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The role of subjectivity in mitigating incentive contracting risks

The role of subjectivity in mitigating incentive contracting risks

Lillis, Anne M., Malina, Mary A. and Mundy, Julia ORCID: 0000-0001-7970-3507 (2021) The role of subjectivity in mitigating incentive contracting risks. The Accounting Review. ISSN 0001-4826 (Print), 1558-7967 (Online) (In Press) (doi:

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We examine how subjectivity in performance measurement and reward systems (PMRS) is used to mitigate incentive contracting risks. Drawing on data from 38 interviews with supervisory and subordinate managers in four firms, we provide a more comprehensive explanation of the role of subjectivity in risk mitigation than is evident in the prior literature. We provide empirical evidence of the importance firms place on the use of subjectivity to mitigate the risk of incentive misalignment and employee sorting errors relative to its well-documented role in mitigating employee compensation risk. We find that incentive misalignment arising from unanticipated behavioral responses to performance measures is a particularly important risk, managed through subjective performance assessments. The extent of subjectivity we observe poses a significant risk of errors and bias. We observe that both vertical and horizontal information gathering and review by calibration panels are key strategies to mitigate the downside risk of subjectivity.

Item Type: Article
Uncontrolled Keywords: subjectivity; incentive alignment; employee sorting; compensation risk; mitigating errors and bias in subjectivity; calibration
Subjects: H Social Sciences > HF Commerce > HF5601 Accounting
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of Accounting & Finance
Faculty of Business > Institute of Political Economy, Governance, Finance and Accountability (IPEGFA) > Centre for Governance, Risk & Accountability (CGRA)
Related URLs:
Last Modified: 11 Jun 2021 18:09
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None

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