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Technology opportunity identification customized to the technological capability of SMEs through two-stage patent analysis

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Abstract

Small and medium enterprises (SMEs) have difficulties identifying appropriate technology opportunities under severe capability and resource constraints. To tackle this issue, we suggest a method for identifying technology opportunities that is customized to the existing technologies and technological capabilities of SMEs through two-stage patent analysis. An expert-based technological attribute–application table makes it possible to identify basic opportunities by multiple keyword matching. Also, non-traditional opportunities can be explored and identified by an iterative action–object analysis of patents. This two-stage patent analysis approach provides managers with a way of identifying specific technology opportunities in which their existing technologies can be utilized to the maximum extent, therefore helping them to develop technology strategies.

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References

  • Albert, M. B., Avery, D., Narin, F., & McAllister, P. (1991). Direct validation of citation counts as indicators of industrially important patents. Research Policy, 20(3), 251–259.

    Article  Google Scholar 

  • Bengisu, M., & Nekhili, R. (2006). Forecasting emerging technologies with the aid of science and technology databases. Technological Forecasting and Social Change, 73(7), 835–844.

    Article  Google Scholar 

  • Blackman, M. (1995). Provision of patent information: A national patent office perspective. World Patent Information, 17(2), 115–123.

    Article  Google Scholar 

  • Cascini, G., Fantechi, A., & Spinicci, E. (2004). Natural language processing of patents and technical documentation. Lecture Notes in Computer Science, 3163, 508–520.

    Article  Google Scholar 

  • Choi, S., Yoon, J., Kim, K., Lee, J. Y., & Kim, C. H. (2011). SAO network analysis of patents for technology trends identification: A case study of polymer electrolyte membrane technology in proton exchange membrane fuel cells. Scientometrics, 88(3), 863–883.

    Article  Google Scholar 

  • Cozzens, S., Gatchair, S., Kang, J., Kim, K. S., Lee, H. J., Ordóñez, G., et al. (2010). Emerging technologies: Quantitative identification and measurement. Technology Analysis and Strategic Management, 22, 361–376.

    Article  Google Scholar 

  • Criscuolo, P., & Verspagen, B. (2008). Does it matter where patent citations come from? Inventor vs. examiner citations in European patents. Research Policy, 37(10), 1892–1908.

    Article  Google Scholar 

  • Daim, T., Rueda, G., Martin, H., & Gerdsri, P. (2006). Forecasting emerging technologies: Use of bibliometrics and patent analysis. Technological Forecasting and Social Change, 73(8), 981–1012.

    Article  Google Scholar 

  • Deerwester, S. C., Dumais, S. T., Landauer, T. K., Furnas, G. W., & Harshman, R. A. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), 391–407.

    Article  Google Scholar 

  • Durand, T. (2003). Twelve lessons from ‘Key Technologies 2005’: The French technology foresight exercise. Journal of Forecasting, 22, 161–177.

    Article  Google Scholar 

  • Ernst, H. (2003). Patent information for strategic technology management. World Patent Information, 25, 233–242.

    Article  Google Scholar 

  • Gerken, J. M., & Moehrle, M. G. (2012). A new instrument for technology monitoring: Novelty in patents measured by semantic patent analysis. Scientometrics, 91(3), 645–670.

    Article  Google Scholar 

  • Geum, Y., Jeon, J., & Seol, H. (2013). Identifying technological opportunities using the novelty detection technique: A case of laser technology in semiconductor manufacturing. Technology Analysis and Strategic Management, 25(1), 1–22.

    Article  Google Scholar 

  • Ghemawat, P. (2003). The forgotten strategy. Harvard Business Online.

  • Gruner, K. E., & Homburg, C. (2000). Does customer interaction enhance new product success? Journal of Business Research, 49(1), 1–14.

    Article  Google Scholar 

  • Hall, B. H., Jaffe, A., & Trajtenberg, M. (2005). Market value and patent citations. RAND Journal of Economics, 36(1), 16–38.

