Systematical Review: How Artificial Intelligence impact Supply Chain Capability and Capacity in Emerging Markets

The purpose of this study is to investigate how Artificial Intelligence (AI) are being implemented in Supply Chain (SC) in emerging markets. Using a systematical literature review methodolody, this research analyze the publications available on Scopus, Emerald and Elsevier that link AI and SC. A total of 55 research studies have been identified, which are futher screened and finalized with 24 research studies. The research reviews and analyzes comprehensively the 24 studies that found relevant with impact supply chain capability and capacity in emerging markets. Our study underscores AI's contributions. AI enhances operational efficiency, resilience, and sustainability in supply chains, crucially impacting economic growth and global competitiveness. It acts as a catalyst for transforming supply chain dynamics, optimizing decision-making, mitigating risks, and fostering innovation across various sectors. Emerging markets play a pivotal role in AI adoption, leveraging its capabilities to adapt to market uncertainties and enhance supply chain agility. This comprehensive analysis not only elucidates AI's transformative potential but also underscores its critical role in shaping the future of global supply chain management. This study makes a comprehensive view from AI implication to SC in emerging market. The source of analyze based on academic credibility, novelty and relevance.

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Publication Details

Journal
INOBIS Jurnal Inovasi Bisnis dan Manajemen Indonesia
Published
2024-12-21
DOI
https://doi.org/10.31842/jurnalinobis.v7i4.333
Citations
1
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
0.55
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article

Systematical Review: How Artificial Intelligence impact Supply Chain Capability and Capacity in Emerging Markets

Franciskus Antonius Alijoyo, Y. Albert
1 citations
INOBIS Jurnal Inovasi Bisnis dan Manajemen Indonesia
Supply Chain Resilience and Risk Management
0.55
article

Systematical Review: How Artificial Intelligence impact Supply Chain Capability and Capacity in Emerging Markets

Franciskus Antonius Alijoyo, Y. Albert
article en
1 citations

Abstract

The purpose of this study is to investigate how Artificial Intelligence (AI) are being implemented in Supply Chain (SC) in emerging markets. Using a systematical literature review methodolody, this research analyze the publications available on Scopus, Emerald and Elsevier that link AI and SC. A total of 55 research studies have been identified, which are futher screened and finalized with 24 research studies. The research reviews and analyzes comprehensively the 24 studies that found relevant with impact supply chain capability and capacity in emerging markets. Our study underscores AI's contributions. AI enhances operational efficiency, resilience, and sustainability in supply chains, crucially impacting economic growth and global competitiveness. It acts as a catalyst for transforming supply chain dynamics, optimizing decision-making, mitigating risks, and fostering innovation across various sectors. Emerging markets play a pivotal role in AI adoption, leveraging its capabilities to adapt to market uncertainties and enhance supply chain agility. This comprehensive analysis not only elucidates AI's transformative potential but also underscores its critical role in shaping the future of global supply chain management. This study makes a comprehensive view from AI implication to SC in emerging market. The source of analyze based on academic credibility, novelty and relevance.

INOBIS Jurnal Inovasi Bisnis dan Manajemen IndonesiaVol. 7(4)
Parahyangan Catholic University (ID)
Industry, innovation and infrastructure
Openalex Percentile: Top 19%
Supply Chain Resilience and Risk Management
0.55
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Systematical Review: How Artificial Intelligence impact Supply Chain Capability and Capacity in Emerging Markets — Franciskus Antonius Alijoyo, Y. Albert · INOBIS Jurnal Inovasi Bisnis dan Manajemen Indonesia (2024) | TGRS Research Map | TGRS