JOURNAL ARTICLE

Incentive Effects of Subjective Allocations of Rewards and Penalties.

  • Published In: Management Science (INFORMS), 2023, v. 69, n. 5. P. 3121 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Cai, Wei; Gallani, Susanna; Shin, Jee-Eun 3 of 3

Abstract

This article investigates the incentive effects of subjectivity in allocating tournament-based monetary rewards and penalties within a Chinese manufacturing firm. Using data where managers combine objective performance metrics with subjective assessments to determine bonuses and penalties—both publicly disclosed to employees—the study finds that subjective rewards (favorable deviations from formula-based expectations) lead to significant subsequent performance improvements, while subjective punishments (unfavorable deviations) result in performance declines. These effects are incremental beyond those of formula-based rewards and penalties and are stronger when subjective outcomes involve actual monetary payoffs rather than mere overrides of expected rewards or penalties. The findings suggest that managerial discretion in rewarding employees can enhance motivation and performance, but subjective punishments may be costly unless accompanied by strong ex ante incentive effects; moreover, observing others' subjective treatment does not significantly affect nonrecipients' performance. The study contributes empirical evidence on the motivational role of subjectivity in incentive contracts and highlights practical implications for designing effective performance evaluation systems.

Additional Information

  • Source:Management Science (INFORMS). 2023/05, Vol. 69, Issue 5, p3121
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2023
  • ISSN:0025-1909
  • DOI:10.1287/mnsc.2022.4501
  • Accession Number:163586468
  • Copyright Statement:Copyright of Management Science (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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