Do Patents Affect Prices?
École polytechnique fédérale de Lausanne, Switzerland
The patent system involves a tradeoff between encouraging innovation and incurring inefficiency due to the monopoly power patent protection confers. The debate is not yet settled, and more research is needed on the costs and benefits of the patent system. One stream studies the private benefits associated with patent protection.
Existing literature on the value of patent protection seek to measure the so-called “patent premium”, defined as the proportional increment in value of patented invention over the un-patented counterparts. Previous scholars have shown a roughly 50% private return to patenting, measured either on firm level or using subjective survey on inventions (Arora et al. 2008; Jensen et al. 2011).
Much studies on the implications of patent protection focused on pharmaceutical products where patent exclusivity guarantees branded drugs substantial monopoly rents. Earlier contributions argue that branded producers distinguish themselves from generic entrants by patent-induced brand loyalty (Caves et al. 1991; Grabowski and Vernon 1992), evidence suggesting a slight decline in the price of branded drug after patent expiry as opposed to a much lower price for generic drugs. Hudson (2000) finds that highly profitable products enjoy exclusive benefits of patents for an extended period after expiry regardless of attracting more competition.
Previous scholarly efforts nevertheless suffer from the limitations of data, i.e., the proxies for outcomes of patent premium are measured indirectly without reflecting the value of inventions. Besides, the unavailability of product data either overlooks the benefits of patent protection beyond patent lifespan or restricts the discussion to drug market.
In this paper, we aim to address the following research questions on top of an intuitive inquiry into whether patents affect prices: to what extend do product prices respond to patent expiry and how does the sensitivity of prices vary by the importance of patent as well as product categories.
We exploit the exogeneous switch of patent status from being active to expiry by browsing USPTO patent maintenance fees data, of which the expected expiry in our sample occurred predominantly during 2011–2018. We adopt fixed-effects specification to estimate the effects of patent expiry on the market price of products.
A sample of 740 products belonging to 44 companies is drawn from a novel database that identifies correspondences between innovative products and the patents upon which they are built through virtual patent marking (VPM) web pages. Since most products fall into the categories of computers, consumer electronics, and consumer goods, we make use of Amazon price history data as well as manually collected product-level information to construct a weekly panel dataset spanning from 2011 to 2018.
Our findings demonstrate that patent expiry leads to about 9% decline in product prices after controlling for product age and availability of successive generations. Whereas expiry of utility patents negatively affects product prices, this negative impact turns statistically insignificant for designs.
Contribution to Scholarship
Our paper departs from existing research on the private returns to patenting by focusing on a broad range of products that have never been studied. In doing so, we contribute to the debate on the effectiveness of patent protection in deferring competition by probing the price dynamics of incumbent innovative producers.
Contribution to Practice
Our research also has far-reaching implications for policy-makers regarding the effectiveness of patent protection. We also contribute to understanding the persistence of benefits of patent protection for innovative firms in off-patent periods.
Our paper relates to the theme of this year’s R&D Management Conference by shedding light on efficient innovation policy implemented to stimulate innovative activities. Our estimates provide new insights on the private value of patents and, therefore, on the effectiveness of patent system.
Arora, A., Ceccagnoli, M., & Cohen, W. M. (2008). R&D and the patent premium. International journal of industrial organization, 26(5), 1153-1179.
Caves, R. E., Whinston, M. D., Hurwitz, M. A., Pakes, A., & Temin, P. (1991). Patent expiration, entry, and competition in the US pharmaceutical industry. Brookings papers on economic activity. Microeconomics, 1991, 1-66.
Grabowski, H. G., & Vernon, J. M. (1992). Brand loyalty, entry, and price competition in pharmaceuticals after the 1984 Drug Act. The journal of law and economics, 35(2), 331-350.
Hudson, J. (2000). Generic take-up in the pharmaceutical market following patent expiry: a multi-country study. International Review of Law and Economics, 20(2), 205-221.
Jensen, P. H., Thomson, R., & Yong, J. (2011). Estimating the patent premium: Evidence from the Australian Inventor Survey. Strategic Management Journal, 32(10), 1128-1138.
