Formation of strategic alternatives for the development of regional production and economic systems in industrial parks

. The article presents the results of research on the formation of strategic alternatives for the development of regional production and economic systems in industrial parks within the framework of the internal rating management mechanism. A generalized scheme of cognitive modeling is proposed, which is based on the synthesis of methods of cognitive analysis, principal components, expert analysis, econometric modeling, which makes it possible to increase the validity of the concepts of the cognitive model and scenarios for the development of regional production and economic systems in the system of industrial parks. The presented cognitive model makes it possible to develop scenarios for the implementation of strategic alternatives for the development of regional production and economic systems, evaluate their effectiveness, and choose the most appropriate development strategy for the current situation, ensuring their sustainable functioning in the system of industrial parks.


Introduction
The development of regional production and economic systems, such as the coalmetallurgical industry in the Kemerovo Region -Kuzbass, based on the formation of industrial parks, i.e., ready-made land plots with the necessary production infrastructure, is a promising form of investment attraction and economic development for industrialised, industrially developed regions.In the basis of extrapolation of the implementation of such projects we take into account the already existing realised experience.
The main subjects of this process are regional production and economic systems, which are understood as both a separate enterprise and an integrated group of enterprises of one or different areas of activity, having organisational and/or economic unity with centralised management, as well as delegation of authority to structural units in terms of decision-making [1].

Materials and Methods
In the course of the study, the authors used the rating approach based on a comprehensive comparative analysis of dynamically developing systems.The rating approach was developed due to the need to control the values of a significant number of indicators in the analysis of economic systems and to make informed management decisions by potential stakeholders [2].
The scheme of interrelation of blocks and stages of the mechanism of internal rating management of RPES development in the IP system, part of which is the formation of strategic alternatives for RPES development, is shown in Fig. 1.
The purpose of this mechanism is to diagnose the state of the external and internal environment of RPES-resident IP, to choose a development strategy that ensures its sustainable development.Source: compiled by the authors As shown by the authors' spatial rating analysis, the most vulnerable positions and a high level of risks and threats are characterised by RPES of developing IP tIPa "greenfield".The dynamic rating analysis of RPES-representatives of clusters allowed to draw a conclusion about the possible refraction of negative trends in the development of RPES of developed and developing IP tIP "brownfield" in the forecast period.
However, for RPES-representatives of the IP type "greenfield" the assessment of inertial dynamics remains negative.This situation indicates the weak efficiency of the adopted development strategy, the need to develop alternative development scenarios, which is the content of block 4 of the proposed mechanism of internal rating management of RPES development in the IP system (Fig. 1).
At the initial stage of this block of the mechanism, the construction of a cognitive model of the level of RPES development in the system of IP functioning is carried out.Cognitive modelling includes: justification of the system of target, basic exogenous and endogenous factors, which are taken into account in the construction of the orgraph; construction of the cognitive model -a weighted oriented graph; evaluation of system indicators of the cognitive model [3].

Data and primary analysis
The developed approach was tested on the data of 150 functioning industrial parks of the Russian Federation for 2019; RPES data of industrial parks-representatives of industrial park groups for 2015-2019 based on official statistics of the geographic information system [4].Data processing was carried out using the Statistica software environment.

