17 Jun 2026
Companies are increasingly embedding artificial intelligence in supply chain forecasting, resource allocation, and supplier evaluation, naturally assuming that "responsible AI" will automatically improve performance However, new research suggest that this is not always the case.
Research published in the International Journal of Production Economics by Professor Lujie Chen of International Business School Suzhou (IBSS) at Xi’an Jiaotong-Liverpool University and her collaborators shows that whether AI‑driven decisions create competitive advantage depends not on the technology itself, but also on whether supply chain partners see those decisions as fair, transparent and trustworthy.
Based on survey data from 218 Chinese firms, the study finds that responsible AI indirectly affects competitive advantage through two fairness mechanisms: distributive justice, which refer to whether outcomes are reasonable, and procedural justice, which refers to whether decision-making processes are transparent, consistent, and unbiased.
Both forms of justice are positively associated with competitive advantage. Notably, once these two mediating mechanisms are taken into account, the direct link between responsible AI and competitive advantage becomes non‑significant. This suggest that responsible AI creates value not simply as a standalone technical capability, but as a governance mechanism that shapes partners’ perceptions of fairness.
The study further reveals an asymmetric effect of supply chain complexity. When supply chains become more fragmented and multi‑layered, the mediating role of distributive justice becomes weaker as partners may find it harder to judge whether outcomes are fair. However, the mediating role of procedural justice remains robust: transparent and consistent decision rules are more visible and defensible in complex environments.
Professor Chen notes: "Firms often focus on the efficiency of AI while overlooking the legitimacy of AI. In complex supply chains, procedural justice is more reliable than distributive justice — because when outcomes are difficult to verify, consistency in rules becomes the cornerstone of trust."
For managers, the study offers three implications. First, firms should treat responsible AI as a governance mechanism rather than a technical tool, and establish clear channels for explanation and review. Second, prioritise procedural justice in complex supply chains. Third, they should integrate AI governance into supply chain relationship management, by paying attention to partners’ trust and responses.
Responsible AI delivers competitive advantage not simply because a firm "uses AI", but because it supports fair, collaborative and stable supply chain relationships.
About the author
Lujie Chen is a full Professor of Management at International Business School Suzhou, part of Xi’an Jiaotong-Liverpool University. Prof Chen is Elsevier-Stanford University World's Top 2% Scientists 2024 and 2025 (the only one in IBSS). She is a Fellow of the Higher Education Academy in the UK and an expert in the fields of supply chain management and business analytics. Professor Chen have published over 60 high-quality and impactful papers in top-tier journals such as the Journal of Operations Management (UTD 24), Harvard Business Review (FT50), International Journal of Operations and Production Management (ABS 4), British Journal of Management (ABS 4), and European Journal of Operational Research (ABS 4), among others. She has served as a guest editor for special issues of several respected journals such as International Journal of Operations and Production Management, Industrial Marketing Management, International Journal of Production Economics, and Journal of Business Research. She is currently serving as an Associate Editor for the International Journal of Operations and Production Management (ABS 4) and department editor for IEEE TEM (ABS 3) and editorial board for Humanities and Social Sciences Communications (Nature Portfolio, CAS Humanities Q1 & JCR Q1).
The International Journal of Production Economics focuses on the intersection of engineering and management, covering manufacturing, process industries, and the full cycle of production activities. It aims to disseminate knowledge to improve industrial practice and strengthen the theoretical foundation for sound decision-making, providing a platform for exchange at the crossroads of engineering technology and the managerial and economic environment. The journal combines academic rigor with practical value for industrial applications.
By Xiaoxuan Chen
Edited by Thomas Durham
17 Jun 2026