Clustering is a well known technique in many areas of science and has been applied in such diverse fields such as botany, zoology, psychology, and market research. Cluster analysis is a multivariate analysis technique that seeks to organize objects described by a number of attributes or variables into relatively homogeneous groups, or ‘clusters'’. This paper presents a new developed clustering method for multivariate data. First, I describe four widely used clustering methods, SINLINK, K-means, CLASS, and Forgy's method. Next, the construct of the algorithm is discussed. Finally, comparisons of the four methods and the new method are described. From these comparisons, new method and CLASS are more suitable for the large data than the others. The best performance in the comparisons of the five methods is the proposed method.

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This paper examines whether corporate governance mechanisms in Taiwan listing companies could reduce incentives for managers to engage in myopic research and development (R & D) investment behavior. Our results show that managers with higher ownerships are less likely to cut R & D investment to meet short-term earnings goals. The probability of reducing R & D investment for earnings-increasing firms is low when CEOs chair the board of directors or CEO compensation-performance sensitivity is high. And, the institutional investors for firms facing earnings marginally decreases could play a monitoring role in reducing incentives to manage earnings with cuts in R & D.

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Child sexual abuse (CSA) has long been regarded as a public health problem. However, in Taiwan, little attention has been paid to understanding the ecological contexts in which children live and providing safe environments for children. Thus, the purpose of the study was to examine how Taiwanese parents perceive their roles in the prevention of CSA. A social survey method was adopted, and we recruited 344 parents who had at least one child under age of 12 from pediatric clinics in Taipei city. The self-report questionnaire included four aspects: the definition of CSA, the indicators of CSA, the grooming process of perpetrator, and demographic variables. All data were coded and analyzed using the Statistical Package for the Social Sciences. Household income was found to be significantly correlated with awareness of the definition of CSA. ANOVA analyses showed that educational level was significantly related to awareness of the indicators of CSA and the grooming process of perpetrator. Awareness of the grooming process of perpetrator should be considered in future research.

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Very often, each individual continues to do something for his/her individual advantage that collectively is damaging to the group as a whole. The conflict is labeled as “social dilemma” or “social trap” by social psychologists. The phenomenon is very common in individualistic cultures (the West), but does the same phenomenon exist in collectivistic cultures which value cooperation and group goals more than individual benefits? The present authors employed a “replenishable ocean resource paradigm” that they developed on a series of studies in Taiwan and found that selfish behaviors were indeed very pervasive in the East. Several significant factors that affected the degree of cooperation and/or competition were also identified: sanction system, personal motivation, interpersonal relation, and the composition of decision making groups. In brief, it was found that the lower the severity of punishment or the less probability of being caught, the more selfish the subjects' behaviors became. Subjects with the motives to maximize “individual gain” and “relative gain” competed more and did not differ from each other, while “joint gain” subjects competed the least. In addition, decisions made by group of three or five people were more selfish than the decisions made by the individual. The present authors and their associates also compared the behaviors of Taiwan and American students in the social dilemma situation directly. It was found that subjects from two cultures did differ on the cooperative behaviors. Taiwan subjects were more competitive than American subjects in general. Both “probability of inspection” and “degree of punishment” had significant effect on the Taiwanese's behaviors, but only “inspection probability known or not” affected American subjects. In respects to Collectivism/Individualism Scale, Taiwan subjects did not score higher than American subjects on total collective measure, but Taiwan subjects scored higher than American subjects on collectivism toward spouses, parents, and relatives, and scored less than American subjects on collectivism toward colleagues/classmates and friends. Therefore, Taiwan subjects interacting with colleagues/classmates or friends were more selfish than American subjects. General discussion on the meaning, application and cross-cultural implication of this series of studies concludes this paper.

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Nowadays, markets are moving from the product-oriented type to the consumer-oriented type, in the light that the modern life cycle of product is becoming shorter and shorter. Kansei engineering is a method used to link emotions and product features. In this paper, we apply Kansei engineering in the automotive GPS industry. This study is of interest to the manufacturers involved, because they wanted to see how the existing GPS designs are perceived by the consumers. The aim of this paper is to propose a conceptual model for connecting the semantic axes to the product properties. By using the factor analysis, quality technology and perceived quality for the GPS monitor center are two main factors extracting form those 8 Kansei words, which were used to assess the service quality. Moreover, Appearance-Function and overall design effect were derived from the physical design. The proposed conceptual model for the automotive GSP products is expected to be useful when performing applications.

