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    A fuzzy-hybrid analytic model to assess investors' perceptions for industry selection
    (Elsevier Science Bv, 2016) Dinçer, Hasan; Hacıoğlu, Ümit; Tatoğlu, Ekrem; Delen, Dursun
    The 2008-2009 global financial crisis and its subsequent ramifications on capital markets have led to an increasing attention on the importance of cognitive and behavioral issues in finance. The purpose of this study is to determine the ranking of the industry alternatives for portfolio investments based on individual investors' perceptions. Accordingly, a hybrid analytic multi-criteria decision model (MCDM)-based on the Fuzzy Analytic Hierarchy Process (FAHP) and the Fuzzy Technique for the Order of Preference by Similarity to Ideal Solution (HOPS'S) methods along with sensitivity analysis is developed to identify and rank-order the best performing industry options. The proposed model is applied to Borsa Istanbul Stock Exchange 100 Index (BIST 100) in Turkey. The results indicate that (i) the investors' perceptions on market conditions and global financial situation influence their industry selection on company stocks; (ii) the investors' perceptions on portfolio investments rely heavily on performance and risk levels of individual asset/stocks, and (iii) traded stocks of financial industry (along with its sub-industries) have greater performance expectations than those of the ones in other industries such as technology, services and tourism.
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    Balanced scorecard-based analysis of customer expectations for cosmetology services: A hybrid decision modeling approach
    (Taylor and Francis Ltd., 2020) Delen, Dursun; Dorokhov, Oleksandr; Dorokhova, Liudmyla; Dinçer, Hasan; Yüksel, Serhat
    The goal of this study is to analyze and characterize customer expectations in the cosmetics sector. Within this framework, first, the extant literature is reviewed, and 12 most prominent performance measurement criteria are identified. Then, these criteria are organized along the four different balanced scorecard dimensions. By employing an Interval Type-2 Fuzzy DEMATEL methodology, the weighted importance of these dimensions and criteria are identified. Additionally, with the Interval Type-2 Fuzzy TOPSIS approach, 13 leading cosmetic service providers in Ukraine are ranked based on their relative scores. The findings of the study indicate thatconsumeris the most significant dimension whilelearning and growthseem to have the least importance. Similarly, it is also concluded that all consumer-focused criteria (i.e.diversification of services,feedback on the product and services, andcustomer loyalty) have the highest priorities in the complete criterion set.
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    Developing a hybrid analytics approach to measure the efficiency of deposit banks
    (Elsevier, 2019) Dinçer, Hasan; Hacıoğlu, Ümit; Tatoğlu, Ekrem; Delen, Dursun
    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.
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    Development of a sustainable corporate social responsibility index for performance evaluation of the energy industry: A hybrid decision-making methodology
    (Elsevier Ltd, 2023) Dinçer, Hasan; Yüksel, Serhat; Hacıoğlu, Ümit; Yılmaz, Mustafa Kemal; Delen, Dursun
    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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    Optimizing sustainable industry investment selection: A golden cut-enhanced quantum spherical fuzzy decision-making approach
    (Elsevier Ltd, 2023) Hacıoğlu, Ümit; Dinçer, Hasan; Yılmaz, Mustafa Kemal; Yüksel, Serhat; Sonko, Mariama; Delen, Dursun
    This study aims to rank sustainable industry alternatives in emerging markets based on the directional impact relations of the environmental, social, and governance (ESG) index components for a socially and environmentally conscious investment strategy. To achieve this goal, we employ a golden cut-enhanced quantum spherical fuzzy decision-making approach. Specifically, we first use a quantum spherical fuzzy DEMATEL technique to identify the impact-relation directions and the weights of the ESG criteria set. Second, we employ the extended TOPSIS with the quantum spherical fuzzy sets to rank the industry alternatives concerning their directional ESG performances. The findings show that (i) H20 Emissions, Innovation, Community Investment, Gender Equity, Human Rights, and CSR Strategy are the main influencing factors based on their impact-relations directional scores, (ii) Resource Usage, Product Responsibility, and Shareholders’ Rights are the set of criteria under the influence of remaining ESG, (iii) Innovation is the strongest ESG performance criterion, whereas Human Rights is the weakest, (iv) technology and communication are the best-performing industries based on the directional ESG index performance scores, whereas real estate and basic materials industries are the worst performing. The study provides valuable and actionable insights for companies that aim to make socially responsible investments.