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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/19529
Title: A data analytic-based logistics modelling framework for E-commerce enterprise
Authors: Verma, Abhishek
Keywords: Management
E-commerce
Data analytics
Machine learning (ML)
Supply chain
Facility location
Issue Date: Jan-2022
Publisher: Taylor & Francis
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.
URI: https://www.tandfonline.com/doi/full/10.1080/17517575.2022.2028195
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/19529
Appears in Collections:Department of Management

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