An Identification of Industrial Functional Zones Based on NLP: Evidence From Online Commercial Registration Data

Author:

Ma Yuanting12,Sun Yong3,Weng Futian4,Xu Yan15ORCID

Affiliation:

1. Ocean University of China, Qingdao, China

2. East China Jiaotong University, Nanchang, China

3. Guangzhou University, Guangzhou, China

4. Xiamen University, Xiamen, China

5. Dongbei University of Finance and Economics, Dalian, China

Abstract

The identification of spatial layout and functional characteristics among industrial clusters is vital to support the development of regional industries. Based on the industrial registration data of more than 330,000 companies in “The First Industrial Clusters in China,” and natural language processing methods (NLP), a set of identification framework for urban industrial functional zones is constructed by introducing commercial registration data and electronic map location data to deal with complex industrial big data, realizing the recognition of industrial spatial layout and functional characteristics of Nanshan. The results show that the industrial coverage of Nanshan is as high as 79.07%, and the wholesale and retail enterprises are its main bodies. Among the nine industrial functional zones, emerging enterprises accounted for the majority and diversified agglomeration areas were more than specialized agglomerations in capital scale and employability. Thus, in future industrial planning, maintaining a diversified industrial agglomeration, while giving more policy favor to functional zones characterized by wholesale and retail, can better stimulate consumption and promote economic development in the region.

Funder

Research Project of Dongbei University of Finance and Economics

Scientific Research Project of Liaoning Education Department

Humanities and Social Sciences of Ministry of Education Planning Fund

Special fund project for graduate innovation in Jiangxi Province in 2021

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

General Social Sciences,General Arts and Humanities

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