Blockchain for supply chain performance and logistics management. (1st October 2020)

• Record Type: Journal Article
• Authors: Yang, Juanjuan; Ma, Xiuming; Crespo, Rubén González; Martínez, Oscar Sanjuán
• Other Names: Srivastava Gautam guestEditor.
• Is Part Of: Applied stochastic models in business and industry. Volume 37:Number 3(2021)
• Page Start: 429
• Page End: 441
• Publication Date: 2020-10-01
• Subjects: blockchain -- digitalization -- logistics management -- stakeholders -- supply chain; Stochastic analysis -- Periodicals; Stochastic processes -- Periodicals; Business mathematics -- Periodicals; Finance -- Mathematical models -- Periodicals; Industrial management -- Mathematical models -- Periodicals; 338.00151923
• DOI: 10.1002/asmb.2577
• Languages: English
• ISSNs: 1524-1904

Abstract

Abstract: The trend of digitalization uses modern relationship models across global supply chain (SC) management. The main objective of this article is to identify SC current problems with the help of the knowledge sharing aspect using blockchain technology. This article addresses selected problems for managing modern SCs with a view to shared knowledge based on information management, effects of product and service on the quality of information, effects of consumer demands occurrences on information flow, outsourcing and globalization, and emerging threats to SCs by concerned parties. These problems are classified as concerns of confidentiality and trust, which are unable to share information among SC stakeholders due to a lack of data standards. To address these problems, a hybridized probabilistic performance and logistics framework (HPP‐LF) has been developed that defines the validity of blockchain to help companies throughout the design and deployment of potential blockchain solutions to address the information sharing issues between SC stakeholders. The proposed HPP‐LF results are compared with the existing PMOS, MIP, UTAUT, and ILOG techniques. The experimental result shows that the proposed method has better performance when compared with other existing systems.