There has been a recent resurgence in interest in the study of personality types. This personality type research has focused on the uncovering of statistical types, rather than relying on rationally developed types. Using the method of cluster analysis, I investigated whether such statistical types could be uncovered and whether they correspond to the types described in previous analyses. The expected number of personality types was uncovered and, while these types resemblanced the personality types discussed in the literature, the patterns of scores for these types were not exactly as hypothesized.

The Strategies of the firms in Patent are not only about the future, but also forming the barrier for competitor. For the sake, we should develop the patent strategies and technological position.This study goes to the discussion of technological position by the patent multivariate analysis, and suggest the patent strategy by the difference within and between the groups which were clustered from IC design companies. This study selects twenty gobal IC design companies,which are always on the top25 of the industry.In case1 ,we wonder figure out the technological postion and the path of technology shift.In case2,we can recognize the technological position as industrial position. In case 1, we got four clusters by cluster analysis.Cluster 1 is called SpecialistII,and cluster2 is called Strong Generalist, and cluster 3 is called Specialist I,and cluster 4 is called Weak Generalist. For further observation, the firms with technology shift will shift from cluster 1 to cluster 2 in the same direction.Others still maintain the same strategies in their clusters. In case 2 , we also got four clusters by the analysis. Cluster 1 is called Weak Generalist ,and cluster 2 is called Strong Generalist, and cluster 3 is called Specialist I,and cluster 4 is called Specialist III.As financial results , we got homogeneity within a cluster except cluster 4. Performance between clusters, we made and observed the line chart of trend in the selected financial ratio and we used the median of samples within a cluster. In case 2,it seems heterogeneous in ROA and Price-to-book ratio in the chart.In case1,it is also heterogeneous in ROA and price-to-book ratio.It¡¦s significant and positively correlated in R&D productivity(GrossMargin-to-R&D ratio) between others by the correlation coefficient matrix.It seems to be the proxy to the other financial ratio.

In recent years, many construct wetlands in Taiwan have been built for the purposes of wastewater treatment, river water purification, and ecology conservation. To evaluate the effectiveness of constructed wetlands on water purification, frequent water quality monitoring is needed. In this study, the multivariate statistical analysis was applied to evaluate the contaminant removal efficiency in a constructed wetland, and the time series method was then used to predict the trend of the indicative pollutant concentration in the wetland. Multivariate statistical analysis simplifies the original data into representative factors, or hive off the similarity between data to cluster, and then identify clustering outcomes. In this study, an artificial wetlands at the site around an old bridge locates at the Kaoping River Basin was used as the study site. The statistical software SPSS 12.0 was used to perform the multivariate statistical analysis to evaluate water quality characteristics of its. Results from this study show that the removal efficiency for the total coliforms (TC) of System A and B was 98%, 55% for biochemical oxygen demand (BOD), 53% for chemical Oxygen demand (COD), 55% for ammonia nitrogen (NH3-N), and 39% for total nitrogen (TN). Moreover, suspended solids (SS) couldn¡¦t be removed in both A and B systems. The box-and-whisker plot indicates that the water quality of inflow was unstable and variable; however, outflow was turning stable with its flow direction. The major pollutant indicators, except SS, were all in a decreasing tendency. The paired t-test shows p value of each item were lower than 0.05, except total phosphorus (TP) in System A, nitrate nitrogen (NO3-N) and Chlorophyll a (Chl-a) in System B. The correlation parameters from TN, nitrogen oxides (NOx), NO3-N and nitrite nitrogen (NO2-N) and so on were all higher than 0.7. The factor analysis of SPSS shows that 17 water-quality items of the study site could obtain four to six principal components, including nitrate nutrition factor, phosphorus nutrition factor, eutrophication factor, organic factor, and environmental background factor, the major influencing components are nutrition factor and eutrophication factor. The ponds of the study site were classified into two or three clusters depend on in-and-out flow location. This study attempted to establish a forecasting model of wetland pollutants concentration through the time series (ARIMA), results show that the outcome of the B7 pond was better than others. Results indicate that the ARIMA model can be used to simulate the trend of treatment efficiency using the wetland system. Experience and results obtained from this study would provide solutions for water quality control.

