Mining demand chain knowledge of life insurance market for new product development

  • Authors:
  • Shu-Hsien Liao;Ya-Ning Chen;Yu-Yia Tseng

  • 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;Department of Management Sciences and Decision Making, Tamkang University, No. 151, Yingjuan Rd., Danshuei Jen, Taipei 251, Taiwan, ROC

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

Demand chain management (DCM) can be defined as ''extending the view of operations from a single business unit or a company to the whole chain. Essentially, demand chain management focuses not only on generating drawing power from customers to purchase merchandises on the supply chain; but also on exploring satisfaction, participation, and involvement from customers in order for enterprises to understand customer needs and wants. Thus, customers have changed their position in the demand chain to assume a leading role in bringing more benefit for enterprises. This article investigates what functionalities best fit the consumers' needs and wants for life insurance products by extracting specific knowledge patterns and rules from consumers and their demand chain. By doing so, this paper uses the a priori algorithm and clustering analysis as methodologies for data mining. Knowledge extraction from data mining results is illustrated as market segments and demand chain analysis on life insurance market in Taiwan in order to propose suggestions and solutions to the insurance firms for new product development and marketing.