Evolution and Trend Analysis of Research Hotspots in the Field of Pollution-Intensive Industry Transfer—Based on Literature Quantitative Empirical Study of China as World Factory - Feng, Langang; Shang, Shu; Feng, Xin; Kong, Ying; Bai, Jiahe (Frontiers in Environmental Science, 2022)
Background: The transfer of pollution-intensive industries in China accounts for an increasing proportion of industrial transfer, and related studies emerge endlessly. Fully exploring its research and development breadth and depth will help clarify the development trend in this field and point out the direction for future research. Method/Process: From the perspective of bibliometric analysis, with keywords as the core and cluster analysis of research hotspots as the basis, the keywords of pollution-intensive industry transfer in CNKI database are analyzed by CiteSpace software and divided into five categories. Established the text corpus model, and the network analysis transformed into a visual form. Due to the diverse research hotspots in pollution-intensive industry transfer, this article analyzes the evolution of research hotspots in this field to predict its future development trend. Conclusion/Significance: China, as the world’s factory, is affected by relevant policies, and industrial transfers have generally occurred. Industrial transfer, especially the transfer of pollution-intensive industries, has gradually attracted the attention of academic circles and has become a hot topic. When dealing with the transfer of pollution-intensive industries, industrial transfer only transfers pollution across regions. If we want to reduce pollution from the origin, innovation is an essential means. In retrospect, there were rare articles concerning the emerging polluting industries, however, recently since the emerging polluting industries have already constituted as the main source of pollution, more academic attentions are definitely needed. Although the mainstream measurement methods, the related share index method, and the input-output table have their weaknesses, respectively, the deviation share method can overcome the shortcomings of both. Therefore, it can be used as a reference for scholars to measure the transfer of pollution-intensive industries in the future.