Unknown

Dataset Information

0

Assessing the dynamic performance of water companies through the lens of service quality.


ABSTRACT: The measurement of performance within the water industry holds significant importance for policymakers, as it can help guide decision-making for future development and management initiatives. In this study, we apply data envelopment analysis (DEA) cross-efficiency techniques to evaluate the productivity change of the Chilean water industry during the years 2010-2018. Water leakage and unplanned interruptions are included in the analysis as quality of service variables. Moreover, we use cluster analysis and regression techniques to better understand what drives productivity change of water companies. The results indicate that the Chilean water industry is characterized by considerable high levels of inefficiency and low levels of productivity change. This is due to the existence of technical regress whereas gains in efficiency were small. Concessionary water companies were found to be more productive than full private and public water companies. Best and worst performers need to make efforts to reduce production costs and improve service quality. Other factors such as customer density and ownership type statistically affect productivity.

SUBMITTER: Sala-Garrido R 

PROVIDER: S-EPMC10697877 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

Assessing the dynamic performance of water companies through the lens of service quality.

Sala-Garrido Ramon R   Mocholi-Arce Manuel M   Molinos-Senante Maria M   Maziotis Alexandros A  

Environmental science and pollution research international 20231110 57


The measurement of performance within the water industry holds significant importance for policymakers, as it can help guide decision-making for future development and management initiatives. In this study, we apply data envelopment analysis (DEA) cross-efficiency techniques to evaluate the productivity change of the Chilean water industry during the years 2010-2018. Water leakage and unplanned interruptions are included in the analysis as quality of service variables. Moreover, we use cluster a  ...[more]

Similar Datasets

| S-EPMC8880942 | biostudies-literature
| S-EPMC11622846 | biostudies-literature
| S-EPMC8494355 | biostudies-literature
| S-EPMC9287491 | biostudies-literature
| S-EPMC7970482 | biostudies-literature
| S-EPMC6474601 | biostudies-literature
| S-EPMC10547161 | biostudies-literature
| PRJEB42286 | ENA
| S-EPMC5734333 | biostudies-literature
| S-EPMC4113882 | biostudies-literature