Maximizing Workforce Diversity In Project Teams: A Network Flow Approach.

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Joyendu Bhadury, Professor, Information Systems and Supply Chain Management (Creator)
The University of North Carolina at Greensboro (UNCG )
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Abstract: Several social, economic and political factors have contributed to the increasing diversity of today's workforce. In addition, in an era when organizations are continuously redesigning their work and restructuring their operations to achieve their goals with fewer resources, performing work in teams has become commonplace. These trends have increased the need for managing diverse work teams effectively. There are several existing models in the management science literature that help managers to assign employees to work groups in order to maximize the groups' diversity and hence, facilitate their effectiveness. This paper introduces a new model that recasts the problem of managing diversity in a different way: it is assumed that the population comes partitioned into `families' with a high degree of intra-familial similarity and inter-familial dissimilarity. The objective of the assignment then is to disperse these family members as evenly into the workgroups as possible. A little known network flow problem, known as the dining problem, is used to develop an efficient algorithm to produce solutions to this new model. This is followed by a report on an experimental application of the developed model to assign Master of Business Administration students in a business school to different projects in a course. As a part of this empirical report, an attractive feature of this model is also demonstrated; namely, how to conduct sensitivity analysis to determine the optimal levels of diversity in the presence of resource constraints. Finally, the paper concludes by discussing limitations of this new model and how they may be addressed in future research on this topic.

Additional Information

OMEGA: International Journal of Management Science, 28, pp 143-153 (2000)
Language: English
Date: 2000
Decision making, Personnel/human resources, Manpower planning, Set partitioning, Optimization, Dining problem

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