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

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

Higher Derivative Corrections and Central Charges from Wrapped M5-branes

We compute four-derivative corrections to the AdS supergravity actions arising from the near-horizon geometry of N M5-branes wrapped on either one or two Riemann surfaces. This setup features the novel presence of both gauged isometries as well as nontrivial hypermultiplets. We argue that the 5d Chern-Simons terms receive not only higher-derivative corrections but also contributions from Killing vector parameters, which we find must also be corrected. We check the central charges found by our supergravity methods against the dual field theory results and find perfect agreement at leading and subleading order in N. Along the way, we find higher derivative corrections to general AdS_5 and AdS_3x\Sigma_g geometries.Comment: 32 pages + 16 pages appendice

Metaverse in the tourism domain – introduction to the special issue

In times of technological innovation and digital transformation, the convergence of Metaverse and tourism emerges as a compelling and revolutionary intersection. As we stand on the edge of a new frontier in information technology, we introduce this special issue of the Journal of Information Technology and Tourism, dedicated to the multifaceted exploration of the Metaverse’s impact on the tourism industry. The Metaverse comprises interconnected digital spaces where users can engage through computer-generated environments. This convergence of cutting-edge tech- nologies, including artificial Intelligence (AI) systems, digital twins, augmented reality (AR), virtual reality (VR), blockchain, non-fungible tokens (NFTs), 3D mod- elling and simulation, cloud computing, and edge computing, defines the Metaverse’s potential. The Metaverse’s profound Influence on the tourism domain is well attested by the rigorous examinations, insightful analyses, and innovative research contributions in this issue. As we embark on this exploration, we encourage researchers, scholars, and industry experts to contribute their expertise and insights, forging a path toward a deeper understanding of the Metaverse’s implications for the future of tourism

Network Analysis Methods for Modelling Tourism Inter- Organizational Systems

This chapter discusses the emerging network science approach to the study of complex adaptive systems and applies tools derived from statistical physics to the analysis of tourism destinations. The authors provide a brief history of network science and the characteristics of a network as well as different models such as small world and scale free networks, and dynamic properties such as resilience and information diffusion. The Italian resort island of Elba is used as a case study allowing comparison of the communication network of tourist organizations and the virtual network formed by the websites of these organizations. The study compares the parameters of these networks to networks from the literature and to randomly created networks. The analyses include computer simulations to assess the dynamic properties of these networks. The results indicate that the Elba tourism network has a low degree of collaboration between members. These findings provide a quantitative measure of network performance. In general, the application of network science to the study of social systems offers opportunities for better management of tourism destinations and complex social systems

Homogeneous nucleation of dislocations as a pattern formation phenomenon

Dislocation nucleation in homogeneous crystals initially unfolds as a linear symmetry-breaking elastic instability. In the absence of explicit nucleation centers, such instability develops simultaneously all over the crystal and due to the dominance of long range elastic interactions it advances into the nonlinear stage as a collective phenomenon through pattern formation. In this paper we use a novel mesoscopic tensorial model (MTM) of crystal plasticity to study the delicate role of crystallographic symmetry in the development of the dislocation nucleation patterns in defect free crystals loaded in a hard device. The model is formulated in 2D and we systematically compare lattices with square and triangular symmetry. To avoid the prevalence of the conventional plastic mechanisms, we consider the loading paths represented by pure shears applied on the boundary of the otherwise unloaded body. These loading protocols can be qualified as exploiting the 'softest' and the 'hardest' directions and we show that the associated dislocation patterns are strikingly different

High coercivity induced by mechanical milling in cobalt ferrite powders

In this work we report a study of the magnetic behavior of ferrimagnetic oxide CoFe2O4 treated by mechanical milling with different grinding balls. The cobalt ferrite nanoparticles were prepared using a simple hydrothermal method and annealed at 500oC. The non-milled sample presented coercivity of about 1.9 kOe, saturation magnetization of 69.5 emu/g, and a remanence ratio of 0.42. After milling, two samples attained coercivity of 4.2 and 4.1 kOe, and saturation magnetization of 67.0 and 71.4 emu/g respectively. The remanence ratio MR/MS for these samples increase to 0.49 and 0.51, respectively. To investigate the influence of the microstructure on the magnetic behavior of these samples, we used X-ray powder diffraction (XPD), transmission electron microscopy (TEM), and vibrating sample magnetometry (VSM). The XPD analysis by the Williamson-Hall plot was used to estimate the average crystallite size and strain induced by mechanical milling in the samples