Abstract

This article summarizes the arguments and counterarguments within the scientific debate on the identification of the main theoretical and practical principles of the functioning of innovative-industrial clusters in different countries, as well as the formalization of the impact of digitalization on their activities. The article summarizes scientific approaches to determining the main characteristics and features of the functioning of innovation-industrial clusters. In order to substantiate the theoretical background of the relationship between innovation-industrial clusters’ performance and digitalization processes, a bibliometric analysis of the main Scopus publications in this direction is carried out using the VOSviewer toolkit. That made it possible to identify the main essential and contextual clusters of scientific research on relevant topics to characterize the evolutionary patterns of their changes during the analysis period. In order to determine the empirical causality of the impact of digitalization on innovative and industrial development, an integral indicator of innovative and industrial development is developed. The Index considers the measurement parameters and regional features of industrial, entrepreneurial, and innovative development. Indicators were integrated using the principal components analysis and additive convolution. The study modelled the influence proxies of the digital economy on the integrated indicator of innovative and industrial development using panel data regression modelling in the Stata 14.2/SE software. In the paper, it is also identified those determinants of the digital development of the state that depends to the greatest extent on the volatility of the innovative and industrial development of the country using one-factor regression models. The study is conducted for the country sample with 10 countries, including Azerbaijan, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Poland, Romania, and Ukraine. The time horizon of the study covers the period 2009-2021 (or the latest available period). The research results can be useful to scientists, state authorities, and local governments.

Keywords: industrial and innovative cluster, digitalization, management, panel data, regression modelling.

JEL Classification: C33, E24, J01, O15, O30.

Cite as: Safarov, G., Sadiqova, S., Urazayeva, M., & Abbasova, N (2022). Theoretical and Methodological Aspects of Innovative-Industrial Cluster Development in the Era of Digitalization Marketing and Management of Innovations, 4, 184-197. https://doi.org/10.21272/mmi.2022.4-17

This work is licensed under a Creative Commons Attribution 4.0 International License

References

1. Andreoni, A., Barnes, J., Black, A., & Sturgeon, T. (2021). Digitalization, Industrialization, and Skills Development: Opportunities and Challenges for Middle-Income Countries. Retrieved from [Link]
2. Caniëls, M. C., & Romijn, H. A. (2005). What drives innovativeness in industrial clusters? Transcending the debate. Cambridge Journal of Economics, 29(4), 497-515. [Google Scholar] [CrossRef]
3. Danieles, A. (2019). Cluster programs in Europe and beyond. Retrieved from [Link]
4. Doumbia, D. (2016). Financial development and economic growth in 43 advanced and developing economies over the period 1975–2009: Evidence of non-linearity. Applied Econometrics and International Development, 16(1), 13-22. [Google Scholar]
5. Gaglio, C., Kraemer-Mbula, E., & Lorenz, E. (2022). The effects of digital transformation on innovation and productivity: Firm-level evidence of South African manufacturing micro and small enterprises. Technological Forecasting and Social Change, 182, 121785. [Google Scholar] [CrossRef].
6. Global Innovation Index Reports (2022). Retrieved from [Link]
7. Kotarba, M. (2017). Measuring digitalization: Key metrics. Foundations of Management, 9(1), 123-138. [Google Scholar]
8. Lai, Y. L., Hsu, M. S., Lin, F. J., Chen, Y. M., & Lin, Y. H. (2014). The effects of industry cluster knowledge management on innovation performance. Journal of business research, 67(5), 734-739. [Google Scholar] [CrossRef]
9. Lämmer-Gamp, T., Meier zu Köcker, G., & Nerger, M. (2014). Cluster Collaboration and Business Support Tools to Facilitate Entrepreneurship, Crosssectoral Collaboration and Growth. Retrieved from [Link]
10. Lines,T., & Monypenny, R. (2006). Industry Clustering. Retrieved from [Link]
11. Liu, L., Ding, T., & Wang, H. (2022). Digital Economy, Technological Innovation and Green High-Quality Development of Industry: A Study Case of China. Sustainability, 14(17), 11078. [Google Scholar] [CrossRef]
12. Milosevic, N., Dobrota, M., & Rakočevic, S. B. (2018). Digital economy in Europe: Evaluation of countries’ performances. Zbornik Radova Ekonomski Fakultet u Rijeka, 36(2), 861-880. [Google Scholar]
13. OECD. (2018). Toolkit for Measuring the Digital Economy. Retrieved from [Link]
14. OECD. (2022). Going Digital Toolkit. Retrieved from [Link]
15. Polder, M., Leeuwen, G. V., Mohnen, P., & Raymond, W. (2010). Product, process and organizational innovation: drivers, complementarity and productivity effects. CIRANO-scientific publications 2010s-28. [Google Scholar]
16. Porter, M. (1998). Clusters and the new economics of competition. Harvard Business Review , 76(6), 77-90. [Google Scholar]
17. Raghupathi, V., & Raghupathi, W. (2017). Innovation at country-level: association between economic development and patents. Journal of Innovation and Entrepreneurship, 6(1), 1-20. [Google Scholar] [CrossRef]
18. Scopus (2022). Retrieved from [Link]
19. Slaper, T., & Orturaz, G. (2015). Industry Clusters and Economic Development . Indiana Business Review . Retrieved from [Link]
20. Tristão, H., Oprime, P. C., Jugend, D., & Da Silva, S. L. (2013). Innovation in industrial clusters: a survey of footwear companies in Brazil. Journal of technology management & innovation, 8(3), 45-56. [Google Scholar]
21. Retrieved from [Link]
22. UNIDO (2019). Statistical Indicators of Inclusive and Sustainable Industrialization. Retrieved from [Link]
23. ). Composite measure of industrial performance for cross-country analysis. Retrieved from [Link]
24. VOSviewer (2022). Retrieved from: [Link]
25. World Bank DataBank (2022). Retrieved from [Link]
26. Xu, J., & Li, W. (2022). The Impact of the Digital Economy on Innovation: New Evidence from Panel Threshold Model. Sustainability, 14(22), 15028. [Google Scholar] [CrossRef]
27. Yamawaki, H. (2002). The evolution and structure of industrial clusters in Japan. Small Business Economics, 18(1), 121-140. [Google Scholar] [CrossRef]
28. Yim, D. S., Kim, W., & Nam, Y. H. (2020). The strategic transformation from innovation cluster to digital innovation cluster during and after COVID-19. Asian Journal of Innovation and Policy, 9(2), 164-186. [Google Scholar] [CrossRef]
29. Yoo, I., & Yi, C. G. (2022). Economic Innovation Caused by Digital Transformation and Impact on Social Systems. Sustainability, 14(5), 2600. [Google Scholar] [CrossRef
30. Zhang, J., Zhao, W., Cheng, B., Li, A., Wang, Y., Yang, N., & Tian, Y. (2022). The Impact of Digital Economy on the Economic Growth and the Development Strategies in the post-COVID-19 Era: Evidence From Countries Along the «Belt and Road». Frontiers in public health, 10, 856142. [Google Scholar] [CrossRef]