Introduction

The increasingly expensive patent maintenance fees needed to protect intellectual property bring the necessity to better approximate patent value and to identify relevant indicators for this patent value. Prior studies on the measurement of patent value assume that this value can be reflected in the length of patent renewals [1–7]. These have showed that patent renewal and expiration data are useful indicators to estimate the value of protected innovations and are counted amongst the few sources of established measures of patent value. Renewal decisions reveal the commercial potential that these patents may bring to the market and are an indication that their value exceeds the cost of their maintenance. While patent protection is an important source of economic returns from innovative activities, valuing patents still poses a challenge to policymakers and analysts in science and technology.

Unlike the attention given to industry patenting, the value of university patenting has received less attention in the literature. Moreover, there is a lack of evidence regarding the relationship between research funding and the economic value of patents. After the passage of the Bayh–Dole Act in 1980, university researchers became more active in patenting. The Bayh-Dole Act has been widely cited as an important technology policy that facilitates the patenting and licensing of academic-led and federally-funded inventions in the US. This act enabled universities to retain the rights to patents which emanate from federally funded research programs and encouraged them to collaborate with industry to promote the utilization of their patents arising from such public funding. The passage of this legislation changed the way academic inventors develop technologies from government-funded research in the US and since then, many countries have adopted similar policies [8–10].

The nature of funding behind university inventions could provide a useful platform though which to study their commercialization and transformation into new products. Although inventions that have been developed using industry funding are intuitively more likely to result in commercial success, because they are often the result of a request or need from the private sector, we hypothesize that government-funded patents owned by universities could also be associated with higher patent value compared with those of less funded or not funded academic inventors. We shed light on this question by studying under which conditions university nanotechnology patents are more valuable, i.e. when it is worth paying the patent renewal fees. Nanotechnology has been under scrutiny ever since its emergence and has led to many patents. Yet, it is still very much a science-based field and as such provides a perfect case for our analysis of the factors that influence university patent renewals.

Because of the substantial public investment in nanotechnology research, the economic value of the resulting academic patents, as a measure of impact of these policies, is of great importance to policy makers. Public decision makers generally combine various patent indicators to measure the impact of their policies on technological outputs in order to infer economic development or performance. The recent CCA report in 2018 [11] on the state of science and technology (S&T) and industrial R&D is the perfect example of this type of measurement. Despite the fact that patent counts are commonly used for this purpose, mainly due to a lack of data on other measures, it is accepted that alternatives related to the importance or value are more useful and give more reliable and practical results. For example Carpenter et al. [12] worked on backward citations, Lerner [13] used the scope of patents, Tong and Frame [14] applied the claims and Lanjouw [15] employed the renewal of patents as value indicators.

The article focuses on the relationship between government support for university research and commercial potential of patents exemplified by renewal decisions by academics and/or their universities. It provides evidence to the effect that receiving government funding infers a higher economic value of academic innovations and as such constitutes a novel research avenue that differs from prior studies of patent renewal data. We are fortunate to have access to a full database of Canadian federal funding with which to explore this relationship. For this purpose, we employ a sample of Canadian patenting data extracted from the United States Patent and Trademark Office (USPTO) integrated with Canadian federal funding agencies data.

The economic literature suggests that characteristics such as including more claims, having more backward citations, and more frequent citations by later patents, constitute evidence of the private value of patents. In this study we also demonstrate the relevance of patent quality indicators–the number of citations that patents received, and the number of claims contained in the patents–on patent renewal decisions. While patent citations are a generally accepted measure of quality that can be used to approximate patent value [16], there is a more complex relationship between the number of patent claims and patent value as it is not systematically associated with patent value [17,18]. Patents with a higher number of claims are better protected and can be more important; yet, the number of claims is an underutilized indicator to measure patent value. One can argue that the number of claims is the most informative measures, but it might be affected by the examiners. Patentees have incentives to claim as much as it is possible to define the rights of the patentees when they file their applications, but the examiners may ask them to narrow the claims. The other factor that would affect the number of claims is the change in patent application fees [17,19].

We find that receiving public funding has a positive effect on the value of patents in universities and these patents are more likely to be renewed in subsequent years. Our analysis establishes clear evidence that government funding is fruitful for researchers in universities and increases the value of the patents to be commercialized in industry.

