标题: | 台电输电系统之生产力与效率分析 Productivity and Efficiency of Transmission Systems of the Taiwan Power Company |
作者: | 马伟富 Wei-Fu Ma 胡均立 Dr. Jin-Li Hu 经营管理研究所 |
关键字: | 资料包络分析;Malmquist生产力指数;Tobit回归;效率;输电系统;data envelopment analysis;Malmquist productivity index;Tobit regression;efficiency;transmission system |
公开日期: | 2005 |
摘要: | 本研究采两阶段方法,分析民国89-93年期间台电输电系统之生产力与效率,第一阶段应用资料包络分析法(data envelopment analysis;DEA),依投入项不同的类别建立成本、设备、品质及总体模型,衡量六个供电区营运处之相对效率。第二阶段进行Tobit回归分析,探讨经营无效率的影响因素。最后再以Malmquist生产力指數,分析歷年來生产力的变动情形及累积成长率。 兹将本研究主要实证结果汇总如下: 1、在设备模型的效率分析中,供电辖区位于台湾中、南部的供电区营运处属于无效率的单位,表示台电第六输变电工程的内容应做适当的调整,以避免中、南部因过度投资导致输电设备利用率低,造成资源浪费的情形。 2、由成本、设备及品质模型等不同构面的效率分析结果发现,在单一模型中具有效率的单位,在另一个模型中可能并不具有效率。 3、在敏感度分析方面,就整个输电系统而言,去除变压器装置容量投入项后,效率值变动最大,故变压器装置容量是影响效率的关键因素,其次则是事故次数。 4、在Malmquist生产力指数分析方面,六区的总平均累积成长率达7.15%,表示整个输电系统营运单位的总要素生产力是处于成长的情形。而生产力的成长主要是源自于技术的成长。 5、在Tobit回归分析方面,人口密度及特高压大用户占全台比率越高的地区,越有助于提升输电系统的效率。而输电线路下地率越高,越有助于品质模型的效率提升,但另一方面也将造成成本模型的效率降低。 This paper applies a two-stage method to examine the productivity and efficiency of transmission systems of the Taiwan Power Company (TPC) during the 2000-2004 period. In the first stage data envelopment analysis (DEA) is used to measure the relative efficiency of six electricity transmission districts. This study constructs four DEA models, according to the input categories of cost, equipment, quality, and all of the above. In the second stage a Tobit regression is used to find the effects of environmental variables on efficiency scores. Finally, the Malmquist productivity index is used to compute the longitudinal total-factor productivity (TFP) changes. Our major findings are as follows: 1. Some electricity transmission districts that perform well in one model may not perform well in another model. 2. The population density and rate of extra-high voltage customers have positive impacts on the efficiency of a transmission system. 3. The rate of underground cables has a positive impact on efficiency in the quality model but a negative impact on efficiency in the cost model. 4. Their average accumulative growth rate of TFP is up to 7.15%. 5. Their TFP growth is mainly due to technology innovation. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT009237541 http://hdl.handle.net/11536/77294 |
显示于类别: | Thesis |