In modern business environments, an effective supply chain management (SCM) is crucial to business continuity. Competition between supply chains (SC) has replaced the traditional competition between companies. Lean, Agile, Resilient and Green (LARG) paradigms are advocated as the foundation of a competitive SCM. To make a supply chain more competitive, capable of responding to the demands of customers with agility and capable of responding effectively to unexpected disturbance, in conjugation with environmental responsibilities and the necessity to eliminate processes that add no value, companies must implement a set of LARG SCM practices and key performance indicators (KPI) to measure their influence on the SC performance. However, the selection of the best LARG SCM practices and KPIs is a complex problem, involving dependencies and feedbacks. This paper proposes an integrated LARG analytic network process (ANP) model to support decision-making in choosing the most appropriate practices and KPIs to be implemented by companies in an SC. To validate the model in an exploratory approach, a case study in an automaker supply chain is presented.