Differentiated Approach Problems to Innovative Development Management in Russian Regions

Rajskaya, Marina V.; Сагдеева, А. А.; Gusarova, I.A.; Panteleeva, Yuliya V.; Malysheva, T. V.; Ershova, Irina

doi:10.18510/hssr.2019.74174

Cited by 9 publications

(7 citation statements)

References 15 publications

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“…There are developments by scientists in the field of innovative development at the regional level, namely the study of industry-specific innovative potential [8], a structured analysis of regional innovations [9], modeling of innovation management in a regional industrial complex [10], the study of regional sustainability [11], the identification of problems of a differentiated approach to the management of innovative development in the Russian regions [12].…”

Section: Literature Review and Research Methodsmentioning

confidence: 99%

Cooperation of Science and Business in Order to Organize High-Tech Production in the Regions of the Russian Federation

Igorevna¹,

Aleksandrovna²,

Vladimirovna³

et al. 2020

Proceedings of the “New Silk Road: Business Cooperation and Prospective of Economic Development” (NSRBCPED 2019)

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The article discusses the regional aspects of the formation of cooperative ties between science and business. The level of cooperation of enterprises with scientific and educational organizations is presented as an important criterion for the organization of high-tech production. The relevance of the article lies in the need to solve the problems of managing joint innovative projects in Russian regions. The purpose of the article is to identify trends and factors that influence the development of cooperative ties in regional production systems of various levels of manufacturability. As the main research methods, the article used the description method to determine the level and trends of innovative development of Russian regions; the method of correlation analysis, which established the factors that have the greatest influence on the degree of cooperation of scientific organizations and industrial enterprises in the development of technological innovations. The article presents an analysis of the dynamics of innovative development of the industrial sector of the Russian regions; the interrelation of factors affecting the degree of cooperation between science and business in the development of technological innovations is determined. The materials of the article can be used in the development of organizational and managerial decisions aimed at enhancing the innovative development of territories, the organization of high-tech industries, taking into account the cooperation of scientific organizations and business.

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Section: Literature Review and Research Methodsmentioning

confidence: 99%

Cooperation of Science and Business in Order to Organize High-Tech Production in the Regions of the Russian Federation

Igorevna¹,

Aleksandrovna²,

Vladimirovna³

et al. 2020

Proceedings of the “New Silk Road: Business Cooperation and Prospective of Economic Development” (NSRBCPED 2019)

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“…The issues of innovative development of energy networks of industries based on the integration of competitive enterprises are considered in the works of Shinkevich et al (2016), Rajskaya et al (2019). In order to determine the impact of energy consumption on the economy, Baz et al (2019) established the relationship between energy consumption and economic growth by asymmetric analysis; Lindberg et al (2019) investigated the structure of energy policy and the transition to sustainable development of the EU countries; Xu and Chen (2019) assessed the relationship between environmental management and the financial sustainability of the energy industry and identified linear and non-linear effects.…”

Section: Literature Reviewmentioning

confidence: 99%

Management of Sustainable Consumption of Energy Resources in the Conditions of Digital Transformation of the Industrial Complex

Shinkevich¹,

Mashkin²,

Ishmuradova³

et al. 2020

IJEEP

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The purpose of the article is to study the dynamics of volumes and stability of the structure of energy resource consumption at manufacturing enterprises, the analysis of the technical readiness of energy systems to implement the ideas of digital transformation. As the main research methods used in this article there are the method of dipole energy analysis to determine the priority of types of energy carriers, the method of graphical visualization of data to find the release points of values from the zone of relative stability, the method of classifying objects to assign products to a group of objects on the level of energy sustainability. The article analyzes the current trends in energy consumption with the determination of the vector of sustainable energy consumption and the parameters of reserves for improving energy efficiency; prioritized separate types of energy production of petrochemical plants; the types of products were classified according to the level of sustainability of energy consumption with the establishment of control points having emissions of values from the zone of relative stability and unproductive consumption of energy resources; the high technical readiness of energy systems of manufacturing industries to automate production processes with the subsequent development of digital technologies has been proved.

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“…The high complexity and uncertainty of energy consumption processes make it preferable to use neural networks to study them [36][37][38][39][40]. In order to expand the mathematical tools for studying the energy efficiency of chemical industries, Jin et al developed approaches to assessing the effectiveness of resource-saving projects based on a backpropagation neural network [41]; Xiang et al proposed an algorithm for learning a multilayer neural network based on photonic spike timing dependent plasticity [42]; Menghi et al systematized methods and tools for energy assessment [43]; Geng et al assessed the energy saving of complex petrochemical industries based on complex clustering of the DEA affinity distribution [44]; Hamedi and Mokhtar applied multivariate linear regression and multilayer perceptronic artificial neural networks to build a baseline for energy consumption in a low-density polyethylene plant [45]; Shinkevich et al showed the advantage of the network model of the value chain for analyzing the resource intensity of production [46]; Rajskaya et al substantiated the expediency of a differentiated approach to assessing the level of innovative development of production resource-saving systems [47].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Energy Consumption in Chemical Production Based on Descriptive Analytics and Neural Network Modeling

et al. 2021

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Improving the energy efficiency of chemical industries and increasing their environmental friendliness requires an assessment of the parameters of consumption and losses of energy resources. The aim of the study is to develop and test a method for solving the problem of optimizing the use of energy resources in chemical production based on the methodology of descriptive statistics and training of neural networks. Research methods: graphic and tabular tools for descriptive data analysis to study the dynamics of the structure of energy carriers and determine possible reserves for reducing their consumption; correlation analysis with the construction of scatter diagrams to identify the dependences of the range of limit values of electricity consumption on the average rate of energy consumption; a method for training neural networks to predict the optimal values of energy consumption; methods of mathematical optimization and standardization. The authors analyzed the trends in the energy intensity of chemical industries with an assessment of the degree of transformation of the structure of the energy portfolio and possible reserves for reducing the specific weight of electrical and thermal energy; determined the dynamics of energy losses at Russian industrial enterprises; established the correlation dependence of the range of limiting values of power consumption on the average rate of power consumption; determined the optimal limiting limits of the norms for the loss of electrical energy by the example of rubbers of solution polymerization. The results of the study can be used in the development of software complexes for intelligent energy systems that allow tracking the dynamics of consumption and losses of energy resources. Using the results allows you to determine the optimal parameters of energy consumption and identify reserves for improving energy efficiency.

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Differentiated Approach Problems to Innovative Development Management in Russian Regions

Cited by 9 publications

References 15 publications

Cooperation of Science and Business in Order to Organize High-Tech Production in the Regions of the Russian Federation

Cooperation of Science and Business in Order to Organize High-Tech Production in the Regions of the Russian Federation

Management of Sustainable Consumption of Energy Resources in the Conditions of Digital Transformation of the Industrial Complex

Optimization of Energy Consumption in Chemical Production Based on Descriptive Analytics and Neural Network Modeling

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