Patent Counts Research Articles

Does a Financial Crisis Impair Corporate Innovation?

AbstractWe examine whether financial crises affect innovation output in the context of the 1997–98 crisis in Japan by developing the data on patent counts and future patent citations. Innovative outputs of firms that relied more heavily on bank finance fell more, and that bank dependence matters more for small firms. By employing semiparametric propensity score weighting methods, we also show that small firms which had long‐term, precrisis relationships with the failed banks exhibited a large decline in innovative outputs. The results suggest that crisis‐induced disruptions in the provision of intermediated funds reduced the innovative capacity of the opaque, bank‐dependent firms.

Corporate innovation and performance: a textual measure based on securities analysts’ research reports

ABSTRACT The relationship between innovation investment and firm performance has been a central focus of academic research. Traditional metrics, such as patent counts and R&D expenditures, are often criticised for their limited scope and lack of diversity. In contrast, analyst reports offer a richer source of information on innovation activities. This study employs textual analysis to assess firms’ innovation efforts by examining research reports on publicly listed companies. Using methods such as word segmentation, the research constructs corporate innovation indicators based on the LDA (Latent Dirichlet Allocation) topic model. Analyzing data from 2010 to 2021, the study empirically validates these new innovation indicators and investigates their impact on firm performance. The findings indicate that corporate innovation significantly enhances firm performance. Compared to traditional metrics like patents, the indicators developed here are more comprehensive, offering a broader measure of innovation and addressing the limitations of conventional metrics. These results are consistent across various robustness checks. Additionally, the study finds that corporate innovation improves performance primarily by increasing total factor productivity. Furthermore, strong corporate governance amplifies the positive impact of innovation on firm performance.

Analyzing the Impact of Scientific and Technological Innovations on Financial Performance: A PCA-Based Study of an AI Healthcare Startup

This study explores the relationship between scientific and technological innovations and the financial performance of startups, focusing on a representative Artificial Intelligence (AI) healthcare startup. Utilizing Principal Component Analysis (PCA), the research aims to dissect the complex interplay between innovation-related metrics—such as R&D spending, patent counts, and technology adoption rates—and financial outcomes like revenue growth, profitability, and market share. The PCA methodology enabled the reduction of high-dimensional data into PCA, which clearly illustrates how several dimensions of innovation impact financial metrics. The approach used in the investigation helps people comprehend more thoroughly how development benefits business viability in several different manners and provides startups with practical advice to use when preparing their revolutionary investments. This paper aims to assist the ecosystem of startup consumers (including investors, business owners, and policymakers) in making better decisions that balance technological progress with economic objectives.

Dual-Credit Policy of New Energy Automobiles in China: Corporate Innovation Capability

This study investigates the impact of China’s Dual-Credit Policy on innovation capability in the new energy vehicle (NEV) industry using a difference-in-differences approach with dynamic panel data from 2013 to 2022. We employ multiple innovation measures, including patent counts, valid invention patents, and patent grant rates. Our findings reveal that the policy has a positive and significant effect on NEV innovation, partially mediated by R&D investment. Using GMM estimation to address endogeneity, we find the policy effect varies across subgroups based on location, ESG rating, and ownership type. Dynamic effect analysis shows the policy’s impact intensifies over time. Threshold effect analysis identifies a critical policy intensity level beyond which innovation effects are amplified. Our results have implications for policymakers in designing effective innovation incentives and for firms in strategically responding to regulatory changes in the NEV sector.

Digital Economy and Its Impact on Sustainable Business Practices: An Analytical Study in the Chinese Context

This research investigates integrating the digital economy with sustainable business practices in China, focusing on the dynamic nature of digital technology adoption and environmental sustainability within Chinese enterprises. The study aims to recommend effective strategies for enhancing sustainable innovation through digitalization, providing guidance for policymakers, corporate leaders, and managers. By selecting a sample of firms from 2008 to 2022, including data from companies listed on the stock exchange and detailed patent information, the study employs zero-inflated negative binomial regression to address the peculiarities of patent counts accurately. This method avoids the assumptions of linearity of dependent variables and normality of residuals common in many empirical innovation studies. The research confirms a positive relationship between digital adoption and green patents. Notably, there is a significant reduction in environmental outputs from firms operating in China’s 'Big Data Comprehensive Pilot Zone,' supporting the argument that policies promoting green innovation are effective. Additionally, the study identifies several key factors influencing the successful implementation of digital technologies and sustainability, including firm size, industry nature, and regional economic characteristics. These findings are crucial for policymakers and managers, emphasizing the importance of digitalization in achieving sustainability goals.

