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

2019 - 201912020 - 20241
Filtreleri Sıfırla

Ayarlar

WoS Q: Q2 ×

Arama Sonuçları

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    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 Bölümü
    This 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.
  • Küçük Resim
    Yayın
    Sustainability assessment of biomass-based energy supply chain using multi-objective optimization model
    (Springer, 2024) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Yıldız, Hatice Güneş; Ayvaz, Berk; Deveci, Muhammet; Garg, Harish; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
    In recent years, population growth and lifestyle changes have led to an increase in energy consumption worldwide. Providing energy from fossil fuels has negative consequences, such as energy supply constraints and overall greenhouse gas emissions. As the world continues to evolve, reducing dependence on fossil fuels and finding alternative energy sources becomes increasingly urgent. Renewable energy sources are the best way for all countries to reduce reliance on fossil fuels while reducing pollution. Biomass as a renewable energy source is an alternative energy source that can meet energy needs and contribute to global warming and climate change reduction. Among the many renewable energy options, biomass energy has found a wide range of application areas due to its resource diversity and easy availability from various sources all year round. The supply assurance of such energy sources is based on a sustainable and effective supply chain. Simultaneous improvement of the biomass-based supply chain's economic, environmental and social performance is a key factor for optimum network design. This study has suggested a multi-objective goal programming (MOGP) model to optimize a multi-stage biomass-based sustainable renewable energy supply chain network design. The proposed MOGP model represents decisions regarding the optimal number, locations, size of processing facilities and warehouses, and amounts of biomass and final products transported between the locations. The proposed model has been applied to a real-world case study in Istanbul. In addition, sensitivity analysis has been conducted to analyze the effects of biomass availability, processing capacity, storage capacity, electricity generation capacity, and the weight of the goals on the solutions. To realize sensitivity analysis related to the importance of goals, for the first time in the literature, this study employed a spherical fuzzy set-based analytic hierarchy method to determine the weights of goals.