Examining Generative AI User Disclosure Intention: A Perceived Affordance Perspective
Generative AI needs to collect user data to provide more accurate answers. This may raise users’ privacy concern and undermine their disclosure intention. The purpose of this research is to examine generative AI user disclosure intention from the perspective of technological–social affordance. We ad...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Journal of Theoretical and Applied Electronic Commerce Research |
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| Online Access: | https://www.mdpi.com/0718-1876/20/2/99 |
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| _version_ | 1839653567560941568 |
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| author | Tao Zhou Xiaoying Wu |
| author_facet | Tao Zhou Xiaoying Wu |
| author_sort | Tao Zhou |
| collection | DOAJ |
| description | Generative AI needs to collect user data to provide more accurate answers. This may raise users’ privacy concern and undermine their disclosure intention. The purpose of this research is to examine generative AI user disclosure intention from the perspective of technological–social affordance. We adopted a mixed method of PLS-SEM and fsQCA to conduct data analysis. The results reveal that perceived affordance of content generation (including information association, content quality, and interactivity), perceived affordance of privacy protection (including anonymity and privacy statement), and perceived affordance of anthropomorphic interaction (including empathy and social presence) affect privacy concern and reciprocity, both of which further affect disclosure intention. The fsQCA identified two paths that trigger user disclosure intention. These results imply that generative AI platforms need to increase users’ perceived affordance in order to promote their disclosure intention and ensure the continuous development of platforms. |
| format | Article |
| id | doaj-art-323661f95c834c99b84b4f2a12e38fba |
| institution | Matheson Library |
| issn | 0718-1876 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Theoretical and Applied Electronic Commerce Research |
| spelling | doaj-art-323661f95c834c99b84b4f2a12e38fba2025-06-25T14:03:45ZengMDPI AGJournal of Theoretical and Applied Electronic Commerce Research0718-18762025-05-012029910.3390/jtaer20020099Examining Generative AI User Disclosure Intention: A Perceived Affordance PerspectiveTao Zhou0Xiaoying Wu1School of Management, Hangzhou Dianzi University, Hangzhou 310018, ChinaSchool of Management, Hangzhou Dianzi University, Hangzhou 310018, ChinaGenerative AI needs to collect user data to provide more accurate answers. This may raise users’ privacy concern and undermine their disclosure intention. The purpose of this research is to examine generative AI user disclosure intention from the perspective of technological–social affordance. We adopted a mixed method of PLS-SEM and fsQCA to conduct data analysis. The results reveal that perceived affordance of content generation (including information association, content quality, and interactivity), perceived affordance of privacy protection (including anonymity and privacy statement), and perceived affordance of anthropomorphic interaction (including empathy and social presence) affect privacy concern and reciprocity, both of which further affect disclosure intention. The fsQCA identified two paths that trigger user disclosure intention. These results imply that generative AI platforms need to increase users’ perceived affordance in order to promote their disclosure intention and ensure the continuous development of platforms.https://www.mdpi.com/0718-1876/20/2/99generative AIperceived affordancedisclosure intention |
| spellingShingle | Tao Zhou Xiaoying Wu Examining Generative AI User Disclosure Intention: A Perceived Affordance Perspective Journal of Theoretical and Applied Electronic Commerce Research generative AI perceived affordance disclosure intention |
| title | Examining Generative AI User Disclosure Intention: A Perceived Affordance Perspective |
| title_full | Examining Generative AI User Disclosure Intention: A Perceived Affordance Perspective |
| title_fullStr | Examining Generative AI User Disclosure Intention: A Perceived Affordance Perspective |
| title_full_unstemmed | Examining Generative AI User Disclosure Intention: A Perceived Affordance Perspective |
| title_short | Examining Generative AI User Disclosure Intention: A Perceived Affordance Perspective |
| title_sort | examining generative ai user disclosure intention a perceived affordance perspective |
| topic | generative AI perceived affordance disclosure intention |
| url | https://www.mdpi.com/0718-1876/20/2/99 |
| work_keys_str_mv | AT taozhou examininggenerativeaiuserdisclosureintentionaperceivedaffordanceperspective AT xiaoyingwu examininggenerativeaiuserdisclosureintentionaperceivedaffordanceperspective |