{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T16:11:54Z","timestamp":1779379914021,"version":"3.53.1"},"reference-count":86,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,2,15]],"date-time":"2026-02-15T00:00:00Z","timestamp":1771113600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Generative AI offers promising potential to promote environmental sustainability through personalized recommendations that influence individual behavior. This study examines the factors influencing the adoption and actual use of generative AI recommendations for environmental sustainability among Gen Z users in the Philippines by integrating the Theory of Planned Behavior (TPB) and the Technology\u2013Environmental, Economic, and Social Sustainability Theory (T-EESST) with key generative AI attributes, together with trust and perceived risk. Survey data were collected from 531 Gen Z users in higher education institutions in the National Capital Region (NCR), Philippines, and analyzed using a hybrid SEM and ANN approach. Results from SEM indicate that key AI attributes, namely perceived anthropomorphism, perceived intelligence, and perceived animacy, significantly influenced users\u2019 attitude towards generative AI recommendations. Attitude, perceived behavioral control, and trust emerged as significant predictors of behavioral intention, which have an eventual positive relation to actual use and environmental sustainability outcomes. In contrast, subjective norms and perceived risk did not significantly affect behavioral intention, which may suggest that Gen Z users\u2019 engagement with generative AI for environmental sustainability is primarily driven by internal evaluations, perceived capability, and trust rather than social pressure or risk concerns. Complementing these findings, the ANN analysis identified perceived behavioral control, attitude, and trust as the most important factors, reinforcing the robustness of the SEM results. Overall, this study integrates existing sustainability and technology-adoption literature by demonstrating how generative AI recommendations can support environmental sustainability among Gen Z users by combining behavioral theory, sustainability theory, and AI attributes through a hybrid SEM\u2013ANN approach in the context of a developing country.<\/jats:p>","DOI":"10.3390\/info17020203","type":"journal-article","created":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T11:11:28Z","timestamp":1771240288000},"page":"203","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Generative AI Recommendations for Environmental Sustainability: A Hybrid SEM\u2013ANN Analysis of Gen Z Users in the Philippines"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8137-5343","authenticated-orcid":false,"given":"Victor James C.","family":"Escolano","sequence":"first","affiliation":[{"name":"Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3949-1498","authenticated-orcid":false,"given":"Yann-Mey","family":"Yee","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5623-5941","authenticated-orcid":false,"given":"Wei-Jung","family":"Shiang","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1264-7499","authenticated-orcid":false,"given":"Alexander A.","family":"Hernandez","sequence":"additional","affiliation":[{"name":"College of Computer Studies and Multimedia Arts, FEU Institute of Technology, Manila City 1015, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5083-3356","authenticated-orcid":false,"given":"Do Van","family":"Nang","sequence":"additional","affiliation":[{"name":"Faculty of Electronics Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4013195","DOI":"10.1155\/2024\/4013195","article-title":"The Road Ahead: Emerging Trends, Unresolved Issues, and Concluding Remarks in Generative AI\u2014A Comprehensive Review","volume":"2024","author":"Balasubramaniam","year":"2024","journal-title":"Int. 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