Artificial Intelligence Opportunities for Resilient Supply Chains

Funlade Sunmola; George Baryannis

doi:10.1016/j.ifacol.2024.09.195

Artificial Intelligence Opportunities for Resilient Supply Chains

Funlade Sunmola, George Baryannis

University of Hertfordshire

Research output: Contribution to journal › Conference article › peer-review

9 Citations (Scopus)

Abstract

The need for supply chains to be resilient is increasingly being recognised, following recent disruptions caused by global socioeconomic crises. Supply chain resilience allows for sustainable growth and development through adaptive capabilities, principally including the ability to effectively respond to disruptions to maintain consistent operations. This paper explores the opportunities presented by Artificial Intelligence (AI) in enhancing supply chain resilience. We first conceptualise resilience through a 4-C model: context, capabilities, choices, and contingencies. We then explore a range of AI approaches and develop a research roadmap that attempts to map particular technologies holding potential to the 4-C model.

Original language	English
Pages (from-to)	813-818
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	58
Issue number	19
Early online date	9 Oct 2024
DOIs	https://doi.org/10.1016/j.ifacol.2024.09.195
Publication status	Published - 9 Oct 2024
Event	18th IFAC Symposium on Information Control Problems in Manufacturing - Vienna, Austria Duration: 28 Aug 2024 → 30 Aug 2024 Conference number: 18 https://www.incom2024.org/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 8 Decent Work and Economic Growth

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10.1016/j.ifacol.2024.09.195Licence: CC BY-NC-ND

Cite this

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title = "Artificial Intelligence Opportunities for Resilient Supply Chains",

abstract = "The need for supply chains to be resilient is increasingly being recognised, following recent disruptions caused by global socioeconomic crises. Supply chain resilience allows for sustainable growth and development through adaptive capabilities, principally including the ability to effectively respond to disruptions to maintain consistent operations. This paper explores the opportunities presented by Artificial Intelligence (AI) in enhancing supply chain resilience. We first conceptualise resilience through a 4-C model: context, capabilities, choices, and contingencies. We then explore a range of AI approaches and develop a research roadmap that attempts to map particular technologies holding potential to the 4-C model.",

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AU - Sunmola, Funlade

AU - Baryannis, George

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N2 - The need for supply chains to be resilient is increasingly being recognised, following recent disruptions caused by global socioeconomic crises. Supply chain resilience allows for sustainable growth and development through adaptive capabilities, principally including the ability to effectively respond to disruptions to maintain consistent operations. This paper explores the opportunities presented by Artificial Intelligence (AI) in enhancing supply chain resilience. We first conceptualise resilience through a 4-C model: context, capabilities, choices, and contingencies. We then explore a range of AI approaches and develop a research roadmap that attempts to map particular technologies holding potential to the 4-C model.

AB - The need for supply chains to be resilient is increasingly being recognised, following recent disruptions caused by global socioeconomic crises. Supply chain resilience allows for sustainable growth and development through adaptive capabilities, principally including the ability to effectively respond to disruptions to maintain consistent operations. This paper explores the opportunities presented by Artificial Intelligence (AI) in enhancing supply chain resilience. We first conceptualise resilience through a 4-C model: context, capabilities, choices, and contingencies. We then explore a range of AI approaches and develop a research roadmap that attempts to map particular technologies holding potential to the 4-C model.

KW - supply chain resilience

KW - artificial intelligence

KW - explainability

KW - industry 5.0

UR - https://www.scopus.com/pages/publications/85208043066

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DO - 10.1016/j.ifacol.2024.09.195

M3 - Conference article

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T2 - 18th IFAC Symposium on Information Control Problems in Manufacturing

Y2 - 28 August 2024 through 30 August 2024

ER -

Artificial Intelligence Opportunities for Resilient Supply Chains

Abstract

UN SDGs

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