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The Strategic Framework for European Cooperation in Education and Training (ET 2020) aimed to promote the exchange of best practices among the Member States. This paper assesses the performance evolution of European countries in terms of the common objectives for the education sector. The framework used to evaluate European education systems is based on constructing a composite indicator adopting a “benefit-of-the-doubt” approach. The evaluation of performance change over time is done using a Global Malmquist Index. Sigma and beta convergence of EU countries are also explored using non-parametric frontier techniques. The results are analysed for the period 2009–2018 and discussed in light of the goals envisaged and the national policies adopted. The results revealed a trend of improvement in the performance of education systems in most European countries in the period analysed. Although most European countries moved closer to the European best practice frontier over time, as confirmed by the values of sigma-convergence, a few countries are still lagging considerably below their peers, as revealed by the existence of divergence in beta.

Jardim, B., Neto, M. D. C., & Barriguinha, A. (2023). A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow. Computers, Environment and Urban Systems, 104(September), [101993]. https://doi.org/10.1016/j.compenvurbsys.2023.101993---This research was funded by the Project C-TECH—Climate Driven Technologies for Low Carbon Cities, grant number POCI-01-0247-FEDER-045919|LISBOA-01-0247-FEDER-045919, co-financed by the ERDF—European Regional Development Fund through the Operational Program for Competitiveness and Internationalization—COMPETE 2020, the Lisbon Portugal Regional Operational Program—LISBOA 2020 and by the Portuguese Foundation for Science and Technology—FCT under MIT Portugal Program. This work was also supported by Portuguese national funds through the Portuguese Foundation for Science and Technology—FCT under research grant FCT UIDB/04152/2020–Centro de Investigação em Gestão de Informação (MagIC). Walkability indicators are a pivotal method to evaluate the role of the built environment in peoples' decisions regarding active mobility, supporting the application of public measures that contribute to more sustainable and resilient regions. Currently, data used to evaluate associations between walkability indicators and travel behavior is obtained via traditional methods of data collection, like questionnaires, that are costly and hard to scale in large urban environments. Moreover, the spatial resolution of most indicators may not be sufficient to support granular local public interventions. To face these issues, we propose a novel walkability indicator that provides a score of walkability for every one-meter street point, based on street conditions and accessibility to points of interest calculated with a Cumulative-Gaussian impedance function. Resorting to Linear and Geospatial Weighted Regressions, we evaluate the associations between walkability features and pedestrian flow data retrieved from mobile phone communication signals for a week in March 2022. The relationship between walkability features and pedestrian flow is stronger during workdays, in which accessibility to education, food amenities and government services are the most important predictors. On the weekend, the features with more explanatory power are accessibility to crosswalks and leisure amenities. Accessibility to public transport, sidewalk width and slope seem to impact pedestrian decisions independently of the day type, although the impact is stronger on weekends. This study provides policy makers and urban planners with a practical tool to effectively support the evaluation of current street conditions and access areas that are underserved, as well as plan and gauge new local interventions, while objectively understanding their impacts on pedestrian mobility. publishersversion epub_ahead_of_print

Regional sustainability assessment has become increasingly important for both scientists and policy-making decisions, as evidenced by the rising amount of academic literature dedicated to this topic. Composite indicators (CI) have remained an assessment tool that is highly appreciated by decision-makers for its ability to summarize a set of indicators into a single index. However, the lack of a unanimously accepted theoretical framework makes the process of composite indicator construction dependent on multiple contextual variables such as the geographical context (national or sub-national), stakeholders’ priorities and data availability. This review paper aims to describe the state of the art in the literature regarding the construction of composite indicators measuring sustainable development at the regional scale and deduce a practical guideline. The review is structured by a set of criteria, derived from the literature, which we consider mandatory for setting up relevant, useful, and meaningful composite indicators at the regional scale that might be adopted by stakeholders. Our main finding is that a CI’s relevance depends not only on its robustness but also on the assessment context and the stakeholders’ involvement. Moreover, we argue for including “governance” as a dimension of sustainable development.

This paper presents a coincident and a leading composite monthly indicator for the world business cycle-the Global Economic Barometers. Both target the world's output growth rate and consist of economic tendency surveys results from many countries around the world. The calculation of these indicators comprises two main stages. The first consists of a variable selection procedure, in which a pre-set correlation threshold and the targeted leads to the reference series are used as selection criteria. In the second stage, the selected variables are combined and transformed into the respective composite indicators, computed as the first partial least squares factor with the reference series as response variable. We analyse the characteristics of the two new indicators in a pseudo real-time setting and demonstrate that both are useful additions to the small number of indicators for the global business cycle published so far. Finally, yet importantly, the Barometers were quick to plunge in the beginning of March 2020 and have since then given a reliable real-time reflection of the economic consequences of the Covid-19 pandemic., Review of World Economics, 158 (3), ISSN:1610-2878, ISSN:1610-2886

En Latinoamérica muchas de las responsabilidades inherentes al desarrollo se han trasladado al nivel subnacional. Las relaciones económicas internacionales forman parte importante del comportamiento actual de muchos Gobiernos regionales. Cuando un espacio subnacional es más cerrado al mundo que otros se evidencia un menor desarrollo en comparación con el resto de su país, por lo tanto gestiones diferenciales en internacionalización explicarían diferentes trayectorias económicas. El análisis de las posibles dimensiones de un comportamiento estratégico de los Gobiernos no centrales en conjunto con la internacionalización de un espacio subnacional será el hilo conductor del presente trabajo. El objetivo será proponer un índice para medir la internacionalización como parte de un comportamiento estratégico y postular su posible impacto en indicadores de desarrollo centrándonos, para ello, en el análisis de Argentina en 2015. In Latin America, many of the development responsibilities have been transferred to sub-national level. International economic relations are an important part of the current behavior of many regional governments. When a sub-national space is more closed to the world than others, it’s verified a less development compared to the rest of the country, therefore differential policies in internationalization would explain different economic path. The analysis of the possible dimensions of a strategic behavior applied together a sub-national internationalization will be the key issue of this work. The objective will be to propose an index to measure internationalization as part of a strategic behavior and analyze its possible impact on development indicators focusing on the analysis of Argentina in 2015. En Amérique latine, nombreaux responsabilités de développement ont été transférées au niveau infranational. Les relations économiques internationales constituent une partie importante des comportement actuelles de nombreux gouvernements régionaux. Quand un espace infranational est plus fermé au monde que d’autres, il a démontré un développement moins significatif que le reste du pays; par conséquent, des actions différentes en matière d’internationalisation expliqueraient une trajectoire économique différente. L’analyse des dimensions possibles d’un comportement stratégique des gouvernements non centraux avec l’internationalisation d’un espace sous-national sera la question clé de ce travail. L’objectif sera de proposer un indice permettant de mesurer l’internationalisation dans le cadre d’un comportement stratégique et d’analyser son impact éventuel sur les indicateurs de développement, en se concentrant sur l’analyse de l’Argentine en 2015. 71-87 aldeamundo@gmail.com javierdiazbay@gmail.com Semestral http://erevistas.saber.ula.ve/aldeamundo

The current global freshwater crisis threatens the present and future supply of water as a resource for humans. The scarcity of drinking water and the dependence of the food indus- try on water-intensive supply chains require the urgent development of strategies to analyze and guarantee the water sustainability of countries. This study proposes a fuzzy-data envel- opment analysis composite index that measures, from a benchmarking approach, water sus- tainability by simultaneously considering capacity and resilience, and captures the uncer- tainty associated with time series variations in three scenarios: pessimistic, indifferent and optimistic. We present and apply an index based on five indicators of capacity and five indicators of resilience in ten European Union countries water risk hotspots. The results in terms of capacity presented a higher variability due to the strong growth in the exploita- tion of water resources in Greece, Spain, France, Italy and Portugal. The most sustainable countries in terms of capacity were Bulgaria and Estonia in a pessimistic and an indifferent scenario and France and Bulgaria in an optimistic scenario. In terms of resilience, Belgium and Portugal were the most sustainable countries. When considering capacity and resil- ience together, some countries such as Bulgaria and Estonia lost positions in the ranking, with Belgium occupying the first position. Some countries, such as Bulgaria, could see the sustainability of their water resources compromised in a scenario of economic develop- ment if they do not improve their governance and water productivity constraints., Universidad de Granada/CBUA

This paper aims to assess the profitability and employees’ productivity of Italian innovative start-ups with a new composite index: the Start-ups Performance score (SP-score). In recent years, the Italian government has made several efforts to foster the economy, establishment, and growth of start-ups. Specifically, the issuing of the Italian Start-up Act in 2012 offers a unique opportunity to examine the Italian setting, given the special conditions that the government granted to the start-ups. The latter obtain generic benefits, tax reductions and hiring facilitations if they meet specific criteria granting the status (label) of “innovative” by law. Based on a sample of Italian start-ups firms (ISPs) and financial statement data for the period 2016–2020, we test whether the performance of the Italian start-ups which are granted the status of “innovative” is higher compared to start-ups without the mentioned status (NISPs). We measure the firm’s performance by building a composite index which synthesizes both profitability and employees’ productivity (controlling for the firms’ size), and find that the ISPs report higher SP-score compared to the NISPs. In addition, we examine whether the SP-score is higher (or lower) among Innovative start-ups located in different regional areas. The derivation of the composite indicator (SP-score) allows a clear and effective evaluation of several characteristics, permitting a more comprehensive understanding of the data that support the strategic choices of management and localization entrepreneurship policies. In addition, our study highlights a certain homogeneity of innovative start-ups’ performance among the Italian territories, which overcomes the classic dualistic division between Northern and Southern regions.

