Managing academic performance by optimal resource allocation

Alexander Grigoriev () and Olga Mondrus ()
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Alexander Grigoriev: Maastricht University School of Business and Economics
Olga Mondrus: HSE University

Scientometrics, 2022, vol. 127, issue 5, No 13, 2433-2453

Abstract: Abstract In this paper, we develop and study a complex data-driven framework for human resource management enabling (i) academic talent recognition, (ii) researcher performance measurement, and (iii) renewable resource allocation maximizing the total output of a research unit. Suggested resource allocation guarantees the optimal output under strong economic assumptions: the agents are rational, collaborative and have no incentives to behave selfishly. In reality, however, agents often play strategically maximizing their own utilities, e.g., maximizing the resources assigned to them. This strategic behavior is typically mitigated by implementation of performance-driven or uniform resource allocation schemes. Next to the framework presentation, we address the cost of such mitigation.

Keywords: Talent performance; Talent recognition; Performance monitoring; Resource allocation; Incentives; Strategic behavior (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:127:y:2022:i:5:d:10.1007_s11192-022-04342-5

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DOI: 10.1007/s11192-022-04342-5

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