Methods for a comprehensive assessment of the development of the creative sector of the regional economy for AHSITS

Aim. The work aimed to develop conceptual methods for a comprehensive assessment of the creative sector of the regional economy as an element of a promising automated hardware and software information and telecommunications system for management decision making support (AHSITS) within formulating socio-economic development strategies at the regional level.

Objectives. The work seeks to substantiate the feasibility of focusing regional socio-economic development strategies on the most promising segments of the economy, primarily on the creative industries sector segments that are relevant to the region; to demonstrate the need to develop a comprehensive methodology for an automated dynamic assessment of the achieved level of development of the creative industries in the region; to consider current methods for assessing the level of development of the creative industries used in Russia and other countries; to develop a conceptual framework for managing the socio-economic development of regional socio-economic systems (RSES), highlighting the factor influencing the creative economy sector, while it will become part of a promising systemic mechanism for managing the RSES socio-economic development, which includes the full range of industries and sectors of the regional economy. The work also seeks to propose monitoring objects used in the methodology for a comprehensive assessment of the creative sector of the regional economy (“Factors influencing creative industries” and “Indicators for the development of creative industries”), as well as specific regional socio-economic indicators, including those related to the creative industries sector; to propose a concept for tracking data in AHSITS, including from the perspective of technical methods for dynamic tracking and obtaining information by the system on selected indicators; to characterize the proposed model for aggregating and processing the received incoming data to form an integrated assessment of the achieved level of overall development of the management object; as well as to reveal the specifics of creating a digital twin of the regional creative economy.

Methods. The study employed logical analysis and synthesis, logical abstractions, modeling, a systems methodological approach, comparative analysis, structural analysis, statistical data processing, expert assessment, and graphical interpretation.

Results. The work demonstrated the critical significance of scientifically substantiated concentration of constrained regional resources distributed within the socio-economic development strategies, primarily in promising and underutilized growth areas of the regional economy, often located in the creative industries sector. Emphasis is placed on the importance of leveraging the benefits of digitalization in this process. The authors propose a conceptual transmission scheme within a promising information and organizational mechanism for the overall management of regional socio-economic development, and the level of development of the creative economy factor as an element influencing the RSES. The main methods for assessing the level of development of creative industries used in Russia and other countries are examined, highlighting their advantages and disadvantages. This paper describes the author’s comprehensive methodology for automated dynamic assessment of the achieved level of development of a region’s creative industries, which incorporates regional factor indicators influencing the development of the creative industries sector and indicators of the achieved level of creative industries development, including specific regional socio-economic indicators related to both the creative industries sector and the RSES as a whole. Methods for dynamic tracking and obtaining information on  selected indicators by the AHSITS are formulated in the paper. Furthermore, the work proposes a model for aggregating and processing the initial data obtained, forming an integrated assessment of the achieved level of overall development of the creative industries in the region using the multivariate mean method. This paper revealed the key concepts and features of  generating a digital twin of the regional creative economy.

Conclusions. In order to support effective management decision-making by government agencies and reduce transaction costs in the creation and adjustment of strategic planning documents, it is advisable to implement an automated mechanism for assessing dynamically the region’s creative economy sector at the regional level during its management. This mechanism would automatically acquire, store, and process big data streams as a set of significant variables that serve as indicators of functioning of this complex socio-economic system. The authors propose implementing this mechanism using the concept of a digital twin, that is, an adaptive cybernetic system that tracks and transforms the inputs of the received big data array into scientifically substantiated assessments of the current state, submitted to government authorities interactively, regularly, and timely, as well as multivariate forecasts for the sector’s development, and draft proposals for decision-making on the creation and adjustment of strategic planning documents. The core of this system is a methodology for a comprehensive assessment of the region’s creative industries sector (hereinafter referred to as the Methodology).

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