Do cohorts matter for technology transfer? The role of IP coordinators' cohorts at technology transfer offices
1NORD University Business School, Norway; 2NIHR Newcastle, Newcastle University, UK
University technology transfer is a big and controversial business, administered by a growing occupational group, Intellectual property (IP) coordinators.
This paper explores the cohort effect, answering the question whether IP coordinators in same cohort exhibit similar patterns in patenting and licensing, thus contributing to the university technology transfer literature.
Van Maanen, J. E., and Schein, E. H. (1979). Toward a theory of organizational socialization. Research in Organizational Behavior, 1, 209-264.
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Lemley, M A. and Sampat, B. (2012). Examiner Characteristics and Patent Office Outcomes. The Review of Economics and Statistics, 94(3), 817–827.
Frakes, M. D. and Wasserman, M. F. (2016). Patent Office Cohorts, Duke Law Journal, 65, 1601-1655.
Technology transfer literature using the concept of cohorts has focused on researchers (e.g. Rappa and Debackere, 1995) and not on technology transfer staff. Cohort effect has also been recorded for a similar group of experts, patent examiners (Frakes and Wasserman, 2016). Similar works encompassing technology transfer offices remain absent.
The main research question of this paper is if cohorts matter in terms of the efficiency of technology transfer offices.
We focus on following hypotheses:
H1: Coordinators in the same cohort exhibit similar patenting patterns.
H2: Coordinators in the same cohort have similar level of success and experience in licensing.
Descriptive and discriminant analysis was done for patent and licensing data.
Correlation matrix gave us an initial insight. We used several dependent variable groups: 1) cognitive proximity, 2) success factors, 3) working practices and 4) organizational features.
Discriminant function analysis (DFA) helped us classify cases and the probability of their classification into groups (defined as cohort). Along with understanding the homogeneity of cases processed by coordinators within a certain group, we also tested whether the method recognizes different licensing and patenting patterns between the cohorts. Based on theory driven approach, we obtained a high percent of correctly classified cases.
For the analysis we build a database using the university’s patent applications data from year 1984 to 2014 merged with licensing (and re-assignment) agreements data. Data processing and merging of the databases was done using STATA 15, data analysis was further enriched using SPSS 23. The final dataset for the analysis was time series data.
In order to gain an accurate picture of the cases assigned to individual IP Coordinators, we needed to acquire two more types of human resource related data. Firstly, their employment data provided information on the term of their engagement in patenting and licensing activities. Secondly, we added data on assignment and reassignment of cases. Sole reliance on administrative data connected to patents and licensing, would give us only a static picture. Static picture could be inaccurate, as cases regularly get assigned and reassigned.
Our database included 18393 cases of IP Coordinators handling patent cases, some of them licensed and some not. A sub-sample is that of only licensed cases (845 cases). We conceptualize cohorts according to the time when coordinator started his work. For this paper we defined 3 groups, carefully selecting the cut-off points.
The exploration into how experience and social interactions influence individuals’ behaviours is new in the context of technology transfer offices (TTO).
Our analysis demonstrates that the year in which an IP coordinator is hired, has an effect on their patenting and licensing proclivities. Variations between cohorts suggest that IP coordinators may follow distinct and enduring practices throughout their career, as influenced by the prevailing practices inside the TT at the time of hiring.
Yet at the first glance, the biggest distinctions between IP coordinator cases inside different cohorts do not seem to be connected with their immediate licensing and patenting output, but rather with the underlying mechanisms and practices, such as their cognitive proximity attitudes.
Our analysis holds a number of important implications for public policy in the field of technology transfer and the organizational competitive advantage of individual universities, as IP coordinators can be catalysts for commercialization success. Knowledge reservoirs (Argote and Ingram, 2000), that include people, tools and tasks (or practices) have the ability to effect knowledge transfer and with it also organisational competitive advantage of organisations. Furthermore, our results are relevant to the ongoing debates about the disperse rates of technology transfer across different technology transfer offices.
Contribution to Scholarship
Cohorts and their potential effects are under-conceptualized and under-researched in terms of different groups inside the technology transfer processes. We present a model allowing for assessment of cohorts’ effects in technology transfer offices, and test the model on individual level data.
