E O Ossai, M S Madukaife, A U Udom, U C Nduka, T E Ugah
{"title":"Effects of Prioritized Input on Human Resource Control in Departmentalized Markov Manpower Framework.","authors":"E O Ossai, M S Madukaife, A U Udom, U C Nduka, T E Ugah","doi":"10.1007/s11009-023-10011-8","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper, extended Markov manpower models are formulated by incorporating a new class of members of a departmentalized manpower system in a homogeneous Markov manpower model. The new class, called limbo class, admits members of the system who exit to a limbo state for possible re-engagement in the active class. This results to two channels of recruitment: one from the limbo class and another from the outside environment. The idea is motivated by the need to preserve trained and experienced individuals who could be lost in times of financial crises or due to contract completion. The control aspect of the manpower structure under the extended models are examined. Under suitable stochastic condition for the flow matrices, it is proved that the maintainability of the manpower structure through promotion does not depend on the structural form of the limbo class when the system is expanding with priority on recruitment from outside environment, nor on the structural form of the active class when the system is shrinking with priority on recruitment from the limbo class. Necessary and sufficient conditions for maintainability of the manpower structure through recruitment in the case of expanding systems are also established with proofs.</p>","PeriodicalId":18442,"journal":{"name":"Methodology and Computing in Applied Probability","volume":"25 1","pages":"37"},"PeriodicalIF":1.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9972330/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methodology and Computing in Applied Probability","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s11009-023-10011-8","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, extended Markov manpower models are formulated by incorporating a new class of members of a departmentalized manpower system in a homogeneous Markov manpower model. The new class, called limbo class, admits members of the system who exit to a limbo state for possible re-engagement in the active class. This results to two channels of recruitment: one from the limbo class and another from the outside environment. The idea is motivated by the need to preserve trained and experienced individuals who could be lost in times of financial crises or due to contract completion. The control aspect of the manpower structure under the extended models are examined. Under suitable stochastic condition for the flow matrices, it is proved that the maintainability of the manpower structure through promotion does not depend on the structural form of the limbo class when the system is expanding with priority on recruitment from outside environment, nor on the structural form of the active class when the system is shrinking with priority on recruitment from the limbo class. Necessary and sufficient conditions for maintainability of the manpower structure through recruitment in the case of expanding systems are also established with proofs.
期刊介绍:
Methodology and Computing in Applied Probability will publish high quality research and review articles in the areas of applied probability that emphasize methodology and computing. Of special interest are articles in important areas of applications that include detailed case studies. Applied probability is a broad research area that is of interest to many scientists in diverse disciplines including: anthropology, biology, communication theory, economics, epidemiology, finance, linguistics, meteorology, operations research, psychology, quality control, reliability theory, sociology and statistics.
The following alphabetical listing of topics of interest to the journal is not intended to be exclusive but to demonstrate the editorial policy of attracting papers which represent a broad range of interests:
-Algorithms-
Approximations-
Asymptotic Approximations & Expansions-
Combinatorial & Geometric Probability-
Communication Networks-
Extreme Value Theory-
Finance-
Image Analysis-
Inequalities-
Information Theory-
Mathematical Physics-
Molecular Biology-
Monte Carlo Methods-
Order Statistics-
Queuing Theory-
Reliability Theory-
Stochastic Processes