Applying structural equation modeling methodology to test validation: an example of cyberspace positive psychology scale

Although the structural equation modeling (SEM) methodology is a powerful tool for validating psychological measurements, few studies have used complete SEM-based indexes in test validation. This study developed and validated the cyberspace positive psychology scale (C-PPS) via SEM techniques. A total of 411 college students were recruited from four universities in Taiwan for the study. Hierarchical confirmatory factor analysis was used to test construct validity, and a structural model provided criterion-related validity. Reliability was reported via composite reliability. Results of the analyses show that the C-PPS demonstrated high reliability and good construct validity. Furthermore, criterion-related validity identified that although positive psychology in cyberspace and positive psychology in real life contexts are correlated, the two are also distinguishable. To conclude, the C-PPS is valid and reliable. The validation of the C-PPS indicates that college students can exhibit positive psychological traits in both the real and virtual worlds.     

Incorporating support vector machines with multiple criteria decision making for financial crisis analysis

Feature selection is an essential pre-processing technique in data mining that eliminates redundant or unrepresentative attributes and improves the performance of classifiers. However, a classifier with different feature selection approaches results in diverse outcomes. Thus, determining how to integrate feature selection methods and yield an appropriate feature set is an issue worth further study. Based on ensemble learning, this investigation develops a SVMMCDM (support vector machines with multiple criteria decision making) model that employs various feature selection techniques as data preprocessing schemes and then uses SVM for financial crisis prediction. The study uses MCDM to determine the most suitable feature selection mechanism when many performance criteria are considered. After the feature selection mechanism has been determined, the study decomposes the SVM to obtain support vectors and predicted labels which are then fed into a decision tree to generate rules. The numerical results for the ex-ante and ex-post periods relative to the financial tsunami show that the proposed SVMMCDM model is an effective way to predict a financial crisis and can provide useful rules for decision makers.     

“Pacific Rim: The forefront of international tourism”: Report on the 1997 conference of the international society of travel and tourism educators (ISTTE)

The 1997 conference of the International Society of Travel and Tourism Educators (ISTTE) was held from October 23–26, 1997 in San Diego, California, USA. More than 150 travel and tourism educators and industry professionals gathered at the Mission Valley Hilton Hotel to attend the society's ninth annual event. Delegates represented over 80 tow‐ and four‐ year colleges and universities, private travel schools, and high school in Australia, Canada, Korea, Japan, New Zealand, the United Kingdom, and the United Sates. Also present were representatives of nearly 30 companies from various sectors of the travel and tourism industry. Special to this year's conference was the theme of “The Pacific Rim: Tomorrow‐Today” —a recognition of the region as the fastest growing inbound and outbound market of international tourism. It was the first time the society chose a region as the center stage of its biggest annual event. It also was the first conference held after the society adopted its present name. At last year's conference in Ottawa, Canada, the Society's Board of Directors recommended, and members voted, to add “International” to its original name to reflect the increasing representation of international membership in the organization. This year's conference was presided over by Dr. Kaye Chon, President of ISTTE and Professor of Conrad N. Hilton College of Hotel and Restaurant Management, University of Houston, USA.     

A Visual Analysis of Destinations in Travel Magazines

This study presents a visual analysis of photographs of six destinations (Hong Kong, Macau, Japan, South Korea, Vietnam, and Taiwan) published in Chinese travel magazines. The object and subject categories, size, and providers of the photographs are content analyzed. The three most popular object categories were Culture, history, and art; Leisure and recreation; and Physical environment. The dominant subject category was No people. Multiple Correspondence Analysis showed that the different destinations correlated with diverse object and subject categories. All six destinations were portrayed differently in terms of the source and size of the photographs. These findings can be utilized by destination marketing organizations (DMOs) to devise positioning and promotion activities for implementation in the Chinese market.     

Enhancing value creation of device vendors in the medical service industry: a relationship perspective

Around the world, hospitals receiving government funding and insurance payments are under increasing pressure to cut costs. Based on the literature in relationship value and transaction cost economics, long-term relationships between suppliers and customers can be beneficial to cost reduction and value creation. This study explores the value of long-term relationships between medical device vendors and hospitals from the hospital perspective. In-depth interviews were conducted employing a grounded theory approach. The results show that in addition to product benefits/costs and supportive services, vendor reputation and sales personnel specificity are most influential towards the value of their long-term relationships.     

Top management team characteristics,R&;D investment and capital structure in the IT industry

This paper is based on agency theory, resource-based and upper-echelons perspectives to examine the relationship between R&D investment and capital structure and the moderating effects of top management team (TMT) characteristics on the financing decisions of R&D investment in small and medium enterprises (SMEs). Using data for SMEs in Taiwan’s IT industry, we find that (1) SMEs involved in R&D activities tend to have lower debt levels and (2) TMT characteristics exert considerable influence on the R&D investment-financial leverage relationship in SMEs. One important implication of the empirical evidence is that for SMEs trying to compete on the basis of innovation, the TMT characteristics significantly influence financing decisions. As innovative activities increase, the selection and development of top executives, who are responsible for choosing an optimal capital structure that could keep financial costs low while providing sufficient financial resources for maintaining a continuous, uninterrupted rate of R&D, is crucial for SMEs.     

Selection model based on ANP and GRA for independent media agencies

This study develops a model for selecting an optimal independent media agency for an advertiser. The proposed model comprises two parts. The first part uses the modified Delphi technique to identify suitable criteria for evaluating media agencies, after which the analytic network process (ANP) is applied to determine the relative weights of the criteria. The second part adopts the grey relational analysis (GRA) to rank alternatives and to select the optimum media agency. Additionally, the example of a famous Taiwanese beverage company is used to demonstrate the process of media agency selection using this model. The proposed model method provides advertisers with an objective and effective of selecting an optimum media agency.     

Student-t distribution based VAR-MGARCH: an application of the DCC model on international portfolio risk management

Significant second-moment transmission effects and obvious time-varying patterns of correlation coefficients among major equity and currency markets in the US, Japan and the UK are found to exist. Such observations inspire the time-varying setting of dynamic conditional correlation coefficients in MGARCH models. On the other hand, the multivariate Student-t distribution is suitable for analysing the visible leptokurtosis that is common in financial markets. Both are important for international portfolio risk management. Thus, a comparison on the hedging efficiency of hypothetical portfolios consisting of stock and currency future positions is conducted in order to justify the multivariate Student-t distribution based on the DCC-MGARCH model.     

A modular fuzzy inference system approach in integrating qualitative and quantitative analysis of store image

The image situation in a store includes various stimuli, such as color, sound, scent, taste, layout and space, which are important clues for buyers. This paper describes store image response and a fuzzy logic model developed by comprehensive literature studies on image measurements (including atmospheric factors) and perceptual measures. Here, a fuzzy inference system is proposed as an alternative approach to handle effectively the impreciseness and uncertainty that are normally found in store image selection processes. This paper also shows that the proposed decision-making model is application to modified stimulus?Corganism?Cresponse (S?CO?CR) framework for integrating qualitative and quantitative analysis. The result of the simulation indicates a numerical and linguistic change in the store image perception after analyzing three input parameters. This finding is able to provide a solid foundation on which retailers and decision makers can base suitable strategies for ensuring the efficiency and stability of store image management system.