Indeed, it is not even clear if this effects exist or not, although knowledge reservoirs that include people, tools and tasks (or practices) have the ability to effect knowledge transfer (Argote and Ingram, 2000), and with it also organizational competitive advantage of organizations, in our case universities. To be able to discern if such effects exist, we carefully construct several groups of independent variables: cognitive proximity, success factor and organizational features.
Contribution to Practice
We advance knowledge on the underlying activities of the technology transfer staff (i.e. IP coordinators), i.e. “a profession in the making” (Owen-Smith, 2011). We do so, by not only using hard-to-acquire individual level data, but also by combining the patenting and licensing data with HR data and case re-allocation data. The later are especially important as it allows us to upgrade the static pictures of licensing and patenting activities of IP Coordinators and utilize data reflecting the dynamic nature of technology transfer processes.
Among numerous organization level recommendations, e.g. systematically supporting inter-cohort knowledge exchange, we also offer policy recommendations.
The conference’s theme is “bridging research, industry and society”. We focus on a key, but mostly overlooked, bridging groups in the university technology transfer (TT): technology transfer offices’ staff. Studied mostly as an homogeneous group, we however focus on their subgroups and explore how cohorts affect outcomes of TT processes.
Argote, L. and Ingram, P. (2000). Knowledge transfer: A basis for competitive advantage in firms. Organizational behavior and human decision processes, 82(1), 150-169.
Frakes, M. D. and Wasserman, M. F. (2016). Patent Office Cohorts, Duke Law Journal, 65, 1601-1655.
Owen-Smith J. (2011). The institutionalization of expertise in university licensing. Theory and Society, 40, 63–94.
Rappa, M. A. and Debackere, K. (1995). An analysis of entry and persistence among scientists in an emerging field of science: the case of neural networks. R&D Management 25, (3), 323-341.
Understanding The Architectural Control of Complex Systems under Collaborative Standardization : An Analysis of The Flow and Network of Technologies in The Mobile Telecommunication Sector
1Yokohama National University, Japan; 2National Cheng Kung University, Taiwan; 3The University of Tokyo
Opening technologies through standardization is considered as one of the critical strategies to encourage a variety of firms to develop complementary goods and technologies (Gawer and Cusumano, 2002; West, 2003). However, when technologies are standardized through interfirm collaboration, even leading incumbents will lose control over their own technologies and advantages.
Even though opening their technologies to public, leading firms, such as platform leaders, can maintain technologies within their control by their proprietary standards (Arikan and Schilling, 2011; Baldwin and Woodard, 2009). Such capabilities is called architectural control. Architectural control is a sort of ability to control the rate at which the technology is upgraded, refined, or its compatibility with previous generations and thereby exert influence on influence technological trajectories and other firms (Arikan and Schilling, 2011; Morris and Ferguson, 1993).
Meanwhile, as systems become complex and thus developed across firms, firms attempt to standardize fundamental technologies in the form of non-exclusive standards through collaborative activities (i.e., standard bodies/consortiums) (Leiponen, 2008; Simcoe, 2012). Different from the case of proprietary standards by specific leading firms (David and Greenstein, 1990), such unsponsored standards on complex systems do not allow even leading firms to preserve architectural control over their technologies.
When standards are set up by standardization consortium of multiple firms, any firms can hardly control the standards and related-technologies at their disposal. Nevertheless, it is still unknown how leading firms can construct and secure their architectural control over the technologies of complex systems under such collaborative standardization.
Prior researches pays little attention to architectural control over complex systems under the technology-sharing regime of collaborative standardization. Thus, this study aims to complement the research gap by revealing how firms can secure their architectural control over the relevant technologies of complex systems under collaborative standardization.
Drawing on the studies of firms’ knowledge and effective innovations (Yayavaram and Ahuja, 2008), this study quantitatively examined the flows and networks of technologies within and across firms with the UCINET tools. First, we considered the longitudinal data of the number of citations (degree centrality), as a measure of architecture control, of each selected firm’s SEPs (standard essential patents) by other firms’ proprietary patents. Second, we conducted a network analysis to examine each firm’s knowledge by the densities of networks by technology specifications and SEPs. Finally, we examined the relationship between the degree centrality and the knowledge density across firms.
