Performance contests and merit pay with empathic employees

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Název: Performance contests and merit pay with empathic employees
Autoři: Fabel, Oliver, Mauser, Sandra, Zhang, Yingchao
Zdroj: Managerial and Decision Economics. 45:353-372
Informace o vydavateli: Wiley, 2023.
Rok vydání: 2023
Témata: 502026 Human resource management, Competition, Strategy and Management, 502026 Personalmanagement, 05 social sciences, Gap, Tournaments, Management Science and Operations Research, Altruism, Gender-differences, Affirmative-action, Management of Technology and Innovation, Preferences, Incentives, 0502 economics and business, Pressure, Women, Business and International Management, 10. No inequality
Popis: This paper studies the behavioral responses of employees who are endowed with empathic abilities to different institutional designs of incentive pay. Empathic abilities motivate altruistic behavior by sensing the other's feelings toward oneself. In performance contests, empathic individuals withhold effort, most (less) strongly when facing a non‐empathic (empathic) contestant. Effort levels of both non‐empathic and empathic individuals increase with a higher probability that the contestant is of their own type. By developing a theoretical model, our analysis contributes to understanding observed individual behavior in experiments and corresponding econometric evidence. With direct merit pay, effort choices only depend on the signaling quality of the performance measure. Individuals with stronger empathic abilities may shy away from performance contests to, instead, receive merit pay. If gender governs empathic abilities, setting incentives by performance contests cannot simultaneously ensure equal pay and equal opportunities.
Druh dokumentu: Article
Popis souboru: application/pdf
Jazyk: English
ISSN: 1099-1468
0143-6570
DOI: 10.1002/mde.4003
Přístupová URL adresa: https://ucrisportal.univie.ac.at/de/publications/6c0d584e-a94f-456d-8887-315d6722fcab
https://doi.org/10.1002/mde.4003
Rights: CC BY
Přístupové číslo: edsair.doi.dedup.....88e86f9b3afb25f8af7bf5c4d024010a
Databáze: OpenAIRE
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