The Manufacturing Sector in Mauritius: Building Supply Chain Resilience and Business Value With Artificial Intelligence

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:AIとSCMの交差領域におけるレジリエンスとGHG削減の関連性についての事例研究として参考になる。

🏢実務担当者:サプライチェーンにおけるAI導入の機会と課題を理解し、自社のレジリエンス強化と排出削減の検討に活用できる。

🏛政策担当者:途上国における製造業のデジタル化と気候変動対策の政策立案に示唆を与える。

Abstract Manufacturing in Mauritius is mostly export-oriented. Any supply chain (SC) failure or resilience deficit may result in cancellation of orders and loss of customers, market share and revenue and reduce capability to compete globally. Addressing this challenge is complex, although digital technologies and artificial intelligence (AI) models can improve resilience by assisting decision-making and mitigate risks, thus infusing greater predictability across the SC. Supply chains are facing increasing disruptions and uncertainties owing to extreme weather events, the war in Ukraine, market volatility and the ongoing COVID-19 pandemic, among other factors. Manufacturing industries and their supply chains essentially create thousands of jobs that enable economic growth and sustain export capability. In addition, they need to maintain or increase both productivity and efficiency and recover quickly from unforeseen or unexpected challenges – that is they need to be resilient. Transformation initiatives, whether in production or supply chain management (SCM), are never easy. Process changes not supported by data or hurried human decisions can sometimes have unintended consequences, mainly adverse. However, in times of greater uncertainty (war and pandemic), setbacks can have greater consequences on the business. Manufacturers are already apprehensive and report slowing exports as recession concerns have caused consumers and businesses to pull back on spending. There is therefore a need to reduce uncertainty and augment resilience by unlocking and synthesising insights that emanate from the power of data analytics, AI and machine learning to improve the resilience efficiency balance. This chapter will discuss the opportunities arising from the adoption and implementation of digital technologies and AI in SCM, leading to better value creation, less greenhouse gas emissions and resilience. The hurdles that enterprises are facing to integrate AI in their logistics and SCs will also be highlighted. This work comments on initiatives that uphold the objectives of SDG 8 – decent work and economic growth, SDG 9 – industry, innovation & infrastructure and SDG 13 – climate action.

• openalex https://doi.org/10.1108/978-1-83753-540-820241018first seen 2026-08-02 18:05:10