The remainder of the paper is organized as follows. Section 2 presents the relevant literature to our theoretical framework and our hypotheses surrounding patent renewal decisions. Section 3 provides a detailed description of the dataset and the constructed variables that are used in this study. Section 4 links funding and two patent indicators to patent renewal decisions and presents the results for the empirical testing our hypotheses. Finally, Section 5 concludes with a brief discussion of the results and of their implications.

Literature review and proposed hypotheses

Most firms that patent are influenced by the potential value of their patents, and patent portfolios are an intrinsic part of the value creation process of a firm. Firms with valuable patent portfolios and strong production capabilities are better positioned to capture greater market share. According to Grimaldi et al. [20], a valuable patent portfolio is essential for a firm’s strategic business objectives and as such supports the value creation process of the firm.

The precise value that a patent contributes to a product is a rather subjective issue and assessing market value of a specific patent in a given product when multiple and complementary patents are incorporated in the said product is a complicated matter [21]. Patents that have higher commercial value can drive technological advances and are of great importance for economists and policymakers. Various indicators have been developed in prior studies on patent statistics—including patent citations, value-weighted patent counts, litigated patents, licensing, and patent renewal—to explore the value estimation of inventions [3]. Pakes and Schankerman [4], Pakes [22], and Schankerman and Pakes [7] were the first to develop models on patent renewal decisions aimed at assessing patent value. Because renewing a patent implies a cost, patent renewals are interpreted as indicators of the expected value of patents. These studies assume that only economically profitable patents are renewed for longer periods of time. Patent renewal decisions also offer a metric of self-valuation of patents by their owners. Using a survey-based estimation of the economic value of patents, Harhoff et al. [23] highlighted that full-term patents are more valuable on average compared to those allowed to lapse at midterm.

To get the full extent of patent protection, owners should pay their maintenance fees three times in a patent’s legal life, and each time, the amount required is larger than for the previous stage. Generally, if the all maintenance fees are paid, patents will expire after 20 years from the granting date. According to United States Patent and Trademark Office (USPTO) policies, if the maintenance fees are not paid by the end of 4^th, 8^th or 12^th years after the grant date of a patent, the patent is considered expired and the entire patent rights lapse. Rational holders of patents should only desire to pay additional fees if patent value is high and exceeds the cost of renewal fees [5]. Meyer and Tang [3] indicated that patentees engage in a renewal decision if the estimation of profit return of the patent is greater than the current cost of renewal. Patent holders also probably decide to patent in patent offices of other countries where net returns are positive on the international flow of returns. Lanjouw and Schankerman [24] showed that patent quality, measured by an index of patent citations and number of claims, plays a role in the renewal decisions of patentees.

Data and methodology

Dependent and explanatory variables

We built a panel dataset at the individual academic-inventor level and defined our dependent variables based on a ratio of the total number of patent renewals attributed to an individual academic inventor divided by the total number of patents of that individual inventor (we have data for each individual over a period of 10 years, 1996–2005). Three dependent variables were constructed based on the number of the years that a patent was renewed: to study the factors that influence whether a patent was renewed 4 years after the grant year (PatentRenew4), we use Eq 1; for patents renewed after 8 years (PatentRenew8), we use Eq 2; and for patent renewed after 12 years (PatentRenew12), we use Eq 3 (we use the total number of patents by year in these equations). These three variables measure the proportion of patents that are renewed in a given year with respect to all patents on which an academic is a named inventor. Assignees cannot renew patents in the second phase (after 8 years) if they have not renewed patent protection after 4 years. The same is true for renewal after 12 years, which is deemed the most valuable renewal. We also define three associated dummy variables (dPatentRenew4, dPatentRenew8 and dPatentRenew12) to indicate whether patents were renewed or not. These dummy variables take the value 1 if their equivalent proportion variable is different from 0, and are used in probit regressions to estimate the probability of being renewed in subsequent years based on the funding that their inventors received.

(Eq 1)(Eq 2)(Eq 3)

Because patents of higher quality are likely to be of greater value (H1), we therefore use the number of forward citations as an explanatory variable to find their relationship with patent renewal decisions. Patents that are renewed are more likely to be highly cited than patents that are allowed to expire before their full term terminates.

We divide the number of forward citations received by the patents granted to an academic inventor over the 5-year period (in the final models, we found that 5-year citations for patents give us more consistently significant results compared to 3-year and 7-year time windows) after the patent grant year by the total number of patents of the same academic inventor (AvgCitPerPat). Because the analysis is performed at the individual academic inventor level, all data were aggregated at the academic inventor-year level to create a panel database.

