Leveraging artificial intelligence to foster pro-environmental and green behavior in organizations

Insights from PLS-SEM and necessary condition analysis

Bibliographic Data

ID6455403
AuthorsMei Peng Low (0000-0002-3141-3081), Fitriya Abdul Rahim (0000-0002-6313-508X), Tai Ming Wut (0000-0002-9383-1094)
Year2025
Volume9
Pages100786-100786
Publication date2025-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSustainable Futures (JOURNAL)
Journal identifiersISSN: 2666-1888
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.sftr.2025.100786
OpenAlexW4411050132
LanguageEN
Citations received4
References cited63

As environmental sustainability becomes an increasingly critical priority for organizations, understanding the technological and psychological factors driving pro-environmental and green behaviors is essential. This study examines the impact of artificial intelligence usage on employee behaviors within service-based organizations. It focuses on currently employed individuals affiliated with these organizations with AI technology experience. This research integrates concepts from the Unified Theory of Acceptance and Use of Technology and Protection Motivation Theory to examine key factors including effort expectancy, performance expectancy, social influence, perceived severity, perceived vulnerability, response cost, response efficacy, and self-efficacy. The study uses Partial Least Squares Structural Equation Modeling and Necessary Condition Analysis to reveal distinct behavior in influencing pro-environmental and green behaviors. Pro-environmental behavior is primarily driven by broader motivational factors such as social influence and perceived severity, whereas green behavior is more strongly associated with practical considerations like effort expectancy and performance expectancy. Additionally, Necessary Condition Analysis identifies critical threshold conditions necessary to achieve specific levels of these behaviors by offering actionable insights for organizational interventions. The research findings underscore the theoretical and practical implications. Theoretically, this research advances understanding by distinguishing the drivers of pro-environmental and green behaviors while demonstrating the methodological utility of Necessary Condition Analysis. Practically, the research provides actionable strategies for organizations seeking to enhance environmental sustainability efforts by leveraging AI technologies. These dynamics highlight the necessity for adaptive strategies to foster a culture of environmental sustainability within organizations in the AI era

Business · Knowledge management · Computer Science · Energy, Environment, Economic Growth · Environmental Sustainability in Business · Psychology · Technology Adoption and User Behaviour

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