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Article

Global Collaboration in Technology Sectors during the COVID-19 Pandemic: A Patent Review

by
Eunsook Jeon
1,
Kyungkook Kim
2,
Hyunjeong Park
1 and
Keuntae Cho
1,3,*
1
Graduate School of Management of Technology, Sungkyunkwan University, Seoburo 2066, Suwon 16419, Republic of Korea
2
Samsung Science & Technology Foundation, 4, 74-gil Seochodaero, Seocho-gu, Seoul 06620, Republic of Korea
3
Department of Systems Management Engineering, Sungkyunkwan University, Seoburo 2066, Suwon 16419, Republic of Korea
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(15), 11831; https://doi.org/10.3390/su151511831
Submission received: 15 June 2023 / Revised: 22 July 2023 / Accepted: 28 July 2023 / Published: 1 August 2023
(This article belongs to the Special Issue Sustainable Planning and Preparedness for Emergency Disasters)
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Abstract

:
This study aims to identify the international technology trends and convergence structures that emerged during the coronavirus disease (COVID-19) pandemic by analyzing COVID-19-related patents. Accordingly, network analysis was performed using data drawn from COVID-19-related patent applications submitted to the World Intellectual Property Organization (WIPO) between 2020 and 2022. The results showed that patent applications were submitted in 21 countries, with 97% of all applications coming from the intellectual property 5 (IP5) countries (US, Korea, China, Japan, and Europe). Technology convergence has occurred between the fields of physics and biology or between different biotechnology sectors. Owing to the nature of government-initiated development processes, technologies related to infectious diseases may exhibit a correlation between national patents and disease control policies. This study is significant since it empirically analyzes the convergence structure and development direction of global technologies engaged in overcoming the COVID-19 pandemic by analyzing new patent applications after the COVID-19 outbreak. The findings of this study will help to establish new directions for overcoming other infectious diseases that may emerge in the future.

1. Introduction

In December 2019, following the first report of a respiratory disease caused by unknown factors in Wuhan, the capital of Hubei Province in the People’s Republic of China, a new infectious disease quickly spread worldwide. In March 2020, the World Health Organization (WHO) officially declared a global pandemic of the novel coronavirus (COVID-19) [1]. As of 12 February 2023, the cumulative number of confirmed cases worldwide was 673,602,250, with 6,779,056 deaths [1]. After the pandemic was declared, numerous variants of COVID-19, including alpha, beta, delta, and omicron, emerged, and the fatality rate decreased. In contrast, due to genetic mutations in the virus, the spread and infection rate increased compared to the initial period of the pandemic [1]. Currently, COVID-19 is transitioning from a pandemic to an endemic due to the strengthened immunity and decreased fatality rate gained through vaccination.
COVID-19 is an infectious disease. Infectious diseases are caused by toxic substances associated with a specific pathogen transmitted from an infected person to a susceptible human host. Starting with the plague in Europe in the 14th century, previous large-scale disease outbreaks included the Spanish flu, which emerged during World War I and killed approximately 50 million people, a higher mortality rate than that caused by the actual war [2]. In 1968, the Hong Kong flu, infected more than 100 million people, killing one million people in 2 years [3]. The 2009 H1N1 flu pandemic caused approximately 19,000 deaths over 3 years, which was significantly less than that of previous pandemics, possibly due to the available treatments [3]. Since the outbreak of Hong Kong flu, research has focused actively on preparing vaccines and treatments to mitigate infectious-disease pandemics [4,5,6]. Consequently, the number of deaths from the H1N1 influenza virus was drastically reduced by the treatment developed in 1996 [7]. Currently, the world is still experiencing COVID-19, which first emerged in 2019 and has been ongoing for 3 years.
Research and development of treatments for infectious diseases are difficult to sustain owing to uncertainties in transmission period demand forecasting, the number of cases, and the mortality rate [8]. Therefore, many therapeutics are insufficiently developed or lose market potential since the transmission of a particular pathogen declines even if treatments become available [9]. Although research outcomes, including patent applications, increase during pandemic or epidemic periods, they tend to decrease as infectious diseases are controlled [10]. This is why research on infectious diseases tends to be led by governments rather than private entities.
According to Lee et al. [11], “a progress of convergence innovation emerged during the COVID-19 pandemic, which involves the use of digital technology, collaborative network, and agile innovation”. During the pandemic, information technology (IT) advances have induced cooperative efforts. Researchers have drawn various technologies from the non-biotechnology sector, including sensing technology for diagnosing infectious diseases, tracking and monitoring technology for identifying the contact routes of infected persons, contactless technology for preventing infection, and system technology for remote medical consultation, in addition to traditional vaccines and treatment development. Owing to the pandemic, various technologies have quickly reached the development and application phases [11,12]. Technological cooperation between the biotechnology and nontechnology sectors was mentioned during a discussion on the Fourth Industrial Revolution (FIR) at the 2016 World Economic Forum. Artificial intelligence (AI) and robot engineering, the internet of things, autonomous vehicles, 3D printing, nanotechnology, bioengineering, material engineering, energy storage technology, and ubiquitous computing are state-of-the-art technologies that can lead to FIR. In particular, information and communications technology (ICT), which led to the third industrial revolution and physics based on digital technology, have exchanged biotechnology. This is expected to induce a new social and economic revolution, in contrast to any previous industrial revolution, through convergence and mutual exchanges [13,14].
Convergence studies are considered promising methodologies for enhancing industrial competitiveness and scientific and technological competence by pursuing innovation. As the scope of convergence gradually expands, the significance of technological convergence as a potential means of solving social problems increases [15,16,17,18]. Technology convergence occurs when different technologies are combined to create new technologies, products, or markets. Recent patent research has examined the status of technology convergence, proposed policy directions through technological discoveries, and analyzed the technology-convergence structure [19,20,21]. Although technological cooperation has occurred worldwide during the COVID-19 pandemic increasing innovative outcomes, to date, no study has analyzed these phenomena empirically. Some studies have examined COVID-19-related research and development (R&D) trends [22] or analyzed specific industries using patent information [23,24,25], as some researchers expect technology convergence to assist in overcoming the COVID-19 crisis [26,27]. However, there is no study to analyze the international collaboration regarding the patent related to COVID-19.
Therefore, the present study aims to (1) identify the technological development characteristics of each country by analyzing COVID-19-related international technology development trends and (2) identify the core technology sector and determine the structure of technology convergence, which is believed to have accelerated due to COVID-19 through basic statistics and network analyses of international COVID-19-related patents applied for or registered immediately after the pandemic. These findings are expected to assist in forecasting promising industries and determining the direction of technological advances to prepare for future pandemics.

