Patent Statistics Research Articles

Causes of German Inventiveness, 1815–1990. What We Can Learn from Patent Statistics

Abstract In the second half of the 19th century, Germany developed into one of the most innovative economies in the world and was able to defend this position in the 20th century. In order to investigate the causes of this inventiveness, it is necessary to quantify innovations and assign them to inventors, regions and industries. For this reason, various historical patent databases have been set up over the last two decades, currently covering the period from 1815 to 1990. We present these patent databases and give an overview of the main empirical studies based on these statistics.

Defining innovative areas and prospects to develop the patenting of technological advances in the automotive power plant industry

The object of this study is the field of patenting of technological advances registered in the world in the field of automotive power plants. The subject of the study is the dynamics of patenting in the automotive power plant industry, associated with the need to harmonize the trajectories of technological development with global trends in energy efficiency and manufacturability, in order to ensure sustainable economic growth. Patenting in the industry is considered in the following areas: gasoline engines, diesel engines, hybrid cars, electric cars, hydrogen cars. The relevance of this study is determined by the general desire of society to innovate through the latest tools and the introduction of systemic measures to comprehensively address the problem of increasing energy efficiency and reducing air pollution caused by road transport. The paper analyzes the statistics of patents registered in the world, examines patent activity and trends in the patenting of technological advances in the automotive industry from 2010 to 2022. In the industry of gasoline and diesel engines, hybrid vehicles, electric vehicles and hydrogen vehicles, the current work investigates through systematization and analysis of important aspects of patenting statistics and innovation dynamics. For the period of 2017–2022, the average increase in the number of registered patents per year compared to the previous period was found to be 1.37 times higher for the area of "hybrid vehicles", 1.3 times higher for the area of "electric vehicles", and 26 times higher for the area of "hydrogen vehicles". A comparative analysis of the number of registered patents by areas was carried out, further patenting rates were predicted, and priority areas of research and innovation were identified

THE IMPACT OF INDUSTRY 4.0 ON THE ECONOMY: THEORETICAL AND EMPIRICAL ASPECTS

The enhanced focus on Industry 4.0 has brought numerous challenges and questions regarding the meaning and impact of this concept. The literature on Industry 4.0 has rapidly expanded recently, indicating its significant influence on the economy as a whole. The study objective is to analyse the impact of Industry 4.0 on the economy and to evaluate the OECD countries in terms of selected indicators in the major fields of science and technology. Science and technology indicators serve as measures, analytical and comparison tools to assess a country's readiness to adopt Industry 4.0. The analysis indicates that the OECD countries vary in terms of R&D spending, with an observed growth in R&D spending by businesses across most OECD countries. Universities also play a crucial role in the implementation of Industry 4.0. On average, higher education facilities in the OECD countries allocated 0.42% of GDP to R&D in 2011, and this figure was slightly up to 0.43% in 2020. The results demonstrate an increase in the number of researchers in most OECD countries between 2011 and 2020. Patent statistics were also analysed to measure technology performance across countries, revealing that Japan and the USA have a significant advantage in patent development.

Ensuring the technological independence of oil and gas companies using patent analytics on the example of companies producing liquefied natural gas

The article analyzes technological development of the oil and gas industry in Russian Federation under international sanctions, as well as the directions of technology development and equipment production. The article purpose is to identify ways to achieve technological sovereignty in the industry. Patent statistics and construction of patent landscapes is considered as a method of choosing the direction of technological development. The study object is Russian oil and gas companies, while the main attention is paid to companies producing and distributing liquefied natural gas. The study subject is application of patent statistics for identifying trends and directions of technological development of the industry. The study result is determination of industry leaders, and the most promising areas of research in the field of means and methods of liquefied natural gas transportation, methods of its liquefaction or curing, as well as storage equipment. The article draws conclusions about the most promising technologies and patent trends, such as the creation of mobile plants for production of liquefied natural gas , including the construction of its own fleet of gas carriers and floating plants for the gas liquefaction to provide access to the infrastructure of offshore fields. In addition, for rapid development of new markets, the use of floating terminals for regasification is proposed. Approaches to assessing the innovation activity and competitiveness of companies have been considered.

