The Study on Service Quality and Customer Satisfaction by Applying Artificial Neural Network for Taiwan Power Company--An Empirical Study of Residential Customers in I-Lan County

• Main Authors: Szu-Fu Chang, 張賜福
• Other Authors: Wen-Hai Chih
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/44408514593901809003

碩士 === 國立東華大學 === 企業管理學系 === 91 === Abstract This research is focus on the “Customer Satisfaction” and “Life Style” for the Taipower residential customers, because of electricity liberalization and privatization, Taipower is going to challenge the market they never have. I hope I can offer some useful and valuable information to improve service quality and increase customer satisfaction for Taipower company. The research use questionnaire survey to collect the specific information that I need, second I use “Multivariate Analysis” and “Artificial Neural Network” to code and analyze information after it has been collected. In conclusion, there are four major points: 1. The perceptions of residential customers in I-Lan county about the service quality characteristics of Taipower company are different due to various satisfaction degree. 2. The important service quality characteristics for the Taipower residential customers, there are five very important dimensions: “Service Quality of Staff and Systems”, “Empathy”, “Service Response”, “Environment Clean and Technical Service”, and “Convenience of e-service”. 3. In the service quality dimensions of satisfaction degree, it is significant influence for the customer whole satisfaction degree by “Service Response”, “Empathy”, and “Staff Quality for the Customer Service”. 4. Life style of “Desire Chasing”, “Depend on Electrical”, “Cheerfulness and Happiness”, “Reality”, “Economical”, and “Information Collection” have effect on the conception of the Taipower residential customers. In addition, this research use “Discriminate Analysis” and “Artificial Neural Network” to identify a customer group who identify the difference in quality, The hit rate are 97.10 % and 98.87 %. The statistic results also found that artificial neural network technique got a better classification rate than discriminate analysis method. Keywords: Service Quality, Customer Satisfaction, Life Style, Multivariate Analysis , Artificial Neural Network.