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.
- Aggregation indicator
- Common weight
- Data envelopment analysis
- Municipal solid waste collection
- Performance assessment