Bridging the gap between waste management policies and technology: The social impact of waste generation prediction tools

Effective waste management is crucial for environmental sustainability and waste generation prediction tools have emerged as a promising solution. However, a significant gap exists between waste management policies and the adoption of innovative technologies. This article explores the social impact of waste generation prediction tools in bridging this gap, examining their potential to enhance waste management practices, improve resource allocation, and promote sustainable development. By analyzing the intersection of policy, technology and social outcomes, this study provides insights into the opportunities and challenges of leveraging waste generation prediction tools for more effective waste management.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-31
DOI
https://doi.org/10.5281/zenodo.17337706
Primary Topic
Municipal Solid Waste Management
Type
article
Field-Weighted Citation Impact
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article

Bridging the gap between waste management policies and technology: The social impact of waste generation prediction tools

Zenodo (CERN European Organization for Nuclear Research)
Municipal Solid Waste Management
article

Bridging the gap between waste management policies and technology: The social impact of waste generation prediction tools

article en

Abstract

Effective waste management is crucial for environmental sustainability and waste generation prediction tools have emerged as a promising solution. However, a significant gap exists between waste management policies and the adoption of innovative technologies. This article explores the social impact of waste generation prediction tools in bridging this gap, examining their potential to enhance waste management practices, improve resource allocation, and promote sustainable development. By analyzing the intersection of policy, technology and social outcomes, this study provides insights into the opportunities and challenges of leveraging waste generation prediction tools for more effective waste management.

Zenodo (CERN European Organization for Nuclear Research)
Medical Laboratory Science Council of Nigeria (NG), Lancaster University (GB), Babson College (US)
Openalex Percentile: Top 45%
Municipal Solid Waste Management
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