Applying a hidden Markov chain model in quality function deployment to analyze dynamic customer requirements

Jiunn I. Shieh, Hsin-Hung Wu

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

This study applies a hidden Markov chain model in quality function deployment to analyze dynamic customer requirements from probabilities viewpoints. In reality, the needed probabilities can be computed based upon the experts' opinions for economic conditions as well as the customers' surveys by asking customers' preferences under different economic conditions. Each customer requirement can be analyzed as time goes by. In addition, the changes for each technical measure can be closely examined from time to time. More importantly, when new customers' surveys are conducted and available as well as the new economic conditions analyzed by experts have been updated, both customer requirements and technical measures can be adjusted in a timely basis to reflect and fulfill the dynamic customer requirements. As a result, this proposed approach provides a decision maker to analyze and satisfy both past and present customer needs early on such that a better strategy can be made based upon the most updated customers' surveys and economic conditions.

Original languageEnglish
Pages (from-to)635-644
Number of pages10
JournalQuality and Quantity
Volume43
Issue number4
DOIs
Publication statusPublished - 2009 Jul 1

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Hidden Markov Chain
Markov Chain Model
customer
Customers
Requirements
Economics
economics
expert
Expert Opinion
decision maker

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Social Sciences(all)

Cite this

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Applying a hidden Markov chain model in quality function deployment to analyze dynamic customer requirements. / Shieh, Jiunn I.; Wu, Hsin-Hung.

In: Quality and Quantity, Vol. 43, No. 4, 01.07.2009, p. 635-644.

Research output: Contribution to journalArticle

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