Discrete Time Hybrid Semi-Markov Models in Manpower Planning

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