Published at : 16 Oct 2020
Volume : IJtech Vol 11, No 4 (2020)
DOI : https://doi.org/10.14716/ijtech.v11i4.4191
|Tatiana Kudryavtseva||Peter the Great St. Petersburg Polytechnic University, Saint Petersburg 195251, Russia|
|Natalia Kulagina||Bryansk State University of Engineering and Technology, Bryansk 241035, Russia|
|Alexandra Lysenko||Bryansk State University of Engineering and Technology, Bryansk 241035, Russia|
|Mohammed Ali Berawi||Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia|
|Angi Skhvediani||Peter the Great St. Petersburg Polytechnic University, Saint Petersburg 195251, Russia|
The purpose of this work is to develop a methodology to assess and monitor cluster structures. The authors’ proposed method assesses the level of cluster structure development by considering cluster transformation analysis in the information and communication sectors of the regional economy, prerequisites for cluster formation, and the current level of digital cluster development in the region. To evaluate the prerequisites of digital economy cluster formation, an integral indicator is calculated and a multi-parameter approach is used to evaluate cluster effectiveness. The integral indicator includes 17 values calculated using the scorecard evaluation method. To make conclusions about the stages of IT cluster development, the authors provide the scale used to interpret integral indicator values. This scale classifies cluster development using four levels: beginner, elementary, intermediate, and advanced. A comparative analysis of IT cluster development in the Kaluga and Bryansk regions of the Russia reveals that IT clusters in Kaluga are at an advanced level of development due to its highly developed infrastructure and work flow organization, while IT clusters in Bryansk are at the beginner stage. This shows that Kaluga has a more effective industrial policy for clusters. The proposed methodology allows researchers to compare clusters from different regions and monitor their development.
Cluster; Innovation; IT cluster; Regional innovation system; Russia
The development of cluster structures boosts regional and national economic processes, which has a positive effect on the investment attractiveness and socio-economic potential of the region and leads to the creation of new enterprises and jobs (Rudskaya and Rodionov, 2017; Isaksen, 2018; Lehmann and Menter, 2018; Schepinin et al., 2018).
In the 20th century, clusters began to be considered the most important factor in regional development (Gutman et al., 2017; Kozonogova et al., 2019). Regions with developed cluster structures are more competitive; clusters are a foothold for successful regional economies. The aggregation of enterprises and organizations into cluster makes it possible to increase their effectiveness (Kudryavtseva et al., 2020). In addition, clusterisation can provide higher localization economies from land and infrastructure usage (Berawi, 2018; Berawi et al., 2019).
In accordance with the Russian Federation’s two main development programs—Digital Economy of the Russian Federation (Government of the Russian Federation, 2017) and Economic Development and Innovative Economy (Government of the Russian Federation, 2014)—clusters (digital clusters in particular) should become one of the main forms of economic activity to ensure economic growth. Therefore, it is essential to analyze existing approaches to cluster development evaluation and test them using a Russian digital cluster.
The paper aims to develop a method for assessing and monitoring cluster effectiveness. To do this, it is necessary to complete the following tasks:
The “Literature review” section discusses various definitions of the term “cluster” present in Russian and international scientific works, as well as existing approaches for assessing cluster effectiveness. The “Data and method” section describes the method for evaluating the effectiveness of digital clusters, taking into account the analysis of prerequisites for cluster formation and the current level of digital development in the regions. The “Results and discussion” section discusses the test results for the authors’ method of assessing the effectiveness of digital economy clusters in the Bryansk region. The main findings of the work are summarized in the “Conclusions” section.
While the study revealed that there are many definitions of the term “cluster”, approaches in the literature highlighted the same cluster characteristics: geographical affiliation, integration of production processes, relationship between enterprises, and benefits for the enterprises in the cluster. These approaches to assessing cluster effectiveness can be divided into the following groups: methods based on measuring individual effects, methods based on cluster assessment through investment projects, parametric methods, and methods based on assessing cluster competitiveness. Most available methods and techniques for assessing cluster effectiveness are related to industrial clusters and are therefore not applicable to digital clusters.
Based on the results obtained, it is possible to assess a cluster's capacity for innovative activities in the field of digital products and the prospects for achieving the main strategic goal of the cluster. The authors proposed a method that classifies administrative districts by their stage of digital development. This is a starting point for the digitalization strategy in the region, as it enables researchers to achieve regional projects’ targets in the field of digital economy.
This research was supported by the Academic Excellence Project 5-100 proposed by Peter the Great St. Petersburg Polytechnic University.
