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Maximizing workforce diversity in project teams: a network flow approach

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  • Bhadury, Joyendu
  • Mighty, E. Joy
  • Damar, Hario

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.

Suggested Citation

  • Bhadury, Joyendu & Mighty, E. Joy & Damar, Hario, 2000. "Maximizing workforce diversity in project teams: a network flow approach," Omega, Elsevier, vol. 28(2), pages 143-153, April.
  • Handle: RePEc:eee:jomega:v:28:y:2000:i:2:p:143-153
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    Cited by:

    1. Lai, Xiangjing & Hao, Jin-Kao, 2016. "Iterated maxima search for the maximally diverse grouping problem," European Journal of Operational Research, Elsevier, vol. 254(3), pages 780-800.
    2. Z P Fan & Y Chen & J Ma & S Zeng, 2011. "A hybrid genetic algorithmic approach to the maximally diverse grouping problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 92-99, January.
    3. Dmitry Krass & Anton Ovchinnikov, 2006. "The University of Toronto’s Rotman School of Management Uses Management Science to Create MBA Study Groups," Interfaces, INFORMS, vol. 36(2), pages 126-137, April.
    4. Kayse Lee Maass & Vera Mann Hey Lo & Anna Weiss & Mark S. Daskin, 2015. "Maximizing Diversity in the Engineering Global Leadership Cultural Families," Interfaces, INFORMS, vol. 45(4), pages 293-304, August.
    5. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "Workforce planning incorporating skills: State of the art," European Journal of Operational Research, Elsevier, vol. 243(1), pages 1-16.
    6. Gusev, Vasily V., 2020. "The vertex cover game: Application to transport networks," Omega, Elsevier, vol. 97(C).
    7. Yang, Xiao & Cai, Zonghui & Jin, Ting & Tang, Zheng & Gao, Shangce, 2022. "A three-phase search approach with dynamic population size for solving the maximally diverse grouping problem," European Journal of Operational Research, Elsevier, vol. 302(3), pages 925-953.
    8. Z P Fan & Y Chen & J Ma & S Zeng, 2011. "Erratum: A hybrid genetic algorithmic approach to the maximally diverse grouping problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1423-1430, July.
    9. Perla, Abhinav & Nikolaev, Alexander & Pasiliao, Eduardo, 2018. "Workforce management under social Link Based Corruption," Omega, Elsevier, vol. 78(C), pages 222-236.
    10. Saber, Hussein M. & Ghosh, Jay B., 2001. "Assigning students to academic majors," Omega, Elsevier, vol. 29(6), pages 513-523, December.
    11. Amina Lamghari & Jacques Ferland, 2010. "Metaheuristic methods based on Tabu search for assigning judges to competitions," Annals of Operations Research, Springer, vol. 180(1), pages 33-61, November.
    12. Hsiang-Hsi Liu & Teng-Kun Wang & Guan-Ting Liu, 2020. "Workforce Diversity Affecting on the Non-financial Performance of Taiwanese Multinational Enterprises under Different Environmental Factors: CEOs' Viewpoints," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 10(4), pages 1-7.
    13. J Desrosiers & N Mladenović & D Villeneuve, 2005. "Design of balanced MBA student teams," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(1), pages 60-66, January.

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