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    政大機構典藏 > 商學院 > 企業管理學系 > 期刊論文 >  Item 140.119/64239


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    题名: Supplier evaluation model for computer auditing and decision-making analysis
    作者: Shih, Kuang-Hsun;Hung, Hsu-Feng;Lin, Binshan
    贡献者: 企管系
    关键词: Computers;Auditing;Internal control;Supplier evaluation;Cybernetics
    日期: 2009.10
    上传时间: 2014-02-26 15:37:40 (UTC+8)
    摘要: Purpose – The purpose of this paper is to present a model and a supporting approach for effective supplier selection decisions. Design/methodology/approach – Structural equation modeling (SEM) and confirmatory factor analysis are applied to test the evaluation principles and samples. Next, the data tested by SEM is used for artificial neural network (ANN) by Likert and fuzzy scales to structure a classification model, accompanying with canonical discriminate analysis (CANDISC) to diminish variables. After the training and test of the model, multiple discriminate analysis is applied to compare the accuracy of the classification. Last, the CANDISC variable reduction method with ANN classification model utilized in the study is applied. Findings – The supplier selection model designed with ANN classification model and fuzzy scales will be more effective than with the traditional statistics analysis. Research limitations/implications – The new paradigm for decision making includes a combination of several effective methods and analysis. Practical implications – This research provides an integrated model for internal auditors and managers to classify their supplier selection decisions. Originality/value – This paper contributes to the new approach of the decision model building process for computer auditing and improves the classification accuracy effectively.
    關聯: Kybernetes, 38(9), 1439-1460
    資料來源: http://dx.doi.org/10.1108/03684920910991469
    数据类型: article
    DOI 連結: http://dx.doi.org/10.1108/03684920910991469
    DOI: 10.1108/03684920910991469
    显示于类别:[企業管理學系] 期刊論文

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