With the rapid Internet development, E-auction is also popular in recent years. In E-auction, the rating is the most effective indicator that can provide a referral for buyer and seller. In addition, buyers can use rating mechanism as feedback to respond their satisfaction after they bought goods. In the other hand, the rating of seller could reflect his transaction history before. When the positive rating is more, which means satisfied and successful transaction is more also, and represents that seller¡¦s credit accumulation. This study uses innovation diffusion model to analyze the seller¡¦s growth trend of rating, critical mass of rating by real data, classify sellers that equal to cluster analysis and discuss further. The samples are the sellers who sell t-shirt in eBay from December 1 in 2010 to January 31 in 2011. We get 8,304 sellers¡¦ data, and pick 116 of them randomly as samples, which are fit in with our research requests. This research is to answer three research questions. The first research question is to verify that growth trend of rating could fit in with diffusion of innovation, then, to analyze and discuss the growing trend and the rating accumulation. That result does verify that rating accumulation fit in with diffusion of innovation, and growing trend fit in with S-shaped curve. Furthermore, rating raise at first if it is affected by external influence, like key searching, website payment advertisement. On the contrary, the rating increases quickly for some time that the seller has good reputation if the rating is affected by internal influence, like word of mouth. The second research question is to calculate the critical mass of rating by Bass model. The result shows that the rating accelerates when it reaches critical mass between 1129 and 1402, it represents the seller accumulates considerable sale amount and customer satisfaction, and also let potential buyers more confident and promote their willingness to purchase. In addition, it can represent the sellers have enough experience and can provide the better marketing strategies when the sellers¡¦ rating reaches critical mass of rating. The third research question is to divide the sellers by cluster analysis and investigate. The result shows the diverseness between the growth trend of rating, the critical mass of rating, product price, and buyer repeated purchase. This study can provide a referral for the novice sellers, and they can develop their marketing strategy base on their characteristics of product.

With the progress of the times, the international financial market link is becoming more and more closely, while the probability of extreme events more and more high, if there are some indicators can be used as a prediction of the crash, as whether to sell the stocks, it can be very useful. The study process for the use of the Fama-French five-factor model, as well as the VaR model, with the cluster analysis method, and clustering for Taiwan 50 constituent stocks in accordance with the five-factor characteristics of the individual stocks, the similar nature of stock into the same group, the establishment of portfolio, the use of portfolio daily returns to calculate the the VaR, and observe the VaR spread before the crash, how the trend, and whether certain characteristics. Comparison of the cluster group for the predictive ability of the collapse events, as well as the relationship between risk factors and predictive ability. The results of VaR spread movements are often subject to fluctuations significantly change the situation before the crash occurs. By intense will be stable or from stable will be severe. Good predictive ability of the cluster, often its constituent stocks and the collapse of the reasons more closely the relationship. Financial stocks sensitive to the financial tsunami; Electronic stocks are subject to exchange rate affect.Overall, the group with the best predictive ability is more sensitive to momentum effects and investor sentiment indicators ,but non-sensitive to book-to-market factor.To use the Var spread as a predictor of reference,choosing to meet the aforementioned conditions of stocks to the portfolio is a nice way.

Due to the financial turmoil in recent years, risk management has become an important issue, investors would like to be fully-prepared to cope with financial crisis before it happen. This research uses the Fama and French three-factor and the U.S. Dollar Index (USDX) as an exchange rate variations indicator to capture the international relations. It constitutes a four-factor model to analyze the S&P100 stock returns changes, and we introduce the skewed-t distribution to simulate the distribution of stock returns and capture the characteristics of skewness and kurtosis. We use cluster analysis to cluster the sample companies by their risk characteristics. And then we observe the explanatory power of each risk factor. The study shows that the S&P100 stocks are subjected to the market premium, and the scale effect is smaller than others. ¡@¡@ At last, in accordance with the GARCH-Skewed-t model to simulate the average, variance, skewness and kurtosis of each cluster. We track the long-term performance of each parameter which are used to observe the unusual changes before financial crisis. The empirical results show that the skewness parameter has perfect warning for financial turmoil. The cluster with warning ability is affected by B/M ratio effect and exchange rate changes. Among the case, the cluster has the best early warning effect when it's influenced by the exchange rate indicator. It displays that by adding an exchange rate risk indicator into the multi-factor model, we will have a better clustering result. It means that the skewness parameter of cluster with influence of exchange rate indicator can be used to observe financial turmoil, which can in turns, be used as an early warning system to determine the occurrence of extreme events.

Two drilled cores were collected from the Jhuoshuei River delta for this study, which is focused on the analyses of sedimentological, statistical analysis, AMS C14 dating and paleoenvironment interpretation based on the benthic foraminiferal fossils. Foraminiferal shell do not exist between 30000 and 12000 yr B.P., indicating the environment of this sections might be terrestrial. Between 12000 and 8000 yr B.P., the southern core do not have traces of foraminifera, suggesting the deposition site was terrestrial. The northern core contains the benthic foraminiferal shell between 12000 and 9000 yr B.P. The foraminiferal assemblage indicates the sedimentation might be a inner shelf like enviroment. An estuarine like environment was suggested between 9000 and 8000 yr B.P.. Between 8000 and 6000 yr B.P., foraminiferal cluster analysis indicates a middle to inner shelf environment at the southern core site; a inner shelf at the northern core. From 6000 to 3000 yr B.P., foraminiferal cluster analysis indicates a inner shelf at the south core while northern core foraminifera became fewer and the environment gradually changing to terrestrial facies. From 3000 yr B.P. upwards, foraminiferal cluster analysis indicates a shallower inner shelf at the southern core. From 2000 yr B.P. to today, the southern core changed to terrestrial.