(Eq 4)

Similarly, the explanatory variable related to the number of claims to examine our second hypothesis was calculated using the same principle as for the number of citations (AvgClaimPerPat).

(Eq 5)

Our third explanatory variable is based on the accumulated amount of funding obtained by academic inventors in each year (PubFunding). Government funding has long been recognized as critical to knowledge development in universities. Since the patenting is more likely to happen at the end of a funding period, i.e. after the research has been performed, we include a one-year lag for funding before the patent application to avoid contemporaneous effects of government funding.

Finally, we account for regional fixed effects by defining dummy variables for each province: dQC takes value 1 if inventors are from Quebec universities, 0 otherwise; dON takes value 1 if inventors are from Ontario universities, 0 otherwise; dBC takes value 1 if inventors are from British Columbia universities, 0 otherwise; dAL takes value 1 if inventors are from Alberta universities, 0 otherwise; dCanada_others takes value 1 if inventors are from universities of provinces other than Quebec, Ontario, British Columbia and Alberta, 0 otherwise.

Descriptive statistics

Our sample comprises 7,664 observations, for 1,112 academic inventors, over a period of 10 years. Some scientists had not started their career in 1996 and other were no longer active in 2005, hence the unbalanced panel. The descriptive statistics of the sample are presented in S1 Table (correlation matrix) and S2 Table (descriptive statistics) in supporting information. Fig 1 shows that most of patents are renewed for the first time at year 4, but that the rate of renewal is much lower after 8 and 12 years.

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Fig 1. Comparing the patent renewal in 4, 8 and 12 years.

https://doi.org/10.1371/journal.pone.0202643.g001

Fig 2A and 2B provide an overview of the average number of patents and average number of patent renewals in 4, 8 and 12 years with respect to the average amount of public funding raised by academic inventors. As public funding increases, the number of renewals observed become increasingly low. Funding seem to play a role for the amounts below $120,000. Fig 2B focuses on inventors who received funds between $10,000 and $100,000. While patents are renewed after 4 and 8 years at a relatively high rate, inventors more often let their patent applications lapse after 12 years without requesting a third patent renewal. Furthermore, the proportion of patents that are renewed in subsequent years shows decreasing returns. In our sample, 55% of the inventors have at least one patent over a period 10 year. Overall, 32% of inventors renewed at least one patent after 4 years, whereas 68% of inventors never renewed their patents at all. After 8 years, these values are much lower: 13% of inventors renewed at least one patent; and the observed patent renewal for 12 years is only of 4%.

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Fig 2. Number of patent renewals by average amount of funding.

https://doi.org/10.1371/journal.pone.0202643.g002

Regression results

This section presents the results of the three types of models (ivtobit, ivprobit and Cox proportional hazard regressions) on the patent renewal decisions (results for ordinary least squares and two-stage least squares regressions are presented in S3, S4 and S5 Tables in supporting information). Multiple regression estimations for different specifications of each model were conducted to evaluate the sensitivity of our results. Separate regressions (models 1 to 3) were estimated to evaluate whether the amount of funding received by inventors for their research, the number of citations and the number of claims of their patents influence the value of these patents. Year dummies were added to control unobserved year fixed effects. The Wald chi-square values are highly significant, confirming that our models fit the data significantly better than a null model (we also use the number of renewed patents of an inventor as dependent variable instead of the ratio in our analysis and the results were the same. Please see S6, S7 and S8 Tables in supporting information).

In each of the three tables, Tables 1, 2 and 3, we report both the second stage (top of the table) and the first stage (bottom of the table) regressions for the ivtobit and ivprobit models. In all three tables, we find a consistently positive and significant effect of our three instruments (dCanadaChair, Age and nbArtCum), suggesting that holding a research chair, being older and having published more articles in the past explain part of the quality of academic researchers who succeed in raising public funding. It is not surprising that the cumulative number of articles published by an academic inventor plays a role in receiving a greater amount of funding. Publishing articles provides visibility to researchers and increases their relative citation rate, which both matter when submitting grant proposals. The prestige of the researcher provides a greater visibility for that researcher and highlights their research and development excellence. A research chair demonstrates the ability of the individual in attracting research funding based on the excellence of her research and has the expected positive influence on the likelihood of raising more government funding.

