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

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.

Assessing eco-efficiency of wastewater treatment plants: A cross-evaluation strategy.

Evaluating the eco-efficiency of wastewater treatment plants (WWTPs) is crucial for enhancing environmental and economic performance in the water utility sector. Previous studies in this area estimated WWTP eco-efficiency through self-evaluation, which might have led to overestimation and biased policy recommendations. To address these issues, this study applies a cross-evaluation strategy, combining self-evaluation and peer-evaluation, to assess the eco-efficiency of WWTPs. The empirical application focuses on a sample of Spanish WWTPs, yielding the following key findings. Average eco-efficiency scores were 0.353 and 0.230, for self-evaluation and global peer-evaluation approaches, respectively, confirming the overestimation of eco-efficiency scores based on self-evaluation. If WWTPs were eco-efficient, they could potentially reduce greenhouse gas (GHG) emissions by up to 0.39 kg CO2eq/year. The application of reliable methods, such as peer-evaluation, for eco-efficiency assessment of WWTPs provides water regulators with a comprehensive understanding of the environmental and economic performance of WWTPs. This knowledge guides decision-making, policy development, and resource allocation, facilitating sustainable and efficient wastewater management practices.

A comprehensive assessment of energy efficiency of wastewater treatment plants: An efficiency analysis tree approach.

Wastewater treatment plants (WWTPs) are energy intensive facilities. Controlling energy use in WWTPs could bring substantial benefits to people and environment. Understanding how energy efficient the wastewater treatment process is and what drives efficiency would allow treating wastewater in a more sustainable way. In this study, we employed the efficiency analysis trees approach, that combines machine learning and linear programming techniques, to estimate energy efficiency of wastewater treatment process. The findings indicated that considerable energy inefficiency among WWTPs in Chile existed. The mean energy efficiency was 0.287 suggesting that energy use should cut reduce by 71.3 % to treat the same volume of wastewater. This was equivalent to a reduction in energy use by 0.40 kWh/m3 on average. Moreover, only 4 out of 203 assessed WWTPs (1.97 %) were identified as energy efficient. It was also found that the age of treatment plant and type of secondary technology played an important role in explaining energy efficiency variations among WWTPs.

The eco-efficiency of municipalities in the recycling of solid waste: A stochastic semi-parametric envelopment of data approach.

Eco-efficiency assessment of municipal solid waste (MSW) suppliers is a useful tool in the transition to a circular economy. Furthermore, it provides evidence of the economic and environmental performance of municipalities that can be used for decision-making and/or elaboration of regulatory policies. In this study, eco-efficiency scores were computed for a sample of 140 Chilean municipalities in the provision of MSW services. In doing so, the stochastic semi-parametric envelopment of data method was applied. It is a novel technique which overcomes the limitations of parametric (stochastic frontier analysis) and non-parametric (data envelopment analysis) methods previously employed to evaluate the eco-efficiency of MSW services. The average eco-efficiency of the 140 assessed municipalities was 0.332 which indicates that they could save 66.8% of their operational costs and recycling the same amount of waste. Moreover, 61.4% of the evaluated municipalities presented an eco-efficiency score which was lower than 0.4, whereas the other municipalities (38.6% of the sample) exhibited an eco-efficiency which raged between 0.4 and 0.80. Hence, none of the municipalities assessed was identified as eco-efficient which, implies that there is room for all municipalities to reduce operational costs in the management of MSW. Population density, tourism and location of the municipality were identified as factors influencing the eco-efficiency of the municipalities in MSW management.

Energy efficiency of drinking water treatment plants: A methodological approach for its ranking.

