CHAPTER 7

CATEGORIZATION AND ANALYSIS OF ACADEMIC PATENTS: DEVELOPING A FRAMEWORK TO EXAMINE DIFFERENCES IN TECHNOLOGY, OPPORTUNITY, AND COMMERCIALIZATION CHARACTERISTICS

Jonas Gabrielsson, Diamanto Politis and Åsa Lindholm Dahlstrand

ABSTRACT

There has been a significant rise in the number of patents originating from academic environments. However, current conceptualizations of academic patents provide a largely homogenous approach to define this entrepreneurial form of technology transfer. In this study we develop a novel categorization framework that identifies three subsets of academic patents which are conceptually distinct from each other. By applying the categorization framework on a unique database of Swedish patents we furthermore find support for its usefulness in detecting underlying differences in technology, opportunity, and commercialization characteristics among the three subsets of academic patents.

Keywords: Commercialization; inventions; technology; opportunity; patents; university

INTRODUCTION

The active contribution of universities to economic development has become a cornerstone in modern higher education policy. This goes beyond the more traditional mandate of universities in providing academic education and basic research (Mowery, Nelson, Sampat, & Ziedonis, 2004) and emphasizes their potential role as engines for innovation and economic development via the transfer of scientific and technological knowledge to industry and broader society (e.g., Cohen, Nelson, & Walsh, 2002; Mansfield, 1998). Nowadays, universities are in this respect expected to serve as “innovation hubs” (e.g., Youtie & Shapira, 2008) in regional and national economies by supporting and promoting the commercialization of academic research conducted within their organizational boundaries (Rasmussen, Moen, & Gulbrandsen, 2006; Wigren-Kristoferson, Gabrielsson, & Kitagawa, 2011).

One widely recognized route for disseminating scientific and technological knowledge originating from universities is by means of academic patenting (Allen, Link, & Rosenbaum, 2007; Shane, 2004; Walsh & Huang, 2014). Academic patenting reflects a unique dimension of academic entrepreneurship since it represents and encapsulates scholarly inventive activity that results in intellectual property (IP) that can be commercially exploited (Allen et al., 2007; Shane, 2004). Academic patenting is also an interesting phenomenon for entrepreneurship scholars since patents provide legal protection from the appropriation of IP by competitors by granting an exclusive right to exploit the underlying technological opportunity on a market (Gans & Stern, 2003). In this respect, a patent provides signals that an academic invention has potential commercial value.

Since the 1980s there has been a significant rise in the number of patents originating from academic environments both in the United States and across Europe (e.g., Geuna & Nesta, 2006; Mowery, Nelson, Sampat, & Ziedonis, 2001; Trajtenberg, Henderson, & Jaffe, 1992; Wright, Clarysse, Mustar, & Lockett, 2007; Zucker & Darby, 2001). The growing interest among scholars in understanding both the determinants and spatial distribution of this trend stem from the underlying potential of academic patents as a technology transfer mechanism that aid entrepreneurial efforts to commercialize and diffuse academic research. Research on academic patenting has identified and distinguished between different kinds of patents as a basis for making theoretical and empirical studies. One main distinction is between university-invented and university-owned patents. The former coincide with the widely accepted definition of academic patents as “any patent signed at least by one academic inventor, while working at his or her university” (Lissoni, 2012, p. 198; see also similar ways of defining academic patents in Göktepe-Hultén, 2008; Ljungberg & McKelvey, 2012; Meyer, 2006). University-owned patents, on the other hand, are a subset of academic patents where universities who employ the inventors retain the IP created from research activity conducted in academic environments. Studies show for example that the relative weight of university-owned patents over academic patents depend largely on both intellectual property rights (IPR) regimes and historical levels of university autonomy embedded in a given country (Della Malva, Lissoni, & Llerena, 2013; Lissoni, Pezzoni, Poti, & Romagnosi, 2013) and these legal and institutional factors also play a significant role in explaining which channels are typically used for commercializing academic patents (e.g., Giuri, Munari, & Pasquini, 2013).

Another main distinction in the literature is between academic patents and corporate patents, where the latter represent IP originating from R&D efforts in private industry. The main issue in this stream of research has been to compare if academic and corporate patents have different or similar value distributions and also if they share common determinants of value (Czarnitzki, Hussinger, & Schneider, 2011; Sapsalis, van Pottelsberghe de la Potterie, & Navon, 2006). At least two generalities can be highlighted from past studies on this issue. First, as emphasized by Sapsalis et al. (2006, p. 1632) there are almost as many potential methodologies to assess the value of patents as the number of existing investigations. Second, studies seem on the aggregate to suggest that the value distribution of academic and corporate patents often is very close to each other (Czarnitzki et al., 2011; Henderson, Jaffe, & Trajtenberg, 1998; Sapsalis et al., 2006). This latter issue may suggest that patent value is driven by things other than inventorship or ownership, but it may also signal that the current way of distinguishing between different kinds of patents are too coarse to detect meaningful features and underlying characteristics.

While past research on academic patents to a large extent has been driven by methodological concerns related to the exploration and assessment of appropriate indicators and building up comprehensive and reliable datasets (Lissoni, 2012), in this study we are interested in understanding academic patenting in the broader frame of academic entrepreneurship. A widely diffused approach in the literature is the highly systemic approach that is taken into account for understanding the dynamic interactions between scholarly research and related technology transfer initiatives, both within the university system itself as well as in collaboration with industry (Kirby, 2006; Rothaermel, Agung, & Jiang, 2007). For example, in their comprehensive and detailed literature review, Rothaermel et al. (2007, pp. 706–708) conceptualize the core of the overall university innovation system as the advancement and diffusion of university-generated technology. This core is furthermore facilitated through technology transfer offices (TTOs) and other intermediaries such as incubators and science parks. However, these intermediaries expand academic entrepreneurship to also include agents and activities outside the local university system and where universities become embedded in a larger environmental context which encompass university–industry ties and other supporting networks of innovation (Balconi, Breschi, & Lissoni, 2004; Beaudry & Kananian, 2013). In this respect, universities assume an expanded boundary-spanning role where they are expected to meditate among academic, industrial, and public spheres in the broader innovation system surrounding these entities (Rothaermel et al., 2007; Youtie & Shapira, 2008).

