Kuşakcı, Ali Osman
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Araştırma projeleri
Organizasyon Birimleri
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
3 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 3 / 3
Yayın Profiling consumers' decision-making styles: The case of environmental conscious consumers in Basaksehir, Istanbul(Bandırma Onyedi Eylül Üniversitesi, 2019) Kuşakcı, Ali Osman; Topaloğlu, Kürşat; Kifo, Nour; Yönetim Bilimleri Fakültesi, İşletme BölümüEvery person has differences from others through personality, lifestyle, economic wealth, and their interest. Hence these differences affect their decisions. This research provides a clear look for antecedent studies on consumer decision-making styles (DMS), connects the findings of those studies with today's consumers, and determine a new dimension of the consumers' DMS that affected by new consumer trends, which is thriving by environmental awareness of consumers. Where, less plastic usage and more green products are consumed by environmentally friendly consumers. The research starts with a brief summary of consumers' DMS dimensions, explains the need for the new dimension, clarifies consumers DMS of people that live in Başakşehir, Istanbul, and make suggestions for firm managers, marketers and the future researches. Lastly, results show that six out of eight factors suggested by Sproles and Kendall, [1986], are validated by the research. Whereas, two of the factors are not confirmed, and a new dimension has determined, which is named as “environmentally conscious consumer".Yayın Country selection for energy company’s new branch using fuzzy topsis(Yıldız Teknik Üniversitesi, 2019) Kuşakcı, Ali Osman; Chlyeh, Douina; Elaiche, Aicha; Yönetim Bilimleri Fakültesi, İşletme BölümüSolar energy is regarded as one of the most important and promising technologies in the field of renewable energies. Turkey has been one of the first countries to adopt solar energy and harness it in the last two decades. Many Turkish companies especially holdings started to invest in North Africa, either by expanding their operations there or through opening new branches and making alliances with the other countries concerned. This paper aims to identify the best North African country for a specific Turkish company to open a solar energy branch. The process involved Fuzzy Topsis multi-criteria decision making where criteria for selection of one of the countries has been collected from experts, and three decision makers have been chosen to rate the criteria in terms of each alternative countries. Fuzzy topsis analysis was chosen because of the level of the uncertainty in this case study. Regardless of the data available concerning each criterion for all the alternative countries, there is still a certain level of ambiguity to overcome. The results of this study suggested that Algeria would be the best choice for this Turkish company to open up a new branch. The second best fitting country would be Egypt followed by Libya. While Morocco and Tunisia had the lowest ranking.Yayın Performance measurement of composite textile industries in Pakistan using data envelopment analysis(2018) Kuşakcı, Ali Osman; Jasmin, Mariam; Bushera, İbrahim; Yönetim Bilimleri Fakültesi, İşletme BölümüThis study aims at evaluating and measuring the relative technical efficiency of Pakistan’s textile industry vertically integrated composite firms using Data Envelopment Analysis under the assumption of variable returns to scale (VRS). The data used for this study is collected from the firm’s official website and the Karachi Stock Exchange. This output oriented study covers 29 firms for the period of 2014-2016 employing three homogeneous inputs and outputs. Current asset, production cost and administration cost of the firms are used as inputs elements, gross profit, and total sales and net income compromised the output constituent. In addition to evaluating technical efficiency, this paper examines variations among efficient and inefficient firms. Our findings indicate that, only 17% percent of the firms are scale efficient while 35% of the firms are technically efficient with a mean value of 0.731. Our analysis also indicates an average of 0.572 technical efficiency from constant returns to scale DEA, an average of 0.731 of technical efficiency from variable returns to scale DEA, and an average of 0.805 Scale efficiency. Accordingly, this study confirmed the existence of scale and technical efficiency difference between the firms of the same industry. Though the determinant and factors of efficiency difference among firms is not examined in this study, we recommend that inefficient firms need to enhance their scale size and perk up their managerial practices to enhance their overall efficiency.