Based on the previous studies on the mobile telecommunication sector (e.g., Bekkers, et al., 2002; Davies, 1999), we can examine the architectural control in the sector by using reliable data from standardization organizations (3GPP and ETSI) and the US and European patent offices. How to increase the degrees of architectural control over a complex system such as telecommunication system has been discussed in the MIT communications future program as well.
After the classification by patent families units and data cleansing, we obtained the data of 25,292 declared SEPs linked with technology specifications from 1990 to 2016 from ETSI in Oct., 2017. Further, we extracted the data of 25 major firms which accounts for about 90 percent of the total SEP activities. At the same time, we classified and examined SEPs by the five large classes of technology specifications downloaded from 3GPP.
For proprietary patents, we downloaded the all proprietary patents, about 910,000 published patents, of 25 firms from the Espacenet patent database without limitation on time period in May, 2017. Then, by integrating the database of proprietary patents with that of SEPs, we generated the data of more than 100,000 patent forward citations by proprietary patents from SEPs.
The results showed that the number of citations by other firms increases with the densities of knowledge (p.<0.01). Typically, leading incumbents and technology providers have been cited by other firms with high frequency. Typically, Qualcomm’s SEPs have been cited by other firms more than 20,000 times. Accordingly, such firms have accumulated high densities of knowledge. Meanwhile, new entrants (e.g., Samsung, LG) and the Japanese firms which show low densities of knowledge have been far less cited by other firms (each firm have been cited less than 3,000).
Thus, we can argue that firms possess higher densities of knowledge can have higher degrees of architecture control even under the technology-sharing regime of collaborative standardization. Though it may require more rigorous statistical examinations including other variables, the result indicates that those firms which attract many citations from other firms are presumed to build effective knowledge on technology systems at a high density, and thereby generate effective innovations that drives the technologies and industry concerned.
Contribution to Scholarship
Although theories and methods need to be refined in a more rigorous way in the future, this study contributes to scholarships in the following senses. This study provides comprehensive implications of leading firms’ architectural control under collaborative standardization which encourages technology spillover and sharing between firms (European Commission, 2014). The approach and perspective proposed in this study will contribute to revealing architectural control under collaborative standardization in terms of systemic knowledge (Fleming and Sorenson, 2001) and capabilities to generate effective innovations (Yayavaram and Ahuja, 2008). In addition, this study proposes methods to understand firms’ knowledge across multiple technologies and its relationship with architectural control.
Contribution to Practice
This study’s perspective and method on the dynamism of firms’ knowledge and innovations will expand practical debates on the strategy of opening technologies particularly for complex systems developed by multiple firms (e.g., IoT). Our results will help practitioners understand the critical factors to control technologies opened through collaborative standardization.
This study tackles the problem of firms’ innovation strategies related to the industrial and societal adoption and diffusion of systemic technologies thorough collective standardization. The attempt contributes to the conference theme, “The Innovation Challenge, “ particularly "Theme 6: Radical and Systemic Innovation.”
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Integrating Patent Management and R&D – An explorative analysis of the new product development process
University of Cambridge, United Kingdom
Patent-related activities, such as securing freedom to operate (FTO), positively influence a new product’s success . However, low patent awareness among R&D personnel and limited patenting resources lead to lacking guidance and missed opportunities . Firms therefore seek to integrate patent management efficiently along the development process of new products.
The main body of literature reviewed in this study is the existing work on cross-functional integration of IP management and R&D , particularly the development of new products (NPD) [8,10], which reveals a significant positive influence of patent management integration on NPD success [5,13]. This is put in broader context by the literature on general cross-functional integration of departments within firms and the different dimensions of the interdepartmental integration .
Additionally, multiple relevant academic literature streams are combined, such as definitions of what patent management precisely consists of and thus how it is differentiated from other development processes [6,7], as well as the theory of organisational resource dependence .