Abashkin, V., Artemov, S., Gusev, A., Khafizov, R., Kutsenko, E., Zaurova, E., 2018. Cluster Policy in Russia: From Local Advantages to Global Competitiveness. Ministry of Economic Development of the Russian Federation; RVC JSC; National Research University Higher School of Economics. – Moscow: HSE, 2018, pp. 1–88
Andreyeva, D.A., Irina, I.V.K., Dvas, G.V., Malinin, A.M., Nadezhina, O.S., 2018. Factors of Effective Regional Development and Labor Market Condition as Indicator of State of the Economy of the Region. In: Proceedings of the 31st International Business Information Management Association Conference, 25-26 April 2018, Milan, Italy, IBIMA publishing, pp. 5507–5513
Beloglazova, S.A., 2019. (Cluster Form of Economic Organization: Determining the Potential and Directions of Development in the Regions of Russia). PhD Thesis, Volgograd State University, pp. 268
Berawi, M.A., 2018. Managing Sustainable Infrastructure and Urban Development: Shaping a Better Future for ASEAN. International Journal of Technology, Volume 9(7), pp. 1295–1298
Berawi, M.A., Suwartha, N., Fathiya Salsabila., Gunawan., Perdana Miraj., Woodhead, R., 2019. Land Value Capture Modeling in Commercial and Office Areas using a Big Data Approach. International Journal of Technology, Volume 10(6), pp. 1150–1156
Boekholt, P., Thuriaux, B., 1999. Public Policies to Facilitate Clusters: Background, Rationale and Policy Practices in International Perspective. In: Boosting Innovation: The Cluster Approach, OECD, pp. 381–412
Caragliu, A., de Dominicis, L., De Groot, H.L.F., 2016. Both Marshall and Jacobs Were Right!. Journal of Economic Geography, Volume 92(1), pp. 87–111
Chen, X., Wang, E., Miao, C., Ji, L., Pan, S., 2020a. Industrial Clusters as Drivers of Sustainable Regional Economic Development? An Analysis of an Automotive Cluster from the Perspective of Firms’ Role. Sustainability, Volume 12(7), pp. 1–22
Chen, P., Xie, R., Lu, M., 2020b. "Resource Conservation” or “Environmental Friendliness”: How do Urban Clusters Affect Total-Factor Ecological Performance in China? International Journal of Environmental Research and Public Health, Volume 17(12), pp. 1–28
Delgado, M., Porter, M.E., Stern, S., 2015. Defining Clusters of Related Industries. Journal of Economic Geography, Volume 16(1), pp. 1–38
Fracasso, A., Vittucci Marzetti, G., 2018. Estimating Dynamic Localization Economies: The Inadvertent Success of the Specialization Index and the Location Quotient. Regional Studies, Volume 52(1), pp. 119–132
Government of the Russian Federation, 2014. (State Program of the Russian Federation «Economic Development and Innovative Economy»)
Government of the Russian Federation, 2017. (Program «Digital Economy of Russian Federation»).
Gutman, S.S., Zaychenko, I.M., Kalinina, O.V., 2017. Selection of Strategy Implementation Tool for Shipbuilding Cluster of Arkhangelsk Oblast. In: Proceedings of the 29th International Business Information Management Association Conference, 3-4 May 2017, Vienna, Austria, IBIMA publishing, pp. 1430–1438
Humphrey, J., Schmitz, H., 2002. How Does Insertion in Global Value Chains Affect Upgrading in Industrial Clusters? Regional Studies, Volume 36(9), pp. 1017–1027
Ibragimova, R.S., Tokunov, A.A., 2016. Evaluation of the Effectiveness of Textile Clusters: A Methodological Aspect. Modern High Technology, Regional Application, Volume 3(47), pp. 75–84
Isaksen, A., 2018. From Success to Failure, the Disappearance of Clusters: A Study of a Norwegian Boat-building Cluster. Cambridge Journal of Regions, Economy and Society, Volume 11(2), pp. 241–255
Kleiner, G.B., Kachalov, R.M., Breast, N.B., 2008. (Synthesis of Cluster Strategy Based on System-integration Theory. Management of Science and Scientometrics). Industrial Markets, 6-6(18), pp. 9–39
Kovaleva, T.Y., 2018. Theoretical-methodological Bases and Results of Estimation of the Effectiveness of Cluster Spatial Development of the Russian Federation Regions. Vestnik of Astrakhan State Technical University. Series: Economics, Volume 2018(2), pp. 101–111
Kozonogova, E., Elokhova, I., Dubrovskaya, J., Goncharova, N., 2019. Does State Cluster Policy Really Promote Regional Development? The Case of Russia. In: IOP Conference Series: Materials Science and Engineering, Volume 497(1), pp. 12044
Kudryavtseva, T., Rodionov, D.G., Skhvediani, A.E., 2018. An Empirical Study of Information Technology Clusters and Regional Economic Growth in Russia. In: SHS Web of Conferences, Volume 44, pp. 1–11
Kudryavtseva, T., Skhvediani, A., Ali, M. 2020. Modeling Cluster Development using Programming Methods: Case of Russian Arctic Regions. Entrepreneurship and Sustainability Issues, Volume 8(1), pp. 150–176
Kuporov, Y.Y., Avduevskaya, E.A., Bogacheva, T.V., 2018. Investments in Human Capital: Efficiency of investments in higher education in Russia. In: Proceedings of the 31st International Business Information Management Association Conference, IBIMA 2018: Innovation Management and Education Excellence through Vision 2020, 25-26 April 2018, Milan, Italy, pp. 926–940
Lehmann, E.E., Menter, M., 2018. Public Cluster Policy and Neighboring Regions: Beggar-thy-neighbor? Economics of Innovation and New Technology. Economics of Innovation and New Technology, Volume 5-6(27), pp. 420–437
Litzel, N., 2017. Does Embeddedness in Clusters Enhance Firm Survival and Growth? An Establishment-level Analysis using CORIS Data. Regional Studies, Volume 4(51), pp. 563–574
Maggioni, M., 2004. The Rise and Fall of Industrial Clusters: Technology and the Life Cycle of Regions. IEB Working Paper 2004/06, pp. 1 –39
Marshall, A., 1890. Principles of Economics. 8th ed. Published in 1920. Palgrave Macmillan, London.
