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E-commerce Product Delivery Analysis
Subject area: Science,Engineering and Technology · Area of research: E-commerce
Abstract
This research investigates the delivery mechanisms within e-commerce, particularly concerning the sales and shipment of electronic products. By examining different phases of the e-commerce product lifecycle, the study employs data analysis and machine learning techniques to gain insights into delivery efficiency and effectiveness. Data was sourced from a prominent e-commerce platform and subjected to exploratory data analysis (EDA) to uncover patterns and trends. Subsequently, machine learning algorithms were used to forecast delivery outcomes, with their performance assessed through various metrics. The results reveal significant factors affecting delivery efficiency and offer practical recommendations for enhancing e-commerce logistics.
Keywords
E-commerce, Data Analysis, Product Sales, Shipment, Machine Learning.
References
[1] d from source- https://www.researchgate.net/figure/E-commerce-Data-Analysis_fig3_259575782
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How to cite this paper
@article{1705925,
author = {Jayesh Patil, Yash Deshmukh, Prafulla Pawar, Prachi Pardeshi, Prof. Harshal Patil},
title = {E-commerce Product Delivery Analysis},
journal = {Iconic Research And Engineering Journals},
year = {2024},
volume = {7},
number = {12},
pages = {177-181},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/17059251.pdf},
abstract = {This research investigates the delivery mechanisms within e-commerce, particularly concerning the sales and shipment of electronic products. By examining different phases of the e-commerce product lifecycle, the study employs data analysis and machine learning techniques to gain insights into delivery efficiency and effectiveness. Data was sourced from a prominent e-commerce platform and subjected to exploratory data analysis (EDA) to uncover patterns and trends. Subsequently, machine learning algorithms were used to forecast delivery outcomes, with their performance assessed through various metrics. The results reveal significant factors affecting delivery efficiency and offer practical recommendations for enhancing e-commerce logistics.},
keywords = {E-commerce, Data Analysis, Product Sales, Shipment, Machine Learning.},
month = {June},
}