Assistance of Internet of Things to Intelligent Business Management Model of Supply Chain Finance and Modern Logistics Enterprises

IF 0.5 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

International Journal of Data Warehousing and Mining Pub Date : 2023-05-19 DOI:10.4018/ijdwm.323189

Qing Li

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引用次数: 0

Abstract

Since its birth, supply chain finance (SCF) has made contributions to the development of small and medium-sized enterprises, but it also faces many challenges in the development process. With the development and continuous progress of the internet and information technology, it has also opened up new ways for urban development and innovation. This article introduced the background of intelligent business model, conducted academic research and summary on the keywords of SCF and the internet of things (IOT), and then summarized urban analysis by combining AI and big data. Then it put forward the business model factor analysis of SCF and modern logistics enterprises. At the end of the article, the simulation experiment was carried out, and the experiment was summarized and discussed. The experimental results showed that the average transaction cost of the new business model was 3.5 lower than that of the traditional business model. With the continuous development of artificial intelligence technology and big data technology, urban planning is also facing new opportunities and challenges.

查看原文本刊更多论文

物联网助力供应链金融和现代物流企业的智能商业管理模式

供应链金融自诞生以来，为中小企业的发展做出了贡献，但在发展过程中也面临着诸多挑战。随着互联网和信息技术的发展和不断进步，也为城市的发展和创新开辟了新的途径。本文介绍了智能商业模式的背景，对SCF和物联网(IOT)的关键词进行了学术研究和总结，并结合人工智能和大数据对城市分析进行了总结。然后对供应链物流与现代物流企业的商业模式因素进行了分析。在文章的最后进行了仿真实验，并对实验进行了总结和讨论。实验结果表明，新商业模式的平均交易成本比传统商业模式低3.5。随着人工智能技术和大数据技术的不断发展，城市规划也面临着新的机遇和挑战。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

2.40

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving