Supply chain financial risk and influence under Internet of Things technology

2021 ◽  
Author(s):  
Yiping Shi
IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 4091-4100 ◽  
Author(s):  
Cai Shousong ◽  
Wang Xiaoguang ◽  
Zhao Yuanjun

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhaoyang Wu ◽  
Shiyong Wang ◽  
Hong Yang ◽  
Xiaokui Zhao

In recent years, with the rapid development of the global economy and the development trend of more and more stable, well-developed network communications, online shopping has become an increasingly common way; as a result, the logistics industry has emerged from many industries and has become one of the most popular industries. However, due to the extensive involvement of the logistics industry, the overly complex technology, and the huge amount of data and information, the security of logistics has become one of the hot topics of special concern. Based on the background of an intelligent environment, this paper constructs a supply chain financial logistics supervision system based on Internet of Things technology. This article refers to the research experience of previous scholars, briefly introduces the theoretical knowledge of the Internet of Things technology, smart environment, and supply chain finance, and makes a certain analysis of the logistics supervision system. We collect and calculate logistics data through the wolf group hunting and siege formula in the wolf group algorithm and analyze the application performance of the logistics supervision system in reality. Then, we briefly designed the system architecture diagram of the logistics supervision system and compared the freight situation of the logistics supervision system before and after and statistics on the deployment of the logistics supervision system in customs, docks, airports, stations, and other places from 2015 to 2019. Finally, a comparative analysis of the performance of wolf pack algorithm and other algorithms was performed under different path planning. The final result shows that the logistics supervision system has important practical value in the logistics industry; in addition, the deployment of logistics supervision systems in customs, terminals, and other places has increased year by year from 2015 to 2019.


Author(s):  
Xu Sun ◽  
Kunliang Shu

AbstractThere are often agricultural product quality problems in the production and circulation of agricultural products. Therefore, there are more and more people on the agricultural product supply chain based on the Internet of things. This article mainly introduces the research on the perception data fusion of agricultural product supply chain in the context of the Internet of things. This is a simple research result based on the Internet of things technology platform, which analyzes the current status of the product according to market demand. After analysis and comparison, a sensory data fusion model suitable for the supply chain of agricultural products is obtained, and information technology based on the Internet of things is used to transform and optimize the Internet of things in the circulation of agricultural products. The experimental results of this article show that data fusion technology based on the Internet of things can solve and track 69.45% of the problem of unknown sources of agricultural products, improve the supply efficiency of agricultural products by 43%, reduce the health problems of agricultural products by 31.24%, and reduce the prices of agricultural products by 13–20%. Improving logistics efficiency can save 5 million tons of agricultural products.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xiaoyan Li

In recent years, the increasing degree of economic globalization has provided a broader platform for the development of enterprises, but it also made enterprises bear more and more pressure of market competition. This paper mainly studies the application of improved nearest neighbor propagation algorithm based on Internet of Things technology in financial management early warning. This paper selects the mixed unbalanced panel data of 40 companies from 2006 to 2008 as the overall research sample. After eliminating the outliers and the samples of companies without data for two consecutive years, 390 datasets of 30 companies are selected as the modeling samples. The selection of risk early warning indicators should follow the following six principles: comprehensiveness, importance, scientificity, objective quantification, comparability, and operability. The standard deviation of index data is calculated to compare the strength and improve the integrity and effectiveness of the value. In this paper, Delphi expert analysis method is used to invite experts who have certain research in this field to propose the corresponding independent evaluation index scheme. On the premise of taking the summary results as the reference, the index contents which are not representative and different from the actual requirements are deleted, so as to finally determine the index system of the risk assessment scheme. The data show that the final correct rate of the financial risk early warning model can reach 91% and the total number of judgments is 200, where 182 are correct and only 18 are wrong. The results show that the establishment of a good financial risk early warning system can help enterprises better find and deal with risks and makes enterprises develop healthily.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hongxiu Cui

In this paper, through the intelligent research of the whole process of logistics and distribution with the Internet of Things supply chain, we study how to improve the development of the cold chain, reduce the loss in circulation, improve the social and economic benefits, and carry out intelligent information collection, monitoring, management, and information tracing of the whole cold chain. This paper analyzes and empirically studies the impact of key technologies of the Internet of Things in cold chain coordination from the perspective of building an intelligent cold chain coordination system with the Internet of Things technology. This paper analyzes the current situation of cold chain logistics and the impact that the application of IoT technology will have, explains that IoT technology can improve the intelligence level of the cold chain, and then introduces the application of intelligent cold chain logistics under IoT orientation, combining the process of cold chain logistics with the three-layer architecture of IoT technology. By extracting the key technologies of IoT perception layer, network layer, and intelligence layer, the intelligent cold chain coordination system based on IoT technology is constructed, and then, the correctness of the system is verified, to have some reference and evaluation for the cold chain construction. The system was then verified to have some reference and guidance significance for the construction and evaluation of the cold chain. The results of this paper are more accurate and more efficient.


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