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Table 1. Impact of government funding on 4-year patent renewal decisions (PatentRenew4) in Canada–Regression results of the ivtobit and ivprobit model.

https://doi.org/10.1371/journal.pone.0202643.t001

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Table 2. Impact of government funding on 8-year patent renewal decisions (PatentRenew8) in Canada–Regression results of the ivtobit and ivprobit model.

https://doi.org/10.1371/journal.pone.0202643.t002

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Table 3. Impact of government funding on 12-year patent renewal decisions (PatentRenew12) in Canada–Regression results of the ivtobit and probit model.

https://doi.org/10.1371/journal.pone.0202643.t003

We formulated the expectation that highly cited patents are correlated with highly valued patents. Our results in Table 1, Table 2 and Table 3 confirm these expectations. A higher number of citations eventually yields a patent that is more likely to be commercialized in the market. For that reason, these patents are more likely to be renewed after 4 years. In regard to the number of citations, at first sight, we found that receiving more citations positively influences the patent renewal decisions after 4 years (Model 2 in Table 1), 8 years (Model 2 in Table 2) and even 12 years (Model 2 in Table 3). We investigated whether non-linear effects would better fit our model. Only in the regressions for the final renewal stage is the quadratic term significant and despite its negative sign, the overall effect remains positive except for the renewal in 12 years (exhibiting diminishing returns). For the first and second renewal stages (after 4 and 8 years), we found a linear and positive impact of the number of citations which suggests that patent renewal decisions benefit from a greater number of patent citations, i.e. patents of a greater quality are more likely to be renewed, hence providing support for our first hypothesis.

The third columns of each table also show that the number of claims positively increase the probability of renewals but when we include non-linear effects, the results are mostly located along the decreasing part of an inverted U-shaped curve. Regarding this non-linear effect, it is important to note that if the patents of an academic inventor have more claims (more than 3 claims in our sample), they are not more likely to be renewed in subsequent years. These findings provide partial support for our second hypothesis. This finding is likely to be linked to the fact that fees vary for excessive claims. There is a large additional fee if a patent documents make multiple claims, and in this case the fees include an additional cost per extra claim in excess of 20 claims in the USPTO (the excess claims fees are charged in excess of three for each independent claim). The negative effect is likely due to these excess claims.

Our third hypothesis examined the influence of public funding. Not surprisingly, our findings support the fact that public funding is associated with a positive impact on patent renewals. In other words, when academic inventors raise more public funding, they have more patents that are renewed in subsequent years. We found significant results for all 4-year, 8-year and 12-year renewal decisions. This could be due to the fact that government funding has a positive effect on patent quality [53]. Higher value patents are more likely to be extended as long as they give benefits to the owner. Public funding has a direct effect on patent quality, and these patents have a higher chance to be renewed. These results validate our third hypothesis and clearly demonstrate the positive correlation between public funding and patent renewal decisions.

Turning now briefly to our control variables, we find that the chances of renewing a patent are higher when academic inventors have more patents, i.e. there is a positive correlation between the total number of patents (nbPatCum) and patent renewals in all three tables (Tables 1, 2 and 3).

Universities are significant bases for the development of technological innovation and enhancing their invention capacity is an important development challenge. Facing these renewal decisions, one can raise the question as to where funding yields the highest impact on renewal decisions in universities in all provinces of Canada. Our results show that the four provinces of Quebec (dQC), Ontario (dON), British Columbia (dBC) and Alberta (dAL) are significantly different from the other provinces (dCanada_others is the omitted dummy variable). Thus inventors from the universities of these provinces have higher renewal rates compared to the other provinces.

Our last model, takes the analysis at the patent level (rather than at the academic inventor level). Table 4 shows the results of Cox proportional hazard regressions. We report three models including control variables and year dummies. In all three models, the hazard ratio is greater than one and the coefficient of average funding is significant and positive. In addition, average funding that was allocated to patents increase the likelihood of renewals. These findings are consistent with our previous funding at the individual level (please note that we apply this survival analysis only for robustness check because there are some issues when patents are analyzed individually in terms of funding. Funding generally comes to researchers and not specific patents and for academic researchers, this funding goes to both publications and patents and allocating funding to each of them is the main issue).

