Patent Counts Research Articles

STATE OWNERSHIP AND INNOVATION: THE RELATIVE MERITS OF LOCAL AND CENTRAL STATE JUDGED BY INNOVATION PERFORMANCE

This paper compares the innovation performance of state-owned firms owned by different levels of government, with that of privately owned firms. Analysis of a 116-firm panel dataset for the Chinese solar photovoltaic industry from 1999 to 2015 suggests that government’s financial support increases the quantity of innovation outputs. However, the efficiency in utilising the financial resources is determined by the effectiveness of agency relationships. Applying agency theory to the Chinese politico-economic context indicates that innovation quality depends on length and complexity of agency chains, engagement of monitors, and the tenure of managers. By using forward citations and proportion of patents in active use, two measures of innovation quality that are more valid and reliable than patent counts, our study finds that municipally owned firms are superior in terms of innovation productivity to those under central ownership, and comparable to private firms.

Decomposition analysis of patenting in renewable energy technologies: From an extended LMDI approach perspective based on three Five-Year Plan periods in China

Renewable energy technological innovation is greatly influenced by renewable energy markets and policies. In this regard, the paper decomposes nine influencing factors of patents of a specific renewable energy technology using the extended logarithmic mean Divisia index (LMDI) method from 2001 to 2015. The differences in a specific renewable energy technological innovation and development during the three Five-Year Plan periods is prioritized at the national level. The contribution of the increase in patents of renewable energy technologies mainly lies in the patents of solar energy technology and wind energy technology, but during the 12th Five-year Plan period, the increments of their patent counts significantly decline. Due to priority given to the development of innovation in a specific renewable energy technology, the improvement in the efficiency of R&D spending, the increases in the share of R&D spending and the share of renewable energy, low carbon economy concept advocacy and carbon scale expansion, the patent counts of a specific renewable energy technology will increase. Additionally, the factors affecting innovation in a specific renewable energy technology at the different economic development levels, as well as different resource distribution levels are investigated.

Triple helix in practice in Indian HEIs using lens of academic patenting

ABSTRACT This paper studies the practice of triple helix phenomena in India using lens of academic patenting. In first part of the paper, using citation counts of patents assigned to Indian HEIs and BSE Sensex constituents by USPTO, we bring out the necessity of continuous collaboration between HEIs, industry and government for creating valuable intellectual property. In second part, we measured the association of external structural changes (awareness of support from Triple helix constituents) and internal individual level changes on readiness to patent among faculty members in HEIs. Results indicated that structural changes and individual level changes influence readiness to patent. Awareness of support from HEIs and government, being open to adapt to change and wanting to have opportunity to help others through research had a significant positive relationship on faculty wanting to disclose their inventions.

Public‐to‐Private Buyouts and Innovation

AbstractWe study the effect of public‐to‐private buyout transactions on investments in innovation using an international sample over the 1997–2017 period. We use patent counts and citations to proxy for the quantity, quality and economic importance of innovation. Our results are based on time analysis and matched sample regressions. The data indicate that buyouts are associated with a significant reduction in patents and patent citations, including a reduction in radical (i.e. more scientific) patents. When we split the sample into institutional and management buyouts, the negative effect of buyouts is confirmed only for institutional buyouts. This suggests that only institutional buyouts prevent target firms from adopting long‐term investments. This finding is confirmed by reductions in innovator employment and innovation efficiency subsequent to going private. Moreover, the data indicate that the negative effect is most prevalent for transactions where the cost of the deal's debt financing is higher than that of the debt post‐buyout. We rule out some alternative explanations for these findings, including but not limited to outliers, truncation bias and endogeneity.

