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The Annals of Regional Science

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20.07.2018 | Original Paper

Interregional inventor collaboration and the commercial value of patented inventions: evidence from the US biotechnology industry

verfasst von: Zafer Sonmez

Erschienen in: The Annals of Regional Science | Ausgabe 2/2018

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Abstract

This paper analyzes the relative importance of the spatiality of inventor collaboration links for the quality of invention. It uses patent citation and renewal data to estimate (expected) economic values for a sample of US biotechnology patents, controlling for a set of inventor and owner characteristics. The investigation extends the research by differentiating the quality of knowledge flows while at the same time refining patents as a source of innovation information. The results of the clustered logistic regression and continuation ratio models provide some support for the hypothesis that interregional (non-local) collaboration results in commercially more valuable inventions relative to patents that are product of intraregional (local) collaboration. The same empirical results also indicate that (1) inter-industry (related) knowledge flows contribute to the patent value more than inter-industry (unrelated) or intra-industry knowledge flows and (2) general-purpose technologies/products as measured by citations of patented inventions received from diverse sets of industries are indicative not only of technological/scientific quality, but also of the economic value of patented inventions. These results are robust in different citation-window designations, exclusion of self-citations, different regional definitions and different patent classifications.

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Knowledge base is usually operationalized at the firm level or at the sectoral level in the economic geography literature, but it is also possible to examine the knowledge base of products/inventions.

As noted in Introduction, empirical research examining the impacts of the spatiality of collaborative relationships on inventive activity to date has been limited to quantifying impacts on the organizational and regional levels of innovativeness. Such studies were selected for review to give a current state of empirical findings and provide a basis for comparison with our results.

Beyond being indicators of patent value, Lee (2009: 627) notes that “patent renewals are informative about various features of the process of innovation, including the nature of the process by which the market for an innovation opens up and the extent to which the returns from an innovation become obsolete over time.”

Some authors refer to public and private value of patents, respectively, as technological and economic values (e.g., Bessen 2008; Lee 2009).

Nagaoka et al. (2010) argue that because there is no way to invent around new chemical entities in drugs (as protected by a compound patent), patents are a relatively effective mechanism for appropriating rents from innovation in the biopharmaceutical industry.

The World Intellectual Property Organization -WIPO- considers biotechnology sectors comprised of the following classes: C07G, C07K, C12M, C12N, C12P, C12Q, C12R, C12S (Schmoch 2008). These classes roughly correspond to those US Patent Classes that are used to identify innovations in the biotechnology industry (see Boschma et al. 2015).

Maurseth (2005) characterizes within-technology class citations as a “creative destruction effect in research rivalry.” That is, citations from same-technology fields to a patent are indicative of this patent being obsolete. This characterization is consistent with Hypothesis 3, and to the extent this is the case in the US biotechnology industry, patents with low generality scores are less likely to be renewed.

Fifteen miles was selected as the lowest threshold point because it is the average commuting distance in the USA (U.S. Depart of Transportation 2003). Although somewhat arbitrary, other thresholds are multipliers of 15 and serve as comparison points. Variables that were constructed using these thresholds are named Interreg_Collab3, Interreg_Collab4 and Interreg_Collab5, respectively.

In order to check the robustness of the results to inconsistencies in patent examiners’ classification decisions, we computed all three forward citation variables using 3-digit US patent technical classes. Results are available upon request.

The analysis of patent citations in our dataset showed that during a 15-year time window, more than 50% of the citations were made within five years following the publication of the patent and more than 90% of the citations were made within the first ten years. Therefore, a 10-year citation window captures nearly all possible citations made.

It is noted in the literature that self-citations are usually added for strategic reasons by the applicants and therefore cannot be considered to signal technological impact or value (Mariani 2004; Hall et al. 2005; Nemet and Johnson 2012). We ran all regression models by excluding self-citations and obtained very similar results. These results are available upon request.

The interpretation of findings in first columns of Table 3 (i.e., renewal 0 vs. renewal 1, 2, 3) is the same as that of binary logistic regression.

These three variables together serve as a substitute for the generality score.

Note that we experimented with the sum approach and still obtained the same results. Similarly, no difference is observed in the model results when the spatial dependence variable (Neighbor_Inv) is replaced with the alternative variable which was constructed using patents (Neighbor_Pat).

We checked the regression residuals for potentially remaining spatial dependencies using Moran’s I. The results indicate that the spatial distribution of residuals is likely random (index: 0.0043, z-score: 0.2022, p value: 0.8397). Similarly, this statistic is not significant for any of the models presented in the following pages. We thank anonymous reviewers for recommending this robustness check.

The assumption appears to hold for three variables only: Inv_Patent_Stock, Frwd_Cit_Internal and Frwd_Cit_Near. That means we will observe constant differences in log odds (logits) across outcome levels for these variables.

We present results for only the baseline and full models.

Note that the results in the first column (Model 2 in Table 3) are the same as the logistic regression results (Model 8 in Table 2, as the sequential logit regression equation suggests).

As noted above, we recognize that those studies provide an indirect comparison for our findings.

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Titel: Interregional inventor collaboration and the commercial value of patented inventions: evidence from the US biotechnology industry
verfasst von: Zafer Sonmez
Publikationsdatum: 20.07.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: The Annals of Regional Science / Ausgabe 2/2018
Print ISSN: 0570-1864
Elektronische ISSN: 1432-0592
DOI: https://doi.org/10.1007/s00168-018-0874-5

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