利用資料包絡分析法評估第三方物流中心之經營績效

Using Data Envelopment Analysis to Evaluate the Performance of the Third Party Distribution Centers

方雪齡(Hsueh-Lin Fang)

指導教授 ： 丁慶榮

元智大學/工程學院/工業工程與管理學系/碩士(2009年)

https://doi.org/10.6838/YZU.2009.00190

摘要

物流已成為現代企業的核心競爭力，許多企業為暸提升自身競爭力與降低成本，紛紛將企業物流作業委外給專業的第三方物流業者，且因消費者對於商品的需求習慣改變，市場結構不同於以往，這更加速了第三方物流中心的發展，因此對於第三方物流中心而言，如何提昇其經營效率並且有效利用資源，在營運管理上無疑是一大挑戰。本研究針對國內第三方物流業者，研究目的有二，一為藉由問卷調查定義出第三方物流中心業者之關鍵經營績效指標，二為利用資料包絡分析法(Data Envelopment Analysis, DEA)之投入導向衡量各業者間之效率值。
DEA為一線性規劃技術，藉由多投入與多產出的衡量，去評估決策者的效率。本研究由業者關鍵經營績效指標，作為DEA的投入與產出項，藉以分析各物流中心相對有效率與無效率單位之差異，提供無效率物流業者明確之改善方向與建議，及Malmquist生產力指數衡量總要素生產力(Total Factor Productivity, TFP)變動的情況。實證結果發現，經由DEA得知造成經營無效率的原因，大多來自於物流中心的規模無效率，且業者皆處於規模報酬遞增階段，表示舊有的物流中心模式已無法滿足企業與客戶的需求，所以物流中心必須轉變且提昇自我的營運體系，來達到並滿足客戶需求的服務，藉此提高營運績效。另外，從研究結果中，發現影響物流中心之績效的好壞，主要決定於物流中心的人力、資源與設備的分配與使用情況，如何應用最少的資源來達到最大的效益，才是物流中心最重要的營運方向。

關鍵字

第三方物流中心；績效指標；資料包絡分析法；敏感度分析；Malmquist 生產力指數

並列摘要

There has been considerable interest worldwide in last few years in the growth of third party logistics (3PL) providers. 3PL distribution center (DC) enables firms to achieve reduced operating costs and increased revenues. If the DC can capture the performance measure, it can not only provide possible corrective action for the DC but also improve customer services appropriately. Thus, this research aims to find the key performance indicators through a survey of a set of DCs and evaluate their efficiency using data envelopment analysis (DEA) model.
DEA is a non-parametric linear programming technique used to evaluate the efficiency of decision making units where multiple inputs and outputs are involved. To collect the proper data, a survey was first conducted to a set of DC managers and operators to find the key performance indicators. Survey responses regard labor, order fulfillment rate, space utilization, sales and number of orders as the top important indicators. Then the data used in this research were collected for a set of 11 distribution centers operated by 3PL providers during 2005-2007. Three analysis methods are used to evaluate business performance after the results of a input-oriented basic DEA are obtained. These methods, including reference set analysis, sensitivity analysis and slack variable analysis provide improvement suggestions for inefficient DMUs. Malmquist productivity index analysis further evaluates efficiency changes between two years. Our results show that scale inefficiency is the reason for the inefficient DMUs. These inefficient DCs all are in increasing returns to scale (IRS), which means they should invest more on the resources. Comparing the performance indicators, such as labor productivity and return per space used, between efficient and inefficient DMUs, the former ones do yields significant better values than the latter DMUs. Therefore, the application of DEA does provide some opportunities to further benchmark and investigate contributions to efficiency among distribution centers. For the future research, more DC data should be collected and different DEA models could be applied for other benchmark studies.

並列關鍵字

Third Party Distribution Center ； Performance Indexes ； Data Envelopment Analysis ； Sensitivity Analysis ； Malmquist Productivity Index

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