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運用Normalization、TOPSIS與EDAS比較供應商定期績效評核之研究

Comparing Suppliers' Performance Evaluation Rankings Using Normalization, TOPSIS, and EDAS

摘要


沒有優良的原物料無法造就優良的產品,優良的供應商為整個企業流程中的起始,面對工業4.0的激烈競爭環境,企業必須隨時根據內外部的資訊環變化調整其採購行動與策略。現今企業對供應商的評選,已由以往單一的購買成本概念,轉換為多指標的考量供應商整體表現。本研究透過文獻探討找出供應商定期評核的指標,包含:品質(quality)、成本(cost)、交期(delivery)與服務(service)四項指標,並且運用多準則決策分析(multiple criteria decision making, MCDM)方法,比較了大多企業界運用的normalization linear: max計算法與學術界常用的normalization linear: max-min及理想解類似度順序偏好法(technique for order preference by similarity to an ideal solution, TOPSIS),及近幾年新發展的基於平均解距離評價 (evaluation based on distance from average solution, EDAS)等四種方法,來評估供應商評核指標的特徵與權重,並做供應商績效優劣排序。得出排序後,再以統計迴歸分析驗證數據,分析數值排序的相關性與顯著性,提供供應商管理(supplier management)單位作為評選供應商的參考。從結果發現,無論使用哪一種方法,其結果之相似度都相當接近,因此企業界在實務進行供應商績效評核時應參考自身重視之指標與標準,選擇系統性之方法以獲得較客觀之量化數據,以利在進行決策時參考。

並列摘要


Good products cannot be made without good materials. Good suppliers are the starting point of the entire business process. Amidst the fierce competition of Industry 4.0, enterprises must constantly adjust their procurement actions and strategies in response to changes in the internal and external information environment. The selection of suppliers by enterprises has shifted from the single purchase cost of the past to a multi-indicator approach that considers the overall performance of suppliers. The present study uses a literature review to identify the indicators of regular supplier evaluations: quality, cost, delivery, and service. We use multiple criteria decision making to compare the normalization linear: max calculation method used by most enterprises, the normalization linear: max-min and technique for order preference by similarity to an ideal solution (TOPSIS) commonly used in academic research, and the evaluation based on distance from average solution (EDAS) developed in recent years to evaluate the characteristics and weighting of supplier evaluation indicators and rank the performance of suppliers. In this study, we use the above methods to evaluate the supplier's performance of ranking selection. The advantage of normalization is that it is simple and easy to use by general industry. And TOPSIS also considers the positive ideal solution and negative ideal solutions of the distance. And the relative distance can be used as a reference for correcting the ranking of solutions. EDAS is a newer method that can be used to solve complex of ranking selection. After the ranking is obtained, statistical regression analysis is used to verify the data, analyze the correlation and significance of the rankings, and provide supplier management departments with a basis for the selection of suppliers. The results are quite similar regardless of the method used. Therefore, when evaluating the performance of suppliers in practice, enterprises should use the indicators and standards that they regard as important and choose a systematic method to obtain objective quantitative data for reference in decision making.

參考文獻


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被引用紀錄


陳文亮、江雅媚(2024)。產品概念設計品質評價方法之研究品質學報31(1),1-26。https://doi.org/10.6220/joq.202402_31(1).0001

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