Kuşakcı, Ali Osman

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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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Listeleniyor 1 - 2 / 2
  • Yayın
    Retailer layout design: A novel hybrid approach with association rules mining and MCRAFT
    (Inderscience, 2020) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Cesur, Elif Karakaya; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
    Spatial layout of a retail store is a crucial decision variable related to both utilisation of store area and purchasing behaviour of the customer. In this respect, the task of optimising the allocation of shelves to specific product segments has become a strategic decision to facilitate a more comfortable shopping environment for customers, which, in turn, increases sales volume. This study proposes a novel hybrid approach to facility layout design problem, which combines association rules mining (ARM) and a facility layout method, MCRAFT. The proposed methodology is composed of two main stages: 1) rule mining; 2) layout design. More specifically, the presented approach exploits the association rules obtained from purchasing records and uses them as a proximity measure input to MCRAFT algorithm to determine the layout of the store. The merit of the proposed methodology is shown with a case study on a prominent Turkish supermarket chain.
  • 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.