33 resultados para Project 2001-010-C : Investment Decision Framework for Infrastructure Assets Management
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OBJECTIVE: To review and update the conceptual framework, indicator content and research priorities of the Organisation for Economic Cooperation and Development's (OECD) Health Care Quality Indicators (HCQI) project, after a decade of collaborative work. DESIGN: A structured assessment was carried out using a modified Delphi approach, followed by a consensus meeting, to assess the suite of HCQI for international comparisons, agree on revisions to the original framework and set priorities for research and development. SETTING: International group of countries participating to OECD projects. PARTICIPANTS: Members of the OECD HCQI expert group. RESULTS: A reference matrix, based on a revised performance framework, was used to map and assess all seventy HCQI routinely calculated by the OECD expert group. A total of 21 indicators were agreed to be excluded, due to the following concerns: (i) relevance, (ii) international comparability, particularly where heterogeneous coding practices might induce bias, (iii) feasibility, when the number of countries able to report was limited and the added value did not justify sustained effort and (iv) actionability, for indicators that were unlikely to improve on the basis of targeted policy interventions. CONCLUSIONS: The revised OECD framework for HCQI represents a new milestone of a long-standing international collaboration among a group of countries committed to building common ground for performance measurement. The expert group believes that the continuation of this work is paramount to provide decision makers with a validated toolbox to directly act on quality improvement strategies.
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ACuteTox is a project within the 6th European Framework Programme which had as one of its goals to develop, optimise and prevalidate a non-animal testing strategy for predicting human acute oral toxicity. In its last 6 months, a challenging exercise was conducted to assess the predictive capacity of the developed testing strategies and final identification of the most promising ones. Thirty-two chemicals were tested blind in the battery of in vitro and in silico methods selected during the first phase of the project. This paper describes the classification approaches studied: single step procedures and two step tiered testing strategies. In summary, four in vitro testing strategies were proposed as best performing in terms of predictive capacity with respect to the European acute oral toxicity classification. In addition, a heuristic testing strategy is suggested that combines the prediction results gained from the neutral red uptake assay performed in 3T3 cells, with information on neurotoxicity alerts identified by the primary rat brain aggregates test method. Octanol-water partition coefficients and in silico prediction of intestinal absorption and blood-brain barrier passage are also considered. This approach allows to reduce the number of chemicals wrongly predicted as not classified (LD50>2000 mg/kg b.w.).
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SUMMARYSpecies distribution models (SDMs) represent nowadays an essential tool in the research fields of ecology and conservation biology. By combining observations of species occurrence or abundance with information on the environmental characteristic of the observation sites, they can provide information on the ecology of species, predict their distributions across the landscape or extrapolate them to other spatial or time frames. The advent of SDMs, supported by geographic information systems (GIS), new developments in statistical models and constantly increasing computational capacities, has revolutionized the way ecologists can comprehend species distributions in their environment. SDMs have brought the tool that allows describing species realized niches across a multivariate environmental space and predict their spatial distribution. Predictions, in the form of probabilistic maps showing the potential distribution of the species, are an irreplaceable mean to inform every single unit of a territory about its biodiversity potential. SDMs and the corresponding spatial predictions can be used to plan conservation actions for particular species, to design field surveys, to assess the risks related to the spread of invasive species, to select reserve locations and design reserve networks, and ultimately, to forecast distributional changes according to scenarios of climate and/or land use change.By assessing the effect of several factors on model performance and on the accuracy of spatial predictions, this thesis aims at improving techniques and data available for distribution modelling and at providing the best possible information to conservation managers to support their decisions and action plans for