Study of the Game Model of E-Commerce Information Sharing in an Agricultural Product Supply Chain based on fuzzy big data and LSGDM

2021 ◽  
Vol 172 ◽  
pp. 121017
Author(s):  
Luo ming ◽  
Zhou GuoHua ◽  
Wei Wei
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Information Sharing ◽  
Agricultural Product ◽  
Game Model

A Game Theoretic Approach for Sensitive Information Sharing in Supply Chain

2010 ◽  
Vol 1 (4) ◽  
pp. 1-12 ◽  
Author(s):  
Xiaofeng Zhang ◽  
William K. Cheung ◽  
ZongWei Luo ◽  
Frank Tong
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Radio Frequency Identification ◽  
Dynamic Environment ◽  
Stackelberg Equilibrium ◽  
Game Model ◽  
Sensitive Information ◽  
Theoretic Approach ◽  
Complex Situation ◽  
Conventional Optimization

With the adoption of radio frequency identification (RFID) technology, information sharing among participants in a supply chain is greatly facilitated, raising privacy concerns on sharing sensitive information. Balancing the conflicts between the improvement of visibility and the decrease of sensitive information shared is paramount. In this paper, the authors propose a leader-follower game model called LFM to model the strategic game between buyer and supplier. A Stackelberg equilibrium state is then computed as the solution to this game model. The proposed approach exhibits better performance when compared with conventional optimization approaches via derivation in terms of the total information sharing level and the total gain acquired verified by the experiments. In the future, the authors will extend this approach to a more complex situation with more participants in a dynamic environment.

Big data use and its outcomes in supply chain context: the roles of information sharing and technological innovation

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hamza Saleem ◽  
Yongjun Li ◽  
Zulqurnain Ali ◽  
Muhammad Ayyoub ◽  
Yu Wang ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Information Sharing ◽  
Technological Innovation ◽  
Dynamic Capabilities ◽  
Survey Methods ◽  
Organizational Outcomes ◽  
Production Costs ◽  
Content Type ◽  
Product And Process

PurposeThis paper aims to investigate the use of big data (BDU) in predicting technological innovation, supply chain and SMEs' performance and whether technological innovation mediates the association between BDU and firm performance. Additionally, this research also seeks to explore the moderating effect of information sharing in the association between BDU and technological innovation.Design/methodology/approachUsing survey methods and structural associations in AMOS 24.0., the proposed model was tested on SME managers recruited from the largest economic and manufacturing hub of China, Pearl River Delta.FindingsThe findings suggest that BDU is positively related to technological innovation (product and process) and organizational outcomes (e.g., supply chain and SMEs performance). Technological innovation (i.e., product and process) significantly mediates the association between BDU and organizational outcomes. Moreover, information sharing positively moderates the association between BDU and technological innovations.Practical implicationsThis research provides deeper insights into how BDU is useful for SME managers in achieving the firm’s goals. Particularly, SME managers can bring technological innovation into their business processes, overcome the challenges of forecasting, and generate dynamic capabilities for attaining the best SMEs’ performance. Additionally, BDU with information sharing enables SMEs reduce their risk and decrease production costs in their manufacturing process.Originality/valueFirms always need to adopt new ways to enhance their productivity using available resources. This is the first study that contributes to big data and performance management literature by exploring the moderating and mediation mechanism of information sharing and technological innovation respectively using RBVT. The study and research model enhances our insights on BDU, information sharing, and technological innovation as valuable resources for organizations to improve supply chain performance, which subsequently increases SME productivity. This gap was overlooked by previous researchers in the domain of big data.

scholarly journals Enhancing Competitive Capabilities of Healthcare SCM through the Blockchain: Big Data Business Model’s Viewpoint

2022 ◽  
Author(s):  
Dae Hyun Jung
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Analysis ◽  
Supply Chain Management ◽  
Information Sharing ◽  
Real Time ◽  
Big Data Analysis ◽  
Logistics System ◽  
Chain Management ◽  
Competitive Capabilities

