In a world in which the pace of cities is increasing, prompt access to relevant information is crucial to the understanding and regulation of land use and its evolution in time. In spite of this, characterization and regulation of urban areas remains a complex process, requiring expert human intervention, analysis and judgment. Here we carry out a spatio-temporal fractal analysis of a metropolitan area, based on which we develop a model which generates a cartographic representation and classification of built-up areas, identifying (and even predicting) those areas requiring the most proximate planning and regulation. Furthermore, we show how different types of urban areas identified by the model co-evolve with the city, requiring policy regulation to be flexible and adaptive, acting just in time. The algorithmic implementation of the model is applicable to any built-up area and simple enough to pave the way for the automatic classification of urban areas worldwide.

Electric vehicles (EVs) are a viable alternative to internal combustion engine (ICE) vehicles, with the potential to alleviate the negative externalities stemming from the present ICE-based transportation sector. Notwithstanding, the current prevalence of ICE creates a lock-in state that averts the adoption of alternative and environmental friendly technologies, bringing forth a social dilemma. Here we investigate the feasibility of escaping the present lock-in state by studying possible incentive mechanisms involving, simultaneously, governments (public), companies (private) and consumers (civil). Resorting to Evolutionary Game Theory (EGT), we develop a theoretical model grounded on the strategic interactions between players from the different sectors, whose co-evolving choices influence (and are influenced by) different policies and social incentives. Our findings suggest that i) Public regulation is necessary but not sufficient for guaranteeing full EV adoption; ii) public-civil synergies are essential; iii) demand for EVs preceding supply is most efficient, providing companies with the needed incentives to counterweigh infrastructure investments; and iv) full adoption of EVs requires coordination between the three sectors to emerge, particularly when changes are initiated by the public sector.

Coordination games provide ubiquitous interaction paradigms to frame human behavioral features, such as information transmission, conventions and languages as well as socio-economic processes and institutions. By using a dynamical approach, such as Evolutionary Game Theory (EGT), one is able to follow, in detail, the self-organization process by which a population of individuals coordinates into a given behavior. Real socio-economic scenarios, however, often involve the interaction between multiple co-evolving sectors, with specific options of their own, that call for generalized and more sophisticated mathematical frameworks. In this paper, we explore a general EGT approach to deal with coordination dynamics in which individuals from multiple sectors interact. Starting from a two-sector, consumer/producer scenario, we investigate the effects of including a third co-evolving sector that we call public. We explore the changes in the self-organization process of all sectors, given the feedback that this new sector imparts on the other two.

The recent rise of the civil sector as a main player of socio-political actions, next to public and private sectors, has largely increased the complexity underlying the interplay between different sectors of our society. From urban planning to global governance, analysis of these complex interactions requires new mathematical and computational approaches. Here, we develop a novel framework, grounded on evolutionary game theory, to envisage situations in which each of these sectors is confronted with the dilemma of deciding between maintaining a status quo scenario or shifting towards a new paradigm. We consider multisector conflicts regarding environmentally friendly policies as an example of application, but the framework developed here has a considerably broader scope. We show that the public sector is crucial in initiating the shift, and determine explicitly under which conditions the civil sector—reflecting the emergent reality of civil society organizations playing an active role in modern societies—may influence the decision-making processes accruing to other sectors, while fostering new routes towards a paradigm shift of the society as a whole. Our results are shown to be robust to a wide variety of assumptions and model parametrizations.

Abstract:We explore the relation between the local fractal dimension and the development of the built-up area of the Northern Margin of the Metropolitan Area of Lisbon (NMAL), for the period between 1960 and 2004. To this end we make use of a Generalized Local Spatial Entropy (GLSE) function based on which urban areas can be classified into five different types. Our analysis of NMAL shows how some of the growth dynamics encountered can be linked to the plethora of social, economic and political changes that have taken place in NMAL (and Portugal), during the last 40 years, allowing for the establishment of urban planning measures to either inhibit or promote sprawl in urban areas.

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Is it possible to derive organizing principles of higher education systems from the applicants' choices? Here, we introduce the Higher Education Space (HES) as a way to describe the complex relationship between degree programs. The HES is based on the application of methods from network science to data on the revealed preferences of applicants to the higher education systems of Chile and Portugal. Our work reveals: 1) the existence of a positive assortment of featuressuch as gender balance, application scores, unemployment levels, demand-supply ratio, etc -along the network structure of the HES; 2) that the decaying of the prevalence level of a feature from a focal degree program extends beyond the dyadic relationships captured by the HES; 3) temporal variations in different features do not spillover/propagate throughout the system in the same way; 4) differences in unemployment levels reported among pairs of degree programs are minimized when taking into consideration the connectivity structure of the HES, largely outperforming the differences in matched pairs using traditional similarity measures; and 5) grouping of degree programs based in the network structure of the HES provides an applicant perspective that complements existing classification systems. Our findings support the HES as a multi-dimensional framework that can effectively contribute to the governance of higher education systems. Chilenas 6 The first option is often considered to reveal the true preference of an applicant.

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