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Logistics 2017, 1(1), 5; doi:10.3390/logistics1010005

Developing Talent from a Supply–Demand Perspective: An Optimization Model for Managers

1
Graduate Program in Operations Research, North Carolina State University, Raleigh, NC 27695, USA
2
Department of Business Management, College of Management, North Carolina State University, 2806-A Hillsborough St., Upper Level, Campus Box 7229, Raleigh, NC 27695-7229, USA
*
Author to whom correspondence should be addressed.
Received: 21 June 2017 / Revised: 27 July 2017 / Accepted: 31 July 2017 / Published: 3 August 2017
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Abstract

While executives emphasize that human resources (HR) are a firm’s biggest asset, the level of research attention devoted to planning talent pipelines for complex global organizational environments does not reflect this emphasis. Numerous challenges exist in establishing human resource management strategies aligned with strategic operations planning and growth strategies. We generalize the problem of managing talent from a supply–demand standpoint through a resource acquisition lens, to an industrial business case where an organization recruits for multiple roles given a limited pool of potential candidates acquired through a limited number of recruiting channels. In this context, we develop an innovative analytical model in a stochastic environment to assist managers with talent planning in their organizations. We apply supply chain concepts to the problem, whereby individuals with specific competencies are treated as unique products. We first develop a multi-period mixed integer nonlinear programming model and then exploit chance-constrained programming to a linearized instance of the model to handle stochastic parameters, which follow any arbitrary distribution functions. Next, we use an empirical study to validate the model with a large global manufacturing company, and demonstrate how the proposed model can effectively manage talents in a practical context. A stochastic analysis on the implemented case study reveals that a reasonable improvement is derived from incorporating randomness into the problem. View Full-Text
Keywords: talent management; nonlinear programming; stochastic programming; chance-constrained programming talent management; nonlinear programming; stochastic programming; chance-constrained programming
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Moheb-Alizadeh, H.; Handfield, R.B. Developing Talent from a Supply–Demand Perspective: An Optimization Model for Managers. Logistics 2017, 1, 5.

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