Kuşakcı, Ali Osman

Profil fotoğrafı
 E-posta Adresi
aliosman.kusakci@ihu.edu.tr
ORCID Profili
0000-0003-1411-0369
WoS Profili
AAG-5110-2019
Scopus Profili
55330793300
YÖK Araştırmacı Profili
43DD5E590083C016
Google Akademik Profili
YZi-UJQAAAAJ&hl=tr&oi=ao
TR-Dizin Profili
720523
Web Sitesi
akademik.ihu.edu.tr/tr/aliosman-kusakci

Araştırma projeleri

Organizasyon Birimleri

Organizasyon Birimi Logosu
Organizasyon Birimi
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

Kurumdaki Durumu

Aktif Personel

Filtreler

2022 - 20252
Filtreleri Sıfırla

Ayarlar

İndeks: Web of Science × search.filters.applied.f.publicationcategory: Tezden Üretilmiş Yayın ×

Arama Sonuçları

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    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 Bölümü
    Accelerating 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.
  • Küçük Resim
    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 Bölümü
    Purpose – 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.