EXPRESS: Untangling the Duality of Emerging Market Firms’ Response to OFDI Policies on Their Innovation Performance: A Resource Dependence Perspective

Firms’ international expansion, affected by outward foreign direct investment (OFDI) policies of home countries, can greatly shape their innovation performance. Yet, existing literature lacks sufficient investigation toward the nexus between corporate response to policies in OFDI activities and subsequent innovation performance. Thus, the authors designed this study to examine how a firm’s response to OFDI policies affects its innovation performance. Drawing upon the resource dependence theory, the authors theorize corporate response to OFDI policies as firm dependence on home government. By arguing that such dependence differentially affects firm innovation through support and control mechanisms, they elucidate the inverted U-shaped relationship between corporate response to OFDI policies (measured by the percentage of a firm’s OFDI projects in policy-favored markets) and innovation performance (measured as patent counts). Furthermore, this curvilinear relationship, they posit, is moderated and strengthened by home-government subsidies the firm receives (calculated as the ratio of annual subsidies received to yearly sales). With archival data of 2,050 Chinese listed manufacturing firms responding to specific OFDI policies during 2013–2021, their predictions are corroborated. Overall, by illuminating the innovation implications of OFDI as corporate response to policies, this study contributes to the international marketing literature in the context of emerging markets.

Correlation Between Scientific and Technological Innovation and Financial Performance of Seed Enterprises: Application of Principal Component Analysis Algorithm in Performance Evaluation

This study explores the relationship between scientific and technological innovations and the financial performance of startups, focusing on a representative Artificial Intelligence (AI) healthcare startup. Utilizing Principal Component Analysis (PCA), the research aims to dissect the complex interplay between innovation-related metrics—such as R&D spending, patent counts, and technology adoption rates—and financial outcomes like revenue growth, profitability, and market share. The PCA methodology enabled the reduction of high-dimensional data into PCA, which clearly illustrates how various dimensions of innovation impact financial metrics. The approach used in the investigation helps people comprehend more thoroughly how development benefits business viability in several different manners and provides startups with practical advice to use when preparing their revolutionary investments. The objective of the research is to assist the ecosystem of startup consumers (including investors, business owners, and policymakers) in making better decisions that balance technological progress with economic objectives.

Analyzing New Energy Vehicle Sales Influencing Factors Based on Statistical Learning

Amid global environmental concerns and the push for sustainable development, the electric vehicle (EV) market is expanding swiftly, recognized as pivotal in curbing greenhouse gas emissions and advancing energy diversification. This thesis investigates factors shaping the EV market and assesses the impact of new energy vehicle development on conventional vehicles. Drawing on industry reports, market data, and relevant literature, it delves into key factors influencing China's new energy vehicle market, such as patent counts, public charging infrastructure, and government subsidies. Based on this analysis, recommendations are proposed to foster the sustainable growth of the new energy vehicle market, including subsidies for related industries, fostering technological innovation, and enhancing charging infrastructure. The study offers insights into the current and future trajectory of the electric vehicle market, revealing rapid expansion at the expense of traditional energy vehicles. By quantifying and visualizing the impact of new energy vehicles on traditional counterparts, this research furnishes valuable insights for policymaking in the new energy vehicle sector.

