How Useful are Computable General Equilibrium Models for Sustainability Impact Assessment

Computable general equilibrium (CGE) modelling represents a powerful tool for hypothesising possible sustainability outcomes that might be triggered with the implementation of policy proposals. Nevertheless, CGE modelling is based on several tight general equilibrium and neoclassical micro-economic theoretical assumptions that make their application to the assessment of all three pillars of sustainability questionable. Although some of these assumptions have been relaxed in recent and more advanced CGE models, further research needs to be undertaken in order to bring model specifications closer to realistic behavioural relationships. CGE models also tend to focus on alternative equilibrium outcomes and rarely deal with the adjustment process or regulation measures needed to realistically bring the economy into the desired new equilibrium stance. Moreover, CGE models inherently face severe rigidities when attempting to deal with environmental and social effects. However, some authors have argued that CGE modelling may provide a suitable backbone for all three dimensions of Sustainability Impact Assessment (SIA). The paper takes a critical stand and supports the view that though CGE models may provide some useful information on individual, particularly economic, impact aspects of policy reforms, it may be inappropriate and even misleading to rely extensively on their use in SIAs.Environmental Economics and Policy,

Automated user modeling for personalized digital libraries

Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information

Modelling chemotaxis of microswimmers: from individual to collective behavior

We discuss recent progress in the theoretical description of chemotaxis by coupling the diffusion equation of a chemical species to equations describing the motion of sensing microorganisms. In particular, we discuss models for autochemotaxis of a single microorganism which senses its own secretion leading to phenomena such as self-localization and self-avoidance. For two heterogeneous particles, chemotactic coupling can lead to predator-prey behavior including chase and escape phenomena, and to the formation of active molecules, where motility spontaneously emerges when the particles approach each other. We close this review with some remarks on the collective behavior of many particles where chemotactic coupling induces patterns involving clusters, spirals or traveling waves.Comment: to appear as a contribution to the book "Chemical kinetics beyond the textbook

Cost of capital in an international context: Institutional distance, quality, and dynamics

Cost of debt is a key cognitive anchor for managerial decisions and an important determinant of firm profitability. We extend international management research by analyzing the effects of institutional distance, institutional quality, and their dynamics on the cost of debt in the context of foreign direct investments (FDI). We test our conceptual model on a sample of companies making 3,764 greenfield foreign direct investments from developed into less developed markets. Using hierarchical linear modelling, we show that the financial consequences of internationalizing into countries with weak institutions depend on both the institutional distance between countries, as well as their institutional quality. Furthermore, we find that recent changes in institutional quality form expectations about future development and ultimately influence post investment financing costs

Temporal Cross-Media Retrieval with Soft-Smoothing

Multimedia information have strong temporal correlations that shape the way modalities co-occur over time. In this paper we study the dynamic nature of multimedia and social-media information, where the temporal dimension emerges as a strong source of evidence for learning the temporal correlations across visual and textual modalities. So far, cross-media retrieval models, explored the correlations between different modalities (e.g. text and image) to learn a common subspace, in which semantically similar instances lie in the same neighbourhood. Building on such knowledge, we propose a novel temporal cross-media neural architecture, that departs from standard cross-media methods, by explicitly accounting for the temporal dimension through temporal subspace learning. The model is softly-constrained with temporal and inter-modality constraints that guide the new subspace learning task by favouring temporal correlations between semantically similar and temporally close instances. Experiments on three distinct datasets show that accounting for time turns out to be important for cross-media retrieval. Namely, the proposed method outperforms a set of baselines on the task of temporal cross-media retrieval, demonstrating its effectiveness for performing temporal subspace learning.Comment: To appear in ACM MM 201

Embodied Robot Models for Interdisciplinary Emotion Research

Due to their complex nature, emotions cannot be properly understood from the perspective of a single discipline. In this paper, I discuss how the use of robots as models is beneficial for interdisciplinary emotion research. Addressing this issue through the lens of my own research, I focus on a critical analysis of embodied robots models of different aspects of emotion, relate them to theories in psychology and neuroscience, and provide representative examples. I discuss concrete ways in which embodied robot models can be used to carry out interdisciplinary emotion research, assessing their contributions: as hypothetical models, and as operational models of specific emotional phenomena, of general emotion principles, and of specific emotion ``dimensions''. I conclude by discussing the advantages of using embodied robot models over other models.Peer reviewe

Agent-based modelling - A methodology for the analysis of qualitative development processes

The tremendous development of an easy access to computational power within the last 30 years has led to the widespread use of numerical approaches in almost all scientific disciplines. The first generation of simulation models was rather focused on stylized empirical phenomena. With agent-based modelling, however, the trade-off between simplicity in modelling and taking into account the complexity of the socio-economic reality has been enhanced to a large extent. This paper serves as a basic instruction on how to model qualitative change using an agent-based modelling procedure. The necessity to focus on qualitative change is discussed, agent-based modelling is explained and finally an example is given to show the basic simplicity in modelling.agent-based modelling, methodology, evolutionary economics, qualitative change