Global patent activities survey in the field of welding for the period of 2013−2022

This study is an example of the application of IPR methods in the R&D management. The purpose of this article is to describe the global situation and trends ofpatenting in the field of welding. In Ukraine such a study put through for the first time.Based on the results of a series of searches using IPC indexes, an analysis of the worldwide patent statistics in the field of welding for 2013−2022 was accomplished. The overwhelming dominance of China was revealed among the countries in which patent applications are filed. China’s share for 2013-2022 was almost 83 % and continues to grow rapidly. The USA has second rate with 4.3 %, and Japan is third with 3.1 %. Ukraine, having its share as of 0.06 %, ranks 15th among almost 50 countries. The top 10 applicants in the field of welding are manufacturing companies that surpass most countries in the world in terms of their patent activity. Five of them are Japanese, two each from the USA and China, and one is Korean. The R&D sector among the first hundred applicants is mainly represented by Chinese universities. There are only three European companies in the top 100 applicants, namely Siemens, Bosch and Fronius.
 Itemized peculiar structure of research and developments in the field of welding was determined and compared with the proper structure of scientific research conducted at the E.O. Paton Electric Welding Institute (PWI). It is typical that in the global dimension, the greatest efforts are focused on patenting universal devices and processes that can be used in various welding methods (44 %), followed by electric arc welding in all its variety of applications (12.2 %) and then laser welding and related technologies (7.5 %). Meanwhile, in the structure of scientific research of PWI, a prominent place is occupied by electric arcwelding technologies (37.0 %), followed by the creation of new substances for the manufacture of rods, electrodes, materials or environments used in welding (15.6 %).On a practical aspect, exploitation of IPR methods in R&D activities is needed not only to determine the freedom to operate of the results of scientific research and newly developed technologies, but for operational and medium-term planning of R&D activities, to determine the place of any scientific institution among other research centers, enterprises and companies which belong to a certain industry.

Global value chains and knowledge spillover to local economy in Visegrad 4 countries

AbstractThis study empirically examines knowledge spillover in Visegrad Four (V4) countries, with an emphasis on global value chains (GVCs). Using patent statistics, the study aims to estimate the knowledge production function, including domestic and foreign knowledge stocks, and found that international knowledge spillover does not contribute much to the innovation of the local economy in the V4 countries because of three factors: i) multinational corporations' (MNCs) strategy to locate a low-cost production base, ii) MNCs' strategy to locate supporting (process, production or non-core product related) research and development (R&D) activities and iii) limited technology spillover effect from MNCs to local firms. Local firms in the V4 countries became dependent on the peripheral products and technologies provided by MNCs, and as a result, local R&D activities in the V4 countries were diverted from patentable innovation.

Cultivating Agricultural Evolution: Revolutionizing Farming Through The Power of AI And Technology

Objective: The objective of this study is to explore the current and potential role of Artificial Intelligence (AI) in the agricultural sector. We aim to analyze the adoption and impact of AI solutions in farming, identify challenges, and discuss the prospects for its future integration.
 Method: We conducted a comprehensive review of existing literature and ongoing research projects related to AI applications in agriculture. We also examined case studies, technological developments, and AI pioneers in the field.
 Results: Our analysis reveals that while AI solutions are being researched and applied in agriculture, there is a gap in widespread industry adoption. Large-scale research projects are underway, and some AI applications are available in the market. However, the development of predictive solutions to address real farming challenges is in the early stages. AI's influence extends across various sectors, contributing to the advancement of technologies such as big data, robotics, and the Internet of Things.
 An illustrative example is the styrofoam container device, which utilizes machine learning and computer vision to detect and categorize "safety occurrences." Although not all-encompassing, this technology gathers significant data, such as driver behavior, speed, and surroundings. IFM's system promptly alerts supervisors to safety breaches, enhancing both safety and productivity.
 Conclusion: The future of AI in agriculture hinges on the widespread adoption of AI solutions. The agricultural industry remains underserved in terms of AI integration, and the development of predictive solutions is in its early stages. However, AI's impact across sectors underscores its importance. Pioneers like IFM and IBM's patent statistics demonstrate the expanding scope of AI innovation.