Drinking water treatment systems (DWTSs) are energy intensive facilities, and are an example of the water-energy nexus. Benchmarking energy efficiency is a valuable tool for improving the economic and environmental performance of such facilities. Data envelopment analysis (DEA) is typically used to assess efficiency, allocating flexible weights (FSW) to variables that maximise energy efficiency scores for each DWTS (DEA-FSW). It means that different conditions are applied to each DWTS. Moreover, the DEA-FSW approach has finite discriminatory power which limits cross-unit comparison of energy efficiency hindering the benchmarking of DWTSs. To overcome these limitations, our study explored the effect of estimating the energy efficiency scores of DWTSs by allocating common sets of weights (CSW) within DEA (DEA-CSW). This approach was applied empirically on a sample of 146 DWTSs. Evaluated DWTSs had poor energetic performance based on both DEA-FSW and DEA-CSW estimates (low energy efficiency scores: 0.329 and 0.163, respectively). Even in the optimistic scenario, the average energy efficiency score was low (0.220), with potential electricity savings of 78 % by DWTPs when energy efficient. Unlike DEA-FSW, DEA-CSW allowed energy efficient DWTSs to be distinguished from the 146 facilities. Significant differences in the weights allocated to electricity and pollutants removed from raw water were reported for both approaches, and contributed to diverging energy efficiency scores. In conclusion, this study demonstrated the relevance of using suitable methods to generate comparable results for water companies, allowing the energy performance of DWTSs to be objectively evaluated for benchmarking purposes.

Eco-efficiency assessment under natural and managerial disposability: an empirical application for Chilean water companies.

Getting a good understanding regarding the economic and environmental performance of water utilities is of great importance to achieve the goal of an efficient and sustainable industry. In this study, we apply the range adjusted measure (RAM) data envelopment analysis (DEA) model to evaluate the integrated (production and environmental) efficiency of several water utilities located in Chile. Integrated efficiency is evaluated using the concepts of natural and managerial disposability. This approach further allows us to quantify the contribution of each input and undesirable product on efficiency scores. The results highlighted that the Chilean water industry showed high levels of production and environmental efficiency over time. Under natural disposability, water utilities could control production costs to reduce water leakage and unplanned water supply interruptions by 3.3% on average. Under managerial disposability, water utilities could further cut down undesirable outputs by 1.4% on average by adopting best managerial practices. On average, potential savings in operating costs, employment, water leakage, and unplanned water supply interruptions were higher for concessionary utilities as they showed slightly lower efficiency scores than full private utilities.

Monetary valuation of unsorted waste: A shadow price approach.

Improving the management of municipal solid waste (MSW) is fundamental to promote circular economy and sustainability. Unsorted waste involves negative environmental impacts which often are ignored in economic feasibility studies due to its difficult valuation. In this study the shadow price of unsorted waste using the directional distance function was estimated. This methodological approach also allowed us to compute eco-efficiency scores of a set of municipalities in the provision of MSW services. The empirical application focused on a sample of 119 Chilean municipalities. The results showed that the average shadow price of unsorted waste was 297.66 €/ton which means that the environmental cost of left waste as unsorted was 297.66 € per ton. A regression tree model illustrated that population density, tourism intensity and the generation of waste per capita significantly influenced the shadow price of unsorted waste. Moreover, it was illustrated that Chilean municipalities were very inefficient in the management of MSW since the average eco-efficiency score was 0.272. The findings from this study reveal that additional and alternative policies should be adopted to improve the management of MSW and increase its recycling rate.

Factors influencing eco-efficiency of municipal solid waste management in Chile: A double-bootstrap approach.

Improving eco-efficiency in the provision of municipal solid waste plays an important role for a sustainable economy. Eco-efficiency of municipal solid waste service providers (MSWSPs) has been generally assessed using the conventional data envelopment analysis (DEA) method. However, this approach is sensitive to data noise and has no statistical properties. To overcome these limitations, in this paper, we adopt the double-bootstrap DEA model to derive robust eco-efficiency scores. This nonparametric method allows conducting statistical inference to explore environmental factors affecting the eco-efficiency of MSWSPs. The empirical approach focused on a sample of 298 MSWSPs in Chile, a middle-income country whose policies for promoting waste recycling are incipient. The results indicated that based on the bias-corrected eco-efficiency scores, the potential saving in costs and unsorted waste could be up to 37.8% on average to generate the same level of output (recycled waste). The findings showed that dealing with data noise and uncertainly is of great importance when conducting benchmarking analysis. The region where the municipality is located, tourism, population density and waste per capita are environmental variables that significantly influenced eco-efficiency of Chilean MSWSPs. Several policy implications are discussed based on the findings of this study.

Understanding water-energy nexus in drinking water provision: An eco-efficiency assessment of water companies.

