Studying the Application of Epidemic Theory in Transmission Cycle of Technology: A Case Study of Nanotechnology Patent

Faramarz Soheili, Saleh Rahimi, Ali Mansouri, Ziba Tousi


The aim of this study was to investigate the term Nano in subject categories of patents and to analyze the conceptual relationship between them. The method of this study is based on the study of mathematical models of the disease outbreaks. Population composed of published patents which used the words of “Nano" or "Nanotechnology” in the title or abstract. The patents retrieved from the Institute of Patent and Trademark of United States of America (USPTO). The findings showed that the patents trend had an exponential relationship and an incremental growth. So that the absolute number of patents has increased from 2 in 1995 to 1474 patents in 2013. The cumulative growth of subclasses has been involved in Nano subject over time that has an S state logistics, which is reached from 2 in 1995 to 3032 in 2014. The results showed that the USPTO patents at this time confirm the theory of Goffman (1971) that transmits of an idea as the dissemination of influenza are reversible. 


Epidemic Theory; Information Epidemic; Co-word analyses; Nanotechnology patent

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Anagnostopoulos, C., Hadjiefthymiades, S., & Zervas, E. (2011). An analytical model for multi-epidemic information dissemination. Journal of Parallel and Distributed Computing, 71(1), 87-104.‏

Bettencourt, L., Cintrón-Arias, A., Kaiser, D., & Castillo-Chávez, C. (2006). The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models. Physica A: Statistical Mechanics and its Applications, 364, 513-536

Borrett, S. R., Moody, J., & Edelmann, A. (2014). The rise of network ecology: Maps of the topic diversity and scientific collaboration. Ecological Modelling, 293, 111-127.

Diekmann, O., & Heesterbeek J.A.P. (2000). Mathematical epidemiology of infectious diseases. Analysis and Interpretation 5(1)303-317.

Goffman, E. (1971) A mathematical method for analyzing the growth of a scientific discipline, Journal of the Association for Computing Machinery, 18(2):173-185.

Goffman, W., & Newill, V. A. (1964). Generalization of epidemic theory. Nature, 204(4955), 225-228.

Iannelli, M. (2005). The mathematical modeling of epidemics. Mathematical Models in Life Science: Theory and Simulation. Florida Gulf Coast University. Diakses dari. Retrieved from:

Kim, C., & Seol, H. (2009). A methodology for identifying core technologies based on technological cross-impact: Association rule mining and anp approach. In Proceedings of the Ninth International Conference on Electronic Business.

Lee, M. R., & Chen, T.T. (2012). Revealing research themes and trends in knowledge management: From 1995 to 2010. Knowledge Based Systems, 28(1): 47-58.

Liu, Y., Goncalves, J., Ferreira, D., Xiao, B., Hosio, S., & Kostakos, V. (2014). CHI 1994-2013: Mapping two decades of intellectual progress through co-word analysis. In Proceedings of the 32nd annual ACM conference on Human factors in computing systems (pp. 3553-3562). ACM.

Luo, R. G., & Jiang, T. (2006). The research of technology diffusion model based on the sir epidemic model. Journal of Industrial Engineering and Engineering Management, 1, 32-35.

Meyer, M. S. (2001). Patent citation analysis in a novel field of technology: An exploration of nano-science and nano-technology, Scientometrics, 51(1):163-183.‏

Nikkam, N. (2006). An introduction to knowing technology patents. Technology Growth, 6(2), 44-45. [In Persian]

Sterman, J. D. (2000). Business dynamics: Systems thinking and modeling for a complex world (pp. 108-117). Boston: Irwin/McGraw-Hill.‏

Tassier, T. (2013). Simple Epidemics and SIS Models. in The Economics of Epidemiology (pp. 9-16). Berlin: Springer-Verlag.

Wittmann, W. W., & Hattrup, K. (2007). Mental models concepts for system dynamics research. Systems Research and Behavioral Science, 21(4), 439-470.‏


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