Mapping Patent Usage in Management Research: The State of Prior Art

Patents play an important, and increasingly influential, role in management scholarship. In this study, we conduct a broad and systematic review of patent-based empirical work in the management field, which involves mapping the ways in which scholars are using patent-based measures to represent concepts and assessing this usage based on measurement principles. With respect to mapping, our review identifies the different types of measures that researchers have constructed based on different types of patent data (e.g., patent counts, backward citations) as well as delineates the classes of theoretical concepts that are being represented by those measures. In terms of assessing, as a complement to prior surveys of patent-based research that have assessed patents as indicators based on features of patents, patenting, and patent offices, we develop a framework that is based on measurement principles. Using this framework, our assessment of patent-based research in management reveals important patterns surrounding foundational measurement issues, i.e., method bias, validation threats, model misspecification. Our review makes two core contributions: one centering on summarizing how patents have been used in management research and one focusing on guiding management scholars in terms of common measurement issues for patent-based indicators. These contributions have important implications for future scholarly work in management.

Search for the Developing Trends by Patent Analysis: A Case Study of Lithium-Ion Battery Electrolytes

Lithium-ion batteries (LIBs) are now used in electric vehicles (EVs), and the electrolyte is one of the major components governing the performance of LIBs. The patent count-based method or patent indicator was used to understand the development status of the specific technology field. However, these approaches cannot provide a complete picture to realize the technology development. Therefore, the goal of this work is to develop a holistic approach to identify technological development trends. The top six patent assignees are first selected by an issued patent counts analysis, including Ube, Mitsubishi Chem., Panasonic, Sony, LG Chem., and Samsung SDI. The “modified” Ernst indicators are applied to reflect different innovation strategies among these patent assignees. The forward-citation analysis and technology-function matrix show that using mixed lithium salts and organic solvents with novel additives compounds are the developing trends to improve the performance of LIBs. The multi-dimensional scaling shows technological similarities among these six companies. The developed approaches can be used to obtain a better overview for electrolyte technology and be also applicable to other technological fields.

What do U.S. biopharmaceutical companies get from patents and research and development spikes for their dynamic corporate performance?

This paper investigates how patents and research and development (R&D) spikes affect the corporate performance of 863 firm‐year observations of U.S. biopharmaceutical companies. First, a dynamic data envelopment analysis model is adopted to evaluate the performance of the U.S. biopharmaceutical companies. Then, ordinary least squares regression is used to explore the effects of three patent‐related variables (patent counts, citations, and claims) and R&D spikes on corporate performance. This study finds positive impacts of patent counts, citations, and claims on corporate performance. In addition, the results show that R&D spikes have negative contemporaneous effects and time‐lagged effects on corporate performance.

Practical Machine Learning Approach to Capture the Scholar Data Driven Alpha in AI Industry

AI technologies are helping more and more companies leverage their resources to expand business, reach higher financial performance and become more valuable for investors. However, it is difficult to capture and predict the impacts of AI technologies on companies’ stock prices through traditional financial factors. Moreover, common information sources such as company’s earnings calls and news are not enough to quantify and predict the actual AI premium for a certain company. In this paper, we utilize scholar data as alternative data for trading strategy development and propose a practical machine learning approach to quantify the AI premium of a company and capture the scholar data driven alpha in the AI industry. First, we collect the scholar data from the Microsoft Academic Graph database, and conduct feature engineering based on AI publication and patent data, such as conference/journal publication counts, patent counts, fields of studies and paper citations. Second, we apply machine learning algorithms to weight and re-balance stocks using the scholar data and traditional financial factors every month, and construct portfolios using the “buy-and-hold-long only” strategy. Finally, we evaluate our factor and portfolio in terms of factor performance and portfolio’s cumulative return. The proposed scholar data driven approach achieves a cumulative return of 1029.1% during our backtesting period, which significantly outperforms the Nasdaq 100 index’s 529.5% and S&P 500’s 222.6%. The traditional financial factors approach only leads to 776.7%, which indicates that our scholar data driven approach is better at capturing investment alpha in AI industry than traditional financial factors.

