Zaim, Selim

Profil fotoğrafı
 E-posta Adresi
selim.zaim@ihu.edu.tr
ORCID Profili
0000-0003-3540-2264
WoS Profili
ABI-8229-2020
Scopus Profili
7004187773
YÖK Araştırmacı Profili
424F081C46C35BAA
Google Akademik Profili
0_S5vswAAAAJ&hl=tr
TR-Dizin Profili
596306
SOBÄ°AD Profili
9095
Web Sitesi
akademik.ihu.edu.tr/tr/selim-zaim

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

Selim Zaim

İlgi Alanları

Multivariate Data Analysis, Data Analytics, Supply Chain Management, Operations Management

Kurumdaki Durumu

Aktif Personel

Filtreler

20192
Filtreleri Sıfırla

Ayarlar

Yazar: Zaim, Selim × Erişim Hakkı: info:eu-repo/semantics/embargoedAccess ×

Arama Sonuçları

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    Yayın
    Using machine learning tools for forecasting natural gas consumption in the province of Istanbul
    (Elsevier, 2019) Beyca, Ömer Faruk; Ervural, Beyzanur Çayır; Tatoğlu, Ekrem; Özuyar, Pınar Gökçin; Zaim, Selim; Tatoğlu, Ekrem; Zaim, Selim; Yönetim Bilimleri Fakültesi, İşletme Bölümü
    Commensurate with unprecedented increases in energy demand, awell-constructed forecastingmodel is vital to managing energy policies effectively by providing energy diversity and energy requirements that adapt to the dynamic structure of the country. In this study, we employ three alternative popular machine learning tools for rigorous projection of natural gas consumption in the province of Istanbul, Turkey's largest natural gas-consuming mega-city. These tools include multiple linear regression (MLR), an artificial neural network approach (ANN) and support vector regression (SVR). The results indicate that the SVR is much superior to ANN technique, providing more reliable and accurate results in terms of lower prediction errors for time series forecasting of natural gas consumption. This study could well serve a useful benchmarking study for many emerging countries due to the data structure, consumption frequency, and consumption behavior of consumers in various time-periods.
  • Küçük Resim
    Yayın
    Information system capabilities and firm performance: Opening the black box through decision-making performance and business-process performance
    (Elsevier, 2019) Aydıner, Arafat Salih; Tatoğlu, Ekrem; Bayraktar, Erkan; Zaim, Selim; Tatoğlu, Ekrem; Zaim, Selim; Yönetim Bilimleri Fakültesi, İşletme Bölümü
    This study contributes to the extant literature on information management by investigating the interrelationships between information systems (IS)-related capabilities and their effects on firm performance. Using the resource-based view (RBV), a set of hypotheses is formulated to examine these links, considering the role that may be played by decision-making performance and business-process performance as mediating variables. Structural equation modeling (SEM) has been applied to a sample of 204 firms in Turkey. The test results obtained confirm the proposed serially mediating model according to which decision-making performance and business-process performance play a critical mediating role in the human resource and administrative-related IS capabilities, and firm-performance relationships. No support, however, has been found concerning the serial mediation effect between infrastructure-related IS capabilities and firm performance.