| Title |
How Business Intelligence Enables E-commerce: Breaking the Traditional E-commerce Mode and Driving the Transformation of Digital Economy |
| ID_Doc |
70305 |
| Authors |
Pan, CL; Bai, X; Li, FY; Zhang, DL; Chen, H; Lai, QT |
| Title |
How Business Intelligence Enables E-commerce: Breaking the Traditional E-commerce Mode and Driving the Transformation of Digital Economy |
| Year |
2021 |
| Published |
|
| DOI |
10.1109/ECIT52743.2021.00013 |
| Abstract |
To pursue the sustainable development of the economy, resources and society, we should adhere to the guidance of technology leading and promote the digital transformation with the help of the opportunity of the industrial Internet. As an important field of digital transformation, e-commerce has great potential in various industries, such as service advantages and marketing methods. At present, large e-commerce platforms (Alibaba, JD, etc.) have small achievements, but there are few studies on the integration of e-commerce AI changing the e-commerce model, especially the lack of systematic review of digital marketing and digital transformation. This paper mainly discusses the application of AI in e-commerce platforms to form a diversified new e-commerce model to guide the transformation of traditional e-commerce. Based on this, 156 articles were selected from the Web of Science (WoS) database to map co-word clustering and analyze their annual trends, topics, publication locations, etc. Using scientific metrology to demonstrate the possibility and practicability of the research content in related fields will help Business managers to master how intelligent technology can enable digital e-commerce, achieve digital transformation and sustainable development, and take reasonable measures accordingly. |
| Author Keywords |
commerce; Business Intelligence; digital transformation; systematic literature review |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science & Humanities (CPCI-SSH) |
| EID |
WOS:000672805700006 |
| WoS Category |
Business; Computer Science, Interdisciplinary Applications; Management |
| Research Area |
Business & Economics; Computer Science |
| PDF |
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