An empirical analysis of complexity management for offshore wind energy supply chains and the benefits of blockchain adoption

IF 1.7 3区 工程技术 Q3 ENGINEERING, CIVIL Civil Engineering and Environmental Systems Pub Date : 2020-07-02 DOI:10.1080/10286608.2020.1810674
S. Keivanpour, A. Ramudhin, Daoud Ait Kadi
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引用次数: 6

Abstract

ABSTRACT The supply chain plays an essential role in the cost reduction of offshore wind energy. Supply chain complexity is a major driver of end-to-end supply chain costs and at the same time a source of competitive advantage. In this study, a strategic complexity management approach is suggested for analysing and controlling the complexity of the supply chain in offshore wind energy. The adoption of blockchain via the development of software architecture and a discussion of its impact on complexity are provided. A comparative study focused on two UK offshore wind farms based on real industrial data illustrates the complexity analysis and the contribution of blockchain technology to the strategic management of this complexity.
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海上风能供应链复杂性管理的实证分析及区块链采用的好处
供应链在降低海上风电成本中起着至关重要的作用。供应链的复杂性是端到端供应链成本的主要驱动因素,同时也是竞争优势的来源。本文提出了一种战略复杂性管理方法来分析和控制海上风电供应链的复杂性。通过软件架构的开发采用区块链,并讨论其对复杂性的影响。一项基于真实工业数据的对两个英国海上风电场的比较研究说明了复杂性分析和区块链技术对这种复杂性的战略管理的贡献。
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来源期刊
Civil Engineering and Environmental Systems
Civil Engineering and Environmental Systems 工程技术-工程:土木
CiteScore
3.30
自引率
16.70%
发文量
10
审稿时长
>12 weeks
期刊介绍: Civil Engineering and Environmental Systems is devoted to the advancement of systems thinking and systems techniques throughout systems engineering, environmental engineering decision-making, and engineering management. We do this by publishing the practical applications and developments of "hard" and "soft" systems techniques and thinking. Submissions that allow for better analysis of civil engineering and environmental systems might look at: -Civil Engineering optimization -Risk assessment in engineering -Civil engineering decision analysis -System identification in engineering -Civil engineering numerical simulation -Uncertainty modelling in engineering -Qualitative modelling of complex engineering systems
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