Unravelling supply chain learning under supply chain coopetition

Abstract

In an era with unprecedented volatility, complexity, and interconnectivity, supply chains are continuously confronted with disruptive forces. This makes dynamic adaptation and collective learning essential for long term viability. Supply chain learning (SCL) and supply chain coopetition (SCC), have emerged as pivotal themes within supply chain management. Nevertheless, the critical intersection between these concepts remains underexplored, with limited comprehensive understanding of how learning processes evolve and generate performance outcomes within the complex and often tense context of coopetition. This doctoral thesis bridges this gap through a systematic, multi-study investigation into the interplay between SCL and SCC.
Guided by a progressive research logic that moves from antecedent mechanisms to configurational pathways and finally to performance outcomes, this thesis employs three interrelated empirical studies to develop a holistic understanding of SCL within the context of SCC. Study 1, grounded in Social Exchange Theory, investigates the antecedent mechanism of SCL by examining how inter-firm justice influences SCL, with SCC serving as a mediating factor and environmental dynamism as a moderating factor. Using survey data from 206 Chinese manufacturing firms and applying regression-based conditional process modeling, the findings confirm that inter-firm justice positively drives SCL both directly and indirectly through SCC. Environmental dynamism amplifies this mediating pathway by strengthening the relationships between inter-firm justice and SCC, as well as between SCC and SCL. This study establishes the relational foundation of SCL in coopetitive contexts, clarifying how fair relational governance fosters learning through the effective management of coopetitive tensions.
Building on the identification of SCC as a key antecedent, Study 2 adopts a configurational perspective informed by Relational Coordination Theory to explore the equifinal pathways leading to high levels of SCL. Building upon the same dataset, this study utilizes fuzzy-set Qualitative Comparative Analysis (fsQCA) to examine how specific dimensions of SCC, knowledge transfer efficacy and digital capability interact synergistically. The analysis focuses on three SCC dimensions: cooperation, constructive conflict, and destructive conflict. It further incorporates knowledge transfer efficacy, measured through knowledge speed and knowledge comprehension, as well as digital agility, which is a specific aspect of digital capability. The results reveal six distinct configurational pathways to high SCL, which can be categorized into three primary types: those dominated by cooperation and digital agility, those dominated by constructive conflict and knowledge comprehension, and those dominated by cooperation and knowledge comprehension. This study transcends linear causal assumptions by demonstrating that effective SCL arises from synergistic combinations of multiple factors rather than from isolated antecedents, thereby clarifying the context-dependent roles of different conflict types and knowledge characteristics.
Study 3, leveraging Complex Adaptive Systems Theory, shifts the focus to the performance outcomes of SCL. It delineates how SCL fosters supply chain flexibility (SCF), encompassing sourcing, manufacturing, and delivery flexibility, with supply chain integration (SCI) as the mediating factor and coopetition capability as the moderating factor. Using regression-based conditional process modeling, the findings indicate that SCL enhances SCF both directly and indirectly through SCI. Coopetition capability reinforces this entire causal pathway. It amplifies the positive effect of SCL on SCI by mitigating relational risks inherent in knowledge sharing, and it strengthens the positive impacts of SCI on sourcing and delivery flexibility by balancing cooperative alignment with strategic autonomy. This study clarifies the mechanism through which SCL converts into supply chain-specific performance outcomes within coopetitive contexts.
Theoretically, this thesis contributes to the supply chain management literature by integrating the hitherto siloed domains of SCL and SCC into a cohesive theoretical framework. It enriches the theoretical understanding of SCL by systematically uncovering its antecedent mechanisms, configurational pathways, and performance outcomes logic. Methodologically, it showcases the value of combining regression-based analysis and fsQCA to examine complex phenomena, thereby providing a robust multi-method research paradigm for future studies on SCL. Practically, the findings offer actionable insights for managers navigating SCL by strategically balancing coopetitive dynamics. These include cultivating fair relational governance to balance cooperative knowledge sharing and competitive risk mitigation, leveraging context-specific configurational capabilities (e.g., aligning cooperation with digital agility or constructive conflict with knowledge comprehension), and developing coopetition capability to convert collective learning into flexibility through enhanced integration. Overall, this thesis provides a comprehensive roadmap for building learning-driven, adaptable, and resilient supply chains through the strategic management of coopetition.

Date of Award	19 Jul 2026
Original language	English
Awarding Institution	University of Nottingham
Supervisor	Jing Dai (Supervisor), Jinan Shao (Supervisor) & Antony Paulraj (Supervisor)