Understanding water-energy nexus in the provision of drinking water services is a challenge which has outstanding relevance in the current climatic emergency. Environmental efficiency and eco-efficiency assessment of water companies are two useful tools to address this challenge. In this study, we estimated hyperbolic and enhanced hyperbolic distance functions to compute the potential reduction in greenhouse gas (GHG) emissions and energy costs in the provision of drinking water. The empirical application focused on the English and Welsh water companies over 2011-2019. Average environmental efficiency and eco-efficiency scores were 0.920 and 0.962, respectively which indicates that water companies performed well but there is room for improvement. Moreover, due to the economies of scale, the cost of reducing GHG emissions was higher for water and sewerage companies than for water only companies. The results and conclusions of this study allow better understanding of the relationship between the provision of drinking water, energy costs and GHG emissions.

How much does it cost to collect recyclable and residual waste in medium-income countries? A case study in the Chilean waste sector.

Improper municipal solid waste (MSW) management leads to contamination of water, soil and air with negative impacts on human health. Moreover, not dealing with residual waste has huge implications for meeting circular economy targets. Understanding how much it costs could lead to a better quality of service and boost environmental sustainability. This study estimates an input distance function using econometric techniques to measure the technical efficiency of the MSW sector in Chile. This approach further allows us to estimate the shadow price of residual waste in terms of total costs. The results indicated that the average technical efficiency of the waste sector was 0.592. This means that the potential savings in costs and residual waste among municipalities could be at the level of 40.8%. Large divergences among municipalities were found since efficiency scores ranged between 0.029 and 0.863. It is found that for 53% of the municipalities evaluated, efficiency scores varied between 0.61 and 0.80. On average, the cost of reducing residual waste was 81.10 US $ per kilogram. This means that on average the cost of preventing one more kilogram of residual waste not being collected and recycled was 81.10 US $. It was also found that on average as population density increased, the shadow price of residual waste increased as well.Implications: The study provides a methodology that allows the policy makers to estimate the efficiency of the solid waste sector where limited available statistical data usually exists in developing and medium-income countries. They have the opportunity to understand what drives costs and identify the best and worst performers. This information is essential to develop local initiatives to enhance waste recycling and therefore, achieving the targets established at national level. Managers can also see if there are other operating factors that could influence performance such as population density. The proposed methodology allows integrating other exogenous variables that might be interesting to policy makers. For instance, a tourism index could be included in the assessment to evaluate whether tourism impacts on the efficiency of municipalities in the provision of municipal solid waste services and therefore, to analyze the implementation of an eco-tax for tourists.

Estimation of greenhouse gases shadow price in the English and Welsh water industry.

Moving to a more sustainable and low-carbon footprint urban water cycle is essential in the light of climate change. In this paper, we estimate the implicit cost of reducing greenhouse gas (GHG) emissions for several English and Welsh water companies from 2013 to 2019. Using econometric techniques, we compute the shadow prices of direct and indirect CO2 emissions associated with the provision of drinking water. This methodological approach also allows us to investigate the impact of a set of environmental variables on the costs of water companies and therefore on the costs of reducing GHG emissions. We then compute the returns to scale, technical change, and technical efficiency of the water companies. The empirical results show the following: (1) the average shadow price of CO2 across years was 0.114 £/kgCO2, which means that the English and Welsh water industry needs to spend an extra £0.114 in operating expenditure to prevent the emission of one kilogramme of CO2; (2) the cost of reducing GHG emissions is very variable among water companies and across years; (3) water taken from boreholes and average pumping head increases cost requirements and therefore the inefficiency of water companies; and (4) the water industry may lower its production costs and thus the costs of reducing GHG emissions by improving its daily operations and adopting new technologies. From a policy perspective, this study evidences that in the English and Welsh water industry, a market-based approach may be more suitable to reduce GHG emissions than a carbon tax policy.

Eco-efficiency assessment of municipal solid waste services: Influence of exogenous variables.

