Savunma Sanayi Ar-Ge Merkezlerinin Performanslarının Bütünleşik Entropi-ARAS Yöntemi ile Değerlendirilmesi

Çalışmanın amacı, Türkiye Savunma Sanayinde faaliyet gösteren Ar-Ge merkezlerinin performanslarının çok kriterli karar verme yöntemleri ile değerlendirilmesidir. Bu doğrultuda 7 farklı firmaya ait 12 Ar-Ge merkezinin verileri ile gerçekleştirilen çalışmada öncelikle literatür araştırması ve uzman görüşleri doğrultusunda Ar-Ge merkezlerinin performansını etkileyen kriterler belirlenmiştir. Ardından Entropi yöntemi kullanılarak bu kriterlerin ağırlık değerleri tespit edilmiştir. Son olarak ARAS yöntemiyle çalışma kapsamında ele alınan alternatifler sıralanmıştır. Elde edilen bulgulara göre, en yüksek ağırlığa sahip olan kriter Ar-Ge gelirleri en düşük ağırlığa sahip olan kriter ise Ar-Ge harcamalarıdır.

Evaluation of the Performance of Defense Industry R & D Centers by Integrated Entropy - ARAS Methods

The aim of this study is to evaluate the performance of R&D centers in defense industry in Turkey by multicriteria decision making techniques. In this sense, 12 R&D centers belonging to seven different companies are included in the evaluation. First of all, the criteria which affect the performances of R&D centers are identified by literature review and expert’s opinion. After, Entropy method is used to determine the weights of the criteria and ARAS method is used to sort out the alternatives mentioned in the scope of the study. According to the results of the study, the most important criterion is R&D revenues and the least important criterion is R&D expenses

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  • Araştırma, Geliştirme ve Tasarım Faaliyetlerinin Desteklenmesi Hakkında Kanun; (2008), T. C. Resmi Gazete, 26814, (28.02.2008).
  • Araştırma ve Geliştirme Faaliyetlerinin Desteklenmesi Hakkında Kanun ile Bazı Kanun Hükmünde Kararnamelerde Değişiklik Yapılmasına Dair Kanun; (2016), T. C. Resmi Gazete, 29636, (26.02.2016).
  • Başar, S. ve Künü, S. (2012). Savunma Harcamalarının İktisadi Büyümeye Etkisi. Sosyal Bilimler Enstitüsü Dergisi, 10,1-30.
  • Beirgh, R. G., Razzaghpour, A., Bina, S. ve Zaralia, A. (2014). Designing a New Integrated Model for Performance Evaluation of R&D Centers (Case Study: Energy Research Institute). European Online Journal of Natural and Social Sciences, 3(2), 237-249.
  • Blomström, M. ve Kokko, A. (1998). Multinational Corporations and Spillovers. Journal of Economic Surveys, 12(3), 247-277.
  • Chakrabarti, A. K. ve Anyanwu, L. C. (1993). Defense R&D, Technology, and Economic Performance: A Longitudinal Analysis of the US Experience. IEEE Transactions on Engineering Management, 40(2), 136-145.
  • Chen, J., Zhang, Y., Chen, Z. ve Nie, Z. (2015). Improving Assessment of Ground water Sustainability with Analytic Hierarchy Process and Information Entropy Method: A Case Study of the Hohhot Plain, China. Environmental Earth Sciences, 73(5), 2353-2363.
  • Chiesa, V., Frattini, F., Lazzarotti, V. ve Manzini, R. (2009). Performance Measurement in R&D: Exploring the Interplay Between Measurement Objectives, Dimensions of Performance and Contextual Factors. R&D Management, 39(5), 487-519.
  • Cuaresma, J. C. ve Wörz, J. (2005). On Export Composition and Growth. Review of World Economics, 141(1), 33-49.
  • Çakır, S. ve Perçin, S. (2013). AB Ülkeleri’nde Bütünleşik Entropi Ağırlık-Topsis Yöntemiyle Ar-Ge Performansının Ölçülmesi. Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 32(1), 77-95.
