Many Chief Information Officers (CIOs) and senior executives face the challenge of finding the appropriate IT resource allocation to meet enterprise strategic goals across multi-organizational units. To address this problem, my dissertation opens the black box of enterprise strategic IT resource allocation by examining the prioritization and selection of IT investment choices (i.e., IT initiatives). Since IT Portfolio Management (ITPM) involves making applicable decisions to achieve a firm’s strategic objectives by fine-tuning budgeted costs and returns as business conditions change, my dissertation examines an important class of IS decision problems: IT portfolio attributes and investment choices. My research addresses how a firm can systematically profile numerous IT portfolios and provide theoretical insights into the components of the optimal solution. Based on design science, my specialized method incorporates mathematical optimization and computational experiments and combines real-world data using the Monte Carlo approach to simulate the experimental data. Consequently, by combining the suggested IT portfolio attributes while addressing a variety of ITPM-related issues, the main contribution for my research is a new ITPM-related methodology built on three proposed ITPM models/techniques: (1) optimal efficiency across multi-organizational levels/units simultaneously; (2) the most qualified IT portfolio selection that incorporates decision-makers’ risk tolerance levels; and (3) accurately estimating the current financial standing of each project in a portfolio of IT projects over the project’s full lifecycle. By applying the proposed ITPM-related methodology with illustrative examples, I develop theoretical propositions based on my main findings.
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