Introduction \ud The veteran population in the UK has been decreasing, however, there remains a proportion of veterans and their families who continue to experience multiple and complex health, financial, and social needs. The complex problems tend to exacerbate each other and deepen over time if appropriate support is not provided. Identifying the veterans with complex needs is crucial for effective support by military charities and health and social care services. The present research aims to develop a complex needs indicator for the veteran population (CNIV) that will quantify complexity and help to identify the risk of having or developing complex needs.\ud \ud Methods \ud The development of the CNIV will be informed by the guidance for constructing composite indicators. The data on grant support received by veterans’ beneficiaries from the UK Royal Marine and SSFA charities will be used for designing the indicator and evaluating its robustness. The crucial step in constructing the indicator is assigning weights to different needs and risk factors associated with complex cases. Factor analysis (FA) and analytical network process (ANP) will be used as weighting methods for the analysed variables. \ud \ud Conclusion \ud The development of CNIV has important implications for research and practice, such as the potential to be used as a screening tool for identifying complex cases, improved provision of the targeted support to veterans, assessing the scope of complex problems among veterans within the country and informing policy makers and a more general audience of the complexity of need within the sector.

The object of this research is the relationship between Transaction Costs and economic performance. Weak or unreliable institutions open space for corruption, generating a negative externality, increasing the economy's Transaction Costs, inhibiting doing business, and reducing economic growth. Although there is a broad debate about the negative relationship between Transaction Costs and economic performance, little is known about this relationship's strength and significance. This gap occurs because most Transaction Costs estimates are performed at the microeconomic level. Besides, the few estimates of countries' Transaction Costs at the national level are from different periods, which make any analysis unfeasible. The objective of this research is twofold. First, to introduce a comparative index of the Transaction Costs of the countries. Second, to analyze the relationship between the Transaction Costs Index and economic performance. The robustness analysis reveals that the Transaction Costs Index is reliable because the countries' average variation in the ranking is relatively low (1.5 positions), serving as an alternative to the Transaction Costs estimates. The research results show a significant (p-value=0.0054), strong, and negative (R=–0.746) correlation between the Transaction Costs Index and the Gross National Income per capita of G7+BRICS countries. BRICS countries and Italy have lower economic performance, and higher scores on the Transaction Costs Index, suggesting that these countries' institutions are more inefficient than other G7 countries. These results reinforce the current understanding of the negative relationship between Transaction Costs and countries' economic performance. Understanding the effects of Transaction Costs on business activity and, consequently, on economic performance is extremely important for governments to promote adjustments in the regulatory environment that encourage business activity., Об’єктом цього дослідження є зв’язок між трансакційними витратами та економічною ефективністю. Слабкі або ненадійні інституції відкривають простір для корупції, створюючи негативні зовнішні ефекти, збільшуючи трансакційні витрати економіки, перешкоджаючи веденню бізнесу та знижуючи економічне зростання. Хоча точаться широкі дебати щодо негативного зв’язку між трансакційними витратами та економічною ефективністю, мало відомо про силу та значення цього зв’язку. Цей розрив виникає через те, що більшість оцінок трансакційних витрат виконується на мікроекономічному рівні. Крім того, кілька оцінок трансакційних витрат країн на національному рівні належать до різних періодів, що робить будь-який аналіз неможливим. Це дослідження має двояке направлення. По-перше, ввести порівняльний індекс трансакційних витрат країн. По-друге, проаналізувати взаємозв’язок між індексом трансакційних витрат та економічною ефективністю. Аналіз стійкості показує, що індекс трансакційних витрат є надійним, оскільки середня різниця країн у рейтингу є відносно низькою (1,5 позиції), що служить альтернативою оцінкам трансакційних витрат. Результати дослідження показують значну (p-value=0,0054), сильну та негативну (R=–0,746) кореляції між індексом трансакційних витрат та валовим національним доходом на душу населення країн G7+BRICS. Країни BRICS та Італія мають нижчі економічні показники та вищі показники за індексом трансакційних витрат, що свідчить про те, що інститути цих країн є більш неефективними, ніж інші країни G7. Ці результати підкріплюють поточне розуміння негативного зв’язку між трансакційними витратами та економічними показниками країни. Розуміння впливу трансакційних витрат на ділову активність і, як наслідок, на економічні показники є надзвичайно важливим для урядів, щоб сприяти коригуванням нормативного середовища, яке заохочує ділову активність.

A loss of the ability to buy and prepare meals, especially in people aged 65 and over, leads to a deterioration in their optimal level of nutrition. The Index of Autonomy in Food Acquisition (IAFA) was used to identify contributing factors. This is a composite indicator for shopping and meal preparation that can be used to assess the degree of autonomous capacity observed in a specific group. Data from the European Health Survey in Spain (7167 respondents aged 65 and over) show that capacity decreased with age and that women were less affected than men, with very little difference found in levels of autonomous capacity by territory. However, in relation to different income levels, after standardizing for age and sex, no evidence was found for differences in the ability to access and prepare meals in groups that were separated by income level. This result shows the importance of standardizing when analysing food acquisition autonomy in groups of people aged 65 years and over.

Compendi d'articles There is increasing interest in the construction of composite indicators to evaluate socio economic concepts. In general, the mathematical approaches on which the most commonly used techniques are based do not allow for reliable benchmarking. Moreover, the determination of the weighting scheme in composite indicators remains one of the most problematic issues. In this thesis, different methodologies are analyzed to extract their strengths and weaknesses. From this analysis it emerges that few of these tools allow comparison between observations. Using the vector space formed by all observations, a new method to construct composite indicators is proposed:a distance or metric that considers the concept of proximity between units. To do so, we take Pena Trapero’s P2 Distance method as a starting point. The proposed methodology eliminates the linear dependence of the model and looks for functional relationships that allow us to build themost efficient model. This approach reduces the subjectivity of the researcher by assigning the weighting scheme with unsupervised machine learning techniques. Monte Carlo simulations confirm that the proposed methodology is robust. As an application of this new approach, a vulnerability index is constructed for the European Union (EU) regions. The cohesion policy is analyzed for the period 2021-2027 focuses on five objectives to make the EU smarter, greener, more connected, more social and closer to citizens. A macroeconomic index is proposed as the predominant criterion for allocating Structural Funds among regions. It is hypothesized that it is possible to take into account new complementary criteria that better reflect the quality of life of citizens. To this end, a composite index of socio-economic vulnerability is constructed for the 233 regions studied. The results show that, following our multidimensional approach for the allocation of Structural Funds, there are notable differences in the maps of priority regions. Moreover, the COVID-19 pandemic represents a welfare threat. Multilevel models are estimated from which it follows that country characteristics interact with those of regions to alter vulnerability patterns. More specifically, increased public spending on education and improved political stability would reduce regional vulnerability or build resilience, while increased poverty would be associated with increased vulnerability. Likewise, the most vulnerable regions would be the most exposed to the negative socio economic effects of COVID-19. Programa de Doctorat en Desenvolupament Local i Cooperació Internacional

There has been a growing consensus in recent years that development is a multidimensional concept that embodies the enhancement of several aspects of human life and, as a result, it is too complex to be captured by single indices. Composite Indicators have increasingly been recognised as useful tools in the measurement of this concept. In the absence of rigorous and comprehensive empirical studies in Greece on this topic, the paper assesses and reveals the developmental transformations of the regional economies at NUTS 2 and 3 levels in the period 1991-2011. In this way, this study provides a more comprehensive and integrative perspective of regional development in Greece presenting empirical evidence not only from a country with large and persistent regional inequalities but also from a cohesion country of the European Union for which regional policy has been of critical importance in the last decades. Moreover, the study adds to the literature shedding light on an under-researched topic; the importance of spatial heterogeneity in the construction of Composite Indicators. The results reveal a heterogeneous regional pattern of development for the Greek case. The findings can be used by policymakers as a way to better understand and improve the regional development process.