Commentary: Customer-Perceived Innovation: Considerations for Financial Performance and Methodological Approaches

As firms increasingly uncover their activities to key stakeholders through various media, the perception of these activities is becoming more important for firm performance. Traditionally, access to industry-wide databases provides important metrics on customer perceptions of performance, such as customer satisfaction and brand equity. In addition, numerous studies have highlighted firms' innovation-related actions (e.g., R&D spending and patent counts) as critical metrics linked to their financial performance. Perceived Firm Innovation (PFI) emerges as a relatively new and under-studied metric with the potential to impact a firm's financial success. Keiningham et al. are among the pioneers in this area. This commentary views their article as a vital initial step in understanding PFI’s impact. Considering that the service sector accounts for over 70 percent of the GDP in any developed country, service innovation is a broad phenomenon. Given the breadth of the area, we point to the challenge of capturing this phenomenon with a single metric like PFI. We also discuss crucial methodological considerations for future research, including estimation methods, sample size, and financial metrics.

Partisanship, optimism, and firm innovation

AbstractPolitical partisanship significantly shapes firm executives’ economic outlook. We find that firms, whose managers share political alignment with the US president, achieve superior innovation outcomes, including higher patent counts, increased patent citations, and greater patent value. We establish a causal relationship through a difference‐in‐differences approach, focusing on periods around US presidential elections. This effect is more pronounced in firms with overconfident CEOs and during periods of heightened policy uncertainty, suggesting that partisan optimism stimulates innovation incentives. Firms led by partisan‐aligned managers generate patents with greater originality, generality, and an exploratory style.

Exploring Technology-Driven Technology Roadmaps (TRM) for Wearable Biosensors in Healthcare

ObjectivesThis paper is proposed to identify both promising technologies and potential products in the domain of biosensor using patent-based Technology-Driven Technology Roadmaps (TRM). Materials and methodsThe technology-driven TRM with timelines in this study is developed in three layers: technology, function and product. Patent applications are collected and identified to interpret technologies and functions for biosensors in healthcare, and product manuals or releases can be used as product introductions. ResultsMost biosensors in healthcare patents are concentrated in biochemical (T2) and electroencephalography (T5). Glycated hemoglobin (F1), measuring of glucose (F3), and biological process and molecular systems (F6) have a relatively larger patent count. Biochemical (T2) can combine with biological process and molecular systems (F6), and then brain's real-time electrical activity monitoring can be handled. Biochemical (T2) can also devote to glycated hemoglobin (F1), and glucose monitoring (F3), and thus create QCM sensor, CGM and GlucoWatch etc. applications. ConclusionBiochemical (T2) has a wide application among different functions for wearable biosensors in healthcare. This paper identifies and explores new developments biochemical (T2), and electroencephalography (T5) in wearable biosensors are expected to play a significant role over the coming decade in improving the current healthcare infrastructure, and enhancing the democratization of information and allocation of medical resources.

Natural resource‐driven prosperity: Unveiling the catalysts of sustainable economic development in the United States

AbstractAchieving economic progress hinges upon the active and strategic utilization of a nation's inherent resources in economic and financial endeavors. This comprehensive study investigates the intricate dynamics influencing the economic development of the United States, employing a time series dataset spanning from 1991 to 2022. Key factors including total natural resource rents, domestic capital formation, the ‘financial risk index (FRI),’ and the count of patents filed by both domestic and foreign investors. Rigorous statistical analyses, including the ‘Modified Dickey‐Fuller’ test and ‘Bayer‐Hanck cointegration’ strategy, were employed to extract meaningful insights from the data. Addressing concerns related to endogeneity and serial correlation, advanced techniques such as ‘Dynamic Ordinary Least Squares’ and ‘Fully Modified Ordinary Least Squares’ were applied. The findings illuminate the pivotal roles played by natural resource rents and domestic capital formation in propelling sustainable economic development in the United States. Notably, this study sheds light on the positive contributions of both domestic and foreign patent filings to the nation's economic trajectory. Furthermore, enhancements in the FRI are identified as catalysts for fostering sustainable economic growth. In essence, our research contributes to the existing body of knowledge by offering nuanced insights into the multifaceted influences shaping the economic landscape of the United States. The results not only underscore the significance of effective resource management and capital formation but also emphasize the positive impact of innovation, represented by patent filings, and improvements in the FRI on the nation's journey towards sustainable economic growth.