    Google Scholar 

  • Hausman, A. (2005). Innovativeness among small businesses: Theory and propositions for future research. Industrial Marketing Management, 34(8), 773–782.

    Article  Google Scholar 

  • Heimeriks, G., & Leydesdorff, L. (2012). Emerging search regimes: Measuring co-evolutions among research, science, and society. Technology Analysis and Strategic Management, 24(1), 51–67.

    Article  Google Scholar 

  • Jaffe, A. B., & Trajtenberg, M. (2002). Patents, citations, and innovations: A window on the knowledge economy. Cambridge, MA: MIT Press.

    Google Scholar 

  • Johnston, R. (2006). Technology planning in major Asian countries: An analysis of recent foresight reports from China and India and comparison with Japan and Korea. Canberra: Australian Centre for Innovation. http://www.aciic.org.au/?page=77.

  • Kerr, C. I. V., Mortara, L., & Probert, D. R. (2006). A conceptual model for technology intelligence. International Journal of Technology Intelligence and Planning, 2(1), 73–93.

    Article  Google Scholar 

  • Klevorick, A. K., Levin, R. C., Nelson, R. R., & Winter, S. G. (1995). On the sources and significance of interindustry differences in technological opportunities. Research Policy, 24, 185–205.

    Article  Google Scholar 

  • Kostoff, R. (2001). Text mining using database tomography and bibliometrics: A review. Technological Forecasting and Social Change, 68(3), 223–253.

    Article  Google Scholar 

  • Landauer, T. K., McNamara, D. S., Dennis, S., & Kintsch, W. (Eds.). (2013). Handbook of latent semantic analysis. New York: Routledge.

    Google Scholar 

  • Lee, S., Lee, S., Seol, H., & Park, Y. (2008). Using patent information for designing new product and technology: Keyword based technology roadmapping. R&D Management, 38(2), 169–188.

    Article  Google Scholar 

  • Lee, S., Yoon, B., & Park, Y. (2009). An approach to discovering new technology opportunities: Keyword-based patent map approach. Technovation, 29(6–7), 481–497.

    Article  Google Scholar 

  • Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to information retrieval (Vol. 1). Cambridge: Cambridge University Press.

    Book  MATH  Google Scholar 

  • Massa, S., & Testa, S. (2008). Innovation and SMEs: Misaligned perspectives and goals among entrepreneurs, academics, and policy makers. Technovation, 28(7), 393–407.

    Article  Google Scholar 

  • Moehrle, M. G., Walter, L., Geritz, A., & Müller, S. (2005). Patent-based inventor profiles as a basis for human resource decisions in research and development. R&D Management, 35(5), 513–524.

    Article  Google Scholar 

  • Narin, F., Albert, M. B., & Smith, V. M. (1992). Strategic planning: Technology indicators in strategic planning. Science and Public Policy, 19(6), 369–381.

    Google Scholar 

  • Newbert, S., Walsh, S., Kirchhoff, B., & Chavez, V. (2006). Technology-driven entrepreneurship: Muddling through and succeeding with the second product. Entrepreneurship: The Engine of Growth, 3, 291–312.

    Google Scholar 

  • Nielsen, P. E. (2004). Evaluating patent portfolios: A Danish initiative. World Patent Information, 26, 143–148.

    Article  Google Scholar 

  • Olsson, O. (2005). Technology opportunity and growth. Journal of Economic Growth, 10, 35–57.

    Article  MATH  Google Scholar 

  • Porter, A. L., & Cunningham, S. W. (2005). Tech mining: Exploiting new technologies for competitive advantage. New York: Wiley.

    Google Scholar 

  • Porter, A. L., & Detampel, M. J. (1995). Technology opportunities analysis. Technological Forecasting and Social Change, 49(3), 237–255.

    Article  Google Scholar 

  • Porter, A. L., & Newman, N. C. (2011). Mining external R&D. Technovation, 31(4), 171–176.

    Article  Google Scholar 

  • Romano, C. A. (1990). Identifying factors which influence product innovation: A case study approach. Journal of Management Studies, 27(1), 75–95.