From 'Rates of Innovation' to Measures for 'Innovation Quality and Culture'

This study provides formal theoretical evidence that the concept of 'rates of innovation' is not amenable to imposition of any preference structure, as such is misleading and non-robust. Dearth of robustness derives from the finding that a decreasing rate of innovation can be shown to be strictly preferred to either of an increasing or constant rate of innovation. This finding rules out either of patent counts, citation-weighted patent counts, or the term, 'innovation rates' as robust parameters for comparative studies of cross-sections of innovation activity. The formal theoretical model endogenously generates two parameters for comparative studies of cross-sections of innovation activity that, respectively are constructs for 'quality of innovation', and 'frequency', equivalently, 'culture of innovation'. Given the parameter for culture of innovation is derived, in entirety, from the quality of innovation parameter, it is obtained in context of a strict preference for higher quality innovations that is formally and theoretically established. A strict preference for higher quality innovations is shown, under regular conditions, to imply an intertemporal 'decreasing cascade' for each of quality of innovation, and frequency of innovation, a cascade that, simultaneously is susceptible to stochastic arrival of innovation events that induce upward 'jumps' to the intertemporal decreasing cascade process. Preliminary empirical tests show the quality of innovation parameter outperforms GDP Per Capita as measure of quality of innovation within cross-sections of countries. Given the terminology, 'studies of rates of innovation' embeds a misnomer, study findings recommend substitution of the terminology, 'studies of Innovation Quality and Culture (IQC)'.

Innovation Institution and Spatial Transfer of Energy Industry: The Case of Jiangsu Province, China

This study aims to explore the effect of innovation institution on spatial transfer of energy industry in Jiangsu, China. We focus on the disparity of innovation and energy industry, and analyze the spatial transfer difference in different types of energy industry, rather than view energy industry as a whole. The study demonstrates the spatial change of energy industry at regional level and maps the spatial pattern at city level. The study chooses intellectual property rights (IPRs) protection intensity, authorization patents and local research and development (R&D) investment as the proxy of innovation. Using official data and employing panel fixed-effect model at city-industry level, we conclude (a) innovation abilities significantly influence the spatial transfer of energy industry in Jiangsu. Especially, due to the different time, IPRs protection, patent counts, and R&D investment have different effects on different regions in Jiangsu; (b) 2010 is an important turning point for energy industry development in Jiangsu, and after 2010, the energy industry begins to shift to the middle and northern Jiangsu, whereas the spatial pattern of energy industry in coastal cities is basically unchanged; (c) there is a great difference between the regions in Jiangsu Province, and industrial upgrading has not been achieved in northern Jiangsu.

Mining technology hot spots in the 3D printing industry for technology strategic planning based on MRCAI

3D printing is the important part of the emerging industry, and the accurate prediction of technology hot spots (THS) in the 3D printing industry is crucial for the strategic technology planning. The patents of the THS are always in the minority and have outlier characteristics, so the existing single and rigid models cannot accurately and robustly predict the THS. In order to make up for the shortcomings of the existing research, this study proposes a model for robust composite attraction indicator (MRCAI), which avoids the impact of outlier patents on prediction accuracy depending on not only extracting the patent attraction indicators (AIs) but also constructing the robust composite attraction indicator (CAI) according to the rough consensus of predicted results of CAIs with high generalization. Specifically, firstly, this study selects the patent AIs from the four dimensions of the attraction: technology group attraction, state attraction, enterprise attraction and inventor attraction. Secondly, in order to completely describe the attraction features of patent, AIs are directly and indirectly integrated into CAIs. Thirdly, we reduce the influence of outlier patents on prediction accuracy from two aspects: on the one hand, we initially select the CAIs with good generalization performance based on the prediction error fluctuation range. On the other hand, we build the robust CAIs by calculating the consensus of CAIs with high generalization performance based on the rough set. Fourthly, the 3D printing industry technology attention matrix is constructed to map the effective technology strategic planning based on predicted patent backward citation count by MRCAI in the short, medium and long term. Finally, the experimental results on 3D printing patent data show that MRCAI can effectively improve the efficiency in dealing with samples with outlier patents and has strong flexibility and robustness in predicting the THS in 3D printing industry.

