A Fuzzy Data Envelopment Analysis Approach for Measuring the Efficiency of Defense Industry Software Projects
Year: 2025
Type: conference-paper
Abstract: For centuries, defense industry projects have been of strategic importance in terms of efficient use of limited resources and achievement of high-performance targets. Such projects require a multidimensional evaluation process that encompasses not only technical capabilities but also process efficiency and resource utilisation effectiveness. Decision makers should evaluate the efficiency analysis of projects in order to optimize the resources of the projects, determine their strengths and weaknesses, and make strategic planning. However, Defense Industry projects include many factors in their processes such as complex structures, having many inputs and outputs, resource usage, cost estimates, optional risks, and evaluation of project performance. For this reason, traditional efficiency analyses cannot model all of these uncertainties and critical elements are overlooked in decision-making processes. In this study, Fuzzy Data Envelopment Analysis (FDEA), a more flexible and reliable method, was used for efficiency measurement of Defense Industry software projects. Since the projects are large and complex, as well as having qualitative and quantitative data, the fuzzy data envelopment method, which is a fuzzy logic version of the traditional data envelopment analysis method, was used. Within the scope of the study, the effectiveness analysis of 10 projects with 5 input criteria ("delivery time", "process management effectiveness", "failure frequency", "number of project personnel", "number of warranty period problems") and 4 output criteria ("customer satisfaction", "technical requirement fulfillment rate", "warranty performance", "revenue") were evaluated with the FDEA method. This study aims to provide decision makers with a flexible, easy and objective evaluation by using the FDEA method in evaluating the effectiveness analysis of defense industry projects with quantitative and qualitative data.
Authors: Buse Uslu, Prof. Dr. Adnan AKTEPE, Prof. Dr. Süleyman ERSÖZ
Institution: Kırıkkale University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7104055372
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