15 resultados para Actor-Network theory

em University of Queensland eSpace - Australia


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Totally generalisable theories of firm internationalisation in the post-industrial era of international business, where national barriers are becoming less significant and technology becoming more influential, appear to be illusory. Stepwise or evolutionary models that predict gradual internationalisation are under challenge from empirical evidence of rapid internationalisation such as the phenomenon of the “born global” firm. Similarly, equilibrium models such as the eclectic paradigm have been criticised for being static and unable to account for process and path dependency. In this paper, the information and knowledge assumptions implied in theories of firm internationalisation are outlined and discussed. From this discussion, we suggest that actor-network theory, with its balance between description and explanation, may be a useful theoretical and empirical tool for investigating the complex and heterogeneous process of firm internationalisation whilst creating opportunities for further theory building.

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Regional tourism organizations (RTOs) plays a central role in planning, coordinating and marketing tourism in many areas, including Queensland, Australia. RTOs rely on interaction with a network of other organizations for their efficient functioning. This paper describes an exploratory case study that develops a method for use of social network analysis techniques to analyse the inter-organizational network in one RTO region in Queensland. Results indicate that differences exist in the structure of inter-organizational links between commercial tourism organizations and planning organizations, between tourism organizations and other sectoral clusters, and between organizations at local, regional and state levels. The results highlight areas or improvement in the role and responsibilities of RTOs in Queensland.

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Policy and social work practice currently lack a theoretical framework that adequately explains the emergence, diffusion, and continuance of the intercountry adoption (ICA) phenomenon. Using South Korea as a case study and the application of actor network theory to the ICA phenomenon, this paper introduces a theoretical approach that allows an examination of the complex interrelationships between the global and local influences of a country's engagement in ICA. This theoretical approach provides a different way of understanding the phenomenon, which, in turn, can better inform policies and practice that affect children and families across the globe.

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In this paper we consider the co-evolutionary dynamics of IS engagement where episodic change of implementation increasingly occurs within the context of linkages and interdependencies between systems and processes within and across organisations. Although there are many theories that interpret the various motors of change be it lifecycle, teleological, dialectic or evolutionary, our paper attempts to move towards a unifying view of change by studying co-evolutionary dynamics from a complex systems perspective. To understand how systems and organisations co-evolve in practice and how order emerges, or fails to emerge, we adopt complex adaptive systems theory to incorporate evolutionary and teleological motors, and actor-network theory to incorporate dialectic motors. We illustrate this through the analysis of the implementation of a novel academic scheduling system at a large research-intensive Australian university.

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Many growing networks possess accelerating statistics where the number of links added with each new node is an increasing function of network size so the total number of links increases faster than linearly with network size. In particular, biological networks can display a quadratic growth in regulator number with genome size even while remaining sparsely connected. These features are mutually incompatible in standard treatments of network theory which typically require that every new network node possesses at least one connection. To model sparsely connected networks, we generalize existing approaches and add each new node with a probabilistic number of links to generate either accelerating, hyperaccelerating, or even decelerating network statistics in different regimes. Under preferential attachment for example, slowly accelerating networks display stationary scale-free statistics relatively independent of network size while more rapidly accelerating networks display a transition from scale-free to exponential statistics with network growth. Such transitions explain, for instance, the evolutionary record of single-celled organisms which display strict size and complexity limits.

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In this paper, we present the results of the prediction of the high-pressure adsorption equilibrium of supercritical. gases (Ar, N-2, CH4, and CO2) on various activated carbons (BPL, PCB, and Norit R1 extra) at various temperatures using a density-functional-theory-based finite wall thickness (FWT) model. Pore size distribution results of the carbons are taken from our recent previous work 1,2 using this approach for characterization. To validate the model, isotherms calculated from the density functional theory (DFT) approach are comprehensively verified against those determined by grand canonical Monte Carlo (GCMC) simulation, before the theoretical adsorption isotherms of these investigated carbons calculated by the model are compared with the experimental adsorption measurements of the carbons. We illustrate the accuracy and consistency of the FWT model for the prediction of adsorption isotherms of the all investigated gases. The pore network connectivity problem occurring in the examined carbons is also discussed, and on the basis of the success of the predictions assuming a similar pore size distribution for accessible and inaccessible regions, it is suggested that this is largely related to the disordered nature of the carbon.

