An analysis on the role of artificial intelligence in green supply chains

Yimin Yang, Chaoqun Yi, Hailing Li, Xuesong Dong, Lulu Yang and Zilong Wang

Technological Forecasting and Social Change, 2025, vol. 217, issue C

Abstract: This paper investigates the retailer’s artificial intelligence (AI) adoption strategies in the green supply chain involving a manufacturer and a retailer. We demonstrate that the decision to introduce AI is influenced by the retailer’s estimation of the consumers’ green preference (CGP) without AI as well as the unit adoption cost of AI. Specifically, irrespective of whether the retailer underestimates or overestimates the CGP without AI, as the estimation bias increases, the retailer becomes more inclined to adopt AI; however, an increase in the unit adoption cost will discourage adoption. Furthermore, we find that if the retailer underestimates the CGP without AI, adopting AI may negatively impact the profits of both the manufacturer and the supply chain, as well as the greenness level, while simultaneously enhancing social welfare. Conversely, if the CGP is overestimated, adopting AI can improve the manufacturer’s profit and the supply chain’s profit but decrease the greenness level and potentially harm social welfare. We extend the model by considering the prediction accuracy of AI, demonstrating that as the prediction accuracy increases, the retailer who underestimates the CGP without AI becomes more inclined to adopt AI; however, this may not hold under certain conditions if the CGP is overestimated.

Keywords: Green supply chain; Artificial intelligence (AI); Technology adoption; Social welfare (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162525002008
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:217:y:2025:i:c:s0040162525002008

DOI: 10.1016/j.techfore.2025.124169

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().