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Articles

Evolution Roadmap Decomposition Model for Resource Dependency During the Process of Economy Transformation

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  • 1. Department of Economics and Management, North China Electric Power University, Baoding 071003, China;
    2. School of Economics and Management, North China Electric Power University, Beijing 102206, China

Received date: 2014-06-15

  Revised date: 2014-12-18

  Online published: 2016-03-18

Abstract

Economic transformation is essential for many resource-based areas. To identify the driving force and resistance factors of the transformation and to evaluate the effects of sustainable development, an evolution roadmap decomposition model for resource dependency is proposed in this paper. Based on the consideration of the geographical components of an economy, the differential to the resource dependency is used to indicate the beginning of the decomposition model. After designing the mean algorithm to solve the problems existed in calculating the definite integral, the complete resource dependency decomposition equation is obtained. By using this model, the change of the resource dependency for an economy can be decomposed to the summation of the contribution of each component through each influence factor in each year. Furthermore, the change of the resource dependency for Shanxi province during 2006-2012 is decomposed by the proposed model and the following conclusions are drawn. 1) The decrease of resource dependency of Shanxi province depended mainly on the "natural" transformation and the changes of the relative development speed of different areas have hindered the transformation; as well as 2) The sustainable development rank from the fast to the slow of all the considered areas is Shuozhou, Yangquan, Jincheng, Xinzhou, Changzhi, Jinzhong, Datong, Taiyuan, Linfen, and Lvliang.

Cite this article

MENG Ming, NIU Dong-xiao, XU Xiao-min . Evolution Roadmap Decomposition Model for Resource Dependency During the Process of Economy Transformation[J]. Chinese Journal of Management Science, 2016 , 24(3) : 18 -23 . DOI: 10.16381/j.cnki.issn1003-207x.2016.03.003

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