Improving the eco-efficiency of municipalities in the provision of municipal solid waste (MSW) services is fundamental in the context of a circular economy. This study evaluates the eco-efficiency of a sample of Spanish municipalities, integrating the total cost as input, recyclable waste as desirable output, and unsorted waste as undesirable output. Following a pioneering approach, the weighted Russell directional distance model (a non-radial data envelopment analysis model) was employed, which allowed us to obtain a global inefficiency score and individual inefficiency scores for each variable integrated in the model. In the second stage of analysis, the potential factors affecting the previously computed inefficiency scores were investigated. The results indicated that one third of the municipalities evaluated were eco-efficient in the provision of MSW services with the total cost being the variable in which the municipalities exhibited the best performance. Moreover, the size of the municipalities, population served, population density, tourism, and availability of containers for separative collection of paper, glass, and plastic significantly affect the eco-efficiency of the municipalities. The findings of this study provide detailed information to support decision-making for the policy makers to improve the eco-efficiency of the municipalities in managing MSW.

Eco-Efficiency of the English and Welsh Water Companies: A Cross Performance Assessment.

Analyzing costs and greenhouse gas (GHG) emissions could be of great importance for the water utilities to supply water services in a healthy and sustainable manner. In this study, we measured the eco-efficiency of several water utilities in England and Wales by incorporating GHG as an undesirable output. For the first time, we evaluated the eco-efficiency of the water production process using robust cross-efficiency data envelopment analysis (DEA) techniques. The further use of clustering and regression techniques allowed us to better understand the drivers of eco-efficiency. The results showed that the mean eco-efficiency of the water sector was 0.748, which indicates that costs and GHG emissions could be reduced by 25.2% to generate the same level of output. Large water companies with high energy costs and levels of GHG emissions belonged to the less eco-efficient group. Environmental factors related to density, topography, and treatment complexity further impacted eco-efficiency. Finally, we linked our results to the regulatory cycle and discuss some policy implications.

Total factor productivity assessment of water and sanitation services: an empirical application including quality of service factors.

Assessing the productivity change of water companies provides relevant information for both water regulators and companies' managers. Past research has illustrated that different indicators and indexes have been applied although not all of them are equally reliable. Thus, this study evaluates the total factor productivity (TFP) change and its drivers employing the Luenberger-Hicks-Moorsteen productivity indicator (LHMPI) including, for the first time, quality of service variables as undesirable outputs. Moreover, unlike the previous studies, LHMPI was decomposed into three drivers; namely technical change, technical efficiency change and scale efficiency change. Our empirical application conducted on a sample of Chilean water companies over 2007-2018 embracing full private water companies (FPWCs) and concessionary water companies (CWCs). Results evidenced that, on average, TFP increased at an annual rate of 2.2%, mainly due to outputs rise. The main driver of productivity growth was scale efficiency change suggesting that adjustments in the water companies' scale of operations could lead to lower operational costs. It was also evidenced that FPWCs performed better than CWCs over the period analyzed.

Evaluating trends in the performance of Chilean water companies: impact of quality of service and environmental variables.

In monopoly services that provide drinking water, it is of paramount importance to evaluate the total factor productivity (TFP) change of water companies. Most of the previous studies have computed the Malmquist productivity index (MPI) by applying non-parametric methods. By contrast, following a pioneering approach, in this study, we estimated the MPI using a parametric method that allows us to decompose TFP change into a larger number of drivers, including exogenous and quality of service variables. An empirical application for the Chilean water industry over 2007-2015 was conducted. We found that productivity change estimates were variable across years, differentiating a first period (2007/11) in which productivity declined and a second period (2011/15) in which TFP notably improved. In both periods, scale efficiency change and input mixed effect were the main drivers of productivity change, illustrating the importance of operation scale in water companies' performance. The decomposition of the TFP change in a large number of drivers is essential to propose incentives and measures to promote productivity across time.

Benchmarking energy efficiency of water treatment plants: Effects of data variability.

This study evaluates, for the first time, the energy efficiency of a sample of drinking water treatment plants (DWTPs) using the data envelopment analysis (DEA) tolerance method, which is based on the simulation of scenarios to integrate data variations. The integration of data uncertainty in energy efficiency estimation changes drastically results for approximately one-third of the DWTPs evaluated. The results showed that, even in the best-case scenario, most of the DWTPs evaluated are inefficient and may therefore, be able to reduce the energy used to treat raw water. From a policy perspective, the findings of this study reveal that omitting data variability in benchmarking would involve critical repercussions when efficiency scores are used by regulators to set water tariffs. Omitting the degree of data uncertainty is likely to result in biased conclusions; in the scenarios evaluated, the inclusion of this information altered the rankings of some energy-efficient DWTPs.

