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• W2800804123 abstract "Abstract Irrigation performance assessment is particularly important in the Water Users Associations (WUAs) operating in Calabria (Southern Italy), where collective irrigation service suffers from poor performances both from an operative and economic point of view. For many years Data Envelopment Analysis (DEA) has been proposed for the diagnosis of Water Users Association performance; however, the number and type of related performance indicators must be selected with caution to avoid misleading and unrealistic results. In this paper, we propose to apply DEA to a limited but significant set of performance indicators and to couple it to Multiple Regression Analysis by Principal Component Regression (PCR). The proposed methods were applied to evaluating the system operation and financial performances of ten of the eleven WUAs operating in Calabria (Southern Italy) to indicate potential improvements. The analysis of the current performance indicators collected throughout five years (2011–2015) showed that in Calabrian WUAs the irrigation service is underutilised, and water delivered to crops is always in excess; the cost recovery of WUAs is very low, because of staff costs and low fee collection. DEA identified five inefficient WUAs and took the remaining five organisations as reference for performance improvement. The input-oriented DEA coupled to PCR has suggested reducing water usage, management and personnel costs and water fees, by increasing the irrigated area and the irrigation service coverage. The output–output oriented DEA coupled to PCR predicted a high increase of the cost recovery capacity of the inefficient WUAs, but in this case the improved scenario required an abnormal increase (10-fold) of the irrigated area, which may be basically unfeasible. Overall, the integration of DEA with multi-regression models and their implementation in the case study, using a limited set of easy-to-survey performance indicators, appears to be a powerful and easy tool for decision makers in the irrigation sector." @default.
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• W2800804123 date "2018-06-01" @default.
• W2800804123 modified "2023-09-27" @default.
• W2800804123 title "Improvement of the irrigation performance in Water Users Associations integrating data envelopment analysis and multi-regression models" @default.
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• W2800804123 doi "https://doi.org/10.1016/j.agwat.2018.04.032" @default.
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