the conservation of biodiversity in Switzerland and beyond. Several monitoring programs have been put in place from the national to the global scale, and different sources of data now exist and start to be available to researchers who want to model species distribution. However, because of the lack of means, data are often not gathered at an appropriate resolution, are sampled only over limited areas, are not spatially explicit or do not provide a sound biological information. A typical example of this is data on 'habitat' (sensu biota). Even though this is essential information for an effective conservation planning, it often has to be approximated from land use, the closest available information. Moreover, data are often not sampled according to an established sampling design, which can lead to biased samples and consequently to spurious modelling results. Understanding the sources of variability linked to the different phases of the modelling process and their importance is crucial in order to evaluate the final distribution maps that are to be used for conservation purposes.The research presented in this thesis was essentially conducted within the framework of the Landspot Project, a project supported by the Swiss National Science Foundation. The main goal of the project was to assess the possible contribution of pre-modelled 'habitat' units to model the distribution of animal species, in particular butterfly species, across Switzerland. While pursuing this goal, different aspects of data quality, sampling design and modelling process were addressed and improved, and implications for conservation discussed. The main 'habitat' units considered in this thesis are grassland and forest communities of natural and anthropogenic origin as defined in the typology of habitats for Switzerland. These communities are mainly defined at the phytosociological level of the alliance. For the time being, no comprehensive map of such communities is available at the national scale and at fine resolution. As a first step, it was therefore necessary to create distribution models and maps for these communities across Switzerland and thus to gather and collect the necessary data. In order to reach this first objective, several new developments were necessary such as the definition of expert models, the classification of the Swiss territory in environmental domains, the design of an environmentally stratified sampling of the target vegetation units across Switzerland, the development of a database integrating a decision-support system assisting in the classification of the relevés, and the downscaling of the land use/cover data from 100 m to 25 m resolution.The main contributions of this thesis to the discipline of species distribution modelling (SDM) are assembled in four main scientific papers. In the first, published in Journal of Riogeography different issues related to the modelling process itself are investigated. First is assessed the effect of five different stepwise selection methods on model performance, stability and parsimony, using data of the forest inventory of State of Vaud. In the same paper are also assessed: the effect of weighting absences to ensure a prevalence of 0.5 prior to model calibration; the effect of limiting absences beyond the environmental envelope defined by presences; four different methods for incorporating spatial autocorrelation; and finally, the effect of integrating predictor interactions. Results allowed to specifically enhance the GRASP tool (Generalized Regression Analysis and Spatial Predictions) that now incorporates new selection methods and the possibility of dealing with interactions among predictors as well as spatial autocorrelation. The contribution of different sources of remotely sensed information to species distribution models was also assessed. The second paper (to be submitted) explores the combined effects of sample size and data post-stratification on the accuracy of models using data on grassland distribution across Switzerland collected within the framework of the Landspot project and supplemented with other important vegetation databases. For the stratification of the data, different spatial frameworks were compared. In particular, environmental stratification by Swiss Environmental Domains was compared to geographical stratification either by biogeographic regions or political states (cantons). The third paper (to be submitted) assesses the contribution of pre- modelled vegetation communities to the modelling of fauna. It is a two-steps approach that combines the disciplines of community ecology and spatial ecology and integrates their corresponding concepts of habitat. First are modelled vegetation communities per se and then these 'habitat' units are used in order to model animal species habitat. A case study is presented with grassland communities and butterfly species. Different ways of integrating vegetation information in the models of butterfly