Power-law distributions of corporate innovative output: evidence from U.S. patent data

This study aims to examine the existence and the characteristics of power laws in the distribution of corporate innovative output. Using a dataset containing information on 1,102,839 U.S. patent applications by 94,103 U.S. private firms during the period of 1976–2000, we find that corporate innovative output, as measured by either simple or quality-adjusted patent counts, follows power-law distributions that theoretically have infinite variances and, in some cases, infinite means. In addition, we find that corporate innovative output is power-law distributed in all technological fields. We further find that the power-law distribution of corporate innovative output tends to be stronger (i.e., the concentration of corporate innovative output in a few firms is more pronounced) in technological fields with more abundant technological opportunities and for firms with higher technological competence.

Fostering innovation in renewable energy technologies: Choice of policy instruments and effectiveness

This paper assesses the effectiveness of different types of renewable energy policies (REP) in fostering innovation activity in the OECD electricity sector over the period 1990–2014. More specifically, we collect and analyse data on policy intervention, innovation activity (patent counts per type of renewable technology) and performance for 21 OECD countries from 1990 to 2014. Using the specific characteristics of each policy, we identify all REP in our sample and categorise them to one of three distinct policy types: technology-push, demand-pull, and systemic policy instruments. We then analyse the effects of policy intervention on innovation, by type of policy instrument and by type of technology. Our results show very clearly that one size does not fit all. Innovation activity is found to be more responsive to demand-pull policy instruments only for some technologies (e.g. geothermal), whereas for others a more mixed approach maybe more effective (e.g. wind). And sometimes policies that are designed to target only one technology are more effective in fostering innovation than multi-technology ones (as in the case of solar). Overall, we find that demand-pull policies have been more effective than any other type of policy intervention in driving innovation in renewable energy technologies.

Flexibility in the selection of patent counts: Implications for p-hacking and evidence-based policymaking

This study analyzes how researchers’ degrees of freedom in selecting patent counts influence econometrically estimated policy effects. Using the evaluation of solar energy policies as an example, we identify 51 strategies to select solar patents from the literature resulting in 306 different solar patent counts, considering six common quality levels of patents. We replicate two leading studies in this literature and re-estimate their econometric models using all of these patent counts. Our results demonstrate severe uncertainty regarding sizes and even signs of key policy effects, opening up the potential for p-hacking and posing a fundamental challenge for evidence-based policymaking. We recommend that more emphasis should be devoted to patent selection procedures, including careful sensitivity analysis regarding key assumptions, such as search strategy and patent quality level. More research is needed to develop common quality standards in working with patent data.

Measuring China’s International Technology Catchup

ABSTRACT This article compares China’s science and technology advance with the US, Japan, South Korea, the United Kingdom, Germany, and France. Using World Intellectual Property Organization and United States Patent and Trademark Office data for the number and quality of patent grants issued by foreign patent offices, several results stand out. First, within a short period, 2010–2017, China has registered a dramatic surge in granted patents, narrowing the foreign patent count gap with a number of largeOECD economies. However, quality adjustments show less impressive gains for Chinese patenting, particularly concerning semiconductors, where a large decline in quality accompanied thesurge in patenting. The article places China’s patent performance in a broader context, taking into account, the dimensions of population, geography, and time.

The impact of environmental innovation on carbon dioxide emissions

Abstract This paper examines the effects of environmental innovation on carbon dioxide emissions in the EU-27 countries between 1992 and 2014. We utilize the Generalized Method of Moments in a dynamic panel setting. Patent counts of environmental patent applications are used as indicator for environmental innovation. We find that environmental innovation did contribute to reductions of carbon dioxide emissions, while general innovative activity does not cause decreases in emissions. However, this effect is found to be comparatively small to the effects of increased economic activity. Further, we find the effect of innovation to differ across countries, with less developed economies showing a higher level of heterogeneity.

Fate of Pure Type II Endoleaks Following Endovascular Aneurysm Repair.

