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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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ASSESSING THE EFFECTIVENESS OF DIGITAL TECHNOLOGIES IN LOGISTICS PROCESS MANAGEMENT

Authors: Omonov Bakhodir Shomirzayevich; ,Jurayev Jamshid Mekhrojidin ogli; Wordly Knowledge Publishing Centre;

ASSESSING THE EFFECTIVENESS OF DIGITAL TECHNOLOGIES IN LOGISTICS PROCESS MANAGEMENT

Abstract

This study examines the effectiveness of digital technologies in managing logistics processes, with a particular focus on small and medium enterprises (SMEs) in Uzbekistan. The research analyzes the role of key information systems, including Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM), as well as data analytics tools in improving operational efficiency, demand forecasting, and supply chain coordination. A mixed-method approach combining comparative and statistical analysis is applied to evaluate the impact of digitalization on key performance indicators such as transportation costs, delivery time, and service reliability. The results indicate that the implementation of digital technologies can reduce logistics costs by 15–25%, improve delivery accuracy, and enhance real-time visibility of supply chains. However, challenges such as high implementation costs, limited digital infrastructure, and lack of qualified personnel remain significant barriers in the Uzbekistan context. The study concludes that the integration of digital solutions is essential for increasing competitiveness and ensuring sustainable development of logistics systems in developing economies.

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    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).
    0
    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.
    Average
    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