Policy recommendations for the development of efficient and smart waste management systems to support sustainable cities based on the SDGs

Urban waste management represent a strategic policy domain requiring technologically driven interventions and multi-stakeholder engagement, partciulary in metropolitan areas such as Surabaya City. This study aims to formulate policy recommendations for the devolepment of an efficient and adaptive waste management system through the integration of intelegent digital technologies. Employin an exploratory qualitative approach, this research synthesizes SWOT, PESTEl, and stakeholder analyses to identify key internal and external determinats affecting the efficacy of waste governance policies. The findings indicate that, despite intitusional strengths such as a smart city vision and adequate techological infrastructure, the implementation remains hindered by centralized decision making patterns and the limited integration of green technologies. Accordingly, this study proporse a waste management system model anchored in the Internet of Things (IoT), manchine leraning, and blockchain as a framework for digital policy transformation. These recommendations are operationalized into eight strategic action plans aimed at an enhancing systemic efficiency, stakeholder participation, and accelerating the achievement of the Sustainable Development Goals (SDGs), particulary in the domains of environmental governance and sustainable urban management.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-08-15
DOI
https://doi.org/10.1051/e3sconf/202564001007/pdf
Primary Topic
Municipal Solid Waste Management
Type
article
Field-Weighted Citation Impact
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article

Policy recommendations for the development of efficient and smart waste management systems to support sustainable cities based on the SDGs

Muhammad Thoriq Alfarizi, Suci Megawati, Laskar Intifada Saifullah Fatah Wardana, Badrudin Kurniawan
Springer Link (Chiba Institute of Technology)
Municipal Solid Waste Management
article

Policy recommendations for the development of efficient and smart waste management systems to support sustainable cities based on the SDGs

Muhammad Thoriq Alfarizi, Suci Megawati, Laskar Intifada Saifullah Fatah Wardana, Badrudin Kurniawan
article en

Abstract

Urban waste management represent a strategic policy domain requiring technologically driven interventions and multi-stakeholder engagement, partciulary in metropolitan areas such as Surabaya City. This study aims to formulate policy recommendations for the devolepment of an efficient and adaptive waste management system through the integration of intelegent digital technologies. Employin an exploratory qualitative approach, this research synthesizes SWOT, PESTEl, and stakeholder analyses to identify key internal and external determinats affecting the efficacy of waste governance policies. The findings indicate that, despite intitusional strengths such as a smart city vision and adequate techological infrastructure, the implementation remains hindered by centralized decision making patterns and the limited integration of green technologies. Accordingly, this study proporse a waste management system model anchored in the Internet of Things (IoT), manchine leraning, and blockchain as a framework for digital policy transformation. These recommendations are operationalized into eight strategic action plans aimed at an enhancing systemic efficiency, stakeholder participation, and accelerating the achievement of the Sustainable Development Goals (SDGs), particulary in the domains of environmental governance and sustainable urban management.

Springer Link (Chiba Institute of Technology)
Sustainable cities and communities
Openalex Percentile: Top 31%
Municipal Solid Waste Management
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Policy recommendations for the development of efficient and smart waste management systems to support sustainable cities based on the SDGs — Muhammad Thoriq Alfarizi, Suci Megawati, et al. · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS