This paper, based on China's resource industries data during 2000 to 2016, studies the temporal-spatial concentration of resource industries via Herfindahl-Hirschman Index (HHI), EG, Locality Entropy, and its changing trend from Theil Index, and analyzes its economic effect of geographic concentration by means of CES. China's resource industries show a remarkable geographic concentration with variances among each industry. Its temporal-spatial changing trend shows a different spatial distribution with leading industries varying with locations, and indicates a diminishing variance among entities within concentrating area, but increasing across areas. It also displays a geographic transfer. Their geographic concentration can promote regional economy, but some may be little even negatively. This paper presents suggestions for resource industries in different regions from boosting resource industries chain management, expanding industrial concentrating effect, intensifying network and coordinated development and materializing resource sharing.

As industrial clusters grow fast, they need to improve their competitiveness and to realize industrial upgrade, which can be reached by using social capitals and increasing organizational learning ability. This paper, based on cases, establishes a conceptual model of industrial cluster competitiveness influenced by social capital from three dimensions of social capital and organizational learning ability, and uses structural function model and Lisrel software to test the assumption. During effects of social capital and organizational learning ability, the three dimensions of social capital, structural, relation and recognition dimensions, promote the organizational learning ability directly and indirectly, and vice versa. This study offers a useful supplement to related theories.