2. Literature Review

2.1. Research Trend: The Use of Patent Information in the Biotechnology Sector, Including Infectious Diseases

The outcomes of infectious disease research are frequently published in research articles or patents if the findings have pharmaceutical potential. Typically, patents are: (1) Product patents for major medicinal substances used to treat infectious diseases, (2) composition-of-matter patents for a combination of components, including the major components, (3) formulation patents to strengthen the effects of medication, and (4) method-of-use patents covering the usage and dosage of medicinal substances, specifying which diseases are considered indications. Patent analysis is conducted since it is crucial to establish a direction when developing new vaccines or treatments, ensuring that the rights of previously applied patents are not infringed and avoiding any replication of past R&D activities. Patent information is used to analyze the past and present status of technologies and suggest the future direction of technology development to overcome the spread of infectious diseases [28,29,30].
Although there are many infectious diseases, marketability is challenging to secure since demand cannot easily be forecasted, and social interest only increases when infectious diseases are prevalent [31]. Kadam et al. [32] and Mifsud et al. [33] identified viral structures through patents and conducted technological analyses to develop vaccines that used a fraction of the viral protein and products designed to suppress viral activity. Oleksak et al. [23] analyzed patents from 2015 to 2021 to examine the structure of a specific suppressant in developing a therapeutic agent, whereas Carneiro et al. [24] inspected the trend in patents for developing antibiotics.
Noticeable progress has been made in research on epidemiology and infectious diseases since the outbreaks of severe acute respiratory syndrome (SARS) in 2003 and middle east respiratory syndrome (MERS) in 2012 [22]. Epidemiological studies are conducted when an infectious disease breaks out to promptly determine its transmission mode and prevent its spread by identifying the source of infection and the transmission process. These studies provide essential information that can be used to predict and prevent infectious disease outbreaks. Prior to the emergence of COVID-19, Magrioti et al. [25] and Rutschman [34] analyzed patents for commercialized vaccines and substances related to suppressants used to treat infectious diseases. Roberts et al. [35] analyzed the international stem-cell patent trend to develop stem-cell therapy technology. Similarly, Morita et al. [36] examined patent-application trends in the US, Japan, and Europe to develop technology related to induced pluripotent stem cells (iPS).
After the outbreak of COVID-19, Banyal et al. [37] examined the technological trend in developing epidemiologic prediction and methods of diagnosing COVID-19 using patent information. Devarapalli et al. [26], Alshrari et al. [27], and Nascimento et al. [38] performed a patent analysis to identify the structure of existing RNA vaccines and reference information on developing vaccines with escalated effects to develop an RNA vaccine for treating COVID-19. To develop a fast in vitro COVID-19 diagnostic method, Vashist [21] and Arun et al. [39] studied the latest in vitro diagnostic methods and technology convergence trends based on patent information. The past and present statuses of technologies were also analyzed to overcome the pandemic crisis, with a patent analysis performed to establish the future direction of technological development after similar or competing technologies were identified.