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A domain dictionary contains many professional words and their definitions. In general, there are many hidden relations among words in a dictionary. In this paper, we use techniques of natural language processing to find out these relations, and bring up a method to construct a domain specific lexical semantic network.

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The profit of investment does not lie solely in the accuracy of prediction, but in the degree of belief as well. The greater the degree of belief is, the more capital the investors might venture, which results in more profit returns. On the contrary, under the condition of an accurate prediction, if the degree of belief is little, investors will not put in too much capital, which leads to limited profit. This study attempts to apply belief functions in explaining the prediction results of multivariate fuzzy time series, i.e. the degree of belief that the prediction model has for the prediction result. By utilizing multivariate fuzzy time series model, combining with two variables of closing price and volume of transaction in weighted stock price index, the author tries to predict the Taiwan weighted stock price index and estimate the degree of belief, which are trusted to be of great meaning for risk control and a better rate of return.

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In this study we investigated quality of life and functional communication activities in a sample of typical Taiwanese communicators and people who stutter (PWS) using an adapted version of the Quality of Communication Scale. In the first phase of this investigation we adapted the Quality of Communication Scale for the Taiwanese population. In the second phase we collected data on typical communicators and on 10 people who stutter. Our data demonstrated that, stuttering has a significant impact on PWS' life satisfaction, quality of communication, and difficulty with communication in daily situations. People who stutter feel least satisfied in their general ability to communicate with others at work or school, and the most difficult communication activity is giving a speech to a large group of strangers. Interestingly, the severity of stuttering and life satisfaction, quality of communication, and difficulty with communication in daily situations were not significantly related.

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The aim of this study was to propose and validate the new scaling method, fuzzy partial credit scaling (FPCS), which combines fuzzy set theory with the partial credit model (PCM) to score rating scales. To achieve this goal, the Chinese version of BDI (Beck Depression Inventory-II) was administrated to a depressed sample of patients and a non-depressed sample. The depressed sample consisted of 240 outpatients who were diagnosed as depressed by a psychiatric doctor, while 321 undergraduate students were recruited for the nondepressed sample.
In FPCS, triangular fuzzy numbers were generated by step parameters to characterize distributions of each alternative value. Next, the center of gravity (COG) method was applied to “de-fuzzify”the fuzzy number into a scalar. Then, the “observed fuzzy scores”defined in FPCS were calculated as the sums of fuzzy number values weighted by membership degrees for the following analysis.
The predictive validity issue of FPCS was investigated. Discrimination analysis was performed to classify the subjects according to the severity of depression into three categories: non-depression, depression with remission and depression without remission. The analytical results exhibited that, via FPCS, the probability of correct classification of severity of depression was raised from 71.2% to 80.7%. These two statistical analyses consistently show that FPCS exhibited higher predictive validity than did the raw score. That is, BDI scoring via FPCS makes more accuracy predictions for depression than raw score.
FPCS has been consistently shown to be superior to raw scoring in terms of reliability, validity, and clustering accuracy. This study has empirically shown that fuzzy set theory is applicable to psychological research.

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How to determine the number of level-2 units in multilevel structural equation modeling (MSEM) as a standard applied to nested or hierarchical data structure was still unknown. This research used Canada data in the large database “Programme for International Student Assessment 2003”(PISA 2003) to check the model-fit indexes and parameters stability in our proposed empirical example processed by MSEM under different numbers of level-2 units. Our proposed example model was first be handled to fit Canada data (26884 students, 948 schools), and then the stabilities of the estimated parameters in the example model under 120, 240, 360, 480, 600, 720, 840 level-2 units were compared. Level-1 units in each school less than10 students will be crossed out in advance. Besides, intraclass correlations of all variables were controlled in a specified range in different numbers of level-2 units. Finally, we found the ratio of the number of level-2 units relative to the number of estimated parameters of between-level in the multilevel model were 8: 1.

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