Investigating the Role of the Components of the Knowledge-Based Economy in Iran Present Situation and the Vision Plan Countries Using Multiple- Group Discriminant Analysis and K-Mean Differentiation Analysis

Document Type : Research Paper


1 Ph.D Candidate in Economy, Faculty of Management and Economic, Islamic Azad University, Kerman Branch, Iran.

2 Assistant prof. In Economy, Faculty of Management and Economic, Islamic Azad University, Kerman Branch, Iran

3 Prof. in Agricultural Economic, Faculty of Shahid Bahonar University, Kerman, Iran.


Objective: One of the long-term goals and strategies of the country for development in the 20-year vision plan is the development of the knowledge-based economy, so that with pursuing this strategy, Iran could become a knowledge-based economy by 1404. The purpose of this research is to explain the economic status of Iran among regional competitors based on the components of knowledge-based economy.
Methods: This study was based on World Bank documentation using clustering methods based on the K-Mean algorithm and Multiple- Group Discriminant Analysis with the aim of calculating the knowledge-based economy index and determining the components and criteria of each country studied between1995and 1995. It should be noted that the under-study countries are clustered into three groups based on 14 variables in the form of four components of knowledge-based economy.
Results: The results of the k-mean method showed that the variables of cell phone users, the quality of regulations, the number of Internet users per thousand ones, the number of telephone lines per thousand ones, and the number of Internet users per thousand ones played the most important role in separating the clusters. For the Multiple- Group Discriminant Analysis method, in the first differentiation function, the variables of the quality of regulation, the number of Internet users per thousand ones, cell phone users, and in the second differentiation function, the variables of tariff and non-tariff barriers, rule of law, the number of telephone lines per thousand ones have the most importance in creating a distinction between different groups of countries.
Conclusion: During 1995-1995, Iran has not seen significant progress in terms of knowledge-based economy index, and in the second group of countries (the average level), it has been considered as a composite index of the knowledge-based economy.


