On performance modeling of project-oriented production
Computers and Industrial Engineering
Project portfolio selection through decision support
Decision Support Systems
Using fuzzy decision making for the evaluation of the project management internal efficiency
Decision Support Systems
Performance measurement of supply chain management: A balanced scorecard approach
Computers and Industrial Engineering
Eight key issues for the decision support systems discipline
Decision Support Systems
Screening in multiple criteria decision analysis
Decision Support Systems
Slipstream: architecture options for real-time process analytics
Proceedings of the 2011 ACM Symposium on Applied Computing
Prioritization and management of inter-enterprise collaborative performance
Decision Support Systems
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This paper discusses the difficulty of controlling a complex project caused by the great number of performance indicators. The problem studied is how to allow project managers to better control the performance of their projects. From a literature review we noted several critical aspects to this problem: there are many dimensions for evaluating project performance (cost, time, quality, risk, etc.); performance factors should be able to be relevantly aggregated for controlling the project, but no formalized tool exists to do this. We suggest a method to facilitate project performance analysis via a multi-criteria approach. The method focuses on three particular axes for the analysis of project performance: project task, performance indicator categories, and a breakdown of the performance triptych (Effectiveness, Efficiency, Relevance). Finally, the MACBETH method is used to aggregate performance expressions. An application case study examining a real project management situation is included to illustrate the implementation.