Using Data Envelopment Analysis to Evaluate the Performance of the Third Party Distribution Centers
| Autor: | Hsueh-Lin Fang, 方雪齡 |
|---|---|
| Rok vydání: | 2009 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 97 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. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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