When Generative AI Meets Abuse: What Are You Anxious About?
The rapid progress of generative artificial intelligence (AI) has sparked growing concerns regarding its misuse, privacy risks, and ethical issues. This study investigates the interplay between Generative AI Abuse Anxiety, trust, perceived usefulness, acceptance, and the intention to use it. Using v...
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| Published in | Journal of theoretical and applied electronic commerce research Vol. 20; no. 3; p. 215 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
14.08.2025
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| Online Access | Get full text |
| ISSN | 0718-1876 0718-1876 |
| DOI | 10.3390/jtaer20030215 |
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| Abstract | The rapid progress of generative artificial intelligence (AI) has sparked growing concerns regarding its misuse, privacy risks, and ethical issues. This study investigates the interplay between Generative AI Abuse Anxiety, trust, perceived usefulness, acceptance, and the intention to use it. Using variance-based partial least squares (PLS-SEM), we analyze 318 valid survey responses. The findings reveal that Generative AI Abuse Anxiety negatively impacts trust, perceived usefulness, acceptance, and the intention to use generative AI. Additionally, different subdimensions of trust play significant roles in influencing users’ technology acceptance and intention to use it, though the specific mechanisms differ. This research extends the applicability of the technology acceptance model to the generative AI context and enriches the multidimensional framework of trust studies. |
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| AbstractList | The rapid progress of generative artificial intelligence (AI) has sparked growing concerns regarding its misuse, privacy risks, and ethical issues. This study investigates the interplay between Generative AI Abuse Anxiety, trust, perceived usefulness, acceptance, and the intention to use it. Using variance-based partial least squares (PLS-SEM), we analyze 318 valid survey responses. The findings reveal that Generative AI Abuse Anxiety negatively impacts trust, perceived usefulness, acceptance, and the intention to use generative AI. Additionally, different subdimensions of trust play significant roles in influencing users’ technology acceptance and intention to use it, though the specific mechanisms differ. This research extends the applicability of the technology acceptance model to the generative AI context and enriches the multidimensional framework of trust studies. |
| Author | Tan, Haowen Song, Yuanzhao |
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