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ECONOMY, ORGANIZATION AND MANAGEMENT
ArticleName Assessment of Russian peat industry using data analytics and intelligent text processing
DOI 10.17580/gzh.2024.11.08
ArticleAuthor Misnikov O. S., Timofeev A. E.
ArticleAuthorData

Tver State Technical University, Tver, Russia

O. S. Misnikov, Dean, Doctor of Engineering Sciences, oleg.misnikov@gmail.com
A. E. Timofeev, Candidate of Engineering Sciences, Associate Professor

Abstract

This study provides a comprehensive review of informational sources and formulates prerequisites for increasing peat production and processing volumes in the Russian Federation. The statistical analysis of the current situation in peat production in Russia revealed the trends in extraction volumes, structural composition and economic efficiency of peat products. The PolyAnalyst digital data analytics platform was utilized to process large datasets, including both structured and unstructured data, to create an integrated overview of the peat industry. The study identifies the primary demand for peat products, predominantly driven by agricultural needs, particularly for enhancing soil fertility. The causes of the decline in extraction and use of fuel peat are highlighted and examined. The share of advanced-processed peat products is minimal, comprising only 0.6% of the total output. The authors identified and grouped existing legal entities operating within the peat industry, followed by the calculation and analysis of specific indicators to evaluate the condition of major peat enterprises in the Russian Federation. Given their current economic conditions, the likelihood of achieving significant growth in peat production through internal resources is low. Considering the complexities and risks associated with peat extraction, it is required to elaborate effective state support mechanisms. For the sustainable development of peat enterprises and for their staffing with qualified technical personnel, the quantitative and qualitative improvements in the higher and secondary specialized education systems are required.

keywords Peat extraction, peat processing, peat enterprises, peat products, digital analytical platform, data analytics, semi-structured and unstructured data, key enterprises
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