Employee shirking and overworking: modelling the unintended consequences of work organisation

Antosz, P., Rembiasz, T. & Verhagen, H., 2-Aug-2020, In : Ergonomics. 63, 8, p. 997-1009 13 p.

Research output: Contribution to journalArticleAcademicpeer-review

Underworking (i.e. shirking) and overworking of employees can have detrimental effects for the individual and the organisation. We develop a computational model to investigate how work structure, specifically the way in which managers distribute work tasks amongst employees, impacts work intensity and working time. The model draws on theories from economics, psychology and management, and on empirical observations. The simulations show that when managers correctly estimate task difficulty, but undervalue the employee's competence, opportunities for shirking are provided due to longer deadlines. Similarly, if managers overvalue the employee's competence, they set tighter deadlines leading to overwork. If task difficulty is misjudged, initially only influence on employee working time is observed. However, it gradually generates competence misjudgements, indirectly impacting the employee's effort level. An interaction between competence misjudgement and task uncertainty slows the manager's ability to correctly estimate employee competence and prolongs initial competence misjudgements. The study highlights the importance of applying dynamic modelling methods, which allows for testing theory assumptions in silico, generating new hypotheses and offers a foundation for future research. Practitioner summary: A computational model was developed to investigate how the structure of work allocation influences opportunities for shirking and overworking by employees. The paper demonstrates how dynamic modelling can be used to explain workplace phenomena and develop new hypotheses for further research.

Original languageEnglish
Pages (from-to)997-1009
Number of pages13
Issue number8
Publication statusPublished - 2-Aug-2020


  • Task performance, shirking, agent-based model, social simulations, PERFORMANCE, PHYSICIANS, AGENT

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