Kamu-Üniversite-Sanayi İşbirliği (KÜSİ) Kapsamnda Bölgesel Etkinlik ve Potansiyel Değerlendirmesi

Üniversitelerde üretilen akademik bilginin sanayide katma de÷ere dönüútürülmesi yoluyla Türkiye’de etkin bir üniversite-sanayi iúbirli÷i modeli oluúturulmasna yönelik bir de÷erlendirme yapmak amacyla yaplan bu çalúmada, istatistiki bölge birimleri snflamasna göre 26 bölge ve 81 il düzeyinde Türkiye’nin üniversite-sanayi iúbirli÷i potansiyeli de÷erlendirilmiútir. Çalúma kapsamnda, illerin/bölgelerin üniversitesanayi iúbirli÷i ba÷lamnda etkin olma durumu, etkin olmayanlarn etkin olmasna yönelik gerçek bir hedef ilin/bölgenin belirlenmesi ve etkinlik sralamas yaplabilmesi adna srasyla veri zarflama analizi, serbest atlabilir zarflama analizi ve süper etkinlik ölçümü metotlarndan yararlanlmútr. Çalúma sonucunda, Türkiye’de üniversite ve sanayi potansiyeli açsndan illerin etkinlikleri de÷erlendirilmiú, kendilerine referans alabilecekleri iller belirlenmiú ve iller potansiyelleri açsndan sralanmútr.

Regional Efficiency and Potential Evaluation withinGovernment-University-Industry Collaboration (GUIC)

The aim of this research is to present a provincial level assessment of Turkey in terms of creating an effective university-industry collaboration that converts academic knowledge produced in universities to added-value in industry. University-industry collaboration potential of 26 regions by using Classification of Statistical Region Units and 81 provinces in Turkey is evaluated. Data Envelopment Analysis, Free Disposal Hull Analysis and Super Efficiency Measurement methods are used in order to measure the efficiency of regions/provinces, identify reference provinces for inefficient regions/provinces and rank the efficient regions/provinces in terms of university-industry collaboration. In the result of the study, the efficiencies of the regions/provinces in Turkey in terms of university and industrial potential are calculated, the region/province references for inefficient region/provinces are determined and regions/provinces are ranked by their university and industry potential.

___

  • Al-Tabbaa, O., Leach, D. ve March, J. (2014), Collaboration between Nonprofit and Business Sectors: A Framework to Guide Strategy Development for Nonprofit Organizations, VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 25, 657:678.
  • Andersen, P. ve Petersen, N.C. (1993), A Procedure for Ranking Efficient Units in Data Envelopment Analysis, Management Science, 39(10), 1261-1264.
  • Coelli, T.J., Rao, D.S., O'DonnelL, C.J. ve Battese, G.E. (2005), An Introduction to Efficiency and Productivity Analysis, Springer; 2nd Edition.
  • De Borger, B., Kerstens, K., Moesen, W. ve Vanneste, J. (1994), A Nonparametric Free Disposal Hull (FDH) Approach to Technical Efficiency: An Illustration of Radial and Graph Efficiency Measures and Some Sensitivity Results, Swiss Journal of Economics and Statistics, 130(4), 647-667.
  • Deprins, D. ve Tulkens, H. (1984), “Measuring Labour Efficiency in Post Offices, the Performance of Public Enterprises: Concepts and Measurement North-Holland, 243-267.
  • Dünya Ekonomik Forumu Küresel Rekabetçilik Endeksi Raporu (2018), https://www.weforum.org/reports/the-global-competitiveness-report2010-2018 (Eriúim Tarihi: 21.03.2019)
  • Etzkowitz, H. (2003), Innovation in Innovation: The Triple Helix of University-Industry-Government Relations, Social Science Information, 42(3), 293-337.
  • Fan, D. ve Tang, X. (2009), Performance Evaluation of Industry-UniversityResearch Cooperative Technological Innovation Based on Fuzzy Integral, School of Management&Economy, Harbin Engineering University, China.
  • Farrell, M.J. (1957), The Measurement of Productive Efficiency, Journal of the Royal Statistical Society, Series A (General), No.3, 120, 253-290.
  • Ivascu, L., Cirjaliu B. ve Draghici A. 2016), Business Model for the University-industry Collaboration in Open Innovation. Procedia Economics and Finance, 39. 674-678.
  • Kaymaz, K. ve Eryi÷it, K.Y. (2011), Determining Factors Hindering University-Industry Collaboration: An Analysis from the Perspective of Academicians in the Context of Entrepreneurial Science Paradigm, International Journal of Social Inquiry, 4, 185-213
  • Mitsuhashi, H. (2002), Uncertainty in Selecting Alliance Partners: The Three Reduction Mechanisms and Alliance Formation Processes, International Journal of Organisational Analysis, 10, 109-133.
  • Othman, R. ve Omar, A.F. (2012), University and Industry Collaboration: Towards a Succesfull and Sustainable Partnership, Social and Behavioral Sciences, 31, 575-579.
  • Perkmann, M., King, Z. ve Pavn, S. (2011), Engaging Excellence? Effects of Facultyquality on University Engagement with Industry, Research Policy 40, 539-552.
  • Rupika, Uddin, A. ve Singh V.K. (2016), Measuring the UniversityIndustry-Government Collaboration in Indian Research Output, Current Science, 110(10), 1904-1909.
  • Seppo, M. ve Lilles, A. (2012), Indicators Measuring University-Industry Cooperation, Estonian Discussions on Economic Policy, 20(1).
  • Ulucan, A. ve Atc K.B. (2010), "Non-parametric Efficiency Analysis in Energy and Environment Issues and a Turkey Application on Energy Efficiency", Journal of the Faculty of Economics and Administrative Sciences, Hacettepe University, 28, 173-203.
  • Ulucan, A. (2011), Measuring the Effficiency of Turkish Universities Using Measure-Specific Data Envelopment Analysis. Sosyo Ekonomi, 181-196.
  • Vielba, I.R., Esquinas, M.F. ve Monteros, E.E. (2010), Measuring University-øndustry Collaboration in a Regional ønnovation System, Scientometrics, 84, 649-667.
  • Zhu, J. (2000), “Multi-factor Performance Measure Model with an Application to Fortune 500 Companies”, European Journal of Operational Research, 123, 105-124.
  • Zhu, J. (2014), Quantitative Models for Performance Evaluation and Benchmarking, Springer; Third Edition.