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

Autor: Sala-Garrido R; Departament of Mathematics for Economics, University of Valencia, Avd. Tarongers S/N, Valencia, Spain., Mocholi-Arce M; Departament of Mathematics for Economics, University of Valencia, Avd. Tarongers S/N, Valencia, Spain., Molinos-Senante M; National Research Center for Integrated Natural Disaster Management (CIGIDEN), CONICYT/FONDAP/15110017, Avda, Vicuña Mackenna, 4860, Santiago, Chile. maria.molinos@uva.es.; Institute of Sustainable Processes, University of Valladolid, C/ Mergelina S/N, Valladolid, Spain. maria.molinos@uva.es., Maziotis A; National Research Center for Integrated Natural Disaster Management (CIGIDEN), CONICYT/FONDAP/15110017, Avda, Vicuña Mackenna, 4860, Santiago, Chile.
Jazyk: angličtina
Zdroj: Environmental science and pollution research international [Environ Sci Pollut Res Int] 2023 Dec; Vol. 30 (57), pp. 121077-121089. Date of Electronic Publication: 2023 Nov 10.
DOI: 10.1007/s11356-023-30779-z
Abstrakt: 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.
(© 2023. The Author(s).)
Databáze: MEDLINE
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