Türkiye’de Yatırım Teşviklerinin Bölgesel Gelişmişlik Farklarını Azaltma Konusunda Etkinliği

Yıl 2024, Cilt: 32 Sayı: 59, 129 - 150, 31.01.2024

Sinan Dündar , Gülay Demir , İlkay Noyan Yalman , Şerife Merve Koşaroğlu , Selçuk Yasin Yıldız

https://doi.org/10.17233/sosyoekonomi.2024.01.06

Öz

Bu çalışmada, Türkiye’de uygulanan yatırım teşvik sisteminin bölgesel gelişmişlik farklarını azaltmada ne ölçüde etkili olduğunun tespit edilmesi amaçlanmaktadır. Bu doğrultuda, 2001-2022 yılları arasında verilen 100.000’den fazla yatırım teşvik belgesi incelenmiştir. Kriterlerin önem düzeyinin belirlenmesi ve illerin yatırım performanslarının sıralanması amacıyla Logarithm Methodology of Additive Weights (LMAW) yönteminden yararlanılmıştır. Elde edilen sonuçlar, yatırım teşvik uygulamalarının bölgesel gelişmişlik farklarını azaltma noktasında yeterli etkinlik sağlayamadığını göstermektedir. Bu açıdan, halihazırda uygulanan teşvik politikalarında ciddi bir revizyon gereksinimi olduğu görülmektedir.

Anahtar Kelimeler

Yatırım, Kalkınma, Teşvik, ÇKKV, LMAW

Destekleyen Kurum

TÜRKİYE BİLİMSEL VE TEKNOLOJİK ARAŞTIRMA KURUMU (TÜBİTAK)

Proje Numarası

222K168

Efficiency of Investment Incentives in Reducing Regional Development Disparities in Türkiye

Öz

This study aims to determine to what extent the investment incentive system implemented in Türkiye 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.

