Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/64239
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 | 上傳時間: | 26-Feb-2014 | 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 |
Appears in Collections: | 期刊論文 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
14391460.pdf | 117.74 kB | Adobe PDF2 | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.