Abstract
This paper describes an exploration process aligned with the core domain of Service Science inside a critical sector of Society, aiming at developing City in a sustainable, responsible, inclusive way. The paper focuses on defining the Public Safety as a Service concept in an inclusive and responsible value co-creation urban design vision for liveable cities. It explains how service intelligence can act on immaterial artefacts to transform data into information to generate value co-creation processes whose outcomes are applied to the evolution of knowledge in public safety services. Public safety is approached within a service ecosystem perspective, following the global targets of the Sendai Framework for Disaster Risk Reduction as an application perspective. Managerial implication are approached from two perspectives: establishment of governance principles with the help of Elinor Ostrom's works, and a Viable Systems Approach on the response to disasters operating rules.

Abstract
This paper investigates the performance of the largest Brazilian hydropower plants. This study covers 78% of the total installed capacity from hydros in the country, and considers indicators reflecting operational and maintenance costs as well as quality of service. The assessment was conducted using a new approach for the construction of composite indicators, based on a directional distance function model. First, we assessed the hydropower plants allowing for complete flexibility in the definition of weights, enabling the identification of underperforming plants, and quantification of their potential for improvement. Next, we assessed the plants considering different perspectives regarding the importance attributed to each indicator. This allowed reflecting different points of view, focusing primarily on operation and maintenance costs or quality issues. The results identify the hydropower plants that can be considered benchmarks in different scenarios, and allow testing the robustness of plants' classification as benchmarks in the unrestricted model.

Abstract
The personal characteristics of entrepreneurs can be importantly related to entrepreneurial startup intentions and behaviors. A country-moderated hypothesis including the relationship between an individual's risk-taking propensity and entrepreneurship (behaviors or intentions of the person) was conceptually developed and empirically tested in this study. The data collection was performed through a structured questionnaire. Multinominal logistic regression was used for analyzing data obtained from 1,414 students in six countries. The crucial contribution of this research is the clarification of the character of risk-taking propensity in entrepreneurship and the indication that the risk-taking propensity-entrepreneurship relationship can be moderated contingent on power distance.

Abstract
Resumo O abandono escolar é um problema complexo que afeta a maioria dos programas de graduação pós-secundária, em todo o mundo. O curso de engenharia industrial do Instituto ISVOUGA, localizado em Santa Maria da Feira, Portugal, não é exceção. Este estudo usou um conjunto de dados contendo informações gerais dos estudantes e suas notas para as unidades curriculares já avaliadas. A partir deste conjunto de dados, foram selecionados dezessete preditores potenciais: cinco intrínsecos (gênero, estado civil, situação profissional, idade e regime de dedicação aos estudos – integral ou parcial) e doze extrínsecos (as notas em todas as doze unidades curriculares ministradas durante os dois primeiros semestres do curso). O objetivo principal desta investigação foi prever a probabilidade de um estudante abandonar o curso com base nos referidos preditores. Foi usada uma regressão logística binária para classificar os estudantes como tendo uma probabilidade alta ou baixa de não se reinscreverem no curso. Para validar se a metodologia utilizada é apropriada para o estudo em causa, a precisão obtida com o modelo de regressão logística foi comparada, por via de uma validação cruzada com cinco partições, com a precisão obtida pela utilização de três métodos muito utilizados em data mining: One R, K Nearest Neighbors e Naive Bayes. O modelo de regressão logística identificou quatro variáveis significativas na previsão do abandono escolar (as classificações nas unidades curriculares de ciência dos materiais, eletricidade, cálculo 1 e química). Os dois preditores mais influentes do abandono dos estudantes são não conseguir aprovação nas unidades curriculares menos exigentes: ciência dos materiais e eletricidade. Ao contrário do que seria de supor antes desta investigação, descobrimos que a não aprovação em unidades curriculares mais exigentes, como física ou estatística, não tem influência significativa no abandono escolar.

Abstract
Air temperature data from many locations worldwide are only available as series of daily minima and maxima temperatures. Historically, several different approaches have been used to estimate the actual daily mean temperature, as only in the last two or three decades automatic thermometers are able to compute its actual value. The most common approach is to estimate it by averaging the daily minima and maxima. When only daily minima and maxima are available, an alternative approach, proposed by Dall'Amico and Hornsteiner in 2006, uses the two daily extremes together with next day minima temperature and a coefficient related to the local daily astronomical sunset time. Additionally, the method uses two optimizable coefficients related to the region's temperature profile. In order to use this approach it is necessary to optimize the region's unknown parameters. For this optimization, it is necessary a dataset containing the maxima, minima, and the actual daily mean temperatures for at least one year. In this research, for the period 2007-2014, we used three datasets of minima, maxima and actual mean temperatures obtained at three automatic meteorological stations located in the Douro Valley to optimize the two unknown parameters in the Dall'Amico and Hornsteiner approach. Moreover, we compared the actual mean daily temperatures available from the three datasets with the correspondent values estimated by using i) the usual approach of averaging the daily maxima and minima temperatures and ii) the Dall'Amico and Hornsteiner approach. Results show that the former approach overestimates, on average, the daily mean temperatures by 0.5 degrees C. The Dall'Amico and Hornsteiner approach showed to be a better approximation of mean temperatures for the three meteorological stations used in this research, being unbiased relative to the actual mean values of daily temperatures. In conclusion, this research confirms that the Dall'Amico and Hornsteiner is a better approach to estimate the mean daily temperatures and provides the optimized parameters for three sites located at each of the three sub-regions of the Douro Valley (Baixo Corgo, Cima Corgo and Douro Superior).

Abstract
Service organizations increasingly understand the importance of managing the customer experience to enhance customer satisfaction and loyalty. This study aims to develop a better understanding of the customer experience by investigating how the customer’s internal mechanisms influence it. That is, how it is perceived and processed at three different levels (visceral, behavioral and reflective), which determines a person’s cognitive and emotional state. To this purpose an exploratory multi-method ethnographic study was undertaken in a healthcare service. The results showed the emotions provoked by the service experience at each level. These levels are interconnected and impact each other working together to influence a person’s cognitive and emotional state, and thus playing a critical role in the overall evaluation of a service. Results show that elements such as servicescape aesthetics, face-to-face and non-human interactions influence emotions and service evaluations. The service should be designed in a way that induces positive emotions, and a feeling of being in control. Especially in healthcare services there is a need to balance the conflicting responses of the emotional stages that may be triggered at the visceral and behavioral levels, while providing reassurance and calm at the reflective level that the health problem is going to be taken care. Using service design approaches this understanding of the customers’ brain can be translated into improving the customer experience. © 2018, Springer Nature Switzerland AG.