Delen, Dursun

Profil fotoğrafı
 E-posta Adresi
dursun.delen@ihu.edu.tr
ORCID Profili
0000-0001-8857-5148
WoS Profili
AGA-9892-2022
YÖK Araştırmacı Profili
9AB745FF7C9BF2C2
Google Akademik Profili
jGLGJIgAAAAJ
TR-Dizin Profili
687500
SOBİAD Profili
263172

Araştırma projeleri

Organizasyon Birimleri

Organizasyon Birimi Logosu
Organizasyon Birimi
Lisansüstü Eğitim Enstitüsü, İşletme Ana Bilim Dalı
İş dünyasının giderek karmaşıklaşan ve dinamik hale gelen yapısı, farklı disiplinlerden gelen bireylerin aynı örgütsel çatı altında aynı amaçlar doğrultusunda etkin ve verimli çalışmalarını zorunlu hale getirmiştir. Bu sebeple de, işletmenin tüm işlevlerini bütüncül bir bakış açısı ile değerlendirebilecek ve bu hususları faaliyet gösterilen ekosistemin diğer dinamikleri ile uyumlu yönetebilecek bireylere duyulan ihtiyaç artmıştır. Ayrıca, teknoloji alanında yaşanan baş döndürücü gelişmeler rekabetin sahasını genişletmiş ve özellikle üretim, dağıtım, pazarlama ve finans alanlarında entegre bilgi birikimine sahip, yönetsel becerisi yüksek insan kaynağına önemli ölçüde bir talep doğurmuştur.

Adı Soyadı

Dursun Delen

İlgi Alanları

Sağlık Analitiği, Karar Destek Sistemleri, Sağlık Analitiği, İş Zekası, İş Analitiği

Kurumdaki Durumu

Pasif Personel

Filtreler

2019 - 201912020 - 20232
Filtreleri Sıfırla

Ayarlar

Bölüm: İHÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü × Konu: Business Analytics ×

Arama Sonuçları

Listeleniyor 1 - 3 / 3
  • Küçük Resim
    Yayın
    Business analytics adoption and technological intensity: An efficiency analysis
    (Springer, 2023) Tatoğlu, Ekrem; Delen, Dursun; Bayraktar, Erkan; Aydıner, Arafat Salih; Yönetim Bilimleri Fakültesi, İşletme Bölümü
    Despite the overwhelming popularity of business analytics (BA) as an evidence-based decision support mechanism, the impact of its adoption on organizational performance has received scant attention from the research community. This study aims to unfold the adoption efficiencies of BA and its applications by proposing a data envelopment analysis (DEA) methodology to holistically assess the underlying factors with respect to the level of achievement regarding organizational performance, operational performance, and financial performance. Furthermore, the study unveils the firm-level and sectoral-level discrepancies in BA adoption efficiency in different industry settings. Relying on survey data obtained from 204 executives in various industries, this study provides empirical support for the cross-industry differences in BA adoption efficiencies. The results show that the firms in low-tech industries seem to achieve the highest efficiency from adopting BA regarding its influence on firm performance.
  • Küçük Resim
    Yayın
    Business analytics and firm performance: The mediating role of business process performance
    (Elsevier, 2019) Aydıner, Arafat Salih; Tatoğlu, Ekrem; Bayraktar, Erkan; Zaim, Selim; Delen, Dursun; Tatoğlu, Ekrem; Zaim, Selim; Delen, Dursun; Yönetim Bilimleri Fakültesi, İşletme Bölümü
    Due to the rapidly increasing popularity of business analytics (BA), investigation of the antecedents/determinants of the adoption of BA and the subsequent impact of the same to the firm performance has become an important research topic. Drawing on the fundamentals of the resource-based view (RBV), this study proposes a model that examines the effects of the BA adoption on business process performance (BPER) and the mediating role that BPER plays in the relationship between the adoption of BA and firm performance (FP). Based on the data collected from 204 medium- to high-level business executives in various industries, the results of this empirical study indicate that the adoption of BA positively influences BPER. There is also positive relationship between BPER and FP. Finally, the results show that BPER fully mediates the relationship between BA adoption and FP.
  • Küçük Resim
    Yayın
    The use of multi-criteria decision-making methods in business analytics: A comprehensive literature review
    (Elsevier, 2022) Delen, Dursun; Yalçın, Ahmet Selçuk; Kılıç, Hüseyin Selçuk; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
    Business analytics (BA) systems are considered significant investments for enterprises because they have the potential to considerably improve firms’ performance. With the value offered by BA, companies are able to discover the hidden information in the data, improve decision-making processes, and support strategic planning. On the other hand, because there are multiple criteria and multiple alternatives involved in most decision- making situations, multi-criteria decision-making (MCDM) methods play an important role in BA practices. Providing inputs to the components of descriptive or predictive analytics or being used as a decision-making tool for evaluating the alternatives within prescriptive analytics exemplify the roles. Therefore, the use of hidden information discovered by business analytics and the need for utilizing the right MCDM method for optimal decision-making made these two concepts inseparable. In this paper, in order to review the use of MCDM methods in BA, the subject of BA is investigated from a taxonomical perspective (descriptive, predictive, and prescriptive), and its connection with MCDM techniques is revealed. Similarly, MCDM methods are studied using two main categories, multi-attribute decision making (MADM) and multi-objective decision making (MODM) methods. Furthermore, tabular and graphical analyses are also performed within the proposed review meth-odology. To the best of our knowledge, this review is the first attempt that holistically considers the use of MCDM methods in BA.