The goal of this paper is to propose a novel modeling framework to help project managers devise optimal workforce assignments that consider both short- and long-term aspects of projects that must be completed through ...
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The goal of this paper is to propose a novel modeling framework to help project managers devise optimal workforce assignments that consider both short- and long-term aspects of projects that must be completed through a multi-organizational social network. The proposed framework is comprised of an evaluation module and an assignment module. Each time a workforce assignment is performed, the Decision Evolution Procedure of the evaluation module first calculates the position value between each pair of currently available workforce members based on various social networking parameters such as trustworthiness, influence, reputation, and proximity. Second, by using these position values, the Extended Regular Equivalence Evaluation algorithm from the evaluation module computes the regular and structural equivalence values between each pair of workforce members. Finally, the assignment module selects an optimal workforce mix that maximizes both the short-term performance (productivity) as well as the long-term performance (workforce training, and robustness) of the project organizations. Agent-based simulation and multi-objective optimization techniques are leveraged for the evaluation module and the assignment module, respectively. The proposed framework is illustrated and successfully demonstrated using the software enhancement request process in Kuali, a multi-organizational alliance-based softwaredevelopment project involving 12 universities.
The development of alliance-based software requires the collaboration of many stakeholders. These different stakeholders across multiple organizations form a complex social network. The goal of this paper is to develo...
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The development of alliance-based software requires the collaboration of many stakeholders. These different stakeholders across multiple organizations form a complex social network. The goal of this paper is to develop a novel modeling framework, which will help task managers devise optimal workforce assignments considering both short-term and long-term aspects of the softwaredevelopment process. The proposed framework is composed of an assignment module and a prediction module. For a given task, the assignment module first selects a candidate workforce mix. Based on the candidate workforce mix, the prediction module then predicts the short-term performance (productivity) as well as the long-term performance (workforce training and robustness of the organization) of the organization. Then, the assignment module selects another candidate mix, and this iteration continues until an optimal workforce mix is found. The prediction module and the assignment module are based on an agent-based simulation method and a multi-objective optimization model, respectively. The proposed modeling framework is illustrated with a software enhancement request process in Kuali, an alliance-based open source softwaredevelopment project involving 12 organizations. The constructed framework is executed with varying parameters to demonstrate its use and benefit in the software enhancement process. (C) 2011 Elsevier B.V. All rights reserved.
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