2.2. Research Trend: Technology Convergence Using Patent Information

According to Acs et al. [40], a “patent is a tool for measuring innovative activities”. Smith [41] introduced patent features as innovation indicators. Patents have been used as tools for measuring performance and are widely used in technology prediction, technology-status analyses, vacant technology discovery, and core technology derivation [42]. Yun et al. [43] performed a network analysis using the co-classification of patents to explore the core technologies of the companies, whereas Barragán-Ocaña et al. [44] performed a network analysis using patents to examine the status of biofuel production technology. Zanella et al. [45] identified the latest blockchain-domain trend through patent analysis. Similarly, researchers actively examined convergence phenomena between different technology sectors using patent classification and reviewed the effects of patents on innovation via data-mining techniques or network analyses of patent information.
Vaishya et al. [46] showed that the COVID-19 pandemic had promoted the convergence of various technologies, including AI heat-detection systems, crowd-computing systems, big-data analyses, contactless medical systems, blockchain, and the internet-based internet of things (IoT), to prepare for future viral infections. Hussain [46] observed that new business sectors and companies emerged during the COVID-19 pandemic through technology convergence, digital transformation, and innovation. Hau [47] reported that technology convergence was effective in overcoming COVID-19 when data on COVID-19 patients were collected and analyzed using public health information technology or virus variants were studied. Kim et al. [22] emphasized the importance of international research cooperation in overcoming the COVID-19 pandemic. Most research cooperation outcomes were contained in research articles and patents. Technology convergence at the international level played a crucial role in overcoming COVID-19.
Technology convergence analyses using patent information are generally grouped into patent citation and co-classification analyses. Patent citation analyses use patent citations and citation counts, in which citations are related to the prior art for patent applications, whereas citation counts represent the number of relevant patents cited in subsequent patents, indicating the technological impact of the patent. Co-classification of patents involves examining one patent with two or more classification codes. If numerous classification codes appear simultaneously in different patents, the relevant technological sectors are highly correlated, and technology convergence is highly possible [43,48,49,50]. However, patent citation analyses are limited, especially in recently applied patents, as citation counts can only be identified after a certain period has passed since the disclosure or registration of a patent. Therefore, this study employed a co-classification of patents.
In the biotechnology sector, including infectious diseases, patent analysis and technology convergence research are performed to investigate prior-art trends in certain sectors to promote future development, establish new patent creation strategies, analyze trends in technological advances, discover core technologies, and forecast future technologies. Most previous studies related to COVID-19 have focused on developing vaccines and treatments [51,52], patent analyses in the technology sector [26,27,38], and technology-convergence predictions to overcome the COVID-19 crisis. A few studies have examined the technology-convergence structure through network analyses by examining the occurrence of technology convergence and the technological development status of each country.

3. Materials and Methods

3.1. Data Collection

The International Patent Classification (IPC), an internationally accepted system used to collect technology data, evolved significantly after the COVID-19 outbreak. Since the initial outbreak, various terms, including coronavirus 2, SARS-CoV-2, COVID, and COVID-2019, have been used as search terms related to COVID-19. However, on 11 February 2020, the WHO officially named the disease COVID-19. Therefore, “COVID 19” was used as the search formula in this study.
To secure international COVID-19-related patents, for the patent database related to COVID-19, we first searched patents related to COVID-19 at WIPO patentscope website. We searched patents with COVID-19 again at website of USPTO (United States Patent and Trademark Office), EPO (European Patent Office), KIPO (Korean Intellectual Property Office), and JPO (Japan Patent Office) based on WIPO patentscope website offering information between 1 January 2020 and 31 December 2021. WIPO, one of the 16 specialized agencies of the United Nations (designated on 17 December 1974), leads the formation of international norms related to intellectual property rights and provides an intellectual property registration service [53]. In February 2023, 193 countries were registered as WIPO members, and disclosed patents comply with strict application criteria. Therefore, the WIPO maintains an international database of approximately 100 million patents from every country worldwide, which is widely used in patent analysis [54,55]. Figure 1 shows that of the 9306 patents initially extracted, 8880 were ultimately obtained after duplicate patents and those unrelated to COVID-19 were excluded. Since the patent cooperation treaty (PCT) patents are given 30 months from application to designation by each country, they were excluded from this study, which targeted patents applied within 2 years of the COVID-19 outbreak.
After the application process, each patent was assigned an IPC classification code. The IPC is the system used by the WIPO to classify patents. Through the systematic classification, search, distribution, and management of the patent technology sector, patent documents can be used efficiently. This classification system is widely used to analyze the structure of technology convergence since it is based on a blended function and application perspective [48,56,57]. In general, each patent is assigned one or more IPC codes, and the coding system applies a section, class, subclass, main group, and subgroup. The collected data were organized using IPC code sections and subclasses to examine the distribution of international patents in the top technology sector. The IPC code sections are categorized from A to H. Table 1 presents the technology sectors represented in each section.

3.2. Method of Analyzing International Patent Status

To understand the overall patent trends after the COVID-19 pandemic based on the status of international patents, this study used a quantitative statistical method to analyze international patent applications in the technology sector and the distribution of single and converging technologies by country. As shown in Table 2, a patent is generally assigned one or more IPC codes; patents assigned one IPC code or the same section codes and different subclasses are defined as a single technology. In contrast, patents assigned two or more IPC codes in different sections are defined as converging technologies. Furthermore, the current status of the technology sector was analyzed by focusing on IP5 patents. The IP5 was established in 2007 as a consultative body of five patent offices in the US, Korea, China, Japan, and Europe. They account for more than 80% of all patent applications worldwide.

