Kuşakcı, Ali Osman
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Araştırma projeleri
Organizasyon Birimleri
Yönetim Bilimleri Fakültesi, İşletme Bölümü
Küresel rekabete ayak uydurmak ve sürdürülebilir olmak isteyen tüm şirketler ve kurumlar, değişimi doğru bir şekilde yönetmek, teknolojinin gerekli kıldığı zihinsel ve operasyonel dönüşümü kurumlarına hızlı bir şekilde adapte etmek zorundadırlar.
Adı Soyadı
Ali Osman Kuşakcı
İlgi Alanları
Business Analytics, Artificial Intelligence, Genetic Algorithm, Constrained Optimization
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2 sonuçlar
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Yayın A hybridized Pythagorean fuzzy AHP and WASPAS method for airline new route selection: Case study of Turkish Airline(Emerald Publishing, 2025) Koma, Şenay; Kuşakcı, Ali Osman; Haji Amiri, Misagh; Yönetim Bilimleri Fakültesi, İşletme BölümüPurpose – This study aims to provide a practical and novel solution for the complex multi-criteria decision-making (MCDM) problem of airline route selection, which is characterized by conflicting criteria, alternative routes, and complex judgments. Design/methodology/approach – This study proposes a hybrid MCDM approach using Interval-valued Pythagorean Fuzzy AHP and Interval-valued Pythagorean Fuzzy weighted aggregated sum product assessment (WASPAS) methods. Decision analysis is applied to select a new route between different alternatives through selection criteria. Pythagorean Fuzzy AHP is used for weighting criteria, and Pythagorean Fuzzy WASPAS is used for assessing alternatives. The pair-wise linguistic comparisons of selection criteria are transferred into Pythagorean fuzzy numbers (PFNs) to weigh each criterion’s importance. Findings – The pair-wise linguistic comparisons of selection criteria are transferred into PFNs to weigh each criterion’s importance. The results of these comparisons show that the main criteria, cost (43% weight) and demand (33% weight), impact route selection decisions more than social/economic conditions (15% weight) and competitiveness (9% weight). Regarding the criteria, the five routes alternative were evaluated by the route development experts, and the best route was selected with Pythagorean Fuzzy WASPAS. Practical implications – The proposed model is used for a route selection problem of Turkish Airlines, the airline that flies to the most countries in the world. Originality/value – To the best of the authors’ knowledge, this study is the first to use the Interval-valued Pythagorean Fuzzy AHP combined with Interval-valued Pythagorean Fuzzy WASPAS to solve the route selection problem. This hybrid MCDM methodology presents a novel and feasible solution for selecting the new route for airlines.Yayın Evaluation of maintenance strategies using Pythagorean fuzzy sets: A novel model for time-constrained processes(Taylor & Francis, 2025) Sancar, Semih; Kuşakcı, Ali Osman; Ayvaz, Berk; Yönetim Bilimleri Fakültesi, İşletme BölümüConsidering the large investment cost as well as expectations such as increased awareness ofoccupational safety and quality, choosing the appropriate maintenance strategy emerges as acritical decision. Time-constrained production processes, which demand defect-free produc-tion within a limited timeframe, intensify the significance of this selection problem. In suchproduction processes, the product is generally short-lived, so stocking is not possible.Therefore, halting operations incurs significant costs. In this study, we aim to choose themost appropriate maintenance planning strategy for time-constrained processes. Given thatthe process of selecting a maintenance strategy is ambiguous and lacks conclusive assess-ments, it involves numerous hazy criteria. Thus, this study presents a framework that includesthe Pythagorean Fuzzy AHP-CRITIC-Entropy combined weighting method hybridized withPythagorean Fuzzy WASPAS. The model evaluates the maintenance options of Türkiye’s largestprinting company, which operates under time-constrained processes, in a real-world case studyproving the merit of the proposed methodology.
