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Banks make good use of capital and have characteristics different from profit businesses. Mismanagement causes collapse, which negatively affects investors, depositors, and employees, and disrupts economic order. Consequences may also affect other industries, triggering financial distress. Therefore, evaluating operational risks in banks and developing an early warning system are critical. This study evaluates data from 858 international banks (including banking holding companies) from 2005 to 2008 and applies a logistic model to analyze critical factors. Results show that equity-to-assets (ETA) and interest income − interest expense/income (NIN) had negative relationships with financial distress. Banks accept deposits and make loans. A higher proportion of NIN shows stable business volume, which could avert financial distress. Therefore, ETA and NIN were indicative of banking financial distress and best predicted trends in Association of Southeast Asian Nations (ASEAN) and European Union (EU) banks.

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The purpose of this study is to develop a model to investigate the tourists’ preference. Ten attributes of tourist destinations were used in this study. Fuzzy set theory was adopted as the main analysis method to find the tourists’ preference. In this study, 248 pieces of data were used. Besides the evaluations for the factors, the overall evaluations (namely, satisfied, neutral, and dissatisfied) for every tourism destination were also inquired. After screening, 201 pieces of these data could be used. In these 201 pieces of data, 141 were classified into “satisfied” with the tourism destination, accounting for 70.15%, and 49 were “neutral,” accounting for 24.38%, while 11 were “dissatisfied,” accounting for 5.47%. Eight rules were obtained with the method of fuzzy preprocess. Regarding the condition attributes, three of the original ten attributes were found influential, namely, level of prices, living costs, information and tourist services, and tourist safety of the tourism destinations. From the results of this study, it is shown that top management of tourism destinations should put resources in these fields first, in order to allow limited resources to perform to maximum effectiveness.

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