Abstract:This paper mainly studies the impact mechanism of industrial agglomeration of science and technology service industries on industrial upgrading with the help of the statistical data of 31 provinces in China from 2014 to 2018. First, the location entropy method is adopted to measure the degree of industrial agglomeration of science and technology service industries in 31 provinces. Also, a spatial econometric model is built and an empirical analysis is conducted to measure the impact of industrial agglomeration of science and technology service industries on industrial upgrading. Moreover, examined are the impact of education capital agglomeration, market agglomeration, R&D investment and other related factors on industrial upgrading. The results show that industrial agglomeration degree in science and technology service industries differs significantly among different districts of China; that after excluding the influences of control variables such as geographic location advantages and historical accumulation of provinces, agglomeration degree of science and technology industries, with differences in time, space and location, exerts a significant impact on industrial upgrading. Therefore, differentiated policies for China’s future industrial upgrading should be formulated based on the specific features of each province, and it is essential to strengthen industrial agglomeration of science and technology service industries in each province, including the education capital agglomeration, market agglomeration, human capital agglomeration, R&D investment agglomeration, and output value agglomeration, etc., in an effort to facilitate China’s industrial upgrading.