1000 resultados para regional feature
Resumo:
The objective of this research was to understand and describe what corpo-rate social and regional responsibility is in SMEs and define the meaning of these concepts to the community and region. Corporate social respon-sibility (CSR) creates a basis for regional responsibility. Regional respon-sibility is a new concept and this research examines it from SMEs’ view-point. This is a theoretical research and the aim is to create a theoretical framework of SMEs’ corporate social and regional responsibility. This framework supports the future research on the subject. The research results show that CSR of SMEs is practical, informal and dependent on the scarce resources of SMEs. CSR is a complex and deep concept and SMEs have their own way of interpreting it. It can be stated that CSR-practises in SMEs are closely connected to employment, envi-ronment, community and supply chain. The challenge is to find motivation to socially and regionally responsible behaviour in SMEs. Benefiting from responsible behaviour and the attitude of SME’s owner-manager are the key reasons for SMEs to involve in CSR and regional responsibility. The benefits of this involvement are for example improved image, reputation and market position. CSR can also be used in SMEs as risk management tool and in cost reduction. This study indicates also that creation of strate-gic partnerships, local government participation, a proper legal system and financial support are the basic issues which support CSR of SMEs. This research showed that regional responsibility of SMEs includes active participation in regional strategy processes, L&RED initiatives and regional philanthropy. For SMEs regional responsibility means good relationships with the community and other related stakeholders, involvement in L&RED initiatives and acting responsibly towards the operating environment. In SMEs’ case this means that they need to understand the benefits of this kind of involvement in order to take action and participate. As regional responsibility includes the relationships between firm and the community, it can be stated that regional responsibility extends CSR’s view of stakeholders and emphasises both, the regional stakeholders and public-private partnerships. Community engagement and responsible be-haviour towards community can be seen as a part of SMEs’ social and regional responsibility. This study indicates that social and regional re-sponsibility of SMEs have a significant influence on the community and region where they are located. Better local and regional relationships with regional and community actors are the positive impacts of social and re-gional responsibility of SMEs. Socially and regionally responsible behav-iour creates a more positive environment and deepens the involvement of SMEs to community and L&RED initiatives.
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An examination of the impact in the US and EU markets of two major innovations in the provision of air services on thin routes - regional jet technology and the low-cost business model - reveals significant differences. In the US, regional airlines monopolize a high proportion of thin routes, whereas low-cost carriers are dominant on these routes in Europe. Our results have different implications for business and leisure travelers, given that regional services provide a higher frequency of flights (at the expense of higher fares), while low-cost services offer lower fares (at the expense of lower flight frequencies).
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Regional disparities in unemployment rates are large and persistent. The literature provides evidence of their magnitude and evolution, as well as evidence of the role of certain economic, demographic and environmental factors in explaining the gap between regions of low and high unemployment. Most of these studies, however, adopt an aggregate approach and so do not account for the individual characteristics of the unemployed and employed in each region. This paper, by drawing on micro-data from the Spanish wave of the Labour Force Survey, seeks to remedy this shortcoming by analysing regional differentials in unemployment rates. An appropriate decomposition of the regional gap in the average probability of being unemployed enables us to distinguish between the contribution of differences in the regional distribution of individual characteristics from that attributable to a different impact of these characteristics on the probability of unemployment. Our results suggest that the well-documented disparities in regional unemployment are not just the result of regional heterogeneity in the distribution of individual characteristics. Non-negligible differences in the probability of unemployment remain after controlling for this type of heterogeneity, as a result of differences across regions in the impact of the observed characteristics. Among the factors considered in our analysis, regional differences in the endowment and impact of an individual’s education are shown to play a major role.
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OBJECTIVE: We evaluated whether regional differences in physical activity (PA) and sedentary behaviour (SB) existed along language boundaries within Switzerland and whether potential differences would be explained by socio-demographics or environmental characteristics. METHODS: We combined data of 611 children aged 4 to 7 years from four regional studies. PA and SB were assessed by accelerometers. Information about the socio-demographic background was obtained by questionnaires. Objective neighbourhood attributes could be linked to home addresses. Multivariate regression models were used to test associations between PA and SB and socio-demographic characteristics and neighbourhood attributes. RESULTS: Children from the German compared to the French-speaking region were more physically active and less sedentary (by 10-15 %, p < 0.01). Although German-speaking children lived in a more favourable environment and a higher socioeconomic neighbourhood (differences p < 0.001), these characteristics did not explain the differences in PA behaviour between French and German speaking. CONCLUSIONS: Factors related to the language region, which might be culturally rooted were among the strongest correlates of PA and SB among Swiss children, independent of individual, social and environmental factors.
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The 51st ERSA Conference held in Barcelona in 2011 was one of the largest ever. By examining the characteristics of the conference, this paper identifies the main trends in Regional Science and draws on a broad array of sources of information: the delegates" demographic details, the conference program itself, a satisfaction survey conducted among delegates, a quality survey addressed to those chairing the sessions and, finally, a bibliometric database including each author signing a paper presented at the conference. We finally run a regression analysis from which we show that for ERSA delegates what matters most is quality, and this must be the direction that future conferences should move toward. Ultimately, ERSA conferences are comprehensive, all-embracing occasions, representing an ideal opportunity for regional scientists to present their work to each other and to network.
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Stochastic learning processes for a specific feature detector are studied. This technique is applied to nonsmooth multilayer neural networks requested to perform a discrimination task of order 3 based on the ssT-block¿ssC-block problem. Our system proves to be capable of achieving perfect generalization, after presenting finite numbers of examples, by undergoing a phase transition. The corresponding annealed theory, which involves the Ising model under external field, shows good agreement with Monte Carlo simulations.
