Kuşakcı, Ali Osman
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Araştırma projeleri
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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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Yayın Performance evaluation of real estate investment trusts using a hybridized interval type-2 fuzzy AHP-DEA approach: The case of Borsa Istanbul(World Scientific Publishing, 2019) Tatoğlu, Ekrem; Yılmaz, Mustafa Kemal; Kuşakcı, Ali Osman; Tatoğlu, Ekrem; Yılmaz, Mustafa Kemal; Kuşakcı, Ali Osman; Yılmaz, Mustafa Kemal; Kuşakcı, Ali Osman; Tatoğlu, Ekrem; İçten, Orkun; Yetgin, Feyzullah; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme BölümüThis study proposes a three-stage holistic methodology combining an interval type-2 fuzzy analytical hierarchy process (IT2F-AHP) and data envelopment analysis (DEA) to deal with the performance evaluation problems encountered in fuzzy decision environments. In the first stage, prospective inputs and outputs are determined by field studies. The second stage employs IT2F-AHP to identify the most appropriate performance indicators based on vague expert judgements. Finally, DEA is applied to the decision-making units (DMUs) based on the selected set of input and output measures. The proposed methodology proves its merit on a case study addressing the performance of real estate investment trusts (REITs) in Turkey during their ten-year journey of trading on Borsa Istanbul (BIST). The results demonstrate that the average scores for technical, pure technical and scale efficiencies are 66%, 80% and 80%, respectively. Considering the technical efficiency scores, Turkish REITs could have reduced their input factors by an average of 34%. The findings also reveal that the majority of Turkish REITs suffer from economies of scale and could have improved their performance by expansion.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.