Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Date of Graduation

Spring 5-7-2010

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Department of Integrated Science and Technology

Advisor(s)

Robert Kolvoord

Abstract

Many business organizations utilize team structures as a way to organize their personnel and integrate the diverse backgrounds and competencies of their employees. As a result, team assembly strategies are important to an organization’s productivity and should be evaluated by managers. This thesis utilizes network modeling and simulation to explore and assess various team assembly strategies that incorporate the concept that some people energize their teammates, whereas others de-energize them. Research in this area of energy networks studies the impact that energizing and de-energizing employees have on the performance of their co-workers and, as a result, the success of business organizations overall. Energy networks have been studied with network analysis, but very little if any research has focused on simulating energy networks so the model in this thesis includes energy as a key attribute to consider when assembling teams. An existing team assembly model is adapted to include an energy rating component for team members and used to investigate two realistic strategies for team assembly based on different energy motivations: organization based on similar energy rating and organization with respect to various team composition constraints. Four different policies are modeled and simulated for the second strategy. Team assembly based on similar energy rating yields high frequencies of occurrence of both energizing and de-energizing teams, while the three policies aimed at achieving teams with balanced energy, mostly energizing, and mostly de-energizing accomplish their respective goals. The policy aimed at integrating a diverse range of energy ratings yields variable results. Analyzing the simulation results elicits recommendation for managers about the energy-focused strategies and policies explored.

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