Patent Strategy in the Digital Transformation Era

The digital transformation and big data paradigms have expanded across many research fields, including both strategy and innovation. Although existing research attempts to keep up with the pace of these phenomena, more in-depth knowledge of how patent big data can help firms and managers in their decision-making process is still needed. Based on patent co-classification analysis, this paper aims to provide two different but complementary patent tools; the first exploits ex-ante patent information whereas the latter integrates it with ex-post details extracted by patent documents. We further investigate the technology positioning and links as well as examine the industry’s «excellence» technology structure conceived as the combination of the technology elements that has yielded high-impactful inventions.

[1]  Michael Blackman,et al.  Provision of patent information: a national patent office perspective , 1995 .

[2]  Nees Jan van Eck,et al.  Visualizing the computational intelligence field [Application Notes] , 2006, IEEE Computational Intelligence Magazine.

[3]  Yongtae Park,et al.  Trajectory patterns of technology fusion: Trend analysis and taxonomical grouping in nanobiotechnology , 2010 .

[4]  Bokyoung Kang,et al.  Novelty-focused patent mapping for technology opportunity analysis , 2015 .

[5]  F. Malerba,et al.  Knowledge-relatedness in firm technological diversification , 2003 .

[6]  Kwangsoo Kim,et al.  A patent intelligence system for strategic technology planning , 2013, Expert Syst. Appl..

[7]  Rosemarie H. Ziedonis Don't Fence Me in: Fragmented Markets for Technology and the Patent Acquisition Strategies of Firms , 2003, Manag. Sci..

[8]  K. R. Harrigan,et al.  Patent value and the Tobin’s q ratio in media services , 2018 .

[9]  K. R. Harrigan,et al.  Sustainability of patent-based competitive advantage in the U.S. communications services industry , 2017 .

[10]  Ivan Zupic,et al.  Bibliometric Methods in Management and Organization , 2014 .

[11]  D. Archibugi,et al.  Measuring technological change through patents and innovation surveys , 1996 .

[12]  Gregory F. Nemet,et al.  Do Important Inventions Benefit from Knowledge Originating in Other Technological Domains? , 2011 .

[13]  Rommert Dekker,et al.  A comparison of two techniques for bibliometric mapping: Multidimensional scaling and VOS , 2010, J. Assoc. Inf. Sci. Technol..

[14]  Kristina Dahlin,et al.  When is an Invention Really Radical? Defining and Measuring Technological Radicalness , 2005 .

[15]  M. Guardo,et al.  Explaining the Effect of M&A on Technological Performance , 2007 .

[16]  Preeta M. Banerjee,et al.  Measuring patent's influence on technological evolution: A study of knowledge spanning and subsequent inventive activity , 2015 .

[17]  Shantanu Dutta,et al.  Benefiting From Alliance Portfolio Diversity , 2014 .

[18]  Janghyeok Yoon,et al.  Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: the case of Korean national R&D , 2013, Scientometrics.

[19]  E. C. Engelsman,et al.  A patent-based cartography of technology , 1994 .

[20]  Jong-Chan Kim,et al.  Technology convergence: What developmental stage are we in? , 2015, Scientometrics.

[21]  O. Sorenson,et al.  Technology as a complex adaptive system: evidence from patent data , 2001 .

[22]  R. Veugelers,et al.  The impact of M&A on the R&D process: An empirical analysis of the role of technological- and market-relatedness , 2005 .

[23]  Bronwyn H Hall,et al.  Market value and patent citations , 2005 .

[24]  Reinhilde Veugelers,et al.  Measuring Technological Novelty with Patent-Based Indicators , 2015 .

[25]  Mark A. Spasser Mapping the terrain of pharmacy: Co-classification analysis of theInternational Pharmaceutical Abstracts database , 1997, Scientometrics.

[26]  M. Trajtenberg A Penny for Your Quotes : Patent Citations and the Value of Innovations , 1990 .

[27]  Bart Nooteboom,et al.  Network Embeddedness and the Exploration of Novel Technologies: Technological Distance, Betweenness Centrality and Density , 2006 .

[28]  L. Waltman,et al.  Bibliometric Mapping of the Computational Intelligence Field Nees , 2007 .

[29]  Maria Chiara Di Guardo,et al.  The theoretical foundations of entrepreneurship education: How co-citations are shaping the field , 2016 .

[30]  Sunghae Jun,et al.  Patent Big Data Analysis using Fuzzy Learning , 2016, International Journal of Fuzzy Systems.

[31]  M. Tushman,et al.  Ambidextrous Organizations: Managing Evolutionary and Revolutionary Change , 1996 .

[32]  M. Calcagno An investigation into analyzing patents by chemical structure using Thomson's Derwent World Patent Index codes , 2008 .

[33]  Wonjoon Kim,et al.  The effect of a firm's strategic innovation decisions on its market performance , 2014, Technol. Anal. Strateg. Manag..

