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    Efficiency of Investment Incentives in Reducing Regional Development Disparities in Türkiye
    (Sosyoekonomi Soc, 2024) Dundar, Sinan; Demir, Gulay; Noyan-Yalman, Ilkay; Kosaroglu, Serife Merve; Yildiz, Selcuk Yasin
    This study aims to determine to what extent the investment incentive system implemented in Turkiye effectively reduces regional development disparities. For this purpose, more than 100,000 investment incentive certificates issued between 2001-2022 are examined. The Logarithm Methodology of Additive Weights (LMAW) determines the criteria's importance and ranks the provinces' investment performances. The results obtained indicate that investment incentive applications cannot provide sufficient effectiveness in reducing regional development disparities. In this respect, there is a severe need for revision in the incentive policies currently implemented.
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    Empirical Application of The Effectiveness of Investment Incentives in Türkiye From The Perspective of Investors
    (Istanbul Univ, 2024) Erilli, Necati Alp; Kosaroglu, Serife Merve; Yalman, Ilkay Noyan; Dundar, Sinan; Yildiz, Selcuk Yasin
    The effectiveness of investment incentives is expected to reduce the imbalance between regions while ensuring economic growth. The sustainability of investment incentives and their expected impact are related to the rational allocation of resources to be used in this field. Although the incentive system, which has been in place in T & uuml;rkiye for many years, has been updated according to economic requirements and planning, the evaluation of incentives from the perspective of investors has been neglected. The opinions and experiences of investors, who are the most important stakeholders in incentives, on the content and implementation of incentives are important in terms of increasing efficiency. The purpose of this study is to evaluate incentive implementation systems from the perspective of investors to enhance the effectiveness of investment incentives. This study aims to develop policy recommendations in line with the answers given to the survey questions prepared to evaluate the views of investors on the implementation of incentives. According to the results, it was determined that investors could not fully utilise the investment incentive system effectively because of both the investors and the system implemented. As a result, it has been concluded that to increase the effectiveness of investment incentives, the general characteristics of the region, sector, and investor should be taken into account in incentive practises and the SEGE criteria should be revised.
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    Performance Analysis of Regional Development Agencies by LMAW-DNMA Methods
    (Eskisehir Osmangazi Univ, Fac Education, 2023) Dundar, Sinan
    In this study, the performances of 26 Regional Development Agencies (RDAs) operating in Turkiy in terms of financial support for for-profit and non-profit organisations were examined. The weights of 9 criteria were determined with the Logarithm Methodology of Additive Weights (LMAW) method, and the performance order of the Regional Development Agencies was revealed with the Double Normalization-based Multiple Aggregation (DNMA) method. Istanbul Development Agency was determined as the most successful Regional Development Agency in terms of financial support programs for non-profit organisations. However, cukurova Development Agency has shown the most successful performance in terms of the financial support programme for for-profit organisations.
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    Selection of a Facility Location for a Cosmetics Company by Integrated F-LBWA and I-RAWEC Methods
    (Springer Heidelberg, 2025) Dundar, Sinan; Karadag, Ilker
    The first step of a company's achievement in upcoming periods starts with the decision of correct investment location. It is also essential to consider scientific approaches in this context. Within the scope of this fundamental principle, this study aimed to determine the most feasible investment location among 47 African countries for a leading cosmetics company operating in T & uuml;rkiye. The indicators outlined in the World Bank's Doing Business reports are used for the first time in this research within the context of investment location selection studies that employ quantitative decision-making methods. The weighting of 10 main criteria and 44 sub-criteria in the report is performed by Fuzzy Level Based Weight Assessment (F-LBWA) method. The priority ordering of 47 African countries is determined using the Improved-Ranking Alternatives with Weights of Criterion (I-RAWEC) method, which is derived by implementing an improvement to the normalization stage of Ranking Alternatives with Weights of Criterion (RAWEC) approach. Moreover, in order to confirm the validity of the proposed method, a sensitivity analysis is conducted, which examines the impact of a gradual change in criterion weights on the order of the alternatives. The findings of this study present a novel approach to assessing potential investment opportunities in Africa for the cosmetics industry and offer a significant starting point for future investment decisions and research endeavors.
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    Selection of compost plant location by K-Means and ARAS methods in TR83 region
    (Gazi Univ, Fac Engineering Architecture, 2023) Dundar, Sinan
    While productivity in agricultural lands continues to be the subject of discussion, the evaluation of animal wastes that cause negative environmental effects is an inevitable problem of the modern age. However, these wastes, which are generated from thousands of livestock enterprises, can be used for compost production for the rehabilitation of the soil. The environmental effects caused by these wastes will be minimized, the farmers engaged in planting activities will be able to get higher yields and economic returns will be provided in both respects. Depending on these reasons, this study is carried out to utilize the wastes generated from 123,123 livestock breeding enterprises operating in the provinces of Samsun, Tokat, corum and Amasya, for compost production. Geographical coordinates of all livestock enterprises were determined and these enterprises were divided into 18 cluster categories with K-Means clustering method. ARAS method, which is among the multi-criteria decision-making techniques, was used in order to choose the most available one among these cluster alternatives for an entrepreneur who aims to invest in compost production. The optimum number of 18 clusters to be applied for cluster analysis has been determined by Elbow and f(K) Function methods. SWARA method was used for determination of 6 criteria and the weights of these criteria before the optimality ranking of the cluster alternatives. According to the results obtained, it has been determined that the three most suitable locations for compost production from animal wastes in TR83 Region among 18 cluster alternatives are the Suluova district center of Amasya province, central district of Tokat province and Kussaray village of the corum center.