Scholarlink

<p>Assessing the performance of water supply systems (WSSs) is crucial for their effective management. This study develops a Composite Indicator (CI) that integrates key performance indicators (KPIs) to evaluate WSS performance comprehensively. We explore the processes of clustering, normalizing, weighting, and aggregating KPIs using data from various WSSs in Iran. The KPIs were categorized into four dimensions: Environmental, Financial, Organizational, and Social, to facilitate a detailed assessment and calculation of an Overall Performance Index (OPI). A new multi-criteria method was used to assign weights to KPIs based on non-compensation principles. WSSs were grouped by population, water resource type, and climate, and KPIs were normalized through fair benchmarking. We employed a non-linear (Geometric) aggregation method to enhance sustainability and address non-compensation interactions. Our comparison of this method with previous approaches revealed significant impacts on the OPI and the ranking of WSSs. Population size emerged as a significant factor, and the study highlighted the substantial influence of resource type and climate on specific KPIs. The non-linear aggregation method demonstrated greater robustness and sustainability compared to linear methods, aligning with fair benchmarking principles and improving WSS sustainability.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Developing an overall performance index for water supply systems: selecting optimal methods for effective benchmarking

  • 期刊论文

  • 发表日期：

    2025年4月19日

查看全文
  • Hassan Baniasadi,
  • Abdollah Rashidi Mehrabadi

摘要

Assessing the performance of water supply systems (WSSs) is crucial for their effective management. This study develops a Composite Indicator (CI) that integrates key performance indicators (KPIs) to evaluate WSS performance comprehensively. We explore the processes of clustering, normalizing, weighting, and aggregating KPIs using data from various WSSs in Iran. The KPIs were categorized into four dimensions: Environmental, Financial, Organizational, and Social, to facilitate a detailed assessment and calculation of an Overall Performance Index (OPI). A new multi-criteria method was used to assign weights to KPIs based on non-compensation principles. WSSs were grouped by population, water resource type, and climate, and KPIs were normalized through fair benchmarking. We employed a non-linear (Geometric) aggregation method to enhance sustainability and address non-compensation interactions. Our comparison of this method with previous approaches revealed significant impacts on the OPI and the ranking of WSSs. Population size emerged as a significant factor, and the study highlighted the substantial influence of resource type and climate on specific KPIs. The non-linear aggregation method demonstrated greater robustness and sustainability compared to linear methods, aligning with fair benchmarking principles and improving WSS sustainability.