A structured approach to explore knowledge flows through technology-based business methods by integrating patent citation analysis and text mining

Technological Forecasting and Social Change

Volumn 97, Issue , 2015, Pages 181-192

  No, Hyun Joung ^a   An, Yoonjung ^a   Park, Yongtae ^a  

^a Seoul National University   (South Korea)

Author keywords

Business method; Knowledge flow; Patent citation analysis; Technological classes; Text mining

Indexed keywords

DATA MINING; INFORMATION ANALYSIS;

BUSINESS METHODS; KNOWLEDGE FLOW; PATENT CITATION ANALYSIS; TECHNOLOGICAL CLASSES; TEXT MINING;

PATENTS AND INVENTIONS;

EID: 84930820307     PISSN: 00401625     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.techfore.2014.04.007     Document Type: Article

References (45)

1. Chang S.B. Using patent analysis to establish technological position: two different strategic approaches. Technol. Forecast. Soc. Chang. 2012, 79(1):3-15.
2. Mounteney S. European Patent Office update, IP Europe January 2002, 32-8.
3. NSF Science and Engineering Indicators 2002, National Science Board, Arlington, VA, (Retrieved from www.nsf.gov/sbe/srs/seind02/c6/c6s5.htm#top).
4. Osterwalder A. The business model ontology: a proposition in a design science approach. Institut d'Informatique et Organisation 2004, 173. University of Lausanne, Ecole des Hautes Etudes Commerciales HEC, Lausanne, Switzerland.
5. Pateli A.G., Giaglis G.M. Technology innovation-induced business model change: a contingency approach. J. Organ. Chang. Manag. 2005, 18(2):167-183.
6. Wu Y.C.J. Unlocking the value of business model patents in e-commerce. J. Enterp. Inf. Manag. 2005, 18(1):113-130.
7. Rausch L.M. International Patenting of Internet-related Business Methods March 2003, National Science Foundation, Arlington, VA, (Retrieved from http://www.nsf.gov/statistics/infbrief/nsf03314/).
8. Kim C., Kim S., Kim M.S. Identifying relationships between technology-based services and ICTs: a patent analysis approach. World Academy of Science. Eng. Technol. 2011, 5:12-22.
9. Lee C., Park H., Park Y. Keeping abreast of technology-driven business model evolution: a dynamic patent analysis approach. Tech. Anal. Strat. Manag. 2013, 25(5):487-505.
10. Hunt R.M. You can patent that? Are patents on computer programs and business methods good for the new economy?. Bus. Rev. 2001, Q1:5-15.
11. Wagner S. Business method patents in Europe and their strategic use-evidence from franking device manufacturers. Econ. Innovation New Tech. 2008, 17(3):173-194.
12. Lukach R., Plasmans J.E. Measuring knowledge spillovers using patent citations: evidence from the Belgian firm's data 2002, CESifo.
13. Hu A.G., Jaffe A.B. Patent citations and international knowledge flow: the cases of Korea and Taiwan. Int. J. Ind. Organ. 2003, 21(6):849-880.
14. Glaeser E.L., Kallal H.D., Scheinkman J.A., Shleifer A. Growth in cities (No. w3787) 1991, National Bureau of Economic Research.
15. Huggins R., Johnston A. Knowledge flow and inter-firm networks: the influence of network resources, spatial proximity and firm size. Entrepreneurship Reg. Devel. 2010, 22(5):457-484.
16. Meagher K., Rogers M. Network density and R&D spillovers. J. Econ. Behav. Organ. 2004, 53(2):237-260.
17. Sammarra A., Biggiero L. Heterogeneity and specificity of inter-firm knowledge flows in innovation networks. J. Manag. Stud. 2008, 45(4):800-829.
18. Crespi G., Criscuolo C., Haskel J.E., Slaughter M. Productivity growth, knowledge flows, and spillovers (No. w13959) 2008, National Bureau of Economic Research.
19. Nelson A.J. Measuring knowledge spillovers: what patents, licenses and publications reveal about innovation diffusion. Res. Policy 2009, 38(6):994-1005.
20. Allison J.R., Tiller E.H. Business method patent myth. Berkeley Tech. LJ. 2003, 18(4):987.
21. Duguet E., MacGarvie M. How well do patent citations measure flows of technology? Evidence from French innovation surveys. Econ. Innovation New Tech. 2005, 14(5):375-393.
