A Decision Model to Predict the Optimal Size of the Diversified Management Industry from the View of Profit Maximization and Coordination of Industrial Scale

Li, Chong-Mao, Cui, Tao, Nie, Rui, Shan, Yuli, Wang, Juan and Qian, Xiangyan (2017) A Decision Model to Predict the Optimal Size of the Diversified Management Industry from the View of Profit Maximization and Coordination of Industrial Scale. Sustainability, 9 (4). ISSN 2071-1050

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Abstract

To avoid the risk of single and homogeneous development, China’s coal enterprises have explored a diversified development model and are actively developing coal-based industries such as electric power, coal chemical, coal equipment manufacturing, logistics, and building materials. In previous studies of the diversification strategy, the focus has been placed on the motivation for diversification, the measurement of diversification, and the relationship between diversification and enterprise performance. From an enterprise strategic decision, we predicted the optimal size of each industry by considering the limited enterprise capital, human resources, the synergetic relationship among industrial clusters (mainly the scale coordination), and policy factors. The optimal decision model for diversified industrial management was constructed using linear programming methods. The decision target was to maximize the enterprise’s profit, but to also consider the social and environmental benefits. One of the largest listed coal enterprises in China, China Coal Energy (also a typical diversified enterprise), was selected as a case for analysis. Data were collected from surveys and annual reports from 2010 to 2014. The optimal scales of coal, electric power, chemical, and equipment manufacturing were predicted, and could be used as a reference for future enterprise production decisions. Furthermore, this decision model can be used as a reference for other diversified enterprises.

Item Type: Article
Faculty \ School: Faculty of Social Sciences > School of International Development
Related URLs:
Depositing User: Pure Connector
Date Deposited: 20 May 2017 05:05
Last Modified: 22 Apr 2020 04:37
URI: https://ueaeprints.uea.ac.uk/id/eprint/63567
DOI: 10.3390/su9040642

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