Regional innovation efficiency in Kazakhstan: Evidence from stochastic frontier and cluster analysis
-
DOIhttp://dx.doi.org/10.21511/ppm.24(3).2026.09
-
Article InfoVolume 24 2026, Issue #3, pp. 118-129
- 9 Views
-
2 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
Type of the article: Research Article
Abstract
Innovative and effective territorial development drives the country’s economic growth and its ability to compete on the world stage. The purpose of this paper is to quantify the effectiveness of regional innovative development and to use cluster analysis to identify typological groups of regions and pinpoint priority points of innovative growth. The study’s statistical database consists of official data from the Bureau of Statistics of Kazakhstan for the period 2003–2024. The study used econometric methods such as panel regression, stochastic, and cluster analysis. The results demonstrate that the innovative development of the regions of Kazakhstan is positively influenced by the human resource factor (β = 1.131, p < 0.001) and socio-economic development (β = 1.894, p < 0.001), and negatively influenced by the level of R&D costs (β = –0.473, p = 0.016). The results of the SFA analysis showed that regions with industrial specialization have the most effective innovative development (Pavlodar TE = 0.764, Kostanay TE = 0.751) in the production of innovative products, and that growth may be driven by investments in fixed assets (SFA (β =1.565, p < 0.001)). Cluster analysis showed that сluster 1 is characterized by a high level of commercialization, whereas сluster 4 demonstrates a high level of innovation activity; cluster 2 has a high level of knowledge intensity and return on science; cluster 3 has a good technological base. The results showed that a high level of financing does not always lead to breakthrough innovation.
- Keywords
-
JEL Classification (Paper profile tab)C23, O31, R58
-
References50
-
Tables7
-
Figures1
-
- Figure 1. Innovation activity vs Efficiency matrix
-
- Table 1. Main variables of econometric analysis
- Table 2. Indicators to group regions into clusters
- Table 3. Fixed effects panel regression
- Table 4. Structural parameters of the stochastic frontier model
- Table 5. Regional technical efficiency scores (Pooled estimates, 2003–2024)
- Table 6. Elasticity of innovation output (SFA)
- Table 7. Characteristics of regional innovation development clusters
-
- Abdelkarim, N., & Zuriqi, K. (2020). Corporate governance and earnings management: Evidence from listed firms at Palestine Exchange. Asian Economic and Financial Review, 10(2), 200-217.
- Abdukadirovna, M. M. (2021). Modern methods of effective management of innovation processes in the context of globalization. Asian Journal of Multidimensional Research, 10(9), 579-583.
- Adilet. (2010). On the State Programme for Accelerated Industrial and Innovative Development of the Republic of Kazakhstan for 2010–2014 and on the recognition as invalid of certain decrees of the President of the Republic of Kazakhstan. (In Russian).
- Adilet. (2024). National Development Plan of the Republic of Kazakhstan until 2029.
- Bae, S. J., & Lee, H. (2020). The role of government in fostering collaborative R&D projects: Empirical evidence from South Korea. Technological Forecasting and Social Change, 151, Article 119826.
- Battese, G. E., & Coelli, T. (1988). Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data. Journal of Econometrics, 38, 387-399.
- Bureau of National Statistics of the Republic of Kazakhstan. (2024a). Statistics of enterprises.
- Bureau of National Statistics of the Republic of Kazakhstan. (2024b). Investments statistics.
- Bureau of National Statistics of the Republic of Kazakhstan. (2024c). Statistics of education, science and innovation.
- Bureau of National Statistics of the Republic of Kazakhstan. (2024d). GRP statistics. (In Russian).
- Cassiman, B., & Veugelers, R. (2006). In search of complementarity in innovation strategy: Internal R&D and external knowledge acquisition. Management Science, 52(1), 68-82.
- Cheung, O. L. (2014). Impact of innovative environment on economic growth: An examination of state per capita GDP and personal income. Journal of Business & Economics Research, 12, 257-270.
- Cubero, J. N., Gbadegeshin, S. A., & Consolación, C. (2021). Commercialization of disruptive innovations: Literature review and proposal for a process framework. International Journal of Innovation Studies, 5(3), 127-144.
- Firms, V. M. (2014). Stochastic frontier analysis of. In An Introduction to Efficiency and Productivity Analysis (pp. 241-261). Boston, MA: Springer.
- Gürler, M. (2022). Innovation as an accelerating effect on Gross Domestic Product (GDP) per capita. The European Journal of Research and Development, 2(3), 26-44.
- Hausman, J. (1978). Specification tests in econometrics. Applied Econometrics, 38, 112-134.
- Huseynova, N.L. (2025). Mechanism for effective management of the innovation process based on a systemic approach. Herald of Uzhgorod National University. Series: International Economic Relations and World Economy, 60-65.
- Iriogbe, H. O., Agu, E. E., Efunniyi, C. P., Osundare, O. S., & Adeniran, I. A. (2024). The role of project management in driving innovation, economic growth, and future trends. International Journal of Management & Entrepreneurship Research, 6(8), 2819-2834.
- Isaksen, A., & Karlsen, J. (2013). Can small regions construct regional advantages? The case of four Norwegian regions. European Urban and Regional Studies, 20, 243-257.
- Jaspen, N., Draper, N. R., & Smith, H. D. (1968). Applied regression analysis. Mathematics of Computation, 22, 689.
- Kangalakova, D.M., & Rakhmetova, D. (2021). Structural features of the intellectual potential of the regions and its impact on the development of the country. Economics: The Strategy and Practice, 16, 22-34. (In Russian).
- Kenzhaliyev, O. B., Ilmaliyev, Z., Tsekhovoy, A. F., Triyono, M. B., Kassymova, G. K., Alibekova, G. Z., & Tayauova, G. (2021). Conditions to facilitate commercialization of R & D in case of Kazakhstan. Technology in Society, 67, Article 101792.
