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The Effectiveness of Corporate Governance: Moderating Effect of Directorates’ Characteristics and TMT Turnover

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Technology for Education and Learning

Part of the book series: Advances in Intelligent Systems and Computing ((AINSC,volume 136))

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Abstract

This paper analyzes the effectiveness of corporate governance for public listed corporations from the perspective of sensitivity between executive turnover and corporation’s performance.It expands the definition of the effectiveness of corporate governance from two aspects. The paper examines how the characteristics of board of directors can affect the internal relationship between corporation’s performance and executive turnover, in order to test the effectiveness of China’s corporate governance with the listed companies’ data from 2005 to 2009.The research methodology and technical route is as following: evaluating the main effect of board character and performance to effectiveness; testing the interaction of directors’ board to effectiveness of corporate governance through MMR; analyzing moderate effect of controlling turnover and executive turnover. The empirical results show that there is the first kind of effectiveness on corporate governance in China, and an obvious inverted-U relationship is obvious between the size of board of directors and the probability of top management turnover.

This Paper was supported by The National Natural Science Foundation of China (71172216): Research on Neural Mechanism of Management’s Decision-making and TMT Governance Evaluation in Corporate Governance (Principle Investigator: Zhang Guoping); The Major Program of National Natural Science Foundation of China (71132001), The Social Science Planning Foundation of Ministry of Education of China (07JA630073), The China Postdoctoral Science Foundation (20100470156) , The National Natural Science Foundation of China (71102113).

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Correspondence to Guoping Zhang .

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Zhang, G., Fan, T., Wang, Z. (2012). The Effectiveness of Corporate Governance: Moderating Effect of Directorates’ Characteristics and TMT Turnover. In: Tan, H. (eds) Technology for Education and Learning. Advances in Intelligent Systems and Computing, vol 136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27711-5_53

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  • DOI: https://doi.org/10.1007/978-3-642-27711-5_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27710-8

  • Online ISBN: 978-3-642-27711-5

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