3.3. Technology-Convergence Analysis

To overcome the COVID-19 crisis, the whole world worked to solve various problems by developing vaccines, treatments, and medical diagnostic equipment; improving the medical process; and innovating manufacturing and supply networks, which inevitably led to the incorporation of converging technologies. Based on patents related to COVID-19, a node is patent IPC code and an edge is co-occurrence. Network is used to present the relationship among nodes using links. This study performed network analysis using the co-occurrence of IPC codes to inspect the structure of technology convergence in IP5 countries. Since the patents used in this study were applied for within 2 years, it was difficult to accurately identify the citation counts. Therefore, technology convergence was analyzed using a co-classification analysis method.
The co-classification method of analysis involves measuring the frequency with which specific patent classification codes co-occur to examine the network relationships among research areas. When a patent is assigned two or more IPC codes, the IPC is referred to as a node, and a link exists between multiple IPCs that occur simultaneously for one patent. Combining the links between multiple patents within a group makes it possible to draw a network among IPCs. Many IPC codes co-occurring in the two technology sectors indicate an exchange between the two fields and a high possibility of convergence [12,47,48].
The centrality indicator shows the IPCs with the greatest impact within a network. The three types of centrality are degree, betweenness, and closeness. The concept of degree centrality focuses on the degree of connection to nodes, with those with more links positioned toward the center of a network having a significant impact [58,59]. This study applied weighted degree centrality to the accumulated frequency of connections between nodes by assigning weights to the nodes and connections between nodes. Betweenness centrality, which mediates between nodes with fewer links, is particularly useful for finding a mediator, whereas closeness centrality is used to find elements that facilitate spread propagation.
Gephi open-source software (v0.9.2) was used for network analysis and visualization. Major IPCs were confirmed based on the degree, betweenness, and closeness centralities of the nodes. Degree centrality is a measure of the number of other nodes to which a node is directly connected, betweenness centrality is a measure of how well a node is connected to other nodes, and closeness centrality is a measurement of how short the distance is from one node to others. The connection or convergence structure between the technology sectors within the network was then identified to analyze the technology-convergence structure by country. The details are shown in Figure 2.

4. Results

4.1. International Patent Status Analysis Results

In 21 countries, 8880 COVID-19-related patent applications were submitted. Table 3 presents the status of each country. IP5 countries filed 8610 patent applications, accounting for 97% of the total applications. According to statistics provided by the WIPO in 2021, patent applications from IP5 countries accounted for approximately 85%. COVID-19-related patents are focused on IP5. This study categorized various technologies using the IPC codes of COVID-19-related patents, making it possible to examine the composition of single and converging technologies. A patent assigned to one or multiple IPCs from the same section was defined as a single technology. However, if a patent was assigned to two or more IPCs from different sections, it was defined as a converging technology. A higher proportion of single technologies than converging technologies in each location was observed. Among the IP5 countries, the US, Japan, and Europe had a higher proportion of single technologies than converging technologies. In contrast, Korea and China had a higher proportion of converging technologies than single technologies [60]. Among the IP5 countries, China had the highest rate of technology convergence.
Since COVID-19 was used as the search formula, Section A, which denotes human necessities and is closely associated with everyday life, had the highest rank. The section analysis results for each location showed that Section A accounted for the highest proportion in all countries, and Section A, followed by Sections G and C, were the top three technology sectors. Since Section A represents human necessities, most COVID-19-related patents were closely related to everyday human lives. Section G was associated with physics, and Section C with chemistry and metallurgy, accounting for the second and third highest proportions, respectively. As shown in Figure 3, all IP5 countries exhibited similar technology distribution patterns.
Patent section codes were divided into single and converging technologies to examine the distribution of technology sectors in the IP5 countries. As shown in Figure 4A,B, this study compared the single and converging technology sectors in each location and between countries. In the US, a noticeable increase was observed in Section B, which covers operations and transportation, and Section H, which covers electricity concerning converging technology. In Korea, a decrease was observed in Sections G (physics) and A (human necessities) with respect to converging technology. An increase in Sections H (electricity) and B (operations and transportation) was observed. In China, a remarkable increase in converging technologies was observed in Section C (chemistry), indicating that chemistry-related patents were frequently associated with converging technologies. Compared with other countries, Japan dominated Section F (mechanical engineering) and Europe Section B (operations and transportation). Overall, Sections A and G contained the highest level of single technology; Section A had a significantly reduced level of converging technology, and Sections B, C, D, E, F, G, and H had an increase in converging technology.

