Artificial intelligence as a catalyst for supply chain resilience and sustainability - A systematic literature review
Type
conference paper
Date Issued
2023-06
Author(s)
Abstract (De)
Purpose
The use of artificial intelligence (AI) is rising sharply in almost all business areas, driven not least by digitization processes and the networking of physical and virtual objects through the Internet of things. Supply chain management (SCM) is also affected by this trend, expressed in practice with an increasing number of AI-based solution providers and in research with growing attention in scientific publications.
Design/methodology/approach
A systematic literature review of numerous research papers and scientific publications on the interplay of AI, supply chain resilience (SCRES), and supply chain sustainability (SCSUS) is conducted. In addition, selective expert interviews will be shown to validate and refine the findings of the systematic literature review.
Findings
This study presents an updated picture of recent developments, emerging trends, and gaps for future research in AI to improve SCRES and SCSUS.
Theoretical implications
From the findings, a theory is derived that relates to the use and possibilities of AI for SCRES and SCSUS so that a general conclusion should be allowed. Furthermore, observations in practice should be made explainable.
Practical implications
From the derived theory, practitioners and decision-makers can conclude their own (smart and digitized) corporate strategy and uncover areas for action.
Original/value
With the help of this systematic literature review, theories in SCM are to be improved, and knowledge of real-world problems is to be advanced.
The use of artificial intelligence (AI) is rising sharply in almost all business areas, driven not least by digitization processes and the networking of physical and virtual objects through the Internet of things. Supply chain management (SCM) is also affected by this trend, expressed in practice with an increasing number of AI-based solution providers and in research with growing attention in scientific publications.
Design/methodology/approach
A systematic literature review of numerous research papers and scientific publications on the interplay of AI, supply chain resilience (SCRES), and supply chain sustainability (SCSUS) is conducted. In addition, selective expert interviews will be shown to validate and refine the findings of the systematic literature review.
Findings
This study presents an updated picture of recent developments, emerging trends, and gaps for future research in AI to improve SCRES and SCSUS.
Theoretical implications
From the findings, a theory is derived that relates to the use and possibilities of AI for SCRES and SCSUS so that a general conclusion should be allowed. Furthermore, observations in practice should be made explainable.
Practical implications
From the derived theory, practitioners and decision-makers can conclude their own (smart and digitized) corporate strategy and uncover areas for action.
Original/value
With the help of this systematic literature review, theories in SCM are to be improved, and knowledge of real-world problems is to be advanced.
Language
English
HSG Classification
contribution to scientific community
HSG Profile Area
SoM - Business Innovation
Event Title
35th NOFOMA 2023 – Logistics During Global Crises
Event Location
Helsinki - Espoo, Finland
Event Date
14 - 16 June 2023
Subject(s)
Division(s)
Eprints ID
269940