Results and Discussion
The review of literature sources has shown the lack of a unified methodological approach to the assessment of sustainable development of RPES [5][6][7][8].The very concept of sustainable development of RPES has no unambiguous interpretation and is considered from the perspective of systemic, resource, adaptive, equilibrium approach, etc.The system approach assumes the interpretation of sustainability as a systemic characteristic that allows achieving the set goals in the conditions of risks and threats within the specified deviations.The second approach emphasises the sustainability potential, the availability of resource support to maintain a sustainable development trajectory.The third approach is based on the analysis of adaptive properties of RPES, which allow changing the structure and parameters that ensure its viability.The equilibrium and most widespread approach is based on the assessment of the system's ability to maintain an equilibrium, balanced, upward trajectory of development.The ambiguity of the interpretation of the concept of "sustainable development" is expressed in the diversity of methodological approaches to assessing the sustainability of RPES development.
Thus, in the work of Averin O.I., Gudkov D.D. as levels of assessing the sustainability of RPES development are identified: the sustainability of the external environment of RPES, the sustainability of the internal environment of RPES, which includes financial and economic, environmental and social sustainability [5].The authors Zhurova L.I., Toporkov A.M. emphasise the economic sustainability of RPES development [6].Noting the effectiveness of the authors' approaches that investigate marketing, production-technological, financial-economic, organisational, environmental, social, innovation-investment, etc. factors of sustainable development of RPES [7], it is necessary to say about the priority of the financial and economic component in assessing the sustainability of RPES development, since it is this component that largely determines its viability as an economic system.The importance of the financial and economic component in assessing the sustainability of RPES development is emphasised in a large number of scientific papers and, in particular, in the works [8][9][10][11][12].It is this component that will be emphasised in the study.
After the formation of a preliminary list of indicators of sustainability of RPES development, including the "core" indicators with the frequency of mentioning them in more than 60% of cases, their informativeness is assessed.For this purpose, the above algorithm is used in the paper.
The authors made a selection of target factors for RPES-resident industrial different groups of IP: developed and developing categories "brownfield" and "greenfield".
Table .1 shows the results of data processing of RPES-residents of the Obninsk Industrial Park, which belongs to the group "Developing IP of "greenfield" category.The data of Table 1 show that the most significant target factors for RPES-residents of the analysed IP group, which should be taken into account in the cognitive model, are indicators of the level of business activity, management quality and financial stability.
To select exogenous factors of the cognitive model at the meso-level, the authors used the results of discriminant analysis of IP clusters with different levels of RPES performance in the IP system.The statistically significant variables that provide the distinction between clusters with high and low level of efficiency of RPES functioning in the IP system include: renting out ready-made production facilities, participation in regional state programmes, profit tax incentives, existing production facilities intended to accommodate residents, free area of production real estate, total area of office real estate intended to accommodate residents, source of heat energy, gas capacity, and the total area of office real estate intended to accommodate residents.
The selection of exogenous factors at the macro level and endogenous factors of the model was carried out with the help of the algorithm for building the information model, which is based on the procedures of expert analysis (ranking and preference methods).The experts named the following as the most significant macro-level factors: system support for the development of industrial parks; demand in the domestic market, development of import substitution.The experts identified as the dominant endogenous factors: business reputation of the enterprise; involvement in the system of technological relations and customer loyalty; competitiveness of products (services); introduction of innovations in production, contributing to the growth of efficiency of resource utilisation of both individual RPES and IP as a whole; quality and level of innovativeness of the management technologies used; experience and qualification of personnel; communication and information strategy.
The final system of factors, obtained on the basis of the method of principal components and expert analysis is shown in Table 2 Location and level of transport infrastructure development (distance to the nearest city, distance to regional centre, etc.) Participation in state and regional programmes (financial and administrative support) Tax benefits for IP residents  17 Basic services of the management company (leasing of production facilities, etc.) Production real estate (existing production facilities designed to accommodate residents, vacant area of production real estate)

𝑥 21
Source: compiled by the authors Thus, the result of the first step of cognitive model building is a list of the most significant target, basic internal (endogenous) and external (exogenous) factors.
Next, the cognitive model is constructed -a weighted oriented graph.The developed oriented graph is shown in Fig. 2. The factors presented in Table 2 are the vertices of the orgraph, the arrows reflect the cause-effect relationships.Direct cause-effect relationships (with the growth of the factorcause, the values of the factor-effect increase) are shown by solid lines, inverse cause-effect relationships (with the growth of the factor-cause, the values of the factor-effect decrease) are indicated by dotted lines.The linguistic scale shown in Table 3 is used to assess the initial level and significance of the influence of factors.Source: [13] Table 4 gives the adjacency matrix of the vertices of the cognitive model orgraph.Source: compiled by the authors Thus, the proposed cognitive model is the basis for the development of RPES development scenarios in the system of IP functioning (Fig. 1).The scenario is understood as a change in the basic target indicators of the RPES development level due to changes in the control variables and forecast background factors.The basic (based on the search forecast) and alternative (based on the normative forecast) scenarios of change in the level of RPES development in the IP system have been developed.

Conclusions
The formation of strategic alternatives is part of the presented scientific and practical approach to the construction of spatial and dynamic rating assessment of the level of sustainability of RPES functioning in the system of industrial parks, taking into account the identified IP clusters: developing "brownfield"; developed "brownfield"; developing "greenfield"; developed "greenfield".The proposed approach is based on the synthesis of methods of multivariate analysis ("centre of gravity", level of development, cluster analysis) and forecasting (analytical trend smoothing, models with switching).The developed approach was tested on data from 150 IP and 30 RPES-resident IP formed clusters.The results obtained made it possible to identify the most vulnerable RPES groups to risks and were used in the formation of a strategy for the development of sustainable development of RPES in the IP system.

Fig. 1 .
Fig. 1.Internal rating management mechanism for RPES development in the IP system

E3SFig. 2 .
Fig. 2. Oriented graph of the cognitive modelSource: developed by the authors

Table 2 .
Factors accounted for in the cognitive model

Table 3 .
Linguistic scale to assess the initial level and significance of the influence of factors