Identifying Strategic Groups with the Data Envelopment Analysis Method–Taking Taiwan Banking Industry as An Example

碩士 === 義守大學 === 工業工程與管理學系碩士班 === 95 === In the recent years, our government allows establishing new banks, impels liberalization and internationalization of the finance, and deregulates and decontrols banking limitations of the finance. The competitive environment in banking industry is changing and...

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Bibliographic Details
Main Authors: Li-Jung Lin, 林俐蓉
Other Authors: I-Ming Chao
Format: Others
Language:en_US
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/99437172711648690959
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Summary:碩士 === 義守大學 === 工業工程與管理學系碩士班 === 95 === In the recent years, our government allows establishing new banks, impels liberalization and internationalization of the finance, and deregulates and decontrols banking limitations of the finance. The competitive environment in banking industry is changing and its uncertainty in increasing, and as numbers of banks rising, the industry turns monopoly market into battle competitive market. Although, the industry is legally divided into commercial, professional, and savings bank, due to the competition of the market and the innovative of the banking, numerous banks in Taiwan extent their product scopes and assert diversification. Therefore, whether domestic bankers can catch the chance, avoid danger of competitive environment, select appropriate competitive strategy and competitive advantage becomes very important to the industry. Identifying and analyzing strategic groups can afford an approach to catch competitive construction of the intra-industry. The strategic groups can help bakers to know the opposable competitive position, real competition and competitive way of each bank. This thesis takes Taiwan banking industry as an example, to begin from the thought of strategic groups, and then to get the weights and efficiency values from the Data Envelopment Analysis. For hψ=1 we define that DMUψ is a strategic leader (SL) since they are in the frontiers of the efficiency, and when hψ<1, DMUψ is not on the frontier and in defined as a strategic follower(SF). And then we use the cluster analysis to identify strategic groups with strategic leaders’ weights and the strategic followers are clustered according to their reference leaders. We analyze domestic banks in years from 2004 to 2006 individually, and the result shows that we can divide the domestic banks into three clusters of strategic groups. Besides, we also use the Malmquist Productivity Index to analyze domestic banks in the three years and regard the relatively efficiency value CCR (2006) as X axis; and the Malmquist Productivity Index as Y axis; we want to know the efficiency change of domestic banks during three years. By the results of the scatter plot which arise from X axis and Y axis, we can divide the domestic banks into six groups. By identifying the strategic groups of domestic bank can help each bank catch its competitive position and whether belong to strategic group that can provide reference for each bank to make future development decisions.