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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4 sonuçlar
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Yayın Towards sustainable cities: A sustainability assessment study for metropolitan cities in Turkey via a hybridized IT2F-AHP and COPRAS approach(Elsevier, 2022) Yılmaz, Mustafa Kemal; Kuşakcı, Ali Osman; Kuşakcı, Sümeyye; Sowe, Samba; Nantembelele, Fatuma Abdallah; Yönetim Bilimleri Fakültesi, İşletme BölümüAccelerating trends of urbanization enforce the integration of sustainability principles into urban planning in a local scale to foster prosperity for the next generation of cities. This study incorporates fifty-three indicators on economic, social, environmental, and institutional dimensions to develop a Sustainable Cities Index (SCI) and assess the sustainability performance of thirty metropolitans in Turkey over 2010-2018. Turkish metropolitans constitute an appealing case study due to the rapid urbanization within the same time span. To answer how new metropolitans have been doing and whether they perform better than formerly declared metropolitans in Turkey, we propose a novel methodology with three stages that hybridizes Interval Type-2 Fuzzy Analytical Hierarchy Process (IT2F-AHP) and Complex Proportional Assessment of Alternatives (COPRAS). The former captures a high degree of uncertainty due to the subjective weight assignment by the experts, while the latter calculates aggregate scores for 30 cities. Finally, we conduct posthoc analyses to examine the significance of the urbani-zation policies in Turkey on the SCI scores. Thus, the study provides valuable insights into urbanization practices and encourages local administrations to spend more effort balancing the benefits and costs of public policies on sustainability.Yayın A Scoping review of artificial intelligence applications in airports(Sigma Xplore, 2024) Amiri, Misagh Haji; Kuşakcı, Ali Osman; Yönetim Bilimleri Fakültesi, İşletme BölümüThis paper aims to synthesize the literature on the application of artificial intelligence for airports. The selected methodology was based on the PRISMA Extension for Scoping Reviews (PRISMA-ScR), a recognized framework for systematic reviews. Authors searched the Scopus and Web of Science databases for articles that met the following criteria: (1) publication in peer-reviewed journals, (2) English language, and (3) relevance to airport operations, demonstrated by either (a) the use of airport datasets for showcasing AI applications or (b) the use of airports as case studies. Articles were assessed by two reviewers, and data were extracted on the articles’ keywords, publication year, and origin country. After screening and checking for eligibility, 121 unique articles were examined. Upon assessment, the included articles were categorized into seven main themes. Each category and its specific subtopics were individually discussed within this paper. Results indicate that the most extensively studied category belongs to airport administration and management. Security and air traffic control (ATC) were the second and third most studied categories, respectively. Notably, a significant portion of the articles focused on optimization techniques, scheduling strategies, and developing decision support systems (DSS) tailored to various airport departments. This paper not only highlights current research trends in the field of AI for airports but also identifies gaps in the existing literature. The paper proposes future research directions to enhance the effective implementation of AI technologies within airport environments.Yayın Efficiency analysis of major airlines: Exploring the operational performance determinants in aviation(Springer, 2024) Çınar Yalçın, Kübra; Kuşakcı, Ali Osman; Tatoğlu, Ekrem; Yönetim Bilimleri Fakültesi, İşletme BölümüThis paper evaluates the performances and dynamics of productivity changes of 38 airlines from different regions of the world between 2015 and 2019, assessing the effects of business model, alliance membership, the economic development level of the home country, and size on the operational performance of the airlines. In this regard, first, constant returns to scale (CRS) and variable returns to scale (VRS) input-oriented data envelopment analysis (DEA) models with three inputs and two outputs are implemented. The input-oriented CRS model super-efficiency DEA is also used to discriminate between efficient airlines. The Malmquist Productivity Index (MPI) estimates efficiency dynamics across time. Further, the determinants of operational efficiencies are assessed by applying Mann-Whitney rank-sum tests. The analysis results show that most airlines suffer from scale inefficiency. MPI signifies productivity deterioration in airlines’ performance. It is found that low-cost carriers (LCC) have performed better than full-service carriers and alliance member airlines are less efficient than non-member airlines. Additionally, developed country airlines show better performance than their emerging country counterparts. Lastly, the size of airlines measured in available seat kilometers (ASK) is found to have no statistically significant effect on performance.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.
