Ali Osman Kuşakcı

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.

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Ali Osman Kuşakcı

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Business Analytics, Artificial Intelligence, Genetic Algorithm, Constrained Optimization

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Listeleniyor 1 - 10 / 12

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.
The evaluation of operational efficiencies of Turkish airports: An integrated spherical fuzzy AHP/DEA approach
(Elsevier, 2022) Hacıoğlu, Ümit; Yılmaz, Mustafa Kemal; Kuşakcı, Ali Osman; Hacıoğlu, Ümit; Yılmaz, Mustafa Kemal; Kuşakcı, Ali Osman; Yılmaz, Mustafa Kemal; Kuşakcı, Ali Osman; Aksoy, Mine; Hacıoğlu, Ümit; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
The demand for air transport services has significantly increased around the globe, which has brought new investments in airports, which, in turn, requires in-depth efficiency analysis of these capital-intensive endeavors. This study examines the operational efficiencies of 46 Turkish civil airports from 2015 to 2018. We employ a novel hybrid methodology that combines Spherical Fuzzy Sets based Analytic Hierarchy Process (SFS-AHP) and Data Envelopment Analysis (DEA), which provides a solid basis for efficiency analysis. To this end, it can handle the hesitancy and uncertainty that the subjective evaluation process of input and output factors possess. Then, we use Self Organizing Maps (SOM), a machine learning method for clustering, to examine the effect of outlier airports on the efficiency scores. Finally, a posthoc analysis is conducted with Tobit regression model to assess the explanatory power of external factors on the efficiency scores, i.e., tourism potential, number of international flights, distance to the city center, population, public/private ownership, and age of airport. The findings show that 67.2% of the Turkish airports operate below the optimal efficiency level, and 93.5% of them should make considerable efforts to refine their operations by implementing managerial and structural changes to reduce input factors. The results also suggest that the airports located in high-density touristic areas achieve higher efficiency levels. Those relatively closer to the city center lead to more airport traffic, generating more revenues. Thus, both factors have a significant impact on efficiency scores. The study provides a novel efficiency analysis framework for airport operators and policy makers that helps them make informed decisions.
Designing reverse logistics network for end-of-life vehicles: A sustainability perspective in a fragile supply chain
(The International Journal of Industrial Engineering, 2021) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Ayvaz, Berk; Kuşakcı, Ali Osman; Aydın, Nezir; Ertaş, Emine; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
Environmental guidelines in the automotive industry greatly emphasize the recycling, remanufacturing, and recovering of end-of-life vehicles (ELVs). Given the principle of extended producer responsibility, developing an effective reverse logistics network is the most significant digit ahead of the industry. However, initial attempts addressing the reverse logistics network design (RLND) problem were short-sighted, focusing on cost minimization. Undoubtedly, the whole concept of recycling was founded on the pillars of sustainability. Accordingly, reverse logistics network design must be motivated by long-term environmental and societal benefits. This fact has become even more prominent in the current pandemic environment as COVID-19 has added serious uncertainties and risks to the supply chain processes. This paper reiterates the essence of sustainability goals and proposes a multi-objective fuzzy mathematical model to RLND problem for ELVs under such a fragile and fuzzy environment. The coverage of the proposed model is to optimally determine the locations and numbers of the facilities and the flows among them concerning environmental, social, and economic aspects. Hence, the model aims to reach a robust compromise solution that leads to a resilient network design. A real case study on the ELV market in Istanbul/Turkey proves the merit of the developed model.
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.
Selection of alternative fuel taxis: A hybridized approach of life cycle sustainability assessment and multi-criteria decision making with neutrosophic sets
(Taylor & Francis Online, 2021) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Aboushaqra, Nour N. M.; Onat, Nuri Cihat; Kucukvar, Murat; Hamouda, A. M. S.; Kuşakcı, Ali Osman; Ayvaz, Berk; Yönetim Bilimleri Fakültesi, İşletme Bölümü
