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.

Investigating the link between medical urgency and hospital efficiency - Insights from the German hospital market

With hospital budgets remaining tight and healthcare expenditure rising due to demographic change and advances in technology, hospitals continue to face calls to contain costs and allocate their resources more efficiently. In this context, efficiency has emerged as an increasingly important way for hospitals to withstand competitive pressures in the hospital market. Doing so, however, can be challenging given unpredictable fluctuations in demand, a prime example of which are emergencies, i.e. urgent medical cases. The link between medical urgency and hospitals' efficiency, however, has been neglected in the literature to date. This study therefore aims to investigate the relationship between hospitals' urgency characteristics and their efficiency. Our analyses are based on 4094 observations from 1428 hospitals throughout Germany for the years 2015, 2016, and 2017. We calculate an average urgency score for each hospital based on all cases treated in that hospital per year and also investigate the within-hospital dispersion of medical urgency. To analyze the association of these urgency measures with hospitals' efficiency we use a two-stage double bootstrap data envelopment analysis approach with truncated regression. We find a negative relationship between the urgency score and hospital efficiency. When testing for non-linear effects, the results reveal a u-shaped association, indicating that having either a high or low overall urgency score is beneficial in terms of efficiency. Finally, our results reveal that higher within-hospital urgency dispersion is negatively related to efficiency.

Key performance indicators to explain energy & economic efficiency across water utilities, and identifying suitable proxies

Water companies consume up to 8% of global energy demand, at billions of dollars' cost. Benchmarking of performance between utilities can facilitate improvements in efficiency; however, inconsistencies in benchmarking practices may obscure pathways to improvement. The aspiration was to conduct an unbiased efficiency comparison within a sample of 17 water only companies and water and sewerage companies in England and Wales, accounting for exogenous factors, whilst evaluating the accuracy of common proxies. Proxies were tested, and bias-corrected energy and economic efficiency scores with explanatory factors were analysed using a double-bootstrap data envelopment method. Bias correction altered the rankings of two companies for energy efficiency only. Results imply that on average, companies could reduce energy inputs by 91.7%, and economic inputs by 92.3%, which was symptomatic of the companies specialising in drinking water supply considerably out-performing combined water and sewerage companies. As exogenous influences were likely to be a factor in the disparity between the companies, five indicators were evaluated. The results varied but of note were average pumping head height, which displayed a significant negative effect for energy efficiency, and proportion of water passing through the largest four treatment works, that exhibited a significant negative effect on economic efficiency. Within proxy performance, population served for drinking water was an adequate replacement for volume of water produced, with results matching the core variable apart from two companies changing rank in the economic analysis. Conversely, length of water mains performed poorly when replacing capital expenditure, implying companies were on average 12.6% more efficient, resulting in ten companies changing their rank and causing explanatory variables to contradict direction of influence and significance. The findings contribute new insights for benchmarking, including how different types of water companies perform under bias-correcting methods, the degree to which factors affect efficiency and how appropriate some proxies are.

Impact of environmental variables on the efficiency of water companies in England and Wales: a double-bootstrap approach

An important aspect of the regulatory process is the performance comparison of regulated firms. This exists in regulated industries where tariffs are determined through a benchmarking process such as the English and Welsh water industry. A double-bootstrap data envelopment analysis (DEA) approach was applied to overcome the uncertainty in efficiency scores and to reveal the influence of environmental variables on 18 water companies in England and Wales during the 2001-2016 period. The results showed that bias and bias-corrected efficiency scores lead to changes in the water companies' rankings. This reveals the importance of using reliable methodologies to support the decision-making process. Higher levels of average pumping head, leakage, and abstraction of water from reservoirs lead to lower efficiency. In contrast, increased population density leads to larger efficiency. We also link the results from the efficiency of water companies with the regulatory cycle. Our findings can be useful to policy makers for them to better understand water utilities' performance and to aid them in reshaping their current policies and practices to improve efficiency and provide better service to customers.

Economic and environmental efficiency of UK and Ireland water companies: Influence of exogenous factors and rurality

For water companies, benchmarking their performance relative to other companies can be an effective way to identify the scope for efficiency gains to be made through infrastructure investment and operational improvements. However, a key limitation to benchmarking is the confounding effect of exogenous factors, which may not be factored in to benchmarking methodologies. The purpose of this study was to provide an unbiased comparison of efficiency across a sample of water and sewage companies, accounting for important exogenous factors. Bias-corrected economic and environmental efficiency estimates with explanatory factors were evaluated for a sample of 13 water and sewage companies in the UK and Ireland, using a double-bootstrap data envelopment analysis (DEA) approach. Bias correction for economic and environmental efficiency changed the rankings of nine and eight companies, respectively. On average, companies could reduce economic inputs by 19% and carbon outputs by 16% if they performed at the efficiency frontier. Variables explaining efficiency were: source of water, leakage rate, per capita consumption and population density. Population density showed statistical significance with both economic (p-value 0.002) and environmental (p-value 0.001) efficiency. Consequently, a rurality factor was defined for each company's operational area, which was then regressed against normalised water company performance data. More rural water companies spend more per property (R² of 0.633), in part reflecting a larger number of smaller sewage treatment works serving rural populations (R² of 0.823). These findings provide new insight into methods for benchmarking, and factors affecting, water company efficiency, pertinent for both regulators and water companies.