  • Dadelo, S., Turskis, Z., Zavadskas, E. K. ve Dadeliene, R. (2012). Multiple Criteria Assessment of Elite Security Personal on the Basis of ARAS and Expert Methods. Economic Computation and Economic Cybernetics Studies and Research, 46(4), 65-88.
  • Deger, S. (1986). Economic Development and Defense Expenditure. Economic Development and Cultural Change, 35(1), 179-196.
  • DPT (2007), Dokuzuncu Kalkınma Planı 2007 Programı, https://sbb.gov.tr/wpcontent/uploads/2018/10/2007.pdf, (Erişim: 23.11.2020)
  • Faini, R.,Annez, P. ve Taylor, L. (1984). Defense Spending, Economic Structure, and Growth: Evidence Among Countries and Over Time. Economic Development and Cultural Change, 32(3), 487-498.
  • Fey, C. F. ve Birkinshaw, J. (2005). External Sources of Knowledge, Governance Model, and R&D Performance. Journal of Management, 31(4), 597-621.
  • Galvin, H. (2003). The Impact of Defense Spending on the Economic Growth of Developing Countries: A Cross-Section Study. Defense and Peace Economics, 14(1), 51-59.
  • Gangopadhyay, D., Roy, S. ve Mitra, J. (2018). Public Sector R&D and Relative Efficiency Measurement of Global Comparators Working on Similar Research Streams. Benchmarking: An International Journal, 25(3), 1059-1084.
  • Geisler, E. (1994). Key Output Indicators in Performance Evaluation of Research and Development Organizations. Technological Forecasting and Social Change, 47(2), 189-203.
  • Goel R. K., Payne J. E., ve Ram R. (2008). R&D Expenditures and US Economic Growth: A Disaggregated Approach. Journal of Policy Modeling, 30(2), 237- 250.
  • Griliches, Z. (1998). Introduction to R&D and Productivity: The Econometric Evidence. In R&D and Productivity: The econometric evidence (pp. 1-14). University of Chicago Press.
  • Hagedoorn, J. (2002). Inter-Firm R&D Partnerships: An Overview of Major Trends and Patterns Since 1960. Research Policy, 31(4), 477-492.
  • Hagedoorn, J. ve Cloodt, M. (2003). Measuring Innovative Performance: Is There An Advantage in Using Multiple Indicators? Research Policy, 32(8), 1365- 1379.
  • Hartley, K. (2014). The Political Economy of Aerospace Industries: A Key driver of Growth and International Competitiveness? Edward Elgar Publishing. Kerssens-Van Drongelen, I. C. ve Bilderbeek, J. (1999). R&D Performance Measurement: More than Choosing A Set of Metrics. R&D Management, 29(1) 35-46.
  • Kim, B. ve Oh, H. (2002). An Effective R&D Performance Measurement System: Survey of Korean R&D Researchers, Omega, 30(1), 19-31.
  • Li, X., Wang, K., Liu, L., Xin, J., Yang, H. ve Gao, C. (2011). Application of the Entropy Weight and TOPSIS Method in Safety Evaluation of Coal Mines. Procedia Engineering, 26, 2085-2091.
  • Lim, D. (1983). Another Look at Growth and Defense in Less Developed Countries. Economic Development and Cultural Change, 31(2), 377-384.
  • Lee, J. W. ve Hong, K. (2010). Economic Growth in Asia: Determinants and Prospects. Asian Development Bank Economics Working Paper Series, (220), 1-29.
  • Mete, H. ve Dağdeviren, M. (2017). Ar-Ge Merkezleri için Bilgi Yönetimi Modellemesi ve Bilgi Yönetiminin Ar-Ge Performansı ile İlişkisi. Verimlilik Dergisi, (2), 75-108.
