4.6 Article

Assessing the Attraction of Cities on Venture Capital From a Scaling Law Perspective

Journal

IEEE ACCESS
Volume 9, Issue -, Pages 48052-48063

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3068317

Keywords

Urban areas; Investment; Venture capital; Statistics; Sociology; Companies; Industries; Venture capital investment; complex systems; urban scaling laws; scale-invariant indicator; growth

Funding

  1. National Natural Science Foundation of China [61903020]
  2. Beijing University of Chemical Technology (BUCT) Talent Start-up Fund [BUCTRC201825]
  3. NSF [PHY-1505000]
  4. Defense Threat Reduction Agency [HDTRA1-14-1-0017]

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This study reveals a clear nonlinear scaling relationship between venture capital activities and urban population in Chinese cities. Different sized cities exhibit varying fluctuations and growth trends in venture capital activities, indicating distinct dynamics and development modes within urban agglomeration regions.
Cities are centers for the integration of capital and incubators of inventions. Attracting venture capital (VC) is of great importance for cities to advance in innovative technology and business models towards a sustainable and prosperous future. Yet we still lack a quantitative understanding of the relationship between urban characteristics and VC activities. In this paper, we find a clear nonlinear scaling relationship between VC activities and the urban population of Chinese cities. In such nonlinear systems, the widely applied linear per capita indicators would be either biased to larger cities or smaller cities depends on whether it is superlinear or sublinear, while the residual of cities relative to the prediction of scaling law is a more objective and scale-invariant metric. Such a metric can distinguish the effects of local dynamics and scaled growth induced by the change of population size. The spatiotemporal evolution of such metrics on VC activities reveals three distinct groups of cities, two of which stand out with increasing and decreasing trends, respectively. The taxonomy results together with spatial analysis also signify different development modes between large urban agglomeration regions. Besides, we notice the evolution of scaling exponents on VC activities are of much larger fluctuations than on socioeconomic output of cities, and a conceptual model that focuses on the growth dynamics of different sized cities can well explain it, which we assume would be general to other scenarios.

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