Afzal, M. N. I. (2014). Knowledge-based Economy (KBE): An Investigation of Frameworks and Measurement Techniques in the South East Asian Region. A Ph.D. dissertation, University of Southern Queensland.
APEC (November, 2000). Towards Knowledge Based Economies in APEC. Report by APEC Economic Committee.
APEC Economic Committee (2001). Towards Knowledge Based Economies in APECAPEC Secretariat.
Azimi, N., & Barkhordari, S. (2008). Knowledge-Based Economy in Southeast Asian Countries. Rahyaft, 43, 32-42. (in Persian)
Azizi F, Moradi F. (2018). Calculating the Index and Sub-Indices of Knowledge-Based Economy for Iran, 26 (85), 243-270.
Despotovic, D., Cvetanovic, D., Vladimir, N. (2015). Perspectives for the Development of Knowledge Economy, Innovativeness, and Competitiveness of Cefta Countries. Economics and Organization, 12(3), 209-223.
Dizaji, M., Daneshvar, S., Babaei Anari, A. (2013). Determining Iran's Position among selected countries from the Perspective of Knowledge Based Economy based. Productivity Management, 6(22), 121-144.
Farhadi kia, A., Azvaji, A. (2015). Comparative Comparison of Iran's Economic Performance Compared to the Contries in Vision Regions in the Period (2005-2014) and the Requirements for Improving Its Position in the Residual Economic Areas. Planning and Budget Organization. Report 3-55.
Fucec, A. A., Corina, M. (2014). Knowledge economies in European Union: Romania’s position. Emerging Markets Queries in Finance and Business, 15, 481–489.
Höppner, F., Klawonn, F., Kruse R., Runkler, T. (1999). Fuzzy cluster analysis: Methods for classification, data analysis and image recognition. Journal of the Operational Research Society, 51 (1999) 769-770.
Imadzadeh, M., Shahnazi, R. A. (2007).  The study of the bases and indicators of knowledge-based economy and its position in selected countries compared to Iran. Research Economic, 7(4), 175-143. (in Persian)
Imadzadeh, M., Shahnazi, R. A., & Dehghan Shabani, Z. (2006). The Study of the Realization of the Knowledge-Driven Economy in Iran. Economic Quarterly, 6(2), 103-132. (in Persian)
Kaufmann, L., Rousseeuw, P. J. (1990). Finding groups in data: an introduction to cluster analysis. Wiley Series in Probability and Statistics, John Wiley & Sons, Inc.
Lucas, R. (1988). On the Mechanics of Economic Development. Journal of Monetary Economics, 22, 3-42.
Maddala, G.S. (1983). Limited-dependent and qualitative variables in econometrics. Cambridge University Press.
Mehrara, M., Rezaei, A.A. (2015), “Knowledge Economy Index (KEI) in Iran and Comparison with other Countries of Region: The Vision 1404 Document. International Journal of applied Economic Studies, 3(2), 1-7.
Mohammadi, B., Kamkar Rouhani, A. (2017).  The application of clustering k-mean, fuzzy, and gustaffson methods in combining the results of inversion of refractive-earthquake tomography and electrical resistivity tomography for the assessment of alluvium and bedrock. KharazmiEarth Sciences, 2(3), 183-198. (in Persian)
Monavarian, A., Askari, N and Ashena., M. (2007). The structural and content dimensions of knowledge-based organizations. First National Knowledge Management Conference. Tehtan. (in Persian)
Noori, J., Bonyad Naeini, A & Esmailzadeh, M. (2015). Determining Iran's Position in the Region from the Perspective of Knowledge Based Economy based on Clustring Algoritm. Quarterly Journal of the Macro and Strategic Policies, 4, 133-155. (in Persian)
Paasche, H., Eberle, D. (2011). Automated compilation of pseudo-lithology maps from geophysical data sets: a comparison of Gustafson-Kessel and fuzzy C-means cluster algorithms. Exploration Geophysics, 42(4), 275-285.
Paz-Marin, M., Gutierrez-Pena, P. A., & Martinez, C. (2015). Classification of countries’ progress toward a knowledge economy based on machine learning classification techniques. Expert Systems with Applications,42(1), 562-572.
Romer, P. M. (1990). Human Capital and Growth: Theory and Evidence. Carnegie Rocheser Conference Series on Public Policy, 32, 251-286.
Shaghaghi Shahri, V. (2015). Evaluating the Economic Condition of Iran in Comparison with “Twenty-Year Vision Document. Quarterly Journal of Economics and Modelling Shahid Beheshti University, 30(8), 1-29. (in Persian)
Smith, K. What is the Knowledge Economy? Knowledge Intensity and Distributed Knowledge Bases, The United Nations University, Institute for New Technologies, UNU/INTECH Discussion Papers. ISSN 1564-8370, (2002).
Smith, R., Sharif, N. (2007). Understanding and Acquiring Technology Assets for Global Competition. Technovation, 27(11), 643-649.
Sun, J., Li, Y. (2016). Joint inversion of multiple geophysical data using guided fuzzy C-Means clustering. Geophysics, 81 (3), 37-57.
Vinnychuk, O., Skrashchuk, L. & Vinnychuk, I. (2014). Research of Economic Growth in the context of Knowledge Economy. Intellectual Economics, 1 (19), 116-127.
Wilson, D.I. (2002). Derivation of the chalk superficial deposits of the North Downs, England: an application of discriminant analysis. Geomorphology, 42(3-4), 343-364.
World Bank (1998/99). World Development Report- Knowledge for Development. New York: Oxford University Press.
World Bank (2013). World Development Indicators 2003. World Bank Institute, Knowledge for Development Program.
World Bank and World Bank Institute. (2002). Knowledge for Development; a Forum for Middle East and North Africa. Marseilles: France, 9- 12.
World Bank. (2008). Measuring Knowledge in the World's Economies. Knowledge for Development, World bank Institute. The World Bank's Knowledge Assessment Methodology. Available at:
World Bank. (2012). Knowledge Assessment Metodology (KAM). World Bank Institute. available at: