Generation Z use of artificial intelligence products and its impact on environmental sustainability: A cross-cultural comparison
Artificial intelligence (AI) products play a significant role in achieving environmental sustainability. These products can save various resources (e.g., energy, water), achieve cost savings, and manage waste better. However, understanding the determinants affecting the use of AI products and their...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Published: |
Elsevier Ltd
2023
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| Subjects: | |
| Online Access: | http://eprints.utm.my/106429/ http://dx.doi.org/10.1016/j.chb.2023.107708 |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | Artificial intelligence (AI) products play a significant role in achieving environmental sustainability. These products can save various resources (e.g., energy, water), achieve cost savings, and manage waste better. However, understanding the determinants affecting the use of AI products and their impact on environmental sustainability is relatively low, specifically in developing countries. To fill this gap in the literature, this study develops a theoretical model by integrating two well-known theories, UTAUT and PMT, to explain the determinants influencing Generation Z use of AI products and their impact on environmental sustainability. The developed model was then evaluated using the PLS-SEM approach based on data collected from 562 respondents in Malaysia and Turkey. Although effort expectancy, performance expectancy, social influence, perceived severity, response efficacy, and response costs are significant drivers of green behavior among Malaysian individuals, effort expectancy, facilitating conditions, perceived severity, response efficacy, and response costs are essential determinants among Turkish individuals. Interestingly, there is no significant difference between the importance of coping appraisals (i.e., self-efficacy, response efficacy, and response costs) among these two populations. The outcomes provide several contributions to the literature on AI and environmental sustainability and offer valuable insights for the practitioners, policymakers, and AI product developers. |
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