A data analytic-based logistics modelling framework for E-commerce enterprise. Issue 6 (3rd June 2023)

• Record Type: Journal Article
• Authors: Verma, Abhishek; Kuo, Yong-Hong; Kumar, M Manoj; Pratap, Saurabh; Chen, Velvet
• Is Part Of: Enterprise information systems. Volume 17:Issue 6(2023)
• Publication Date: 2023-06-03
• Subjects: E-commerce -- data analytics -- machine learning -- supply chain -- facility location -- forecasting; Information storage and retrieval systems -- Periodicals; Management information systems -- Periodicals; Electronic commerce -- Periodicals; 658.4038011
• DOI: 10.1080/17517575.2022.2028195
• Languages: English
• ISSNs: 1751-7575

Abstract

ABSTRACT: Data-driven approaches have noteworthy significance in managing and improving logistics in E-commerce enterprises. This study focuses on the development of an integrated framework to analyse the Brazilian E-Commerce enterprise public dataset. From the analysis, it is found that sellers of Ibitinga city of SP state had the most count of late deliveries where 42 sellers are under-performing in terms of estimated delivery time. Locations of customers and sellers were spotted on a map to get a geographical representation. The proposed framework may help E-Commerce enterprise owners and retail merchants to make better decisions related to sales and E-Commerce enterprise logistics.