distribution were also evaluated. Finally, a glimpse to climate change is given in the fourth paper, recently published in Ecological Modelling. This paper proposes a conceptual framework for analysing range shifts, namely a catalogue of the possible patterns of change in the distribution of a species along elevational or other environmental gradients and an improved quantitative methodology to identify and objectively describe these patterns. The methodology was developed using data from the Swiss national common breeding bird survey and the article presents results concerning the observed shifts in the elevational distribution of breeding birds in Switzerland.The overall objective of this thesis is to improve species distribution models as potential inputs for different conservation tools (e.g. red lists, ecological networks, risk assessment of the spread of invasive species, vulnerability assessment in the context of climate change). While no conservation issues or tools are directly tested in this thesis, the importance of the proposed improvements made in species distribution modelling is discussed in the context of the selection of reserve networks.RESUMELes modèles de distribution d'espèces (SDMs) représentent aujourd'hui un outil essentiel dans les domaines de recherche de l'écologie et de la biologie de la conservation. En combinant les observations de la présence des espèces ou de leur abondance avec des informations sur les caractéristiques environnementales des sites d'observation, ces modèles peuvent fournir des informations sur l'écologie des espèces, prédire leur distribution à travers le paysage ou l'extrapoler dans l'espace et le temps. Le déploiement des SDMs, soutenu par les systèmes d'information géographique (SIG), les nouveaux développements dans les modèles statistiques, ainsi que la constante augmentation des capacités de calcul, a révolutionné la façon dont les écologistes peuvent comprendre la distribution des espèces dans leur environnement. Les SDMs ont apporté l'outil qui permet de décrire la niche réalisée des espèces dans un espace environnemental multivarié et prédire leur distribution spatiale. Les prédictions, sous forme de carte probabilistes montrant la distribution potentielle de l'espèce, sont un moyen irremplaçable d'informer chaque unité du territoire de sa biodiversité potentielle. Les SDMs et les prédictions spatiales correspondantes peuvent être utilisés pour planifier des mesures de conservation pour des espèces particulières, pour concevoir des plans d'échantillonnage, pour évaluer les risques liés à la propagation d'espèces envahissantes, pour choisir l'emplacement de réserves et les mettre en réseau, et finalement, pour prévoir les changements de répartition en fonction de scénarios de changement climatique et/ou d'utilisation du sol. En évaluant l'effet de plusieurs facteurs sur la performance des modèles et sur la précision des prédictions spatiales, cette thèse vise à améliorer les techniques et les données disponibles pour la modélisation de la distribution des espèces et à fournir la meilleure information possible aux gestionnaires pour appuyer leurs décisions et leurs plans d'action pour la conservation de la biodiversité en Suisse et au-delà. Plusieurs programmes de surveillance ont été mis en place de l'échelle nationale à l'échelle globale, et différentes sources de données sont désormais disponibles pour les chercheurs qui veulent modéliser la distribution des espèces. Toutefois, en raison du manque de moyens, les données sont souvent collectées à une résolution inappropriée, sont échantillonnées sur des zones limitées, ne sont pas spatialement explicites ou ne fournissent pas une information écologique suffisante. Un exemple typique est fourni par les données sur 'l'habitat' (sensu biota). Même s'il s'agit d'une information essentielle pour des mesures de conservation efficaces, elle est souvent approximée par l'utilisation du sol, l'information qui s'en approche le plus. En outre, les données ne sont souvent pas échantillonnées selon un plan d'échantillonnage établi, ce qui biaise les échantillons et par conséquent les résultats de la modélisation. Comprendre les sources de variabilité liées aux différentes phases du processus de modélisation s'avère crucial afin d'évaluer l'utilisation des cartes de distribution prédites à des fins de conservation.La recherche présentée dans cette thèse a été essentiellement menée dans le cadre du projet Landspot, un projet soutenu par le Fond National Suisse pour la Recherche. L'objectif principal de ce projet était d'évaluer la contribution d'unités 'd'habitat' pré-modélisées pour modéliser la répartition des espèces animales, notamment de papillons, à travers la Suisse. Tout en poursuivant cet objectif, différents aspects touchant à la qualité des données, au plan d'échantillonnage et au processus de modélisation sont abordés et améliorés, et leurs implications pour la conservation des espèces