What factors influence blockchain technology adoption in shipping supply chain: An empirical study from China

IF 4.4 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management Pub Date : 2025-08-25 DOI:10.1016/j.rtbm.2025.101494

Ruihua Zhang, Xianhua Wu

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引用次数: 0

Abstract

Industry 4.0 presents significant opportunities for digitalizing the shipping supply chain (SC), featuring blockchain technology (BT) as a key example. This research innovatively developed the Technology-Organization-Environment (TOE) theory by integrating economic perspective. It explored how factors such as regulatory support, compatibility, complexity, risk, competitive pressure, relative advantage, cost, top management support, organizational readiness, and efficiency influence the deployment of BT by Chinese shipping SC enterprises. This paper collected data from 285 respondents in shipping SC enterprises in China, and the analysis was carried out with structural equation modelling (SEM) combined with artificial neural network (ANN) approach. The findings showed that compatibility, organizational readiness, competitive pressure, regulatory support, and complexity are key variables affecting the application of BT, while the other examined factors do not have a significant impact. ANN determined the ranking of important variables, which was in descending order as follows: regulatory support > organizational readiness > compatibility > competitive pressure > complexity. Additionally, this study summarized and compared the variables shaping the integration of BT in the SCs of various industries, offering a clearer perspective on the differences in the results. This empirical study offers valuable insights for organizations, project participants, and policymakers, assisting them in making informed judgments concerning BT implementation.

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航运供应链中区块链技术采用的影响因素：来自中国的实证研究

工业4.0为数字化航运供应链（SC）提供了重要机会，区块链技术（BT）是一个关键例子。本研究通过整合经济学视角，创新性地发展了技术-组织-环境（TOE）理论。研究了法规支持、兼容性、复杂性、风险、竞争压力、相对优势、成本、高层管理支持、组织准备和效率等因素如何影响中国航运SC企业部署BT。本文收集了285家中国航运供应链企业的调查数据，采用结构方程模型（SEM）和人工神经网络（ANN）相结合的方法进行分析。研究结果表明，兼容性、组织准备程度、竞争压力、监管支持和复杂性是影响BT应用的关键变量，而其他因素没有显著影响。人工神经网络确定了重要变量的排序，按降序排列为：监管支持度>；组织准备度>；兼容性>；竞争压力>；复杂性。此外，本研究还总结和比较了影响各行业SCs中BT整合的变量，为研究结果的差异提供了更清晰的视角。该实证研究为组织、项目参与者和政策制定者提供了有价值的见解，帮助他们做出有关BT实施的明智判断。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Research in Transportation Business and Management Multiple-

CiteScore

7.10

自引率

8.30%

发文量

175

期刊介绍： Research in Transportation Business & Management (RTBM) will publish research on international aspects of transport management such as business strategy, communication, sustainability, finance, human resource management, law, logistics, marketing, franchising, privatisation and commercialisation. Research in Transportation Business & Management welcomes proposals for themed volumes from scholars in management, in relation to all modes of transport. Issues should be cross-disciplinary for one mode or single-disciplinary for all modes. We are keen to receive proposals that combine and integrate theories and concepts that are taken from or can be traced to origins in different disciplines or lessons learned from different modes and approaches to the topic. By facilitating the development of interdisciplinary or intermodal concepts, theories and ideas, and by synthesizing these for the journal''s audience, we seek to contribute to both scholarly advancement of knowledge and the state of managerial practice. Potential volume themes include: -Sustainability and Transportation Management- Transport Management and the Reduction of Transport''s Carbon Footprint- Marketing Transport/Branding Transportation- Benchmarking, Performance Measurement and Best Practices in Transport Operations- Franchising, Concessions and Alternate Governance Mechanisms for Transport Organisations- Logistics and the Integration of Transportation into Freight Supply Chains- Risk Management (or Asset Management or Transportation Finance or ...): Lessons from Multiple Modes- Engaging the Stakeholder in Transportation Governance- Reliability in the Freight Sector