Anahtar Kelimeler

Incentive, Development, Investment, MCDM, LMAW

Proje Numarası

222K168

Kaynakça

• Asadi, M. et al. (2023), “The appropriation of blockchain implementation in the supply chain of SMEs based on fuzzy LMAW”, Engineering Applications of Artificial Intelligence, 123, 106169.
• Božanić, D. et al. (2021), “Modeling of Neuro-Fuzzy System as a Support in Decision-Making Processes”, Reports in Mechanical Engineering, 2(1), 222-234.
• Božanić, D. et al. (2022), “Modification of the Logarithm Methodology of Additive Weights (LMAW) by a Triangular Fuzzy Number and Its Application in Multi-Criteria Decision Making”, Axioms, 11(3), 89.
• Candan, G.T. & V. Yurdadoğ (2017), “Incentive Policies as Fiscal Policy Instruments in Turkey”, Pamukkale University Journal of Social Sciences Institute, 27, 154-177.
• Demir, G. (2022), “Analysis of the Financial Performance of the Deposit Banking Sector in The COVID-19 Period with LMAW-DNMA Methods”, International Journal of Insurance and Finance, 2(2), 17-36.
• Dündar, S. (2019), “Yatırımlarda Devlet Yardımları ve Sivas Yansımaları”, in: İ. Noyan-Yalman (ed.), Sivas Ekonomisi-Geçmişi, Bugünü, Geleceği (349-368), Sivas Vilayet Kitaplığı.
• Dündar, S. (2023), “Performance Analysis of Regional Development Agencies by LMAW-DNMA Methods”, Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 18(2), 354-380.
• Erdoğan, E. & R. Ataklı (2012), “Investment Incentives and FDI in Turkey: The Incentives Package after the 2008 Global Crisis”, Procedia - Social and Behavioral Sciences, 58, 1183-1192.
• Ghorabaee, M.K. et al. (2015), “Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS)”, Informatica, 26(3), 435-451.
• Gigović, L. et al. (2016), “The Combination of Expert Judgment and GIS-MAIRCA Analysis for the Selection of Sites for Ammunition Depots”, Sustainability, 8(4), 372.
• Görçün, Ö.F. & H. Küçükönder (2022), “Evaluation of The Transitions Potential to Cyber-Physical Production System of Heavy Industries in Turkey with A Novel Decision-Making Approach Based On Bonferroni Function”, Verimlilik Dergisi, (Dijital Dönüşüm ve Verimlilik Özel Sayısı), 1-16.
• Hafezalkotob, A. & A. Hafezalkotob (2015), “Comprehensive MULTIMOORA method with target-based attributes and integrated significant coefficients for materials selection in biomedical applications”, Materials & Design, 87, 949-959.
• Hazman, G.G. & P.B. Kaya (2018), “Bölgesel Teşvik Uygulamaları ile İhracat İlişkisinin Afyonkarahisar İli Örneğinde Regresyon Analizi ile Değerlendirilmesi”, Avrasya Sosyal ve Ekonomi Araştırmaları Dergisi, 5(5), 42-57.
• Keeney, R.L. et al. (1979), “Decisions with Multiple Objectives: Preferences and Value Trade-Offs”, IEEE Transactions on Systems, Man, and Cybernetics, 9(7), 403.
• Liao, H. & X. Wu (2020), “DNMA: A Double Normalization-Based Multiple Aggregation Method for Multi-Expert Multi-Criteria Decision Making”, Omega, 94(3), 102058.
• Lukic, R. (2023), “Measurement and Analysis of The Information Performance of Companies in The European Union and Serbia Based on The Fuzzy LMAW and MARCOS Methods”, Informatica Economică, 27(1), 17-31.
• Pamucar, D. & G. Ćirović (2015), “The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC)”, Expert Systems with Applications, 42(6), 3016-3028.
• Pamucar, D. et al. (2021), “A New Logarithm Methodology of Additive Weights (LMAW) for Multi-Criteria Decision-Making: Application in Logistics”, Facta Universitatis Series Mechanical Engineering, 19(3), 361-380.
• Puška, A. et al. (2022a), “Green Supplier Selection in an Uncertain Environment in Agriculture Using a Hybrid MCDM Model: Z-Numbers-Fuzzy LMAW-Fuzzy CRADIS Model”, Axioms, 11(9), 427.
• Puška, A. et al. (2022b), “Evaluation and Selection of Healthcare Waste Incinerators Using Extended Sustainability Criteria and Multi-Criteria Analysis Methods”, Environment, Development and Sustainability, 24(9), 11195-11225.
• Şahin, M.Y. & H. Kaplan (2021), Dönüşüm Sürecinde Yatırım Teşviklerinin Dünü ve Bugünü, Ankara, Türkiye: TOBB Yayınları.
• Seli̇m, S. et al. (2014), “Effect on Employment of the Investment Incentives and Fixed Investments in Turkey: Panel Data Analysis”, Ege Academic Review, 14(4), 661-674.
• Sıcakyüz, Ç. (2023), “Analyzing Healthcare and Wellness Products’ Quality Embedded in Online Customer Reviews: Assessment with a Hybrid Fuzzy LMAW and Fermatean Fuzzy WASPAS Method”, Sustainability, 15(4), 3428.
• Subotić, M. et al. (2021), “Development of a New Risk Assessment Methodology for Light Goods Vehicles on Two-Lane Road Sections”, Symmetry, 13(7), 1271.
• Sungur, O. (2019), “Spatial Distribution of Investment Incentives and the Impact of New Incentive System for Less Developed Regions in Turkey”, Review of Economic Perspectives, 19, 25-48.
• Tešić, D. et al. (2023), “Development of the MCDM Fuzzy LMAW - Grey MARCOS Model for Selection of a Dump Truck”, Reports in Mechanical Engineering, 4(1), 1-17.
• Yanıkkaya, H. & H. Karaboga (2017), “The Effectiveness of Investment Incentives in the Turkish Manufacturing Industry”, Prague Economic Papers, 26(6), 744-760.
• Yazdani, M. et al. (2018), “A Combined Compromise Solution (CoCoSo) Method for Multi-Criteria Decision-Making Problems”, Management Decision, 57(9), 2501-2519.
• Zavadskas, E.K. & Z. Turskis (2010), “A New Additive Ratio Assessment (ARAS) Method in Multicriteria Decision‐Making”, Technological and Economic Development of Economy, 16(2), 159-172.
• Žižović, M. et al. (2020), “Eliminating Rank Reversal Problem Using a New Multi-Attribute Model - The RAFSI Method”, Mathematics, 8(6), 1015.