Digitalization as a tool for managing innovation-driven sustainable development in the Arctic industrial sector.

The sustainable development of industrial production is particularly critical in the Arctic regions. However, achieving this goal requires effective management, which can be improved through digitalization based on algorithmic processes. Accordingly, this study aims to substantiate and outline the key stages of algorithmizing the management of sustainable industrial development. The research identifies two essential conditions for effective management: first, establishing the relationship between technological advancement and sustainability levels; second, quantitatively determining sustainability levels. The study demonstrates that these objectives can be addressed using the methodology of economic analysis applied to technological renewal in production. The proposed algorithmization process consists of four stages. The first stage involves analyzing industrial activity in the Arctic regions over a retrospective period of at least 15 years to identify trends in material productivity, capital productivity, and technological development. The second stage employs a graphical life cycle model of technological development and a scoring method to perform a quantitative assessment of industrial sustainability, both overall and by specific sectors. The third stage involves developing an analytical simulation model to project future sustainability levels based on industrial investment capacity and potential financial support from regional and national governments. A block diagram of this simulation model is presented, along with an overview of the calculation procedure. Finally, the fourth stage formulates three potential industrial development scenarios, each achieving different levels of sustainability. Future research will focus on implementing the simulation model programmatically and conducting scenario-based calculations for the industrial sector in the Arctic.