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Articles

Sources of technological innovation: Radical and incremental innovation problem-driven to support competitive advantage of firms

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Pages 1048-1061 | Received 15 Jan 2016, Accepted 28 Nov 2016, Published online: 29 Dec 2016
 

ABSTRACT

A fundamental problem in the field of management of technology is how firms develop radical and incremental innovations that sustain the competitive advantage in markets. Current frameworks provide some explanations but the general sources of major and minor technological breakthroughs are hardly known. The study here confronts this problem by developing a conceptual framework of problem-driven innovation. The inductive study of the pharmaceutical industry (focusing on ground-breaking drugs for lung cancer treatment) seems to show that the co-evolution of consequential problems and their solutions induce the emergence and development of radical innovations. In fact, firms have a strong incentive to find innovative solutions to unsolved problems in order to achieve the prospect of a (temporary) profit monopoly and competitive advantage in markets characterised by technological dynamisms. The theoretical framework of this study can be generalised to explain one of the sources of innovation that supports technological and industrial change in a Schumpeterian world of innovation-based competition.

JEL CLASSIFICATION:

Notes on contributor

Mario Coccia is a Senior researcher at the National Research Council of Italy and Visiting Scholar at the Arizona State University (Center for social dynamics and complexity). He has been Research Fellow at the Max Planck Institute of Economics, Visiting Professor at the Polytechnics of Torino and University of Piemonte Orientale (Italy). He has conducted research work at the Georgia Institute of Technology, Yale University, United Nations University – MERIT, University of Maryland, Bureau d’Économie Théorique et Appliquée, University of Toronto, RAND Corporations and University of Bielefeld. He has written extensively more than 280 papers in economics of science and technology, R&D management and related disciplines.

Notes

1. This research began in 2014 at the UNU-MERIT (The Netherlands) and is further developed in 2015 and 2016 at Arizona State University while I am a visiting scholar funded by National Research Council of Italy. This paper benefited from helpful comments and suggestions by Christopher S. Hayter and two anonymous referees. The author declares that he has no relevant or material financial interests that relate to the research discussed in this paper.

3. Dosi (Citation1982, 152, original emphasis) posits that ‘“technological paradigm” as “model” and a “pattern” of solution of selected technological problems based on selected principles derived from natural sciences and on selected material technologies’ (cf. Dosi, Citation1988).

4. Age-standardized rate (W) is the rate that a population would have if it had a standard age structure. Standardization is necessary when comparing several populations that differ with respect to age because age has a powerful influence on the risk of cancer (GLOBOCAN, Citation2012, http://globocan.iarc.fr/ –accessed February 2015).

5. Cf. Afshar (Citation2003) and Fraser and Pai (Citation2014). For countries with high R&D investment, see Coccia (Citation2005, Citation2007, Citation2008a, Citation2008b, Citation2009c, Citation2009d, Citation2010a, Citation2010c, Citation2013b, Citation2015b); Rolfo and Coccia (Citation2005).

6. An exon is the portion of a gene that codes for amino acids.

7. ‘A characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to therapeutic intervention’ (National Institute of Health, as quoted by Amir-Aslani and Mangematin Citation2010, 204)

8. The literature is vast and not fully cited here, but a good list of references is found in Dempke, Sutob, and Reck (Citation2010, 262–263, 271–274) and Coccia (Citation2012d, Citation2014d).

9. The evolution of technological paradigms is also based on developing new technological trajectories by ‘inventive analogical transfer’ from experience and solutions in one knowledge field—source domain e.g. a type of cancer—to solve new problems in other fields -target domains e.g. other cancers (cf. Kalogerakis, Lüthje, and Herstatt Citation2010, 418).

10. Cf. also Coccia Citation2001b, Citation2006a, Citation2008, Citation2009a, Citation2009e; Coccia and Cadario Citation2014; Coccia and Rolfo Citation2007, Citation2013; Coccia, Falavigna, and Manello Citation2015; for public research labs see also Coccia Citation2001a, Citation2003; Coccia and Rolfo Citation1999, Citation2002, Citation2010.

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