4.2. Patent Characteristics of IP5 Countries

The technology sectors of the US patent applications were examined since the US is the most important research partner in the world from the perspective of international research collaborations [22], with the highest number of patent applications among the IP5 countries. As shown in Table 4, the US patents comprised 42% of Section A (human necessities) and 26% of Section G (physics), a higher percentage than in any other location.
Regarding detailed technology sectors, Sections A and C were associated with vaccines and treatments, whereas Section G was associated with health-state monitoring, COVID-19 diagnostic, and data-analysis technologies. Moreover, 81% of US patents were applied for by US citizens, and only 2% of the patent applications were submitted by citizens of two or more countries. In contrast to papers considering joint research, patent applications are less likely to feature work collaborations due to commercial interests. A few non-US COVID-19-related patents were jointly applied by multiple parties. As for the nationality of COVID-19-related patent applicants, Canada, India, China, the UK, Switzerland, and Australia were the countries with the most citizens collaborating with US citizens on patent applications, respectively. The US and Canada jointly applied for patents in the disinfection, disease control, and ICT sectors, while the US and India jointly applied for patents on methods for treating infections. The US and China have jointly applied for patents related to sterilization and shielding technologies.
As Korea was introduced through the Organization for Economic Co-operation and Development (OECD) for its exemplary response to COVID-19, it used its government-initiated 3T (testing, tracing, and treatment with isolation) strategy. Fast and innovative digital technologies included notifying people of their polymerase chain reaction (PCR) test results within 48 h, drive-thru testing, an isolation system that incorporated life-treatment centers, a system for tracking infected people using card-usage history and mobile phone location tracking, and access control using QR codes, mask applications, and vaccine appointment applications. These measures resulted in a lower mortality rate in Korea than in other countries. COVID-19-related data were comprehensively integrated, eventually called “K-Quarantine” [60,61,62]. When Korean patents were closely examined, 23% involved the 3Ts, the second highest category after the vaccine and treatment-related technologies. Sterilization and disinfection technologies, which attracted many patent applications during the early days of the pandemic, accounted for 19%, followed by mask-related technologies at 12%.
Most Chinese patents involved vaccines as the government initiated vaccine development. Other patents were related to diagnosis, acupuncture technology, and COVID-19 data processing and analysis using deep learning. In Japan, 26% of patents involved sterilization, disinfection, or air purification technologies, the category with the highest ranking, followed by masks (16%), vaccines and treatment technologies (12%), and isolation-related technologies (10%). Japan had a higher percentage of sterilization, disinfection, and air purification technology and a lower percentage of vaccine, treatment, and diagnostic technology than Korea. Moreover, Japan had a lower proportion of patents related to vaccines and treatments than the other IP5 countries. The strong emphasis on technologies related to sterilization, disinfection, air purification, and masks, which accounted for 42% of the total patent applications, can be traced back to the Japanese government’s COVID-19 policy and response. The 2020 Summer Olympics and Paralympics were held in Tokyo in July 2020; therefore, the Japanese government restricted the test and diagnosis of COVID-19. As the identities and contact tracing of infected people remained confidential, compliance with quarantine guidelines became a critical factor in preventing the spread of COVID-19 infection [63]. Given this background, Japan has applied for more patents related to personal disease control, disinfection, and mask-related technologies than the other IP5 countries.
As an economic community comprising multiple member countries, Europe’s most prominent unity-related policy is free movement across borders. However, based on the prior experience of the fatal plague outbreak in the 14th century, Europe limited cross-border movements to overcome the COVID-19 crisis. National borders were closed, although the disease control policies of individual countries still guaranteed a minimal level of freedom in daily life [64]. For this reason, European patents were evenly distributed between new vaccines and treatment technologies, drug repositioning technologies designed to use existing medications to treat COVID-19, in vitro diagnostic technologies, and monitoring and forecasting technologies using ICT. Notably, there is a patent involving an aircraft for a method of collecting samples from an aircraft cabin.
Patent information is used to analyze the current technological situation when establishing the direction of technological development. Table 5 shows the vaccine- and treatment-related patents registered by well-known companies, including Pfizer (New York, NY, USA), Moderna (Cambridge, MA, USA), AstraZeneca (Cambridge, UK), Janssen (Beerse, Belgium), and Novavax (Gaithersburg, MD, USA). The patents were assembled to identify the characteristics of patented COVID-19-related vaccines and treatments for other infectious diseases that could emerge in the future, with 72% of patents originating in the US and most related to vaccine and treatment technologies as converging technology rather than single technologies.
Since the use of ICT and digital technology increased significantly during the COVID-19 pandemic, and these industries were seen as important in overcoming the crisis, the present study investigated which of the top 20 global IT companies applied for COVID-19-related patents. The results showed that eleven COVID-19-related patent applications were submitted by four of the top 20 global IT companies: Apple (Cupertino, CA, USA), Microsoft (Redmond, WA, USA), Samsung Electronics (Suwon, Republic of Korea), and Facebook (Menlo Park, CA, USA) (Table 6). Samsung Electronics applied seven patents that were mostly single technologies. Their patents are sections G, H, and A in the ICT and digital technology sectors. Rather than focusing on smartphone-based technology, Samsung Electronics applied for patents in the infectious diseases field for its flagship products. Microsoft’s technology was established to improve the productivity of remote work processes, such as contactless or telecommuting work, which increased dramatically during the pandemic. Facebook developed predictable cryptography technology, whereas Apple developed iPhone technology for portable temperature detection.

4.3. Characteristics of Converged COVID-19-Related Patents

Products or services in which various technologies converged were expected to emerge during the efforts to overcome the COVID-19 crisis [11,12]. Therefore, a network analysis of converging technology in COVID-19-related patents was conducted to identify the major technology sectors and technology-convergence structure.

