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Growing Science » Authors » M. Mutingi

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Sort articles by: Volume | Date | Most Rates | Most Views | Reviews | Alphabet
1.

Fuzzy system dynamics and optimization with application to manpower systems Pages 873-886 Right click to download the paper Download PDF

Authors: M. Mutingi, C. Mbohwa

DOI: 10.5267/j.ijiec.2012.05.004

Keywords: Fuzzy set theory, Policy optimization, Human resources, Manpower systems, System dynamics

Abstract:
The dynamics of human resource recruitment and training in an uncertain environment creates a challenge for many policy makers in various organisations. In the presence of fuzzy manpower demand and training capacity, many companies fear losing critical human resources when their employees leave. As such, the development of effective dynamic policies for recruitment and training in a fuzzy dynamic environment is imperative. In this frame of mind, a fuzzy systems dynamics modelling approach is proposed to enable the policy maker to develop reliable dynamic policies relating recruitment, training, and available skills, from a systems perspective. It is anticipated in this study that fuzzy system dynamics and optimization approach would help organizations to design effective manpower policies and strategies.
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Journal: IJIEC | Year: 2012 | Volume: 3 | Issue: 5 | Views: 2668 | Reviews: 0

 
2.

Dynamic simulation for effective workforce management in new product development Pages 2571-2580 Right click to download the paper Download PDF

Authors: M. Mutingi

DOI: 10.5267/j.msl.2012.07.006

Keywords: System dynamics, Knowledge management, New product development, Workforce

Abstract:
Effective planning and management of workforce for new product development (NPD) projects is a great challenge to many organisations, especially in the presence of engineering changes during the product development process. The management objective in effective workforce management is to recruit, develop and deploy the right people at the right place at the right time so as to fulfill organizational objectives. In this paper, we propose a dynamic simulation model to address the workforce management problem in a typical NPD project consisting of design, prototyping, and production phases. We assume that workforce demand is a function of project work remaining and the current available skill pool. System dynamics simulation concepts are used to capture the causality relationships and feedback loops in the workforce system from a systems thinking. The evaluation of system dynamics simulation reveals the dynamic behaviour in NPD workforce management systems and shows how adaptive dynamic recruitment and training decisions can effectively balance the workforce system during the NPD process.
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Journal: MSL | Year: 2012 | Volume: 2 | Issue: 7 | Views: 2745 | Reviews: 0

 

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