Perceptions of AI adoption and their impact on supply chain learning

Operationalisation of supply chain learning (SCL) is a major challenge. Technologies such as artificial intelligence (AI) are expected to favour supply chain information sharing, collaboration, and coordination, hence, supporting SCL. This paper examines how organisations’ perceptions about AI adoption influence SCL, exploring the relationship between AI’s perceived usefulness and ease of use with the SCL dimensions. We performed an online survey-based investigation with 206 Brazilian practitioners from different organisations of several industry sectors, whose responses were examined using multivariate data techniques. Similar trends in results were observed regardless of whether the relationship was between the focal company and its suppliers or between the focal company and its customers. When the perception about AI’s usefulness and ease of use are both low, captive SCL tends to occur; when both are high, SCL might occur in a distributed way. A consortium SCL prevails if only AI’s perceived ease of use is high; a selective SCL occurs if only the perceived usefulness is high. Identifying how SCL is impacted by organisations’ perceptions about AI adoption may help managers to prioritise their digitalisation efforts, adjusting them according to the expected type of knowledge to be created and shared across the supply chain.

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Publication Details

Journal
International Journal of Logistics Research and Applications
Published
2025-08-18
DOI
https://doi.org/10.1080/13675567.2025.2547202
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

Perceptions of AI adoption and their impact on supply chain learning

Rafaela Alfalla-Luque, Daniel Luiz de Mattos Nascimento, Mohsin Malik, Daryl Powell et al.
1 citations
International Journal of Logistics Research and Applications
Big Data and Business Intelligence
2.28
article

Perceptions of AI adoption and their impact on supply chain learning

Rafaela Alfalla-Luque, Daniel Luiz de Mattos Nascimento, Mohsin Malik, Daryl Powell, Alberto Portioli Staudacher, Guilherme Luz Tortorella
article en
1 citations

Abstract

Operationalisation of supply chain learning (SCL) is a major challenge. Technologies such as artificial intelligence (AI) are expected to favour supply chain information sharing, collaboration, and coordination, hence, supporting SCL. This paper examines how organisations’ perceptions about AI adoption influence SCL, exploring the relationship between AI’s perceived usefulness and ease of use with the SCL dimensions. We performed an online survey-based investigation with 206 Brazilian practitioners from different organisations of several industry sectors, whose responses were examined using multivariate data techniques. Similar trends in results were observed regardless of whether the relationship was between the focal company and its suppliers or between the focal company and its customers. When the perception about AI’s usefulness and ease of use are both low, captive SCL tends to occur; when both are high, SCL might occur in a distributed way. A consortium SCL prevails if only AI’s perceived ease of use is high; a selective SCL occurs if only the perceived usefulness is high. Identifying how SCL is impacted by organisations’ perceptions about AI adoption may help managers to prioritise their digitalisation efforts, adjusting them according to the expected type of knowledge to be created and shared across the supply chain.

International Journal of Logistics Research and Applications
The University of Melbourne (AU), SINTEF (NO), Austral University (AR), University of South-Eastern Norway (NO), Barcelona Graduate School of Mathematics (ES), Barcelona School of Economics (ES), SINTEF Manufacturing, Swinburne University of Technology (AU), Fundação Dom Cabral (BR), Universitat de Barcelona (ES), Universidad de Sevilla (ES), EAE Business School (ES), Politecnico di Milano (IT)
Openalex Percentile: Top 10%
Big Data and Business Intelligence
2.28
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