discutées. Les principaux 'habitats' considérés dans cette thèse sont des communautés de prairie et de forêt d'origine naturelle et anthropique telles que définies dans la typologie des habitats de Suisse. Ces communautés sont principalement définies au niveau phytosociologique de l'alliance. Pour l'instant aucune carte de la distribution de ces communautés n'est disponible à l'échelle nationale et à résolution fine. Dans un premier temps, il a donc été nécessaire de créer des modèles de distribution de ces communautés à travers la Suisse et par conséquent de recueillir les données nécessaires. Afin d'atteindre ce premier objectif, plusieurs nouveaux développements ont été nécessaires, tels que la définition de modèles experts, la classification du territoire suisse en domaines environnementaux, la conception d'un échantillonnage environnementalement stratifié des unités de végétation cibles dans toute la Suisse, la création d'une base de données intégrant un système d'aide à la décision pour la classification des relevés, et le « downscaling » des données de couverture du sol de 100 m à 25 m de résolution. Les principales contributions de cette thèse à la discipline de la modélisation de la distribution d'espèces (SDM) sont rassemblées dans quatre articles scientifiques. Dans le premier article, publié dans le Journal of Biogeography, différentes questions liées au processus de modélisation sont étudiées en utilisant les données de l'inventaire forestier de l'Etat de Vaud. Tout d'abord sont évalués les effets de cinq méthodes de sélection pas-à-pas sur la performance, la stabilité et la parcimonie des modèles. Dans le même article sont également évalués: l'effet de la pondération des absences afin d'assurer une prévalence de 0.5 lors de la calibration du modèle; l'effet de limiter les absences au-delà de l'enveloppe définie par les présences; quatre méthodes différentes pour l'intégration de l'autocorrélation spatiale; et enfin, l'effet de l'intégration d'interactions entre facteurs. Les résultats présentés dans cet article ont permis d'améliorer l'outil GRASP qui intègre désonnais de nouvelles méthodes de sélection et la possibilité de traiter les interactions entre variables explicatives, ainsi que l'autocorrélation spatiale. La contribution de différentes sources de données issues de la télédétection a également été évaluée. Le deuxième article (en voie de soumission) explore les effets combinés de la taille de l'échantillon et de la post-stratification sur le la précision des modèles. Les données utilisées ici sont celles concernant la répartition des prairies de Suisse recueillies dans le cadre du projet Landspot et complétées par d'autres sources. Pour la stratification des données, différents cadres spatiaux ont été comparés. En particulier, la stratification environnementale par les domaines environnementaux de Suisse a été comparée à la stratification géographique par les régions biogéographiques ou par les cantons. Le troisième article (en voie de soumission) évalue la contribution de communautés végétales pré-modélisées à la modélisation de la faune. C'est une approche en deux étapes qui combine les disciplines de l'écologie des communautés et de l'écologie spatiale en intégrant leurs concepts de 'habitat' respectifs. Les communautés végétales sont modélisées d'abord, puis ces unités de 'habitat' sont utilisées pour modéliser les espèces animales. Une étude de cas est présentée avec des communautés prairiales et des espèces de papillons. Différentes façons d'intégrer l'information sur la végétation dans les modèles de répartition des papillons sont évaluées. Enfin, un clin d'oeil aux changements climatiques dans le dernier article, publié dans Ecological Modelling. Cet article propose un cadre conceptuel pour l'analyse des changements dans la distribution des espèces qui comprend notamment un catalogue des différentes formes possibles de changement le long d'un gradient d'élévation ou autre gradient environnemental, et une méthode quantitative améliorée pour identifier et décrire ces déplacements. Cette méthodologie a été développée en utilisant des données issues du monitoring des oiseaux nicheurs répandus et l'article présente les résultats concernant les déplacements observés dans la distribution altitudinale des oiseaux nicheurs en Suisse.L'objectif général de cette thèse est d'améliorer les modèles de distribution des espèces en tant que source d'information possible pour les différents outils de conservation (par exemple, listes rouges, réseaux écologiques, évaluation des risques de propagation d'espèces envahissantes, évaluation de la vulnérabilité des espèces dans le contexte de changement climatique). Bien que ces questions de conservation ne soient pas directement testées dans cette thèse, l'importance des améliorations proposées pour la modélisation de la distribution des espèces est discutée à la fin de ce travail dans le contexte de la sélection de réseaux de réserves.
