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Innovative Mesosystems Algorithm for Sustainable Development Priority Areas Identification in Industry Based on Decision Trees Construction

Author

Listed:
  • Aleksey I. Shinkevich

    (Logistics and Management Department, Kazan National Research Technological University, 420015 Kazan, Russia)

  • Irina G. Ershova

    (Department of Finance and Credit, Southwest State University, 305040 Kursk, Russia)

  • Farida F. Galimulina

    (Logistics and Management Department, Kazan National Research Technological University, 420015 Kazan, Russia)

  • Alla A. Yarlychenko

    (Logistics and Management Department, Kazan National Research Technological University, 420015 Kazan, Russia)

Abstract

Globally, assessing sustainable development methodology is kept in sustainable society index (SSI) format, but at the level of meso- and microsystems it remains undeveloped. The aim of the study is to typologize innovative mesosystems in Russian industry in the context of sustainable development based on the CART algorithm and to develop an algorithm for identifying priority areas of sustainable development. The research methods applied included formalization, a systematic approach, and the CART algorithm (calculation of the Gini index, training sample segmentation, the use of a recursive function and regression assessment). As a result of the study, the algorithm for the differentiated identification of innovative mesosystems sustainable development priority directions in industry based on the unique author’s methodology (ISDI) is proposed. The predominance of mesosystems with weak level of sustainable development requiring state support in favor of such mesosystems restructure is revealed. The novelty of the research lies in the development of new science-based solutions to ensure an accelerated transition of industry to the path of sustainable development. The difference of the author’s approach from the provisions known in science is the inclusion of environmental innovations in the mechanism for managing the sustainable development of innovative mesosystems and subsequent accounting in the process of mathematical processing of an array of data, which determines the uniqueness of the constructed decision trees.

Suggested Citation

  • Aleksey I. Shinkevich & Irina G. Ershova & Farida F. Galimulina & Alla A. Yarlychenko, 2021. "Innovative Mesosystems Algorithm for Sustainable Development Priority Areas Identification in Industry Based on Decision Trees Construction," Mathematics, MDPI, vol. 9(23), pages 1-18, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:23:p:3055-:d:689874
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    References listed on IDEAS

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    Cited by:

    1. Aleksey I. Shinkevich & Alsu R. Akhmetshina & Ruslan R. Khalilov, 2022. "Development of a Methodology for Forecasting the Sustainable Development of Industry in Russia Based on the Tools of Factor and Discriminant Analysis," Mathematics, MDPI, vol. 10(6), pages 1-16, March.
    2. Yaliu Yang & Yuan Wang & Cui Wang & Yingyan Zhang & Cuixia Zhang, 2022. "Temporal and Spatial Evolution of the Science and Technology Innovative Efficiency of Regional Industrial Enterprises: A Data-Driven Perspective," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    3. Lefa Zhao & Yafei Zhu & Tianyu Zhao, 2022. "Deep Learning-Based Remaining Useful Life Prediction Method with Transformer Module and Random Forest," Mathematics, MDPI, vol. 10(16), pages 1-15, August.
    4. Monica Aureliana Petcu & Liliana Ionescu-Feleaga & Bogdan-Ștefan Ionescu & Dumitru-Florin Moise, 2023. "A Decade for the Mathematics : Bibliometric Analysis of Mathematical Modeling in Economics, Ecology, and Environment," Mathematics, MDPI, vol. 11(2), pages 1-30, January.
    5. Aleksey I. Shinkevich & Irina G. Ershova & Farida F. Galimulina, 2022. "Forecasting the Efficiency of Innovative Industrial Systems Based on Neural Networks," Mathematics, MDPI, vol. 11(1), pages 1-25, December.

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