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Automated Toolkit for Encouraging a Producer to Use Innovative Technologies in Environmentally Oriented Economic Development of Mining Regions

The automated toolkit for assessing environmental and investment attractiveness of a mining region and the results of its application are discussed in the article. This toolkit includes the optimization mathematical model, the algorithms for the interaction between a regional control center and a producer within the territory, as well as the automated software package for their analysis. The use of the optimization mathematical model makes it possible to take into account the maximum economic potential of a producer, which determines, respectively, a mining region’s environment pollution potential. Accounting for environmental risks will allow the control center or other decision makers to identify not only the optimal pattern of eco-economic interaction in the region, but also reflect changes in the environmental and investment climate as a combination of economic potential and involved risks. The model and the algorithms of interaction between a regional control center and a producer, as well as the results of their numerical analysis given in this paper, allow considering this toolkit as an effective decision support tool aimed at improving environmental and investment attractiveness of a mining region by encouraging a producer to use the best available technologies and conserve the natural environment.
- Kuzbass State Technical University Russian Federation
- University of Zurich Switzerland
- University of East Anglia - School of Biological Sciences
- ITÄ-SUOMEN YLIOPISTO Finland
- Plekhanov Russian University of Economics Russian Federation
Environmental sciences, GE1-350
Environmental sciences, GE1-350
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).2 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