In this study we follow the systemic approach advocated by Rothaermel et al. (2007). Academic patents as an entrepreneurial form of university technology transfer are in this respect often conceptualized and understood in terms of the professional affiliation of its inventors (Lissoni, 2012). However, when framed as embedded in a larger university innovation system (Rothaermel et al., 2007) academic patents can also be conceptualized and understood in terms of IP originating from academic environments (Shane, 2004), thus creating dual entries for understanding the phenomenon. Interestingly, this duality in understanding academic patents target a fundamental issue in contemporary research on academic patents; namely that of how to define and demarcate the phenomenon. In this respect, based on our argumentation above we argue in this study for the need to open up and develop the conceptualization of academic patents based on the professional affiliation of the inventor (Lissoni, 2012; Ljungberg & McKelvey, 2012) by also including whether the source of the IP underlying the invention originated from academic research (Shane, 2004).

Against this backdrop, the aim of this study is to develop and refine our understanding of academic patents by presenting and testing a novel categorization framework to better understand the complex and multidimensional nature of this phenomenon. While past research on academic patents undoubtedly has contributed to the development of a rich and highly potent body of scholarly knowledge, we believe that defining academic patents based only on the professional affiliation of the inventor(s) provide an overly simplified and largely homogeneous view of this entrepreneurial form of university technology transfer that potentially hide underlying differences in opportunity and commercialization characteristics. In this scholarly effort, we thus challenge the traditional way of defining academic patents by identifying three different and conceptually distinct categories of academic patents:

• Academics employed by a university who patent inventions originating from university research
• Academics employed by a university but who patent inventions originating from sources outside the university
• Individuals that are not employed by a university but who patent inventions originating from university research

The central hypothesis we put forward in this study is that a more elaborated definition and categorization of academic patents can open up for identifying and distinguishing potential differences in technology, opportunity and commercialization characteristics. By providing such a framework, the study has great potential to contribute to current literature and research on academic entrepreneurship in several ways. First and foremost, our framework builds on and integrates findings from the broader literature on academic entrepreneurship by recognizing that university-employed academics can be engaged in a wide range of enterprising activities outside their own research (Klofsten & Jones-Evans, 2000; Wigren-Kristoferson, Gabrielsson, & Kitagawa, 2011), which may then serve as a viable source of academic inventions. The framework also recognizes that academic patents may be based on IP originating from academic research but where the inventor(s) are not formally employed by a university at the time when the patent is applied for (Lindholm Dahlstrand, 1999). Hence, although university-employed academics who patent inventions may base this more or less directly linked to their own academic research there is a potential risk that definitions of academic patents that look only on the affiliation of the inventor may contain a proportion of not-so-relevant patents (a type I error) while also missing other patents that would be potentially relevant to include and assess (a type II error).

Second, our framework for categorizing different kinds of academic patents has also potential to generate a more fine-grained understanding of academic patents with respect to their features and underlying characteristics. Based on a unique handcrafted database with detailed information about patents granted to private individuals in Sweden between 1996 and 2005, we analyze whether the resulting categories of academic patents perform with respect to parameters such as technological fields (Ernst, 2003), novelty (Abernathy & Clark, 1985), level of technological opportunity which underlie the patented invention (Zahra, 1996) as well as their routes of commercialization (Giuri et al., 2013; Svensson, 2012).

Third, we also believe that the categorization framework that we develop in this study can be a useful device for TTO managers and other actors who operate in the university innovation system with the assigned task of promoting and supporting technology transfer. Our approach provides them with a theoretical foundation for distinguishing, segmenting, and targeting different groups of academic patents. Much in line with the comment by Gartner (1985) that the process of creating a business is not “a well-worn route marched along again and again by identical entrepreneurs” (p. 697), we analogously emphasize that there is little practical value in conceptualizing academic patents as a homogenous group of inventions. Following this line of reasoning we thus suggest that different kinds of academic patents can be conceptually distinguished from each other based on two basic dimensions; one based on whether the patent is signed at least by one academic inventor (Lissoni, 2012), and the other based on whether the IP underlying the patented invention originated from an academic environment (Shane, 2004). Thereby, our categorization framework enables the development of more tailored and customized efforts to promote technology transfer initiatives, which also support the current move toward embracing an economic development mandate in contemporary higher education policy.

LITERATURE REVIEW

Technology, Innovation, and Economic Growth

Economic theories have long emphasized the critical role of technical inventions and new scientific discoveries for driving innovation, industrial renewal, and growth in society. A main foundation for this theoretical conception is the work of Schumpeter who in his long series of influential writings described the economic system as an evolutionary process of continuous innovation and creative destruction (e.g., 1934, 1939, 1942). In his pioneering work, Schumpeter rejected the idea of economies being in a stationary state characterized by perfect competitive equilibrium and instead he put forward the notion of long wave cycles of economic activity that alters and displaces the previous technological and economic order. In his theorizing, technological change and economic development was hence an intertwined process that proceed in cyclical fashion along several time scales, going through periods of depression, recovery, and boom and back to depression again (see also, Freeman & Louca, 2001). Each cycle is moreover unique in the sense that they form around the application of a new set of technologies that together destroy previous economic, organizational, and regulatory paradigms, which subsequently have a powerful transforming effect on the economy (Aghion & Howitt, 1992). Largely building on these ideas, contemporary theories of innovation often emphasize the potent and potentially disruptive force of novel technologies that over time sustain economic development and growth, while also destroying and displacing the equilibrium state that previously existed (e.g., Fagerberg, Mowery, & Nelson, 2004).

Universities and Innovation

A consistent theme in research on innovation and economic development is that universities have come to be increasingly seen as crucial stakeholders in the innovation process (i.e., Feller, Ailes, & Roessner, 2002; Mansfield & Lee, 1996). Universities are in this stream of research often depicted as important sources of technical inventions and new scientific discoveries that may lead to industrial applications that benefit business and broader society. In line with this, there has been a notable shift in the perception of the fundamental role of universities in society (Kirby, 2006; Rothaermel et al., 2007). From a stance where universities were only expected to perform conventional academic functions, such as conducting basic research and providing higher education, they now have the mandate to also serve as innovation-promoting knowledge hubs that better link academic research with contemporary needs in society and especially the needs of industry (Clark, 1998; Mowery et al., 2004; Rhodes & Slaughter, 2004).

