Abstract
The paper investigates the relationship between public research and radical technological development. This study draws on the theory of recombinant innovation and builds on two newly developed indicators of novelty that proxy different forms of radicalness, to analyse UK patents filed at the European Patent Office. It assesses whether the proximity of the invention to public research is related to a higher probability of the invention being radical. The results show that, depending on the type of novelty embodied by the radical invention (novelty in recombination or novelty in technological origin), different forms of public research output (proprietary output or open science) relate to the radicalness of invention in different ways. Moreover, these relationships are highly heterogeneous among technological sectors, and most of the proximity between codified public research and radical inventions occurs in the chemistry technology field. We provide some implications for policy.
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Notes
The terms public research, public R&D and public science are used interchangeably in this work to refer to the research activities conducted in public research institutions, such as universities, and funded by public expenditure, regardless of their basic or applied nature. Therefore, they exclude public finance for private R&D and private funding for public research. The construction of the variables is described in Sect. 4.3.
Note that the relationship between public research and technology is complex and the two are mostly co-evolving and are self-reinforcing (Rosenberg and Nelson 1994; David 1997; Rosenberg 1976). The development of inventions and the diffusion of new technologies are a function of the stock of available useful knowledge (Rosenberg 1974; Mokyr 2002) and the output of continuous knowledge exchange and coordination between private and public R&D (Metcalfe 1995; Loasby 1999). Moreover, an important share of the knowledge exchanged is tacit and generally involves a process of knowledge transfer via direct interaction between public sector scientists and private organizations (Rosenberg and Nelson 1994; Murmann 2003).
The PATSTAT database provides various information on applicants, including name and country of residence.
Organizations or individual names for which we were unable to find information were assigned to neither private companies nor public institutions.
Some patents have missing information, which makes this approach unfeasible. In these cases, following other studies (i.e., Hall and Helmers 2013), we identified technological field and geographical code in the patent document with the earliest priority date, and assigned them to the whole patent family. Since some patents within the same family can have the same earliest priority date, we calculated the share of patent documents for each single code and assigned to the whole family the code with the highest share.
The results of the empirical analysis hold when we calculate the minimum value for each indicator within these patent families, showing that this methodological choice does not affect the results.
E.g., the EP1950000 (A1) filed by Rolls Royce PLC includes 4 different IPC 8-digit codes. Among the 6 possible pairs of IPC 8-digit codes, the patent combines for the first time IPC B23K 37 and IPC G21K 1. This results in novelty in recombination and Nr equal to 1.
A further example related to Nto is EP0065814 (A1), filed by ICI PLC, which includes 6 IPC 8-digit codes and cites 3 patents. Out of 28 eight possible pairs of IPC 8-digit codes between the focal patent and its references, 2 provide an innovative knowledge recombination, i.e., IPC A01N 43 - C07B 49 and IPC C07B 49 – C07C 27. This leads to novelty in technological origins and Nto equal to 1.
A shortcoming of these indicators of novelty is related to changes in the IPC structure. When new IPC codes are introduced, patent offices review and re-classify older patents and, eventually, re-assign them to the new codes. This causes two main problems arise. First, patents may be novel because of the introduction of a new IPC code: Verhoeven et al. (2016) provide evidence that new IPC codes do not affect the validity of the indicators since only 0.5% of patent families are novel due to the introduction of new IPCs. Second, potentially novel patents may not be novel because a new IPC has not been introduced. This could lead to some false negatives, i.e., failure to identify potential novel patents.
433 patents were co-applied for by public and private organizations: provided some public funds were dedicated to the research that led to patent the invention, we consider these patent to represent the output of public rather than private research (Sapsalis et al. 2006). The results of robustness checks (not reported here, but available upon request) excluding these patents do not differ from those reported in the Empirical Analysis section.
Most studies use non-patent literature to proxy for basic research or science.
To provide a better measure of the correlation between binary variables, we computed tetrachoric correlations. Using this measure, our two dependent variables (Nr and Nto) correlate to 0.7, indicating substantial association between the two measures of radicalness. Accordingly, all the estimates have been replicated using a bivariate probit model that takes into account the potential correlation between errors. Errors reveal to be correlated, however signs, significance, magnitude and differences between coefficients are in line with the ones reported in the paper, and are available upon request. Conversely, the correlation between our two main independent variables (Public and Npl) increases from 0.14 to 0.34. This may lead to multicollinearity problems: we therefore calculated the variance inflation factor (vif) in our regressions. The vif in our estimates reaches a maximum value of 3.44, although the vifs of the independent variables of interest 2.01 at most, considerably below threshold levels (see e.g., O’Brien 2007).
We excluded the sector “Other” which includes 3 non-related technological field (Furniture and games, Other consumer goods and Civil engineering).
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Appendix 1: Robustness check
Appendix 1: Robustness check
To test the robustness of our measures of novelty, that is, Nr and Nto, we run the models specified in Sect. 4.2 using an alternative measure of radicalness conceptualized by Shane (2001) and refined by Squicciarini et al. (2013). The indicator captures to what extent a patent differs from its knowledge sources in terms of technological classification codes. It measures the number of IPC 4-digit codes assigned to the cited patents that do not characterize the citing, focal patent. By so doing, the radicalness indicator gauges the difference between the patent and its knowledge sources in terms of the pieces of knowledge recombined. Since this indicator relies on backward citations, it can be employed to proxy for novelty in technological origin.
Table 9 presents the results of our analysis using the radicalness indicator as the dependent variable. Given the censored nature of this variable, we estimate the coefficients using a Tobit regression to capture the association between the Public and Npl variables and the radicalness indicator.
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Rizzo, U., Barbieri, N., Ramaciotti, L. et al. The division of labour between academia and industry for the generation of radical inventions. J Technol Transf 45, 393–413 (2020). https://doi.org/10.1007/s10961-018-9688-y
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DOI: https://doi.org/10.1007/s10961-018-9688-y