Is AI adoption a pro-environmental choice? Integrating value-belief-norm theory and theory of planned behavior

Purpose Artificial intelligence (AI) could be essential to helping organizations improve efficiency and enable quick, accurate decision-making. This study investigates the adoption behavior of AI technology from an ecological perspective. Using the value-belief-norm (VBN) and the theory of planned behavior (TPB), a conceptual model was developed to address the research gap. Design/methodology/approach A survey of 343 respondents in Malaysia was conducted. Partial least squares structural equation modeling was used to identify the critical drivers of AI adoption behavior. Findings Egoistic values do not enhance the new ecological paradigm for AI, while altruistic and biospheric values do. This paradigm strengthens awareness of AI's consequences, shaping responsibility, personal norms, subjective norms, attitudes and perceived behavioral control. These factors, in turn, positively influence AI adoption behavior. Originality/value This study offers theoretical and practical insights into how a new ecological paradigm could affect individuals' adoption behavior of new technologies such as AI. The findings also provide practical guidance for managers and policymakers to promote the adoption of environmentally responsible AI by strengthening environmental values, awareness and pro-environmental attitudes.

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Publication Details

Journal
Management & Sustainability An Arab Review
Published
2026-09-21
DOI
https://doi.org/10.1108/msar-02-2026-0096
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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Is AI adoption a pro-environmental choice? Integrating value-belief-norm theory and theory of planned behavior

Mosharrof Hosen, Idrees Waris, Irfan Talib Hameed, Midhat Nadeem et al.
Management & Sustainability An Arab Review
AI in Service Interactions
article

Is AI adoption a pro-environmental choice? Integrating value-belief-norm theory and theory of planned behavior

Mosharrof Hosen, Idrees Waris, Irfan Talib Hameed, Midhat Nadeem, Rajat Subhra Chatterjee
article en

Abstract

Purpose Artificial intelligence (AI) could be essential to helping organizations improve efficiency and enable quick, accurate decision-making. This study investigates the adoption behavior of AI technology from an ecological perspective. Using the value-belief-norm (VBN) and the theory of planned behavior (TPB), a conceptual model was developed to address the research gap. Design/methodology/approach A survey of 343 respondents in Malaysia was conducted. Partial least squares structural equation modeling was used to identify the critical drivers of AI adoption behavior. Findings Egoistic values do not enhance the new ecological paradigm for AI, while altruistic and biospheric values do. This paradigm strengthens awareness of AI's consequences, shaping responsibility, personal norms, subjective norms, attitudes and perceived behavioral control. These factors, in turn, positively influence AI adoption behavior. Originality/value This study offers theoretical and practical insights into how a new ecological paradigm could affect individuals' adoption behavior of new technologies such as AI. The findings also provide practical guidance for managers and policymakers to promote the adoption of environmentally responsible AI by strengthening environmental values, awareness and pro-environmental attitudes.

Management & Sustainability An Arab Review
Samarkand State University named after Sharof Rashidov (UZ), Daffodil International University (BD), University of Nizwa (OM), High Institute for Management Sciences (EG), Taylor's University (MY), Institute of Business Management (PK), Institute of Business, Psychology and Management (RU), University of Plymouth (GB)
Openalex Percentile: Top 9%
AI in Service Interactions
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Is AI adoption a pro-environmental choice? Integrating value-belief-norm theory and theory of planned behavior — Mosharrof Hosen, Idrees Waris, et al. · Management & Sustainability An Arab Review (2026) | TGRS Research Map | TGRS