The changing expectation put on universities to become more enterprising and entrepreneurial has furthermore been taken up by policy makers (Wright et al., 2007). One way of supporting the entrepreneurial transformation of universities and the commercialization and diffusion of academic research has been to enforce changes in patent policy and practice (Jaffe, 2000; Wright et al., 2007). Patents are in this respect a way to support the commercialization of academic research as it gives the holder exclusive rights to a new invention for a designated period of time. As such, patent protection provides economic incentives to continue developing industrial applications by reducing or eliminating the fear of competition. Moreover, a patent transforms academic research results into a commodity that can be marketed and sold, thus favoring the creation of knowledge-based enterprises spinning out of the university (Shane, 2004). It also encourages other forms of commercialization of IP, such as licensing activities, as existing firms can see if the invention is useful for them and thereby negotiate with the patent holder for the right to use the invention for a pecuniary fee (Bray & Lee, 2000).

Patent rules and the ownership of IP of universities are linked to national legal regimes and thus there is a difference in the way different countries support and protect inventive activities in the universities that fall within their jurisdictions. A pioneer in the promotion of academic research commercialization is the United States, which in 1980 implemented the Bayh–Dole Act to create a uniform patent policy among the many federal agencies funding academic research existing at the time. This change has in turn led to a significant growth in the number patents owned by US universities (Jaffe, 2000; Sampat, 2006), which in turn has led to a related growth in licensing revenues and start-ups based on academic patents (Shane, 2004). The US experience has been a guiding example for many European countries when increasing expectations and demands from society has been put on universities to commercialize and diffuse their research results (Lissoni, Llerena, McKelvey, & Sanditov, 2008). For example, Belgium and Denmark adopted similar laws as the Bayh–Dole Act in the second half of the 1990s and Germany, Norway, Finland, and Austria followed the same way during the 2000s. Today, the majority of countries in Europe have a system where universities more or less own the IP generated from academic inventions, including France, Ireland, the Netherlands, Poland, and Spain. In contrast, countries such as Sweden, Iceland, and Italy are exceptions with legal systems that today grant ownership of university-generated IP to the academic inventor. Thus, patents are in most European countries university-owned while in the latter three countries they are “managed” by individual academics.

Definition of Academic Patents

The increasing rate at which universities have scaled up their efforts to commercialize academic research has sparked a growing interest among entrepreneurship scholars in examining how research activity conducted in academic environments translates into inventive activity via academic patents. Although widely discussed in the public domain as a single and unified phenomena, different studies use different ways of identifying and defining an academic patent. However, two principal approaches can be identified in academic literature and research (Meyer, 2003). The first approach is to regard academic patents as university-owned patents (i.e., Sapsalis & van Pottelsberghe de la Potterie, 2007). This means that only patents where the university is the assignee, that is, the entity that has the property right to the patent, is considered as academic patents. The other approach is to identify academic patents based on the affiliation and position of the inventor. Academic patents are in this tradition generally defined as patents with one or several inventors affiliated to a university, regardless of assignee (Göktepe-Hultén, 2008; Ljungberg & McKelvey, 2012; Meyer, 2006).

The first option, where academic patents are defined as university-owned patents, may at first sight be a straightforward approach which is relatively easy to operationalize. However, there are considerable differences across countries when it comes to their national innovation systems and traditions for organizing interactions between university and industry (Edquist & Hommen, 2008). For example, in countries such as Sweden, Iceland, and Italy where patents are “managed” by individual academics, little is gained by looking for patents owned by universities. Moreover, Crespi, Geuna, and Nesta (2007) find that university-owned patents in Europe only account for about 15 percent of all patents with at least one academic inventor. Most academic patents in Europe are instead a result of joint research projects where the IP generated is directly assigned outside the university, predominantly to firms (Lissoni et al., 2008). Thus, there is a risk that the approach of defining academic patents as university-owned patents severely underestimate the participation of universities in patenting activities. Due to this, the second approach where the definition of academic patents is based on the affiliation and position of the inventor is generally seen as a more viable option than the first one (Meyer, 2003).

However, another issue which to a much less extent is debated and discussed when it comes to definitional issues is the source of the patent. To some extent this fallacy relates to the general tendency to assume that the IP that academics generate originates from their academic research. However, there are two potential caveats that should be considered before taking this assumption as a fact. First, academics who are involved in inventive activities may not necessarily base them on their own research. Instead, they may own or run one or several businesses alongside their academic position (Klofsten & Jones-Evans, 2000) and the inventions they make may in this respect come from a variety of different commercial sources. Adding to this, it could also be that there is some university research that generates IP conducted by individuals who are not formally employed by the university. This group may consist of students who have worked with their own projects in close cooperation with research units at the university (Lindholm Dahlstrand & Berggren, 2010). They can also be postgraduate or doctoral students who are not formally employed by the university, but who finance their studies by scholarships. This group may also contain academics that once have been active researchers, but who for various reasons has left their employment (Lindholm Dahlstrand, 1999). These concerns about the need to evaluate the source of the academic patent consequently add an additional dimension to the issue of academic patents, which is illustrated in the framework in Fig. 1.

Fig. 1. Framework for Categorizing Different Academic Patents.

Based on our two dimensions, the tentative framework emphasizes four categories of patents which are conceptually distinct from each other. Of these, nonacademic patents represent one category, while the three remaining categories represent different kinds of academic patents. In the upper right corner we have a category of university-employed academics that generate IP based on their research. They consequently fulfill the criteria of academic patents in terms of both affiliation and source, thus placing them in the “core” of the discussion of academic patents. Thereafter, in the upper left corner we have university-employed academics who may or may not be research active but who patent inventions which originate from outside the university context. While fulfilling the criteria of university employment they consequently fail with respect to the source of the invention. These can in this respect be seen as quasi-academic patents, since they do not connect to any research conducted within the university. In the lower right corner, we finally have patents signed by inventors who are not formally employed by the university but based on IP generated from academic research. From this point of view, these are academic patents that are “hidden” in the sense that they cannot be traced and found in databases with information only about the professional affiliation of the inventor(s).

In sum, our categorization framework recognizes the need to define and demarcate different subsets academic patents based on both the affiliation of the inventor(s) as well as the source of the patented invention. To the best of our knowledge this is a novel approach that challenges the traditional way of defining academic patents. Starting from a core of academic patents represented by university-employed inventors who patent IP originating from academic research, the framework recognizes a subset of largely hidden academic patents that are not typically detected in empirical studies but which would be highly relevant to include in future scholarly studies. Moreover, the framework also identifies another subset of quasi-academic patents whereby university-employees are involved as inventors but which are not directly linked to any academic research. Based on these outcomes, the rest of the study will be devoted to analyzing and assessing underlying differences in technology, opportunity, and commercialization characteristics among the three identified subsets of academic patents.