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Executive Summary The first essay of this dissertation investigates whether greater exchange rate uncertainty (i.e., variation over time in the exchange rate) fosters or depresses the foreign investment of multinational firms. In addition to the direct capital financing it supplies, foreign investment can be a source of valuable technology and know-how, which can have substantial positive effects on a host country's economic growth. Thus, it is critically important for policy makers and central bankers, among others, to understand how multinationals base their investment decisions on the characteristics of foreign exchange markets. In this essay, I first develop a theoretical framework to improve our knowledge regarding how the aggregate level of foreign investment responds to exchange rate uncertainty when an economy consists of many firms, each of which is making decisions. The analysis predicts a U-shaped effect of exchange rate uncertainty on the total level of foreign investment of the economy. That is, the effect is negative for low levels of uncertainty and positive for higher levels of uncertainty. This pattern emerges because the relationship between exchange rate volatility and 'the probability of investment is negative for firms with low productivity at home (i.e., firms that find it profitable to invest abroad) and the relationship is positive for firms with high productivity at home (i.e., firms that prefer exporting their product). This finding stands in sharp contrast to predictions in the existing literature that consider a single firm's decision to invest in a unique project. The main contribution of this research is to show that the aggregation over many firms produces a U-shaped pattern between exchange rate uncertainty and the probability of investment. Using data from industrialized countries for the period of 1982-2002, this essay offers a comprehensive empirical analysis that provides evidence in support of the theoretical prediction. In the second essay, I aim to explain the time variation in sovereign credit risk, which captures the risk that a government may be unable to repay its debt. The importance of correctly evaluating such a risk is illustrated by the central role of sovereign debt in previous international lending crises. In addition, sovereign debt is the largest asset class in emerging markets. In this essay, I provide a pricing formula for the evaluation of sovereign credit risk in which the decision to default on sovereign debt is made by the government. The pricing formula explains the variation across time in daily credit spreads - a widely used measure of credit risk - to a degree not offered by existing theoretical and empirical models. I use information on a country's stock market to compute the prevailing sovereign credit spread in that country. The pricing formula explains a substantial fraction of the time variation in daily credit spread changes for Brazil, Mexico, Peru, and Russia for the 1998-2008 period, particularly during the recent subprime crisis. I also show that when a government incentive to default is allowed to depend on current economic conditions, one can best explain the level of credit spreads, especially during the recent period of financial distress. In the third essay, I show that the risk of sovereign default abroad can produce adverse consequences for the U.S. equity market through a decrease in returns and an increase in volatility. The risk of sovereign default, which is no longer limited to emerging economies, has recently become a major concern for financial markets. While sovereign debt plays an increasing role in today's financial environment, the effects of sovereign credit risk on the U.S. financial markets have been largely ignored in the literature. In this essay, I develop a theoretical framework that explores how the risk of sovereign default abroad helps explain the level and the volatility of U.S. equity returns. The intuition for this effect is that negative economic shocks deteriorate the fiscal situation of foreign governments, thereby increasing the risk of a sovereign default that would trigger a local contraction in economic growth. The increased risk of an economic slowdown abroad amplifies the direct effect of these shocks on the level and the volatility of equity returns in the U.S. through two channels. The first channel involves a decrease in the future earnings of U.S. exporters resulting from unfavorable adjustments to the exchange rate. The second channel involves investors' incentives to rebalance their portfolios toward safer assets, which depresses U.S. equity prices. An empirical estimation of the model with monthly data for the 1994-2008 period provides evidence that the risk of sovereign default abroad generates a strong leverage effect during economic downturns, which helps to substantially explain the level and the volatility of U.S. equity returns.
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Although active personal dosemeters (APDs) are not used quite often in hospital environments, the possibility to assess the dose and/or dose rate in real time is particularly interesting in interventional radiology and cardiology (IR/IC) since operators can receive relatively high doses while standing close to the primary radiation field.A study concerning the optimization of the use of APDs in IR/IC was performed in the framework of the ORAMED project, a Collaborative Project (2008-2011) supported by the European Commission within its 7th Framework Program. This paper reports on tests performed with APDs on phantoms using an X-ray facility in a hospital environment and APDs worn by interventionalists during routine practice in different European hospitals.The behaviour of the APDs is more satisfactory in hospitals than in laboratories with respect to the influence of the tube peak high voltage and pulse width, because the APDs are tested in scattered fields with dose equivalent rates generally lower than 1 Sv.h(-1).
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The development of forensic intelligence relies on the expression of suitable models that better represent the contribution of forensic intelligence in relation to the criminal justice system, policing and security. Such models assist in comparing and evaluating methods and new technologies, provide transparency and foster the development of new applications. Interestingly, strong similarities between two separate projects focusing on specific forensic science areas were recently observed. These observations have led to the induction of a general model (Part I) that could guide the use of any forensic science case data in an intelligence perspective. The present article builds upon this general approach by focusing on decisional and organisational issues. The article investigates the comparison process and evaluation system that lay at the heart of the forensic intelligence framework, advocating scientific decision criteria and a structured but flexible and dynamic architecture. These building blocks are crucial and clearly lay within the expertise of forensic scientists. However, it is only part of the problem. Forensic intelligence includes other blocks with their respective interactions, decision points and tensions (e.g. regarding how to guide detection and how to integrate forensic information with other information). Formalising these blocks identifies many questions and potential answers. Addressing these questions is essential for the progress of the discipline. Such a process requires clarifying the role and place of the forensic scientist within the whole process and their relationship to other stakeholders.
