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Please use this identifier to cite or link to this item: https://digital.lib.ueh.edu.vn/handle/UEH/72918
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dc.contributor.advisorĐinh Tiên Minhen_US
dc.contributor.authorNguyễn Kim Cườngen_US
dc.contributor.otherHồ Thị Trang Bạchen_US
dc.contributor.otherLê Tuấn Kiệten_US
dc.contributor.otherTrần Phương Maien_US
dc.contributor.otherTrịnh Thị Thanh Huyềnen_US
dc.date.accessioned2024-11-21T02:31:38Z-
dc.date.available2024-11-21T02:31:38Z-
dc.date.issued2024-
dc.identifier.urihttps://digital.lib.ueh.edu.vn/handle/UEH/72918-
dc.description.abstractStudy “Applying Artificial Intelligence (AI) toward a green lifestyle: Evidencefrom implementing Mobile application in source-separated waste sorting in Ho Chi Minh City" aims to understand the interaction of AI and the intention to use mobile applications in implementing waste separation at source, the study focuses on the HoChi Minh City market. After referencing theories and results of related studies, there search team proposed a new research model base on the Theory of Planned Behavior(TPB) and Technology Acceptance Model (TAM), adding the correlations between factors that most previous studies have not shown, suitable with the context of the HoChi Minh City market. The research was carried out utilizing both qualitative and quantitative methodologies. In the first step, the research team obtained preliminary findings using the qualitative approach of interviewing specialists and conducting focus groups. Specifically, two specialists and a group of six representatives provided ideas for correcting the theory, building the scale, logic, and so on. In the second stage, the quantitative research approach was conducted on 308 Gen Z and Y citizens in Ho Chi Minh City using the non-probability sampling method and the convenience sampling methodology. Finally, Cronbach's Alpha reliability test, exploratory factor analysis (EFA), AVE, CR and structural equation modeling (SEM) were used to evaluate the scale, hypotheses, and proposed study model. Based on the findings of the study, all of the hypotheses were approved. Perceived Usefulness, Perceived Ease of Use, Perceived Playfulness and Environmental Concern both influence Behavioral Intention, Perceived Ease of Use have influence on Perceived Usefulness, Behavioral Intention have influence on Behavior in using the AI waste classification applications. The study has identified the components affecting Behavioral Intention as Perceived Usefulness, Perceived Ease of Use, Perceived Playfulness and Environmental Concern, from which solutions and governance implications will be proposed. Some limitations of the study and future research directions are also mentioned. The theoretical and practical implications of this study are also discussed.en_US
dc.format.medium113 p.en_US
dc.language.isoenen_US
dc.publisherUniversity of Economics Ho Chi Minh Cityen_US
dc.relation.ispartofseriesGiải thưởng Nhà nghiên cứu trẻ UEH 2024en_US
dc.subjectWaste classificationen_US
dc.subjectSource-separated waste sortingen_US
dc.subjectMobile applicationsen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectAIen_US
dc.subjectHo Chi Minh Cityen_US
dc.titleApplying Artificial Intelligence (Ai) Toward A Green Lifestyle: Evidence From Implementing Mobile Application In Source-Separated Waste Sorting In Ho Chi Minh City.en_US
dc.typeResearch Paperen_US
ueh.specialityKinh tếen_US
ueh.awardGiải Ben_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextreserved-
item.cerifentitytypePublications-
item.fulltextFull texts-
item.openairetypeResearch Paper-
item.languageiso639-1en-
Appears in Collections:Nhà nghiên cứu trẻ UEH
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