SAMPLE AND DATA COLLECTION

The legal regime in Sweden provides full ownership of academic inventions to individual academics. Due to this, we targeted patents granted to private individuals. The first step in this process was to identify our sample. A critical decision was whether we should rely on patents granted by the Swedish Patent Office (PRV) or the European Patent Office (EPO). A guiding parameter for our decision was that we wanted to examine patents granted between 1996 and 2005 to increase the sample size and control for potential year-to-year variations. During the 1990s there was a steady growth in patent applications (first filings) to PRV. The trend was broken around 2001, when a reverse trend of a steady yearly decline started in favor of EPO patents (e.g., Granstrand, 2006). Hence, we choose patents granted by PRV as it was the main target for applicants during our time period of interest. Subsequently, we screened the public records of PRV between 1996 and 2005. In this 10-year period we identified a total of 18,906 granted patents. A review of these patents revealed that 14,934 patents were granted to Swedish firms, while 150 patents were granted to research institutions. In addition 3,822 patents were granted to private individuals/inventors. A closer review at these patents further revealed that these patents were distributed among 2,926 private applicants.

The next step included a labor-intensive identification of the 2,926 identified private applicants. In this phase we reviewed all applicants and matched applicant data from PRV with Swedish address registers to make an update of the postal address listed in the patent application. We were in this process unable to track 810 individuals. This step consequently resulted in a final sample of 2,116 individuals who in total had been granted 2,805 patents.

The primary source of information in the study is a structured questionnaire (see below for further information about the data and the variables used in the questionnaire). The questionnaire was sent out in spring 2011 to all identifiable individuals in our sample. We immediately received back 41 returned envelopes. Of these, 25 applicants had moved to an unknown address while the remaining 16 applicants were deceased. In addition, we received phone calls from 76 mistaken identities. This consequently reduced the total number of applicants to 1,999 individuals. After one reminder, we had received a total of 909 completed surveys. This corresponds to a valid response rate of approximately 45.5 percent. Thereafter we removed 53 questionnaires that were containing missing or incomplete information. As a result, we ended up with 856 questionnaires that could be used in our analyses.

Finally, we performed statistical tests to detect potential nonresponse biases. The tests were made on variables such as age, gender, geographical location, serial-inventorship, inventor-applicant duality, and technology (based on IPC subclassification). On the whole, we could not find any major statistically significant biases between respondents and nonrespondents. Thus, on these parameters we may conclude that a representative sample had been collected.

DATA AND VARIABLES

Our primary source of information in the study is a structured questionnaire that has enabled the collection of data about the background and profile of the inventor, the assignee, and the invention, as well as a reconstruction of what has happened with the patent after it was granted. The various items used in the questionnaire were derived from a careful review of previous theoretical and empirical work on academic patents and technological innovation. We then pilot tested the questionnaire on six technical entrepreneurs with experience from patenting research. After filling in the questionnaire, they were all interviewed about their experience of answering the questions. We also contacted some scholars familiar with innovation and entrepreneurship studies to get feedback on the items used to measure our theoretical constructs. Based on the feedback from these sources we made adjustments in the questionnaire before finalizing the research instrument. The questionnaire items used in the study are elaborated later.

The Affiliation of the Inventor(s)

The variable measuring the affiliation of the inventor(s) was based on information provided in the questionnaire. We followed previous studies by considering academic patents as situations when a university should employ at least one of the inventors at the time when the patent application was prepared (e.g., Göktepe-Hultén, 2008; Lissoni, 2012; Meyer, 2006). The information was transformed into a binary variable. In total, we could identify that 16.7 percent of all patents in our sample were having at least one inventor employed by a university.

The Source of the Patented Invention

The variable measuring the source of the invention was based on information provided in the questionnaire. The information was then transformed into a binary variable. In total, we could identify that 10.4 percent of all patents were based on IP originating from university research.

Technological Field of the Patents

The variable measuring the technological field of the patent was based on secondary data available for all patents available in the PRV database. This information follows the IPC classification system (Allan, 2000), which distinguish between technologies in the following fields: (1) Human necessities, (2) Operations, transports, (3) Chemistry, metallurgy, (4) Textiles, paper, (5) Fixed constructions, (6) Mechanical engineering, (7) Physics, and (8) Electricity. This information was then transformed into a categorical variable with eight principal options mirroring the eight different technological fields.

Novelty of Technological Opportunity

The novelty of the technological opportunity underlying the patented invention was measured with four independent Likert-scale items based on information provided in the questionnaire. The first two items were derived from literature and research on innovation and technology entrepreneurship (Gabrielsson, Politis, & Lindholm Dahlstrand, 2013; Smith, 2005) where respondents were asked to rate the extent (1 = very low extent, 7 = very high extent) they evaluated the patent as (i) contributing to an entirely new product and (ii) contributing to an entirely new production process. The second two items was derived from the theoretical work of Abernathy and Clark (1985), where respondents were asked to rate the extent (1 = very low extent, 7 = very high extent) they evaluated the patent as contributing to (i) a product or production process that is radically different and creates a technological breakthrough compared to already existing product or production processes and (ii) a customer need that is substantially different and creates a completely new market compared to already existing product or production processes. The four items have a Cronbach’s alpha of 0.71, and an item-to-total correlation of between r = 0.67 and r = 0.78.

Level of Technological Opportunity

The level of technological opportunity in the primary industry where the patent belongs was measured with four independent Likert-scale items and based on information provided in the questionnaire. These items was derived from the work of Zahra (1996), where respondents were asked to rate the extent (1 = very low extent, 7 = very high extent) to which the primary industry where the patent belong to is performing with respect to (i) opportunities for product/process innovation, (ii) opportunities for technological innovation, (iii) opportunities for major technological breakthroughs, and (iv) overall level of spending on R&D. The four items have a Cronbach’s alpha of 0.85, and an item-to-total correlation of between r = 0.65 and r = 0.91.

Commercialization Routes

The identification of different commercialization routes for the patents in our sample was based on information provided in the questionnaire. The available options were derived from literature and research that have addressed the issue of patents in relation to technology commercialization. The information was then transformed into a categorical variable with nine principal options, including categories such as complete abandonment or putting the patent “on hold” (Schwartz, 2004), selling or licensing the patent (Audretsch, 1995; Serrano, 2008), and exploiting the patent in a new or existing independent firm (Gans & Stern, 2003; Shane & Stuart, 2002).

