A Second Chance for Failed Projects Using Data Envelopment Analysis Based on Project Attractiveness Factors

Abstract

Assessing project profitability using Net Present Value (NPV), Internal Rate of Return (IRR), and Modified Internal Rate of Return (MIRR) is a common practice. However, these metrics often overlook key differences between new and existing projects, leading to potential data uncertainty and the failure to capture the complex interrelationships among influencing factors. This paper introduces data envelopment analysis (DEA) as a supplementary tool to identify the most efficient year within a project's lifecycle, optimize inputs and outputs, and evaluate the factors most impacting the efficiency of decision-making units (DMUs). By optimizing these values, the paper reexamines NPV, IRR, and MIRR to allow for a comparison with the original assessment. If profitability improves, the project becomes more attractive, with the modified inputs and outputs serving as the new benchmark. A case study of a non-viable road project demonstrates this approach. While NPV, IRR, and MIRR showed improvement, the project remained unappealing under optimal conditions. Additionally, a simulated dataset, based on case study parameters, revealed enhanced profitability and new project viability when analyzed. With revised input and output values, the project's appeal and viability were significantly improved.