Managing knowledge in tourism planning: How to assess your capability

This paper explores the theme of strategic planning in a State Tourism Organization (STO) from a knowledge management perspective. It highlights the value of knowledge in strategy making and the importance of an organisation's knowledge management agenda in facilitating a strategic planning process. In particular, it considers the capability of an STO to implement knowledge management as the key to a successful strategic planning exercise. In order to develop greater insight into the factors that impact on planning competence, the key aim of this paper is to develop a framework on which the capability of a STO to implement a knowledge-based agenda in strategic planning can be assessed. Research on knowledge management in the field of tourism is limited and there is little practical account of the application of knowledge management principles in tourism planning. Further, there is no apparent tool or instrument that allows for the assessment of an STO's capability to implement knowledge management in planning initiatives. Based on a literature review, a three-point framework of assessment is developed. The three elements of the framework are identified as: 1. Integration of knowledge management objectives with strategic imperatives; 2. A planning approach that balances top-down (outcome focused) with bottom-up (process focused) planning processes; and 3. Organisational capacity, including leadership, people and culture, process, technology, content and continuous improvement. The framework is tested through application to a practical case study - a planning initiative undertaken by a leading tourism STO in Australia. The results demonstrate that the framework is a useful means to evaluate organisational capability in knowledge-led strategic planning exercises and would be of practical value as a point of reference for future knowledge- based strategic planning projects. Copyright © by The Haworth Press, Inc. All rights reserved.

Development of a web-service-agents-based family wealth management system

The roiling financial markets, constantly changing tax law and increasing complexity of planning transaction increase the demand of aggregated family wealth management (FWM) services. However, current trend of developing such advisory systems is mainly focusing on financial or investment side. In addition, these existing systems lack of flexibility and are hard to be integrated with other organizational information systems, such as CRM systems. In this paper, a novel architecture of Web-service-agents-based FWM systems has been proposed. Multiple intelligent agents are wrapped as Web services and can communicate with each other via Web service protocols. On the one hand, these agents can collaborate with each other and provide comprehensive FWM advices. On the other hand, each service can work independently to achieve its own tasks. A prototype system for supporting financial advice is also presented to demonstrate the advances of the proposed Webservice- agents-based FWM system architecture.

Expansion-based algorithms for finding single pair shortest path on surface

Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.

Probabilistic world modelling for distributed team planning

This paper describes an application of decoupled probabilistic world modeling to achieve team planning. The research is based on the principle that tbe action selection mechanism of a member in a robot team cm select am effective action if a global world model is available to all team members. In the real world, the sensors are imprecise, and are individual to each robot, hence providing each robot a partial and unique view about the environment. We address this problem by creating a probabilistic global view on each agent by combining the perceptual information from each robot. This probsbilistie view forms the basis for selecting actions to achieve the team goal in a dynamic environment. Experiments have been carried ont to investigate the effectiveness of this principle using custom-built robots for real world performance, in addition, to extensive simulation results. The results show an improvement in team effectiveness when using probabilistic world modeling based on perception sharing for team planning.

Sustainable tourism planning: A content analysis of local tourism plans

Tourism planning has been advocated by many as a possible means of alleviating some of the negative impacts of tourism. While a number of approaches have evolved, tourism planning based on the philosophies of sustainability has emerged as the most comprehensive approaches. To investigate the tourism planning approaches of local tourism destinations in Queensland, particularly the extent to which tourism plans exhibit the sustainable approach to tourism planning, 30 local tourism planning documents have been reviewed. Despite claims that sustainable tourism planning is one of the most accepted approaches the study has shown that this is not necessarily the case in practice. It was found that although a number of plans addressed the issue of sustainability, the subsequent strategies and actions suggest that the sustainable approach is not the dominant planning approach, but in fact the economic and infrastructure approaches are the primary planning methods.