[34]  Nees Jan van Eck,et al.  Journal Editorials give indication of driving science issues , 2010, Nature.

[35]  Yangrae Cho,et al.  A stochastic patent citation analysis approach to assessing future technological impacts , 2012 .

[36]  Maria Chiara Di Guardo,et al.  A Collective Reasoning on the Automotive Industry: A Patent Co-citation Analysis , 2015, ISSI.

[37]  Stijn Viaene,et al.  Linking technology intelligence to open innovation , 2010 .

[38]  Curba Morris Lampert,et al.  Entrepreneurship in the large corporation: a longitudinal study of how established firms create breakthrough inventions , 2001 .

[39]  Fang-Mei Tseng,et al.  Using patent data to analyze trends and the technological strategies of the amorphous silicon thin-film solar cell industry , 2011 .

[40]  Maria Chiara Di Guardo,et al.  Using a distance measure to operationalise patent originality , 2017, Technol. Anal. Strateg. Manag..

[41]  Arho Suominen,et al.  Firms' knowledge profiles: Mapping patent data with unsupervised learning , 2017 .

[42]  Sai Yayavaram,et al.  Decomposability in Knowledge Structures and Its Impact on the Usefulness of Inventions and Knowledge-base Malleability , 2008 .

[43]  Loet Leydesdorff,et al.  Patent classifications as indicators of intellectual organization , 2008, J. Assoc. Inf. Sci. Technol..

[44]  K. R. Harrigan,et al.  M&A and diversification strategies: what effect on quality of inventive activity? , 2018, Journal of Management and Governance.

[45]  Maria Chiara Di Guardo,et al.  Disentangling the automotive technology structure: a patent co-citation analysis , 2016, Scientometrics.

[46]  J. Leker,et al.  Anticipating converging industries using publicly available data , 2010 .

[47]  K. R. Harrigan,et al.  Shaping the path to inventive activity: the role of past experience in R&D alliances , 2016 .

[48]  M. Gittelman,et al.  Patent Citations as a Measure of Knowledge Flows: The Influence of Examiner Citations , 2006, The Review of Economics and Statistics.

[49]  K. R. Harrigan,et al.  Mapping research on strategic alliances and innovation: a co-citation analysis , 2012 .

[50]  G. Valentini,et al.  M&A and the profile of inventive activity , 2012 .

[51]  Daniele Rotolo,et al.  Determinants of Patent Citations in Biotechnology: An Analysis of Patent Influence Across the Industrial and Organizational Boundaries , 2014, ArXiv.

[52]  L. Fleming Recombinant Uncertainty in Technological Search Lee Fleming , 2001 .

[53]  Ludo Waltman,et al.  Bibliometric Mapping of the Computational Intelligence Field , 2007, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[54]  A. Jaffe Technological Opportunity and Spillovers of R&D: Evidence from Firms&Apos; Patents, Profits and Market Value , 1986 .

[55]  Kuei-Kuei Lai,et al.  Exploring technology diffusion and classification of business methods: Using the patent citation network , 2009 .

[56]  Xianwen Wang,et al.  Divergence and convergence: technology-relatedness evolution in solar energy industry , 2013, Scientometrics.

[57]  R. Katila,et al.  Technological acquisitions and the innovation performance of acquiring firms: a longitudinal study , 2001 .

[58]  R. Tijssen A quantitative assessment of interdisciplinary structures in science and technology: Co-classification analysis of energy research☆ , 1992 .

[59]  Inchae Park,et al.  Exploring technological opportunities by linking technology and products: Application of morphology analysis and text mining , 2014 .

[60]  Victor Gilsing,et al.  The two faces of inventions: The relationship between recombination and impact in pharmaceutical biotechnology , 2016 .

[61]  Xianwen Wang,et al.  Are significant inventions more diversified? , 2014, Scientometrics.

[62]  Deepak Hegde,et al.  Examiner Citations, Applicant Citations, and the Private Value of Patents , 2009 .

[63]  Bruno van Pottelsberghe de la Potterie,et al.  The Worldwide Count of Priority Patents: A New Indicator of Inventive Activity , 2012 .

[64]  Clayton M. Christensen The Innovator's Dilemma: The Revolutionary Book That Will Change the Way You Do Business , 2011 .

[65]  M. Gittelman,et al.  Applicant and Examiner Citations in US Patents: An Overview and Analysis , 2008 .

[66]  Rosemarie H. Ziedonis,et al.  The patent paradox revisited: an empirical study of patenting in the U , 2001 .

[67]  Tuomo Kässi,et al.  Patent citations as a tool for analysing the early stages of convergence , 2013 .

[68]  Loet Leydesdorff,et al.  Co-occurrence matrices and their applications in information science: Extending ACA to the Web environment , 2006, J. Assoc. Inf. Sci. Technol..

[69]  J. Hagedoorn,et al.  Measuring innovative performance: is there an advantage in using multiple indicators? , 2003 .