Blockchain Technology Adoption and Supply Chain Performance in China’s Automotive Industry: The Mediating Role of Trust and the Moderating Role of Transparency

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Zhang Yuan
Cheang Peck Yeng Sharon

Abstract

Purpose: This paper aims to explore how blockchain technology influences supply chain performance in the Chinese automotive industry. Drawing on trust theory and information asymmetry theory, it investigates the mechanisms through which blockchain enhances performance via technological trust, supply chain trust, and institutional trust, and examines the moderating role of supply chain transparency. Design/methodology/approach: A conceptual model is developed based on existing theories. The study employs a quantitative research design and plans to use Partial Least Squares Structural Equation Modeling (PLS-SEM) to empirically test the proposed hypotheses using data from the Chinese automotive sector. Findings: Preliminary theoretical analysis suggests that blockchain technology adoption can improve supply chain performance by reducing information asymmetry and enhancing multiple dimensions of trust among supply chain partners. Transparency is expected to strengthen these trust-building effects. (As the study is ongoing) Research limitations/implications: Since the research is still in progress, empirical results are not yet available. Future studies can complement this work with longitudinal data and cross-industry comparisons to validate the model’s broader applicability. Practical implications: The study provides guidance for firms and policymakers seeking to build blockchain-enabled trust mechanisms within complex industrial supply chains. It highlights how improving technological, relational, and institutional trust can enhance operational efficiency and coordination. Originality/value: This paper integrates trust theory and information asymmetry theory to conceptualize blockchain’s governance role in supply chains. It offers a multi-dimensional trust framework and identifies transparency as a key moderating factor, contributing new theoretical insight and practical relevance to blockchain-based supply chain research.

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