This study attempts to integrate the decision tree algorithm with the Apriori algorithm to explore the relationship among financial ratio, corporate governance, and stock returns to establish a stock investment decision model. The sports and leisure related industries are employed as the research target. The data are collected and processed for generating decision tree and association rules. Based on the analysis outcome, an investment decision model is constructed for investors expecting to decrease their investment risks and further increase their profits. This stock investment decision model is one type of multiple-criteria decision-making model. This study makes three critical contributions to investors. (1) It proposes a systematical model of exploring related data through the decision tree algorithm and the Apriori algorithm to reveal the implicit investment knowledge. (2) An effective investment decision model is established and expected to provide a reference basis during stock-picking decisions. (3) The investment decision model is enhanced with implicit rules found among variables using association rules.

By determining critical success factors (CSFs), this study intends to identify indicators and offer suggestions for existing owners or operators to improve their critical works in business management, as well as for newcomers interested in investing or studying the chain business. To achieve the purpose of this study, document analysis, expert interviews, and the Delphi technique were used to verify that there are five-dimension indicators to explore the CSFs for tea drink chains. The critical success items in this study are as follows: (1) Regarding “brand image management”, the most critical factors unanimously agreed by the professionals are the certification of raw materials and the guarantee of food safety, which are mainly affected by the recent food safety crisis. (2) Regarding “quality and cost control”, the sub-items of raw material supplier’s stability and timeliness are the most important factors. (3) Regarding the “location of business”, the most important factors are the sub-items of visibility, convergence of people flow, and the structural consumption characteristics of the population in the area. Although these are not considered to be the most important factors in the questionnaires by professionals, the professors considered these sub-items to be the most critical factors in the dimension and should provide valuable references for CSFs. (4) Regarding “personnel training and customer satisfaction”, the sub-item of maintaining hygiene in shop fronts is the most important critical factor, followed by the attitude and affinity of the staff, as well as their clothing, appearance, and cleanliness. (5) Regarding the “marketing mode and promotion mode”, the two important sub-items include new product tasting and the irregular launch of new seasonal products.

In order to reconsider the changes of adjustment speed caused by the recapitalization cost, this research adopted dynamic capital structure theory with adjustment speed as one of the independent variables to analyze the relationship between capital structure and company performance. Instead of applying the commonly used regression models, this research used the decision tree C4.5 algorithm and association rules of priori algorithm. Taking the predictive models created by the decision tree as the main result and supporting it with association rules which help to explain the relationships between capital structure and company performance, this research shows how capital structure influences company performance. As the result presents, a company tends to have better performance when its debt ratio is low, and Tobin’s Q and ROA will turn worse as the ratio gets higher. However, maybe because of the financial leverage, ROE will not decrease when the ratio is high but will increase instead. In addition, this research found out that adjustment speed is negatively related to company performance, meaning that even though a company is more flexible in adjusting itself, it might still perform badly since it is deviating from its optimum leverage. This research found that not only capital structure, but other variables such as price-earnings ratio, research and development expense ratio, and dividend payout ratio also determine a company’s performance.