Using a Markov chain model in quality function deployment to analyse customer requirements

Wu, Hsin-Hung; Shieh, Jiunn-I

doi:10.1007/s00170-005-0023-z

Cited by 56 publications

(40 citation statements)

References 10 publications

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“…The decision makers can easily to prioritize the importance of technical measures by their respective future trends. Furthermore, the weight w i for CR i can be described by a Markov chain model (Wu and Shieh 2006). Thus, the computations discussed above would become time-dependent and predictions in terms of the expected values become practical.…”

Section: Rmentioning

confidence: 99%

Applying a markov chain model in quality function deployment

Shieh

2007

Qual Quant

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Section: Rmentioning

confidence: 99%

Applying a markov chain model in quality function deployment

Shieh

2007

Qual Quant

Self Cite

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“…The patent claims that changing customer requirements can be sensitively detected based on the method [18]. Wu and Shieh [19] proposed the application of Markov chain model on QFD to monitor the dynamism of customer requirements from probabilistic viewpoint. Similarly, a dynamic QFD (as opposed to the traditional static versions) was proposed to handle the constantly evolving customer needs [20].…”

Section: Sensitivity To the Changing Needsmentioning

confidence: 99%

Management and forecast of dynamic customer needs: An artificial immune and neural system approach

Chong¹,

Chen²

2010

Advanced Engineering Informatics

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“…Studies of future VOC have been done by Shen et al (2000) through developing fuzzy trend analysis. Their study was extended by Wu and Shieh (2006) by incorporating Markov chain modelling in the HOQ. Markov's processes assume that a system that starts at the initial state will change over time.…”

Section: The Markov Chain Model To Analyse Customer Preference In Thementioning

confidence: 99%

Incorporating Markov chain modelling and QFD into Kansei engineering applied to services

Hartono

Chuan

Ishihara

et al. 2012

IJHFE

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Instead of usability, customers today concern themselves more on satisfying their emotions/Kansei. This paper discusses an integrative framework that incorporates the Kano model, Markov chain, and quality function deployment (QFD) into Kansei engineering (KE). Its purposes are: 1 to exhibit the relationship between service performance and Kansei 2 to enable service designers to establish the extent to which they prioritise their improvement programmes in dealing with current and future preferences. Incorporating Markov chain modelling and QFD into Kansei engineering 75A comprehensive case study involving Indonesian, Japanese, and Singaporean tourists, was carried out. Understanding the cultural differences with respect to Kansei evaluation will yield valuable insights for international marketing strategies.

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Using a Markov chain model in quality function deployment to analyse customer requirements

Cited by 56 publications

References 10 publications

Applying a markov chain model in quality function deployment

Applying a markov chain model in quality function deployment

Management and forecast of dynamic customer needs: An artificial immune and neural system approach

Incorporating Markov chain modelling and QFD into Kansei engineering applied to services

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