NPD has been shown to profit from patent management , but not how and when both fields should be integrated. Integration into early stages was found to be beneficial [8,14], but the existing studies lack precision about efficient timing and the exact NPD activities that patent management can support.
How is patent management integrated along the stages in the new product development process?
How can patent management efficiently support NPD activities?
Qualitative research is used to discover new phenomena . To understand how patent management is integrated into NPD, this study uses explorative semi-structured interviews and interactive workshops with both NPD and patent management employees from selected manufacturing firms from R&D-intensive sectors. Following the logic of polar sampling , one firm was deliberately chosen for its low R&D-intensity to provide a contrasting case to R&D-intensive firms for a clear pattern recognition of central constructs.
25 interviews and 2 workshops were conducted via Skype, telephone or in person. Interviewees were guided through the R&D-based stages of the stage-gate innovation process by Cooper , namely idea generation, scoping, business case and development. The interviewers indicated where patent management activities take place in their firms and why. When needed, the model was adapted to the NPD process model in place at the respective firm.
The investigated firms are from manufacturing industries which are traditionally R&D-intensive, which, in turn, is shown to be correlated with substantial patenting activities . In particular, the sampling covered a range of different industries including the automotive, automation, chemical, electrical and wind energy industries, elevator and heating and cooling technologies, as well as manufacturing plants. Data was collected both from NPD and patent management representatives.
In two cases, it was possible to conduct workshops to gather data interactively from several firm representatives. One workshop was conducted virtually by means of the online workshop software ‘Stormboard’. The other was conducted at the firm’s headquarter. All firms operate internationally whilst all except one have their headquarters in Germany. The exception is the one case chosen for polar sampling purposes and is headquartered in Spain.
The data shows that patent management continuously accompanies NPD. Patent management support appears to be necessary in NPD from early stages onwards and is especially important at the scoping stage, where ideas are mature, whilst no heavy development investments have occurred yet. In the later stages, the integration decreases.
By analysing how patent management activities can support NPD activities, and how important this support is for NPD compared to other patent management activities, patent management and NPD “activity pairs” along the NPD stages were revealed. At the scoping stage, the NPD activity "feasibility testing" is supported by means of an extensive FTO, "market assessment" by a patent database analysis, and "technical assessment" by investing competitors’ patents for inspiration. The activity pairs taking place at the other stages are the following:
● Looking for available technologies internally and externally - Searching patents inside
and outside the firms
● Sketch scenarios of future product: Checking IPRs of third parties - developing
strategies around others’ IPRs
● Idea formulation - Patent research as driver for new ideas
● Detailed product definition - Final FTO
● Specification of product and production parts - Final FTO of details, product
improvements evaluated for possible new patents
Contribution to Scholarship
This study contributes to the previous literature showing the positive impact of patent management integration into R&D processes [13,5], and that the different phases of NPD processes incorporate different IP-related activities [8,10,14]. By revealing activity pairs of NPD and patent management that indicate the direct connection and support of patent management for NPD, this study provides an in-depth qualitative analysis where, unlike precedent studies, a detailed investigation into different NPD stages to identify the timing and relevance of patenting activities was undertaken. This way, the scoping stage was identified as being particularly heavy on integration between the NPD and patent management.
The sampling includes various firms across different manufacturing industries and therefore focusses on firms that conduct substantial patenting activities. Thus, implications are derived from relatively mature patent management concepts and contribute towards enlarging the literature on R&D and IP management integration.
Contribution to Practice
The stage-gate innovation process is often applied in practice, and the NPD activities that this study shows to be supported by patent management take place across many different NPD processes. The integration of patent management activities with NPD activities that the interviewees reported for every stage can be used by those in charge (e.g. the head of innovation or technology manager) as a guideline to structure patent management processes along NPD.
The findings are particularly useful for firms that have limited resources devoted to patent management and hence a strong need for efficient patent management integration in NPD.
Patents are a means to protect and incentivise the creation of innovations in corporate R&D. Yet, IP in general, and patents in particular, receive low awareness within R&D. An efficient integration of managing patents can, however, help to transform as much innovative research as possible into successful commercialised products.
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