Applying DEA to Evaluate the Performance of BSMI regional Branches

碩士 === 國立高雄應用科技大學 === 工業工程與管理系碩士在職專班 === 103 === The research is to impersonally evaluate the performance of such as, the vertical and horizontal efficiency and returns to scale of the 6 regional branches of the Bureau of Standards, Metrology and Inspection (BSMI), and to analyze the developing tren...

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Bibliographic Details
Main Authors: Perng-chyuan Wei, 魏鵬權
Other Authors: Lai-Chin Lu
Format: Others
Language:zh-TW
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/pbyre9
Description
Summary:碩士 === 國立高雄應用科技大學 === 工業工程與管理系碩士在職專班 === 103 === The research is to impersonally evaluate the performance of such as, the vertical and horizontal efficiency and returns to scale of the 6 regional branches of the Bureau of Standards, Metrology and Inspection (BSMI), and to analyze the developing trend of the characteristics and stabilities of each individual branches by applying Data Envelopment Analysis (DEA). To find out the major causes of the comparatively inefficient units, so as to provide improving strategies. The empirical research is to do the performance evaluation of the 6 regional branches by using their operational data from 2007 to 2013. The selected inputs are manpower, operational cost, and expenses of instruments & equipment, and the outputs are volume of business and revenue, Then to provide directions and scope for improving to the inefficient units by the slack variable analysis. Summary of the conclusions are: I.From the overall technical efficiency and scale efficiency point of view, unit A is comparatively efficient, and unit B next. II.Units C, D, and F are in increasing status according to the return to scale analysis and should adjust and increase scale of operation. III.According to the benchmarking target analysis, unit A in the years of 2008, 2010, and 2013, unit B in the year of 2012, and unit E in the years of 2011 and 2013 can be benchmarked by those comparatively inefficient units. IV.The window analysis reveals, units A and B are better practices in developing trend of efficiency characteristics and stabilities among all units by the analysis of mean efficiency, variance, composite column range, and total range. V.With the exertion of slack variable to help reaching an optimal scale, the comparatively inefficient units C and F could cut down on manpower, cost, and the expenses of instruments and equipment. Units A, B, and D could increase revenue to the output, and increase volume of business for units C, E, and F.