Abstract
Assessing the evolution of the performance of water supply and sanitation services is essential to monitor progress towards the universalization of water services, as specified by the Sustainable Development Goal 6 of Agenda 2030, adopted by United Nations member countries. Brazil, a developing country with a continental size and geographical diversity, will face significant challenges to achieve this goal. The main objective of this paper is to evaluate the evolution of productivity of water supply and sanitation services in Brazilian municipalities in the period 2012-2019. The analysis also explores whether water services' performance is balanced across the country, with a specific analysis of performance at the macroregion level. From a methodological perspective, this research evaluates productivity change over time using a Malmquist Productivity Index estimated with a metafrontier, satisfying the circularity property. It also develops a pseudo Malmquist index that compares productivity levels across macro-regions. The results revealed a productivity loss of approximately 4% at the national level, with an unequal profile across the macro-regions. The Southeast municipalities stand out for exhibiting, on average, higher productivity levels than the South and Northeast municipalities.

Abstract
In a world facing unprecedented challenges, such as climate changes and growing social problems, the pharmaceutical industry must ensure that its supply chains are environmentally sustainable and resilient, guaranteeing access to key medications even when faced with unanticipated disruptions or crises. The core goal of this work is to develop an innovative simulation-based approach to support more informed and effective decision making, while establishing reasonable trade-offs between supply chain robustness and resiliency, operational efficiency, and environmental and social concerns. Such a decision-support system will contribute to the development of more resilient and sustainable pharmaceutical supply chains, which are, in general, critical for maintaining access to essential medicines, especially during times of crises or relevant disruptions. The system will help companies to better manage and design their supply chains, providing a valuable tool to achieve higher levels of resilience and sustainability. The study we conducted has two primary contributions that are noteworthy. Firstly, we present a new advanced approach that integrates multiple simulation techniques, allowing for the modeling of highly complex environments. Secondly, we introduce a new conceptual framework that helps to comprehend the interplay between resiliency and sustainability in decision-making processes. These two contributions provide valuable insights into understanding complex systems and can aid in designing more resilient and sustainable systems.

Abstract
Fires in large buildings can have tragic consequences, including the loss of human lives. Despite the advancements in building construction and fire safety technologies, the unpredictable nature of fires, particularly in large buildings, remains an enormous challenge. Acknowledging the paramount importance of prioritising human safety, the academic community has been focusing consistently on enhancing the efficiency of building evacuation. While previous studies have integrated evacuation simulation models, aiding in aspects such as the design of evacuation routes and emergency signalling, modelling human behaviour during a fire emergency remains challenging due to cognitive complexities. Moreover, behavioural differences from country to country add another layer of complexity, hindering the creation of a universal behaviour model. Instead of centring on modelling the occupant behaviour, this paper proposes an innovative approach aimed at enhancing the occupants' behaviour predictability by providing real-time information to the occupants regarding the most suitable evacuation routes. The proposed models use a building's environmental conditions to generate contextual information, aiding in developing solutions to make the occupants' behaviour more predictable by providing them with real-time information on the most appropriate and efficient evacuation routes at each moment, guiding the occupants to safety during a fire emergency. The models were incorporated into a context-aware recommender system for testing purposes. The simulation results indicate that such a system, coupled with hazard and congestion models, positively influences the occupants' behaviour, fostering faster adaptation to the environmental conditions and ultimately enhancing the efficiency of building evacuations.

Abstract
The manufacturing industry faces a new revolution, grounded on the intense digitalization of assets and industrial processes and the increasing computation capabilities imposed by the new data-driven digital architectures. This reality has been promoting the Digital Twin concept and its importance in the industrial companies' business models. However, with these new opportunities, also new threads may rise, mainly related to industrial data protection and sovereignty. Therefore, this research paper will demonstrate the International Data Spaces reference model's application to overcome these limitations. Following a pilot study with a Portuguese machine producer/maintainer enterprise, this paper will demonstrate the development of a cutting and bending machine Digital Twin, leveraged on an International Data Spaces infrastructure for interoperability, for the plastic and metal industry and its importance to introduce this machine manufacturing company in a new business-to-business marketplace from the EU project Market 4.0.

Abstract
This paper explores the problem of sectorization of a parcel delivery service that wants to assign an action region to each of its teams, regarding the number of deliveries scheduled for each zone, so that there is a balanced service amongst sectors, covering contiguous zones, and considering limited capacities for the teams. Besides being relatively easy to model, the available optimization tools and software provide poor results when dimension increases in these types of problems, with computational capacity exceeding. In this paper an integer programming model, combined with an heuristic to return a faster solution, was implemented to solve a sectorization problem in two different situations. The main advantage of the strategy proposed, compared to previous ones, is its simplicity and easy implementation while still returning an optimal solution. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
This study explores asset management performance of Portuguese water supply companies operating in the bulk market. The focus of the analysis are the managerial practices and the condition of infrastructures. This assessment is based on the information conveyed by the indicators collected by the Portuguese water and waste services' regulator authority (ERSAR) between 2016 and 2020. The main contribution of this research is to propose innovative methods to enhance the knowledge on asset management practices in the water sector. Two Benefit-of-the-Doubt (BoD) Composite Indicators are developed to highlight different aspects of asset management approaches. The first reflects organisations' performance in maintaining their infrastructures at acceptable operational levels, and the other reveals their maturity in asset management practices. Robust and conditional approaches for estimating the BoD indicators are applied, allowing to obtain results that account for the effect of contextual variables on companies' performance. Additionally, the performance of the companies is analysed over a 5-year period. The results show that there is significant room for improvement given the indicators' values estimated in the benchmarking analysis. The type of management systems and areas of intervention (urban, semi-urban or rural) are factors that present significant impact in asset management performance. The analysis of trends in the evolution of performance over time revealed improvements both in the companies' managerial practices and operational results.