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The Rational Use of Water Resources in the Strategy of Industry 4.0

Author

Listed:
  • Natalia A. Kosolapova

    (Southern Federal University)

  • Ludmila G. Matveeva

    (Southern Federal University)

  • Anastasia Y. Nikitaeva

    (Southern Federal University)

  • Lesego Molapisi

    (Botswana Institute for Development Policy Analysis)

Abstract

The article substantiates that the transformation of the world economy associated with Industry 4.0 leads to a significant change in the way resources are used and affects the possibility of implementing the concept of sustainable development. In this regard, a combined analysis of the concept of new industrial development and the concept of sustainable development, as well as an assessment of the current practice of their implementation is required. In this paper, such an analysis was carried out on the example of water resources management. The paper proposes a methodology for assessing the correlation of water management and industrial development levels of regions. This includes the use of both traditional statistical approaches to the analysis of the level of development of economic systems, and elements of data mining. The neural network is constructed in order to estimate the forecasted values of the water intensity of the gross regional product when the indicators of the level of industrial development of the regions change. The results show that the most significant indicators for changing water intensity include advanced production technologies used, the share of value-added to high-tech industries, and innovative activities of organisations.

Suggested Citation

  • Natalia A. Kosolapova & Ludmila G. Matveeva & Anastasia Y. Nikitaeva & Lesego Molapisi, 2021. "The Rational Use of Water Resources in the Strategy of Industry 4.0," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(9), pages 3023-3041, July.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:9:d:10.1007_s11269-021-02889-1
    DOI: 10.1007/s11269-021-02889-1
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    References listed on IDEAS

    as
    1. Lee, Changhun & Lim, Chiehyeon, 2021. "From technological development to social advance: A review of Industry 4.0 through machine learning," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    2. Xinxin Liu & Xiaosheng Wang & Haiying Guo & Xiaojie An, 2021. "Benefit Allocation in Shared Water-Saving Management Contract Projects Based on Modified Expected Shapley Value," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 39-62, January.
    3. Silvestre, Bruno S., 2015. "Sustainable supply chain management in emerging economies: Environmental turbulence, institutional voids and sustainability trajectories," International Journal of Production Economics, Elsevier, vol. 167(C), pages 156-169.
    4. Kopnova, Elena, 2013. "Trend analysis of water use at the metallurgical enterprises of Sverdlovsk region," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 115-126.
    5. Li, Zongmin & Zhang, Qi & Liao, Huchang, 2019. "Efficient-equitable-ecological evaluation of regional water resource coordination considering both visible and virtual water," Omega, Elsevier, vol. 83(C), pages 223-235.
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    Cited by:

    1. Carolina Henao & Jenny Paola Lis-Gutiérrez & Melissa Lis-Gutiérrez & Janitza Ariza-Salazar, 2024. "Determinants of efficient water use and conservation in the Colombian manufacturing industry using machine learning," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-11, December.

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