Measuring science and innovation linkage using text mining of research papers and patent information

In this study, the text information of academic papers published by Japanese authors (about 1.7 million papers) and patents filed with the Japan Patent Office (about 12.3 million patents) since 1991 are used for analyzing the inter-relationship between science and technology. Specifically, a distributed representation vector using the title and abstract of each document is created, then neighboring documents to each are identified using the cosine similarity. A time trend and sector specific linkages within science and technology are identified by using the count of neighbor patents (papers) for each paper (patent). It is found that the science intensity of inventions (the number of neighbor papers for patents) increases over time, particularly for university/PRI patents and university–industry collaboration patents over the 30 years studied. As for university/PRI patents, the institutional reforms for the science sector (government laboratory incorporation in 2001 and national university incorporation in 2004) contributed to the interactions between science and technology. In contrast, the technology intensity of science (the number of neighbor patents by paper) decreases over time. It is also found that the technology intensity of life science papers is rather low, although they have a significant impact on subsequent patents. However, there are some scientific fields which are affected by technological developments, so that the state of science and innovation interactions is heterogeneous across the fields.

Measuring Innovativeness: A ranking of the ordinal utility from consumption is more robust than either of ‘outcomes of commercialization’ or patent counts

This study provides formal theoretical evidence that patent counts are not robust measures of the innovativeness of economic agents. Study inferences are rationalized by two complementary insights, the first quantitative, the second qualitative. Whereas, feasibly the assumption that the distribution of patent counts is quasiconcave surmounts the quantitative rationale, the qualitative rationale – Net Present Values (NPVs) of patents dominate patent counts as measures of the innovativeness of agents – is binding. The robustness of the qualitative rationale is evident in the finding that it rules out the feasibility, to wit, all other tools for the appropriation of innovations, such as secrecy, lead time, learning curve, etc. are robust proxies for the innovativeness of agents. The realization that a higher NPV can be the outcome of high demand that is induced by consumers’ budget constraints, equivalently can be the ‘outcome of commercialization’, vis-a-vis the ‘technological dominance’ of new products results in the insight that the NPV rule also is, itself not a robust measure of the innovativeness of agents. In aggregate, ‘a ranking of the ordinal utility’ that rational consumers derive from products, a ranking that, feasibly is violated by their budget constraints, is shown to be a more robust measure of the innovativeness of agents than a ranking of innovations’ NPVs. Since technological complexity has, as objective the satisficing of consumers’ utility, a ranking of utility also is a more robust measure of the innovativeness of agents than a ranking of technological complexity.

Firm innovation under import competition from low‐wage countries

AbstractIn recent years, manufacturing firms in the United States have faced increasing import competition from low‐wage countries, especially China. Does this competition hurt or help firm innovation? This paper studies the effect of the surge in imports from China on innovation by US manufacturing firms. We first propose a theoretical framework that generates an inverted‐U‐shaped curve of innovation on imitation, which is based on the endogenous price elasticity of demand for the product in a Cournot model. We then take the theoretical prediction to data on publicly listed firms in the Compustat data set from 1990 to 2010. We find consistent evidence that Chinese import competition had an inverted‐U effect on firm innovation, as measured by patent counts and citation‐weighted patents. Our result suggests that when import penetration is less than 60% it positively affects firm innovation, but when it is more than 60%, this positive effect is inverted. This inverted‐U relation persists when we instrument import competition in the United States by using Chinese import penetration in the United Kingdom and when we test the robustness of the results by including sector‐specific trends. We find that the inverted‐U relationship is steeper for firms in high‐tech industries.

A Business Strategy Framework for Patent Pooling in the Solar Cell Supply Chain

In the green energy sector, which includes the solar cell industry, effectively combining the patents of various manufacturers within the supply chain to collectively create sustainable patent market value is of paramount importance. This study aimed to establish a business strategy framework for project-based licensing through the analysis of solar cell patents and the integration of supply chain manufacturers’ patents, with the goal of collectively creating market value for patents in a sustainable manner. The research methodology included analysis of the literature and focus group discussions. The study began with an analysis of solar cell industry patents from the past decade using the WIPS Global Patent database to identify projects with the highest patent count. Subsequently, through the use of focus group discussions, the feasibility of a patent pool strategy within the supply chain was explored. Finally, a strategy framework was proposed for project-based patent pool licensing, focusing on the top 15 projects with the highest count of 5579 patents. The results indicate that adopting this strategy framework for supply chain manufacturer patents can result in higher commercial patent value.