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Chronic exposure to airborne fungi has been associated with different respiratory symptoms and pathologies in occupational populations, such as grain workers. However, the homogeneity in the fungal species composition of these bioaerosols on a large geographical scale and the different drivers that shape these fungal communities remain unclear. In this study, the diversity of fungi in grain dust and in the aerosols released during harvesting was determined across 96 sites at a geographical scale of 560 km(2) along an elevation gradient of 500 m by tag-encoded 454-pyrosequencing of the internal transcribed spacer (ITS) sequences. Associations between the structure of fungal communities in the grain dust and different abiotic (farming system, soil characteristics, geographic and climatic parameters) and biotic (wheat cultivar, previous crop culture) factors were explored. These analyses revealed a strong relationship between the airborne and grain dust fungal communities and showed the presence of allergenic and mycotoxigenic species in most samples, which highlights the potential contribution of these fungal species to work-related respiratory symptoms of grain workers. The farming system was the major driver of the alpha and beta phylogenetic diversity of fungal communities. In addition, elevation and soil CaCO3 concentrations shaped the alpha diversity whereas wheat cultivar, cropping history and the number of freezing days per year shaped the taxonomic beta diversity of these communities.
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El treball Ressuscitant a Disney: Rastrejant el sempre present esperit de Walt Disney en els llargmetratges animats de l'era Michael Eisner (1984-2004) pretén definir i analitzar les característiques, tant respecte al procés creatiu com en la definició de contingut, integrades en els clàssics originals de Disney per, a continuació, demostrar que aquestes van ser recuperades i implementades de nou després de la mort de Walt Disney -amb lleus adaptacions- per donar lloc a una segona edat d'or de l'animació
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Climate change affects the rate of insect invasions as well as the abundance, distribution and impacts of such invasions on a global scale. Among the principal analytical approaches to predicting and understanding future impacts of biological invasions are Species Distribution Models (SDMs), typically in the form of correlative Ecological Niche Models (ENMs). An underlying assumption of ENMs is that species-environment relationships remain preserved during extrapolations in space and time, although this is widely criticised. The semi-mechanistic modelling platform, CLIMEX, employs a top-down approach using species ecophysiological traits and is able to avoid some of the issues of extrapolation, making it highly applicable to investigating biological invasions in the context of climate change. The tephritid fruit flies (Diptera: Tephritidae) comprise some of the most successful invasive species and serious economic pests around the world. Here we project 12 tephritid species CLIMEX models into future climate scenarios to examine overall patterns of climate suitability and forecast potential distributional changes for this group. We further compare the aggregate response of the group against species-specific responses. We then consider additional drivers of biological invasions to examine how invasion potential is influenced by climate, fruit production and trade indices. Considering the group of tephritid species examined here, climate change is predicted to decrease global climate suitability and to shift the cumulative distribution poleward. However, when examining species-level patterns, the predominant directionality of range shifts for 11 of the 12 species is eastward. Most notably, management will need to consider regional changes in fruit fly species invasion potential where high fruit production, trade indices and predicted distributions of these flies overlap.
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Landslide processes can have direct and indirect consequences affecting human lives and activities. In order to improve landslide risk management procedures, this PhD thesis aims to investigate capabilities of active LiDAR and RaDAR sensors for landslides detection and characterization at regional scales, spatial risk assessment over large areas and slope instabilities monitoring and modelling at site-specific scales. At regional scales, we first demonstrated recent boat-based mobile LiDAR capabilities to model topography of the Normand coastal cliffs. By comparing annual acquisitions, we validated as well our approach to detect surface changes and thus map rock collapses, landslides and toe erosions affecting the shoreline at a county scale. Then, we applied a spaceborne InSAR approach to detect large slope instabilities in Argentina. Based on both phase and amplitude RaDAR signals, we extracted decisive information to detect, characterize and monitor two unknown extremely slow landslides, and to quantify water level variations of an involved close dam reservoir. Finally, advanced investigations on fragmental rockfall risk assessment were conducted along roads of the Val de Bagnes, by improving approaches of the Slope Angle Distribution and the FlowR software. Therefore, both rock-mass-failure susceptibilities and relative frequencies of block propagations were assessed and rockfall hazard and risk maps could be established at the valley scale. At slope-specific scales, in the Swiss Alps, we first integrated ground-based InSAR and terrestrial LiDAR acquisitions to map, monitor and model the Perraire rock slope deformation. By interpreting both methods individually and originally integrated as well, we therefore delimited the rockslide borders, computed volumes and highlighted non-uniform translational displacements along a wedge failure surface. Finally, we studied specific requirements and practical issues experimented on early warning systems of some of the most studied landslides worldwide. As a result, we highlighted valuable key recommendations to design new reliable systems; in addition, we also underlined conceptual issues that must be solved to improve current procedures. To sum up, the diversity of experimented situations brought an extensive experience that revealed the potential and limitations of both methods and highlighted as well the necessity of their complementary and integrated uses.
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In this paper, we propose a new supervised linearfeature extraction technique for multiclass classification problemsthat is specially suited to the nearest neighbor classifier (NN).The problem of finding the optimal linear projection matrix isdefined as a classification problem and the Adaboost algorithmis used to compute it in an iterative way. This strategy allowsthe introduction of a multitask learning (MTL) criterion in themethod and results in a solution that makes no assumptions aboutthe data distribution and that is specially appropriated to solvethe small sample size problem. The performance of the methodis illustrated by an application to the face recognition problem.The experiments show that the representation obtained followingthe multitask approach improves the classic feature extractionalgorithms when using the NN classifier, especially when we havea few examples from each class
Resumo:
Peer-reviewed