Pregledni rad
https://doi.org/10.7307/ptt.v37i1.355
Machine Learning Application for Improving Customer and Postal Logistics Operator Satisfaction in Urban Areas – A Review
Adisa MEDIĆ
; University of Sarajevo, Faculty of Traffic and Communications
Amel KOSOVAC
; University of Sarajevo, Faculty of Traffic and Communications
Ermin MUHAREMOVIĆ
; University of Sarajevo, Faculty of Traffic and Communications
Muhamed BEGOVIĆ
; University of Sarajevo, Faculty of Traffic and Communications
Sažetak
Machine learning (ML) is a crucial component of artificial intelligence that has recently attracted attention for its application in logistics. ML algorithms are used on large datasets. They create logic correlations among given data and provide predictions of specific values. This research paper aims to conduct a systematic literature review to showcase the potential applications of machine learning in urban logistics systems, specifically focusing on enhancing satisfaction for postal logistics operators and their customers. The authors used various research publication databases in this context (Web of Science, Scopus, Google Scholar etc). The analysis of different models provides insights into diverse aspects, such as predicting product prices and types of cargo, evaluating user satisfaction, forecasting user departures, assessing optimal geographical locations for implementing postal centres, predicting purchase times before online orders, estimating delivery times in the last phase of the logistics chain and more. The significance of this research is highlighted through the identification of shortcomings in existing literature, offering guidelines for future research in developing new machine learning model for optimal operator selection. This model aims to achieve improvements in both customer and operator satisfaction simultaneously.
Ključne riječi
machine learning; urban logistics; postal logistics operator; literature review
Hrčak ID:
329155
URI
Datum izdavanja:
30.4.2025.
Posjeta: 0 *