34,966 research outputs found

    Knowledge transfer in a tourism destination: the effects of a network structure

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    Tourism destinations have a necessity to innovate to remain competitive in an increasingly global environment. A pre-requisite for innovation is the understanding of how destinations source, share and use knowledge. This conceptual paper examines the nature of networks and how their analysis can shed light upon the processes of knowledge sharing in destinations as they strive to innovate. The paper conceptualizes destinations as networks of connected organizations, both public and private, each of which can be considered as a destination stakeholder. In network theory they represent the nodes within the system. The paper shows how epidemic diffusion models can act as an analogy for knowledge communication and transfer within a destination network. These models can be combined with other approaches to network analysis to shed light on how destination networks operate, and how they can be optimized with policy intervention to deliver innovative and competitive destinations. The paper closes with a practical tourism example taken from the Italian destination of Elba. Using numerical simulations the case demonstrates how the Elba network can be optimized. Overall this paper demonstrates the considerable utility of network analysis for tourism in delivering destination competitiveness.Comment: 15 pages, 2 figures, 2 tables. Forthcoming in: The Service Industries Journal, vol. 30, n. 8, 2010. Special Issue on: Advances in service network analysis v2: addeded and corrected reference

    Approaches for advancing scientific understanding of macrosystems

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    The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them

    Three Conceptual Themes for Future Research on Teams

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    [Excerpt] Tannenbaum, Mathieu, Salas, and Cohen (2011) identify three change themes – dynamic composition, technology/distance, and delayering/empowerment – that are affecting the nature of teams and discuss future research directions within each thematic area. They acknowledge that these emerging research needs may require new theories, research methods, and analyses and describe a few specific approaches that may hold promise, but focus their attention largely on describing the substantive issues and questions research should target going forward. We do not dispute that these themes are important – they are garnering substantial research attention (see Bell, 2007; Chen & Tesluk, in press; Kirkman, Gibson, & Kim, in press). However, they are among many issues that are in flux and important to consider in future research on teams. In this commentary, we adopt a broader perspective aimed at highlighting several conceptual, rather than substantive, themes that we believe can focus and leverage future research on the changing nature of teams. These conceptual themes are: (1) multilevel influences, (2) emergence, and (3) temporal dynamics. Sophisticated research questions and designs that encompass these conceptual issues will advance our understanding of the themes identified by Tannenbaum et al. (2011) as well as other emerging issues surrounding teams. In the following sections, we describe the three conceptual themes and then highlight the implications of these themes for future research on the changing nature of teams

    Supporting security-oriented, collaborative nanoCMOS electronics research

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    Grid technologies support collaborative e-Research typified by multiple institutions and resources seamlessly shared to tackle common research problems. The rules for collaboration and resource sharing are commonly achieved through establishment and management of virtual organizations (VOs) where policies on access and usage of resources by collaborators are defined and enforced by sites involved in the collaboration. The expression and enforcement of these rules is made through access control systems where roles/privileges are defined and associated with individuals as digitally signed attribute certificates which collaborating sites then use to authorize access to resources. Key to this approach is that the roles are assigned to the right individuals in the VO; the attribute certificates are only presented to the appropriate resources in the VO; it is transparent to the end user researchers, and finally that it is manageable for resource providers and administrators in the collaboration. In this paper, we present a security model and implementation improving the overall usability and security of resources used in Grid-based e-Research collaborations through exploitation of the Internet2 Shibboleth technology. This is explored in the context of a major new security focused project at the National e-Science Centre (NeSC) at the University of Glasgow in the nanoCMOS electronics domain

    Large emergency-response exercises: qualitative characteristics - a survey

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    Exercises, drills, or simulations are widely used, by governments, agencies and commercial organizations, to simulate serious incidents and train staff how to respond to them. International cooperation has led to increasingly large-scale exercises, often involving hundreds or even thousands of participants in many locations. The difference between ‘large’ and ‘small’ exercises is more than one of size: (a) Large exercises are more ‘experiential’ and more likely to undermine any model of reality that single organizations may create; (b) they create a ‘play space’ in which organizations and individuals act out their own needs and identifications, and a ritual with strong social implications; (c) group-analytic psychotherapy suggests that the emotions aroused in a large group may be stronger and more difficult to control. Feelings are an unacknowledged major factor in the success or failure of exercises; (d) successful large exercises help improve the nature of trust between individuals and the organizations they represent, changing it from a situational trust to a personal trust; (e) it is more difficult to learn from large exercises or to apply the lessons identified; (f) however, large exercises can help develop organizations and individuals. Exercises (and simulation in general) need to be approached from a broader multidisciplinary direction if their full potential is to be realized
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