{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T22:19:52Z","timestamp":1777587592786,"version":"3.51.4"},"reference-count":74,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T00:00:00Z","timestamp":1754438400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Chengdu University of Technology Higher Education Talent Training Quality and Teaching Reform Project","award":["JG2430085"],"award-info":[{"award-number":["JG2430085"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>In the context of increasing Artificial Intelligence integration in higher education, understanding the factors influencing university teachers\u2019 adoption of AI tools is critical for effective implementation. This study adopts a perception\u2013intention\u2013behavior framework to explores the roles of perceived usefulness, perceived ease of use, perceived trust, perceived substitution crisis, and perceived risk in shaping teachers\u2019 behavioral intention and actual usage of AI tools. It also investigates the moderating effects of peer influence and organizational support on these relationships. Using a comprehensive survey instrument, data was collected from 487 university teachers across four major regions in China. The results reveal that perceived usefulness and perceived ease of use are strong predictors of behavioral intention, with perceived ease of use also significantly influencing perceived usefulness. Perceived trust serves as a key mediator, enhancing the relationship between perceived usefulness, perceived ease of use, and behavioral intention. While perceived substitution crisis negatively influenced perceived trust, it showed no significant direct effect on behavioral intention, suggesting a complex relationship between job displacement concerns and AI adoption. In contrast, perceived risk was found to negatively impact behavioral intention, though it was mitigated by perceived ease of use. Peer influence significantly moderated the relationship between perceived trust and behavioral intention, highlighting the importance of peer influence in AI adoption, while organizational support amplified the effect of perceived ease of use on behavioral intention. These findings inform practical strategies such as co-developing user-centered AI tools, enhancing institutional trust through transparent governance, leveraging peer support, providing structured training and technical assistance, and advancing policy-level initiatives to guide digital transformation in universities.<\/jats:p>","DOI":"10.3390\/systems13080664","type":"journal-article","created":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T07:45:11Z","timestamp":1754466311000},"page":"664","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["From Perception to Practice: Artificial Intelligence as a Pathway to Enhancing Digital Literacy in Higher Education Teaching"],"prefix":"10.3390","volume":"13","author":[{"given":"Zhili","family":"Zuo","sequence":"first","affiliation":[{"name":"School of Management Science, Chengdu University of Technology, Chengdu 610059, China"}]},{"given":"Yilun","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5962-9911","authenticated-orcid":false,"given":"Shiyu","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Management Science, Chengdu University of Technology, Chengdu 610059, China"}]},{"given":"Lisheng","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Management Science, Chengdu University of Technology, Chengdu 610059, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"121101","DOI":"10.1007\/s11432-021-3449-x","article-title":"Toward the third generation artificial intelligence","volume":"66","author":"Zhang","year":"2023","journal-title":"Sci. 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