Catching up or forging ahead in the era of 5G? Evidence from Chinese patent data

Probing the development of technology can offer insights into its future implementation. In this study, patent statistics are used to examine the changes in the technological capacity of the telecommunication sector in China and shed light on the development of 5G technology. Given full access to patent data, we find an increase in patent applications eventually leads to an increase in the innovation quality of the Chinese telecommunication sector. Firms, particularly industry leaders, greatly contribute to technological capacity by constantly producing high-quality innovation. Unlike those of previous studies, our findings reveal that a robust advancement reduces the technological capacity gap between the telecommunication sectors of the U.S. and China. Patent measures not only enable us to determine that Chinese telecommunication technology is at the gradual catch-up stage of the catch-up cycle, but also reveal responses to the technology window, the demand window, and the institutional windows of opportunity. Moreover, patent statistics can track knowledge flows. It can also find that accessing foreign knowledge has helped the Chinese telecommunication sector for learning and assimilating such knowledge to cultivate its knowledge base. We further find other than training qualified professionals, universities offer limited contributions to the technological capacity of the telecommunication sector.

Predicting the value of Chinese patents using patent characteristics: evidence based on a Chinese patent auction

Abstract This study revisits the question of predicting patent value with observed patent statistics, exploiting a rare public auction of patents in China in which the starting prices are used as approximates of patent private value. Family size and the number of assignees come out as the most consistent indicators, while notably, forward citations turn out to be not important. This discrepancy with past studies is investigated. We propose some of the institutional features in the Chinese patent system could lead to the forward citations not as informative as their counterpart in other jurisdictions. The findings bear important implications as Chinese patent data are increasingly being used in innovation studies.

Mapping firms’ locations in technological space: A topological analysis of patent statistics

Where do firms innovate? Mapping their locations and directions in technological space is challenging due to its high dimensionality. We propose a new method to characterize firms’ inventive activities via topological data analysis (TDA) that represents high-dimensional data in a shape graph. Applying this method to 333 major firms’ patents in 1976–2005 reveals hitherto undocumented industry dynamics: some firms remain undifferentiated; others develop unique portfolios. Firms with unique trajectories, which we define and measure graph-theoretically as “flares” in the Mapper graph, tend to perform better. This association is statistically and economically significant, and continues to hold after we control for portfolio size, firm survivorship, and industry classification.

Employing online big data and patent statistics to examine the relationship between end product's perceived quality and components' technological features

The aim of this work is to analyse the relationship between components' technological features and a product's perceived quality by consumers. The information about technological features is gathered from patent data, whereas the perceived quality is based on a voluminous set of online users' opinions. The research intends to let emerge the usefulness of big data for managing the technological development of high-tech products. The relationship is tested in the smartphone industry, focusing on 168 flagship smartphones. The work demonstrates the role of components of a product architecture in improving the end product's market value. Specifically, the perceived quality of a smartphone seems to be particularly affected by technological features of three components - application processor, camera module, and image sensor - in terms of both technological capacity and technological strategy.

Appropriability and basicness of R&D: Identifying and characterising product and process inventions in patent data

We present a database that classifies all patent applications filed at either the United States Patent and Trademark Office (USPTO) or the European Patent Office (EPO) as being either product patents, process patents or ‘mixed patents’. We use the share of claims that refer to either product or process inventions which allows to classify all patent applications along a continuum of pure process patents and pure product patents. We find that process-oriented patents draw more on previous knowledge, are more original and more radical than product patents. Lower breadth of protection is positively associated with pure process patenting, whereas product and mixed variants can be protected more broadly. This characterisation uncovers heterogeneity of patented inventions that allows for a more sophisticated use of patent statistics. It can improve the accuracy of analyses, but also reveal new aspects related to property rights.

Understanding Technological Input and Low-Carbon Innovation from Multiple Perspectives: Focusing on Sustainable Building Energy in China

Low-carbon technological innovation has been attached importance to realize cleaner future in buildings, transportations and industries. As a major carbon emitter country, it is important to evaluate China’s indigenous low-carbon technological innovation capacity. By analyzing the impact of economic and technological input indicators on the growth of low-carbon technology innovation, this paper conducts general regression and quantile regression analysis through the statistics of enterprise investment and patent statistics of low-carbon technology innovation in cities from 1990 to 2019. The empirical results show that when the economic and technological input increases, it has a positive impact on low-carbon technological innovation. Secondly, when the scale of low-carbon technological innovation in a region is still at a low level, the impact of technological input brings a strong marginal effect, but with the growth of the scale of low-carbon technological innovation, the marginal effect gradually decreases. In order to further observe the micro-level specific technology development, by taking China’s subdivided patents related to building energy efficiency (BEE) as an example, the dynamic changes of low-carbon innovation are explained and demonstrated with the green productivity factors. In case of Yangtze River Delta, the Moran Index increased from 0.031048 to 0.055296 from 2005 to 2020, and the influencing factors in each time period gradually increase, which reflects that the interpretation of BEE low-carbon innovation becomes more and more complex over time. Future research needs more combination of macro and micro to achieve more effective judgment and decision-making.

