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 / 25

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.
Mühendisler için sistem benzetimi
(Nobel Akademik Yayıncılık, 2022) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Ayvaz, Berk; Borat, Oğuz; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
Gözlem, insanoğlunun en etkin öğrenme aracıdır. Gerçek hayata ilişkin bir olguyu incelerken olgular arasında neden-sonuç ilişkisi kurarken gözlemler yaparız. Doğa olaylarını açıklayıcı genel kanunlara ulaşmak, yeni sistemler kunnak ve bunların işleyişlerindeki problemleri tespit etmek ve yeni çözümler üretebilmek için gözlem önemli bir fonksiyon ifade etmektedir. Ancak gerçek bir sistemi gerçek zamanlı olarak gözlemenin bazı zorlukları vardır. Örneğin, doğru şekilde gözlemleyebilmek için sistemi durdurmanız gerekebilir. Fakat bu her zaman mümkün olmayacaktır. Gerçek bir sistemi gözlemenin başka bir zorluğu da gözlemin ciddi zaman almasıdır. Tam da bu noktada benzetim yaklaşımları bir alternatif olarak devreye girmektedir.
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.
Assessment of Ibn Haldun’s model for sustainability using structural equation modelling
(International Association for Business and Society (IABS), 2020) Kuşakcı, Ali Osman; Kuşakcı, Sümeyye; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
This work firstly aims to develop a sustainability model based on Ibn Haldun’s teaching of sustainability. Religious coloring refers to the spirituality, which is re-discovered in modern ages and transferred to the workplace. Spirituality stimulates virtuousness at personal and organizational level, which in turn generates managerial sustainability meaning the lifespan of a company. While personal virtuousness refers social ethics, organizational level virtuousness could be considered as Corporate Social Responsibility. Secondly, it attempts to evaluate the relevance of Ibn Haldun’s approach to contemporary business organizations. In order to demonstrate the relationship between spirituality, virtuousness, CSR, and sustainability; data collected from Corporate Knights’ Global 100 companies were analyzed using structural equation modelling. According to the results, while workplace spirituality leads to ethical conduct and higher CSR/CS score, the relationship between spirituality or CSR/CS and financial performance is not significant. However, it seems that higher lifespan of business enterprises is related to their CSR/CS score.
Yapay zekanın bir parçası olarak doğadan esinlenen optimizasyon algoritmaları
(Beta Yayınları, 2020) Kuşakcı, Ali Osman; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
[No Abstract Available]
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.
A Scoping review of artificial intelligence applications in airports
(Sigma Xplore, 2024) Amiri, Misagh Haji; Kuşakcı, Ali Osman; Yönetim Bilimleri Fakültesi, İşletme Bölümü
This paper aims to synthesize the literature on the application of artificial intelligence for airports. The selected methodology was based on the PRISMA Extension for Scoping Reviews (PRISMA-ScR), a recognized framework for systematic reviews. Authors searched the Scopus and Web of Science databases for articles that met the following criteria: (1) publication in peer-reviewed journals, (2) English language, and (3) relevance to airport operations, demonstrated by either (a) the use of airport datasets for showcasing AI applications or (b) the use of airports as case studies. Articles were assessed by two reviewers, and data were extracted on the articles’ keywords, publication year, and origin country. After screening and checking for eligibility, 121 unique articles were examined. Upon assessment, the included articles were categorized into seven main themes. Each category and its specific subtopics were individually discussed within this paper. Results indicate that the most extensively studied category belongs to airport administration and management. Security and air traffic control (ATC) were the second and third most studied categories, respectively. Notably, a significant portion of the articles focused on optimization techniques, scheduling strategies, and developing decision support systems (DSS) tailored to various airport departments. This paper not only highlights current research trends in the field of AI for airports but also identifies gaps in the existing literature. The paper proposes future research directions to enhance the effective implementation of AI technologies within airport environments.
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.
Integrated modelling for sustainability assessment and decision making of alternative fuel buses
(Elsevier, 2023) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Elagouz, Noura; Onat, Nuri Cihat; Kucukvar, Murat; Ayvaz, Berk; Kutty, Adeeb A.; Kutty, Adeeb A.; Kuşakcı, Ali Osman; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
In this paper, a hybrid life cycle sustainability assessment (LCSA) model integrating multi region input–output analysis with novel multi-criteria decision-making techniques is proposed to assess three different fuel alternatives: compressed natural gas (CNG), electric buses (EBs), and diesel buses (DBs). A global hybrid LCSA model first quantified the environmental, economic, and social impacts of alternative fuel buses. The results were investigated in terms of multiple combinations of manufacturing and end-of-life scenarios by encompassing impacts embedded in the global supply chains taking Qatar as a case applied to the proposed model. The Interval-Valued Neutrosophic Fuzzy (IVNF)-Analytic Hierarchy Process with the Combined Compromise Solution (CoCoSo) approach is used to rank the alternative fuel buses based on their corresponding sustainability performance. The proposed model will help in quantitatively capturing the macrolevel life cycle socioeconomic and environmental impacts along with optimally selecting alternatives to support sustainable urban transport policy towards a net-zero transportation system globally.
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.

Kuşakcı, Ali Osman

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