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• W3194335782 abstract "Purpose Workforce planning must answer how many workforces, in which positions, and talents, and when each organization is needed. To find the requirements workforce, organizations need to know the organizational position and talents pools. Clarifying the number of workforces required in each pool requires attention to workforce flows, including hiring, promotion, degradation, horizontal movement, and exiting the organization. It is a dynamic issue and must be addressed over several periods over a specific duration, which adds to the complexity. According to the talent management presented in this research, all the above complex questions are answered by applying the optimal control (OC) model according to talent management presented in this research. Design/methodology/approach This research presents a dynamic model by using a linear-quadratic optimal control model, which was solved by Pontryagin's maximum principle, to achieve an optimal number of workforce requirements for each of the positions of nursing services manager, supervisor, head nurses and nurses in the health sector according to the required talents in each position. Findings The results have shown that the target value of workforce numbers has been achieved in the planning period, and the validation test and sensitivity analysis justified the model by reaching the workforce planning targets. Originality/value This study provides a dynamic model for achieving quantitative workforce planning targets; the model presented in this manuscript has included an important qualitative factor, namely workforce talents. According to the authors' review, there is no comprehensive research devoted to workforce planning through optimal control models by attention to workforces skills." @default.
• W3194335782 created "2021-08-30" @default.
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• W3194335782 date "2021-08-10" @default.
• W3194335782 modified "2023-09-23" @default.
• W3194335782 title "Multi-level nursing workforce planning considering talent management in healthcare with a dynamic quantitative approach" @default.
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• W3194335782 doi "https://doi.org/10.1108/k-04-2021-0261" @default.
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