PurposeType II endoleaks (T2ELs) are the most common type of endoleaks observed after endovascular aneurysm repair (EVAR). However, whether T2ELs should be treated remains debatable. In the present study, we aimed to describe the natural course of T2ELs and suggest the direction of their management.Materials and MethodsWe reviewed the data of 383 patients who underwent EVAR between 2007 and 2016. Data, including demographic and anatomical details, were collected, and patients with T2ELs were compared to those without them. Patients with T2ELs were categorized into subgroups according to changes in sac size and treatment requirement.ResultsWe found patent lumbar artery count and lesser thickness of mural thrombi to be significant risk factors for T2ELs. Among the 383 patients, 85 (22.2%) patients were diagnosed with pure T2ELs. Among these 85 patients, the sac size increased in 29 (34.1%) patients, showed no significant change in 39 (45.9%) patients, and decreased in 17 (20.0%) patients. Fifteen (17.6%) patients, among 85 with initial pure T2ELs, showed spontaneous resolution. Five (5.9%) patients among 29, in whom the sac size increased, developed combined-type endoleaks. No sac ruptures were noted among the patients with T2ELs.ConclusionT2ELs with sac expansion potentially contribute to other types of endoleaks. Therefore, periodic screening is important for these patients, particularly for those showing an increasing sac size. In addition, intervention should be considered when other types of endoleaks occur.

Founder CEOs and innovation: Evidence from CEO sudden deaths in public firms

Using a unique dataset on U.S. publicly listed firms that experienced sudden deaths of CEOs during the 1979–2002 period, this paper investigates the relationship between founder CEOs and innovation in public firms. Our main results show that the exogenous change from a founder CEO to a professional CEO is associated with a 43.8% decrease in a firm's citation-weighted patent count, even when controlling for R&D expenditures, suggesting that founder CEOs are better managers of innovations than professional CEOs. To better understand the relationship, we also explore plausible mechanisms that may underlie this relationship. Our analyses show that founder-CEO-managed firms are more likely to generate innovations at the both tails of innovations’ quality distribution (highest and lowest quality patents) and explorative patents than professional-CEO-managed firms. We also determine that change in leadership from a founder CEO to a professional CEO leads employee inventors to leave the firm, suggesting that founder CEOs are better at retaining innovative minds than professional CEOs. However, we do not find evidence that founder-CEO-managed firms allocate more capital to R&D investments than professional-CEO-managed firms.

Where Does Innovation Come From?: Project Hindsight, TRACEs, and What Structured Case Studies Can Say About Innovation

Engineers and scientists often seek to use their work to benefit society, but they face difficulty in tracing the benefits of research and development. Assessing the technical and societal outcomes of research and development is an old and continuous challenge [1]-[5]. Bozeman and Sarewitz [4] argue that formal economic calculations m like tracking patent and publications counts m cannot fully capture the impact that a technological development brings. Instead, they argue for value mapping: causally mapping specific research and development activities to public goods by employing social scientists to conduct historical case studies of those innovation areas. Case studies and qualitative research in general thus present a way to both understand the benefits of past research and find the sources of innovation and the causal links between how research and development connects to public goods.

On the transfer of technology from universities: The impact of the Bayh–Dole Act of 1980 on the institutionalization of university research

While the academic and policy literature has focused on patent counts and patent quality as possible outcome measures to evaluate the impact of the U.S. Bayh–Dole Act of 1980, we argue that the impact of the Act on university effort to transfer its technology to the private sector might be seen more accurately by examining the trend in the initial establishment of technology transfer offices (TTOs). Using an econometric framework to identify the presence of multiple structural breaks in data on the annual number of university TTOs, we find multiple break dates over the period 1925 to 2014. One break date was in the late-1960s and a second break date occurred about 1982. We suggest, in contrast to previous findings in the literature, that the Act did have an impact on the formal internal transfer of technology from universities through patenting by providing an incentive for universities to invest in a TTO research infrastructure. We also suggest that our empirical methodology is applicable to an assessment of the impact of legislation similar to the Bayh–Dole Act in the many countries with such legislation.