    Article  Google Scholar 

  • Savioz, P., & Blum, M. (2002). Strategic forecast tool for SMEs: How the opportunity landscape interacts with business strategy to anticipate technological trends. Technovation, 22(2), 91–100.

    Article  Google Scholar 

  • Savransky, S. D. (2000). Engineering of creativity: Introduction to TRIZ methodology of inventive problem solving. London: CRC Press.

    Book  Google Scholar 

  • Shibata, N., Kajikawa, Y., Takeda, Y., & Matsushima, K. (2008). Detecting emerging research fronts based on topological measures in citation networks of scientific publications. Technovation, 28(11), 758–775.

    Article  Google Scholar 

  • Valk, T. Van Der, Moors, E., & Meeus, M. (2009). Conceptualizing patterns in the dynamics of emerging technologies: The case of biotechnology developments in the Netherlands. Technovation, 29, 247–264.

    Article  Google Scholar 

  • van Raan, A. F. J. (1996). Advanced bibliometric methods as quantitative core of peer review based evaluation and foresight exercises. Scientometrics, 36(3), 397–420.

    Article  Google Scholar 

  • Wartburg, I. V., Teichert, T., & Rost, K. (2005). Inventive progress measured by multi-stage patent citation analysis. Research Policy, 34(10), 1591–1607.

    Article  Google Scholar 

  • Xin, L., Jiwu, W., Lucheng, H., Jiang, L., & Jian, L. (2010). Empirical research on the technology opportunities analysis based on morphology analysis and conjoint analysis. Foresight, 12(2), 66–76.

    Article  Google Scholar 

  • Yoon, J., & Kim, K. (2011). Identifying rapidly evolving technological trends for R&D planning using SAO-based semantic patent networks. Scientometrics, 88(1), 213–228.

    Article  Google Scholar 

  • Yoon, B., & Park, Y. (2005). A systematic approach for identifying technology opportunities: Keyword-based morphology analysis. Technological Forecasting and Social Change, 72(2), 145–160.

    Article  Google Scholar 

  • Yoon, B., & Park, Y. (2007). Development of new technology forecasting algorithm: Hybrid approach for morphology analysis and conjoint analysis of patent information. IEEE Transactions on Engineering Management, 54(3), 588–599.

    Article  Google Scholar 

  • Zhang, Y., Zhou, X., Porter, A. L., Vicente Gomila, J. M., & Yan, A. (2013). Triple Helix innovation in China’s dye-sensitized solar cell industry: Hybrid methods with semantic TRIZ and technology roadmapping. Scientometrics,. doi:10.1007/s11192-013-1090-9.

    Google Scholar 

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Authors and Affiliations

  1. Department of Policy Research, Korea Institute of Science and Technology Information, 335 Gwahangno, Yuseong, Taejon, 305-806, Republic of Korea

    Yongho Lee

  2. Department of Technology Opportunity Analysis, Korea Institute of Science and Technology Information, 66 Hoegiro, Dongdaemun-gu, Seoul, Republic of Korea

    So Young Kim & Inseok Song

  3. Department of Industrial Engineering, Seoul National University, San 56-1, Shilim-Dong, Kwanak-Gu, Seoul, 151-742, Republic of Korea

    Yongtae Park

  4. Department of Systems Management Engineering, Sungkyunkwan University, 300 Chunchun-dong, Jangan-gu, Suwon, Gyoenggi-do, 440-746, Republic of Korea

    Juneseuk Shin

Authors
  1. Yongho Lee
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  2. So Young Kim
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  3. Inseok Song
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  4. Yongtae Park
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  5. Juneseuk Shin
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Correspondence to Juneseuk Shin.

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Lee, Y., Kim, S.Y., Song, I. et al. Technology opportunity identification customized to the technological capability of SMEs through two-stage patent analysis. Scientometrics 100, 227–244 (2014). https://doi.org/10.1007/s11192-013-1216-0

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  • DOI: https://doi.org/10.1007/s11192-013-1216-0

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