Network effect of knowledge spillover: Scale-free networks stimulate R&D activities and accelerate economic growth
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DOI: 10.1016/j.physa.2016.04.005
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Cited by:
- Liu, Hui & Su, Bingbing & Guo, Min & Wang, Jingbei, 2024. "Exploring R&D network resilience under risk propagation: An organizational learning perspective," International Journal of Production Economics, Elsevier, vol. 273(C).
- Mao, Chongfeng & Yu, Xianyun & Zhou, Qing & Harms, Rainer & Fang, Gang, 2020. "Knowledge growth in university-industry innovation networks – Results from a simulation study," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
- Zeng, Yongchao & Shi, Yingying & Shahbaz, Muhammad & Liu, Qin, 2024. "Scenario-based policy representative exploration: A novel approach to analyzing policy portfolios and its application to low-carbon energy diffusion," Energy, Elsevier, vol. 296(C).
- Zhu, He & Ma, Jing, 2018. "Knowledge diffusion in complex networks by considering time-varying information channels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 225-235.
- Wang, Ding & Guo, Peng & Kilgour, D. Marc & Ponnambalam, Kumaraswamy & Hipel, Keith W., 2022. "The evolution of R&D collaboration in inter-organizational project networks: Effects of reference points for competitive preference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
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Keywords
Scale-free networks; Network heterogeneity; Knowledge spillover process; Complex networks; Economic growth; Research and development (R&D);All these keywords.
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