Mining customer knowledge for tourism new product development and customer relationship management Original Research ArticleExpert Systems with ApplicationsIn recent years tourism has become one of the fastest growing sectors of the world economy and is widely recognized for its contribution to regional and national economic development. Tourism product design and development have become important activities in many areas/countries as a growing source of foreign and domestic earnings. On the other hand, customer relationship management is a competitive strategy that businesses need in order to stay focused on the needs of their customers and to integrate a customer-oriented approach throughout the organization. Thus, this paper uses the Apriori algorithm as a methodology for association rules and clustering analysis for data mining, which is implemented for mining customer knowledge from the case firm, Phoenix Tours International, in Taiwan. Knowledge extraction from data mining results is illustrated as knowledge patterns, rules, and knowledge maps in order to propose suggestions and solutions to the case firm for new product development and customer relationship management.Article Outline1. Introduction2. The case firm – the Phoenix Tours International 2.1. Background of the case firm2.2. The new product development procedure of the case firm3. Methodology 3.1. Research framework3.2. Questionnaire design and data collection3.3. Relational database design3.4. Association rule – Apriori algorithm3.5. Clustering analysis4. Research results 4.1. New product development 4.1.1. Travel area – inbound travel (pattern A) 4.1.1.1. Inbound travel association analysis4.1.1.2. Inbound travel cluster analysis4.1.2. Travel area – outbou...
