Using DEA model to the efficiency evaluation in top 50 of Taiwan stock market

碩士 === 逢甲大學 === 合作經濟學系 === 104 === In the process of nation’s development, economic fluctuation is easily changed over time. In order to probe into the effect on Taiwanese companies which fluctuation in Taiwan’s business brings, top 50 listed companies in Taiwan are chosen to evaluate the achievemen...

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Bibliographic Details
Main Authors: LIN, TSAI-YIN, 林采瑩
Other Authors: 劉文榮
Format: Others
Language:zh-TW
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/7sy468
Description
Summary:碩士 === 逢甲大學 === 合作經濟學系 === 104 === In the process of nation’s development, economic fluctuation is easily changed over time. In order to probe into the effect on Taiwanese companies which fluctuation in Taiwan’s business brings, top 50 listed companies in Taiwan are chosen to evaluate the achievement. Because of the fact that top 50 listed companies in Taiwan including various industries stand for certain power of influence to some extent, it has much more industrial symbolic features. The industry sample in this research is divided into three parts: electronics industry, traditional industry and the banking business. Data Envelopment Analysis is used to serve as a way to evaluate the performance of the company. By doing so, the condition of resource using of the company can be understood and the result can be reference for the future improvement of operating strategy. The data collected in this research are from Taiwan Economic Journal(TEJ). Thirty-six listed companies except those missing data in the database are chosen to evaluate. The period of the research is from 2004 to 2013. Operating costs, the number of employees and fixed asset are considered as input variables; net operating revenue and revenue and market capitalizatim are considered as output variables. Each performance of the company is presented with the analysis conducted through Data Envelope Analysis. The empirical result suggests that the prime of overall operating performance is 2013, and the worst appears in 2009. Presumably, it is influenced by the financial panic in 2008. According to the result of industrial analysis, it indicates that the failure to reach the best efficiency among three industries respectively are following; lack of input resource to boost the performance in the banking business, too much input resources in electronic industry; excess redundant employees in traditional industry. Additionally, among the thirty-six samples, 16 of them do not have relative efficiency, while they are potential in the future.