Summarization: We propose a holistic evaluation framework that banks could adopt when screening corporate entities. The framework is based on the development of a composite indicator of social, environmental and financial performance. This integrated view of evaluation is conceptually aligned with ISO standards and empirical proposals of academics and market practitioners in defining inclusive performance. We complement those proposals with a methodological framework that permits incorporation of a plethora of viewpoints in the evaluation process, reflecting the expectations of the various stakeholders in the environment of a bank. We further enhance the evaluation process with analytics of a more detailed hierarchical view of performance, fine-tuning of the evaluation process, and provide implications and suggestions to the senior executive team of a bank’s clients. Presented on: European Journal of Operational Research

Known as the second most profitable industry worldwide, tourism is now very important to states and can have a prominent role in their economic growth. Therefore, it is necessary to analyze the factors affecting tourism. In addition to the exchange rate, these factors include economic, political, cultural, infrastructural, and environmental indicators, all of which were analyzed in this study. For this purpose, a vector autoregressive (VAR) model was developed to analyze data of Iran from 1981 to 2018. According to the research findings, the exchange rate and economic, political, cultural, infrastructural, and environmental composite indicators had significant impacts on Iran’s tourism revenue. Conhecida como a segunda indústria mais rentável do mundo, o turismo agora é muito importante para os estados e pode ter um papel de destaque em seu crescimento econômico. Portanto, é necessário analisar os fatores que afetam o turismo. Além da taxa de câmbio, esses fatores incluem indicadores econômicos, políticos, culturais, de infraestrutura e ambientais, todos analisados neste estudo. Para esse fim, um modelo de vetor autoregressivo (VAR) foi desenvolvido para analisar os dados do Irã de 1981 a 2018. De acordo com os resultados da pesquisa, a taxa de câmbio e os indicadores compostos econômicos, políticos, culturais, de infraestrutura e ambientais tiveram impactos significativos sobre o Irã. receita de turismo.

Early intervention in quality education is a way to equalize opportunities, a premise assumed by several countries. As a result, interest has grown in preschool education, which is now an important area of public policy. However, the performance of preschool education centers has received relatively scarce research attention. Consistent with the above, the aim of this study is to examine the problem and evaluate the performance of preschool education centers that serve children from lower socioeconomic families in Chile. To this end, a centralized DEA Assurance Region model is proposed and compared with two other models. In addition, a second stage analysis is carried out using decision trees to identify variables that determine the composition of homogeneous preschool groups according to their effectiveness. The results show an average efficiency index of 70.54% with important heterogeneities between regions of the country, and significantly less than the 84.47% obtained through a traditional benefit-of-the-doubt model. The centralized (unique) weights obtained were 45% for learning, and 32% for user satisfaction and job satisfaction. A second stage analysis reveals the importance of three structural factors that mark the effectiveness of kindergartens: (i) size of the kindergarten; (ii) family income; and (iii) urban or rural location of the kindergarten. These results are relevant to public policy since they propose a valid and useful methodology for decision makers, quantify the levels of effectiveness, and emphasize the importance of focusing efforts on the centers that, due to their structural conditions, are more prone to lower levels of effectiveness. Similarly, they validate and align with the changes at this level of education in Chile in recent years.

The established variable selection methods for building composite indicators have strong limitations with respect to the results obtained. Some of them focus on getting an index structure with a high alpha reliability and/or a high percentage of the total data variance explained. These methods are likely to omit variables with strong explanatory power, and lead to an unsatisfactory classification of countries. Decision trees can also be used in selecting variables that are the most relevant for building composite indicators. An example of variable selection for building a composite indicator, which compares results using Cronbach's coefficient alpha, factor analysis, and decision trees, shows that the latter method yields comparable, or better results. Using cluster analysis on the selected variables, we show that the decision tree variable shortlist has better discrimination power than those obtained with the other methods, even in the presence of outliers and missing values.

The assessment of the teacher performance is a subject of criticism due to the lack of a well-establish methodology. This study develops an overall score to measure the dimensions that encompass the academic activities. To that end, a Benefit-of-the-doubt model is proposed. The advantage of this technique is the flexibility in the weights, so that the model selects for each teacher the most favourable set of weights. Furthermore, the paper proposes the barycentric coordinate system as a method to classify the teachers in clusters depending on their contribution to the dimensions. A specific pie chart has been proposed as an efficient way to report the contribution of the teachers to the dimensions and the overall teacher performance.

This paper measures and analyses well-being in the 349 regions in OECD countries. It is argued that the multidimensional nature of well-being and the disparate policy priorities of nations/regions calls for a reconciliatory performance evaluation framework, for which this paper advocates the use of Benefit-of-the-Doubt (BoD) weighting. In particular, using the BoD-model, three multidimensional measures of regional well-being are computed: a material condition measure, a quality of life index and a subjective life satisfaction measure. To account for the presence of certain exogenous conditions in the regional policy environments, the conditional robust order-m version of the BoD-model is applied. Results show considerable between- and within-country disparity in regional performances across the three domains of well-being. Countries such as Australia, Canada, Norway and Iceland show consistently high levels of regional well-being. Consistently low performance levels are observed for Chile, Turkey and Poland.

Inclusive and equitable education and the promotion of lifelong learning opportunities for all are important targets in the 2030 Agenda for Sustainable Development. Deprivation in education, read also as deprivation of opportunities and rights i.e. health, culture, participation, social relations, referred to as educational poverty (EP), has attracted interest of researchers, which highlighted its complexities and consequences, such as being excluded from acquiring the skills needed to live in a world characterized by knowledge-based economy, rapidity and innovation. In the last few years, the Italian National Statistical Institute started to measure it by a multidimensional index, the composite educational poverty index (EPI). The index is based on survey direct estimates, which are reliable only at regional (NUTS 2) level, while to monitor and contrast the phenomenon it is important to obtain information at a finer geographical level. In this paper small area estimation models are applied to the unidimensional indicators which compose the multidimensional EPI. The aim is to enhance the knowledge of the spatial distribution of EP at local level in Italy, separating urban and non urban areas and focusing on peripheries in Italian Regions, using DEGURBA classification in order to help the policy maker to address resources towards the areas where the phenomenon is strongly present.

Since 2012, driven by the desire to propose a subjective well-being index (SWBI) complementary to the traditional measures, with high time and space frequency, our team evaluates, analysing Twitter data, a composite index that captures various aspects and dimensions of individual and collective life. The SWBI is a multidimensional indicator whose components were inspired by the dimensions adopted for the Happy Planet Index provided by the New Economic Foundation. In detail, it consists of eight dimensions that describe three different areas: personal well-being, social well-being and well-being at work. The Italian subjective well-being index ($$\hbox {SWBI}_{{ITA}}$$), that we display here, audits the Italian subjective well-being revealed by tweets acquired via the public Twitter API, written in the Italian language, and posted from Italy from January 2012 to December 2017. Around 1–5% of the data includes geo-referenced information, which allows us to provide an index at local level. The Twitter data analysis is carried on with a human supervised sentiment analysis method, the Integrated Sentiment Analysis (iSA) algorithm. In this work, after a weighting procedure adopted to partially overcome the selection bias caused by the use of data from social network, we describe the $$\hbox {SWBI}_{{ITA}}$$ dimensions in the considered period at the regional level. Moreover, for some dimensions, for which a similar currently available measure provided by Italian official statistics exists, comparisons are proposed emphasizing novelties, similarities and differences.

The paper aims to improve the methodology of the Digital Economic and Society Index (DESI), the European Commission’s newest index to assess the development of the digital economy. In particular, we investigate whether methodological changes to the structure of DESI improve its ability to capture the digital transformation of EU economies. Using the sensitivitybased analysis, we check whether the selection of weights of individual elements included in the DESI is optimal or should be improved. We also verify the importance of DESI in explaining changes in GDP per capita in EU economies. In the literature, we find that digital transformation has enabled the creation of new business models and maximized efficiency in traditional firms. Using DESI, we empirically test whether the gap between rich and poor countries in European Union can be closed or eliminated through rapid and intensive digital transformation. Our results show that the DESI – when modified by eliminating the pillars on internet services and digital public services – has the same explanatory power. Connectivity is the dimension with the largest impact on digital transformation in EU countries. We also find that DESI is a significant regressor to explain changes in GDP per capita in EU countries.

