Aksoy, Tamer

Profil fotoğrafı
 E-posta Adresi
tamer.aksoy@ihu.edu.tr
ORCID Profili
0000-0001-6483-4547
WoS Profili
GPT-4648-2022
Scopus Profili
57712522900
YÖK Araştırmacı Profili
E190529DD404D84E
Google Akademik Profili
tr&user=l8txZ6IAAAAJ
TR-Dizin Profili
326585
SOBİAD Profili
242237
Web Sitesi
akademik.ihu.edu.tr/tr/tamer-aksoy

Araştırma projeleri

Organizasyon Birimleri

Organizasyon Birimi Logosu
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

Tamer Aksoy

İlgi Alanları

Finansal Muhasebe, Yönetim Muhasebesi, Stratejik Denetim/İç Denetim, İç Kontrol, Finans/Sürdürülebilirlik

Kurumdaki Durumu

Aktif Personel

Filtreler

20221
Filtreleri Sıfırla

Ayarlar

İndeks: Web of Science × WoS Q: Q1 ×

Arama Sonuçları

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  • Küçük Resim
    Yayın
    Application of M-SWARA and TOPSIS methods in the evaluation of investment alternatives of microgeneration energy technologies
    (MDPI AG, 2022) Hacıoğlu, Ümit; Aksoy, Tamer; Hacıoğlu, Ümit; Aksoy, Tamer; Dinçer, Hasan; Yüksel, Serhat; Aksoy, Tamer; Hacıoğlu, Ümit; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
    Investments in microgeneration technologies help to boost the usage of clean energy while reducing pollution. However, selecting the appropriate investment remains the most critical phase in developing these technologies. This study aims to design a multi-criteria decision-making method (MCDM) to evaluate investment alternatives for microgeneration energy technologies. The proposed MCDM is based on a Multi Stepwise Weight Assessment Ratio Analysis (M-SWARA), to define the relative importance of the factors. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and q-Rung Orthopair Fuzzy Soft Sets (q-ROFSs) are used to rank investment alternatives. Calculations were also made with Intuitionistic Fuzzy Sets (IFSs) and Pythagorean Fuzzy Sets (PFSs). For analysis, five evaluation criteria were selected based on the literature: frequency of maintenance, ease of installation, environmental adaptation, transmission technologies, and efficiency of cost. Similarly, six alternatives for microgeneration technology investments were selected: ground source heat pumps, micro hydroelectric power, micro combined heat and power, micro bioelectrochemical fuel cell systems, small-scale wind turbines, and photovoltaic systems. The results showed that cost efficiency was the most significant factor in the effectiveness of microgeneration energy investments, and the photovoltaic system was the best alternative to increase microgeneration energy technology investment performance. Furthermore, the results were the same for the analyses made with IFSs and PFSs, demonstrating the reliability of the proposed method. Therefore, investors in microgeneration technologies should prioritize photovoltaic systems. This conclusion is supported by the fact that photovoltaic is a renewable energy source that has witnessed the most technological improvements and cost reductions over the last decade.