Original Research

Artificial intelligence and information systems capabilities for supply chain resilience: A study in the South African fast-moving consumer goods industry

Karl Hirsch, Wesley Niemann, Brendan Swart
Journal of Transport and Supply Chain Management | Vol 18 | a1025 | DOI: https://doi.org/10.4102/jtscm.v18i0.1025 | © 2024 Karl Hirsch, Wesley Niemann, Brendan Swart | This work is licensed under CC Attribution 4.0
Submitted: 27 February 2024 | Published: 31 May 2024

About the author(s)

Karl Hirsch, Department of Business Management, Faculty of Economic and Management Sciences, University of Pretoria, Pretoria, South Africa
Wesley Niemann, Department of Business Management, Faculty of Economic and Management Sciences, University of Pretoria, Pretoria, South Africa
Brendan Swart, Department of Business Management, Faculty of Economic and Management Sciences, University of Pretoria, Pretoria, South Africa

Abstract

Background: Fast-moving consumer goods (FMCG) supply chains have become increasingly exposed to disruptions during and after the coronavirus disease 2019 (COVID-19) pandemic. The industry is vulnerable to supply chain disruptions due to unstable commodity markets and demand volatility. Artificial intelligence (AI) and information systems as technology enablers provide capabilities that can improve supply chain resilience to recover from a disruption. However, FMCG firms are slow with digital transformation and often do not leverage the capabilities of AI and information systems to improve their supply chain resilience.

Objectives: The purpose of this generic qualitative study was to determine how AI and information systems capabilities can be leveraged to improve supply chain resilience in the South African FMCG industry.

Method: This study employed purposive sampling methods to identify 12 FMCG manufacturers and retailers that participated in this study. Semi-structured interviews were used to collect data. A thematic analysis approach was followed to analyse the data.

Results: Supply chain integration, automation, monitoring and analytical capabilities of AI and information systems should be considered when designing post-COVID-19 supply chains to deal with increased complexity. Furthermore, supply chain resilience is enhanced by having AI and information systems capabilities such as information sharing, planning and predictive capabilities and decision-making capabilities. This study identified internal and external organisational driving factors, such as reducing costs and competitive factors, leading to the adoption of AI or information systems.

Conclusion: This study creates awareness of the value-adding benefits of AI and information systems that improve supply chain resilience.

Contribution: This study expands on existing literature by identifying various capabilities of AI and information systems that improve FMCG manufacturers’ and retailers’ supply chain resilience in a developing country context.


Keywords

artificial intelligence; information systems; supply chain resilience; disruption; fast-moving consumer goods; generic qualitative research; South Africa.

JEL Codes

M10: General; M11: Production Management

Sustainable Development Goal

Goal 12: Responsible consumption and production

Metrics

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