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This study aims to identify the structural relationship among social capital, knowledge sharing, innovation and performance of small- and medium-sized enterprises (SMEs) in a tourism cluster.

A total of 199 valid questionnaires are collected from SMEs in the Bomun tourism cluster in South Korea. A structural equation modeling approach is used to test the research hypotheses.

The findings suggest that social capital constructs, including network density of structural capital, relational capital and cognitive capital, all positively influence knowledge sharing among SMEs in the cluster. This implies that creating social capital is critical to enhancing the competitiveness of SMEs. This study confirms that knowledge sharing positively affects SME performance through innovation.

This study suggests that social capital, consisting of structural, cognitive and relational capital, facilitates increased knowledge sharing and innovation in a tourism cluster, which in turn enhances SME business performance.

This study suggests that tourism cluster policies should focus on how to create a friendly operational climate to build social capital and support SME innovation.

This study contributes to the literature on social capital and innovation as well as the discourse on tourism clusters by addressing knowledge sharing among SMEs in a tourism cluster. It also expands the knowledge sharing and innovation literature by focusing on inter-organizational social networking among SMEs.

In this chapter, the authors contribute toward building a better understanding of farmers’ responses to behavioral drivers of land-use decision by establishing an alternative analytical procedure, which can overcome various drawbacks suffered by methods currently used in existing studies. Firstly, our procedure makes use of spatially high-resolution data, so that idiosyncratic effects of physical environment drivers, e.g., soil textures, can be explicitly modeled. Secondly, we address the well-known censored data problem, which often hinders a successful analysis of land-use shares. Thirdly, we incorporate spatial error dependence (SED) and heterogeneity in order to obtain efficiency gain and a more accurate formulation of variances for the parameter estimates. Finally, the authors reduce the computational burden and improve estimation accuracy by introducing an alternative generalized method of moments (GMM)–quasi maximum likelihood (QML) hybrid estimation procedure. The authors apply the newly proposed procedure to spatially high-resolution data in England and found that, by taking these features into consideration, the authors are able to formulate conclusions about causal effects of climatic and physical environment, and environmental policy on land-use shares that differ significantly from those made based on methods that are currently used in the literature. Moreover, the authors show that our method enables derivation of a more effective predictor of the land-use shares, which is utterly useful from the policy-making point of view.

This paper describes the development process of a mobile Voice User Interface (VUI) for Korean users with dysarthria with currently available speech recognition technology by conducting systematic user needs analysis and applying usability testing feedback to prototype system designs.

Four usability surveys are conducted for the development of the prototype system. According to the two surveys on user needs and user experiences with existing VUI systems at the stage of the prototype design, the target platforms, and target applications are determined. Furthermore, a set of basic words is selected by the prospective users, which enables the system to be not only custom designed for dysarthric speakers but also individualized for each user. Reflecting the requests relating to general usage of the VUI and the UI design preference of users through evaluation of the initial prototype, we develop the final prototype, which is an individualized voice keyboard for mobile devices based on an isolated word recognition engine with word prediction.

The results of this paper show that target user participation in system development is effective for improving usability and satisfaction of the system, as the system is developed considering various ideas and feedback obtained in each development stage from different prospective users.

We have developed an automatic speech recognition-based mobile VUI system not only custom designed for dysarthric speakers but also individualized for each user, focussing on the usability aspect through four usability surveys. This voice keyboard system has the potential to be an assistive and alternative input method for people with speech impairment, including mild to moderate dysarthria, and people with physical disabilities.

This research paper aim at providing a new approach of calculating the destinations competitiveness index. How can these variables been aggregated in other to reflect the realities of very distinct productive environments? We assume that: The weighting of variables provides a better measure of destinations competitiveness. Base on the Neo-Technological theory, after a life cycle differentiation, we used a panel data approach to calculate the weight of each variable as the spearman correlation coefficient of its contribution to tourism inflows growth. After integrating these weights, we came to the point that by applying an appropriate weight to its components, we end up having a competitiveness index that significantly improve the correlation between competitiveness and tourism inflows growth.