4.3.1. Network-Centrality Analysis Results

To analyze the characteristics of IP5 converged patents, a network analysis was conducted to determine the weighted degree, betweenness, and closeness centralities using the subclasses of IPC codes. In network analysis, a high weighted-degree centrality value toward a node indicated a high level of influence within the network. Table 7 lists the most influential technology sectors in each location.
Regarding influence, A61K was associated with pharmaceuticals, dental and cosmetic compounds, and natural extracts, including antibodies and cells. A61K was the most influential in the US and Europe. Associated with amino acids, peptides, and interferon technology, C07K was the most influential in Korea and China. A61L, the most influential in Japan, was associated with sterilization, disinfection, and deodorization technologies. Therefore, vaccines, treatment, and diagnosis technologies played a central role in converged patents in the US, Korea, China, and Europe. In contrast, disinfection and sterilization technologies played a central role in Japan. Several technologies in Section G, including G16H (healthcare informatics), G01N (material-analysis technology), G06F (electrical digital data-processing technology), and G06Q (data-processing system technology), were the most influential nodes in the US.
For each country, betweenness and closeness centralities were analyzed to identify the sectors that mediated and spread convergence in the cases where technology convergence occurred in less influential technology sectors (Table 8). A high betweenness centrality indicated that the node was a mediator in the network. In contrast, a high closeness centrality node is the most connecting or communicating via other nodes.
Among the American, Korean, Japanese, and European patents, the A61L (air purification technology) was the link between other technologies. In contrast, among Chinese patents, G01N (measuring or testing technology involving enzymes and microorganisms) was the link between other technologies. Among the American, Korean, Chinese, Japanese, and European patents, the C04B (cement and ceramics), C22C (alloys), F16K (valves), B01L (chemical or physical laboratory apparatus), and A45D (heating technology), respectively, is high closeness centrality, which promoted the spread of convergence.
Accordingly, A61L has high degree of betweenness centrality during technology convergence in most countries, except for China, owing to the nature of COVID-19, an airborne respiratory infectious disease. Technologies that promoted the propagation of convergence varied by location.

4.3.2. The Technology-Convergence Structure of IP5 Countries

The COVID-19 pandemic fostered convergence among different technology sectors through collaboration with diverse technologies in the non-biotechnology sector, including diagnostic sensing technology, technology for tracking and monitoring infected persons, contactless technology for infection prevention, and IT for remote medical consultations, in addition to traditional vaccines and treatment development [12,46,47]. This study examined technology sectors with high rates of interactions through a co-occurrence analysis of converged COVID-19-related patents in different sections. To identify the detailed technology sectors, patents consisting of different sections were extracted and then analyzed using the lower subclass classification level. The top three technology sectors that exchanged most actively with other sectors of IP5 countries are shown in Table 9.
The network of converged US patents is shown in Figure 5. The size of each node represents its influence, with thicker lines between nodes indicating higher levels of interactions. The node sizes of the top five IPCs vary depending on their influence. The connection was the thickest between C07K (vaccine and treatment technologies involving amino acids, peptides, and interferons) and A61K, revealing the highest level of interaction between these two sectors. The sectors with the second highest levels of interaction were enzymes, microorganisms, and preparations for medical purposes. The sectors with the third-highest levels of interactions were healthcare informatics and diagnosis. In contrast to patents in other countries, G16H (handling or processing medical or healthcare data) and A61B (diagnosis and identification technology) had high levels of influence and actively converged.
The top three technology sectors with active interactions in Korea and China were associated with vaccine and treatment development. However, they ranked differently in each country. In contrast to other countries, Japan had a high level of interaction between sectors associated with air purification technology (A61L-F24F). In Europe, the technology sectors associated with vaccines and treatments also had active interactions. Notably, even when patents with different sections were classified as converged patents, convergence was observed in the same sections (e.g., A61K-A61P and C07K-C12N), which can be attributed to the fact that subclasses were used to examine detailed technology sectors. For patents B and D, which comprised sections A and G, respectively, the subclasses of patent B were A61K, A61P, A61L, and G16H, whereas those of patent D were A61K, A61P, and G16H. Owing to the patent IPC composition, A61K and A61P co-occurred in other converged patents and were thus included in technology sectors with active interactions.

