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Hidden heterogeneity in manpower systems: A Markov-switching model approach

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  • Guerry, Marie-Anne

Abstract

In modeling manpower systems, it is of crucial importance to deal with heterogeneity. Until recently, manpower models are dealing with heterogeneity due to observable sources, neglecting heterogeneity due to latent sources. In this paper a two-step procedure is introduced. In the first step personnel groups homogeneous with respect to the transition probabilities are determined in a classical way by taking into account the observable sources of heterogeneity. In the second step heterogeneity caused by latent sources is handled. A multinomial Markov-switching manpower model is introduced that deals with heterogeneity due to latent sources for the internal flows as well as for the wastage flows. The model incorporates the mover-stayer principle. A re-estimation algorithm is presented to estimate the parameters of the Markov-switching manpower model. The switching approach offers a methodology to build a Markov model with personnel groups as states that are more homogeneous, and therefore can contribute to a better validity of the manpower model.

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  • Guerry, Marie-Anne, 2011. "Hidden heterogeneity in manpower systems: A Markov-switching model approach," European Journal of Operational Research, Elsevier, vol. 210(1), pages 106-113, April.
    • Handle: RePEc:eee:ejores:v:210:y:2011:i:1:p:106-113
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    1. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    2. Tim De Feyter, 2006. "Modelling heterogeneity in manpower planning: dividing the personnel system into more homogeneous subgroups," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 22(4), pages 321-334, July.
    3. F.I. Ugwuowo & S.I. McClean, 2000. "Modelling heterogeneity in a manpower system: a review," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 16(2), pages 99-110, April.
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    7. Georgiou, Andreas C. & Thanassoulis, Emmanuel & Papadopoulou, Alexandra, 2022. "Using data envelopment analysis in markovian decision making," European Journal of Operational Research, Elsevier, vol. 298(1), pages 276-292.

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