ANALYSIS AND RESULTS

So far, we have developed a categorization framework that identifies three distinct subsets of academic patents: academic core patents, quasi-academic patents, and hidden academic patents. Based on our unique handcrafted database with detailed information about Swedish patents granted to private individuals between 1996 and 2005 we are also able to analyze the relative share of these distinct subsets of academic patents in relation to each other and compared to nonacademic patents. The share of different categories of patents is shown in Fig. 2.

Fig. 2. Share of Different Categories of Patents.

As can be seen in Fig. 2, 79.8 percent of all patented inventions in our sample were not signed by an inventor with a professional affiliation at a university and nor was it based on IP originating from university research as a primary source of the invention. Accordingly, they could be defined as nonacademic patents and placed in the lower left corner in our conceptual framework. While this subset represent the lion share of all patents in our sample it nevertheless suggest that a significant share – a total of 20.2 percent – of all patents granted to private individuals in Sweden in our study period originate from academic settings. As such, our study provides empirical evidence that speaks against the dominant policy belief that Sweden as an example of a country with a legal IPR systems that prioritize professors’ privileges underperforms in the commercialization of publicly funded research. In this respect, our findings are in line with recent scholarly debates that question the dominant beliefs and instead argues that Swedish academia performs well in terms of commercialization (Jacobsson, Lindholm Dahlstrand, & Elg, 2013).

Following this discussion, the remaining three identified subsets of academic patents based on our framework originate from academic settings either by inventor affiliation or by source of the IP underlying the patented invention. In this respect, they can be considered as representing various forms of technology transfer in an open and dynamic university innovation system (Rothaermel et al., 2007). In the upper right corner we have academic patents that have at least one inventor employed by the university and where university research is a primary source of the IP. These academic “core” patents account for a total of 6.9 percent of all patents in our sample. In the upper left corner we then have academic patents that have at least one inventor employed by the university, but where university research is not a primary source of the IP. Interestingly, this subset of quasi-academic patents account for no less than 9.8 percent of all patents. Finally, in the lower right corner, we have the subset of academic patents that have university research as a primary source of the IP but where the inventors are not formally employed by a university. These “hidden” academic patents account for 3.5 percent of all patents, which is a small but still significant share compared to the other subsets of patents.

The Technological Field of the Patents

Academic patents are often viewed as key indicators of technology transfer activities in technology fields such as biology, pharmacology, electronics, and chemistry, while being less useful in mechanical engineering and for consumer goods. In this respect, we started with a comparison of the identified subsets of patents based on their technological field. To enable search for previous inventions in the field – formally known as prior art – all patents in Sweden are classified according to the international patent classification (IPC), which covers all areas of technology. The IPC is a standardized scheme developed and administered by the World Intellectual Property Organization (WIPO) that facilitates detailed analysis of specific technological aspects (Allan, 2000). As such, there is a large amount of technological information contained in patent applications that can be used for purposes such as technology assessment, competitor monitoring, R&D portfolio management, and the recognition of technological changes (Brockhoff, 1991; Ernst, 2003). The results of the overall comparison are shown in Table 1.

Table 1. Technological Fields Per Patent Category.

We can in Table 1 observe that “hidden” patents are a bit different compared to “core” and “quasi” patents, where the latter are patents with inventors employed at universities and thereby representing the traditional way of defining academic patents. Hidden academic patents are overly represented in physics and chemistry/metallurgy, while they to a much less extent can be found in human necessities. At the same time we can see that “core” patents in contrast to “quasi” patents much more often are found in physics. “Quasi” patents are instead overly represented in human necessities, operations/transports, and mechanical engineering.

The Novelty of the Technological Opportunity Underlying the Patent

We also compared the different categories of academic patents based on an assessment of the novelty of the technological opportunity. When the opportunity underlying the patent is highly novel it implies a major breakthrough or radical change compared to existing industry norms and standards, which in turn can make current organizational routines and practices obsolete (Christensen, 1997). Moreover, more novel opportunities have a higher likelihood to lead to new customer needs that are substantially different and which thereby create completely new markets (Abernathy & Clark, 1985). The results of our comparison are shown in Table 2.

Table 2. Opportunity Novelty Per Patent Category.

Table 2 suggests that academic “core” patents are perceived as slightly more novel by the respondents when it comes to its contribution to a new and entirely different product. “Hidden” patents also show an interesting characteristic in that they are perceived as more novel when it comes to its contribution to entirely new production process. However, the differences are in most cases marginal and on the whole there seem to be no major differences across the different types of academic patents.

The Level of Technological Opportunity in the Industry

The different categories of academic patents were also compared with respect to the level of technological opportunity in the primary industry where the patent belongs to. Industries with high levels of perceived technological opportunities are usually characterized by high growth potential, rapid and frequent introductions of new technology, high levels of knowledge spillovers and R&D spending, and low costs of developing and introducing new innovations (e.g., Angelmar, 1985; Fung, 2004; Geroski, 1990; Jaffe, 1986). A higher level of technological opportunities in an industry also means that there is considerable room for growth through product and process innovations (Zahra, 1996). The level of technological opportunity per patent category is shown in Table 3.

Table 3. Level of Technological Opportunity Per Patent Category.

In Table 3 we can see that “hidden” academic patents score considerably higher than the other academic patents in all four measures. We can also see that “core” academic patents follow not far behind. “Quasi” academic patents are however receiving much lower ratings and are more similar to nonacademic patents. In all the results signal different perceptions of risk and rewards among the individual patent holders across different types of academic patents.

Finally, we compared the different categories of academic patents based on their commercialization routes. Examples of popular commercialization routes for academic patents are selling or licensing the patented technology to third parties (Serrano, 2008; Thursby & Thursby, 2002) as well as the formation of spin-off firms (Shane, 2004; Shane & Stuart, 2002). Patents are however relatively crude proxies for de facto commercialization (Griliches, 1990) and many filed patents are in this respect not renewed and thereby abandoned before they generate any significant income (Svensson, 2012). Patents may also be retained just for the purpose of blocking the inventive efforts of others (Cozzi & Galli, 2014; Granstrand, 1999). Thus, against this background it can be of interest to see whether the different categories of patents differ when it comes to potential commercialization routes. This is illustrated in Table 4.

Table 4. Commercialization Route Per Patent Category.