Quantitative Analysis of China's Artificial Intelligence Technology Patents

Traditional patent statistics cannot accurately reflect the real development level of technology. In order to overcome this deficiency, this study adopts quantitative research methods to conduct empirical research on global artificial intelligence technology-related patent applications, and on this basis, provides suggestions for the government and enterprises on how to improve my country's innovation capabilities in the field of artificial intelligence. First, this paper analyzes patent application trends, technology application areas and innovation trends using the incoPat patent search database and information visualization tools. On this basis, the Herfindahl-Hirschman index is further used to measure and analyze the patent concentration of artificial intelligence technology patent applicants in various regions of my country. The analysis results show that my country has the largest number of patent applications in the area of artificial intelligence technology, but the proportion of high-value patents is relatively low, which needs to be further improved. Patents in the eastern region are relatively scattered, while patents in the western region are relatively concentrated. The government should introduce policies according to local conditions to avoid excessive concentration and dispersion of patents.

Аналіз тенденцій технологічного розвитку країн світу в контексті патентної статистики

In the face of increased competition in the world market, the issue of assessing the factors of influence on the technological development of the world countries is actualized. To this end, the article measures the indicators of patent activity in the context of individual regions and countries of the world, together with technological areas, using the patent statistics databases. According to the results of the research, the following main conclusions are made: – a noteworthy feature of modernity is the dynamic growth of patent activity (+42% for 2012-2021) as a significant criterion for technological development of the world countries; – in particular, the active patent position of three Asian countries (China, Japan, South Korea: a combined share of 54.1% of PCT applications in 2021) provided them with leading positions in the international patenting of inventions, as well as control over large niches of the global market in the field of computer (31.4%) and digital (26.7%) technologies, as well as electrical machine-building (20.2%); – the first-rank status belongs to China, which in both computer (15.6%), and digital technologies (15.2%) is ahead of even the United States (12.4% and 9.7%, respectively), where these technologies de facto originated; – a significant sphere of U.S. interests in the global market are also medical technologies (10.8%), while for Germany it is energy (10.3%) and transport (9.6%); – however, Ukraine has no place on the world technological map, as indicated by almost zero share of patent activity (0.06% in 2012; 0.05% in 2021) and its negative dynamics (–17%). Taking into account the extremely negative assessments obtained for Ukraine, which is a contradiction with the global tendency, the need to raise patent activity appears a key task of technical and technological reconstruction of the economy.

Industrial innovation characteristics and spatial differentiation of smart grid technology in China based on patent mining

Based on the perspective of smart grid patent, this study crawls the smart grid patent data from 2009 to 2020, and extracts the hotspots of innovation space in different stages. By mining the patent information, this paper identifies the hot innovation fields of smart grid in China and the world, and selects IPC classifications of H02J, G01R and H04L as the main hot smart grid technologies for innovation space analysis. In further study, methods such as global autocorrelation analysis are used to comprehensively analyze the spatial distribution of smart grid innovation in China. It is found that innovation activities of China's smart grid industry are spatially agglomerated. However, during 2017–2020, such spatial distribution represents China's smart grid industry has approached the distribution pattern of normal innovation industries which tends to be discrete or competitive. According to autocorrelation analysis, China's smart grid innovation space has obvious agglomeration characteristics, showing a gradual decline trend from the center to the periphery, and the diffusion effect has initially appeared. Finally, the smart grid patent statistics and the spatial ellipse parameters intuitively present the innovation characteristics of China's smart grid industry in terms of the evolution of the spatial differentiation during 2009–2012, 2013–2016, and 2017–2020.

