Research on the Application of Big Data Technology in Electronic Commerce Supply Chain

2020 ◽  
Author(s):  
Song Ziang ◽  
Baohua Li
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Electronic Commerce ◽  
Big Data Technology

scholarly journals Pricing Strategies of a Three-Stage Supply Chain: A New Research in the Big Data Era

2017 ◽  
Vol 2017 ◽  
pp. 1-16
Author(s):  
Pan Liu
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Stackelberg Game ◽  
Chain Model ◽  
Pricing Strategies ◽  
Supply Chain Model ◽  
Investment Cost ◽  
New Research ◽  
New Situation ◽  
Big Data Technology

In the Big Data era, Data Company as the Big Data information (BDI) supplier should be included in a supply chain. In the new situation, to research the pricing strategies of supply chain, a three-stage supply chain with one manufacturer, one retailer, and one Data Company was chosen. Meanwhile, considering the manufacturer contained the internal and external BDI, four benefit models about BDI investment were proposed and analyzed in both decentralized and centralized supply chain using Stackelberg game. Meanwhile, the optimal retail price and benefits in the four models were compared. Findings are as follows. (1) The industry cost improvement coefficient, the internal BDI investment cost of the manufacturer, and the added cost of the Data Company on using Big Data technology have different relationships with the optimal prices of supply chain members in different models. (2) In the retailer-dominated supply chain model, the optimal benefits of the retailer and the manufacturer are the same, and the optimal benefits of the Data Company are biggest in all the members.

Customer demand analysis of the electronic commerce supply chain using Big Data

2016 ◽  
Vol 268 (1-2) ◽  
pp. 113-128 ◽  
Author(s):  
Lei Li ◽  
Ting Chi ◽  
Tongtong Hao ◽  
Tao Yu
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Electronic Commerce ◽  
Demand Analysis ◽  
Customer Demand

scholarly journals Research on Supply Chain Financial Risks and Preventive Measures in the Era of Big Data

2020 ◽  
Vol 214 ◽  
pp. 03032
Author(s):  
Weiting Sun ◽  
Puxue Shen
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Financial Institutions ◽  
Financial Risk ◽  
Large Scale ◽  
Theory And Practice ◽  
Privacy And Security ◽  
Internet Applications ◽  
Supply Chain Finance ◽  
Big Data Technology

The emergence of supply chain finance has reduced the financing costs of SMEs. Due to the development of a diversified supply chain financial subject platform, there is a lack of risk control in terms of theory and practice. Big data is generated in Internet applications and combined with information technology to form big data technology. It can provide financial institutions with large-scale data analysis methods and can effectively improve the efficiency and ability of financial institutions to serve supply chain members. However, big data has some problems, such as higher processing cost, lower authenticity, and difficulty in effectively protecting the privacy and security of users. There are many problems with this new development model. This article focuses on the risk problems faced by supply chain finance. It discusses the use of big data technology to effectively solve the supply chain financial risk problems, and gives some measures that can be effectively solved for how to effectively avoid these risk factors. By effectively solving the financial risk problem in the era of big data, it provides guarantee for the benign development of enterprises, and provides a certain reference for researchers engaged in related fields and workers in this field.

Product Quality Tracing in Manufacturing Supply Chain Based on Big Data Technology

2020 ◽  
Vol 13 (4) ◽  
pp. 340-351
Author(s):  
Yin Huang ◽  
Shumin Huang ◽  
Yichen Zhang ◽  
Xue Yang ◽  
Runda Liu
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Product Quality ◽  
Patent Analysis ◽  
Development Mode ◽  
Product Lifecycle ◽  
Whole Process ◽  
Manufacturing Supply Chain ◽  
Process Product ◽  
Big Data Technology

