Resident action in smart waste management during landfill disclosure transition: Insights from Yogyakarta's smart city initiatives

作     者：Suhardono, Sapta Lee, Chun-Hung Phan, Thi Thanh Thuy Suryawan, I. Wayan Koko 

作者机构：Univ Sebelas Maret Fac Math & Nat Sci Environm Sci Study Program Surakarta 57126 Indonesia Natl Dong Hwa Univ Coll Environm Studies & Oceanog Dept Nat Resources & Environm Studies Hualien 97401 Taiwan Univ Pertamina Ctr Environm Solut CVISION Jalan Sinabung 2 Jakarta 12220 Indonesia Natl Dong Hwa Univ Coll Environm Studies & Oceanog Ctr Interdisciplinary Res Ecol & Sustainabil Hualien 97401 Taiwan Vietnam Natl Univ Forestry Dong Nai Campus Bien Hoa 810000 Dong Nai Vietnam Univ Pertamina Fac Infrastruct Planning Dept Environm Engn Jalan Sinabung 2 Jakarta 12220 Indonesia 

出 版 物：《CLEANER PRODUCTION LETTERS》 (Clean Prod. Lett.)

年 卷 期：2025年第8卷

主　　题：Smart waste management Resident participation Smart cities Landfill closure Urban sustainability Smart city solutions 

摘      要：Globally, the rise of smart cities underscores the critical role of resident participation in advancing sustainable urban systems, particularly in managing waste during periods of transition. While technological innovations such as sensing and data analytics have garnered attention, the integration of these solutions with social dynamics remains underexplored. This study addresses this gap by investigating the dynamics of resident engagement in smart waste management during the transitional phase of landfill closures, using Yogyakarta, Indonesia, as a case study. The research aims to bridge the disconnect between technological advancements and community involvement, emphasizing their interplay in ensuring sustainable outcomes. Adopting a mixed-methods approach, this study integrates advanced computational intelligence with qualitative insights into behavioral drivers. Key elements of the methodological framework include sensing, learning, understanding, and acting, enabling a comprehensive exploration of the technological and human dimensions of waste management. Advanced predictive models analyze patterns in waste generation, optimizing system responsiveness and efficiency, while qualitative data reveal the critical role of education and tailored communication strategies in fostering resident participation. Findings demonstrate that combining cutting-edge technology with communitycentric initiatives leads to significant improvements in waste management outcomes. Strategic educational campaigns and adaptive communication tailored to local contexts enhance public engagement and sustainable practices. Furthermore, the study underscores the importance of continuous learning and adaptive management, enabling urban planning frameworks to evolve in response to emerging challenges. This synergy between technology and civic participation is pivotal for the long-term success of smart city initiatives. The novelty of this research lies in its holistic integration of technolog