- Kumbhakar, S. C., & Lovell, C. A. (2000). Stochastic frontier analysis. Cambridge University Press.
- Lapaev, S., & Moldagulova, Z. (2019). Innovative development of the Republic of Kazakhstan. Intelligence. Innovations. Investment, 2, 45-49.
- Lehmann, E. E., Warning, S., & Weigand, J. G. (2004). Governance Structures, Multidimensional Efficiency and Firm Profitability. Journal of Management and Governance, 8, 279-304.
- Liao, K., & Zhang, J. (2022). Analysis on the innovation path of enterprise human resource management in the era of digital economy. Frontiers in Business, Economics and Management, 4(1), 128-131.
- Lin, X., Ahmed, Z., Jiang, X., & Pata, U.K. (2023). Evaluating the link between innovative human capital and regional sustainable development: Empirical evidence from China. Environmental Science and Pollution Research, 30, 97386-97403.
- Menard, S. (1996). Applied logistic regression analysis. Journal of the Royal Statistical Society. Series D (The Statistician), 45(4), 534-535.
- Mincer, J. (1981). Human capital and economic growth. Economics of Education Review, 3(3), 195-205.
- Moncada-Paternò-Castello, P. (2022). Top R&D investors, structural change and the R&D growth performance of young and old firms. Eurasian Business Review, 12, 1-33.
- Mukayev, A., Satpayeva, Z. T., Kangalakova, D. M., Doskeyeva, G. Z., & de Matos Pedro, E. (2023). Assessment of the population’s quality of life in Kazakhstan during COVID-19: The effectiveness of public policy. Problems and Perspectives in Management, 21(3), 69-83.
- Nemlioglu, I., & Mallick, S.K. (2021). Effective innovation via better management of firms: The role of leverage in times of crisis. Research Policy, 50(7), Article 104259.
- Oguzturk, B. S., Özbay, F., Arıcan, M., & Kaleli̇, F. (2021). The role and effect of human capital and R&D on the sales of new product: A study on the innovation performance of the manufacturing industry of Keihanshin region in Japan. Uluslararası Akademik Yönetim Bilimleri Dergisi, 7(11), 1-18.
- Osińska, M., Gałecki, M., Boehlke, J., Fałdziński, M., Khan, A. M., & Shachmurove, Y. (2022). Extended Threshold Error Correction Model of economic growth in Israel. Bulletin of Geography. Socio-economic Series, 57, 45-63.
- Podra, O., Litvin, N., Zhyvko, Z., Kopytko, M., & Kukharska, L. (2020). Innovative development and human capital as determinants of knowledge economy. Business: Theory and Practice, 21(1), 252-260.
- Pylypenko, H. M., Pylypenko, Y. I., Dubiei, Y., Solianyk, L., Pazynich, Y. M., Buketov, V., Smolinski, A. V., & Magdziarczyk, M. (2023). Social capital as a factor of innovative development. Journal of Open Innovation: Technology, Market, and Complexity, 9(3), Article 100118.
- Raithatha, M., & Haldar, A. (2021). Are internal governance mechanisms efficient? The case of a developing economy. IIMB Management Review, 33(3), 191-204.
- Schot, J., & Steinmueller, W. E. (2018). Three frames for innovation policy: R&D, systems of innovation and transformative change. Research Policy, 47(9), 1554-1567.
- Seo, S., & Jung, Y. (2025). R&D collaboration partner search in deep tech firms: A feasibility study of the digital therapeutics sector in Korea. The Korean Career, Entrepreneurship and Business Association, 7, 215-243.
- Sharma, S., Kleinbaum, D. G., & Kupper, L. L. (1978). Applied regression analysis and other multivariate methods. Journal of Marketing Research, 15(3).
- Slavova, S., Rubalcaba, L., & Franco-Riquelme, J.N. (2025). Understanding imbalanced transmission from R&D inputs into innovation outputs and impacts: Evidence from Kazakhstan. Economies, 13(2), Article 25.
- Susantinah, N., Krishernawan, I., & Murthada (2023). Human Resource Management (HRM) Strategy in Improving Organisational Innovation. Journal of Contemporary Administration and Management (ADMAN), 1(3), 201-207.
- Thao, H. T., & Minh Anh, N. N. (2025). Trends in venture capital investment in Israel and policy implications for mobilizing capital for innovative startups in Vietnam. International Journal of Education, Business and Economics Research, 5(6), 20-38.
- Wang, Y., Li, A., & Cheng, S. (2021). Harmonious development and dynamic correlation analysis of new energy industry agglomeration innovative human capital and green economic growth. E3S Web of Conferences, 269, Article 01006.
- WIPO. (n.d.). Kazakhstan ranking in the Global Innovation Index 2025.
- World Bank. (2024). Research and development expenditure (% of GDP). Kazakhstan.
- Xie, Q., & Khan, M.S. (2024). Sustainable housing and quality of life in Shenzhen: The role of knowledge, technology and innovation. Journal of Infrastructure, Policy and Development, 8(9), Article 7620.
- Yucel, M., Yanik, G., Dayı, F., & Benek, A. (2025). Strategic management of environmental, social, and governance scores and corporate governance index: A panel data analysis of firm value on the Istanbul Stock Exchange. Sustainability, 17(11), Article 4971.
- Zhang, L., & Huang, S. (2022). Social capital and regional innovation efficiency: The moderating effect of governance quality. Structural Change and Economic Dynamics, 62, 343-359.
- Zhao, S., Tian, W., & Dagestani, A. (2022). How do R&D factors affect total factor productivity: Based on stochastic frontier analysis method. Economic Analysis Letters, 1(2), Article 10.


