Patent bibliometrics and its use for technology watch

Björn Jürgens, Victor Herrero-Solana

Abstract


Technology watch is a methodology for organisations to systematically analyze
technical information in a continuous way in order to gain insight and competitive advantage
in a specific technical domain and is based mainly on statistical analysis of patent information.
Patent statistics are commonly based on bibliographic data and generated with bibliometric
techniques. In this paper we describe the differences between patent bibliometrics and classic
bibliometrics and propose several patent indicators for technology watch activities which we
classified into four categories: performance, technology, patent value and collaboration
indicators. In a case study we undertook a bibliometric patent analysis using the described
groups of indicators in order to generate a technology watch of nanotechnology for the domain
of a whole country (Spain) and explained the different data visualizations we used in order to
represent the indicators. We conclude that statistical analysis of patent information and its
visualization is a powerful methodology for any competitive intelligence activity centred on
technology but there are also some limitations to bear in mind when undertaking technology
watch activities using patent information discussed in terms of its timeliness, patentability
criteria, sector dependence, quantity vs. quality.


Keywords


Competitive intelligence, nanotechnology, patent bibliometrics, patent indicators, patent information, patent statistics, patents, Spain, technology intelligence, technology monitoring, technology watch

Full Text:

PDF

References


Andaluz, D. J., & Sánchez J. (2006).

Nanotecnología en España. http://www.

madrimasd.

org/revista/revista34/tribuna/tribuna4.asp

(Accessed: 05.02.2015)

Alcacer, J., & Gittelman, M. (2006). Patent

citations as a measure of knowledge flows: The

influence of examiner citations. The Review of

Economics and Statistics, 88(4), 774-779.

Azagra-Caro, J. M., Fernández-de-Lucio, I.,

Perruchas, F., & Mattsson, P. (2009). What do

patent examiner inserted citations indicate for

a region with low absorptive capacity?.

Scientometrics, 80(2), 441-455.

Deshpande, N., Ahmeda, S., & Khodea, A. (2016).

Business intelligence through patinformatics:

A study of energy efficient data centres using

patent data. Journal of Intelligence Studies in

Business, 6(3).

E-IPR (2013). Fact Sheet - Automatic Patent

Analysis. European IPR Helpdesk

https://www.iprhelpdesk.eu/sites/default/files/

newsdocuments/20131127_Patent%20Analysi

s_updated_0.pdf (Accessed: 09.02.2016)

Fleisher, C. S., & Bensoussan, B. E. (2003).

Strategic and competitive analysis: methods

and techniques for analyzing business

competition (p. 457). Upper Saddle River, NJ:

Prentice Hall.

García, C. Q., & Velasco, C. A. B. (2006).

Inteligencia competitiva, prospectiva e

innovación: la norma UE 166006 EX sobre el

Figure 5 Citation node map of a Spanish nanotech patent (orange box) reveals who was influenced by the technology (green

boxes). sistema de vigilancia tecnológica. Boletín

económico de ICE, Información Comercial

Española, (2896), 47-64.

Glänzel, W., Meyer, M., Du Plessis, M., Thijs, B.,

Magerman, T., Schlemmer, B., ... & Veugelers,

R. (2003). Nanotechnology: Analysis of an

emerging domain of scientific and

technological endeavour. Steunpunt O&O

Statistieken.

Hodgson, A., Arman, H., & Gindy, N. N. (2008).

An intelligent technology watch function for

the high technology enterprise. International

Journal of Industrial and Systems

Engineering, 3(1), 38-52.

Hullmann, A., & Meyer, M. (2003). Publications

and patents in nanotechnology.

Scientometrics, 58(3), 507-527.

Jürgens, B., Herrero-Solana, V. (2011). Estudios

sectoriales de vigilancia tecnológica para la

comunidad empresarial e investigadora de

Andalucía. El profesional de la información,

(5), 533-541.

Jürgens, B., Herrero-Solana,V. (2015).

Espacenet, Patentscope and Depatisnet: A

comparison approach. World Patent

Information. Vol. 42.

doi:10.1016/j.wpi.2015.05.004

Jürgens, B., & Herrero-Solana, V. (2017).

Monitoring nanotechnology using patent

classifications: an overview and comparison of

nanotechnology classification schemes.

Journal of Nanoparticle Research, 19(4), 151.

Jürgens, B. (2016). Nanotechnology in Spain:

technology watch by patents (Doctoral

dissertation). University of Granada.

Maghrebi, M., Abbasi, A., Amiri, S., Monsefi, R.,

& Harati, A. (2010). A collective and abridged

lexical query for delineation of nanotechnology

publications. Scientometrics, 86(1), 15-25.

Meyer, M. (2002). Tracing knowledge flows in

innovation systems. Scientometrics, 54(2),

-212.

Miller, S. H. (2001). Competitive Intelligence–an

overview. Competitive Intelligence Magazine,

(11).

Narin, F. (1994). Patent bibliometrics.

Scientometrics, 30(1), 147-155.

Negash, S. (2004). Business intelligence. The

communications of the Association for

Information Systems, 13(1), 54.

Lloyd, M. (2015). Patent vs scientific literature -

how do they compare?, Amberblog.

http://www.ambercite.com/index.php/amberbl

og/entry/patent-vs-scientific-literature-acomparison

(Accessed 10.10.2015)

Salvador, M. R., & Bañuelos, M. A. T. (2012).

Applying patent analysis with Competitive

technical intelligence: the case of Plastics.

Journal of Intelligence Studies in Business,

(1).

Salvador, M. R., Zamudio, P. C., Carrasco, A. S.

A., Benítez, E. O., & Bautista, B. A. (2014).

Strategic foresight: determining patent trends

in additive manufacturing. Journal of

Intelligence Studies in Business, 4(3).

Schmookler, J. (1966). Invention and economic

growth. Harvard University Press,

Cambridge, MA

Palop, F., & Vicente, J. M. (1999). Vigilancia

tecnológica e inteligencia competitiva: su

potencial para la empresa española. Madrid:

Cotec.

Palmberg, C., Dernis, H., & Miguet, C. (2009).

Nanotechnology: an overview based on

indicators and statistics.

Pavitt, K. (1985). Patent statistics as indicators of

innovative activities: Possibilities and

problems, Scientometrics 7(1-2), 77–99.

Pritchard, A. (1969). Statistical bibliography or

bibliometrics?. Journal of documentation, (25),

-349.

Zuniga, P., Guellec, D., Dernis, H., Khan, M.,

Okazaki, T., & Webb, C. (2009). OECD patent

statistics manual. Organisation for economic

co-operation and development.


Refbacks

  • There are currently no refbacks.

Comments on this article

View all comments


JISIB is indexed by ESCI, SCOPUS, EBSCO, DOAJ, Google Scholar, EconBib and SCImago, and is ranked as a Level 1 publication by the Norwegian Social Science Data Services. JISIB has applied for admittance to Web of Science.