In Table 4 we can observe that academic patents compared to nonacademic patents have a higher likelihood to be abandoned, with “core” and “quasi” patents showing a total share of abandonment from 50 percent and up. However, there are also marked differences between the different categories of academic patents with respect to other paths of commercialization. Compared to “quasi” patents, “core” and “hidden” patents are more often sold to another party. Interestingly, we can also observe that “core” patents more often are under development in a recently started firm. Another interesting observation is that “hidden” academic patents are much more often commercialized in a newly started firm compared to other types of academic patents, while “quasi” academic patents instead are more often commercialized in an already existing firm. In all, our findings provide empirical evidence that speak in favor of the need to distinguish between different categories of academic patents when it comes to their commercialization routes.

DISCUSSION

Much in line with the rise of the conception and idea of the entrepreneurial university (Clark, 1998), the past decades have seen an increasing rate at which universities have become proactive in their efforts to commercialize research (Kirby, 2006; Rothaermel et al., 2007). As a result, the past there has been an increasing recognition and emphasis on academic patents as a channel for the transfer of knowledge from universities to industry (Geuna & Nesta, 2006). This development has also been accompanied by an increasing number of scholarly studies that examine the frequency, impact, and quality of academic patents (Wright et al., 2007; van Zeebroeck, van Pottelsberghe de la Potterie, & Guellec, 2008). However, academic patents are in contemporary literature and research treated and discussed as a single and largely unified phenomena. Current debates have focused on definitional issues, often related to whether academic patents should be defined according to whether the university is the assignee of the patent, so called university-owned patents, or based on the affiliation of the inventor (Lissoni, 2012; Meyer, 2003). Following the latter approach that has come to dominate research on academic patents, we have in this study argued for an additional dimension that will enable scholars and policy makers to distinguish between different subsets of academic patents. In this theorizing, we have argued for the need to acknowledge both the professional affiliation of the inventor (Göktepe-Hultén, 2008; Lissoni, 2012; Meyer, 2006) as well as the source of the IP underlying the patented invention (Lindholm Dahlstrand, 1999; Shane, 2004). By doing this we can identify four conceptually distinct categories, where three of them represent different subsets of academic patents with underlying differences in technology, opportunity, and commercialization characteristics.

By applying the categorization framework on a unique handcrafted database with detailed information about patents granted to private individuals in Sweden between 1996 and 2005 we furthermore find support for its usefulness in detecting underlying differences in technology, opportunity, and commercialization characteristics among the three subsets of academic patents. The results show that all three subsets of academic patents identified in our theoretical framework represent a significant share of the total amount of patents in the sample. The standard definition based on inventor affiliation (Meyer, 2003) suggests that 16.7 percent of all patents during the time period we have studied are academic patents. On the other hand, a definition based on the source of the IP underlying the patented invention suggests that 10.4 percent of all patents during the studied time period are academic patents. Interestingly, this suggests that a relatively large share of what we usually regard as academic patents is not based on IP originating from university research but comes from other sources. It also suggests that a smaller, but still significant share of patents are hidden from us since they are not detected and represented in databases which define and target academic patents based on the affiliation of the inventor. Thus, a subset not normally regarded as academic patents are in fact based on IP originating from university research.

Limited empirical research has examined and compared different subsets of academic patents in terms of their underlying characteristics and effectiveness for commercialization. Following this observation, we conducted empirical analyses to examine our sample of patents with respect to these issues. Our analyses confirm our expectation that there are some notable differences among the different subsets of academic patents. For example, academic core patents are to a higher extent assessed as contributing to entirely new products and representing a technological breakthrough. The subset of hidden academic patents are on the other hand overly represented in technological fields such as chemistry, metallurgy, and physics and they are also to a higher extent connected to industry sectors with higher levels of technological opportunity. Adding to this, hidden academic patents are much more often leading to new independent business start-ups. In all, our empirical analyses speaks in favor of the argument to separate different academic patents based on our categorization framework.

IMPLICATIONS AND FUTURE RESEARCH

The categorization framework and empirical findings in this study contribute to scholarly knowledge and practical understanding of academic patents as an entrepreneurial form of technology transfer. First, we provide theoretical arguments for the need to conceptualize and differentiate between different kinds of academic patents based on both the affiliation of the inventor (Meyer, 2003) as well as the source of the invention (Lindholm Dahlstrand, 1998). Adding to this, our categorization framework and empirical findings provide an actionable framework for policy makers and TTO managers working in the innovation system surrounding universities. Our categorization framework can in this respect be seen as a “cognitive tool” (Jonassen, 1992) that may facilitate learning and interpretation by enabling a conceptual foundation for both discussing the heterogeneity of patents in academic environments as well as tailoring customized strategies for different kinds of academic patents.

Our study also provides directions for future research efforts in this area. For example, one viable path of inquiry would be to examine more in depth the individuals who are included in the group representing hidden academic patents. One particular interesting aspect is that they are not identified in the typical databases that dominate this field of research and where academic patents are defined based only on the professional affiliation of the inventor(s). However, this group of individuals is also interesting since in our analysis they seem to be attached to patents that in many respects are different compared to the other subsets of academic patents, such as when it comes to spin-off activities. Along this line, we have provided some examples of individuals that may be part of this small but apparently highly potent group, such as graduate students, doctoral students on scholarships, and academics that no longer are formally affiliated with a university.

Adding to this, we can also identify a need to examine more in depth the individuals who are represented and included in the other two subsets. While it is easy to connect and associate our conceptual framework directly with individuals it should be emphasized that it identifies and categorize different patents. This means that one and the same individual can invent patents that belong to different categories. This is especially relevant to consider when thinking about quasi-academic patents and core-academic patents. For example, we know that patenting is a highly skewed activity, and it may be that individuals that patent IP originating from their university research also are involved in other patents based on IP originating outside the university context. However, due to the anonymity promised in our empirical study we are unable to delve further into these issues within the context of our current dataset. In this respect, we therefore call for further studies that can explore these individuals and their patenting behaviors.

Finally, while our categorization framework as an abstraction is applicable across contexts it should be emphasized that our empirical results are highly contextual as they are based on patents granted to private individuals in Sweden between 1996 and 2005. While the Swedish legal IPR system related to academic inventions speaks in favor of this approach we would also like to emphasize that about 80 percent of all patents in Sweden are granted directly to firms (Ljungberg & McKelvey, 2012). Thus, the empirical results should from an international perspective primarily be seen as an exploration of the usefulness of our categorization framework in detecting underlying differences in technology, opportunity, and commercialization characteristics among the three subsets of academic patents. Along this line, we see potential in extending our empirical analysis of academic patents to further explore what distinguishes and characterizes the different subset of academic patents as well as how the categorization framework relates to samples of patents granted to private firms.

