Driving sustainability, resilience, and digitalisation in automotive supply chains: A stochastic maturity model for future-oriented transformation

Abstract

Digitalisation, resilience, and sustainability are key drivers of contemporary supply chain transformation, requiring organisations to make strategic decisions under conditions of uncertainty. To support such decisions, this paper presents a stochastic maturity model that supports the assessment, prioritisation, and continuous improvement of SCM and logistics megatrends and trends under uncertainty. The proposed model combines a configurable maturity structure with Stochastic Multicriteria Acceptability Analysis (SMAA) and empirical probability distributions to enable uncertainty-aware prioritisation of transformation initiatives while remaining adaptable to organisation-specific contexts and continuously evolving business environments. To evaluate the proposed assessment methodology in practice, nine of its ten phases were implemented at a passenger car manufacturer using a panel of six experts. The automotive industry was selected because of the complexity of its global supply chains and advanced logistics practices, providing a demanding environment for evaluating the proposed model. The results demonstrate the feasibility of the proposed assessment procedure in a real industrial environment and illustrate its potential to support strategic decision-making, prioritise transformation initiatives, and facilitate sustainability-oriented supply chain transformation under conditions of uncertainty.