Affiliation:
1. School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
2. School of Geographical Sciences & Urban Planning, Arizona State University, Tempe, AZ 85287, USA
3. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
Abstract
Urban networks have been widely examined using infrastructure connection and firm connection data. In particular, urban networks constructed based on firm connection data have been used to depict the circulation of capital, information, personnel, and products between cities. Existing studies on firm connection networks rely on either inter- or intrafirm relationships. However, there exist various important extra-firm relationships, such as those between firms and governments, research institutions, and nonprofit organizations. This study innovatively incorporates the extra-firm relationships between governments and firms into urban network construction to provide new insights into the field of urban network research. Using Northeast China as a case study, we construct government procurement activity (GPA) connection networks for both central projects and local projects at the regional and national scales. Social network analysis and regression analysis are used to analyze the network characteristics and factors associated with the network structure. The results show that three provincial capitals (Harbin, Changchun, and Shenyang) hold dominant positions across all the networks. While these capitals serve as GPA suppliers in the region, they are mainly GPA consumers nationally. The factors of spatial proximity, economic development, population, and provincial boundaries were found to be significantly associated with GPA connections. Our study provides important insights into the role of cities in firm-government supply-demand networks. This research can be used to help formulate effective strategies to improve a city’s competitiveness and cities’ cooperation in the GPA supply-demand network.
Funder
National Natural Science Foundation of China
Subject
Multidisciplinary,General Computer Science
Cited by
2 articles.
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