№2, 2025

MCDM APPROACH FOR PERFORMANCE EVALUATION OF THE RESEARCH INSTITUTIONS

Rasim Alguliyev, Ramiz Aliguliyev, Narmin Adigozalova

Evaluation of research institutions activities is one of the significant fields of scientometrics. We should note that in the previous approaches, the assessment of scientific institutions have been carried out mainly according to their scientific-theoretical activity. It is obvious that the activity of research institutions is not limited only to scientific-theoretical activity, their activity is multifarious. For this purpose, the paper first defines the system of criteria characterizing the activity of research institutions and then evaluates their activity based on these criteria. It is known that the importance degree of the criteria plays key role in multi-criteria evaluation. Thus, a new approach based on the "worst case" and "best case" methods was proposed for the calculation of criteria weights. VIKOR and TOPSIS methods were used for multi-criteria assessment of alternatives. The results of the experiments conducted in the study showed that the proposed approach demonstrates a stable result compared to others (pp.23-44).

Keywords: Multi-criteria evaluation of research institutions, "Worst case" method, "Best case" method, "Best-worst case" method, VIKOR, TOPSIS.
References
  • Alguliyev, R. M., Aliguliyev, R. M., & Mahmudova, R. S. (2015). Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method. The Scientific World Journal, 2015, 612767. https://doi.org/10.1155/2015/612767
  • Aliguliyev, R. M. (2009). Performance evaluation of density-based clustering methods. Information Sciences, 179(20), 3583-3602. https://doi.org/10.1016/j.ins.2009.06.012
  • Chang, T. (2014). Fuzzy VIKOR method: A case study of the hospital service evaluation in Taiwan. Information Sciences, 271, 196-212. https://doi.org/10.1016/j.ins.2014.02.118
  • Chang, Y., Yeh, C., & Chang, Y. (2013). A new method selection approach for fuzzy group multicriteria decision making. Applied Soft Computing, 13(4), 2179-2187. https://doi.org/10.1016/j.asoc.2012.12.009
  • Dursun, M., & Karsak, E. E. (2010). A fuzzy MCDM approach for personnel selection. Expert Systems with Applications, 37(6), 4324-4330. https://doi.org/10.1016/j.eswa.2009.11.067
  • Geisler, E. (1994). Key Output indicators in performance evaluation of research and development organizations. Technological Forecasting and Social Change, 47(2), 189-203. https://doi.org/10.1016/0040-1625(94)90028-0
  • Hu, S., Lu, M., & Tzeng, G. (2014). Exploring smart phone improvements based on a hybrid MCDM model. Expert Systems W ith Applications, 41(9), 4401-4413. https://doi.org/10.1016/j.eswa.2013.12.052
  • Hwang, C.L. & Yoon, K. (1981). Methods for multiple attribute decision making. In: Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems, vol. 186. Springer, Berlin. https://doi.org/10.1007/978-3-642-48318-9_3
  • Iyer, N.R. & Vijayalakshmi, S. (2014). Analytical framework for performance evaluation of research organizations. Research Journal of Applied Sciences, Engineering and Technology 7(15): 3134-3144. https://doi.org/10.19026/rjaset.7.652
  • Lee C.C. (1990). Fuzzy logic in control systems: fuzzy logic controller, Parts I and II. IEEE Transactions on Systems, Man, and Cybernetics, 20(2), 404–435.
  • Lin, H. (2010). Personnel selection using analytic network process and fuzzy data envelopment analysis approaches. Computers & Industrial Engineering, 59(4), 937-944. https://doi.org/10.1016/j.cie.2010.09.004
  • Opricovic, S. (2007). A fuzzy compromise solution for multicriteria problems. International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, 15(3), 363–380. https://doi.org/10.1142/S0218488507004728
  • Opricovic, S. (2011). Fuzzy VIKOR with an application to water resources planning. Expert Systems With Applications, 38(10), 12983-12990. https://doi.org/10.1016/j.eswa.2011.04.097
  • Patil, S. K., & Kant, R. (2014). A fuzzy AHP-TOPSIS framework for ranking the solutions of Knowledge Management adoption in Supply Chain to overcome its barriers. Expert Systems With Applications, 41(2), 679-693. https://doi.org/10.1016/j.eswa.2013.07.093
  • Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57. https://doi.org/10.1016/j.omega.2014.11.009
  • Robertson, I. T., & Smith, M. (2001). Personnel selection. Journal of Occupational and Organizational Psychology, 74(4), 441-472. https://doi.org/10.1348/096317901167479
  • Rostamzadeh, R., Govindan, K., Esmaeili, A., & Sabaghi, M. (2015). Application of fuzzy VIKOR for evaluation of green supply chain management practices. Ecological Indicators, 49, 188-203. https://doi.org/10.1016/j.ecolind.2014.09.045
  • Saaty, T. L. (2008). Decision Making with the Analytic Hierarchy Process. International Journal of Services Sciences, l(1), 83-98. https://doi.org/10.1504/IJSSCI.2008.017590
  • Sanaliyeva, L. K., Goncharenko, L. P., Rakhimova, S. A., Titkov, A. A., & Kunyazova, S. K. (2021). Strategic priorities for the development of intellectual potential of developing countries in the context of constructing an innovative economy. Public policy and administration, 20(3), 474-483. https://doi.org/10.5755/j01.ppaa.20.3.28350
  • Stukalova, I. B., Stukalova, A. A., & Selyanskaya, G. N. (2016). Assessment of effectiveness of use of intellectual potential of a university: a methodological approach. International Journal of Environmental & Science Education, 11(15), 7961-7974.
  • Sugeno, M. (1985). An introductory survey of fuzzy control. Information Sciences, 36(1-2), 59-83. https://doi.org/10.1016/0020-0255(85)90026-X
  • Varmazyar, M., Dehghanbaghi, M., & Afkhami, M. (2016). A novel hybrid MCDM model for performance evaluation of research and technology organizations based on BSC approach. Evaluation and Program Planning, 58, 125-140. https://doi.org/10.1016/j.evalprogplan.2016.06.005
  • Wan, S., Wang, Q., & Dong, J. (2013). The extended VIKOR method for multi-attribute group decision making with triangular intuitionistic fuzzy numbers. Knowledge-Based Systems, 52, 65-77. https://doi.org/10.1016/j.knosys.2013.06.019
  • Yücenur, G. N., & Demirel, N. Ç. (2012). Group decision making process for insurance company selection problem with extended VIKOR method under fuzzy environment. Expert Systems with Applications, 39(3), 3702-3707. https://doi.org/10.1016/j.eswa.2011.09.065
  • Zong, F., & Wang, L. Evaluation of university scientific research ability based on the output of sci-tech papers: A D-AHP approach. PLOS ONE, 12(2), e0171437. https://doi.org/10.1371/journal.pone.01714