Background: Big data technology has been widely used in manufacturing supply chain management. However, traditional big data technology has some limitations, and it cannot achieve the continuous improvement of whole-process product quality tracing. Objective : The purpose of this study is to overcome the limitations by patents analysis and provide new big data technology and technical modes to make the continuous improvements of whole-process product quality tracing for achieving effective product lifecycle management based on big data technology. Methods: The research method, patent analysis, and comparative analysis are employed in this study to analyze product quality tracing in the manufacturing supply chain based on big data technology. Moreover, the procedure and steps of the new big data technology - Product Digital Twin (PDT), and its technical modes are designed by process design methods. Its key technologies are also analyzed and compared with traditional big data technology by the comparative study. Results: The research achieves the continuous improvements of whole-process product quality tracing based on new big data technology - PDT by patent analysis. The formation process and behavior of manufactured products in the realistic environment are simulated, monitored, diagnosed, predicted, and controlled. In this way, the high-efficient coordination in various stages of the product lifecycle is propelled fundamentally and the continuous improvements of the whole-process product quality tracing based on big data technology is analyzed. Conclusion: Three new technical modes based on big data technology are predicted for future researches and patents, namely, the immersive development mode integrating big data and the virtual reality technology, the knowledge-based multivariant coordinated development mode, and the lifecycle extended development model based on multi-domain interoperability.

scholarly journals E-Commerce Enterprise Supply Chain Cost Control under the Background of Big Data

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Haijun Mao ◽  
Long Chen
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chains ◽  
Cost Control ◽  
Cost Management ◽  
Rapid Development ◽  
Operation Mode ◽  
Enterprise Management ◽  
Systematic Analysis ◽  
Big Data Technology

Since the twentieth century, it has been an era of rapid development of information technology; the scale of data is almost the growth rate of the blowout type; no matter what it is, a large number of enterprises or departments are increasing a large number of cost data. However, the current cost management model still remains in the traditional management method and lacks a smarter big data analysis method. In addition, there is a lot of research on big data applications, and there are few e-commerce supply chains. Therefore, the research purpose of this study is to use big data technology to explore a series of practical operation methods for supply chain Cultural Communication Enterprises and summarize the operation mode of building SCC control by using big data technology. In terms of research methods, this study combined bibliographic review and empirical analysis, explored cost-based mobile e-commerce (EU) cost control related to big data information, used smart and digital analysis methods to thoroughly analyze CCE business issues from internal and external supply chains, established an e-commerce business supply chain cost control model based on big data technology and elaborated cost control procedures and measures. Finally, it summarized the research results and drew conclusions to provide a theoretical basis for promoting enterprises products products to reduce supply chain costs. The research in this study has achieved a breakthrough in the cost management and control of EE; it provides empirical guidance and theoretical reference for EE to adopt big data technology for cost command of supply chain (CCSC), could help EE to reduce cost of supply chain management to gain higher profit margins, and promote e-commerce industry as a whole to the next level eventually. This study concluded that the use of big data technology for cost command can solve a series of problems effectively, such as the lack of systematic analysis of cost, the lack of contractual partners, the serious waste of sales links, and the policy errors of logistics links, and continuously improve the enterprise management level and the decline of comprehensive cost. The application mode of supply chain CCE enterprises using big data technology constructed in this study has universal applicability.

scholarly journals Research on the Innovation of Supply Chain Management Mode of Cross-Border B2B Foreign Trade Export Enterprises in the Context of Big Data

2021 ◽  
pp. 203-219
Author(s):  
ChuJia Liu, Dr. Nolan Guillao
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Foreign Trade ◽  
Development Strategy ◽  
Market Competition ◽  
Management Mode ◽  
Chain Management ◽  
Cross Border ◽  
Big Data Technology

With the continuous advancement of global economic integration, the influence of big data on cross-border B2B foreign trade export companies is increasing. Every cross-border B2B foreign trade export company needs to deal with increasingly fierce market competition, and cross-border B2B foreign trade export companies want to gain a competitive advantage, which it is necessary to actively introduce big data technology to innovate the management model of cross-border B2B foreign trade export enterprises. The managers of cross-border B2B foreign trade export enterprises must innovate decision-making concepts in a timely manner, collect and analyze big data, and make them a foreign trade enterprise. Meanwhile we need to pay attention to the introduction of high-quality professional data talents. This article first puts forward the concept and main characteristics of big data, which clarifies the various problems faced by foreign trade export enterprises since entering the era of big data. With the help of supply chain management mode, we need to innovates the management mode of cross-border B2B foreign trade export enterprises and actively applies big data technology and supply Chain management which promotes the healthy development strategy of foreign trade export enterprises and improves the core competitiveness of foreign trade export enterprises.

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