Predictive algorithms for supply chain management: a comprehensive approach to forecasting delivery times and managing risk

The article delves into the challenges of delivery time management in today's business landscape. The authors underscore the need for precise delivery time forecasts, a key factor in maintaining a competitive edge and meeting customer expectations. They outline various methods for estimating the time of a selected commodity based on historical data, and stress the necessity of modern tools that can adapt to the intricate web of factors influencing delivery times and facilitate swift responses to changes. The following article presents an innovative delivery time forecasting application that integrates advanced predictive algorithms with historical data, current data, and external factors affecting the delivery process. The application was developed to provide more accurate delivery time forecasts and optimize logistics processes. Through advanced technologies, it can consider even the most complex scenarios and changes, allowing companies to plan and manage their logistics operations more effectively.

Authors

Publication Details

Journal
Journal of Modern Science
Published
2024-08-20
DOI
https://doi.org/10.13166/jms/191218
Citations
1
Primary Topic
Quality and Supply Management
Type
article
Field-Weighted Citation Impact
0.53
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article

Predictive algorithms for supply chain management: a comprehensive approach to forecasting delivery times and managing risk

Rafał Szrajnert, J. Stokłosa, Robert Chmura, Dariusz Woźniak et al.
1 citations
Journal of Modern Science
Quality and Supply Management
0.53
article

Predictive algorithms for supply chain management: a comprehensive approach to forecasting delivery times and managing risk

Rafał Szrajnert, J. Stokłosa, Robert Chmura, Dariusz Woźniak, Michał Warszycki
article en
1 citations

Abstract

The article delves into the challenges of delivery time management in today's business landscape. The authors underscore the need for precise delivery time forecasts, a key factor in maintaining a competitive edge and meeting customer expectations. They outline various methods for estimating the time of a selected commodity based on historical data, and stress the necessity of modern tools that can adapt to the intricate web of factors influencing delivery times and facilitate swift responses to changes. The following article presents an innovative delivery time forecasting application that integrates advanced predictive algorithms with historical data, current data, and external factors affecting the delivery process. The application was developed to provide more accurate delivery time forecasts and optimize logistics processes. Through advanced technologies, it can consider even the most complex scenarios and changes, allowing companies to plan and manage their logistics operations more effectively.

Journal of Modern ScienceVol. 57(3)
Industry, innovation and infrastructure
Openalex Percentile: Top 27%
Quality and Supply Management
0.53
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Predictive algorithms for supply chain management: a comprehensive approach to forecasting delivery times and managing risk — Rafał Szrajnert, J. Stokłosa, et al. · Journal of Modern Science (2024) | TGRS Research Map | TGRS