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Manpower Planning Under Stochastic Turnover Behavior

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Manpower Planning and Organization Design

Part of the book series: NATO Conference Series ((SYSC,volume 7))

Abstract

In the past decade, Markovian Analysis has been utilized for manpower planning purposes in a number of organizations. The main assumption in these models was the stability of the transition probabilities for turnover behavior. In real life this assumption is rarely met. In this paper a remedy for this problem is proposed. This remedy is the utilization of multiple transition matrices depending on the socio-economic changes in the work environment.

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References

  1. J.W. Merck, A. Markovian Model for Projecting Movements of Personnel Through a System, Technical Report 65–6 (1965)

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  2. H. Victor Vroom and Kenneth R. MacCrimmon, “Towards a Stochastic Model of Managerial Careers,” Administrative Science Quarterly, XIII (June, 1968), 24–46

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  3. Mason Haire, “Approach to an Integrated Personnel Policy,” Industrial Relations, VII (February, 1968), 107–117

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  4. Kendrith M. Rowland and Michael G. Sovereign, “Markov-chain Analysis of Internal Manpower Supply,” Industrial Relations IX (October 1969), 88–99

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  5. B.Curtis Eaton, “Studying Mass Layoff Through Markov Chains,” Industrial Relations, IX (October, 1970), 394–403

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  6. Uyar, Kivilcim M., “Markov-Chain Forecasts of Employee Replacement Needs,” Industrial Relations, Vol.11, No. 1, February 1972, pp.96–106.

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  7. Uyar, op.cit., pp. 96–106.

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  8. Common examples for this would be: Changes in national unemployment rate, supply and demand fluctuations, changes in management, etc.

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  9. The expected desired level of employment was not available for this analysis.

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© 1978 Plenum Press, New York

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Uyar, K., Uyar, C.K. (1978). Manpower Planning Under Stochastic Turnover Behavior. In: Bryant, D.T., Niehaus, R.J. (eds) Manpower Planning and Organization Design. NATO Conference Series, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-4622-7_26

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  • DOI: https://doi.org/10.1007/978-1-4613-4622-7_26

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-4624-1

  • Online ISBN: 978-1-4613-4622-7

  • eBook Packages: Springer Book Archive

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