The Spread of Feed-In Tariff Legislation in Europe: A Diffusion of Innovation Study

Environmental policy has become increasingly important as states attempt to curb negative environmental impacts and adopt a more a sustainable economic approach that relies on alternative energies instead of fossil fuels. Many countries have adopted policies to foster the production of renewable energy, chief among them feed-in tariffs (FiT) and renewable portfolio standards (RPS). Extensive study as to the pros and cons of both of these approaches has been done using a multitude of methodologies, but little research exists that examines why states choose one approach over the other. This paper seeks to address this gap in the existing research by exploring the following question: why have some European states adopted FiT legislation and others not? I test the primary model for state policy adoption - the integrated diffusion of innovation (DOI) model - in order to determine the extent to which this theoretical approach applies in an EU context. I use event history analysis to examine FiT legislation adoption in order to identify patterns and traits of those most likely to employ FiT. Using existing DOI literature as a guide, I test several internal determinants - problem severity, energy dependency, wealth, ideology, and interest group pressure - as well as spatial diffusion to understand the determinants of FiT legislation adoption. My results suggest that regional effects strongly influence FiT diffusion in Europe, while internal determinants are less likely to predict policy-making. To conclude, I offer suggestions for future research in this area

Business process affordances through the lens of activity theory

Business process designers are increasingly being challenged to develop processes that are not only useful in achieving business objectives but also accepted by the process participants and followed in the work place. Those objectives can only be achieved when both the business and the social/cultural aspects of the specific business environment are taken into account. Humans are not unaided individuals separated from a social group and from supporting artefacts but they are complemented by the environment in which they live in. This paper presents a novel framework for the design of business processes based on the application of activity system, providing a comprehensive framework of humans acting in the world, and the theory of affordances, representing action opportunities offered by the environment. The contribution of this paper is two-fold. First, it provides a theoretical contribution to affordance studies by offering a conceptual model that consolidates new developments in the concept, post Gibson. Second, it introduces a new framework (Activity/Affordance Framework - AAF) to aid the design of business processes. Finally, a case study is used to illustrate the utility of the framework in design practice.<br /

The Glass House

A collaboration of Architects and Architectural Engineers to design a unique depiction of the 50x50 Glass House with Miesian Architectural appeal

Teaching Data Analysis with Interactive Visual Narratives

Data analysis is a major part of business analytics (BA), which refers to the skills, methods, and technologies that enable managers to make swift, quality decisions based on large amounts of data. BA has become a major component of Information Systems (IS) courses all over the world. The challenge for IS educators is to teach data analysis – the foundational BA concepts – to early years undergraduate students who commonly have an aversion to statistics as well as poor problem-solving skills. This article describes the development and evaluation of a learning intervention, Interactive Visual Narratives (IVN), which is informed by previous research into the efficacy of interaction, visualization, and narratives across a variety of learning contexts. The results suggest that a combination of interactive visualizations and narratives can improve the acquisition of data analysis knowledge, facilitate essential skills in problem analysis and the application of BA solutions, and enhance student engagement. These findings provide useful insights for improving students’ learning outcomes and engagement

Influence of Social Class Perceptions on Attributions among Mental Health Practitioners

Objective: A vignette-based study assessed the influence of social class attributions toward a hypothetical client\u27s difficulty. Method: 188 licensed mental health professionals who were recruited through professional listservs completed an online survey after reviewing one of two versions of a vignette describing a hypothetical client that varied based on social class cues. Results: As expected, this sample of licensed mental health practitioners detected social class differences based on the descriptors of the hypothetical client across the two vignettes. These perceived social class differences, however, did not impact participants\u27 attributions toward the client for causing or solving her problems, level of Global Assessment of Functioning score ascribed to the client, or willingness to work with the client. Conclusions: There was no evidence that participants differentially ascribed attributions based on social class. Implications and directions for future research are provided

Large-scale genomics unveils the genetic architecture of psychiatric disorders

Family study results are consistent with genetic effects making substantial contributions to risk of psychiatric disorders such as schizophrenia, yet robust identification of specific genetic variants that explain variation in population risk had been disappointing until the advent of technologies that assay the entire genome in large samples. We highlight recent progress that has led to a better understanding of the number of risk variants in the population and the interaction of allele frequency and effect size. The emerging genetic architecture implies a large number of contributing loci (that is, a high genome-wide mutational target) and suggests that genetic risk of psychiatric disorders involves the combined effects of many common variants of small effect, as well as rare and de novo variants of large effect. The capture of a substantial proportion of genetic risk facilitates new study designs to investigate the combined effects of genes and the environment

Familial occurrence of chronic respiratory disease and familial resemblance in ventilatory capacity

One of the main hypotheses of the Tecumseh Study is that no matter whether genetic, constitutional or environmental factors are involved, new cases of disease will occur among family members of affected persons. During the second cycle of examinations, 82 per cent of the population were examined. Eighty-nine per cent of these 9226 persons had one or most first-degree relatives who was also a member of the study population. We have found that the prevalences of chronic bronchitis, asthma and allergic rhinitis were higher in the offspring when one or both parents were affected than when neither was. Clustering of these conditions also occurred in affected sibships but there was evidence of disease aggregation among spouses only for chronic bronchitis. There were statistically significant correlations of parents' lung function variables with those of their children and these were greater at younger than older ages and when parent and child were of the same sex. Intraclass correlation coefficients of F.E.V.1.0 scores for two-person sibships were statistically significant and varied with sex and age of the sibs. Statistically significant correlations were also found between F.E.V.1.0 scores of spouses but these were appreciably smaller than those between first-degree relatives. The scores of the variables are age- and height-adjusted and therefore, the resemblances in lung function are not merely a reflection of resemblances in height.The patterns of clustering and resemblance vary with disease as well as with age and sex. They implicate both environmental and genetic factors as determinants of chronic bronchitis, asthma, allergic rhinitis and level of ventilatory capacity.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/22086/1/0000510.pd

Scalable adaptive label propagation in Grappa

Nodes of a social graph often represent entities with specific labels, denoting properties such as age-group or gender. Design of algorithms to assign labels to unlabeled nodes by leveraging node-proximity and a-priori labels of seed nodes is of significant interest. A semi-supervised approach to solve this problem is termed ``LPA-Label Propagation Algorithm'' where labels of a subset of nodes are iteratively propagated through the network to infer yet unknown node labels. While LPA for node labelling is extremely fast and simple, it works well only with an assumption of node-homophily -- connected nodes are connected because they must deserve a similar label -- which can often be a misnomer. In this paper we propose a novel algorithm ``Adaptive Label Propagation'' that dynamically adapts to the underlying characteristics of homophily, heterophily, or otherwise, of the connections of the network, and applies suitable label propagation strategies accordingly. Moreover, our adaptive label propagation approach is scalable as demonstrated by its implementation in Grappa, a distributed shared-memory system. Our experiments on social graphs from Facebook, YouTube, Live Journal, Orkut and Netlog demonstrate that our approach not only improves the labelling accuracy but also computes results for millions of users within a few seconds