Resumen Objetivo: En el diseño de una prótesis de mano robótica surgen variedad de problemáticas para las cuales existen múltiples soluciones propuestas en la literatura. Una de las problemáticas es la selección de una estrategia para el control automático del movimiento de la mano. Entre las funcionalidades de una prótesis, la de agarre de poder es una de las más importantes. Dada la gran cantidad de propuestas en cuanto técnicas de control para el agarre de poder, el diseñador se enfrenta al dilema de cuál de ellas es la más adecuada para su diseño particular. Aunque hay métricas para cuantificar la calidad del agarre, las que se han propuesto abordan diversos aspectos de manera independiente, lo cual no permite tomar una decisión acerca de la mejor opción para el caso particular. En este trabajo se propone un método para calcular un indicador compuesto que permite la evaluación del desempeño de técnicas de control en el agarre de poder, con base en las siguientes métricas individuales que evalúan diferentes aspectos en la ejecución del agarre de poder: la fuerza del dedo, la fuerza del agarre, la eficiencia del agarre, el tiempo de ciclo de agarre, la resistencia al deslizamiento, el error de seguimiento y el sobreimpulso de la respuesta transitoria. Gracias al método propuesto en este trabajo, se da respuesta a la pregunta: "De varias opciones de control a probar, ¿cuál ofrece un mejor desempeño funcional?". Metodología: Se adoptó un conjunto de métricas con las cuales obtener datos cuantitativos relacionadas con la calidad del agarre de poder y con el desempeño del objetivo de control para gobernar la prótesis. Posteriormente, se calcularon métricas individuales seleccionadas para cada una de las técnicas de control de agarre a evaluar, sobre un entorno virtual, constituido por una mano robótica y un objeto a agarrar. Luego se construyeron dos indicadores compuestos para obtener una valoración cuantitativa de la calidad del agarre a partir de un análisis estadístico, y se contrastaron los resultados contra las métricas individuales utilizadas. Resultados: Se planteó un método para la construcción de un indicador compuesto que permitiera la evaluación del desempeño de técnicas de control, en agarres de poder en manos robóticas. Al implementar dicho método, se encontraron los mejores valores de desempeño en controladores híbridos. Conclusiones: En este trabajo se sugiere una alternativa tendiente a facilitar la toma de decisiones del diseñador en cuanto a la técnica de control más adecuada, entre varias disponibles, para el logro del agarre de poder con una prótesis específica. El método busca construir un indicador compuesto que agrupa variadas métricas para evaluar funcionalidad particular de agarre, y también para cuantificar el logro de seguimiento de consignas, facilitando la toma de decisiones acerca de la incidencia de la técnica de control en el logro del objetivo final. Financiamiento: Este trabajo fue financiado por la Universidad del Cauca, en el marco del programa de Maestría en Automática. ABSTRACT Objective: In the design of a robotic hand prosthesis, a variety of problems arise for which there are multiple solutions proposed in the literature. One of them is the selection of a strategy for the automatic control of the movement of the hand. Within the functionalities of a prosthesis, the power grip functionality is one of the most important. Given the wide variety of proposals in terms of control techniques for power grip, the designer is faced with the dilemma of which of them is the most suitable for his particular design. Although there are metrics to quantify the quality of the grip, those that have been proposed address various aspects independently, which does not allow making a decision about the best option for the particular case. In this work, a method is proposed to calculate a composite indicator that allows the evaluation of the performance of control techniques in the power grip based on the following individual metrics that evaluate different aspects in the execution of the power grip: finger strength, grip strength, grip efficiency, grip cycle time, slip resistance, following error, and transient response overshoot. Thanks to the method proposed in this work, the question is answered: of several control options to be tested, which one offers better functional performance? Methodology: A set of metrics are adopted with which to obtain quantitative data related to the quality of the power grip and to the performance of the control target to govern the prosthesis; subsequently, selected individual metrics are calculated for each of the grip control techniques to be evaluated on a virtual environment, consisting of a robotic hand and an object to be grasped; then two composite indicators are constructed to obtain a quantitative assessment of the quality of the grip based on a statistical analysis, and the results are contrasted against the individual metrics used. Results: A method is proposed for the construction of a composite indicator, which allows the evaluation of the performance of control techniques, in power grips in robotic hands. By implementing this method, the best performance values were found in hybrid controllers. Conclusions: In this work, a method has been proposed to facilitate the decision-making of the designer regarding the most adequate control technique, among several available, to achieve the power grip with a specific prosthesis. The method seeks to build a composite indicator that groups together various metrics to evaluate particular grip functionality, and also to quantify the achievement of following instructions, facilitating decision-making about the incidence of the control technique in the achievement of the final objective. Financing: This work was supported by University of Cauca under the Master of Science in Automation program.

This work was supported by the project FEDER-University of Granada ( B-SEJ-242.UGR20 ), 2021-2023: An innovative methodological approach for measuring multidimensional poverty in Andalusia (COMPOSITE). Eduardo Jiménez-Fernández would also like to thank the support received from Universitat Jaume I under the grant E-2018-03 ., This study aims at developing a new methodological approach for building composite indicators, focusing on the weight schemes through an unsupervised machine learning technique. The composite indicator proposed is based on fuzzy metrics to capture multidimensional concepts that do not have boundaries, such as competitiveness, development, corruption or vulnerability. This methodology is designed for formative measurement models using a set of indicators measured on different scales (quantitative, ordinal and binary) and it is partially compensatory. Under a benchmarking approach, the single indicators are synthesized. The optimization method applied manages to remove the overlapping information provided for the single indicators, so that the composite indicator provides a more realistic and faithful approximation to the concept which would be studied. It has been quantitatively and qualitatively validated with a set of randomized databases covering extreme and usual cases., FEDER-University of Granada B-SEJ-242, Universitat Jaume I UJI E-2018-03

This research proposes a decision framework that allows for the identification of the most suitable methods to construct stable composite indicators that capture the concept of multidimensional social phenomena. This decision framework is applied to discover which method among six best represents the social exclusion of eight medium-sized Brazilian cities. The results indicate that space is important in the definition and performance of the method, and ease methods to apply present the best performance. However, one of them fails to capture the concept of the multidimensional phenomenon in two cities. The research makes six important contributions to the literature. First, it offers a decision framework for choosing the best-fit method to construct a composite social indicator. Second, it shows to what extent geographic space matters in defining the best-fit method. Third, it identifies the best-fit method regarding stability and linkage with the conceptually most significant indicator of social exclusion. Fourth, it reveals the methods to be avoided, given their poor performance. Fifth, it indicates the mathematical properties that best represent composite social phenomena. Sixth, it illuminates the debate on social exclusion from a geographical and public policy perspective.

Composite indicators play an important role in the analysis of socio-economic phenomena. A number of different approaches to constructing composite indicators have been proposed in the literature. Depending on the degree of compensation, they can be divided into compensatory, partially compensatory, and non-compensatory. The following article focuses on the method of relative taxonomy and its dynamic modification. While this method is typically applied to metric data, the authors propose using the dynamic approach for interval-valued data, which describes objects of interest more precisely. Metric data are of an atomic nature; i.e., an observation of each variable is expressed as one real number. In contrast, each observation of an interval-valued variable is expressed as an interval. By making use of interval-valued data, it is possible to assess objects not only at the regional level but also at a lower level of territorial aggregation, taking into account spatial variation across districts that make up each region. The study described in the article was conducted by applying relative taxonomy in its dynamic approach to interval-valued data in order to measure the level of social cohesion in Poland’s NUTS2 regions during the period 2010–2019. The target dataset was obtained by aggregating numeric data about social cohesion in districts (LAU1) at the level of regions. The lower and upper limit of the interval for each region was based on district-level data and corresponded to the 2nd and 8th decile, respectively (60% of observations), which helped to mitigate the effect of outliers. By applying dynamic relative taxonomy to interval-valued data, it was possible to graphically represent changes in the level of social cohesion that took place across 17 Poland’s NUTS2 regions between 2010 and 2019. It was found that during the reference period, the level of social cohesion in the regions systematically improved. Despite the observed variation, the distance between the regions consistently decreased over time. The level of social cohesion was found to be higher in regions that had received more EU funding to support regional development.

This paper develops and tests new (alternative) models for assessing the development of subnational government units in Croatia. The aim is to assess the possibilities for improving the existing official model for calculating the development index of subnational units. Given its high policy impact, especially in terms of central-level support for the local development projects, there is a strong policy interest for continuous monitoring and evaluation of model’s validity. In essence, the paper considers different variants of the existing model, since all tested variants retain some of its key elements. In particular, all variants still use the balanced z- score method to calculate standardized values. Also, each development indicator included has equal weight in the final assessment of development. However, we alter the choice of development indicators and consider some other aspects of the calculation and categorization of units by development groups. Testing of new variants was performed in two steps: in the first step, we examine the suitability of new potential indicators, and in the second step, we test different models by retaining some existing and adding new indicators. A total of seven new model variants were developed, which differ from each other based on the indicators included. To this end, the scenario analysis was performed to assess the effectiveness of various models in identifying less developed local government units. Despite our efforts to identify new indicators that would be more effective in categorizing local and regional government units based on their level of development, we recommend retaining the existing set of indicators. However, the Government might consider excluding the own-source revenue per capita as an indicator for calculating the development index because the indicator of fiscal capacity is already used for redistributive purposes within the fiscal equalization policy.

