Abstract: In the 21st century, with the economic globalization, the third industrial revolution, "four simultaneous", global industrial structure change to “service economy” form and so on, scientific and technological development, financial services, marketing and other productive services as an important component of the service sector producer services, which is becoming an important “weapon” of the regional and urban reconstruct competition pattern, ascend order-scale, and participate in the new international division of labor during economy in the low growth rate of "new normal state" in China. At the same time, the national "13th Five-Year Plan" clearly put forward to speed up the promotion of high-quality and efficient development of services, to promote the production of services to the professional and high-end extension of the value chain.Based on the logic of “quantitative measurement-time-space identification-mechanism analysis”, the mathematical statistics model and GIS spatial analysis technique were used to reveal the evolution characteristics, spatial effect and influencing factors of the 65 counties in Zhejiang Province. So as to provide scientific basis for the overall arrangement and development of producer service industry under the background of new urbanization. The results show that: The scale structure of the producer service system conforms to the order-scale distribution rule of Zipf, and internal six industry spatial agglomeration presents the information service industry as the leading “three gradient” different forms. The evolution of space-time pattern is characterized by low-level homogeneity space to the non-equilibrium spatial polarization of the first-class cities in the municipal districts, especially Hangzhou and Ningbo “double centers”. Finally, the geographical process and pattern are characterized as the result of the nonlinear effect factors such as information technology level, human capital abundance and market development maturity.
Key words：producer services industry; exploratory spatial data analysis; geographically weighted regression; temporal-spatial evolution; Zhejiang