Dursun Delen

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.

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Dursun Delen

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

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Listeleniyor 1 - 10 / 20

Developing a hybrid analytics approach to measure the efficiency of deposit banks
(Elsevier, 2019) Dinçer, Hasan; Hacıoğlu, Ümit; Tatoğlu, Ekrem; Delen, Dursun; Yönetim Bilimleri Fakültesi, İşletme Bölümü
This study aims at analyzing the efficiency of deposit banks using contemporary analytics-based decision-making techniques within a fuzzy environment. Specifically, a hybrid analytic model drawing on a fuzzy analytical network process and data envelopment analysis was developed and applied to the assessment of Turkish deposit banks quoted on Borsa Istanbul. The findings revealed that; (i) the efficiency results for banking activity vary for competitiveness and for the adoption of new technologies before and after the financial recession; (ii) the majority of deposit banks operating primarily with non-interest based factors found to be less-efficient; (iii) the ownership and capital structure of banks do not significantly contribute to their banking performance, as they were technically inefficient during the same period; and (iv) the inputs of the banking activities could be reduced while a constant level of output is maintained by adopting and properly using the most efficient technology to boost the technical efficiency.
A critical analysis of COVID-19 research literature: Text mining approach
(Elsevier, 2021) Delen, Dursun; Delen, Dursun; Delen, Dursun; Zengul, Ferhat D.; Zengul, Ayşe G.; Mugavero, Michael J.; Oner, Nurettin; Özaydın, Bünyamin; Delen, Dursun; Willig, James H.; Kennedy, Kierstin C.; Cimino, James; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
Objective: Among the stakeholders of COVID-19 research, clinicians particularly experience difficulty keeping up with the deluge of SARS-CoV-2 literature while performing their much needed clinical duties. By revealing major topics, this study proposes a text-mining approach as an alternative to navigating large volumes of COVID-19 literature. Materials and methods: We obtained 85,268 references from the NIH COVID-19 Portfolio as of November 21. After the exclusion based on inadequate abstracts, 65,262 articles remained in the final corpus. We utilized natural language processing to curate and generate the term list. We applied topic modeling analyses and multiple correspondence analyses to reveal the major topics and the associations among topics, journal countries, and publication sources. Results: In our text mining analyses of NIH’s COVID-19 Portfolio, we discovered two sets of eleven major research topics by analyzing abstracts and titles of the articles separately. The eleven major areas of COVID-19 research based on abstracts included the following topics: 1) Public Health, 2) Patient Care & Outcomes, 3) Epidemiologic Modeling, 4) Diagnosis and Complications, 5) Mechanism of Disease, 6) Health System Response, 7) Pandemic Control, 8) Protection/Prevention, 9) Mental/Behavioral Health, 10) Detection/Testing, 11) Treatment Options. Further analyses revealed that five (2,3,4,5, and 9) of the eleven abstract-based topics showed a significant correlation (ranked from moderate to weak) with title-based topics. Conclusion: By offering up the more dynamic, scalable, and responsive categorization of published literature, our study provides valuable insights to the stakeholders of COVID-19 research, particularly clinicians.
Business analytics adoption and technological intensity: An efficiency analysis
(Springer, 2023) Tatoğlu, Ekrem; Delen, Dursun; Tatoğlu, Ekrem; Delen, Dursun; Bayraktar, Erkan; Tatoğlu, Ekrem; Aydıner, Arafat Salih; Delen, Dursun; Yönetim Bilimleri Fakültesi, İşletme Bölümü; 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.
An explanatory analytics framework for early detection of chronic risk factors in pandemics
(Elsevier, 2022) Delen, Dursun; Delen, Dursun; Davazdahemami, Behrooz; Zolbanin, Hamed M.; Delen, Dursun; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
Timely decision-making in national and global health emergencies such as pandemics is critically important from various aspects. Especially, early identification of risk factors of contagious viral diseases can lead to efficient management of limited healthcare resources and saving lives by prioritizing at-risk patients. In this study, we propose a hybrid artificial intelligence (AI) framework to identify major chronic risk factors of novel, contagious diseases as early as possible at the time of pandemics. The proposed framework combines evolutionary search algorithms with machine learning and the novel explanatory AI (XAI) methods to detect the most critical risk factors, use them to predict patients at high risk of mortality, and analyze the risk factors at the individual level for each high-risk patient. The proposed framework was validated using data from a repository of electronic health records of early COVID-19 patients in the US. A chronological analysis of the chronic risk factors identified using our proposed approach revealed that those factors could have been identified months before they were determined by clinical studies and/or announced by the United States health officials.
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.
An analytic approach to assessing organizational citizenship behavior
(Elsevier, 2017) Tatoğlu, Ekrem; Zaim, Selim; Delen, Dursun; Tatoğlu, Ekrem; Zaim, Selim; Delen, Dursun; Arda, Özlem Ayaz; Delen, Dursun; Tatoğlu, Ekrem; Zaim, Selim; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
This study examines the organizational citizenship behavior (OCB) of employees by designing and developing an analytic network process (ANP) methodology. The viability of the proposed methodology is demonstrated via the sales representatives of Beko, a brand name controlled by Koç Group. We first develop a conceptual framework based on qualitative research methods – in-depth interviews and focus group sessions. We employ the principles of ANP methodology to examine and discover the inter-relationships among the OCBs. This process results in a descriptive model that encapsulates the findings from both qualitative and analytics methods. Necessity, altruism, departmental, compliance, and independence are the underlying dimensions of OCBs found to be the most influential/important. The key novelty of this study resides in designing and developing a prescriptive analytics (i.e. ANP) methodology to evaluate the OCBs, which is rare in the area of organizational behavior (a managerial field of study that have been dominated by traditional statistical methods), and thus serves as a useful contribution/augmentation to the business/managerial research methods, and also extends the reach/coverage of analytics-based decision support systems research and practice into a new direction.