Achieving key dimensions of sustainability: Strategic visioning as a tourism destination planning tool

Tourism has had, and is continuing to have, a profound impact upon destinations, economically, environmentally and socially. The negative impacts of tourism have been attributed, among other things, to inadequate or non-existent planning frameworks for tourism development, and it has therefore been advocated that tourism planning is vital to offset some of these negative impacts. While several different approaches have been supported over the years, tourism planning based on the philosophies of sustainability has emerged as one ofthe most comprehensive approaches. However, two critical concepts have been identified as precursors to sustainable development: a strategic Qrientation towards tourism planning and enhanced levels of multiple stakeholder participation in the tourism planning process (Simpson 2001 ). While both strategic tourism planning and stakeholder participation and collaboration, have received considerable attention in the academic literature, there has been relatively little written about its practical application. However, the somewhat recent emergence of the strategic visioning concept as a destination planning tool may provide the necessary practical framework for incorporating stakeholder collaboration into destination strategic planning and management. This paper will provide a synthesis of the stakeholder collaboration, strategic planning and strategic visioning literatures, before conceptually examining the potential applicability._ of the strategic visioning process in achieving meaningful stakeholder participation and collaboration in destination planning.

The information specialist in the clinical team: Building expertise in evidence-based healthcare

The Clinician Development Program (CDP) is an initiative of Queensland Health’s Quality Improvement and Enhancement Program. At the Royal Brisbane & Royal Women's Hospital Health Service Districts, evidence-base practice (EBP) is an important CDP area in which several projects were carried out in 2002. This paper describes one such project. A medical librarian was invited to accompany the clinical team on morning rounds in the Medical Assessment & Planning Unit (MAPU). The librarian conducted information skills training in the ward and helped clinicians to answer questions directly related to patient care. Questions not answered during the round were followed-up, usually within 48 hours, and responses emailed to the consultant who led the rounds. At the project’s conclusion the librarian was invited to continue as a member of the MAPU clinical team, thus acknowledging the valuable role an information specialist can play in incorporating research evidence into patient care. Clinical librarianship (CL) creates a space, albeit a contentious one, for the health librarian at the bedside. This paper describes an Australian CL project and attempts to demystify the role of an information specialist in EBP. It also highlights some of the challenges facing librarians and clinicians attempting to embed EBP in clinical settings.

Bayesian retrieval of scatterometer wind fields

The retrieval of wind fields from scatterometer observations has traditionally been separated into two phases; local wind vector retrieval and ambiguity removal. Operationally, a forward model relating wind vector to backscatter is inverted, typically using look up tables, to retrieve up to four local wind vector solutions. A heuristic procedure, using numerical weather prediction forecast wind vectors and, often, some neighbourhood comparison is then used to select the correct solution. In this paper we develop a Bayesian method for wind field retrieval, and show how a direct local inverse model, relating backscatter to wind vector, improves the wind vector retrieval accuracy. We compare these results with the operational U.K. Meteorological Office retrievals, our own CMOD4 retrievals and a neural network based local forward model retrieval. We suggest that the neural network based inverse model, which is extremely fast to use, improves upon current forward models when used in a variational data assimilation scheme.

Regularised mixture density networks for modelling wind direction

This technical report contains all technical information and results from experiments where Mixture Density Networks (MDN) using an RBF network and fixed kernel means and variances were used to infer the wind direction from satellite data from the ersII weather satellite. The regularisation is based on the evidence framework and three different approximations were used to estimate the regularisation parameter. The results were compared with the results by `early stopping'.

Flexible Gaussian process wind field models

This technical report builds on previous reports to derive the likelihood and its derivatives for a Gaussian Process with a modified Bessel function based covariance function. The full derivation is shown. The likelihood (with gradient information) can be used in maximum likelihood procedures (i.e. gradient based optimisation) and in Hybrid Monte Carlo sampling (i.e. within a Bayesian framework).

Non-zero mean Gaussian process prior wind field models

This report outlines the derivation and application of a non-zero mean, polynomial-exponential covariance function based Gaussian process which forms the prior wind field model used in 'autonomous' disambiguation. It is principally used since the non-zero mean permits the computation of realistic local wind vector prior probabilities which are required when applying the scaled-likelihood trick, as the marginals of the full wind field prior. As the full prior is multi-variate normal, these marginals are very simple to compute.