Research on robustness of R&D network under cascading propagation of risk with gray attack information
Yanlu Zhang and
Naiding Yang
Reliability Engineering and System Safety, 2013, vol. 117, issue C, 1-8
Abstract:
Facing the cascading propagation phenomenon of risk in R&D network and the imprecision of attack information, this paper builds the cascading propagation model of risk with gray attack information. In this model, gray attack information described by node degree is measured by negative and positive deviations, and the critical threshold of resisting risk is also proposed as a new indicator of robustness of R&D network. Then the paper analyzes the robustness of R&D network under cascading propagation of risk with gray attack information through numerical simulation. The results show that R&D network has the strongest robustness under random attack, but has the weakest one under intentional attack; robustness of R&D network increases with the increase of deviation from attack information, which becomes increasingly significant when all enterprises' capacities distribution is heterogeneous; robustness of R&D network under one attack decreases with the increasing heterogeneity of all enterprises' capacities distribution; robustness of R&D network is more sensitive to the negative deviation than to the positive deviation from attack information. This research work will provide a theoretical basis for preventing and controlling cascading propagation in R&D network in the future.
Keywords: R&D network; Robustness; Cascading propagation of risk; Gray information; Complex network; Numerical simulation (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832013000793
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:117:y:2013:i:c:p:1-8
DOI: 10.1016/j.ress.2013.03.009
Access Statistics for this article
Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares
More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().