Resilient supply chains: advancing technology integration with pre- and post-disruption technology roadmap

Abstract

Purpose

Industry 4.0 (I4.0) technologies are pivotal in enhancing supply chain resilience (SCRES). The extant literature identifies multiple antecedents of SCRES. However, the holistic impact of I4.0 technologies on all the antecedents of SCRES has not been rigorously studied. Practising managers have a limited understanding of the interrelationship of these technologies and their impact on each SCRES antecedent and its subfactors. This highlights the need for a comprehensive technology roadmap that integrates I4.0 technologies with SCRES antecedents and subfactors, benefiting both the pre- and post-disruption phases.

Design/methodology/approach

Interpretive structural modelling is used to develop the hierarchical structure of technologies based on their interrelationship. ANP-SVNTOPSIS (Analytic Network Process – Single Valued Neutrosophic Technique for Order of Preference by Similarity to Ideal Solution) approach to quantify technology impact factors (TIFs) value of each technology corresponding to each antecedent of SCRES is applied.

Findings

The result reveals that data-driven technologies and additive manufacturing have the highest impact on SCRES. The detailed analysis of the TIF values identifies high-impacting technologies for each SCRES antecedent and subfactor. The results are used to propose a technology roadmap integrating I4.0 technologies with SCRES antecedents for pre- and post-disruption phases.

Originality/value

The positive impact of I4.0 technologies on SCRES is well established. However, many companies face challenges in their I4.0 implementation projects despite the manifold advantages. To the best of our knowledge, no previous research has conducted such a rigorous analysis at the individual technology level and SCRES antecedents to quantify the multifaceted dimensions of SCRES. The present study addresses this gap. Furthermore, it proposes a technology roadmap which incorporates pre- and post-disruption phases, which is its uniqueness.