  • OECD (2002), Frascati Manual, Proposed Standard Practice for Surveys on Research and Experimental Development, 6. Version, OECD: Paris. OECD (2004), OECD Principles of Corporate Governance http://www.oecd.org/corporate/ca/corporategovernanceprinciples/31557724.pd f Erişim Tarihi: 23.11.2020.
  • Özdağoğlu, A., Yakut, E. ve Bahar, S. (2017). Performance Evaluation of Turkish Banking Sector with Data Envelopment Analysis Using Entropic Weights”, İşletme Fakültesi Dergisi, 18(1), 1-28.
  • Peled, D. (2001). Defense R&D and Economic Growth in Israel: A Research Agenda. Samuel Neaman Institute for Advanced Studies in Science and Technology, Israel Institute of Technology, University of Haifa, Israel. Pessoa, A. (2010). R&D and Economic Growth: How Strong is the Link? Economic Letters107, 152- 154.
  • Salimi, N. ve Rezaei, J. (2018). Evaluating Firms’ R&D Performance Using Best Worst Method. Evaluation and Program Planning, 66, 147-155.
  • Sanayi ve Teknoloji Bakanlığı Ar-Ge Hizmetleri Genel Müdürlüğü, https://agtm.sanayi.gov.tr, 23.11., 2020.
  • Shariati, S., Yazdani-Chamzini, A., Salsani, A. ve Tamosaitiene, J. (2014). Proposing A New Model for Waste Dump Site Selection: Case Study of Ayerma Phosphate Mine, Inzinerine Ekonomika-Engineering Economics, 25(4), 410-419.
  • Shemshadi, A., Shirazi, H.,Toreihi, M. ve Tarokh, M. (2011). A Fuzzy VIKOR Method for Supplier Selection Based on Entropy Measure for Objective Weighting, Expert Systems with Applications, 38(10), 12160-12167.
  • Sıkı, N. ve Acartürk, F. (2019). Türkiye’deki İlaç Ar-Ge Merkezlerinin Faaliyetlerinin Patent ve Yenilik Açısından Değerlendirilmesi. Ankara Üniversitesi Eczacılık Fakültesi Dergisi, 43(1), 44-63.
  • Sliogeriene, J., Turskis, Z., ve Streimikiene, D. (2013). Analysis and Choice of Energy Generation Technologies: The Multiple Criteria Assessment on the Case Study of Lithuania. Energy Procedia, 32, 11-20.
  • Szakonyi, R. (1994). Measuring R&D Effectiveness”-I. Research- Technology Management,37(2), 27-32.
  • Tsai, K. H. ve Wang, J. C. (2004). The R&D Performance in Taiwan's Electronics Industry: A Longitudinal Examination, R&D Management, 34(2), 179-189.
  • Tunca, Z. M., Ömürbek, N., Cömert, H. G. ve Aksoy, E. (2016). OPEC Ülkelerinin Performanslarının Çok Kriterli Karar Verme Yöntemlerinden Entropi ve Maut ile Değerlendirilmesi. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 7(14),1-12.
  • Wang, T. C. ve Lee, H. D. (2009). Developing a Fuzzy TOPSIS Approach Based on Subjective Weights and Objective Weights. Expert Systems with Applications, 36(5), 8980-8985.
  • Wang, C. H. (2011). Clarifying the Effects of R&D on Performance: Evidence from the High Technology Industries. Asia Pacific Management Review, 16(1), 51-64.
  • Wu, H.Y., Chen, I. S., Chen, J., K. ve Chien, F. C. (2019). The R&D Efficiency of the Taiwanese Semiconductor Industry. Measurement, 137, 203-213.
  • Yıldız, H. (2005). Türkiye'de Üniversite-Sanayi İlişkileri ve Kobi'ler (Küçük Sanayi) Açısından Önemi. Sosyoloji Konferansları, (31), 207-229.
  • Zavadskas, E. K. ve Turskis, Z. (2010). A New Additive Ratio Assessment (ARAS) Method in Multi Criteria Decision‐Making. Technological and Economic Development of Economy, 16(2), 159-172.