How artificial intelligence-based supply chain analytics enable supply chain agility and innovation? An intellectual capital perspective

Purpose This study aims to empirically examine the impact of intellectual capital on the adoption of artificial intelligence-based supply chain analytics in manufacturing companies. It also aims to examine the potential impact of artificial intelligence (AI)-based supply chain analytics on supply chain innovation and supply chain agility. Furthermore, this study explores the association supply chain innovation and supply chain agility. Design/methodology/approach Data were collected from 252 respondents who work in supply chain management of manufacturing companies in Jordan. AMOS software, which is based on the Structural Equation Modeling approach, was used to test hypotheses. Findings The findings reveal positive effects of the three components of intellectual capital, including human capital, structural capital, and social capital, on AI-based supply chain analytics. They also confirm a positive effect of AI-based supply chain analytics on both supply chain innovation and supply chain agility. Furthermore, the empirical results support a positive effect of supply chain agility on supply chain innovation. Originality/value This study provides valuable practical implications and enriches the literature on the determinants of supply chain analytics adoption and its role in developing the dynamic capabilities of manufacturing companies, such as supply chain innovation and supply chain agility.

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Publication Details

Journal
Supply Chain Management An International Journal
Published
2025-03-11
DOI
https://doi.org/10.1108/scm-09-2024-0558
Citations
8
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
18.27
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article

How artificial intelligence-based supply chain analytics enable supply chain agility and innovation? An intellectual capital perspective

T. Ramayah, Al-Zoubi Lamees
8 citations
Supply Chain Management An International Journal
Big Data and Business Intelligence
18.27
article

How artificial intelligence-based supply chain analytics enable supply chain agility and innovation? An intellectual capital perspective

T. Ramayah, Al-Zoubi Lamees
article en
8 citations

Abstract

Purpose This study aims to empirically examine the impact of intellectual capital on the adoption of artificial intelligence-based supply chain analytics in manufacturing companies. It also aims to examine the potential impact of artificial intelligence (AI)-based supply chain analytics on supply chain innovation and supply chain agility. Furthermore, this study explores the association supply chain innovation and supply chain agility. Design/methodology/approach Data were collected from 252 respondents who work in supply chain management of manufacturing companies in Jordan. AMOS software, which is based on the Structural Equation Modeling approach, was used to test hypotheses. Findings The findings reveal positive effects of the three components of intellectual capital, including human capital, structural capital, and social capital, on AI-based supply chain analytics. They also confirm a positive effect of AI-based supply chain analytics on both supply chain innovation and supply chain agility. Furthermore, the empirical results support a positive effect of supply chain agility on supply chain innovation. Originality/value This study provides valuable practical implications and enriches the literature on the determinants of supply chain analytics adoption and its role in developing the dynamic capabilities of manufacturing companies, such as supply chain innovation and supply chain agility.

Supply Chain Management An International JournalVol. 30(2)
Universiti Sains Malaysia (MY), Sohar University (OM)
Openalex Percentile: Top 1%
Big Data and Business Intelligence
18.27
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How artificial intelligence-based supply chain analytics enable supply chain agility and innovation? An intellectual capital perspective — T. Ramayah, Al-Zoubi Lamees · Supply Chain Management An International Journal (2025) | TGRS Research Map | TGRS