Ministry of Economic Development, 2008. (Methodical recommendations on realization of cluster policy in the Russian Federation).
Moeis, A.O., Desriani, F., Destyanto, A.R., Zagloel, T.Y., Hidayatno, A., Sutrisno, A., 2020. Sustainability Assessment of the Tanjung Priok Port Cluster. International Journal of Technology, Volume 11(2), pp. 353–363
Porter, M.E., 1998. Clusters and Competition: New Agendas for Companies, Governments, and Institutions. Boston, MA, USA: Harvard Business School,
Pososhkov, P., 2017. (Clustering of the oil and gas industry as a factor in increasing the level of economic security of Russia. Saint Petersburg), PhD Thesis, Saint Petersburg State University of Economics, pp. 173
Putri, E.P., Chetchotsak, D., Ruangchoenghum, P., Jani, M.A., Hastijanti, R., 2016. Performance Evaluation of Large and Medium Scale Manufacturing Industry Clusters in East Java Province, Indonesia. International Journal of Technology, Volume 7(7), pp. 1269–1279
Rodionov, D., Rudskaia, I., 2019. Problems of Infrastructural Development of “Industry 4.0” in Russia on Sibur Experience. In: Proceedings of the 32nd International Business Information Management Association Conference, 15-16 November, 2018, Seville, Spain, IBIMA publishing, pp. 3534–3544
Rudskaya, I., Rodionov, D., 2017. Econometric Modelling as a Tool for Evaluating the Performance of Regional Innovation Systems (with Regions of the Russian Federation as the Example). Academy of Strategic Management Journal, Volume 2(16), pp. 18
Schepinin, V., Skhvediani, A., Kudryavtseva, T., 2018. An Empirical Study of the Production Technology Cluster and Regional Economic Growth in Russia. In: Amorim, M.P.C., Costa, C., Au-Yong-Oliveira, M., (eds.). Proceedings of the European Conference on Innovation and Entrepreneurship. ECIE 2018, Aveiro, 20-21 September 2018. Academic Conferences and Publishing International Limited: pp. 732–740
Selentyeva, T.N., Degtereva, V.A., Ivanova, M.V., Mikheyenko, O.V., 2018. The Competitiveness of Innovation Clusters: Approaches to Assessing and Role of State Cluster Policy. In: Proceedings of the 32nd International Business Information Management Association Conference, 15-16 November, 2018, Seville, Spain, IBIMA publishing, pp. 1706–1709
Steinfield, C., Scupola, A., López-Nicolás, C., 2010. Social Capital, ICT Use and Company Performance: Findings from the Medicon Valley Biotech Cluster. Technological Forecasting and Social Change, Volume 77(7), pp. 1156–1166
Strøjer Madsen, E., Smith, V., Dilling-Hansen, M., 2003. Industrial Clusters, Firm Location and Productivity – Some Empirical Evidence for Danish Firms. Working Papers 03-26, University of Aarhus, Aarhus School of Business, Department of Economics. Handle: RePEc:hhs:aareco:2003_026
Taglioni, D., Winkler, D., 2016. Making Global Value Chains Work for Development. Trade and Development. Washington, DC: World Bank
Tsertseil, Y.S., Kokuyeva, V.V., 2018. (Features of an Estimation of Efficiency of Industrial Innovative Clusters in the Foreign Literature). Economics and Management: Science to Practice Journal, Volume 5(143), pp. 117–121
Wiratmadja, I.I., Govindaraju, R., Handayani, D., 2016. Innovation and Productivity in Indonesian IT Clusters: The Influence of External Economies and Joint Action. International Journal of Technology, Volume 7(6), pp. 1097–1106
Zhu, H., Dai, Z., Jiang, Z., 2017. Industrial Agglomeration Externalities, City Size, and Regional Economic Development: Empirical Research Based on Dynamic Panel Data of 283 Cities and GMM Method. Chinese Geographical Science, Volume 27(3), pp. 456–470