The Power of AI Transparency, Rewards, and Tracking

How Mobile App Features Drive the Adoption of Smart Trash Bins Through Trust and Perceived Value

Bibliographic Data

ID21578683
AuthorsKang Li (0000-0001-6218-5715, Zayed University, corresponding author), Wei Chen (0000-0002-9419-148X, Khalifa University of Science and Technology)
Year2026
Pages1-21
Publication date2026-06-22
Open AccessYes
TypeARTICLE
VenueJournal of Broadcasting & Electronic Media (JOURNAL)
Journal identifiersISSN: 0883-8151 • E-ISSN: 1550-6878
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/08838151.2026.2690271
OpenAlexW7165541966
LanguageEN
References cited44

This study investigates how mobile app features (AI transparency, rewards, and tracking) influence smart bin adoption. Grounded in nudge theory and the Stimulus-Organism-Response framework, an online experiment tested their effects on trust, perceived value, and adoption intention. Trust mediated the effect of all three features on adoption intention. Perceived value also mediated the effect of AI type and rewards, but only white-box AI showed a direct effect on intention. An interaction effect between rewards and tracking was found in the system with black-box AI. The findings offer theoretical contributions and practical guidelines for promoting sustainable technology use

Bin · Grounded theory · Mobile apps · Mobile device · AI in Service Interactions · Human-Automation Interaction and Safety · Technology Adoption and User Behaviour

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