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ZENODO
Article . 2021
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2021
License: CC BY
Data sources: Datacite
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Административное управление и оптимизация бизнес-процессов в траковом бизнесе США

Administrative management and optimization of business processes in the US truck business

Административное управление и оптимизация бизнес-процессов в траковом бизнесе США

Abstract

The article discusses modern methods of administrative management and optimization of business processes in the US trucking business. The analysis of the key problems of the industry, including rising operating costs, staff shortages, regulatory changes and the need for digital transformation. The successful cases of leading companies that have implemented advanced technologies to improve logistics efficiency are presented. Special attention is paid to the implementation of automated control systems, autonomous trucks and alternative fuels. The economic efficiency of digitalization and optimization strategies aimed at reducing costs and increasing competitiveness are substantiated.

В статье рассматриваются современные методы административного управления и оптимизации бизнес-процессов в траковом бизнесе США. Проведен анализ ключевых проблем отрасли, включая рост операционных затрат, кадровый дефицит, регуляторные изменения и необходимость цифровой трансформации. Представлены успешные кейсы ведущих компаний, внедривших передовые технологии для повышения эффективности логистики. Особое внимание уделено внедрению автоматизированных систем управления, автономных грузовиков и альтернативных видов топлива. Обоснована экономическая эффективность цифровизации и стратегий оптимизации, направленных на сокращение затрат и повышение конкурентоспособности.

Keywords

траковый бизнес США, IoT, оптимизация бизнес-процессов, AI-аналитика, операционные затраты, автономные грузовики, транспортная логистика, транспортные управляющие системы, цифровизация

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average