A digital econometric analysis of the influence of small innovation enterprises of the petrochemical industry cluster on the regional economic system: The Republic of Tatarstan case study
Subject. This article examines the volume of shipped goods of the petrochemical industry cluster of the Republic of Tatarstan in 2012–2018, as well as the works and services performed on the basis of clean product economic activities in the whole region and organizations that are not related to small enterprises. Objectives. The article aims to determine the importance of small innovative enterprises and find the optimal ratio of processing productions of the petrochemical industry cluster in the regional economic system with a predominant share of revenues from oil and gas extraction and processing in the context of the national digital economy strategy. Methods. For the study, I used the methods of multivariate regression and simplex optimization. Results. The article states that the models of multivariate regression and simplex optimization of the regional petrochemical industry cluster's development in the Republic of Tatarstan as a whole and by aggregate of major budget revenue generating enterprises only practically coincide completely. The predominance of large-scale production in the economy of the region is characteristic of the 20th century and therefore the Kazan and Kama industrial agglomerations are now recognized as ineffective. Conclusions. The post-industrial economy is based on digital innovation technologies. Their greatest efficiency is possible in the organizations related to small business. Concerning the digital aspect, it is necessary to improve the methods of economic and mathematical modeling of innovative projects ensuring the improvement of innovation infrastructure efficiency and the transfer of technology and innovations.
Keywords: regional economy, innovative enterprise, petrochemical cluster, digital economy
References:
Witjes S., Lozano R. Towards a More Circular Economy: Proposing a Framework Linking Sustainable Public Procurement and Sustainable Business Models. Resources Conservation and Recycling, 2016, vol. 112, pp. 37–44. URL: Link
Yun J.J., Won D., Jeong E.S. et al.The Relationship between Technology, Business Model, and Market in Autonomous Car and Intelligent Robot Industries. Technological Forecasting and Social Change, 2016, vol. 103, pp. 142–155. URL: Link
Quang H.T., Sampaio P., Sameiro Carvalho M. et al. An Extensive Structural Model of Supply Chain Quality Management and Firm Performance. International Journal of Quality & Reliability Management, 2016, vol. 33, iss. 4, pp. 444–464. URL: Link
Dong J.Q., Netten J.Information Technology and External Search in the Open Innovation Age: New findings from Germany. Technological Forecasting and Social Change, 2017, vol. 120, pp. 223–231. URL: Link
Yun J.J., Yang J., Park K. Open Innovation to Business Model: New Perspective to Connect between Technology and Market. Science, Technology and Society, 2016, vol. 21, iss. 3, pp. 324–348. URL: Link
Halicka K. Innovative Classification of Methods of the Future-Oriented Technology Analysis. Technological and Economic Development of Economy, 2016, vol. 2, no. 4, pp. 574–597. URL: Link
Popescu A.S. The Absorption Capacity of European Funds – Concepts. Annals of the Constantin Brâncuşi University of Târgu Jiu, Economy Series, 2015, iss. 3, pp. 119–125. URL: Link
Arshed N., Carter S., Mason C. The Ineffectiveness of Entrepreneurship Policy: Is Policy Formulation to Blame? Small Business Economics, 2014, vol. 43, iss. 3, pp. 639–659. URL: Link
Acs Z., Åstebro Th., Audretsch D., Robinson D.T. Public Policy to Promote Entrepreneurship: A Call to Arms. Small Business Economics, 2016, vol. 47, iss. 1, pp. 35–51. URL: Link
Crescenzi R., De Fillipis F., Pierangeli F.In Tandem for Cohesion? Synergies and Conflicts between Regional and Agricultural Policies of the European Union. Regional Studies, 2015, vol. 49, iss. 4, pp. 681–704. URL: Link
Novosák J., Hájek O., Novosáková J., Linder M. Enterprise Support Policy and Territorial Cohesion: The Czech Republic (2007–2013). Journal of Urban and Regional Analysis, 2017, vol. 9, iss. 2, pp. 141–157.