REFERENCES

Abernathy, W. J., & Clark, K. B. (1985). Innovation: Mapping the winds of creative destruction. Research Policy, 14(1), 3–22.

Aghion, P., & Howitt, P. (1992). A model of growth through creative destruction. Econometrica, 60(2), 323–352.

Allan, S. (2000). Using the international patent classification in an online environment. World Patent Information, 22, 291–300.

Allen, S. D., Link, A. N., & Rosenbaum, D. T. (2007). Entrepreneurship and human capital: Evidence of patenting activity from the academic sector. Entrepreneurship Theory & Practice, 31(6), 1042–2587.

Angelmar, R. (1985). Market structure and research intensity in high-technological opportunity industries. Journal of Industrial Economics, 34, 69–79.

Audretsch, D. (1995). Innovation and industry evolution. Cambridge, MA: MIT Press.

Balconi, M., Breschi, S., & Lissoni, F. (2004). Networks of inventors and the location of academic research: An exploration of Italian data. Research Policy, 33(1), 127–145.

Beaudry, C., & Kananian, R. (2013). Follow the (industry) money: The impact of science networks and industry-to-university contracts on academic patenting in nanotechnology and biotechnology. Industry and Innovation, 20(3), 241–260.

Bray, M. J., & Lee, J. N. (2000). University revenues from technology transfer – Licensing fees vs. equity positions. Journal of Business Venturing, 15(5), 385–392.

Brockhoff, K. (1991). Competitor technology intelligence in German companies. Industrial Market Management, 20, 91–98.

Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Boston: Harvard Business School Press.

Clark, B.-R. (1998). Creating entrepreneurial universities: Organizational pathways of transformation. Oxford: Elsevier Science.

Cohen, W., Nelson, R. R., & Walsh, J. (2002). Links and impacts: The influence of public research on industrial R&D. Management Science, 48, 1–23.

Cozzi, G., & Galli, S. (2014). Sequential R&D and blocking patents in the dynamics of growth. Journal of Economic Growth, 19, 183–219.

Crespi, G., Geuna, A., & Nesta, L. (2007). The mobility of university inventors in Europe. The Journal of Technology Transfer, 32(3), 195–215.

Czarnitzki, D., Hussinger, K., & Schneider, C. (2011). Commercializing academic research: The quality of faculty patenting. Industrial and Corporate Change, 20(5), 1403–1437.

Della Malva, A., Lissoni, F., & Llerena, P. (2013). Institutional change and academic patenting: French universities and the innovation act of 1999. Journal of Evolutionary Economics, 23(1), 211–239.

Edquist, C., & Hommen, L. (2008). Small country innovation systems: Globalization, change and policy in Asia and Europe. Cheltenham: Edward Elgar.

Ernst, H. (2003). Patent information for strategic technology management. World Patent Information, 25(3), 233–242.

Fagerberg, J., Mowery, D., & Nelson, R. (2004). The Oxford handbook of innovation. Oxford: Oxford University Press.

Feller, I., Ailes, C. P., & Roessner, J. D. (2002). Impacts of research universities on technological innovation in industry: Evidence from engineering research centers. Research Policy, 31(3), 457–474.

Freeman, C., & Louca, F. (2001). As time goes by. from the industrial revolutions to the information revolution. Oxford: Oxford University Press.

Fung, M. K. (2004). Technological opportunity and productivity of R&D activities. Journal of Productivity Analysis, 21(2), 167–181.

Gabrielsson, J., Politis, D., & Lindholm Dahlstrand, Å. (2013). Patents and entrepreneurship: The impact of opportunity, motivation and ability. International Journal of Entrepreneurship and Small Business, 19(2), 142–166.

Gans, J. S., & Stern, S. (2003). The product market and the market for “ideas”: Commercialization strategies for technology entrepreneurs. Research Policy, 32(2), 333–350.

Gartner, W. B. (1985). A conceptual framework for describing the phenomenon of new venture creation. Academy of Management Review, 10, 696–706.

Geroski, P. (1990). Innovation, technological opportunity, and market structure. Oxford Economic Papers, 42, 586–602.

Geuna, A., & Nesta, L. J. J. (2006). University patenting and its effects on academic research: The emerging European evidence. Research Policy, 35, 790–807.

Giuri, P., Munari, F., & Pasquini, M. (2013). What determines university patent commercialization: Empirical evidence on the role of IPR ownership. Industry and Innovation, 20(5), 488–502.

Granstrand, O. (1999). The economics and management of intellectual property: Towards intellectual capital. Cheltenham, UK: Edward Elgar.

Granstrand, O. (2006). Intellectual property rights for governance in and of innovation systems. In and Anderson, B. (Ed.), Intellectual property rights: Innovation, governance and the institutional environment. Cheltenham: Edward Elgar.

Griliches, Z. (1990). Patent statistics as economic indicators: A survey. Journal of Economic Literature, 28, 1661–1707.

Göktepe-Hultén, D. (2008). Academic inventors and research groups: Entrepreneurial cultures at universities. Science and Public Policy, 35(9), 657–667.

Henderson, R., Jaffe, A., & Trajtenberg, M. (1998). Universities as a source of commercial technology: A detailed analysis of university patenting, 1965–1988. Review of Economics and Statistics, 80(1), 119–127.

Jacobsson, S., Lindholm Dahlstrand, Å., & Elg, L. (2013). Is the commercialization of European academic R&D weak? A critical assessment of a dominant belief and associated policy responses. Research Policy, 42(4), 874–885.

Jaffe, A. (2000). The U.S. patent system in transition: Policy innovation and the innovation process. Research Policy, 29, 531–557.

Jaffe, A. B. (1986). Technological opportunity and spillovers of R&D: Evidence from firms’ patents, profits and market value. American Economic Review, 76(5), 984–1001.

Jonassen, D. H. (1992). What are cognitive tools? Cognitive Tools for Learning, 81, 1–6.

Kirby, D. A. (2006). Creating entrepreneurial universities in the UK: Applying entrepreneurship theory to practice. Journal of Technology Transfer, 31(5), 599–603.

