Selecting projects to develop from the many that are usually possible, or "project portfolio selection " is a crucial decision in many organizations. Many different methods for portfolio selection have been suggested in the literature but no integrated framework has been developed for carrying it out. In this thesis, we suggest a framework that builds on the strengths of existing methods. The proposed framework separates the project portfolio analysis and selection process into distinct stages and allows users to choose the techniques they find the most suitable for each stage. Since finding the optimal solution is the most sophisticated part of the proposed framework, we developed a zero-one linear integer-programming model for this stage that overcomes the shortcomings of existing models and advances previous work in this area. The model we developed considers multiple, conflicting goals, including qualitative objectives, and selects and schedules the optimal set of projects. The solution maximizes benefits according to pre-specified priorities without violating any constraints such as resource limitations, project interdependencies, and portfolio balancing. We implemented the proposed framework in the form of a decision support system (DSS) to facilitate and encourage decision maker involvement throughout the process. For this purpose we developed PASS (Project Analysis and Selection System). PASS is a user-friendly DSS that suits the knowledge level of potential users and allows interaction with the system as well as intervention to make adjustments to the solution it provides. We tested the usefulness, perceived usefulness and perceived ease of use of PASS in a lab setting and gained significant results in support of the developed hypotheses. We also presented our approach to two high-tech firms who wanted to investigate the feasibility of PASS for project portfolio selection, and received very promising feedback from these companies.

Doctor of Philosophy (PhD)