Performance assessment for municipal solid waste collection in Taiwan

Collecting municipal solid waste (MSW) is a major and expensive task for local waste management authorities, thus efficient MSW collection is a necessity. This study presents a procedure for developing an aggregate indicator (AI) to assess MSW collection efficiency based on multiple factors. The app...

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Bibliographic Details
Published in:Journal of environmental management 2011-04, Vol.92 (4), p.1277-1283
Main Authors: Huang, You-Ti, Pan, Tze-Chin, Kao, Jehng-Jung
Format: Article
Language:English
Subjects:
Aggregates
Aggregation indicator
Animal, plant and microbial ecology
Applied ecology
Artificial intelligence
Biological and medical sciences
Business metrics
Collection
Collection services
Common weight
Comparative analysis
Conservation, protection and management of environment and wildlife
Criteria
Data envelopment analysis
Economic efficiency
Efficiency
Efficiency, Organizational
Evaluation
Fundamental and applied biological sciences. Psychology
General aspects
Indicators
Local government
Models, Organizational
Municipal solid waste
Municipal solid waste collection
Operations research
Performance assessment
Performance evaluation
Refuse Disposal - methods
selection criteria
Solid wastes
Studies
Taiwan
Tasks
Urban services
Waste management
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Description
Summary:Collecting municipal solid waste (MSW) is a major and expensive task for local waste management authorities, thus efficient MSW collection is a necessity. This study presents a procedure for developing an aggregate indicator (AI) to assess MSW collection efficiency based on multiple factors. The applicabilities of various key performance indicators (KPIs) are evaluated based on five selection criteria, and five KPIs are chosen to form the AI. The relative efficiencies of local MSW collection services are analyzed by the data envelopment analysis (DEA) method. A set of common weights for all five KPIs is then generated based on DEA results and four selection rules by modifying a previous approach. Finally, the proposed AI is applied to assess the MSW collection services provided by 307 local governments in Taiwan, and associated results are compared and discussed.
ISSN:0301-4797
1095-8630
DOI:10.1016/j.jenvman.2010.12.002