Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/14966
Title: E-Commerce Business Model Analysis and Success in Urban Areas Using Ai-Distributed Machine Learning
Authors: Sungheetha, Akey
Bharathi, B
Ganesan, D
Karthikeyan, T
Bindu Madhavi, N
Chairma Lakshmi, K R
Keywords: Ai
Business Model
Distributed Machine Learning
E-Commerce
Urban Areas
Issue Date: 2023
Publisher: 2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2023
Institute of Electrical and Electronics Engineers Inc.
Abstract: This study presents a comprehensive analysis of the e-commerce business model success in urban areas through the integration of AI distributed machine learning techniques. The rapid growth of e-commerce in urban settings has led to increased competition among businesses striving to capture market share. To achieve a competitive edge, companies are increasingly turning to AI and machine learning to enhance various aspects of their operations. This research examines the symbiotic relationship between e-commerce success and AI technologies, specifically focusing on distributed machine learning role in optimizing operations, personalizing user experiences, and predicting market trends. By leveraging real-world case studies and empirical data, this study sheds light on the mechanisms through which AI distributed machine learning contributes to the sustainable development of e-commerce enterprises in urban environments. The findings of this study provide valuable insights for e-commerce businesses, urban planners, and policymakers to formulate strategies that foster a conducive ecosystem for e-commerce success in urban areas. © 2023 IEEE.
URI: https://doi.org/10.1109/RMKMATE59243.2023.10369718
http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/14966
ISBN: 9.79835E+12
Appears in Collections:Conference Papers

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