A Methodology to Analyze Technology Convergence: Patent-Citation Based Technology Input-Output Analysis

Authors: Jeeeun Kim, Sungjoo Lee

Abstract:

This research proposes a methodology for patent-citation-based technology input-output analysis by applying the patent information to input-output analysis developed for the dependencies among different industries. For this analysis, a technology relationship matrix and its components, as well as input and technology inducement coefficients, are constructed using patent information. Then, a technology inducement coefficient is calculated by normalizing the degree of citation from certain IPCs to the different IPCs (International patent classification) or to the same IPCs. Finally, we construct a Dependency Structure Matrix (DSM) based on the technology inducement coefficient to suggest a useful application for this methodology.

Keywords: Technology spillover effect, technology relationship, IO table, technology inducement coefficients, patent analysis, patent citation.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1057849

References:

[1] Hacklin, F., Marxt, C. and Fahrni, F. (2009), Coevolutionary cycles of convergence: an extrapolation from the ICT industry, Technological Forecasting & Social Change, Vol. 76, pp. 723-736.
[2] Xing, W, Ye, X. and Kui, L. (2011), Measuring convergence of China's ICT industry: an input-output analysis, Telecommunications Policy, Vol. 35, pp.301-313.
[3] Lee, M. Lee, J. and Cho, Y. (2009), How a convergence product affects related markets: The case of the mobile phone, ETRI Journal, Vol. 31, No. 2, pp. 215-224.
[4] Bores, C., Saurina, C. and Torres, R. (2003), Technological convergence: a strategic perspective, Technovation, Vol 23, No.1, pp.1-13.
[5] Ernst H, Patenting strategies in the German mechanical engineering industry and their relationship to company performance, Technovation, 15 (4) (1995) 225-240.
[6] Geum, Y., Kim, C., Lee, S. and Kim, M. (2012), Technological convergence of IT and BT: evidence from patent analysis, ETRI Journal, Vol. 34, No. 3, pp. 439-449.
[7] No, H.J. and Park, Y. (2010), Trajectory patterns of technology fusion: trend analysis and taxonomical grouping in nanobiotechnology, Technological Forecasting & Social Change, Vol. 77, pp. 63-75.
[8] Curran, C.S. and Leker, J. (2011), Patent indicators for monitoring convergence - examples from NFF and ICT, Technological Forecasting and Social Change, vol. 78, pp. 256-273.
[9] Tijssen, R.J.W. (1992), A quantitative assessment of interdisciplinary structures in science and technology: co-classification analysis of energy research, Research Policy, Vol. 21, No. 1, pp. 27-44.
[10] Engelsman, E.C. and van Raan, A.F.J. (1994), A patent-based cartography of technology, Research Policy, Vol. 23, pp. 1-26.
[11] Leontief, W.W. (1986), Input-Output Economics. 2nd ed., New York: Oxford University Press.