Research on product common attribute model with consumption value theory applied in food industry

T. Y. Chen, Y. C. Liu, Y. M. Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Knowing why consumers choose their favorite products can help enterprises to stay ahead of market trends and thereby increase profits and reduce losses. There are various theories which attempt to explain what happens in the minds of consumers when they purchase a product. However, methods of applying these theories to an enterprise are needed but are rarely discussed in the literature even though having a practical method of understanding consumer thinking would help enterprises understand those proposed theories easily. In this study, we propose a Product Common Attribute (PCA) model and provide quantified values to help enterprises to apply consumption value theory to their products. Because it is difficult to quantify each value index of a consumption value theory, the PCA model is proposed to correspond to the five value indices of consumption value theory, incorporating a questionnaire survey to verify the corresponding relationships. Consequently, this study quantifies and applies the relationship between the PCA model and consumption value theory.

Original languageEnglish
Title of host publicationIEEE International Conference on Industrial Engineering and Engineering Management
PublisherIEEE Computer Society
Pages447-451
Number of pages5
ISBN (Electronic)9781479909865
DOIs
Publication statusPublished - 2014 Nov 18
Event2013 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2013 - Bangkok, Thailand
Duration: 2013 Dec 102013 Dec 13

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Other

Other2013 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2013
Country/TerritoryThailand
CityBangkok
Period13-12-1013-12-13

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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