How different patterns of urbanization affect regional innovation? Evidence from Russia

ABSTRACT The present paper assesses the impact of general urbanization and urbanization patterns (the number of cities of a certain size in the region) on different phases of the regional innovation process: knowledge creation, implementation, and production of innovation production. Knowledge creation is measured by patent statistics, knowledge implementation – by the share of innovative organizations, innovation production – by the volume of innovation production produced by industrial organizations. We apply the dynamic panel data model technique by using data from the period of 1998 to 2016. Our results suggest that general urbanization has a positive influence on every stage of the innovation process, while the impact of different urbanization patterns varies depending on its stage. Million plus cities affect knowledge creation in the region but have no considerable impact on knowledge implementation and innovation production. At the same time, the presence of cities with a population from 0.5 million to 1 million people in the region positively influences more mature stages of the innovation process: knowledge implementation and manufacturing of innovation production. So far as the effective innovation development demands complete innovation cycle, not only million plus cities should be considered as the main drivers of innovation, but cities of lower size (at least with population from 0.5 million to 1 million people) as well should attend the innovation agenda.

Trends and relationship among intellectual capital disclosures, patent statistics and firm performance in Indian manufacturing sector

PurposeThis study highlights the trends of qualitative intellectual capital disclosures and patent statistics in the Indian manufacturing context by considering the numerous patent applications, patent grants, forward citations and backward citations. Furthermore, the study investigates the relation among qualitative disclosures, patent statistics and firm performance.Design/methodology/approachAll manufacturing companies of CNX 500 Index of National Stock Exchange of India Limited are considered. Based on data availability, 243 manufacturing firms spanning across seven major manufacturing sectors are included. Secondary data were obtained from the annual report of companies and patent databases from 2004 to 2005 to 2013–2014, generating a sample of 2,430 firm years. Content analysis and citation analysis are used for collecting the relevant data.FindingsOverall, the study results indicated increasing trends for all types of intellectual capital disclosures. Similar trends are observed for patent applications and patent grants, indicating a surge in patenting activities across the manufacturing sector. However, increasing trends in patenting activities are not reflected for forward and backward citations. In addition, significant differences in means and trend coefficients for qualitative disclosures and patent statistics indicated industry specificity within the Indian manufacturing sector. Furthermore, industry specificity is observed when translating intellectual capital to firm performance. The measure of firm performance, that is, Tobin's Q, is having a significant positive association with qualitative disclosures and patent statistics.Research limitations/implicationsAs the study is based on secondary data, its accuracy is limited by the accuracy of the data sources such as the annual reports of companies and patent databases.Practical implicationsThe study findings imply that policymakers should devise and execute sector-specific policy interventions. Moreover, managers and policymakers should emphasize the qualitative aspect of patenting activities.Originality/valueThe study is an original work that highlights the trends in qualitative disclosures in the Indian manufacturing context. The value relevance of intellectual capital and patent statistics has been established.

Predicting innovative firms using web mining and deep learning.

Evidence-based STI (science, technology, and innovation) policy making requires accurate indicators of innovation in order to promote economic growth. However, traditional indicators from patents and questionnaire-based surveys often lack coverage, granularity as well as timeliness and may involve high data collection costs, especially when conducted at a large scale. Consequently, they struggle to provide policy makers and scientists with the full picture of the current state of the innovation system. In this paper, we propose a first approach on generating web-based innovation indicators which may have the potential to overcome some of the shortcomings of traditional indicators. Specifically, we develop a method to identify product innovator firms at a large scale and very low costs. We use traditional firm-level indicators from a questionnaire-based innovation survey (German Community Innovation Survey) to train an artificial neural network classification model on labelled (product innovator/no product innovator) web texts of surveyed firms. Subsequently, we apply this classification model to the web texts of hundreds of thousands of firms in Germany to predict whether they are product innovators or not. We then compare these predictions to firm-level patent statistics, survey extrapolation benchmark data, and regional innovation indicators. The results show that our approach produces reliable predictions and has the potential to be a valuable and highly cost-efficient addition to the existing set of innovation indicators, especially due to its coverage and regional granularity.

Global patent statistical analysis for drug testing technology.

BACKGROUND:In recent decades, illicit drug testing has become a high priority area in law enforcement and forensic analysis.OBJECTIVE: Since patents are the largest source of technical information in the world, patent database analysis for illicit drug testing is extremely important to effectively promote the development and protection of the related intellectual property rights.METHODS:In the present study, we first retrieve a database of 1732 drug detection patents using keywords and logical expressions related to the title, abstract, and claims, and subsequently discuss the current global patent statistics in detail.RESULTS:The relevant patent information is presented, including patent application quantity, filing country, ownership, and technical field.CONCLUSIONS: Finally, we summarize the current development trend in drug testing and propose several suggestions focused on the bottleneck of analytical techniques.