Examining blockchain adoption determinants and supply chain performance: an empirical study in the logistics and supply chain management industry

IF 1.8 Q3 MANAGEMENT
Hanan Alkatheeri, Syed Zamberi Ahmad
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引用次数: 0

Abstract

Purpose

The purpose of this study is to explore the potential impact of blockchain technology on supply chain performance (SCP). This study further delves into the enablers of blockchain adoption (BA) in SCM and investigates both the direct and mediated effects of blockchain assimilation on garnering a competitive edge in the supply chain and bolstering innovation proficiency, ultimately enhancing SCP.

Design/methodology/approach

This study used a quantitative approach, leveraging partial least squares structural equation modelling. Empirical data were sourced from 500 validated data sets obtained through questionnaires.

Findings

The results indicate that technological readiness and knowledge sharing are key drivers for integrating blockchain into supply chains, with technology readiness displaying a substantially stronger influence. Furthermore, BA significantly enhances supply chain innovation capabilities (SCIC), competitive performance (CP) and overall supply chain efficiency. Notably, both SCIC and CP mediate and amplify the positive effects of blockchain on SCP, emphasising the vital role of innovation and competition in optimising the benefits of blockchain.

Originality/value

To the best of the authors’ knowledge, this study is the first to bridge the gap in the literature connecting SCM and blockchain. The established model augments the theoretical discourse on the SCM-blockchain, offering scholars a validated framework that can be adapted and built upon in future studies.

考察区块链采用的决定因素和供应链绩效:物流和供应链管理行业的实证研究
本研究旨在探讨区块链技术对供应链绩效(SCP)的潜在影响。本研究进一步探讨了在供应链管理中采用区块链技术(BA)的促进因素,并调查了区块链同化对获得供应链竞争优势和提高创新能力的直接影响和中介影响,最终提高了 SCP。研究结果表明,技术准备程度和知识共享是将区块链整合到供应链中的关键驱动因素,其中技术准备程度的影响更大。此外,区块链技术大大提高了供应链创新能力(SCIC)、竞争绩效(CP)和供应链整体效率。值得注意的是,供应链创新能力(SCIC)和供应链竞争绩效(CP)都对区块链对供应链控制(SCP)的积极影响起到了中介和放大作用,强调了创新和竞争在优化区块链效益方面的重要作用。所建立的模型扩充了有关供应链管理-区块链的理论论述,为学者们提供了一个经过验证的框架,可在今后的研究中加以调整和利用。
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来源期刊
CiteScore
5.50
自引率
12.50%
发文量
52
期刊介绍: Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications. JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between ''antecedents and modelling'' (how to tackle certain problems) and ''modelling and consequences'' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions. JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as: A priori theorizing conceptual models, Artificial intelligence, machine learning, Association rule mining, clustering, feature selection, Business analytics: Descriptive, Predictive, and Prescriptive Analytics, Causal analytics: structural equation modeling, partial least squares modeling, Computable general equilibrium models, Computer-based models, Data mining, data analytics with big data, Decision support systems and business intelligence, Econometric models, Fuzzy logic modeling, Generalized linear models, Multi-attribute decision-making models, Non-linear models, Optimization, Simulation models, Statistical decision models, Statistical inference making and probabilistic modeling, Text mining, web mining, and visual analytics, Uncertainty-based reasoning models.
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