Kuşakcı, Ali Osman

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Organizasyon Birimleri

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

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Listeleniyor 1 - 2 / 2
  • 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.
  • Yayın
    Optimization of reverse logistics network of End of Life Vehicles under fuzzy supply: A case study for Istanbul Metropolitan Area
    (Elsevier, 2019) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Ayvaz, Berk; Cin, Emine; Aydın, Nezir; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
    Recycling aims at preventing rapid depletion of natural resources while transforming produced waste into value for economy. However, this process becomes a major challenge in automotive industry, which requires cooperative engagement of multiple players within a complex supply chain. In line with the essence of the topic, government agencies around the world issue directives drawing regulatory frameworks for designing recycling operations comprising various activities such as collection of end-of-life vehicles (ELVs), recovery of reusable components, shredding ELV's body, recycling valuable materials and disposal of the hazardous waste. In general, the amount of returned product in a reverse logistics network is highly uncertain, and the ELV market in Turkey is no exception to this. For that purpose, this study aims developing a fuzzy mixed integer location-allocation model for reverse logistic network of ELVs conforming to the existing directives in Turkey. Accordingly, this study uses a novel approach and assumes that ELV supply in the network is uncertain. The merit of the proposed mathematical model is proved on a real world scenario addressing the reverse logistics design problem for ELVs generated in metropolitan area of Istanbul. The network generated specifies that recycling process is not profitable under the existing circumstances with the given level of supplied ELV and the returned product records per capita in Istanbul are far beyond the EU averages. Consequently, sensitivity analyses question the reliability of the obtained results.