A "peer advisory group" essentially melds a business advisory board with a peer group. Peer advisory groups consist of business managers who meet together for the purpose of mutual self-improvement and learning through the sharing of experiences. The entire peer advisory group concept encompasses many variations and this research focuses on groups consisting of farm managers. Unfortunately, some farm managers who wish to participate have expressed frustration with group formation: they find it difficult to identify suitable individuals to participate in a peer advisory group with. Peer advisory groups can take many forms, and experts have suggested an individual should specifically seek out people interested in the same type of group. For example, an individual who wants to strictly focus discussion on production issues should seek out other individuals who also seek to focus on production discussions. Some individuals have suggested that some type of "clearinghouse" organizations could be beneficial in assisting individuals with the peer advisory group formation problem. Such an organization would likely need to adapt some sort of method for identifying individuals who have interest in a similar type of group. Although this could be approached from several different angles, one possible approach involves the practice of cluster analysis?a wide set of procedures intended to break down a set of objects into "clusters" of individuals with similar attributes. Cluster analysis comes with several attractive benefits; however, literature includes countless variations in the methods and criticisms of certain aspects of the methodology. This thesis focuses on using cluster analysis to assist with peer advisory group formation. More specifically, this thesis seeks to answer the following question: how could a clearinghouse organization apply cluster analysis methods to a pool of candidates to effectively create peer advisory groups congruent to the individuals' needs and wants? An approach was proposed which differs slightly from traditional cluster analysis methods, and this was applied to a hypothetical pool of candidates, along with several control methods. The proposed approach was found to most effectively create peer advisory groups which fulfilled the desires of the individuals.

Negotiation is one of the key elements in the business activity. Traditional approach to negotiation takes place in a face-to-face environment. E-negotiations present all or part of the negotiating processes through the electronic media or digital channels, to transfer data or to help to achieve better negotiation effects. With the rapid development in E-Commerce, the Internet has becoming an important and inevitable channel of trade and business communication, as well as E-negotiations. Therefore, E-negotiation is progressively popularized and valued. In addition to assisting in communication and decision, the other significant contribution to adopt e-negotiation is to collect the complete and detailed data in every negotiation process, as well as the result. We are able to have clearer understanding in negotiation behavior through analyzing the negotiation behavior data, and therefore will be able to proceed to construct the theory of negotiation. The purpose of negotiations is to successfully agree on, explore which negotiation strategies minister to agreements, and to obtain more knowledge in achieving successful negotiations. Likewise, this is the purpose of this research. Inspire is the first web-based e-negotiation system, and built in 1996. The data collected by this system include users¡¦ demographic data, system usage, offers and counter offers, final agreements, strategy adopted, utility values, and so on. This research has collected 700 pairs of one-to-one negotiation activity records from Inspire negotiation support system, and has grouped negotiators into two groups, cooperative and non-cooperative, using the clustering analysis technology. These two groups manifest differences in the aspects of negotiation outcome and negotiation strategy.

Abstract The near shore water intake pollutants from the land area and is heavily polluted. In order to assess such impact efficiently, the focus of marine environmental monitoring is shifting from inspecting pollutants in a water body to the measurement of pollutants adhered to sediments on seabed. The statistical methods are then used to analyze survey data for the purpose of interpretation. As for the problem of identifying the spatial distributions of classified pollutants over the water around Kaohsiung harbor, the result from the commonly used K-Means Cluster Analysis is not very satisfactory. It is therefore that the proposed research is trying to use the Fuzzy Cluster Method (FCM) to achieve better results. Through adaptive searching approach, the FCM should be able to generate the appropriate cluster centers for discerning the pollutants¡¦ spatial distribution, which in turn would convey more meaning to support feasible interpretation. The FCM model developed by this research will also help to trace the most suspicious or new pollutant source with the assistance from the domain expertise if an unusual pollutant were found in the study area. The benefit is therefore obvious that the authority in charge of marine environment can respond efficiently and correctly against such pollution event and take appropriate actions. FCM has been heavily applied to the research on computer vision and pattern recognition with great success. Recently quite amounts of literatures in the environmental and natural resource management study, including geo-statistical modeling, pollution mitigation, and groundwater quality management, have probed into the applications of cluster analysis using FCM. The problems of marine environment are highly complex and full of uncertainty in nature. Nevertheless by introducing advanced analysis techniques, such as FCM, for tackling such problems, the overall managerial efficiency of marine environment will be improved.