Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Artificial Intelligence for Supply Chain Resilience: Learning from Covid-19

Modgil, S, Singh, RK and Hannibal, C (2021) Artificial Intelligence for Supply Chain Resilience: Learning from Covid-19. The International Journal of Logistics Management. ISSN 0957-4093

Artificial intelligence for supply chain resilience Learning from Covid-19.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.

Download (1MB) | Preview


Purpose: Many supply chains have faced disruption during Covid-19. Artificial intelligence (AI) is one mechanism that can be used to improve supply chain resilience by developing business continuity capabilities. This study examines how firms employ AI and considers the opportunities for AI to enhance supply chain resilience by developing visibility, risk, sourcing and distribution capabilities.
Design/Methodology: We have gathered rich data by conducting semi-structured interviews with 35 experts from the e-commerce supply chain. We have adopted a systematic approach of coding using open, axial, and selective methods to map and identify the themes that represent the critical elements of AI-enabled supply chain resilience.
Findings: The results of the study highlight the emergence of five critical areas where AI can contribute to enhanced supply chain resilience; (i) transparency, (ii) ensuring last-mile delivery, (iii) offering personalized solutions to both upstream and downstream supply chain stakeholders, (iv) minimizing the impact of disruption, and (v) facilitating an agile procurement strategy.
Originality: The study presents the dynamic capabilities for supply chain resilience through the employment of AI. AI can contribute to readying supply chains to reduce their risk of disruption through enhanced resilience.
Implications: The study offers interesting implications for bridging the theory-practice gap by drawing on contemporary empirical data to demonstrate how enhancing dynamic capabilities via AI technologies further strengthens supply chain resilience. The study also offers suggestions for utilizing the findings and proposes a framework to strengthen supply chain resilience through AI.

Item Type: Article
Additional Information: Modgil, S., Singh, R.K. and Hannibal, C. (2021), "Artificial intelligence for supply chain resilience: learning from Covid-19", The International Journal of Logistics Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJLM-02-2021-0094
Uncontrolled Keywords: 08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services
Subjects: H Social Sciences > HF Commerce > HF5001 Business
H Social Sciences > HF Commerce
H Social Sciences > HF Commerce > HF5001 Business > HF5410 Marketing. Distribution of Products
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Doctoral Management Studies (from Sep 19)
Publisher: Emerald
Date Deposited: 28 Jul 2021 09:21
Last Modified: 04 Sep 2021 05:13
DOI or ID number: 10.1108/IJLM-02-2021-0094
URI: https://researchonline.ljmu.ac.uk/id/eprint/15291
View Item View Item