Machine learning based control rights analysis of critical resources and the optimal ownership for management integration

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• 作者：Ziyuan Sun ; Yunhai Zhu ; Ying Li ; Mengdi Xie ; Gang Li ; Jianhua Song
• 刊名：Cluster Computing
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：19
• 期：4
• 页码：1925-1935
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Processor Architectures; Operating Systems; Computer Communication Networks;
• 出版者：Springer US
• ISSN：1573-7543
• 卷排序：19

文摘

The paper first divides control rights of critical resources into government macroeconomic regulation power and insider control power for the management. After the discussion of the current status of Chinese coal industry integration, the paper mathematically and empirically analyzes influences of the government and state owned enterprises’ management to ownership’s boundary, and suggests the optimal ownership in different cases. The contributions of the paper are as follows: (1) Based on incomplete contract theory, the paper builds two mathematical models -the model of management’s investment level of relationship-specific human capital and ownership boundary model demonstrating the government utility under different ownership cases; (2) With the application of numerical simulation and empirical test, the paper analyzes impacts on coal resource integration from the aspects of government regulation and insider control, and discusses the optimal option of ownerships. By the analysis of the control power and ownership boundary based on the models, the paper eventually raises the optimal option of ownership allocation.