4.5 Article

A Framework for Prioritization and Selection of Strategic Projects

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEM.2022.3177364

Keywords

Industries; Organizations; Indexes; Correlation; Stakeholders; Semantics; Investment; Criteria importance through intercriteria correlation (CRITIC); multicriteria decision analysis; project ranking; strategic project selection; technique for order of preference by similarity to ideal solution (TOPSIS)

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This article proposes a framework and analytical methodologies to support decision-making for selecting cross-industry strategic projects, demonstrating its applicability in Qatar's real estate and transportation projects.
Strategic projects are critical for the sustenance of an organization; however, they are subject to different types of constraints in terms of risk, management capabilities, resources, and political and cultural factors. Therefore, prioritizing and selecting these projects becomes a challenging task in each organization that focuses on multiple strategic projects spanning different sectors or industries. This article proposes a framework for analyzing strategic projects to rank heterogeneous projects across industries. The framework uses a multiple-criteria decision analysis model to prioritize strategic projects based on a set of criteria. The criteria were developed through clustering the relevant factors. Projects are first weighted with the criteria importance through intercriteria correlation method and then ranked using the technique for order of preference by similarity to ideal solution method. Vector weighting is then applied to rank the projects. The framework is demonstrated by its application to Qatar's real estate and transportation projects. This article contributes by providing a holistic framework and analytical methodologies to support decision-making for selecting one or more types of cross-industry strategic projects. Results show that the cross-industry project ranking obtained from the model is highly correlated with the ranks assigned by experts. The applicability of the model and the future research direction are also discussed.

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