Decision support for extracting and dissolving consumers’ uneasiness over foods using stochastic DEMATEL

H. Tamura,H. Okanishi,K. Akazawa

Published 2006 in Journal of Telecommunications and Information Technology

ABSTRACT

In this paper we try to extract consumers’ uneasy factors on foods such as carcinogenic substance, bovine spongiform encephalopathy (BSE) problem, genetic recombination, etc., and try to construct structural models among these uneasy factors using stochastic DEMATEL. Stochastic DEMATEL is developed as a revised DEMATEL (Decision Making Trial and Evaluation Laboratory) to extract structural models of a complex problematique composed of many factors under uncertainty. For structural modeling of uneasy factors on foods we look at the binary relation such that “How much would it help to dissolve uneasy factor j by dissolving uneasy factor i?” Finally, we try to find the priority of dissolving each factor among all the uneasy factors based on the information of stochastic composite importance. This would contribute for decision support to dissolve uneasy feeling and to get sense of security on foods.

PUBLICATION RECORD

  • Publication year

    2006

  • Venue

    Journal of Telecommunications and Information Technology

  • Publication date

    2006-12-30

  • Fields of study

    Agricultural and Food Sciences, Computer Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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