This study presents a combined application of hybrid life cycle sustainability assessment and multi-criteria decision-making, aiming to further advance an integrated sustainability assessment and decision-making for the selection of alternative-fuel taxis. First, a multiregional hybrid life cycle sustainability assessment model is built to evaluate macro-level sustainability impacts of various vehicle types: conventional gasoline vehicles, compressed natural gas vehicles, hybrid, and battery electric vehicles. Second, considering the subjective nature of the evaluation process, the intervalvalued neutrosophic sets-based analytic hierarchy process is suggested to assess the results obtained from the life cycle model to determine the weight of each evaluation criterion. Then, the technique for order preference by similarity to the ideal solution is used to rank the sustainability performance. Two different charging scenarios are also tested. The results show that solar-powered BEVs are the best in the environmental impacts with the exceptions of water consumption and land use. Solar-powered BEVs are superior in human health impact, while, ICVs are the best in compensation and employment generations. The ranking results reveal that solar-powered BEVs are the best alternatives when all indicators are considered, followed by CNG vehicles. The proposed method provides a practical and life cycle-based decision-making approach to support and prioritize effective policies for more sustainable transportation.
Digital transformation in the defense industry: A maturity model combining SF-AHP and SF-TODIM approaches
(Elsevier, 2022) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Nebati, Emine Elif; Ayvaz, Berk; Kuşakcı, Ali Osman; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
As an inevitable process, digitalization has become a priority for many companies. The measurement of digital maturity is the first step toward adequately executing this. Although digital maturity models (DMM) have been developed for different sectors in the literature, such studies in the defense industry are lacking due to sector-specific dynamics. This study aims to close this gap and proposes a digital maturity model specific to the defense industry. In this study, a novel model was developed that combines the SF-AHP and SF-TODIM methods due to the uncertainty and hesitancy contained in the evaluation. The validity of the presented novel model has been demonstrated in a prominent defense company in Turkey. According to the results, the most notable digital maturity dimensions are the evaluation of opportunities and alignment with stakeholders. In addition, the model indicates that the company owns the required soft skills, such as leadership, organizational culture, and strategic determination for digital transformation (DT). On the other hand, essential hard skills such as technology and operational competencies are yet to be improved. Lastly, sensitivity and comparison analyses are conducted to validate and verify the obtained results’ stability and robustness.
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.
ERP system evaluation in the defense industry: A hybridized spherical fuzzy AHP-codas approach
(World Scientific, 2023) Nebati, Emine Elif; Ayvaz, Berk; Kuşakcı, Ali Osman; Yönetim Bilimleri Fakültesi, İşletme Bölümü
Design/methodology/approach: Converting data into information and its diffusion along all organization units has become a vital survival skill. At this point, an ERP system provides an invisible network among a company's internal and external stakeholders and plays a strategic role. Moreover, ERP systems offer some advantages. For example, integrating financial, customer, and order information, speeding up production processes, and reducing stock level and order lead time. Therefore, we propose an integrated spherical fuzzy-analytical hierarchy process (SF-AHP) and spherical fuzzy-combinative distance-based assessment (SF-CODAS) framework to prioritize the best ERP software provider for the defense industry. Purpose: Despite having the advantages mentioned above, some crucial aspects must be considered while selecting an ERP package. Factors such as high cost, difficulty in installation, and security threats can be very challenging. The latter issue needs special care in the defense industry. This study aims to design an evaluation framework for the ERP selection problem in the sector.Findings: One of the pivoting defense companies in Turkey is chosen as a case study. Seven ERP systems are evaluated with the proposed model. The results show that the proposed model can be successfully implemented in a defense company context. Furthermore, a sensitivity analysis proves the robustness of the approach to varying threshold parameters in CODAS and different fuzzy weighting approaches.Originality/value: The defense professionals prioritize a different set of selection criteria than conventional manufacturing firms. The study provides a rare holistic framework for the defense industry using a hybridized SF-AHP-CODAS technique. Thus, the study may serve as reference work for the researchers and decision-makers during the digitalization journey of defense firms.
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.
Sustainability assessment of biomass-based energy supply chain using multi-objective optimization model
(Springer, 2024) 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.

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