中国互联网发展的区域差异分析

互联网发展的区域差异及其与区域发展的相互影响研究已成为地理学研究中一个新的问题。从网络普及率、网络信息资源丰度及互联网商业应用三个角度初步探讨了中国互联网发展存在的区域差异,并设计了互联网发展指数(IDI)、从人均的角度反映互联网发展的综合水平。表明:东部地区的发展水平明显高于中部和西部地区,但与传统意义上的经济发展梯度不同的是,西部地区的互联网发展水平稍高于中部地区;中国大陆31个省、直辖市、自治区的互联网发展综合水平的差异同样显著,按照IDI值大小被划分为6个等级。互联网发展区域差异的影响因素是多方面的,应用多元回归分析方法研究发现,区域人口素质水平、区域信息和知识生产能力对我国互联网发展区域差异的解释能力最强,区域对外开放程度和区域城市化水平的影响也较显著。

Analysis on the Regional Differential of the Internet Diffusion in China

Internet as a new kind of geographical factor represents an exclusive regional differential features, it attracts more and more concerns of geographers and other discipline researchers as well. Internet in China shows an overwhelming increasing trend recently, though this momentum was commenced late in 1994. According to the report of the China Internet Network Information Center (CNNIC), by December 31, 2002, in Mainland China, there are 59.1 million Internet users, 20.83 million computers connected to the Internet, 179.544 thousand domains registered under ‘CN’, and 371.6 thousand websites under ‘www’. As in many western countries, Internet in China has unevenly diffused from the eastern to the western region and among 31 mainland provincial units. Based on the regularly released data by CNNIC, this study explores regional differential of Internet diffusion in China by quantitative methods. The authors design an Internet Diffusion Index (IDI) to stratify Internet diffusion level of the 31 provincial units. IDI is the geometric mean of 3 indicators; they are Internet users per thousand people, the domain names per 10 thousand people and the websites per 10 thousand people. Given the national average IDI is 1.000, the final results show that the IDI of the eastern coastal region is 1.754, it is much higher than 0.389 of the central region and 0.422 of the western region. However it is easy to find that IDI of the west is slightly higher than that of the central region. The IDI topology is different from that of social and economic development, which has new implication for China's regional development. As to the 31 provincial unites, 6 groups are further sorted out, Beijing and Shanghai rank the highest group, only Guizhou is in the lowest group, 6 coastal provinces are in the second and third groups, the left majorities are distributed in the fourth or fifth groups. By method of Multiple Linear Regression Analysis, the authors further analyses 6 impact factors with 14 variables (V₁-V₁₄). The result shows that human quality and information & knowledge productivity have stronger impact on Internet diffusion than the other 4 factors such as economic development level, opening up level, existing telecommunication infrastructure level and urbanization level. Stepwise Regression Analysis on the 14 variables produces that the standard partial regression coefficients of V₇, V₃,V₈,V₉,V₁₄ and V₁₂ are 0.709,0.595,-0.507, 0.490,-0.405 and 0.096 respectively,which indicates that number of patent per 10 thousand people, number of the high educated per 10 thousand people, share of the import and export value in GDP, hosted foreign tourists per 10 thousand people, urbanization level and regional density of laser cable have strong impact on Internet diffusion.