Land Use and Management
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Abstract
Abstract
The article presents a comprehensive analysis of the efficiency of using the fleet of automotive and special machinery in the institutions of the Melioration Department, based on the example of 30 territorial departments connected to the GLONASS/GPS satellite monitoring system (control.t1-group.ru). The study period covers January–September 2026. The object of the study is 964 units of machinery, divided into automotive transport and special machinery. It was established that the aggregated summary reports of the monitoring system significantly underestimate the actual efficiency of fleet utilization: the actual utilization coefficient is 55% (530 units) versus 32.6% (314 units) according to the system data, since the rigid criterion of "activity over the last 3 days" does not take into account the seasonality and work schedules of special machinery. It was revealed that 35% of the fleet (341 units) has not been used for more than two years or has no data, and 10% (93 units) are in the "grey zone" (activity in 2024–2025). Automotive transport is used more efficiently than special machinery (60.5% versus 51.9%). Donor departments (8D, 14K, 18R, 6V, 27S, 17P) with a redistribution potential of up to 434 units and recipient departments (30Ch, 13K, 22S, 24S) with high fleet utilization were identified. An algorithm for machinery redistribution was developed, including pool formation, status verification, application submission, commission decision, and utilization control. The practical significance lies in the possibility of increasing the overall fleet utilization coefficient and optimizing budget costs for machinery maintenance.
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@article{Mischenko2026ANALYSIS,
title = {ANALYSIS OF THE EFFICIENCY OF USING THE VEHICLE AND SPECIAL EQUIPMENT PARK IN INSTITUTIONS OF THE LAND RECLAMATION DEPARTMENT (USING THE EXAMPLE OF 30 TERRITORIAL DEPARTMENTS CONNECTED TO THE MONITORING SYSTEM) STUDY PERIOD: 01.01.2026 – 01.09.2026},
author = {Nikolay Mischenko and Stanislav Shestakov},
journal = {Moscow Economic Journal},
year = {2026},
doi = {10.55186/2413046x_2026_11_8_135},
url = {https://doi.org/10.55186/2413046x_2026_11_8_135}
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