Mining customer knowledge for tourism new product development and customer relationship management

  • Authors:

  • Shu-hsien Liao;Yin-Ju Chen;Min-yi Deng

  • Affiliations:

  • Department of Management Sciences and Decision Making, Tamkang University, No. 151, Yingjuan Rd., Danshuei Jen, Taipei 251, Taiwan, ROC;Department of Management Sciences and Decision Making, Tamkang University, No. 151, Yingjuan Rd., Danshuei Jen, Taipei 251, Taiwan, ROC;Graduate School of Resource Management, National Defense University, Management College, P.O. Box 90046-17 Jon-Ho, Taipei County, Taiwan, ROC

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2010

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Abstract

In 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.