Hájek O., Novosák J., Horváth P., Novosáková J. Absorpční kapacita strukturálních fondů (2007–2013): typologie českých mikroregionů [Absorption capacity of structural funds (2007–2013): typology of Czech microregions]. Scientific Papers of the University of Pardubice. Series D, Faculty of Economics and Administration, 2017, vol. 24, iss. 39, pp. 28–38. URL: Link
Colombelli A., Krafft J., Quatraro F. High-Growth Firms and Technological Knowledge: Do Gazelles Follow Exploration or Exploitation Strategies? Industrial and Corporate Change, 2014, vol. 23, iss. 1, pp. 261–291. URL: Link
Guisado-González M., González-Blanco J., Coca-Pérez J.L. Analyzing the Relationship between Exploration, Exploitation and Organizational Innovation. Journal of Knowledge Management, 2017, vol. 21, iss. 5, pp. 1142–1162. URL: Link
Zacher H., Rosing K. Ambidextrous Leadership and Team Innovation. Leadership & Organization Development Journal,2015, vol. 36, iss. 1, pp. 54–68. URL: Link
Zhang J.A., Edgar F., Geare A., O'Kane C. The Interactive Effects of Entrepreneurial Orientation and Capability-Based HRM on Firm Performance: The Mediating Role of Innovation Ambidexterity. Industrial Marketing Management, 2016, vol. 59, pp. 131–143. URL: Link
Vrontis D., Thrassou A., Santoro G., Papa A. Ambidexterity, External Knowledge and Performance in Knowledge-Intensive Firms. The Journal of Technology Transfer, 2017, vol. 42, iss. 2, pp. 374–388. URL: Link
Sheng M.L.A Dynamic Capabilities-Based Framework of Organizational Sensemaking through Combinative Capabilities towards Exploratory and Exploitative Product Innovation in Turbulent Environments. Industrial Marketing Management, 2017, vol. 65, pp. 28–38. URL: Link
Chen X., Christensen T.M. Optimal Sup-Norm Rates and Uniform Inference on Nonlinear Functionals of Nonparametric IV Regression. Cowles Foundation Discussion Paper, 2017, no. 1923R2. URL: Link
Kilian L., Lütkepohl H. Structural Vector Autoregressive Analysis. Cambridge University Press, 2017, 735 p. URL: Link
Andrews D.W.K.Examples of L2-Complete and Boundedly-Complete Distributions. Journal of Econometrics, 2017, vol. 199, iss. 2, pp. 213–220. URL: Link
Freyberger J. On Completeness and Consistency in Nonparametric Instrumental Variable Models. Econometrica, 2017, vol. 85, iss. 5, pp. 1629–1644. URL: Link
De Luca G., Jan R.M., Peracchi F. Balanced Variable Addition in Linear Models. Journal of Economic Surveys, 2018, vol. 32, iss. 4, pp. 1183–1200. URL: Link
Card D., Lee D.S., Pei Zh., Weber A. Inference on Causal Effects in a Generalized Regression Kink Design. Econometrica, 2015, vol. 83, iss. 6, pp. 2453–2483. URL: Link
Chen X., Christensen T.M. Optimal Uniform Convergence Rates and Asymptotic Normality for Series Estimators under Weak Dependence and Weak Conditions. Journal of Econometrics, 2015, vol. 188, iss. 2, pp. 447–465. URL: Link
Chen X., Pouzo D. Sieve Wald and QLR Inferences on Semi/Nonparametric Conditional Moment Models. Econometrica, 2015, vol. 83, iss. 3, pp. 1013–1079. URL: Link
Beilin I.L., Arkhireev V.P. The Supermolecular Structure of New Copolymer Products Based on Cyclic Carbonates. International Polymer Science and Technology, 2011, vol. 38, no. 1, pp. 37–40. URL: Link
Beilin I.L. Analysis of Efficiency of the Innovative Project in the Field of Chemistry Fuzzy Logic. Journal of Economics and Economic Education Research,2016, vol. 17, sp. iss. 3, pp. 177–185. URL: Link
Beilin I.L. Economic-Mathematical Modeling of the Total Costs of Innovative Chemical Enterprise Methods of Fuzzy Set Theory. Journal of Engineering and Applied Sciences, 2017, vol. 12, iss. 19, pp. 4865–4869. URL: Link
