From Triple‐A to AAA +: Recalibrating Agility, Adaptability, and Alignment for Digital, Responsible, and Resilient Supply Chains
回顾Lee的Triple-A框架，提出AAA+更新版，解释在数字化、可持续性和生态系统治理下，敏捷性、适应性和协调性如何产生竞争优势，为管理者和研究者提供新视角。
ABSTRACT Two decades after Lee's (2004) Triple‐A framework—agility, adaptability, and alignment—redefined supply chain excellence, the context that shaped it has undergone a significant transformation. Supply chains now function through digital platforms, extended ecosystems, and under growing social and environmental expectations. This Journal of Business Logistics Special Topic Forum (STF) revisits the Triple‐A concept to explore how these capabilities evolve under today's conditions and the need for responsiveness. Drawing on the STF contributions, we introduce AAA+, an updated view of the Triple‐A model that clarifies the conditions under which agility, adaptability, and alignment generate competitive advantage. The framework extends the original logic through three evolutions: digital super‐agility, enabled by real‐time data, analytics, and automation; strategic and sustainable adaptability, embedding resilience and environmental responsibility into network redesign; and ecosystem alignment, emphasizing coordination and shared governance across multi‐tier and multi‐stakeholder networks. Together, these dimensions shift Triple‐A from a firm‐level performance framework to a network‐level capability system. The AAA+ perspective also outlines a forward agenda for research and practice. It calls for studies that examine how digitalization, sustainability, and ecosystem governance interact to shape capability development, and it offers managers a lens to assess whether their supply chains are prepared for an era defined by data speed, global risk, and public accountability. In revisiting Triple‐A through this broader lens, the STF reaffirms Lee's enduring insight: the most successful supply chains are not simply efficient—they are those that learn, adapt, and align better across an increasingly connected world.