Industry structure optimization via the complex network of industry space: A case study of Jiangxi Province in China.

Based on the complex network of industry space, this paper investigates the industry structure optimization in Jiangxi Province in China. For the prefecture-level cities in Jiangxi Province, the location quotient is applied to obtain the specialized sub-industries. The conditional probability is used to analyze the interdependencies between industries. The complex network of industry space is presented to illustrate the relatedness among industries and analyze the space and structure of the regional overall industry. The index of transitional potential is proposed to measure the potential of a non-specialized industry which will become a specialized one in the future. The transformation difficulty index of industry is obtained to analyze the difficulty level of the transformation of the original specialized industry set to a new specialized one of a city. The results show that more industries have positive than negative interdependencies with one another in Jiangxi Province; rare industries specialize in cities at higher-level GDP, and common industries dominate the cities at lower-level GDP; it is more difficult for rarer non-specialized industries to become specialized ones, more common non-specialized industries can become specialized ones more easily, and the cities with higher GDP can transform industries more easily. By discussing the industries that have positive interdependencies with existing specialized industries, the detailed direction of industry structure optimization is analyzed. Finally, the policy implications are proposed, and these can be applied to other developing countries. • The conditional probability is used to analyze the interdependencies between industries. • The complex network of industry space is presented to illustrate the relatedness among industries. • The index of transitional potential is used to measure the potential of a non-specialized industry becoming specialized. • The transformation difficulty index is the difficulty level of the transformation of the originally specialized industry. • The industry structure can be optimized by developing the industries that have positive interdependencies with existing specialized industries. [ABSTRACT FROM AUTHOR]