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Table 4. Impact of government funding on patent renewal decisions–results of Cox proportional hazards.

https://doi.org/10.1371/journal.pone.0202643.t004

Fig 3 illustrates the smoothed hazard function and smoothed hazard estimates of our model estimated using a kernel method. This actually plots the log estimated hazards and the curve uses the mean values of predictors. The plot suggests that the risk of death for patents as the hazard increases over time. The analysis time indicates the renewal decisions at time t where t equals 1 for the renewal after 4 years, t equals 2 for the renewal after 8 years and equals 3 for the renewal after 12 years.

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Fig 3.

Hazard function curve (a: smoothed hazard estimate and b: cox proportional hazards regression), analysis time indicates the renewal decisions at time t, (t equals 1 for the renewal after 4 years, t equals 2 for the renewal after 8 years and equals 3 for the renewal after 12 years).

https://doi.org/10.1371/journal.pone.0202643.g003

Discussion and conclusion

This empirical study explores the question of the impact of public funding on patent renewals over their lifetime. For this purpose, we employed a sample of Canadian nanotechnology patents. Our study compiled the academic patents to which Canadian academic inventors have contributed. Our dataset enabled us to extend our research in various directions: first, to analyze whether the number of citations received by patents is a valid indicator of economic value of inventions; second, to test the impact of the number of claims on patent quality; third, to empirically investigate whether public policies and funding programs affect patent values using the renewal of patents.

We indeed find that government-funded research in universities is an important consideration when we examine academic patents. With this data, we have shown that the amount of funding received by an academic inventor exhibits a positive effect on the tendency to renew their patents. The effect of funding programs on the value of granted patents is to enhance the probability of renewing patents in subsequent years and encourage inventors with great commercialization opportunities. In universities, because government accounts for a comprehensively larger amount of funding, it is important to disentangle the role of government in the economic value of patents; this is undoubtedly the most important finding of this paper. By matching renewal information data with bibliometric analysis of patent statistics, we are able to evaluate the policy impacts on the quality and value of patents. To the best of our knowledge, no such analysis has been performed on the relationship between funding and renewal decisions. This gives a clear view on how public funding serves as an indicator of invention output of academic research, and it highlights to what extent government incentives can be fruitful for researchers. Our detailed examination reveals insights on effective policy regarding the market value of patents. University patents are usually slow to acknowledge the effort required to transform a patent into a commercial product. More substantial work is necessary to increase the opportunities for a patent to be commercialized in industry. Applicability and marketability of a granted patent is a time related process, and inventors need to maintain their inventions for a longer time before they are commercially viable. Due to the fact that university funds mainly come from government, government should not only intensify the funding of inventive activities, but also make the relevant supporting policies to provide a long-term funding mechanism for the innovation of academic inventors.

In regard to number of claims, our results provide useful policy designs to encourage strategies to narrow patent claims. This study shows that perceived importance of the claims is not associated with patent value in terms of renewal decisions. Interestingly, regarding the challenge of assessing the effect of the number of claims in determining patent value, we cannot find a positive impact of claims on patent renewal decisions in subsequent years after the grant year despite the relationship of number of claims to patent quality. Most interestingly, our model explains patent citations as an indicator of patent value with a strong explanatory power for patent renewals.

However, the limitations of our study cannot be neglected as they affect the generalization of our findings to all university patents. First, our sample data was drawn from a population of nanotechnology university patents, and generalization to other fields should be done cautiously. Second, although patent renewals are good indicators of patent value, they are not perfect. Inventors can maintain their patents for a longer time even if they have low value, but this is difficult to identify. Finally, one needs to verify whether private funding has an effect on these renewal decisions. Our data suffers from a lack of information regarding private funding, as the private sector might be more interested than the public sector in technological inventions from universities. And often, private funding represents direct commands for the solving of specific industrial problems. Lacking this data, we are unable to say how such an effect would influence our findings.

Although this study provides insights about funding and patent value in universities, a number of other avenues for future research are open. One would have to rule out the other factors that play a role in patent renewal decisions in universities. One such factor is the market potential of these inventions. Market maturity is expected to be an important indicator in renewal decisions. One would expect that the potential market of the granted patent is at early stages and it is likely to have a successful market for a long time or on the opposite, it could be in the late stage and may have less success in the market. There is also a need to find out how government funding acts in reducing researchers’ financial constraints to pay the corresponding renewal fees. This would require funding information for the entire duration of the period, i.e. from 1995 to 2017.

Supporting information