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A Stochastic Actor-Based Modelling of the Evolution of an Intercity Corporate Network

Author

Listed:
  • Xingjian Liu

    (Department of Geography, University of Cambridge, Downing Place, Cambridge CB2 3EN, England)

  • Ben Derudder

    (School of Geography and Environmental Science, Monash University, Vic 3800, Australia, and Geography Department, Ghent University, Belgium)

  • Yaolin Liu

    (MOE Key Laboratory of GIS and School of Resource and Environmental Science, Wuhan University, Wuhan, China 430079)

  • Frank Witlox

    (Geography Department, Ghent University, 9000 Ghent, Belgium)

  • Wei Shen

    (ESSCA Graduate School of Management in Angers, 49003 Angers Cedex 1, France)

Abstract

We adopt a stochastic actor-based modelling framework to present a longitudinal analysis of an intercity corporate network formed by 53 globalised advanced producer service firms across 107 cities for three different time points in the period 2000–10. Our longitudinal framework allows us to investigate the different processes underlying firm networks' dynamics. The observed network changes are explained by a combination of exogenous city characteristics (eg, GDP and population) and endogenous local network structures (eg, ‘star’ and ‘4-cycle’ structures). Our analysis contributes to an understanding of how interactions amongst cities and firms at the local scale give rise to the empirically observed network patterns at the global scale.

Suggested Citation

  • Xingjian Liu & Ben Derudder & Yaolin Liu & Frank Witlox & Wei Shen, 2013. "A Stochastic Actor-Based Modelling of the Evolution of an Intercity Corporate Network," Environment and Planning A, , vol. 45(4), pages 947-966, April.
    • Handle: RePEc:sae:envira:v:45:y:2013:i:4:p:947-966
    DOI: 10.1068/a45350
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    References listed on IDEAS

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    Cited by:

    1. Luqi Li & Ben Derudder & Wei Shen & Xiang Kong, 2022. "Exploring the dynamics of the disaggregated intercity corporate network in the Yangtze River Delta, China: a relational event approach," Journal of Geographical Systems, Springer, vol. 24(1), pages 115-140, January.
    2. Chong, Zhaohui & Wei, Xiaolin, 2023. "Exploring the spatial linkage network of peer-to-peer lending in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    3. Guo, Ying & Cao, Lingyan & Song, Ying & Wang, Yan & Li, Yongkui, 2022. "Understanding the formation of City-HSR network: A case study of Yangtze River Delta, China," Transport Policy, Elsevier, vol. 116(C), pages 315-326.
    4. Xu Zhang & Yajuan Li, 2019. "Serving the culture: Spatial interactions between cultural industries and advanced producer services in mainland China," Environment and Planning A, , vol. 51(2), pages 374-392, March.
    5. Stefan Hennemann & Ben Derudder, 2014. "An Alternative Approach to the Calculation and Analysis of Connectivity in the World City Network," Environment and Planning B, , vol. 41(3), pages 392-412, June.
    6. Vladimír Pažitka & Dariusz Wójcik, 2021. "The network boundary specification problem in the global and world city research: investigation of the reliability of empirical results from sampled networks," Journal of Geographical Systems, Springer, vol. 23(1), pages 97-114, January.
    7. Tom Broekel & Marcel Bednarz, 2018. "Disentangling link formation and dissolution in spatial networks: An Application of a Two-Mode STERGM to a Project-Based R&D Network in the German Biotechnology Industry," Networks and Spatial Economics, Springer, vol. 18(3), pages 677-704, September.
    8. David Emanuel Andersson & Saileshsingh Gunessee & Christian Wichmann Matthiessen & Søren Find, 2014. "The Geography of Chinese Science," Environment and Planning A, , vol. 46(12), pages 2950-2971, December.

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