Assessing Destination Competitiveness: An Application to the Hot Springs Tourism Sector

This paper proposes a model to identify the factors determining the competitiveness of the hot springs tourism sector, with particular application to Taiwan. The proposed conceptual framework brings together two approaches, namely the theories of industry organization (10) and the resource-based view (RBV). The proposition underlying this framework is that destination competitiveness is achieved by the adoption of policies and strategies aligned with market opportunities, drawing upon the unique or distinctive tourism features offered by the destination. It is proposed that three major influences are evident in the case of hot springs tourism, namely Tourism Destination Resources and Attractors, Tourism Destination Strategies and Tourism Destination Environments. An evaluation is provided of the administration of a three-round Delphi survey, which was intended to validate the determinants of destination competitiveness that were derived from the literature. Drawing upon the results of the pilot study it is concluded that the development of a sector-specific model of destination competitiveness is capable of capturing the nature and characteristics of the hot springs tourism sector

Consumer Willingness to Pay and Marketing Opportunities for "Quality Guaranteed Tree-Ripened Peaches" in New York State

This study identifies consumer characteristics associated with willingness to pay a higher price for quality guaranteed tree-ripened peaches, with a focus on evaluating factors important to consumers when making decisions to purchase tree-ripened peaches. Telephone interviews were conducted with consumers in New York State in summer, 2002. Seventy-eight percent of the 258 survey respondents reported that they were willing to pay a higher price. A logistical regression model of willingness to pay was estimated. The empirical results indicated that willingness to pay was positively affected by the existence of previous experiences in purchasing tree-ripened peaches and by consumer dissatisfaction with peaches consumed in the past. An analysis of consumer experiences and consumer dissatisfaction showed that consumers in the two identified segments had mutually exclusive characteristics that present marketing opportunities for high quality New York-grown peaches.Consumer/Household Economics,

Online Bearing Remaining Useful Life Prediction Based on a Novel Degradation Indicator and Convolutional Neural Networks

In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life (RUL) for REBs are of crucial importance to ensure the reliability and safety of mechanical systems. To tackle this challenge, model-based approaches are often limited by the complexity of mathematical modeling. Conventional data-driven approaches, on the other hand, require massive efforts to extract the degradation features and construct health index. In this paper, a novel online data-driven framework is proposed to exploit the adoption of deep convolutional neural networks (CNN) in predicting the RUL of bearings. More concretely, the raw vibrations of training bearings are first processed using the Hilbert-Huang transform (HHT) and a novel nonlinear degradation indicator is constructed as the label for learning. The CNN is then employed to identify the hidden pattern between the extracted degradation indicator and the vibration of training bearings, which makes it possible to estimate the degradation of the test bearings automatically. Finally, testing bearings' RULs are predicted by using a $\epsilon$-support vector regression model. The superior performance of the proposed RUL estimation framework, compared with the state-of-the-art approaches, is demonstrated through the experimental results. The generality of the proposed CNN model is also validated by transferring to bearings undergoing different operating conditions

Microencapsulation and viability of a probiotic in a simulated gastrointestinal environment

The human-origin probiotic Lactobacillus rhamnosus strain GG (LGG) proved to exert health benefits in dogs. Like other strains, the viability of this probiotic is reduced while passing through the stomach and upper intestine because of the low pH and presence of bile. In this study, calcium alginate microcapsules, loaded with LGG, with and without the addition of xanthan gum coated chitosan, were prepared with the traditional extrusion method. The capsules of all formulations were able to improve the viability of LGG (P107 CFU/g when separately exposed to simulated gastric fluid (SGF) for 2 h and simulated intestinal fluid (SIF) for 4 h. However, results of sequential incubation in SIF after SGF revealed a dramatic reduction in the viability of encapsulated cells with no difference from control, which cannot be explained with little information in the literature. The alginate beads incorporated with xanthan gum resulted in less severe wrinkles on the surface. All the formulations achieved encapsulation yields of around 80% and the cell viability remained at least 107 CFU/g after 4 weeks storage at refrigeration temperature. The overall situation indicated that the most stable microcapsules were chitosan-coated alginate (2.5% w/v)-xanthan gum (0.15% w/v) beads. These results indicated the potential of industrial application of chitosan-coated alginate-xanthan gum microcapsules