Percolation on the institute-enterprise R&D collaboration networks

• Authors: Chenguang Li , Yongan Zhang
• Languages of publication: EN

Abstracts

EN

Realistic network-like systems are usually composed of multiple networks with interacting relations such as school-enterprise research and development (R&D) collaboration networks. Here, we study the percolation properties of a special class of R&D collaboration network, namely institute-enterprise R&D collaboration networks (IERDCNs). We introduce two actual IERDCNs to show their structural properties, and we present a mathematical framework based on generating functions for analyzing an interacting network with any connection probability. Then,we illustrate the percolation threshold and structural parameter arithmetic in the sub-critical and supercritical regimes.We compare the predictions of our mathematical framework and arithmetic to data for two real R&D collaboration networks and a number of simulations. We find that our predictions are in remarkable agreement with the data. We show applications of the framework to electronics R&D collaboration networks

Keywords

EN

networks; percolation; generating function

Discipline

• 64.60.aq: Networks
• 64.60.ah: Percolation

• Publisher: De Gruyter Open
• Journal: Open Physics
• Year: 2015
• Volume: 13
• Issue: 1

Dates

published

1 - 1 - 2015

received

21 - 11 - 2013

accepted

23 - 8 - 2014

online

9 - 10 - 2014

Contributors

author

Chenguang Li

• School of Economics and Management, North China University of Technology, 100144 Beijing, P. R. China

author

Yongan Zhang

• Economics and Management School, Beijing University of Technology, 100124 Beijing, P. R. China

References

• [1] R. Albert, H. Jeong, A. L. Barabasi, Nature 401, 130 (1999)
• [2] D. S. Callaway, M. E. J. Newman, S. H. Strogatz, D. J.Watts, Phys. Rev. Lett. 85, 5468 (2000)
• [3] M. E. J. Newman, Proc. Natl. Acad. Sci. 98, 404 (2001)
• [4] J. Stelling, S. Klamt, K. Bettenbrock, S. Schuster, E. D. Gilles, Nature 420, 190 (2002)
• [5] C. M. Song, S. Havlin, H. A. Makse, Nature 433, 392 (2005)
• [6] J. Nagler, A. Levina, M. Timme, Nat. Phys. 7, 265 (2011)
• [7] Y. Y. Liu, E. Csoka, H. J. Zhou, M. Posfai, Phys. Rev. Lett. 109, 205703 (2012)
• [8] E. A. Leicht, R. M. D’Souza, arXiv:0907.0894 [cond-mat.dis-nn]
• [9] S. V. Buldyrev, R. Parshani, G. Paul, H. E. Stanley, S. Havlin, Nature 464, 1025 (2010)
• [10] R. Parshani, S. V. Buldyrev, S. Havlin, Phys. Rev. Lett. 105, 048701 (2010)
• [11] S. V. Buldyrev, N.W. Shere, G. A. Cwilich, Phys. Rev. E 83, 016112 (2011)
• [12] J. Shao, S. V. Buldyrev, S. Havlin, H. E. Stanley, Phys. Rev. E 83, 036116 (2011)
• [13] J. X. Gao, S. V. Buldyrev, H. E. Stanley, S. Havlin, Nat. Phys. 8, 40 (2012)
• [14] A. Bashan, R. Parshani, S. Havlin, Phys. Rev. E. 83, 051127 (2011)
• [15] X. Q. Huang, J. X. Gao, S. V. Buldyrev, S. Havlin, H. E. Stanley, Phys. Rev. E 83, 065101 (2011)
• [16] T. Fu, Y. N. Chen, Z. Qin, L. P. Guo, Physica A 392, 2807 (2013)
• [17] S. Valverde, R. V. Sole, M. A. Bedau, N. Packard, Phys. Rev. E 76, 056118 (2007)
• [18] M. E. J. Newman, S. H. Strogatz, D. J. Watts, Phys. Rev. E 64, 026118 (2001)
• [19] M. E. J. Newman, Phys. Rev. E 66, 016128 (2002)
• [20] T. Kalisky, R. Cohen, Phys. Rev. E 73, 035101 (2006)
• [21] J. X. Gao, S. V. Buldyrev, S. Havlin, H. E. Stanley, Phys. Rev. Lett. 107, 195701 (2011) [Crossref]

Identifiers

DOI

10.1515/phys-2015-0008