5. Discussion

The period between the emergence of COVID-19 and the declaration of the pandemic was 4 months. In response to COVID-19, which was spreading rapidly, every country worldwide used various measures to prevent COVID-19 transmission, including strict lockdowns, social distancing, infection reduction through strengthened disease-control systems [60,61,62,63,64] and therapeutics and vaccine developments [65,66,67,68,69]. Therefore, this study aimed to identify the structure of technology convergence and the presence of interactions between different technology sectors involved in overcoming the pandemic crisis by examining trends in international technological development over the 2 years since the COVID-19 outbreak.
Therefore, the present study collected and analyzed 8880 international COVID-19-related patent applications submitted between January 2020 and December 2021. The results showed that 97% of COVID-19-related patent applications were submitted by IP5 countries, with American patents accounting for 55.6%, followed by Korean patents at 19.4%. Section A, which accounted for a large proportion of single-technology patents, decreased significantly compared to converged patents. In contrast, Sections B, C, D, F, and H in converged patents showed increased diversity in technology sectors. The US, Korea, and Europe had a similar distribution of convergence technology, while China exhibited a particularly sharp increase in Section C (chemistry in convergence technology) owing to the Chinese government’s vaccine and treatment-development policy. Compared with other countries, Japan had the highest proportion of Section F patents (isolation technology), proving that the Japanese government’s disease control policy, focusing on isolation and personal disease control measures and hygiene, eventually affected the relevant patents.
Although wearing masks is one of the most effective ways to prevent the spread of COVID-19 [70,71], fewer people wore masks in Western than Eastern countries. The proportion of COVID-19-related patents involving masks used for personal disease control was only 6% in the US and even lower in Europe and Russia. In contrast, in Asia, 16%, 12%, and 6% of the patent applications submitted by Japan, Korea, and China, respectively, were mask-related, a higher percentage than those in other countries. According to Biddlestone et al. [70] and Kang et al. [71], people in Eastern countries were more willing to wear masks than those in Western countries, and people in Western cultures were more likely to refuse to adopt disease control measures that limit their personal freedom than those in Eastern cultures. These phenomena were also observed in patent applications.
Alongside the IP5 countries, Russia, Australia, and Taiwan have submitted many patent applications. Most Russian patents reflected a government-led policy that concentrated on vaccine development, similar to China. Although Australia submitted more Section G (physics) patent applications than other countries, most were related to a COVID-19 detection and screening system based on AI and deep learning technologies rather than physics technology related to virus detection or diagnosis. Among Taiwanese patents associated with vaccines and treatment technology, only 9% of applicants were Taiwanese citizens; the remaining 91% were applicants from the US, China, Germany, the Netherlands, and corporations. Taiwan is highly dependent on foreign technologies rather than in-house technology development. Overseas companies applied for patents in Taiwan to secure the market.
Technological convergence is one way to overcome the COVID-19 pandemic. The sectors with the greatest impact on technology convergence were A61K (preparation for medical purposes), C07K (peptides), and A61L (air purification), which may reflect the traditional vaccine and treatment technology development and the characteristics of COVID-19 as an infectious respiratory disease.
The technology convergence of the IP5 countries was particularly active between A61K, A61P, C07K, C12N, G16H, A61B, and F24F, which are related to public health care and digital technology. Convergence occurred between different technology sectors in the non-biotechnology sector, including diagnostic sensing technology, technology for tracking and monitoring infected persons, contactless technology for infection prevention, and IT for remote medical consultation, in addition to traditional vaccine and treatment development. Governments typically initiate research on infectious diseases, and research funds and disease control policies affect patents.
Our results indicate that patents are frequently used to analyze technological trends. However, previous analyses of patent information in the biotechnology sector are limited by their focus on specific or company-owned technologies for technological development. Although several attempts have been made to overcome these limitations using patent citation index or research articles, qualitative research focused on technicality has been ineffective in identifying the structure and core sectors of technologies.
The significance of this study is as follows: First, technological characteristics were identified through network and basic statistics of COVID-19-related patents worldwide. In contrast, previous studies simply focused on specific research fields or industry- or company-owned patents [23,24,25,34,35,36]. Therefore, basic data have been established to objectively confirm COVID-19-related technology trends. Second, this study conducted an empirical network analysis based on a co-classification analysis of the structure and occurrence of convergence between technologies in various sectors. Then, the technology convergence trends caused by COVID-19, including the influential technology sectors in each country and the major technology sectors experiencing convergence, were identified. Further research on trends will help in establishing a strategy for predicting new industries that are likely to emerge due to technology convergence. Third, this study provided basic data that can be used to establish international policies to respond to future infectious disease outbreaks. Patents related to infectious diseases are likely to correlate with national disease control policies due to the nature of government-initiated development processes. Based on technological trends that emerged during the COVID-19 pandemic, our results are expected to contribute to shaping the direction of effective response strategies by establishing research and government response policies to combat future infectious disease outbreaks.

6. Conclusions

Since patents are disclosed 18 months after being applied, the present moment, 2 years after the COVID-19 pandemic outbreak, is the most important period for researchers to analyze the flow of global technological development that emerged in response to the pandemic. This study investigated the characteristics of technology convergence in each country by analyzing international patent applications designed to overcome COVID-19. This study also confirmed the correlation between national pandemic policies and patents and examined the interaction between technology sectors related to the Fourth Industrial Revolution. The empirical results obtained by analyzing COVID-19-related patents can be used to analyze fast-changing global technology and market environments and explain the industrial fields derived from them. Despite its significance, this study has limitations since it only considered patent applications submitted after the COVID-19 outbreak rather than comparing patent applications submitted before and after the outbreak. In addition, the use of various indicators, such as the patent citation index, to analyze technology convergence is limited since recent patent applications are the subject of analysis. Future research addressing these limitations will help to overcome future infectious disease outbreaks.

