Science, Technology and Innovation Policy Indicators and Comparisons of Countries through a Hybrid Model of Data Mining and MCDM Methods

Abstract

Science, technology and innovation (STI) policies are of great importance for countries to reach their sustainable development goals. Numerous global databases have many indicators that measure and compare the performance of STI policies of countries. However, many problems arise regarding how to identify, classify and systematically analyze these indicators in order to measure, monitor and improve the performance of STI. The study includes a literature review on global problems and new trends in STI policies, while mentioning the necessity of an internationally comparable STI indicator set, current STI indicator studies and efforts, and studies for each continent. In light of these, all the indicators selected are introduced in detail. The strengths and weaknesses of the countries in the study in terms of evaluation indicator values are indicated. After determining the indicator weights objectively with the entropy method, 40 countries are compared with TOPSIS, VIKOR, PROMETHEE I-II, ARAS, COPRAS, MULTIMOORA, ELECTRE, SAW and MAUT methods. In addition, countries that show similarities with each other are evaluated by cluster analysis, which is one of the data mining classification methods. This study offers a new and original approach with MCDM methods on this subject. Considering all the results obtained in the study together, these rankings are compared among themselves and with the rankings specified in the Global Innovation (2019) and Global Competitiveness (2019) indices, and it is seen that the results are consistent. In addition, it is possible to update and publish this study every year with updated data.

Comparison between Multi-Criteria Decision-Making Methods and Evaluating the Quality of Life at Different Spatial Levels

“…Linear normalized of decision matrix values based on Equations ( 23) and (24). If the index has a positive aspect, Equation ( 22) is used, and if the index has a negative aspect, Equation ( 23) is used [28].…”

“…where S i is the final weight of each factor, w j is the weight of each criterion, and normalized r ij of each variable of each criterion. The higher the S i than the other criterion, the simpler the weight of that criterion is selected [28].…”

“…In this step, the weight normalized matrix (V) is obtained using the vector w and Equation ( 27) [28].…”

“…In this step, the concordance matrix, which is a square matrix m×m and its diameter has no element, is calculated. Moreover, the elements of this matrix are obtained from the sum of the weights of the criterions belonging to the concordance set (Equation ( 32)) [28].…”

“…The results of this study showed that the use of the TOPSIS method could improve the decision-making process. Ozkaya et al [28] used TOPSIS, VIKOR, PROMETHEE I-II, ARAS, COPRAS, MULTIMOORA, ELECTRE, and SAW methods to compare and rank 40 countries in terms of science, technology and innovation indicators. Sałabun et al [29] examined the methods of TOPSIS, VIKOR, COPRAS, and PROMETHEE II and tested 4 selected methods for multi-criteria analysis.…”