[ES] La Evaluación Ambiental Estratégica (EAE) proporciona el marco para la articulación de los proyectos de forma coherente y respetuosa con el medio ambiente, condiciones sociales, políticas y económicas (Arce y Gullón, 2000) y aunque comúnmente se le conoce a la EAE como una herramienta, esta representa un proceso que puede mejorar la toma de decisiones y propiciar el desarrollo sostenible (Bidstrup y Hansen, 2014). El análisis de alternativas es una de las áreas más débiles de la EAE, debido a que no se ha investigado suficientemente qué funciona y qué no en el desarrollo, evaluación y selección de alternativas. Estas investigaciones deben incluir enfoques sistemáticos para la identificación y el desarrollo de alternativas, para involucrar plenamente a las partes interesadas en su definición y evaluación, y proporcionar detalles suficientes al documentar el proceso de la selección (González et al., 2018). A estas debilidades se añade la dificultad de desarrollar una metodología que sea adaptable a diferentes con-textos. Estos condicionantes han encauzado la construcción de la metodología desarrollada en esta tesis y así, lograr minimizar estas brechas, planteando un método analítico, simple y flexible. La metodología denominada "Índice de Selección de Alternativas Estratégicas Ambientales (ISAEA) y sus incertidumbres", parte de la utilización de indicadores simples construidos en base a las metas que se plantean en el instrumento evaluado en la EAE. Al construir los indicadores partiendo de los criterios de los propios objetivos o metas del Plan, Proyecto o Programa (PPP), se disminuye la complejidad y ambigüedad que típicamente existe en la construcción y/o selección de indicadores ambientales, pues queda claro la dirección que debe seguirse en la construcción del indicador. Los criterios de construcción permiten optimizar la calidad del indicador, ya que el mismo describe el objetivo y, por ende, se manejan indicadores que son los adecuados para ese PPP en particular, es decir, adaptado al contexto preciso del PPP. El ISAEA se complementa con un análisis de incertidumbre, que ofrece al tomador de decisiones herramientas completas para proceder a seleccionar con información cuantitativa, la alternativa que más conveniente para el PPP estudiado. De este modo, la metodología propuesta proporciona un índice que representa en qué medida se acerca la alternativa a la meta planteada, aportando además una adaptación de los análisis de incertidumbre al uso de indicadores compuestos. La experiencia de la aplicación de esta metodología en ambos de sus componentes principales, el ISAEA y el análisis de incertidumbre, deja de manifiesto la importancia de la cooperación abierta de la entidad promotora del PPP para garantizar el flujo de información y más importante aún, de información confiable. Tras el desarrollo de la presente investigación se concluye que la metodología desarrollada aporta una herramienta valiosa, que puede ser utilizada de forma simple y a la vez permite reflejar las circunstancias propias del PPP. A la vez, la metodología ofrece resultados en un lenguaje matemático llano, fácilmente entendible para los tomadores de decisiones. La metodología que se aporta en esta investigación doctoral llega a minimizar una brecha en la temática de selección de alternativas en la EAE, ya que se basa en información cuantitativa y a la vez ha asumido un desafío pendiente en evaluaciones ambientales al incorporar el análisis de incertidumbre como un criterio de acompañamiento al ISAEA, que permite realizar una selección de alternativas estratégicas en base a criterios científicos., [CA] L'Avaluació Ambiental Estratègica (AAE) proporciona el marc per a l'articulació dels projectes de forma coherent i respectuosa amb el medi ambient, condicions socials, polítiques i econòmiques (Arce i Gullón, 2000) i encara que comunament se li coneix a la AAE com una eina, aquesta representa un procés que pot millorar la presa de decisions i propiciar el desenvolupament sostenible (Bidstrup i Hansen, 2014). L'anàlisi d'alternatives és una de les àrees més febles de la AAE, pel fet que no s'ha investigat prou què funciona i què no en el desenvolupament, avaluació i selecció d'alternatives. Aquestes investigacions han d'incloure enfocaments sistemàtics per a la identificació i el desenvolupament d'alternatives, per involucrar plenament a les parts interessades en la seva definició i avaluació, i proporcionar detalls suficients al documentar el procés de la selecció (González et al., 2018). A aquestes debilitats s'afegeix la dificultat de desenvolupar una metodologia que sigui adaptable a diferents contextos. Aquests condicionants han canalitzat la construcció de la metodologia desenvolupada en aquesta tesi i així, aconseguir minimitzar aquestes bretxes, plantejant un mètode analític, simple i flexible. La metodologia anomenada "Índex de Selecció d'Alternatives Estratègiques Ambientals (ISAEA) i les seves incerteses", part de la utilització de indicadors simples construïts en base a les metes que es plantegen en el instrument avaluat en l'AAE. Al construir els indicadors partint dels criteris dels propis objectius o metes de el Pla, Projecte o Programa (PPP), es disminueix la complexitat i ambigüitat que típicament existeix en la construcció i/o selecció d'indicadors ambientals, ja que queda clar la direcció que ha de seguirse en la construcció de l'indicador. Els criteris de construcció permeten optimitzar la qualitat de l'indicador, ja que el mateix descriu el objectiu i, per tant, es manegen indicadors que són els adequats per a aquest PPP en particular, és a dir, adaptat al context precís de l'PPP. L'ISAEA es complementa amb una anàlisi d'incertesa, que ofereix al prenedor de decisions eines completes per a procedir a seleccionar amb informació quantitativa, l'alternativa que més convenient per al PPP estudiat. D'aquesta manera, la metodologia proposada proporciona un índex que representa en quina mesura s'acosta l'alternativa a la meta plantejada, aportant a més una adaptació de les anàlisis d'incertesa a l'ús d'indicadors com-llocs. L'experiència de l'aplicació d'aquesta metodologia en tots dos dels seus components principals, l'ISAEA i l'anàlisi d'incertesa, deixa de manifest la importància de la cooperació oberta de l'entitat promotora de l'PPP per garantir el flux d'informació i, més important encara, d'informació ambfiable. Després de concloure la present investigació queda demostrat que la metodologia desenvolupada aporta una eina valuosa, que pot ser utilitzada de forma simple i alhora permet reflectir les circumstàncies pròpies de l'PPP. Alhora, la metodologia ofereix resultats en un llenguatge matemàtic pla, fàcilment comprensible per als prenedors de decisions. La metodologia que s'aporta en aquesta tesi doctoral arriba a minimitzar una bretxa en la temàtica de selecció d'alternatives a l'EAE, ja que es basa en informació quantitativa i alhora ha assumit un repte pendent en avaluacions ambientals a l'incorporar el anàlisi d'incertesa com un criteri d'acompanyament a l'ISAEA, que permet realitzar una selecció d'alternatives estratègiques en base a criteris científics, [EN] Strategic Environmental Assessment (SEA) provides the framework for the articulation of projects in a coherent and respectful way with the environment, social, political and economic conditions (Arce and Gullón, 2000). Although SEA is commonly known as a tool, it represents a process that can improve decision-making and promote sustainable development (Bidstrup and Hansen, 2014). The analysis of alternatives is one of the weakest areas of SEA, because what works and what does not in the development, evaluation and selection of alternatives has not been sufficiently investigated. These investigations should include systematic ap-proaches for the identification and development of alternatives, to fully involve stake-holders in their definition and evaluation, and provide sufficient detail when documenting the selection process (González et al., 2018). Besides these weaknesses, the difficulty of developing a methodology that is adaptable to different contexts appears. These conditioning factors have guided the construction of the methodology developed in this thesis and thus, manage to minimize these gaps, proposing an analytical, simple and flexible method. The methodology called "Selection Index for Strategic Environmental Alternatives (ISAEA) and its uncertainties", starts from the use of simple indicators built on the basis of the goals set out in the instrument evaluated by the SEA. By constructing the indicators based on the criteria of the objectives or goals of the Plan, Project or Program (PPP), the complexity and ambiguity that typically exists in the construction and/or selection of environmental indicators is reduced, since the direction to be followed in the construction of the indicator. The construction criteria allow optimizing the quality of the indicator, since it describes the objective and, therefore, indicators are used that are appropriate for that particular PPP, that is, adapted to the precise context of each PPP. The ISAEA is complemented with an uncertainty analysis, which offers the decision maker complete tools to proceed to select with quantitative information, the most convenient alternative for the PPP studied. Therefore, the proposed methodology provides an index that represents to what extent the alternative approaches the proposed goal, also providing an adaptation of the uncertainty analyzes to the use of composite indicators. The experience of applying this methodology in both of its main components, the ISAEA and the uncertainty analysis, shows the importance of the open cooperation of the PPP promoter to guarantee the flow of information and, more importantly, reliable information. After the development of this research, it is concluded that the developed methodology provides a valuable tool, which can be used in a simple way while allowing reflecting the circumstances of the PPP. At the same time, the methodology offers results in plain mathematical language, easily understood by decision makers. The methodology provided in this doctoral research minimizes a gap in the subject of selecting alternatives in SEA, since it is based on quantitative information and at the same time has assumed a pending challenge in environmental evaluations by incorporating the uncertainty analysis as an accompanying criterion to the ISAEA, which allows a selection of strategic alternatives based on scientific criteria.