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BACKGROUND: Pediatric rheumatic diseases have a significant impact on children's quality of life and family functioning. Disease control and management of the symptoms are important to minimize disability and pain. Specialist clinical nurses play a key role in supporting medical teams, recognizing poor disease control and the need for treatment changes, providing a resource to patients on treatment options and access to additional support and advice, and identifying best practices to achieve optimal outcomes for patients and their families. This highlights the importance of investigating follow-up telenursing (TN) consultations with experienced, specialist clinical nurses in rheumatology to provide this support to children and their families. METHODS/DESIGN: This randomized crossover, experimental longitudinal study will compare the effects of standard care against a novel telenursing consultation on children's and family outcomes. It will examine children below 16 years old, recently diagnosed with inflammatory rheumatic diseases, who attend the pediatric rheumatology outpatient clinic of a tertiary referral hospital in western Switzerland, and one of their parents. The telenursing consultation, at least once a month, by a qualified, experienced, specialist nurse in pediatric rheumatology will consist of providing affective support, health information, and aid to decision-making. Cox's Interaction Model of Client Health Behavior serves as the theoretical framework for this study. The primary outcome measure is satisfaction and this will be assessed using mixed methods (quantitative and qualitative data). Secondary outcome measures include disease activity, quality of life, adherence to treatment, use of the telenursing service, and cost. We plan to enroll 56 children. DISCUSSION: The telenursing consultation is designed to support parents and children/adolescents during the course of the disease with regular follow-up. This project is novel because it is based on a theoretical standardized intervention, yet it allows for individualized care. We expect this trial to confirm the importance of support by a clinical specialist nurse in improving outcomes for children and adolescents with inflammatory rheumatisms. TRIAL REGISTRATION: ClinicalTrial.gov identifier: NCT01511341 (December 1st, 2012).
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One of the key emphases of these three essays is to provide practical managerial insight. However, good practical insight, can only be created by grounding it firmly on theoretical and empirical research. Practical experience-based understanding without theoretical grounding remains tacit and cannot be easily disseminated. Theoretical understanding without links to real life remains sterile. My studies aim to increase the understanding of how radical innovation could be generated at large established firms and how it can have an impact on business performance as most businesses pursue innovation with one prime objective: value creation. My studies focus on large established firms with sales revenue exceeding USD $ 1 billion. Usually large established firms cannot rely on informal ways of management, as these firms tend to be multinational businesses operating with subsidiaries, offices, or production facilities in more than one country. I. Internal and External Determinants of Corporate Venture Capital Investment The goal of this chapter is to focus on CVC as one of the mechanisms available for established firms to source new ideas that can be exploited. We explore the internal and external determinants under which established firms engage in CVC to source new knowledge through investment in startups. We attempt to make scholars and managers aware of the forces that influence CVC activity by providing findings and insights to facilitate the strategic management of CVC. There are research opportunities to further understand the CVC phenomenon. Why do companies engage in CVC? What motivates them to continue "playing the game" and keep their active CVC investment status. The study examines CVC investment activity, and the importance of understanding the influential factors that make a firm decide to engage in CVC. The main question is: How do established firms' CVC programs adapt to changing internal conditions and external environments. Adaptation typically involves learning from exploratory endeavors, which enable companies to transform the ways they compete (Guth & Ginsberg, 1990). Our study extends the current stream of research on CVC. It aims to contribute to the literature by providing an extensive comparison of internal and external determinants leading to CVC investment activity. To our knowledge, this is the first study to examine the influence of internal and external determinants on CVC activity throughout specific expansion and contraction periods determined by structural breaks occurring between 1985 to 2008. Our econometric analysis indicates a strong and significant positive association between CVC activity and R&D, cash flow availability and environmental financial market conditions, as well as a significant negative association between sales growth and the decision to engage into CVC. The analysis of this study reveals that CVC investment is highly volatile, as demonstrated by dramatic fluctuations in CVC investment activity over the past decades. When analyzing the overall cyclical CVC period from 1985 to 2008 the results of our study suggest that CVC activity has a pattern influenced by financial factors such as the level of R&D, free cash flow, lack of sales growth, and external conditions of