Measuring the eco-efficiency of wastewater treatment plants under data uncertainty.

Eco-efficiency assessment is a useful tool for improving the sustainability of wastewater treatment plants (WWTPs). However, it is a complex task that requires the integration of several performance indicators into a single index. Data envelopment analysis (DEA) is established as a highly effective methodology for achieving this as it permits the integration of the service value, resource consumption and environmental impact variables as the desirable outputs, inputs and undesirable outputs, respectively. However, traditional DEA models omit uncertainties in the data that are likely to result in biased conclusions. This study pioneers the assessment of the eco-efficiency of WWTPs while accounting for the data uncertainty and integrating the greenhouse gas emissions as an undesirable output. The DEA-tolerance model was applied to compute the eco-efficiency scores for 729 scenarios for each facility tested for identifying the best- and worst-case scenarios. The WWTPs were also ranked based on their eco-efficiency scores. The results demonstrated the importance of integrating data uncertainty in eco-efficiency assessments; the performances of the WWTPs change notably based on the evaluated set of scenarios. The proposed methodological approach provides a reliable and robust framework for supporting decision-making processes.

Energy intensity modeling for wastewater treatment technologies.

Wastewater treatment plants (WWTPs) are energy intensive facilities; therefore increased pressure has been placed on managers and policy makers to reduce the facilities' energy use. Several studies were conducted to compare the energy intensity (EI) of WWTPs, which showed large dispersion in EI among the facilities. In the present study, the degree EI influenced WWTPs was tested using a set of technical variables by modeling the EI of a 305 WWTP sample grouped into five secondary treatment technologies. Results indicated the following two major findings: i) WWTPs using conventional activated sludge, extended aeration, trickling biofilters, and biodisks exhibited significant economies of scale in energy use; and ii) pollutant removal efficiency demonstrated low impacts on WWTP EI. The methodology and results of this study are of value to policy makers in planning new WWTPs and developing management plans to improve energy efficiency of wastewater treatment.

Benchmarking the efficiency of the Chilean water and sewerage companies: a double-bootstrap approach.

Benchmarking the efficiency of water companies is essential to set water tariffs and to promote their sustainability. In doing so, most of the previous studies have applied conventional data envelopment analysis (DEA) models. However, it is a deterministic method that does not allow to identify environmental factors influencing efficiency scores. To overcome this limitation, this paper evaluates the efficiency of a sample of Chilean water and sewerage companies applying a double-bootstrap DEA model. Results evidenced that the ranking of water and sewerage companies changes notably whether efficiency scores are computed applying conventional or double-bootstrap DEA models. Moreover, it was found that the percentage of non-revenue water and customer density are factors influencing the efficiency of Chilean water and sewerage companies. This paper illustrates the importance of using a robust and reliable method to increase the relevance of benchmarking tools.

Assessing the productivity change of water companies in England and Wales: A dynamic metafrontier approach.

The assessment of productivity change and its drivers across water companies and over time is a powerful tool for both regulators and companies when setting water tariffs. Water and sewerage companies (WaSCs) and water only companies (WoCs) provide different services. Hence, their productivity change cannot directly be evaluated jointly. In this paper and for the first time, we provide a pioneering approach to assess and compare the dynamics of productivity change of WaSCs and WoCs. To achieve this, both the traditional Malmquist productivity index and the metafrontier Malmquist productivity index and its components are computed to assess the productivity change for a sample of English and Welsh water companies over the period 2001-2014. The findings from both indices indicate that productivity for both WaSCs and WoCs did not improve during this period, mainly due to the negative shift in the production frontier which offset the positive effect of efficiency change. It is also reported that the performance of the WoCs over time was slightly better than that of the WaSCs. Finally, our study provides some insights into the relationship between productivity change and the regulatory cycle. This information is essential to improve the regulation of water and sewerage services, contributing to the long-term sustainability of the urban water cycle.