A brief survey of machine learning and deep learning techniques for e-commerce research

X Zhang, F Guo, T Chen, L Pan, G Beliakov… - Journal of Theoretical …, 2023 - mdpi.com
The rapid growth of e-commerce has significantly increased the demand for advanced
techniques to address specific tasks in the e-commerce field. In this paper, we present a …

Which industrial sectors are affected by artificial intelligence? A bibliometric analysis of trends and Perspectives

L Espina-Romero, JG Noroño Sánchez… - Sustainability, 2023 - mdpi.com
In recent times, artificial intelligence (AI) has been generating a significant impact in various
industry sectors, which implies that companies must be ready to adjust to this promising start …

Analysis of 105 IT project risks

V Nikolaenko, A Sidorov - Journal of Risk and Financial Management, 2023 - mdpi.com
The article is aimed at increasing the probability of successful IT project completion by
identifying the sources of 105 universal risks as well as establishing cause-and-effect …

A Sales Forecasting Model for New-Released and Short-Term Product: A Case Study of Mobile Phones

S Hwang, G Yoon, E Baek, BK Jeon - Electronics, 2023 - mdpi.com
In today's competitive market, sales forecasting of newly released and short-term products is
an important challenge because there is not enough sales data. To address these …

Enhancing last-mile delivery: a hybrid approach with machine learning techniques that captures drivers' knowledge

MA Carvalhosa, MT Pereira, MG Pereira… - … Journal of Logistics …, 2024 - Taylor & Francis
The rise of e-commerce has transformed last-mile delivery, with companies' prioritising
faster, more flexible options and implementing innovations such as route optimisation …

Optimizing e-commerce Supply Chains with Categorical Boosting: A Predictive Modeling Framework

J Sayyad, K Attarde, N Saadouli - IEEE Access, 2024 - ieeexplore.ieee.org
Managing various aspects of the Supply Chain (SC) has become increasingly challenging in
today's complex business landscape. To improve profitability, boost sales, and enhance …

WSN-Assisted Consumer Purchasing Power Prediction via Barracuda Swarm Optimization-Driven Deep Learning for E-Commerce Systems

L Almuqren, N Alruwais, AA Alhashmi… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The conventional e-commerce business chain is undergoing a transformation centered on
short videos and live streams, giving rise to interest-based e-commerce as a burgeoning …

[PDF][PDF] ADVANTAGES AND CHALLENGES REGARDING THE USAGE OF DRONES IN E-COMMERCE.

DM PETROȘANU, A Pirjan - Journal of Information Systems & Operations …, 2022 - rau.ro
E-commerce has been on the rise in recent years, as more and more businesses have
moved their operations online. There are many advantages to this shift, including increased …

Optimizing E-Commerce with Ensemble Learning and Iterative Clustering for Superior Product Selection

Y Liu, M Wang, G Li, TR Payne, Y Yue… - KSII Transactions on …, 2024 - koreascience.kr
With the continuous growth of e-commerce sales, a robust product selection model is
essential to maintain competitiveness and meet consumer demand. Current research …

Optimizing E-Sports Revenue: A Novel Data Driven Approach to Predicting Merchandise Sales Through Data Analytics and Machine Learning

MA Sufian, J Varadarajan, M Hanumanthu… - Science and Information …, 2024 - Springer
This research work presents a comprehensive approach to predicting merchandise sales in
the rapidly growing E-sports industry. Utilizing a rich dataset for data analytics, comprising of …