This study aims to investigate the relationship between antecedents of coopetition within supply chains and develop a comprehensive, practical framework to guide the strategic application of coopetition. The research introduces the Antecedent-Driven Coopetition Strategy Framework (ADCSF) to provide supply chain managers with a reliable toolkit for integrating coopetition into their organizational practices.
The research uses Interpretive Structural Modeling (ISM) and Fuzzy Matrice d‘Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis to identify and map 26 antecedents of coopetition within supply chains. The relationships between these antecedents were analyzed to build the ADCSF, a four-step framework designed to help managers strategically implement coopetition.
This study revealed key antecedents that influence the adoption of coopetition strategies in supply chains, providing a structured pathway for their application. The ADCSF highlights essential actions, such as aligning with governance, fostering coopetitive engagement, harmonizing resources and leading coopetitive evolution. These steps offer clear, actionable insights into managing coopetition effectively.
The reliance on ISM and Fuzzy MICMAC models focuses on theoretical relationships and may not capture the whole dynamics of coopetition in practice. Future research could incorporate empirical data and case studies to validate and expand on the findings.
The ADCSF equips supply chain managers with a systematic approach to navigating coopetitive relationships, helping them align strategies with regulatory frameworks, optimize resources and build trust with competitors for operational efficiency and competitive advantage.
This paper advances the understanding of coopetition by providing a structured, antecedent-driven framework for its adoption in supply chains. It bridges the gap between theoretical insights and practical applications, offering a unique contribution to the strategic management of coopetition in complex and competitive environments.
