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The purpose of this paper is to estimate and compare the efficiency of several water utilities using three frontier techniques. Moreover, this study estimates the impact of several qualities of service variables on water utilities’ performance.

The paper utilizes three frontier techniques such as data envelopment analysis (DEA), stochastic frontier analysis (SFA) and stochastic non-parametric envelopment of data (StoNED) to estimate efficiency scores.

Efficiency scores for each methodological approach were different being on average, 0.745, 0.857 and 0.933 for SFA, DEA and StoNED methods, respectively. Moreover, it was evidenced that water leakage had a statistically significant impact on water utilities’ costs.

The choice of an adequate and robust method for benchmarking the efficiency of water utilities is very relevant for water regulators because it affects decision making process such as water tariffs and design incentives to improve the performance and quality of service of water utilities.

This paper evaluates and compares the performance of a sample of water utilities using three different frontier methods. It has been revealed that the choice of the efficiency assessment method matters. Unlike SFA and DEA, a lower variability was shown in the efficiency scores obtained from the StoNED method.

The chapter illustrates the relationships between concepts, theories, and processes presented so far in the book.

The cases explored show how this model can be recognized first and foremost in publicly owned waste operators linked to the territory where the service is provided. The content that justifies and legitimizes their presence is that of the integral recovery of materials through the zero waste strategy.

Innovation, responsibility, stakeholder engagement, and knowledge sharing have been highlighted as the four key drivers of sustainable urban waste management. These drivers reciprocally reinforce each other in a virtuous exploitation system that generates a positive circular path of new managerial and technical resources and competencies, and new responsibility schemes shared among managers, policymakers, employees, and users.

Further, each key driver impacts the economic, environmental, and social performance of urban waste operators, increasing the overall impact and strengthening the effect of the other drivers in a virtuous exploitation of benefits for waste operators and stakeholders beyond the served territory.

Chapter 4 focuses on how can we best measure and compare performance of waste management companies, discussing the triple bottom line perspective as a driving approach for public service provision like urban waste management. This approach contributes to extend relevant performance dimensions, broadening its scope to encompass not only cost and efficiency in waste collection and treatment but also environmental and social implications.

The purpose of this paper is to examine the technical, social and moral aspects of accounting through the implementation of a novel balanced scorecard (BSC) that addresses the United Nations Sustainable Development Goal (UN SDG) 6 – Clean Water and Sanitation – within the Portuguese water utilities sector.

A novel research design is adopted, using actor network theory (ANT) as a broad approach to frame the study. ANT emphasizes the importance of ever-evolving networks of relationships and how concepts such as the BSC are just as important in structuring social practice. A set of expert interviews was conducted with stakeholders in the water utilities sector in Portugal, which led to the iterative development of a context-relevant BSC proposal and associated indicators.

A novel BSC architecture to achieve UN SDG 6 is proposed through a unique engagement between professionals and academics. The BSC, and the specific definition of indicators for an entire sector (water), contribute to bridging business processes with the common good to improve life and planetary conditions. Ultimately, the study discusses how the technical aspects of accounting can be enhanced to achieve social and moral imperatives. The paper also reflects on the limitations of broadening existing technical practices.

There is a burgeoning literature on how organizations are engaging with the UN SDG agenda. However, there is a dearth of studies on how management control systems are currently addressing, or can potentially contribute to measuring and managing specific UN SDGs such as Clean Water and Sanitation. This study makes a unique contribution to the literature by developing a novel BSC solution to SDG 6 measurement and management using a novel practitioner-led approach. Ultimately, our study highlights how accounting can be broadened to enhance technical practices while also serving a moral and social purpose.

This paper contributes to the field of public services’ performance measurement systems by proposing a benchmarking-based methodology that improves the effective use of big and open data in analyzing and evaluating efficiency, for supporting internal decision-making processes of public entities.

The proposed methodology uses data envelopment analysis in combination with a multivariate outlier detection algorithm—local outlier factor—to ensure the proper exploitation of the data available for efficiency evaluation in the presence of the multidimensional datasets with anomalous values that often characterize big and open data. An empirical implementation of the proposed methodology was conducted on waste management services provided in Italy.

The paper addresses the problem of misleading targets for entities that are erroneously deemed inefficient when applying data envelopment analysis to real-life datasets containing outliers. The proposed approach makes big and open data useful in evaluating relative efficiency, and it supports the development of performance-based strategies and policies by public entities from a data-driven public sector perspective.

Few empirical studies have explored how to make the use of big and open data more feasible for performance measurement systems in the public sector, addressing the challenges related to data quality and the need for analytical tools readily usable from a managerial perspective, given the poor diffusion of technical skills in public organizations. The paper fills this research gap by proposing a methodology that allows for exploiting the opportunities offered by big and open data for supporting internal decision-making processes within the public services context.