Klofsten, M., & Jones-Evans, D. (2000). Comparing academic entrepreneurship in Europe – The case of Sweden and Ireland. Small Business Economics, 14(4), 299–309.

Lindholm Dahlstrand, Å. (1999). Technology-based SMEs in the Göteborg region: Their origin and interaction with universities and large firms. Regional Studies, 33(4), 379–389.

Lindholm Dahlstrand, Å., & Berggren, E. (2010). Linking innovation and entrepreneurship in higher education: A study of Swedish schools of entrepreneurship. In and R. Oakey, A. Groen, G. Cook, & P. Van Der Sijde (Eds.), New technology-based firms in the new millennium (pp. 35–50). Bingley, UK: Emerald Group Publishing Limited.

Lissoni, F. (2012). Academic patenting in Europe: An overview of recent research and new perspectives. World Patent Information, 34, 197–205.

Lissoni, F., Llerena, P., McKelvey, M., & Sanditov, B. (2008). Academic patenting in Europe: New evidence from the KEINS database. Research Evaluation, 17, 87–102.

Lissoni, F., Pezzoni, M., Poti, B., & Romagnosi, S. (2013). University autonomy, IP legislation and academic patenting: Italy, 1996–2007. Industry and Innovation, 20(5), 399–421.

Ljungberg, D., & McKelvey, M. (2012). What characterizes firms’ academic patents? Academic involvement in industrial inventions in Sweden. Industry and Innovation, 19(7), 585–606.

Mansfield, E. (1998). Academic research and industrial innovation: An update of empirical findings. Research Policy, 26, 773–776.

Mansfield, E., & Lee, J. L. (1996). The modern university: Contributor to industrial innovation and recipient of industrial R&D support. Research Policy, 25, 1047–1058.

Meyer, M. (2003). Academic patents as an indicator of useful research? A new approach to measure academic inventiveness. Research Evaluation, 12(1), 7–27.

Meyer, M. (2006). Academic inventiveness and entrepreneurship: On the importance of start-up companies in commercializing academic patents. Journal of Technology Transfer, 31(4), 501–510.

Mowery, D. C., Nelson, R. R., Sampat, B., & Ziedonis, A. A. (2001). The growth of patenting and licensing by U.S. universities: An assessment of the effects of the Bayh–Dole Act of 1980. Research Policy, 30(1), 99–119.

Mowery, D. C., Nelson, R. R., Sampat, B. N., & Ziedonis, A. A. (2004). “Ivory Tower” and industrial innovation: University–industry technology transfer before and after the Bayh–Dole Act. Stanford, CA: Stanford University Press.

Rasmussen, E., Moen, Ø., & Gulbrandsen, M. (2006). Initiatives to promote commercialization of university knowledge. Technovation, 26(4), 518–533.

Rhodes, G., & Slaughter, S. (2004). Academic capitalism in the new economy: Challenges and choices. American Academic, 1(1), 37–59.

Rothaermel, F. T., Agung, S. D., & Jiang, L. (2007). University entrepreneurship: A taxonomy of the literature. Industrial and Corporate Change, 16(4), 691–791.

Sampat, B. N. (2006). Patenting and US academic research in the 20th century: The world before and after Bayh–Dole. Research Policy, 35, 772–789.

Sapsalis, E., & van Pottelsberghe de la Potterie, B. (2007). The institutional sources of knowledge and the value of academic patents. Economics of Innovation and New Technology, 16(2), 139–157.

Sapsalis, E., van Pottelsberghe de la Potterie, B., & Navon, R. (2006). Academic versus industry patenting: An in-depth analysis of what determines patent value. Research Policy, 35(10), 1631–1645.

Schumpeter, J. (1939). Business cycles: A theoretical, historical, and statistical analysis of the capitalist process. (Vol. 2). New York, NY: McGraw-Hill.

Schumpeter, J. A. (1934). The theory of economic development. Cambridge, MA: Harvard University Press.

Schumpeter, J. A. (1942). Capitalism, socialism and democracy. New York, NY: Harper & Row.

Schwartz, E. S. (2004). Patents and R&D as real options. Economic Notes, 33(1), 23–54.

Serrano, C. J. (2008). The dynamics of the transfer and renewal of patents. NBER Working Paper No. 13938, pp. 1–26. National Bureau of Economic Research.

Shane, S. (2004). Academic entrepreneurship: University spinoffs and wealth creation. Cheltenham, UK: Edward Elgar.

Shane, S., & Stuart, T. (2002). Organisational endowments and the performance of university spin-offs. Management Science, 48(1), 122–137.

Smith, D. (2005). Exploring innovation. London: McGraw-Hill Higher Education.

Svensson, R. (2012). Commercialization, renewal, and quality of patents. Economics of Innovation and New Technology, 21(2), 175–201.

Thursby, J. C., & Thursby, M. C. (2002). Who is selling the ivory tower? The sources of growth in university licensing. Management Science, 48, 90–104.

Trajtenberg, M., Henderson, R., & Jaffe, A. B. (1992). University versus corporate patents: A window on the basicness of inventions. CEPR Working Paper No. 372, Stanford University, Stanford.

van Zeebroeck, N., van Pottelsberghe de la Potterie, B., & Guellec, D. (2008). Patents and academic research: A state of the art. Journal of Intellectual Capital, 9(2), 246–263.

Walsh, J. P., & Huang, H. (2014). Local context, academic entrepreneurship and open science: Publication secrecy and commercial activity among Japanese and US scientists. Research Policy, 43(2), 245–260.

Wigren-Kristoferson, C., Gabrielsson, J., & Kitagawa, F. (2011). Mind the gap and bridge the gap: Research excellence and diffusion of academic knowledge in Sweden. Science and Public Policy, 38(6), 481–492.

Wright, M., Clarysse, B., Mustar, P., & Lockett, A. (2007). Academic entrepreneurship in Europe. Cheltenham, UK: Edgar Elgar.

Youtie, J., & Shapira, P. (2008). Building an innovation hub: A case study of the transformation of university roles in regional technological and economic development. Research Policy, 37(8), 1188–1204.

Zahra, S. A. (1996). Governance, ownership and corporate entrepreneurship: The moderating impact of industry technological opportunities. Academy of Management Journal, 39(6), 1713–1735.

Zucker, L. G., & Darby, M. R. (2001). Capturing technological opportunity via Japan’s star scientists: Evidence from Japanese firms’ biotech patents and products. Journal of Technology Transfer, 26(1–2), 37–58.