the economy, with the NASDAQ price index as the most significant variable influencing CVC during this period. II. Contribution of CVC and its Interaction with R&D to Value Creation The second essay takes into account the demands of corporate executives and shareholders regarding business performance and value creation justifications for investments in innovation. Billions of dollars are invested in CVC and R&D. However there is little evidence that CVC and its interaction with R&D create value. Firms operating in dynamic business sectors seek to innovate to create the value demanded by changing market conditions, consumer preferences, and competitive offerings. Consequently, firms operating in such business sectors put a premium on finding new, sustainable and competitive value propositions. CVC and R&D can help them in this challenge. Dushnitsky and Lenox (2006) presented evidence that CVC investment is associated with value creation. However, studies have shown that the most innovative firms do not necessarily benefit from innovation. For instance Oyon (2007) indicated that between 1995 and 2005 the most innovative automotive companies did not obtain adequate rewards for shareholders. The interaction between CVC and R&D has generated much debate in the CVC literature. Some researchers see them as substitutes suggesting that firms have to choose between CVC and R&D (Hellmann, 2002), while others expect them to be complementary (Chesbrough & Tucci, 2004). This study explores the interaction that CVC and R&D have on value creation. This essay examines the impact of CVC and R&D on value creation over sixteen years across six business sectors and different geographical regions. Our findings suggest that the effect of CVC and its interaction with R&D on value creation is positive and significant. In dynamic business sectors technologies rapidly relinquish obsolete, consequently firms operating in such business sectors need to continuously develop new sources of value creation (Eisenhardt & Martin, 2000; Qualls, Olshavsky, & Michaels, 1981). We conclude that in order to impact value creation, firms operating in business sectors such as Engineering & Business Services, and Information Communication & Technology ought to consider CVC as a vital element of their innovation strategy. Moreover, regarding the CVC and R&D interaction effect, our findings suggest that R&D and CVC are complementary to value creation hence firms in certain business sectors can be better off supporting both R&D and CVC simultaneously to increase the probability of generating value creation. III. MCS and Organizational Structures for Radical Innovation Incremental innovation is necessary for continuous improvement but it does not provide a sustainable permanent source of competitiveness (Cooper, 2003). On the other hand, radical innovation pursuing new technologies and new market frontiers can generate new platforms for growth providing firms with competitive advantages and high economic margin rents (Duchesneau et al., 1979; Markides & Geroski, 2005; O'Connor & DeMartino, 2006; Utterback, 1994). Interestingly, not all companies distinguish between incremental and radical innovation, and more importantly firms that manage innovation through a one-sizefits- all process can almost guarantee a sub-optimization of certain systems and resources (Davila et al., 2006). Moreover, we conducted research on the utilization of MCS along with radical innovation and flexible organizational structures as these have been associated with firm growth (Cooper, 2003; Davila & Foster, 2005, 2007; Markides & Geroski, 2005; O'Connor & DeMartino, 2006). Davila et al. (2009) identified research opportunities for innovation management and provided a list of pending issues: How do companies manage the process of radical and incremental innovation? What are the performance measures companies use to manage radical ideas and how do they select them? The fundamental objective of this paper is to address the following research question: What are the processes, MCS, and organizational structures for generating radical innovation? Moreover, in recent years, research on innovation management has been conducted mainly at either the firm level (Birkinshaw, Hamel, & Mol, 2008a) or at the project level examining appropriate management techniques associated with high levels of uncertainty (Burgelman & Sayles, 1988; Dougherty & Heller, 1994; Jelinek & Schoonhoven, 1993; Kanter, North, Bernstein, & Williamson, 1990; Leifer et al., 2000). Therefore, we embarked on a novel process-related research framework to observe the process stages, MCS, and organizational structures that can generate radical innovation. This article is based on a case study at Alcan Engineered Products, a division of a multinational company provider of lightweight material solutions. Our observations suggest that incremental and radical innovation should be managed through different processes, MCS and organizational structures that ought to be activated and adapted contingent to the type of innovation that is being pursued (i.e. incremental or radical innovation). More importantly, we conclude that radical can be generated in a systematic way through enablers such as processes, MCS, and organizational structures. This is in line with the findings of Jelinek and Schoonhoven (1993) and Davila et al. (2006; 2007) who show that innovative firms have institutionalized mechanisms, arguing that radical innovation cannot occur in an organic environment where flexibility and consensus are the main managerial mechanisms. They rather argue that radical innovation requires a clear organizational structure and formal MCS.
