral impact of previous choices might influence subsequent choices. We investigated that question by making two major contributions to the literature. First, we developed an experimental paradigm for measuring sequential choices in employee selection and second, we implemented a widely applicable computational model, the Dependent Sequential Sampling Model, for explaining sequential effects in choices. By using this methodological approach, we uncovered sequential effects in employee selection. Participants (N=600) were especially motivated to compensate for morally dubious choices, with some participants showing consistent choice behavior if their previous choices had been morally virtuous. These results support the assumption of asymmetric compensation of morally dubious choices, sometimes referred to as the moral cleansing hypothesis.
Original language | English |
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Title of host publication | CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society |
Subtitle of host publication | Computational Foundations of Cognition |
Pages | 2457-2462 |
Number of pages | 6 |
ISBN (Electronic) | 9780991196760 |
Publication status | Published - 2017 |
Event | 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017 - London, United Kingdom Duration: 26 Jul 2017 → 29 Jul 2017 |
Publication series
Series | CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition |
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Conference
Conference | 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017 |
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Country/Territory | United Kingdom |
City | London |
Period | 26/07/17 → 29/07/17 |
Bibliographical note
Publisher Copyright:© CogSci 2017.
Research programs
- RSM MKT