Spatial analysis of big data industrial agglomeration and development in China

• Main Authors: LU, Yanru, CAO, Kai
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: industrial agglomeration; big data industry; GIS; spatial statistics; China; Asian Studies; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5462; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6465&context=sis_research
• Institution: Singapore Management University

Nowadays, our daily life constantly creates and needs to utilize tremendous amounts of datasets. Fortunately, the technologies of the internet, both in software and hardware, have the capability to transmit, store, and operate big data. With China being the most populous country in the world, developing the big data industry is, therefore, seen as an urgent task. As generating industrial agglomeration is important for forming a mature industry, this study aims to characterize the phenomenon of big data industrial agglomeration in China, and to identify the factors for developing the big data industry using spatial analysis approaches and GIS technology from a geographer’s perspective. The problems and strengths of these representative cities are discussed, from which the solutions and the possible directions for the future are also provided. The findings argued that China is still at the primary stage of the development in the big data industry. Only several cities had the presence of a strong agglomeration, but the intercity space spillover was weak. However, comparing the changes in industry distribution, the trend of agglomeration have appeared, and the benefits of industrial agglomeration have also worked. The principal factors of the big data industry and its agglomeration include the support of government and the outstanding higher education agglomeration. In addition, it was also noted that each city has its own characteristics and potentials to attract more big data enterprises, talent, and investment.