This study emphasizes the necessity of introducing a blockchain-based joint logistics system to strengthen the competency of medical supply chain management (SCM) and tries to develop a healthcare supply chain management (HSCM) competency measurement item through an analytic hierarchy process. The variables needed for using blockchain-based joint logistics are the performance expectations, effort expectations, promotion conditions, and social impact of the UTAUT model, and the HSCM competency results in increased reliability and transparency, enhanced SCM, and enhanced scalability. Word cloud results, analyzing the most important considerations to realize work efficiency among medical industry-related agencies, mentioned numerous words, including sudden situations, delivery, technology trust, information sharing, effectiveness, urgency, etc. This might imply the need to establish a system that can respond immediately to emergency situations during holidays. It could also suggest the importance of real-time information sharing to increase the efficiency of inventory management. Therefore, there is a need of a business model that can increase the visibility of real-time medical SCM through big data analysis. By analyzing the importance of securing reliability based on the blockchain technology in the establishment of a supply chain network for HSCM competency, we reveal that joint logistics can be achieved and synergistic effects can be created by implementing the integrated database to secure HSCM competency. Strengthening partnerships, such as joint logistics, will eventually lead to HSCM competency. In particular, HSCM should seek ways to upgrade its competitive capabilities through big data analysis based on the establishment of a joint logistics system.

scholarly journals Research on the Impact of Big Data on the Development of Supply Chain Logistics Management

2021 ◽  
Vol 251 ◽  
pp. 01039
Author(s):  
Xinchun Wang ◽  
Dan Zhang
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Information Sharing ◽  
Work Experience ◽  
Price Competition ◽  
Logistics Management ◽  
High Tech ◽  
Logistics System ◽  
Supply Chain Logistics ◽  
The Impact

In the era of big data, information sharing functions are of great significance. Moreover, under the effect of big data technology, information sharing can also avoid the problems of traditional supply chain logistics management, develop personalized service content for users, and fully control order risks. This article summarizes the current situation of traditional supply chain logistics services based on previous work experience. The author discusses the impact of big data on supply chain logistics management from how to improve the effect of high-tech management and control, how to shift from price competition to value competition, how to build a “big logistics” system, reduce logistics costs, strengthen distribution efficiency, and improve the stability of the enterprise, how to enhance the user service experience these all six aspects.

scholarly journals Supply Chain Finance for Targeted Poverty Alleviation: A Case Study of Suning

2020 ◽  
Author(s):  
Shanliang Li ◽  
Shan Yan ◽  
Liwen Liu
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Traffic Control ◽  
Poverty Alleviation ◽  
Economic Benefits ◽  
Agricultural Product ◽  
Financial Measures ◽  
Supply Chain Finance ◽  
Agricultural Supply

The sudden emergence of ‘COVID-19’ in 2020 has tightened traffic control in various places, which has posed a huge challenge to the agricultural product supply chain. This research introduces the perspective of supply chain finance, uses in-depth case study methods, and takes Suning’s agricultural supply chain finance as an example to discuss how e-commerce companies relying on big data adopt agricultural supply chain finance practices to promote accurate poverty alleviation. By analyzing Suning’s four agricultural supply chain financial operation models, we find that the internal and external stakeholders of the enterprise are the driving factors for enterprises to adopt agricultural supply chain finance, and the adoption of agricultural supply chain finance measures has brought economic benefits and social benefits to enterprises benefit. Advanced big data tools, fintech and cooperation with other partners are necessary to adopt agricultural supply chain financial measures.

A Game Theoretic Approach for Sensitive Information Sharing in Supply Chain

Cyber Crime ◽  
2013 ◽  
pp. 1265-1275
Author(s):  
Xiaofeng Zhang ◽  
William K. Cheung ◽  
ZongWei Luo ◽  
Frank Tong
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Radio Frequency Identification ◽  
Dynamic Environment ◽  
Stackelberg Equilibrium ◽  
Game Model ◽  
Sensitive Information ◽  
Theoretic Approach ◽  
Complex Situation ◽  
Conventional Optimization

With the adoption of radio frequency identification (RFID) technology, information sharing among participants in a supply chain is greatly facilitated, raising privacy concerns on sharing sensitive information. Balancing the conflicts between the improvement of visibility and the decrease of sensitive information shared is paramount. In this paper, the authors propose a leader-follower game model called LFM to model the strategic game between buyer and supplier. A Stackelberg equilibrium state is then computed as the solution to this game model. The proposed approach exhibits better performance when compared with conventional optimization approaches via derivation in terms of the total information sharing level and the total gain acquired verified by the experiments. In the future, the authors will extend this approach to a more complex situation with more participants in a dynamic environment.

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