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.
Description:
DATA AVAILABILITY : The data that support the findings of this study are available
on request from the corresponding author, W.N. Data are
stored according to institutional policy.
This article is based on the dissertation of K.H. and B.S. who were the main researchers. W.N. acted as the supervisor with the conceptualisation, literature review, research instrument and development of this manuscript.
