Exploring the impact of AI investments on waste management and mitigation from the Lens of sustainable circular economy

Bibliographic Data

ID21403444
AuthorsShanshan Li (0000-0001-5116-3588, Hunan University of Finance and Economics), Ummara Razi (0000-0002-5981-5736, Bahçeşehir University), Hawazen Almugren (Princess Nourah bint Abdulrahman University), Leilei Zhang (0000-0002-5296-8430, Zhengzhou University, corresponding author), Aradhana Galgotia (Galgotias University)
Year2026
Volume224
Pages124468
Publication date2026-03-01
Open AccessYes
TypeARTICLE
VenueTechnological Forecasting and Social Change (JOURNAL)
Journal identifiersISSN: 0040-1625 • E-ISSN: 1873-5509
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.techfore.2025.124468
OpenAlexW7113904311
LanguageEN
Citations received3
References cited47

Although artificial intelligence (AI) is boosting environmental and socio-economic progress in developed countries, its role in waste reduction, management, and recycling remains limited. Hence, this study explores the role of AI investments in waste management (WGN) and waste mitigation efforts in G7 economies through quarterly data from 2012Q1 to 2022Q4. In doing so, several econometric techniques were applied, which range from diagnostic tests for unit root and multicollinearity issues, while the primary method used was quantile regression due to the nonlinearity of the data. The outcomes show that AI's impact increases from lower to higher quantiles, from Q 15th − 0.001 towards Q 75th 0.030. In other words, AI is efficient in areas where WGN is low. However, WGN might increase due to AI, where the waste is already high due to the acceleration of industrial sectors and consumption. Furthermore, industrial productivity has a positive but insignificant impact, while urbanization has a negative and significant impact on WGN across quantiles. Air pollution has asymmetrical effects on WGN in both models. Novel policies that adopt AI technologies and applications and reduce air pollution should acknowledge the rising significance of waste management and circular economic models

Circular economy · Econometric model · Multicollinearity · Productivity · Proxy (statistics) · Quantile regression · Unit (ring theory) · Urbanization · Food Waste Reduction and Sustainability · Municipal Solid Waste Management · Recycling and Waste Management Techniques

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