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An extended Markov-switching model approach to latent heterogeneity in departmentalized manpower systems.

Authors :
Ossai, Everestus O.
Nduka, Uchenna C.
Madukaife, Mbanefo S.
Udom, Akaninyene U.
Ugwu, Samson O.
Source :
Communications in Statistics: Theory & Methods. 2024, Vol. 53 Issue 19, p6957-6976. 20p.
Publication Year :
2024

Abstract

In recent works in manpower planning interest has been awakened in modeling manpower systems in departmentalized framework. This, as a form of disaggregation, may solve the problem of observable heterogeneity but not latent heterogeneity; it rather opens up other aspects of latent heterogeneity hitherto unaccounted for in classical (non departmentalized) manpower models. In this article, a multinomial Markov-switching model is formulated for investigating latent heterogeneity in intra-departmental and interdepartmental transitions in departmentalized manpower systems. The formulation incorporates extensions of the mover-stayer principle resulting in several competing models. The best manpower model is chosen based on the optimum number of hidden states established by the use of Expectation-Maximization iterative algorithm for estimation of the model parameters and a search procedure for assessing model performance against one another. The illustration establishes the usefulness of the model formulation in highlighting hidden disparities in personnel transitions in a departmentalized manpower system and in avoiding wrong model specification. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03610926
Volume :
53
Issue :
19
Database :
Academic Search Index
Journal :
Communications in Statistics: Theory & Methods
Publication Type :
Academic Journal
Accession number :
178943805
Full Text :
https://doi.org/10.1080/03610926.2023.2255322