Environmental efficiency evaluation of China's power system considering factor's spatial dependence: A dynamic spatial network DEA approach

Evaluating and improving the environmental efficiency of the power system is the key to achieving sustainable development. However, the classic DEA approach is susceptible to producing biased results due to its inability to address spatial dependence across factors. Considering the spatial dependence of inputs and outputs, this paper proposes a dynamic spatial network DEA model with slacks-based measure (SNSBM) to examine the environmental efficiency of China's power systems, with a focus on the undesirable outputs of CO2, NOx, and SO2. The investigation incorporates the Moran's I test to account for the spatial interactions of patent counts, coal consumption, CO2 emissions, and renewable power generation. Compared to the classic network DEA, the SNSBM results reveal distinct spatial characteristics and a heightened level of differentiation, which highlights the importance of eliminating spatial dependence. From a dynamic perspective, environmental efficiency shows a visible surge in transmission and distribution divisions after 2015, confirming the success of China's market-oriented reform. In addition, CO2 is the largest contributor to the environmental inefficiency of the power systems, followed by NOx and SO2. This study highlights the importance of spatial dependence and provides many insightful policy recommendations for improving the environmental efficiency of China's power systems.

The role of human capital: Evidence from corporate innovation

This paper examines the distinct roles played by inventors and firms in contributing to corporate innovation. Inventors are six to eight times as important as firms in contributing to innovation performance as measured by patent and citation counts, but their importance is about the same in innovation strategies as captured by patent exploratory and exploitative scores. Furthermore, when labor mobility is reduced, the relative importance of firms to inventors in contributing to innovation strategy increases. Additional tests suggest that our main findings are unlikely driven by endogenous matching between firms and inventors.

Heterogeneous Innovation over the Business Cycle

Abstract Schumpeter (1939) claims that recessions are periods of “creative destruction,” concentrating innovation that is useful for the long-term growth of the economy. However previous research finds that standard measures of firms’ innovation, such as R&D expenditures or raw patent counts, concentrate in booms. We argue that these measures do not capture shifts in firms’ innovative search strategies. We contemplate firms’ choice between exploration versus exploitation over the business cycle and find evidence with more nuanced measures of patent characteristics that firms shift toward exploration during contractions and exploitation during expansions, with a stronger effect for firms in more cyclical industries.

Employment Trends and Relative Influence of U.S. Retail Subsector Employments on GDP

This paper studies employment trends of the U.S. retail industry and its twelve subsectors for the period 1998 through 2021. The retail subsectors are: motor vehicle and parts dealers (NAICS 441), furniture and home furnishing stores (NAICS 442), electronics retail stores (NAICS 443), building material retail stores (NAICS 444), food and beverage stores (NAICS 445), health and personal care retail stores (NAICS 446), gasoline stations (NAICS 447), clothing and accessories retail stores (NAICS 448), sporting goods, hobby goods, books, and music retail stores (NAICS 451), general merchandise stores (NAICS 452), miscellaneous retail stores (NAICS 453), and nonstore retail stores (NAICS 454). Comparing the pre-pandemic (2017-19) and post-pandemic (2019-21) employment growth rates, this study finds nonstore retailers (NAICS 454) and Food and beverages stores (NAICS 445) to be the most pandemic-proof subsectors in terms of retail employment. Besides multi-jurisdictional employment trends of this industry, this paper also explores the state-level influence of retail sub-sectoral employments on U.S. GDP using a fixed panel regression model. The retail subsectors that displayed statistically significant positive correlation with GDP are motor vehicle dealerships, health and personal care stores, clothing stores, and nonstore retailers such as electronic shopping and mail order businesses. Among the control variables, state-level total patent counts had statistically significant positive correlation with GDP.