Exploring the dynamics of the disaggregated intercity corporate network in the Yangtze River Delta, China: a relational event approach

Luqi Li (), Ben Derudder (), Wei Shen () and Xiang Kong ()
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Luqi Li: Zhejiang University of Technology
Ben Derudder: Ghent University
Wei Shen: Deakin University
Xiang Kong: East China Normal University

Journal of Geographical Systems, 2022, vol. 24, issue 1, No 7, 115-140

Abstract: Abstract There has been a proliferation of studies trying to explain the driving forces behind the formation and evolution of intercity corporate networks. Previous approaches, however, require the input of aggregated data such as the connectivities of cities, a static network or a few discrete-time network snapshots. This may potentially cause the loss of information on the microscopic dynamics in corporate networks. In this paper, we explore the use of an approach invoking relational event models (REM), which has the advantage of being able to directly process continuously recorded disaggregated data on the establishment of each office. This allows for a more fine-grained analysis of the dynamics underlying the formation of the network. To demonstrate its potential in this research field, this paper applies REM to explain the temporal dynamics of the intercity corporate network in the Yangtze River Delta region of China. The result shows that there are preferential attachment and persistence effects in the evolution of the network, and this alongside the impact of several city covariates. Nonetheless, REM relies on event history and cannot model the forward-looking process in firms’ location choice. The lack of detailed information regarding the date of the establishment of offices also poses a challenge to the application of REM in the study of corporate networks. We also conclude that it may be fruitful to apply REM to other forms of intercity networks, especially those significantly affected by event histories, such as commuting and knowledge networks.

Keywords: Intercity corporate networks; Relational event models; Disaggregated data; Dynamics; Yangtze River Delta (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10109-021-00358-2

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