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題名 Supplier evaluation model for computer auditing and decision-making analysis
作者 Shih, Kuang-Hsun ; Hung, Hsu-Feng ; Lin, Binshan
貢獻者 企管系
關鍵詞 Computers; Auditing; Internal control; Supplier evaluation; Cybernetics
日期 2009.10
上傳時間 26-Feb-2014 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
資料類型 article
DOI http://dx.doi.org/10.1108/03684920910991469
dc.contributor 企管系en_US
dc.creator (作者) Shih, Kuang-Hsun ; Hung, Hsu-Feng ; Lin, Binshanen_US
dc.date (日期) 2009.10en_US
dc.date.accessioned 26-Feb-2014 15:37:40 (UTC+8)-
dc.date.available 26-Feb-2014 15:37:40 (UTC+8)-
dc.date.issued (上傳時間) 26-Feb-2014 15:37:40 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/64239-
dc.description.abstract (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.en_US
dc.format.extent 120561 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Kybernetes, 38(9), 1439-1460en_US
dc.source.uri (資料來源) http://dx.doi.org/10.1108/03684920910991469en_US
dc.subject (關鍵詞) Computers; Auditing; Internal control; Supplier evaluation; Cyberneticsen_US
dc.title (題名) Supplier evaluation model for computer auditing and decision-making analysisen_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1108/03684920910991469en_US
dc.doi.uri (DOI) http://dx.doi.org/10.1108/03684920910991469en_US