The establishment of incentive zones represents a cluster policy approach that a country can implement to boost economic growth. Being influenced by regional characteristics, the success of specific incentive types (special economic zones, free-trade zones, free zones) may vary considerably. By using a new composite indicator, differently designed according to each type of development plan, this study analyses 51 European incentive zones so as to identify best practices. Moreover, propensity score matching allows the net impact of the industrial policy to be assessed. The findings show significant positive results achieved by the various industrial policy instruments with differing levels of success.

Sustainability is defined as “meeting the needs of the present without compromising the ability of future generations to meet their own needs”. Commonly, it is evaluated using three basic dimensions: social, economic, and environmental. Ideally, the best sustainability situation would be attained when maximizing the benefits in the economic, social, and environmental dimensions, but there is a natural conflict among these three dimensions. Here, we study the sustainability performance of European Countries by applying a methodology that combines both multiple criteria decision-making techniques and econometrics. Using individual sustainability development indicators available in the EUROSTAT database (from 2010-2019), we first build composite indicators to assess the economic, social, and environmental dimensions of the territories, using the Multiple Reference Point Weak and Strong Composite Indicators methodology. Secondly, we perform an econometric analysis to regress the composite indicators only considering individual indicators that are controllable by policy makers. The purpose is to get insights into the impact that a modification of these controllable individual indicators would have on the overall sustainable development of the territories. Finally, we focus on Spain, whose sustainability situation can be improved. However, to make a decision about how to improve its situation, further information is needed in order to know the extent of the possible improvement, the trade-offs existing among the dimensions, and how this improvement could be attained. Therefore, we build a multiobjetive optimization problem based on the econometric analysis to identify the most desired compromise among the three dimensions to enhance the sustainability situation of Spain. Using preference-based multiobjective optimization techniques, we solve the problem with different preferences to analyse the possible improvements that could be achieved under different scenarios. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.

A utilização de indicadores para gerenciamento e manejo das águas pluviais urbanas pelos gestores municipais brasileiros tem se difundido nos últimos anos. No entanto, são observadas elevada subjetividade e incertezas associadas à elaboração dos indicadores e índices, interpretação e aplicação dos resultados pelos tomadores de decisão. Estudos que apontem alternativas para a redução da subjetividade e de incertezas associadas à percepção e interpretação dos resultados dos indicadores para gerenciamento de águas pluviais urbanas pelos tomadores de decisão são escassos. Este trabalho tem por objetivo principal estruturar uma ferramenta de suporte para o gerenciamento das águas pluviais urbanas baseada em um conjunto de indicadores, problemas e medidas mitigadoras, com vistas a fomentar a tomada de decisão por parte dos gestores públicos municipais. Para atingir o objetivo foram identificados os problemas e medidas mitigadoras relacionadas ao gerenciamento e manejo de águas pluviais urbanas, estruturado um conjunto de indicadores simples e indicadores compostos, relacionados os indicadores simples e os problemas, relacionados os problemas e possíveis medidas mitigadoras, de forma sistematizada e, por fim, realizada a validação. A validação foi realizada por meio da comparação entre os problemas e medidas mitigadoras resultantes da aplicação dos indicadores em municípios piloto e problemas e medidas mitigadoras indicadas nos Planos Municipais desses municípios. A ferramenta foi aplicada em oito municípios pilotos, localizados na região Sul do Brasil, com contingente populacional de até cem mil habitantes. Com base nos 59 problemas relacionados ao gerenciamento e manejo das águas pluviais urbanas identificados, foi estruturado um conjunto de 42 indicadores simples que, posteriormente, foram agregados em cinco indicadores compostos. O conjunto de indicadores simples desenvolvido demonstrou ser capaz de identificar 88,14% dos problemas listados relacionados ao gerenciamento e manejo de águas pluviais urbanas. Em relação aos indicadores, após análise de sensibilidade, o método de Processo de Análise Hierárquica (PAH) resultou como o mais adequado para ponderação de indicadores compostos. Quando sistematizados os problemas com as 30 medidas mitigadoras identificadas, a associação demonstrou ser abrangente e com dificuldades de apontar medidas específicas para resolver os problemas mais impactantes. O desenvolvimento, aplicação e análise de indicadores simples e compostos indicaram que indicadores simples são mais adequados para o gerenciamento e manejo das águas pluviais para fins de suporte à gestão municipal, uma vez que possibilitam identificar com maior clareza e facilidade quais itens carecem de maior atenção, de forma mais específica e de mais fácil entendimento. The use of indicators for the management of urban stormwater by Brazilian municipalities managers has become widespread in recent years. However, high subjectivity and uncertainties associated with the elaboration of indicators and indexes, interpretation and application of results by decision makers are observed. Studies that point to alternatives to reduce subjectivity and uncertainties associated with the perception and interpretation of the results of indicators for urban stormwater management by decision makers are scarce. The main objective of this work is to structure a support tool for the management of urban stormwater based on a set of indicators, problems and mitigating measures, in order to encourage decision-making by municipal public managers. To achieve the objective, problems and mitigating measures related to the management of urban stormwater were identified, structured a set of simple indicators and composite indicators, related to simple indicators and problems, related to problems and possible mitigating measures, in a systematic way and, finally, validation was performed. The validation was performed by comparing the problems and mitigating measures resulting from the application of indicators in pilot municipalities and the problems and mitigating measures indicated in the Municipal Plans of these municipalities. The tool was applied in eight pilot municipalities, located in the southern region of Brazil, with a population of up to 100,000 inhabitants. Based on the 59 problems related to the management of urban stormwater identified, a set of 42 simple indicators was structured, which were later aggregated into five composite indicators. The set of simple indicators developed proved to be able to identify 88.14% of the listed problems related to the management of urban stormwater. Regarding the indicators, after a sensitivity analysis, the Hierarchical Analysis Process (PAH) method proved to be the most suitable for weighting composite indicators. When the problems with the 30 mitigating measures identified were systematized, the association proved to be embracing and with difficulties in pointing out specific measures to solve the most impacting problems. The development, application and analysis of simple and composite indicators have indicated that simple indicators are more appropriate for the management of stormwater for the purpose of supporting municipal management, since they make it possible to identify with greater clarity and ease which items need more attention, in a more specific and easier way to understand.

Conventional local public health planning and monitoring are insufficiently addressing the conjugated impact of urban development change and climate change in the future. The existing checklist and index often ignore the spatial-network interaction determining urban public health services in forward-looking aspects. This study offers and demonstrates a climate-resilient operationalization framework for urban public health services considering the interaction between urban development change and climate change across scales. A combination of collaborative scenario planning and tailor-made composite indicators were applied based on the IPCC Fifth Assessment Report (AR5)’s climate risk concept to adhere to local realities and diverse sets of scenarios. The framework was contested in a medium-sized city with a universal health care coverage setting, Khon Kaen city, Thailand. The results show that the coupling of collaborative scenario planning and composite indicators allows local public health care to operationalize their potential impact and climate-resilient targets in the future(s) in multiple service operation aspects. The scenarios assessment outcomes prove that although public health devotion can be fail-safe, achieving climate-resilient targets requires sectoral integration with urban development and health determining domains. Further exploration and disputation of the framework with a wider scale and diversified settings are recommended to enhance their robustness and universality.

This paper studies deprivation dynamics at the subnational level, introducing a Local Multidimensional Poverty Index (“LMPI”), and focusing on multidimensional poverty in Ecuador and Uruguay between the last two available censuses, 1990–2010 and 1996–2011, respectively. As a first step, we construct the “LMPI” at the municipal level using microdata from both counties. Subsequently, we explore spatial and temporal dynamics through a set of tools such as thesalter graph, Moran’s I, Moran scatterplot, and spatial transition matrix. The results indicate that compared to Ecuador, Uruguay was initially in a better position in terms of the “LMPI”. However, Ecuador achieved a generalized reduction of the “LMPI” during the period of analysis, reaching levels close to that of Uruguay. Nevertheless, spatial persistence in the “LMPI” is observed., Este trabajo estudia la dinámica de la “deprivation” a nivel subnacional por medio de un indicador llamado Índice de Pobreza Multidimensional (“LMPI”), que cubre la pobreza multidimensional en Ecuador y Uruguay entre los dos censos 1990-2010 y 1996-2011. Primero, construimos el “LMP” a nivel municipal para-ambos países usando microdatos. Después, exploramos la dinámica espacial y temporal usando “salter graph”, test de Moran y “scatter plot” de Moran y la matriz de transición espacial. Resultados muestran que Uruguay está en mejor posición que Ecuador inicialmente, sin embargo, Ecuador mejoro significativamente durante el periodo de estudio. Ambos países presentan persistencias espaciales en el “LMPI”.

