| Summary: | 碩士 === 國立彰化師範大學 === 企業管理學系 === 101 === Since the early 1990s, many traditional industries in Taiwan were closed and allocating their operations overseas due to increased production costs and the trend of globalization. The Ministry of Economic Affairs had to foster ineffective and inefficient traditional industries and enterprises to transform into tourism factories since 2003. Thus, tourism factories become the new focus by domestic enterprises when the elements of tourism and leisure are introduced. According to the statistics from Industrial Development Bureau, Ministry of Economic Affairs, the factory tourists were roughly more than tens of millions of people and to create the output value of several hundred million NT dollars together with hundreds of millions NT dollars in related service sector.
With this new trend along with customer-oriented era, it is critically important for tourism factories to maintain competitiveness by increasing customers’ purchase willingness and enhancing their profitability. In this study we use Brand’s Health Museum as the object example, using data mining techniques to explore the impact of demographic variables on customers’ purchase intentions during the factory tour. We use two-step Bayesian Network, Bayesian Network with dimension reduction, and other prediction models to analyze customers' purchase intentions. After further analysis by performance evaluation, the best model was selected for this study. The evaluation results show that the best mode for the predicted demographic variables of customers' purchase intentions was two-step Bayesian Network analysis.
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