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The theoretical impacts of anthropogenic habitat degradation on genetic resources have been well articulated. Here we use a simulation approach to assess the magnitude of expected genetic change, and review 31 studies of 23 neotropical tree species to assess whether empirical case studies conform to theory. Major differences in the sensitivity of measures to detect the genetic health of degraded populations were obvious. Most studies employing genetic diversity (nine out of 13) found no significant consequences, yet most that assessed progeny inbreeding (six out of eight), reproductive output (seven out of 10) and fitness (all six) highlighted significant impacts. These observations are in line with theory, where inbreeding is observed immediately following impact, but genetic diversity is lost slowly over subsequent generations, which for trees may take decades. Studies also highlight the ecological, not just genetic, consequences of habitat degradation that can cause reduced seed set and progeny fitness. Unexpectedly, two studies examining pollen flow using paternity analysis highlight an extensive network of gene flow at smaller spatial scales (less than 10 km). Gene flow can thus mitigate against loss of genetic diversity and assist in long-term population viability, even in degraded landscapes. Unfortunately, the surveyed studies were too few and heterogeneous to examine concepts of population size thresholds and genetic resilience in relation to life history. Future suggested research priorities include undertaking integrated studies on a range of species in the same landscapes; better documentation of the extent and duration of impact; and most importantly, combining neutral marker, pollination dynamics, ecological consequences, and progeny fitness assessment within single studies.

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Consider a network of unreliable links, modelling for example a communication network. Estimating the reliability of the network-expressed as the probability that certain nodes in the network are connected-is a computationally difficult task. In this paper we study how the Cross-Entropy method can be used to obtain more efficient network reliability estimation procedures. Three techniques of estimation are considered: Crude Monte Carlo and the more sophisticated Permutation Monte Carlo and Merge Process. We show that the Cross-Entropy method yields a speed-up over all three techniques.

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The Great Barrier Reef Marine Park, an area almost the size , of Japan, has a new network of no-take areas that significantly improves the protection of biodiversity. The new marine park zoning implements, in a quantitative manner, many of the theoretical design principles discussed in the literature. For example, the new network of no-take areas has at least 20% protection per bioregion, minimum levels of protection for all known habitats and special or unique features, and minimum sizes for no-take areas of at least 10 or 20 kat across at the smallest diameter Overall, more than 33% of the Great Barrier Reef Marine Park is now in no-take areas (previously 4.5%). The steps taken leading to this outcome were to clarify to the interested public why the existing level of protection wets inadequate; detail the conservation objectives of establishing new no-take areas; work with relevant and independent experts to define, and contribute to, the best scientific process to deliver on the objectives; describe the biodiversity (e.g., map bioregions); define operational principles needed to achieve the objectives; invite community input on all of The above; gather and layer the data gathered in round-table discussions; report the degree of achievement of principles for various options of no-take areas; and determine how to address negative impacts. Some of the key success factors in this case have global relevance and include focusing initial communication on the problem to be addressed; applying the precautionary principle; using independent experts; facilitating input to decision making; conducting extensive and participatory consultation; having an existing marine park that encompassed much of the ecosystem; having legislative power under federal law; developing high-level support; ensuring agency Priority and ownership; and being able to address the issue of displaced fishers.

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Infrastructureless networks are becoming more popular with the increased prevalence of wireless networking technology. A significant challenge faced by these infrastructureless networks is that of providing security. In this paper we examine the issue of authentication, a fundamental component of most security approaches, and show how it can be performed despite an absence of trusted infrastructure and limited or no existing trust relationship between network nodes. Our approach enables nodes to authenticate using a combination of contextual information, harvested from the environment, and traditional authentication factors (such as public key cryptography). Underlying our solution is a generic threshold signature scheme that enables distributed generation of digital certificates.

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As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.