In our knowledge society, where universities are key players, the assessment of higher education institutions should meet the new demands of the present complex environment. This calls for the use of techniques that are able to manage this complexity. In this paper, we propose a novel combination of methodologies, jointly using a multi-criteria reference point scheme and the data envelopment analysis (DEA) for the assessment of universities. This combination allows us to take into account all the aspects regarded as relevant to assess university performance, and use them as outputs in the efficiency analysis. Our findings highlight the convenience to assess the university performance by using both compensatory and non-compensatory schemes. This way, the information provided allows to detect the actions needed to improve the performances of the universities, rather than just giving an overall performance measure. Furthermore, combining the use of composite indicators with the DEA analysis provides a more complete picture of the institutions assessed, allowing universities to check their efficiency and to detect their weaknesses and strengths accordingly. The approach is illustrated using data of 47 Spanish public universities for the academic year, 2016–2017. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Funding for open access charge: Universidad de Málaga / CBUA.

We employ the ‘benefit of the doubt’ approach rooted in non-parametric techniques to evaluate the entrepreneurial ecosystem of 71 countries for the period 2016. By scrutinizing the relative efficiency of countries’ entrepreneurial ecosystems, the proposed analysis of composite indicators allows the computation of endogenous (country-specific) weights that can be used for developing more informed policy making. The results show that countries prioritize different aspects of their national system of entrepreneurship which confirms that, contrary to homogeneous prescription, tailor-made policy is necessary if the objective is to optimize the resources deployed to enhance the countries’ entrepreneurial ecosystem. The findings of the empirical application reveal significant improvements in the quality of the entrepreneurial ecosystem can be realized by targeting the policy priorities of the local entrepreneurship system identified by the ‘benefit of the doubt’ weights. By analyzing the variation in economic and entrepreneurship outcomes over the seven-year period centered on the study year (period 2013–2019), we found a significant positive correlation between quality improvements in the entrepreneurial ecosystem and venture capital investments.

In the analysis of well-being, according to the “beyond GDP” approach, it is important to measure well-being and how it is distributed across territories and among the different groups that make up society. This paper focuses on job quality, which is an important aspect of life that contributes to well-being. More precisely, the social environment at workplace is measured by a composite indicator, and its distribution across European countries is investigated. A comparison of different aggregation approaches for the construction of the composite indicator is provided, and the measure is examined by means of influence and robustness analyses.

Il cambiamento climatico e uno dei temi più urgenti nel dibattito pubblico, incluso nell’Agenda 2030 per lo sviluppo sostenibile adottata dalle Nazioni Unite, a causa dei rischi che può comportare per la vita umana. Esso rappresenta un fenomeno multidimensionale definito da diverse dimensioni, ognuna delle quali misurata da un insieme di variabili direttamente osservabili, che riguardano le emissioni di gas serra, le cause del cambiamento climatico, le sue conseguenze per gli umani e la natura e gli sforzi messi in campo dal genere umano per evitare e adattarsi a tali conseguenze. In questo lavoro, introduciamo un nuovo approccio basato su modello per studiare questo fenomeno e le sue diverse caratterizzazioni nei paesi europei. La proposta metodologica ha l’obiettivo di costruire un sistema di indicatori compositi per identificare i principali fattori che determinano il cambiamento climatico e fornire di conseguenza indicazioni per attuare politiche nel contesto europeo volte a combattere il cambiamento climatico. Nowadays climate change is one of the most urgent topics in public de bate, also included into the 2030 Agenda for Sustainable Development adopted by the United Nations, because of its risks for human life. It represents a multidimensional phenomenon defined by different dimensions that pertain to greenhouse as emissions, human causes of climate change, impacts on humans and natural systems, and efforts of human to avoid and adapt to the consequences, each of which is described by a set of variables directly observed. In this paper, we introduce a new model-based approach to study this phenomenon and its different characterization in European countries. The proposal aims at building a system of composite indicators in order to understand the main determinants of this phenomenon, and to provide guidelines for policy decisions to combat climate change in the European Union framework.

Asia and Europe have made connectivity between people, businesses and institutions a top political priority in the frame of the Asia-Europe Meeting (ASEM) intergovernmental cooperation forum. In the ASEM context, policy leaders agreed that improving connectivity between countries should contribute to achieve the Sustainable Development Goals. Connectivity is a complex concept involving multiple dimensions. Yet in order to provide clear data-driven evidence to support policymaking on Asia-Europe sustainable connectivity, this concept calls for a measurement framework. The mismatch between the politically adopted definition of sustainable connectivity and existing metrics, led to the development of the two indexes described in this paper. Taken together, they help to explore and understand the relationship between connectivity and sustainability. The results suggest that connectivity and sustainability policy agendas have the potential to mutually reinforce one another. Higher values in connectivity are strongly associated with higher values in the social dimension of sustainability. There are evident gaps between European and Asian nations in terms of connectivity and sustainability. However, both continents are underpinned by the common challenge of reducing the environmental impacts of connectivity without neglecting economic/financial sustainability aspects, while at the same time ensuring that benefits will accrue to society at large.

Well-being is a multidimensional concept that cannot be described using a single indicator. By the synthesis of different dimensions it is possible to obtain composite indicators (CIs). Principal Components Analysis (PCA) is one of the most popular multivariate statistical techniques used building CIs. However, the fact that PCA does not take into account the spatial dimension of the phenomenon makes it unsuitable for studying the well-being of urban areas. In this paper, we propose to use Spatial Principal Component Analysis (SPCA) for measuring well-being. The SPCA technique provides principal component scores that summarize both the spatial variability and the spatial autocorrelation structure among the statistical units. In this paper, the SPCA is used to construct well-being CIs for the Italian provinces.

This paper proposes a new composite indicator for the assessment of the implementation of Aichi Targets (ATCI) following a benchmarking approach simultaneously considering performance and drawbacks. ATCI is based on 37 indicators related to the 5 Aichi Strategic Goals and its aggregated scores and ranks are calculated using three BoD-DEA models to integrate performance and drawback scores for Targets. ATCI was applied to 21 European countries and its scores were mapped and classified into four groups according to their location in performance-drawbacks space: S1) Caution, S2) Excellence, S3) Fragility and S4) Catching up. Countries in S1 and S3 are recommended to mitigate drawbacks to facilitate the implementation of the Aichi Targets. Results showed that 52% of the countries (Italy, Hungary, Greece, Czechia, Belgium, Poland, Portugal, Spain, Latvia, Slovenia and Slovakia) should pay urgent attention to the Aichi Targets since they show the highest limitations. Based on limitations, two country profiles were identified: countries with high economic development, high population density and corresponding impacts on biodiversity, and countries of medium/low economic development, weak governance and few drawbacks related to human impacts on the environment. These impacts, however, can be aggravated if their economic situation improves and institutional constraints are not addressed. info:eu-repo/semantics/publishedVersion

The analysis and measurement of poverty is a crucial and unsolved issue in the field of social science. This work aims to measure poverty as a multidimensional notion using a new composite indicator. However, subjective choices as different weighting schemes on the indicator's construction could affect their interpretation and policy. It is necessary to consider the possible weighting configurations randomly to overcome this problem, and it is proposed in this work as interval-based composite indicators based on the results. This work aims to obtain robust and reliable measures based on a relevant conceptual model of poverty we have identified, considering various factors as weightings. Methodologically speaking, it is proposed an original procedure for measuring poverty in which it is computed a different composite indicator for each simulated weighting scheme of the identified factors. The weighting scheme in the Monte-Carlo simulation randomly creates an interval-based composite indicator based on the results. The different intervals are compared using different criteria (upper bound, center, and lower bound), and various rankings help analyze extreme scenarios and policy hypotheses. Critical situations are identified in Sicilia, Calabria, Campania and Puglia. The results demonstrate a relevant and consistent indicator measurement and the shadow sector's relevant impact on the final measures

