Yazar "Gunduz, Selim" seçeneğine göre listele

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    A Moral Mapping for Corporate Responsibility: Introducing the Local Dimension-Corporate Local Responsibility (COLOR)
    (MDPI, 2025) Cetin, Mahmut Berkan; Gunduz, Selim
    Although the accumulated knowledge repository of the Corporate Responsibility (CR) literature continues to expand, organizational- and institutional-level studies dominate the field. This article addresses this gap by introducing a driver-based approach to CR through the moral mapping of CR policies and theory-building case studies in the textile sector. Considering the CR notion's diverse stakeholder involvement and cross-disciplinary nature, process tracing of diverse actors from the Industrial Revolution is conducted. A reconstituted Kantian method is employed to assess the moral responsibility of individual agents. Employing this technique, the study categorizes diverse policies and strategies based on decision-makers and the most probable ethical thought processes, or maxims, at the time of the decision-making. The findings identify gaps in conventional CR practices, giving rise to CSR-washed actions and irresponsible corporate behavior. To tackle these challenges, we introduce the Corporate Local Responsibility (COLOR) model. This model is based on moral mapping by integrating them into its four pillars to minimize the ethical dilemmas of various actors by engaging broader stakeholders and local communities in the decision-making process.
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    A New Unit Distribution Based On The Unbounded Johnson Distribution Rule: The Unit Johnson SU Distribution
    (Univ Punjab, 2020) Gunduz, Selim; Korkmaz, Mustafa C.
    This paper proposes a new probability distribution, which belongs a member of the exponential family, defined on (0,1) unit interval. The new unit model has been defined by relation of a random variable defined on unbounded interval with respect to standard logistic function. Some basic statistical properties of newly defined distribution are derived and studied. The different estimation methods and some inferences for the model parameters have been derived. We assess the performance of the estimators of these estimation methods based on the three different simulation scenarios. The analysis of three real data examples which one is related to the coronavirus data, show better fit of proposed distribution than many known distributions on the unit interval under some comparing criteria.
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    Assessing the dynamic nexus between international trade, foreign direct investment, economic growth, and climate change within the EKC framework
    (SAGE Publications Ltd, 2025) Fumey, Michael Provide; Yeboah, Evans; Bekun, Festus Victor; Gunduz, Selim; Cavdar, Seyma Caliskan
    This study explores the dynamic relationship between trade, foreign direct investment (FDI), population growth, carbon emissions, exchange rates, and economic growth for Ghana from 1990 to 2020 using the annual frequency. The study employs the autoregressive distributed lag (ARDL) model, augmented with variance decomposition, impulse response, and causality tests to estimate both the short-run and long-run effects of the variables. The empirical results shows that FDI and CO2 emissions have a positive long-run impact on economic growth, while exchange rate volatility and trade openness have a negative short-run impact on economic growth. The term for the error correction confirmed the presence of a stable equilibrium in the long run. Furthermore, the results show that the economic growth of Ghana remains associated with a higher environmental pollution, reflecting the first phase of the environmental Kuznets curve (EKC) hypothesis. The growth in population has marginal but persistent impacts from the impulse response models, showing that the population pressure without productivity increases in the short term. Additionally, the model converges at eight to ten periods, a result which shows that the economy adjusts to exogenous shocks, and returns to the long-run equilibrium as time progresses. Policy suggestions also incline towards further promoting green investment channels, environmental regulations, and adjusting trade and FDI policies in order to promote sustainable development.
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    Comparison of Machine Learning Models for Sentiment Analysis of Big Turkish Web-Based Data
    (MDPI, 2025) Ozmen, Cemile Gokce; Gunduz, Selim
    E-commerce sites have generated large amounts of unstructured data as they allow millions of users to generate product reviews. Thus, although there have been significant improvements in the characteristics of big data, such as speed and volume, developing various analysis techniques to monitor, understand, and extract useful information from this web-based data has become challenging. This study aims to analyze cosmetic products on a Turkish-based e-commerce website with sentiment analysis and to create a new domain-specific Turkish sentiment dictionary model with manual labeling. In the study, a Turkish sentiment dictionary consisting of 65,378 words was created by manually labeling 875,455 product reviews for 24 cosmetic brands sold on the Turkey-based trendyol e-commerce site, and sentiment analysis was performed using this dictionary. The dataset, divided into seven product groups, was analyzed using K-NN, SVM, DT, RF, and LR algorithms to address three classification problems. The algorithms were evaluated with comparative analysis using accuracy, precision, recall, and f-1 score metrics. SVM gave the highest performance result with over 93% accuracy, 92% precision, 93% recall, and a 91% f-1 score in all product groups. The dictionary model created for the cosmetics industry in the study helps businesses and researchers to use their resources more efficiently and save time by performing fast and low-cost analyses on large datasets of product reviews. Moreover, by analyzing customer feedback, brands can offer long-lasting and environmentally friendly products that align with customers' feelings. Thus, businesses have the opportunity to develop or improve products.
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    Determination of Wind Potential by Two Components Mixture Probability Distribution Models in the Ankara, Turkey
    (Int Journal Renewable Energy Research, 2020) Servi, Tayfun; Gunduz, Selim; Erisoglu, Ulku; Yalcin, Levent
    In this study, hourly average wind speed data in the Ankara, Turkey are modeled with Weibull, Gamma and Rayleigh probability distribution and theirs two component mixture probability distributions. Expectation-Maximization (EM) algorithm is introduced for Maximum Likelihood Estimation (MLE) of mixture probability distributions used in modeling wind speed data. In comparing the modeling performances of probability distributions, the Akaike information criteria, the coefficient of determination, the root of the mean squares and chi-square criteria were used as comparison criteria. Also, in this study, the success in estimation of wind potential was evaluated with relative error. In the study results, it was observed that the mixture distribution models obtained from two different distributions were more successful in modeling wind speed data. The results obtained from the study revealed that the wind potential of Kecioren/Baglum region is higher than Cankaya/Caldag region. According to the wind speed data observed in Kecioren/Baglum and Cankaya/Caldag regions, wind power densities per unit area were calculated as 153.926 W/m(2), and 62.785 W/m(2), respectively.
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    Satisfaction Levels of Cooperative Partners in The New World Order: Case of Cukobirlik
    (Kahramanmaras Sutcu Imam Univ Rektorlugu, 2021) Haseki, Murat Ismet; Gunduz, Selim; Dolekoglu, Celile Ozcicek
    The continuity of the organizations is directly proportional to the satisfaction of the service recipients. The presence of many partners, beneficiaries and employees in cooperatives requires high cooperation. Therefore, it is important to reveal the service quality of the cooperatives and to determine the expectations of the partners. This study was carried out in Cukobirlik, which ranks third in Turkey cooperatives and first among the agricultural cooperatives in terms of number of partners, with the aim of determining the partners' service satisfaction, their perception related to cooperative activities and their intentions for diversification of these activities. 831 surveys were applied. 94.8% of the participants in the study are men and the agricultural production experience of 76.4% of them is over 21 years. It was seen that the satisfaction level of the partners from Cukobirlik's services is high in all dimensions, and the dimensions of assurance, competency and enthusiasm came to the fore compared to other dimensions. With the global pandemic of Covid-19, it has once again manifested itself that agricultural production is an activity that is the first and most affected by all extraordinary situations and affects all humanity with its results. The collective production model is a guarantee of sustainability.