Discrete Time Hybrid Semi-Markov Models in Manpower Planning

Brecht Verbeken and Marie-Anne Guerry
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Brecht Verbeken: Department of Business Technology and Operations, Vrije Universiteit Brussel, Pleinlaan, 2, 1050 Brussels, Belgium
Marie-Anne Guerry: Department of Business Technology and Operations, Vrije Universiteit Brussel, Pleinlaan, 2, 1050 Brussels, Belgium

Mathematics, 2021, vol. 9, issue 14, 1-13

Abstract: Discrete time Markov models are used in a wide variety of social sciences. However, these models possess the memoryless property, which makes them less suitable for certain applications. Semi-Markov models allow for more flexible sojourn time distributions, which can accommodate for duration of stay effects. An overview of differences and possible obstacles regarding the use of Markov and semi-Markov models in manpower planning was first given by Valliant and Milkovich (1977). We further elaborate on their insights and introduce hybrid semi-Markov models for open systems with transition-dependent sojourn time distributions. Hybrid semi-Markov models aim to reduce model complexity in terms of the number of parameters to be estimated by only taking into account duration of stay effects for those transitions for which it is useful. Prediction equations for the stock vector are derived and discussed. Furthermore, the insights are illustrated and discussed based on a real world personnel dataset. The hybrid semi-Markov model is compared with the Markov and the semi-Markov models by diverse model selection criteria.

Keywords: semi-Markov model; Markov model; hybrid semi-Markov model; manpower planning (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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