22. Plasmans J., Lukach R. The patterns of inter-firm and inter-industry knowledge flows in the Netherland (From). http://www.cesifo-group.de/portal/page/portal/DocBase_Content/WP/WP-CESifo_Working_Papers/wp-cesifo-2010/wp-cesifo-2010-05/cesifo1_wp3057.pdf.
23. Lukach R., Plasmans J. International knowledge flows from and into a small open economy: patent citation analysis. Beyond Borders: Internationalisation of R&D and Policy Implications for Small Open Economies 2005, 331-357. Elsevier, Amsterdam, The Netherlands. A. Spithoven, P. Teirlinck (Eds.).
24. van Raan A.F.J., Tijssen R.J.W. The neural net of neural network research. Scientometrics 1993, 26(1):169-192.
25. Leydesdorff L. Words and co-words as indicators of intellectual organization. Res. Policy 1989, 18(4):209-223.
26. Choi C., Park Y. Monitoring the organic structure of technology based on the patent development paths. Technol. Forecast. Soc. Chang. 2009, 76(6):754-768.
27. No H.J., Park Y. Trajectory patterns of technology fusion: trend analysis and taxonomical grouping in nanobiotechnology. Technol. Forecast. Soc. Chang. 2010, 77(1):63-75.
28. Wartburg I.V., Teichert T., Rost K. Inventive progress measured by multi-stage patent citation analysis. Res. Policy 2005, 34(10):1591-1607.
29. Wang X., Zhao Y., Liu R., Zhang J. Knowledge-transfer analysis based on co-citation clustering. Scientometrics 2013, 97(3):859-869.
30. Information Retrieval: Data Structures & Algorithms 1992, Prentice-Hall. W.B. Frakes, R.A. Baeza-Yates (Eds.).
31. Han J., Kamber M., Pei J. Data Mining: Concepts and Techniques 2011, Morgan Kaufmann.
32. Salton G., McGill M.J. Introduction to Modern Information Retrieval 1986, McGraw-Hill.
33. Janssens F. Clustering of scientific fields by integrating text mining and bibliometircs 2007, (Ph.D. thesis,), Faculty of Engineering, Katholieke Universiteit Leuven, Belgium, (Retrived from http://hdl. Handle.net/1979/847).
34. Calado P., Cristo M., Goncalves M.A., De Moura E.S., Riberiro-Neto B., Ziviani N. Link-based similarity measures for the classification of web documents. JASIST 2006, 57:208-221.
35. Janssens F., Tran Quoc V., Glanzel W., De Moor B. Integration of textual content and link information for accurate clustering of science fields. Proc. Of the Intl. Conf. on Multidisciplinary Information Sacience and Technolgies (InSciT2006) 2006, 615-619. Merida, Spain. V.P. Guerrero-Bote (Ed.).
36. Glenisson P., Glanzel W., Janssens F., De Moor B. Combining full text and bibliometric information in mapping scientific disciplines. Inf. Process. Manag. 2005, 41:1548-1572.
37. Janssens F., Glanzel W., de Moor B. A hybrid mapping of information science. Scientometrics 2003, 75(3):607-631.
38. Zhang J., Rasmussen E.M. Developing a new similarity measure from two different perspectives. Inf. Process. Manag. 2001, 37(2):279-294.
39. McGill M., Koll M., Noreault T. An evaluation of factors affecting document ranking by information retrieval systems. School of Information Studies 1978, Syracuse University, Syracuse, NY.
40. Zhang J., Korfhage R. A distance and angle similarity measure. J. Am. Soc. Inf. Sci. 1990, 50(9):772-778.
41. Trajtenberg M., Henderson R., Jaffe A. University versus corporate patents: a window on the basicness of invention. Patents, Citations and Innovations-A Window on Knowledge Economy 2002, MIT Press, Cambridge, MA.
42. Priego J.L. A vector space model as a methodological approach to the triple helix dimensionality: a comparative study of biology and biomedicine centres of two European national councils from a webometric view. Scientometrics 2003, 58(2):429-443.
43. Jones W.P., Furnas G.W. Pictures of relevance: a geometric analysis of similarity measures. J. Am. Soc. Inf. Sci. 1987, 38:420-442.
44. Grandon E.E., Pearson J.M. Electronic commerce adoption: an empirical study of small and medium US businesses. Inf. Manag. 2004, 42(1):197-216.
45. Healey P.H., Rothman P.Hoch An experiment in science mapping for research planning. Res. Policy 1986, 15(5):233-251.