• DocumentCode
    3213484
  • Title

    Web questionnaire validation and vendor selection using Adaptive Neuro Fuzzy Inference System

  • Author

    Priyal, P. ; Iyakutti, K. ; Devi, S. Prasanna

  • Author_Institution
    Dept. of Comput. Sci., Bharathiar Univ., Coimbatore, India
  • fYear
    2011
  • fDate
    20-22 July 2011
  • Firstpage
    805
  • Lastpage
    808
  • Abstract
    Framing the questionnaire for supplier evaluation and selection is a serious problem in the automobile industry. Particularly, in an e-procurement scenario, the instrument has to be completely tested and verified before publishing the questionnaire for supplier evaluation. Therefore this paper presents an approach for validating the questionnaire using Factor analysis from the data set obtained from the manual records. The factors chosen for supplier evaluation are Cost, Quality, Service, Relationship, Organization and Past relationship. Initially, the 48 questions were confined to the questionnaire which was then confined into 9 components by Factor analysis. Finally the Adaptive Neuro Fuzzy Inference System was trained and tested to rate the supplier using the data collected from the e-procurement system.
  • Keywords
    Internet; automobile industry; fuzzy neural nets; fuzzy reasoning; procurement; Web questionnaire validation; adaptive neuro fuzzy inference system; automobile industry; e-procurement scenario; factor analysis; supplier evaluation; supplier selection; vendor selection; ANFIS prediction; Web based Supplier selection; automobile industry; factor analysis; questionnaire analysis;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Sustainable Energy and Intelligent Systems (SEISCON 2011), International Conference on
  • Conference_Location
    Chennai
  • Type

    conf

  • DOI
    10.1049/cp.2011.0476
  • Filename
    6143425