The past century was a period of highly active innovation activities, which greatly promoted economic development and social progress. However, with the emergence of gene editing babies, data leakage, environmental pollution and other events, people gradually realized the negative impact of innovation, and thus responsible innovation was born. As the public is one of the important participants in responsible innovation, it is necessary to study the diffusion of the public's responsible innovation behavior. In this paper, a new infectious epidemic model based on two-layers is proposed to explore the influence of information on responsible innovation behavior diffusion. In this paper, the microscopic Markov chain (MMCA) method is used for analysis, and the Monte Carlo (MC) is used for verification. It is found that the transmission rate of information, the forgetting rate of information and other factors will affect the scale and burst threshold of responsible innovation. Through the research on the influencing factors of the diffusion of responsible innovation, we can get inspiration to draw policy inspiration, so as to promote the diffusion of responsible innovation in the public.

Ting Pan. Diffusion of Public Responsible Innovation Behavior in Multiplex Networks. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 14: 100-112. https://doi.org/10.25236/AJCIS.2022.051416.

[1] Macnaghten, P., et al., Responsible innovation across borders: tensions, paradoxes and possibilities. Journal of Responsible Innovation, (2014) 1, 191-199.

[2] Owen, R., P. Macnaghten and J. Stilgoe, Responsible research and innovation: From science in society to science for society, with society. Science and Public Policy, (2012) 39, 751-760.

[3] Stilgoe, J., R. Owen and P. Macnaghten, Developing a framework for responsible innovation. Research Policy, (2013) 42, 1568-1580.

[4] Nelson, J.P., C.L. Selin and C.T. Scott, toward anticipatory governance of human genome editing: a critical review of scholarly governance discourse. Journal of Responsible Innovation, (2021) 8, 382-420.

[5] Buhmann, A. and C. Fieseler, towards a deliberative framework for responsible innovation in artificial intelligence. Technology in Society, (2021) 64, 101475.

[6] Eastwood, C.R., J.P. Edwards and J.A. Turner, Review: Anticipating alternative trajectories for responsible Agriculture 4.0 innovation in livestock systems. Animal, (2021) 15, 100296.

[7] Rose, D.C., et al., Agriculture 4.0: Making it work for people, production, and the planet. Land Use Policy, (2021) 100, 104933.

[8] Klerkx, L. and D. Rose, Dealing with the game-changing technologies of Agriculture 4.0: How do we manage diversity and responsibility in food system transition pathways? Global Food Security, (2020) 24, 100347.

[9] Eastwood, C., et al., Managing Socio-Ethical Challenges in the Development of Smart Farming: From a Fragmented to a Comprehensive Approach for Responsible Research and Innovation. Journal of Agricultural and Environmental Ethics, (2019) 32, 741-768.

[10] Inigo, E.A. and V. Blok, Strengthening the socio-ethical foundations of the circular economy: Lessons from responsible research and innovation. Journal of Cleaner Production, (2019) 233, 280-291.

[11] Halme, M. and M. Korpela, Responsible Innovation toward Sustainable Development in Small and Medium-Sized Enterprises: a Resource Perspective. Business Strategy and the Environment, (2014) 23, 547-566.

[12] Chilvers, J. and M. Kearnes, Remaking Participation in Science and Democracy. Science, Technology, & Human Values, (2020) 45, 347-380.

[13] Brand, T. and V. Blok, Responsible innovation in business: a critical reflection on deliberative engagement as a central governance mechanism. Journal of Responsible Innovation, (2019) 6, 4-24.

[14] Moore, C. and M.E.J. Newman, Epidemics and percolation in small-world networks. Physical Review E, (2000) 61, 678-5682.

[15] Zanette, D.H., Critical behavior of propagation on small-world networks. Physical Review E, (2001) 64, 050901.

[16] Zanette, D.H., Dynamics of rumor propagation on small-world networks. Physical Review E, (2002) 65, 041908. 

[17] Pastor-Satorras, R. and A. Vespignani, Epidemic Spreading in Scale-Free Networks. Physical Review Letters, (2001) 86, 3200-3203.

[18] Granell, C., S. Gómez and A. Arenas, Dynamical Interplay between Awareness and Epidemic Spreading in Multiplex Networks. Physical Review Letters, (2013) 111, 128701.

[19] Granell, C., S. Gómez and A. Arenas, Competing spreading processes on multiplex networks: Awareness and epidemics. Physical Review E, (2014) 90, 012808.

[20] Zheng, C., et al., Interplay between SIR-based disease spreading and awareness diffusion on multiplex networks. Journal of Parallel and Distributed Computing, (2018) 115, 20-28.

[21] Silva, D.H., C. Anteneodo and S.C. Ferreira, Epidemic outbreaks with adaptive prevention on complex networks. Communications in Nonlinear Science and Numerical Simulation, (2023) 116, 106877.

[22] Xia, C., et al., A new coupled disease-awareness spreading model with mass media on multiplex networks. Information Sciences, (2019) 471, 185-200.

[23] Wang, Z. and C. Xia, Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media. Nonlinear Dynamics, (2020) 102, 3039-3052.

[24] Wang, Z. and Y. Guo, Rumor events detection enhanced by encoding sentimental information into time series division and word representations. Neurocomputing, (2020) 397, 224-243.