Crafting performance-based cryptocurrency mining strategies using a hybrid analytics approach
(Elsevier, 2021) Chlyeh, Dounia; Hacıoğlu, Ümit; Tatoğlu, Ekrem; Yılmaz, Mustafa Kemal; Delen, Dursun; Yönetim Bilimleri Fakültesi, İşletme Bölümü
Crafting and executing the best cryptocurrency mining strategy is vital to succeeding in cryptocurrency market investments. This study aims to identify the best cryptocurrency mining strategy based on service providers’ performance for cryptocurrency mining using a hybrid analytics approach, which integrates the Analytic Hierarchy Process (AHP) and Fuzzy-TOPSIS techniques, along with sensitivity analysis. The results show that hosted mining is the overall best cryptocurrency mining strategy, followed by home mining and cloud mining, based on both total cost of operations and cryptocurrency payout criteria. The empirical findings also suggest that the critical features of the highest performing service providers (i.e., hosted mining strategies and cloud mining) were their flexibility of contracts and the superior efficiency in terms of the daily payout. Finally, of the three location alternatives for home mining, Turkey ranks first compared to the U.S. and Europe.
Can customer sentiment impact firm value? An integrated text mining approach
(Elsevier, 2022) Delen, Dursun; Delen, Dursun; Eachempati, Prajwal; Srivastava, Praveen Ranjan; Kumar, Ajay; Mu˜noz de Prat, Javier; Delen, Dursun; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
Developing measures to capture customer sentiment and securing a positive customer experience is a strategic necessity to improve firm profitability and shareholder value. The paper considers the relationship between customer satisfaction, earnings, and firm value as these drives change in stock prices, customer, and investor sentiment. The present study investigates the impact of customer sentiment polarity on stock prices based on Indian automobile sector databased such as the Indian Nifty Auto SNE (Maruti Suzuki, Tata Motors, and Eicher). A top-down approach is adopted to construct a financial proxy-based sentiment index completed with sentiment extracted from automobile news and customer reviews. The paper uses a text mining approach to holistically measure customer sentiment’s impact on investor sentiment and stock prices. The study was initially performed at the overall individual stock from the Nifty Auto NSE but focused on the top three passenger vehicle manufacturing companies i.e., Maruti Suzuki, Tata Motors, and Eicher. It was found that the sentiment index was augmented with news and customer reviews allows predicting more accurately NIFTY AUTO stock price movements. This implies that customer sentiment is a major driver of investor sentiment which in turn impacts the stock market and the firm value. Thus, the present study is an integrated approach to holistically measure customer sentiment’s impact on investor sentiment and stock prices.
An integrated approach for lean production using simulation and data envelopment analysis
(Springer, 2021) Zaim, Selim; Delen, Dursun; Zaim, Selim; Delen, Dursun; Buyuksaatci Kiris, Sinem; Eryarsoy, Enes; Zaim, Selim; Delen, Dursun; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
According to the extant literature, improving the leanness of a production system boosts a company’s productivity and competitiveness. However, such an endeavor usually involves managing multiple, potentially conflicting objectives. This study proposes a framework that analyzes lean production methods using simulation and data envelopment analysis (DEA) to accommodate the underlying multi-objective decision-making problem. The proposed framework can help identify the most efficient solution alternative by (i) considering the most common lean production methods for assembly line balancing, such as single minute exchange of dies (SMED) and multi-machine set-up reduction (MMSUR), (ii) creating and simulating various alternative assembly line configuration options via discrete-event simulation modeling, and (iii) formulating and applying DEA to identify the best alternative assembly system configuration for the multi-objective decision making. In this study, we demonstrate the viability and superiority of the proposed framework with an application case on an automotive spare parts production system. The results show that the suggested framework substantially improves the existing system by increasing efficiency while concurrently decreasing work-in-process (WIP).
Development of a sustainable corporate social responsibility index for performance evaluation of the energy industry: A hybrid decision-making methodology
(Elsevier, 2023) Hacıoğlu, Ümit; Yılmaz, Mustafa Kemal; Delen, Dursun; Hacıoğlu, Ümit; Yılmaz, Mustafa Kemal; Delen, Dursun; Dinçer, Hasan; Yüksel, Serhat; Hacıoğlu, Ümit; Yılmaz, Mustafa Kemal; Delen, Dursun; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
The ever-increasing pressure from stakeholders and policymakers on energy companies to achieve Sustainable Development Goals (SDGs) and Corporate Social Responsibility (CSR) mission requires them to reinvent their policies and practices. This study aims to examine the performance of alternative business models for the oil and gas industry by employing a hybrid business analytics methodology under a fuzzy environment resulting in a generalizable model named “Sustainable Development Goals-oriented CSR Index.” The proposed methodology employs a hybrid framework that utilizes bipolar Q-rung Orthopair Fuzzy (q-ROF), Multi Stepwise Weight Assessment Ratio Analysis (M-SWARA), and Elimination and Choice Translating Reality (ELECTRE) methods. The findings show that (i) the proposed model is reliable and consistent throughout the similar fuzzy set value ranges, (ii) clean energy is the most important SDG-oriented CSR Index factor for the sustainable energy industry in emerging economies, (iii) drilling is the best alternative energy sourcing for the oil and gas industry, and (iv) clean energy projects have the highest priority for energy investors. The results also highlight that global warming can be managed with effective energy practices for long-term sustainability. Finally, the findings suggest that energy companies should have the essential technological infrastructure and capable workforce to increase investment efficiency.

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