SCIENTIA GEOGRAPHICA SINICA ›› 2018, Vol. 38 ›› Issue (2): 214-222.doi: 10.13249/j.cnki.sgs.2018.02.007

• Orginal Article • Previous Articles     Next Articles

Coupling Coordination and Spatio-temporal Differentiation of Scientific and Technological Innovation and Sustainable Development in China

Chuansong Zhao(), Jianlan Ren, Yanbin Chen, Kai Liu   

  1. College of Geography and Environment, Shandong Normal University, Jinan 250014, Shandong, China
  • Received:2017-03-02 Revised:2017-12-14 Online:2018-04-10 Published:2018-04-10
  • Supported by:
    National Natural Science Foundation of China (41571525)


'There would be no sustainable development without science', which has been proposed by UNESCO at the United Nations Conference on Environment and Development. The relationship between scientific and technological innovation and sustainable development has become an important part of sustainable development theory. Both of them have natural interaction and mutual relations, restricting and promoting each other. Sustainable development goals can be achieved through scientific and technological innovations, and scientific and technological innovations maintain positive interaction with society for recognition and support by the concept of sustainable development. Based on Chinese relevant data about scientific and technological innovation and sustainable development from 1995 to 2014, this paper analyzes the interaction mechanism of scientific and technological innovation and sustainable development. Using entropy method, coupling coordination degree model and exploratory data analysis method, this paper analyzes the coupling degree and spatio-temporal differentiation of scientific and technological innovation and sustainable development, and comes to the following conclusion. At first, scientific and technological innovation and sustainable development shows a positive correlation and a high consistency in both sectional evolution and overall development, and the coupling coordination degree tends to rise to a stage of highly coupling and coordinating steadily. Secondly, the coupling degree of scientific and technological innovation and sustainable development shows a weak positive correlation in space, the degree of spatial agglomeration is not significant, and the spatial clustering distribution has not enhanced with time. Finally, from the perspective of spatial and temporal evolution, the local spatial autocorrelation regularity is obvious. The regional scale of HH gradually spreads, and mainly concentrates in the eastern coastal areas; LH area, which concentrates in the central and western regions, is the most extensive, and shows the situation from the scattered to the contiguous; LL regional range changes significantly with the overall shrinking trend, and the spatial distribution transits from midwest to northwest region; HL area is relatively less stable, and the scope tends to focus on the Yangtze River Economic Belt. Although the different agglomeration areas show expansion and contraction in the evolution of time and space, the general spatial pattern is high in east and low in west, and the gap between east and west is gradually narrowing. Accordingly, HH area should continue to maintain good momentum of development, and play a leading role in technology diffusion and radiation. Meanwhile, LL area should be further developed due to the policy support of the country to increase R&D investment and to focus on the introduction of technology digestion and absorption, and this area should learn advanced experience actively and dock industry shift from eastern coastal areas. With scientific and technological innovation, this area will change the development way to achieve the corner overtaking. HL and LH areas should strengthen cross-regional cooperation and enhance hard and soft power to promote coordinated development of scientific and technological innovation and sustainable development.

Key words: scientific and technological innovation, sustainable development, coupling coordination degree, explore spatial data analysis

CLC Number: 

  • G311