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Background: Shared decision making (SDM) is a process by which a healthcare choice is made jointly by the healthcare professional and the patient. SDM is the essential element of patient-centered care, a core concept of primary care. However, SDM is seldom translated into primary practice. Continuing professional development (CPD) is the principal means by which healthcare professionals continue to gain, improve, and broaden the knowledge and skills required for patient-centered care. Our international collaboration seeks to improve the knowledge base of CPD that targets translating SDM into the clinical practice of primary care in diverse healthcare systems. Methods: Funded by the Canadian Institutes of Health Research (CIHR), our project is to form an international, interdisciplinary research team composed of health services researchers, physicians, nurses, psychologists, dietitians, CPD decision makers and others who will study how CPD causes SDM to be practiced in primary care. We will perform an environmental scan to create an inventory of CPD programs and related activities for translating SDM into clinical practice. These programs will be critically assessed and compared according to their strengths and limitations. We will use the empirical data that results from the environmental scan and the critical appraisal to identify knowledge gaps and generate a research agenda during a two-day workshop to be held in Quebec City. We will ask CPD stakeholders to validate these knowledge gaps and the research agenda. Discussion: This project will analyse existing CPD programs and related activities for translating SDM into the practice of primary care. Because this international collaboration will develop and identify various factors influencing SDM, the project could shed new light on how SDM is implemented in primary care.
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While the hospital remains an important element of the psychiatric health-care system, the fact that it is always the best place to treat acute psychotic episodes is still debated. After a brief review of the literature relative to the main existing community care models, the authors describe the development in the Department Universitaire de Psychiatrie Adulte (DUPA), of an alternative to hospitalisation for patient going through a severe acute psychiatric episode. They present three clinical situations and the aims of the research project, which will follow this pilot phase.
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BACKGROUND AND PURPOSE: Intensity-modulated radiotherapy (IMRT) credentialing for a EORTC study was performed using an anthropomorphic head phantom from the Radiological Physics Center (RPC; RPCPH). Institutions were retrospectively requested to irradiate their institutional phantom (INSTPH) using the same treatment plan in the framework of a Virtual Phantom Project (VPP) for IMRT credentialing. MATERIALS AND METHODS: CT data set of the institutional phantom and measured 2D dose matrices were requested from centers and sent to a dedicated secure EORTC uploader. Data from the RPCPH and INSTPH were thereafter centrally analyzed and inter-compared by the QA team using commercially available software (RIT; ver.5.2; Colorado Springs, USA). RESULTS: Eighteen institutions participated to the VPP. The measurements of 6 (33%) institutions could not be analyzed centrally. All other centers passed both the VPP and the RPC ±7%/4 mm credentialing criteria. At the 5%/5 mm gamma criteria (90% of pixels passing), 11(92%) as compared to 12 (100%) centers pass the credentialing process with RPCPH and INSTPH (p = 0.29), respectively. The corresponding pass rate for the 3%/3 mm gamma criteria (90% of pixels passing) was 2 (17%) and 9 (75%; p = 0.01), respectively. CONCLUSIONS: IMRT dosimetry gamma evaluations in a single plane for a H&N prospective trial using the INSTPH measurements showed agreement at the gamma index criteria of ±5%/5 mm (90% of pixels passing) for a small number of VPP measurements. Using more stringent, criteria, the RPCPH and INSTPH comparison showed disagreement. More data is warranted and urgently required within the framework of prospective studies.
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ABSTRACT: BACKGROUND: Shared decision-making is not widely implemented in healthcare. We aimed to set a research agenda about promoting shared decision-making through continuing professional development. METHODS: Thirty-six participants met for two days. RESULTS: Participants suggested ways to improve an environmental scan that had inventoried 53 shared decision-making training programs from 14 countries. Their proposed research agenda included reaching an international consensus on shared decision-making competencies and creating a framework for accrediting continuing professional development initiatives in shared decision-making. CONCLUSIONS: Variability in shared decision-making training programs showcases the need for quality assurance frameworks.