High profile composite indicators seeking to summarise aspects of the quality of healthcare organisations often have important impacts: they may be reputationally consequential for healthcare organisations, may affect prioritisation for inspection or action by regulators, and may be responsible for effecting changes in the way services are delivered. Use of composite indicators, which include examples such as the Hospital Compare Star Ratings in the US and the Quality and Outcomes Framework in the UK, is proliferating in healthcare. But to date there is limited understand of how such indicators should be designed and reported. This thesis seeks to address this gap, characterising relevant challenges in the design of composite indicators and exploring their reporting might be improved. My examination of composite indicators is formed from two principal components. The first comprises two quantitative studies, which are conceptually linked. These studies investigate the sensitivity of the ratings and rankings of hospitals to the exact technical methods by which composite indicators are produced. I show that composite indicators can be highly sensitive to technical decisions, and that different composite indicators are affected differently by these, rarely examined, technical issues. The second component is a qualitative interview study, for which I interviewed experts in performance measurement about the process of developing a composite indicator. This study highlighted two crucial aspects of the development of composite indicators. First, the purpose of a composite indicator needs to drive every aspect of technical decisions relating to their specification. Second, the development process should be iterative: developers must be willing and able to revise the purpose of the indicator and restart the development process if it subsequently becomes apparent that the composite indicator does not match the purpose for which it is being developed. The results of the quantitative and qualitative studies in this thesis revealed a number of challenges for the design of composite indicators, but also helped to identify possible ways for improving their design. The qualitative study catalogues important decision points which could be used as a framework for design choices for composite indicators. In combination with the results of the quantitative studies, which inter alia show the usefulness of applications of Monte Carlo sensitivity analysis as part of the development and evaluation of composites, this catalogue of decisions holds promise for identifying and addressing problems with composite indicator in the design stage and for offering critiques of existing indicators. Together these considerations point toward designing-in an iterative approach to processes used in the development of composite indicators, in which sensitivity analysis is used to assess the implications of each design decision. Finally, my results lay the groundwork for future development of a reporting guideline for the development and reporting of composite indicators of healthcare quality., This research project was funded by a combination of Mary Dixon-Woods��� Wellcome Trust Investigator award (grant number WT097899) , the Health Foundation���s award to The Healthcare Improvement Studies (THIS) Institute at the University of Cambridge and Georgios Lyratzopoulos���s Departmental discretionary fund. The Health Foundation is an independent charity committed to bringing about better health and health care for people in the UK.

This research presents a framework through which a new Higher Education Access and Deprivation (HEAD) composite index was created to assist UK universities in efficiently recruiting and supporting students from areas with traditionally low engagement rates in higher education. The index was designed to be easily adaptable by university staff to suit their own work priorities and/or an institution’s strategic requirements by utilising open socio-demographic data and construction techniques that require minimal technical statistical skills. Although Cornwall was used as the study area in this research, this index has been designed such that it can be readily applied elsewhere. Two differently weighted models were created using the framework – one with equal weights and the other based on the frequency the constituent indicators appeared in the reviewed academic literature. Both models were mapped across Cornwall, identifying areas of deprivation at a finer resolution than under the current widely used Participation of Local Areas (POLAR) methodology. The weighted model performed marginally better than both the equal weighted model and the current POLAR methodology when validated against external data, and additionally it worked well in both rural and urban environments leading to it being selected as the new HEAD index. The HEAD index maps smaller scale areas of deprivation than previously available, and by enabling users to investigate the underlying socio-demographic characteristics of an area, it also allows universities to create interventions, support, and policies that best targets the students they aim to recruit and teach.

Natural resources are gradually coming under continuous and increasing pressure due to anthropogenic interventions and climate variabilities. The result of these pressures is reflected in the sustainability of natural resources. Significant scientific efforts during the recent years focus on mitigating the effects of these pressures and on increasing the sustainability of natural resources. Hence, there is a need to develop specific indices and indicators that will reveal the areas having the highest risks. The Water and Land Resources Degradation Index (WLDI) was developed for this purpose. WLDI consists of eleven indicators and its outcome results from the spatiotemporal performance of these indicators. The WLDI is based on the Standardized Drought Vulnerability Index (SDVI) and the Environmentally Sensitive Areas Index (ESAI). The WLDI is applied for the period from October 1983 to September 1996, considering Greece as a study area. The results of the application of this index reveal the areas with the highest risks, especially in the agricultural sector, with less than the needed water quantities due to extensive periods of droughts. This index could be used by scientists, but also by policy makers, to better and more sustainably manage environmental pressures.

Research background: Composite indicators are commonly used as an approximation tool to measure economic development, the standard of living, competitiveness, fairness, effectiveness, and many others being willingly implemented into many different research disciplines. However, it seems that in most cases, the variable weighting procedure is avoided or erroneous since, in most cases, the so-called ‘weights by belief’ are applied. As research show, it can be frequently observed that weights do not equal importance in composite indicators. As a result, biased rankings or grouping of objects are obtained. Purpose of the article: The primary purpose of this article is to optimise and improve the Human Development Index, which is the most commonly used composite indicator to rank countries in terms of their socio-economic development. The optimisation will be done by re-scaling the current weights, so they will express the real impact of every single component taken into consideration during HDI’s calculation process. Methods: In order to achieve the purpose mentioned above, the sensitivity analysis tools (mainly the first-order sensitivity index) were used to determine the appropriate weights in the Human Development Index. In the HDI’s resilience evaluation process, the Monte Carlo simulations and full-Bayesian Gaussian processes were applied. Based on the adjusted weights, a new ranking of countries was established and compiled with the initial ranking using, among others, Kendall tau correlation coefficient. Findings & Value added: Based on the data published by UNDP for 2017, it has been shown that the Human Development Index is built incorrectly by putting equal weights for all of its components. The weights proposed by the sensitivity analysis better reflect the actual contribution of individual factors to HDI variability. Re-scaled Human Development Index constructed based on proposed weights allow for better differentiation of countries due to their socio-economic development.

The 2030 Agenda for Sustainable Development (2015) can be considered the synthesis of a debate, which sets the sustainable development as a priority for the International Community. The achievement of the sustainable development goals has made necessary to develop a system of indicators. Indicators and data should be collected and reported sub-nationally, giving attention to the territory. This is a necessity even more for Italy, a country historically characterized by strong regional specificities and differences, which find their radicalization in the so-called North–South gap. In this paper, we want to examine and monitor the Italian situation as to the achievement of the SDGs, based on the analysis of the Regions, to highlight potential differences or territorial homogeneity. In particular, we want to emphasize not only how there is actually a gap between the North and the South of the country, but also how the synthesis tends often to be representative of situations profoundly different from each other, as a result of different values in the basic indicators, or similar situations between them. Due to the difficulty of reporting on a paper a detailed analysis of all 17 sustainable development goals, we focus only on the first three goals one. In particular, for each goal we select indicators all useful for the analysis of regional realities and appropriate some for monitoring the present condition, others for providing information on the future one (risk). The research methodology is to use the Adjusted Mazziotta–Pareto Index for creating a composite index for each goal considered. This analysis is preceded by an exploratory analysis of the basic indicators over time through the use of within and between correlations and the average PCA.

The object of research is a system of processes for determining the level of a country's development in the context of a sustainable development model. One of the most problematic places is the mistakenly constructed or incorrectly interpreted composite indicators, which can lead to simplified analytical or political conclusions. A study is conducted on the use of composite indicators as tools for identifying development trends in the countries of the European Union, which makes it possible to determine the advantages and disadvantages of their use. And also to establish common and distinctive features with the indicators specified in the Sustainable Development Strategy of the country until 2030. The hierarchical system of composite indicators is built with their subsequent verification for completeness and dimensionality in accordance with the requirements of the selected theoretical and methodological methods of analysis. An interconnected sequence of steps is identified to determine the integral index for each of the studied countries with a view to rating them on the basis of the system of obtained composite indicators and their weight. Based on the obtained eigenvalues of the centered-normalized main components for each of the studied countries and certain substantive interpretations of the main components, a pair-wise comparative analysis is conducted within the studied set of countries. And also carried out a cluster analysis, which allowsto identify groups of countries that are close in value to the integral index. The ranking of the studied countries is carried out on the basis of the calculation of individual integral development indicators, calculated as the sum of its integral indicators for two subsets – stimulant indicators and disincentive indicators. The study of 33 countries allowsto identify the place of Ukraine in the direction of the implementation of individual goals of its development based on a system of composite indicators. And also to assess the relative remoteness of Ukraine both from states that are close in their socio-economic development, and from highly developed European countries.

In the paper, two composite indicators – the indices of material and social deprivation – are analyzed based on the Survey of Health, Ageing and Retirement in Europe exploring the population aged 50 and over. A finite normal mixture model for the social deprivation index and a finite mixture of Bernoulli and normal distributions are used to model the distribution of the indices of deprivation for the Czech Republic in 2013. Applying a logistic regression model, the parameter of Bernoulli distribution is supposed to be dependent on explanatory variables. In terms of material deprivation, the situation in the Czech Republic is comparable to other European countries, the social deprivation index, showing, however, higher values.