Building artificial intelligence enabled resilient supply chain: a multi-method approach

Abstract

Purpose

In the uncertain business environment, the supply chains are under pressure to balance routine operations and prepare for adverse events. Consequently, this research investigates how artificial intelligence is used to enable resilience among supply chains.

Design/methodology/approach

This study first analyzed the relationship among different characteristics of AI-enabled supply chain and how these elements take it towards resilience by collecting the responses from 27 supply chain professionals. Furthermore, to validate the results, an empirical analysis is conducted where the responses from 231 supply chain professionals are collected.

Findings

Findings indicate that the disruption impact of an event depends on the degree of transparency kept and provided to all supply chain partners. This is further validated through empirical study, where the impact of transparency facilitates the mass customization of the procurement strategy to Last Mile Delivery to reduce the impact of disruption. Hence, AI facilitates resilience in the supply chain.

Originality/value

This study adds to the domain of supply chain and information systems management by identifying the driving and dependent elements that AI facilitates and further validating the findings and structure of the elements through empirical analysis. The research also provides meaningful implications for theory and practice.

Citation

Singh, R.K., Modgil, S. and Shore, A. (2024), "Building artificial intelligence enabled resilient supply chain: a multi-method approach", Journal of Enterprise Information Management, Vol. 37 No. 2, pp. 414-436. https://doi.org/10.1108/JEIM-09-2022-0326