인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
This study investigates whether affordance-driven bin design can improve waste sorting behavior in low-engagement communal spaces. Grounded in the Elaboration Likelihood Model and Hartson’s User Action Framework, we derived three intervention types (Attention, Instantly Recognizable, and Goal Visualization) and evaluated them in a field study on the third floor of Building 49, S University. Disposal cases report observational outcomes. Under the Attention intervention, 17 disposal cases were recorded, and one case was sorted correctly. After applying unified iconography and color connectivity in the Instantly Recognizable stage, 279 disposal cases were recorded: 111 of 163 recyclable cases were sorted correctly (68%). Disposable cup sorting improved from 0 of 2 cup cases in Attention to 22 of 39 cup cases in Instantly Recognizable. Constraint and alternative interventions produced further gains: constraint designs increased sorting to approximately 82 percent for observed recyclable cases under that condition, and a dedicated liquid-only bin yielded an overall success rate of 78 percent and a 97 percent success rate for disposable cups (31 of 32). The results indicate that attention-capturing cues must be paired with clear, low-effort informational affordances, and that alternatives or constraints are effective for changing entrenched habits. The study is exploratory and limited to a single site. Future work should replicate the model across other sites and independently test the induction element.
본문·목차
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