An Application of Data Envelopment Analysis and Malmquist Index to Measure the Relative Performance of Commissaries in Taiwan

碩士 === 國防管理學院 === 國防財務資源研究所 === 92 === Sales in the National Defense Welfare Department of the welfare merchandise has been limited in its business operation and development. The operation in the General Welfare Department has become increasingly difficult under the current environment of market sa...

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Bibliographic Details
Main Author: 葉正國
Other Authors: Wei-Kang Wang
Format: Others
Language:zh-TW
Published: 2004
Online Access:http://ndltd.ncl.edu.tw/handle/41068004472133866612
Description
Summary:碩士 === 國防管理學院 === 國防財務資源研究所 === 92 === Sales in the National Defense Welfare Department of the welfare merchandise has been limited in its business operation and development. The operation in the General Welfare Department has become increasingly difficult under the current environment of market saturation. The supply stations of the welfare merchandise should devote themselves to raise their business operation efficiency to achieve their organizational goal in caring the welfare of the military personnel''s families. The main purpose of the efficiency evaluation is to diagnose, with the evaluation results, the evaluated units’ business management condition and, further, to improve the current condition and bring up proposals. Since the Data Envelopment Analysis Method (DEA) possesses a capability in handling multiple inputs and production outputs and in self-assigning weights without the need to preset a production function, this method has been becoming mature and can be objectively proceeded in efficiency evaluation. The empirical results show that there exist significant differences in efficiency performances among the West, the East, the South and the North districts in comparing their business performances. We also examine levels and trends in sales and productivity in 31 welfare supply stations over three years. The study uses DEA to derive Malmquist productivity indexes. In considering the differences of productivity among four distinct districts, the results reveal that there are no significant differences among them.