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Personnel turnover in organizations: an agent-based simulation model.

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Department of Statistics and Applied Mathematics, University of Turin, Piazza Arbarello 8, I-10122 Turin, Italy.


We study how personnel turnover policies may affect the global behavior of a simple model of organization. In the model we propose, heterogeneous agents interact dynamically, adapting their effort level. Effort equilibria in populations consisting of both perfectly rational and bounded-rational agents are considered. The problem is approached theoretically in simple cases, while simulation is used when more complex situations are examined. We are interested in finding a hiring/firing policy that is effective in selecting high effort in more complex cases and when agent effort may not be directly observed. We prove that, while generally the existence of such a policy is not guaranteed, in most situations an opportune choice may increase overall population effort. This research suggests that, even if explicit incentives are not considered, an opportune policy in personnel turnover can improve the general effort level of the organization. In particular, policies adapting to contingent situations are those that are likely to obtain best results.

[Indexed for MEDLINE]

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