Methodological Approach to the Efficiency Analysis of Regional Industrial Ecosystems

Formation of a new model of limited open sovereign economy in Russia requires the improvement of the theoretical and methodological basis for evaluating the efficiency of regional industry. The research aims to develop a methodological approach to the efficiency analysis of regional industrial ecosystems. To this end, an ecosystem approach to analysing the efficiency of regional industry was employed. In order to establish evaluation criteria, the study defined the structure of regional industrial ecosystems, comprising a set of intrinsic characteristics (development projections): scale, production potential, production infrastructure, human capital, research and development (R&D), innovation, integration potential, competitiveness, and ecology. Efficiency evaluation and comparative analysis of regional industrial ecosystems were performed using a developed system of twenty-seven indicators to provide an objective assessment of the state of industry. The paper examined five industrially developed regions of the Volga Federal District: the Republics of Bashkortostan and Tatarstan, Perm krai, Nizhny Novgorod and Samara oblasts. Testing of the authors' approach revealed the uneven development of regions according to projections and indicators of industrial ecosystems. Nizhny Novgorod oblast achieved the best result in terms of the totality of indicators, as well as in terms of scale and production potential, R&D and ecology. Perm krai is a leader according to such indicators as production infrastructure and product competitiveness. The Republic of Tatarstan leads in innovation, while the Republic of Bashkortostan has the greatest integration potential. Samara oblast is the outsider characterised by high depreciation of fixed assets and discharge of contaminated wastewater. The findings confirmed the research hypothesis about the possibility of representing processing industries of industrially developed Russian regions as industrial ecosystems.