Blockchain sharding for e-commerce supply chain performance analytics towards Industry 5.0

Y. P. Tsang; Youqing Fan; C. K.M. Lee; H. C.W. Lau

doi:10.1080/17517575.2024.2311807

Blockchain sharding for e-commerce supply chain performance analytics towards Industry 5.0

Y. P. Tsang, Youqing Fan, C. K.M. Lee, H. C.W. Lau

Research output: Journal article publication › Journal article › Academic research › peer-review

5 Citations (Scopus)

Abstract

In today’s competitive and volatile e-commerce markets, effective supply chain performance measurement (SCPM) gradually becomes essential for investigating pitfalls and loopholes in strategic vendor management and business development. Surrounding the atmosphere of Industry 5.0, sustainability and resilience are two primary pillars, which should be further considered in the SCPM beyond merely operational effectiveness and efficiency. This study customises evaluation criteria based on the green supply chain operations reference model. Moreover, a blockchain sharding-enabled performance analytics system is designed, where a real-life case analysis is conducted to verify the system efficacy. Consequently, the supply chain sustainability and resilience can be fostered.

Original language	English
Article number	2311807
Number of pages	25
Journal	Enterprise Information Systems
Volume	18
Issue number	4
DOIs	https://doi.org/10.1080/17517575.2024.2311807
Publication status	Published - 2 Apr 2024

Keywords

blockchain
e-commerce
fuzzy inference system
performance measurement
Supply chain

ASJC Scopus subject areas

Computer Science Applications
Information Systems and Management

More information

10.1080/17517575.2024.2311807

Cite this

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title = "Blockchain sharding for e-commerce supply chain performance analytics towards Industry 5.0",

abstract = "In today{\textquoteright}s competitive and volatile e-commerce markets, effective supply chain performance measurement (SCPM) gradually becomes essential for investigating pitfalls and loopholes in strategic vendor management and business development. Surrounding the atmosphere of Industry 5.0, sustainability and resilience are two primary pillars, which should be further considered in the SCPM beyond merely operational effectiveness and efficiency. This study customises evaluation criteria based on the green supply chain operations reference model. Moreover, a blockchain sharding-enabled performance analytics system is designed, where a real-life case analysis is conducted to verify the system efficacy. Consequently, the supply chain sustainability and resilience can be fostered.",

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N1 - Funding information: The authors would like to thank the Department of ISE, Hong Kong Polytechnic University and the Western Sydney University for supporting the research. The work described in this paper was supported by a grant from The Hong Kong Polytechnic University (Project code: 1-CD4E). Also, this research is funded by the Laboratory for Artificial Intelligence in Design (Project Code: RP2-2), Hong Kong Special Administrative Region. Publisher Copyright: © 2024 Informa UK Limited, trading as Taylor & Francis Group.

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N2 - In today’s competitive and volatile e-commerce markets, effective supply chain performance measurement (SCPM) gradually becomes essential for investigating pitfalls and loopholes in strategic vendor management and business development. Surrounding the atmosphere of Industry 5.0, sustainability and resilience are two primary pillars, which should be further considered in the SCPM beyond merely operational effectiveness and efficiency. This study customises evaluation criteria based on the green supply chain operations reference model. Moreover, a blockchain sharding-enabled performance analytics system is designed, where a real-life case analysis is conducted to verify the system efficacy. Consequently, the supply chain sustainability and resilience can be fostered.

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KW - blockchain

KW - e-commerce

KW - fuzzy inference system

KW - performance measurement

KW - Supply chain

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Blockchain sharding for e-commerce supply chain performance analytics towards Industry 5.0

Abstract

Keywords

ASJC Scopus subject areas

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