This analysis highlights supplier selection using fuzzy AHP and fuzzy TOPSIS in public procurement, suggesting improved decision-making.
Comprehensively examining costs and benefits in supplier selection makes the right choice challenging Globalization increases alternatives, yet selecting the most appropriate remains difficult. Therefore, the use of scientific methods is critical when choosing among alternatives. Such methods not only facilitate the decision-making process but also enable more accurate and reliable outcomes. In the public sector, outsourcing supplier selection is typically conducted through a tender-based process, where cost is primary; however, relying solely on it can lead to suboptimal decisions. Public procurement processes proceed by identifying needs, making announcements, and inviting companies to participate in the tender. Multi-Criteria Decision-Making (MCDM) methods are commonly used tools for addressing complex problems with multiple factors, such as supplier selection. MCDM methods allow decision makers to evaluate each criterion for all alternatives and determine the option that best meets the desired requirements. Furthermore, techniques such as fuzzy logic within MCDM methods go beyond numerical data and enable decision makers to evaluate the criteria and alternatives with more understandable linguistic expressions. Although supplier selection problems are frequently examined using Fuzzy AHP and Fuzzy TOPSIS methods, studies specifically focusing on the public sector remain limited. This study addresses the problem of selecting a cleaning company. It integrates Fuzzy AHP and Fuzzy TOPSIS, aiming first to determine criteria weights using Fuzzy AHP and then to identify the most suitable supplier via Fuzzy TOPSIS. The study was implemented as an alternative method to tender-based outsourcing company selection in the public sector and is deemed beneficial.
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Bayındır et al. (2025) studied this question.
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