Author Contributions

Conceptualization, E.J., K.K. and K.C.; methodology, E.J. and K.K.; software, E.J. and H.P.; validation, E.J.; formal analysis, E.J. and H.P.; writing—original draft preparation, E.J.; writing—review and editing, E.J., K.K. and K.C.; and supervision, K.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. WHO. WHO Coronavirus (COVID-19). Available online: https://www.who.int/emergencies/overview (accessed on 15 April 2023).
  2. Erkoreka, A. Origins of the Spanish Influenza pandemic (1918–1920) and its relation to the First World War. J. Mol. Genet. Med. Int. J. Biomed. Res. 2009, 3, 190. [Google Scholar]
  3. Dalekou, S.; Michaleas, S.N.; Tsitsika, A.K.; Karamanou, M. Comparative study of pandemics and their impact on children and adolescents: COVID-19 and Spanish Flu. Le Infez. Med. 2023, 31, 131. [Google Scholar]
  4. Wood, J.M. Developing vaccines against pandemic influenza. Philos. Trans. R. Soc. Lond. Ser. B 2001, 356, 1953. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Webby, R.J.; Perez, D.R.; Coleman, J.S.; Guan, Y.; Knight, J.H.; Govorkova, E.A.; McClain-Moss, L.R.; Peiris, J.S.; Rehg, J.E.; Tuomanen, E.I.; et al. Responsiveness to a pandemic alert: Use of reverse genetics for rapid development of influenza vaccines. Lancet 2004, 363, 1099–1103. [Google Scholar] [CrossRef] [PubMed]
  6. Memoli, M.J.; Morens, D.M.; Taubenberger, J.K. Pandemic and seasonal influenza: Therapeutic challenges. Drug Discov. Today 2008, 13, 590–595. [Google Scholar] [CrossRef] [Green Version]
  7. Laver, G. Antiviral drugs for influenza: Tamiflu® past, present and future. In Future Virology; Future Medicine Ltd.: London, UK, 2006. [Google Scholar] [CrossRef]
  8. Kaufmann, S.H.; McElrath, M.J.; Lewis, D.J.; Del Giudice, G. Challenges and responses in human vaccine development. Curr. Opin. Immunol. 2014, 28, 18–26. [Google Scholar] [CrossRef] [Green Version]
  9. Oyston, P.; Robinson, K. The current challenges for vaccine development. J. Med. Microbiol. 2012, 61, 889–894. [Google Scholar] [CrossRef]
  10. Boltz, D.A.; Aldridge, J.R.; Webster, R.G.; Govorkova, E.A. Drugs in development for influenza. Drugs 2010, 70, 1349–1362. [Google Scholar] [CrossRef] [Green Version]
  11. Lee, S.M.; Trimi, S. Convergence innovation in the digital age and in the COVID-19 pandemic crisis. J. Bus. Res. 2021, 123, 14–22. [Google Scholar] [CrossRef]
  12. Hussain, Z. Paradigm of technological convergence and digital transformation: The challenges of CH sectors in the global COVID-19 pandemic and commencing resilience-based structure for the post-COVID-19 era. Digit. Appl. Archaeol. Cult. Herit. 2021, 21, e00182. [Google Scholar] [CrossRef]
  13. Prisecaru, P. Challenges of the Fourth Industrial Revolution. Knowl. Horiz. Econ. 2016, 8, 57–62. [Google Scholar]
  14. Davis, N. What is the Fourth Industrial Revolution; World Economic Forum: Davos-Klosters, Switzerland, 2016; p. 19. [Google Scholar]
  15. Kodama, F. Technology fusion and the new R & D: Harv. Bus. Rev. 1992, 70, 70–78. [Google Scholar]
  16. Noh, Y.; Park, M.; Lee, K.H. A Study of Relationship between Research Outcome and Policy Decision Making: For invigoration of Convergence Research. J. Korea Contents Assoc. 2020, 20, 43–55. [Google Scholar]
  17. Lee, H.M.; Kim, S.J.; Kim, H.Y. The Analysis Methods Based on Patent Citation Networks for the Convergence Technologies Development Planning: A Case of Smart Factory′s ICT Technologies. J. Korea Acad. Ind. Coop. Soc. 2018, 19, 34–47. [Google Scholar]
  18. Kwon, Y.E.; Kim, J. Analysis of national R&D patent performance network in bio-healthcare sector. J. Korea Converg. Soc. 2018, 9, 17–24. [Google Scholar]
  19. Park, H.; Yoon, J. Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: The case of Korean national R&D. Scientometrics 2014, 98, 853–890. [Google Scholar]
  20. Park, S.H.; Yun, Y.M.; Kim, H.Y.; Kim, J.S. Technology Convergence & Trend Analysis of Biohealth Industry in 5 Countries: Using patent co-classification analysis and text mining. J. Korea Converg. Soc. 2021, 12, 9–21. [Google Scholar]
  21. Vashist, S.K. In vitro diagnostic assays for COVID-19: Recent advances and emerging trends. Diagnostics 2020, 10, 202. [Google Scholar] [CrossRef] [Green Version]
  22. Kim, K.; Cho, K.T. A Review of Global Collaboration on COVID-19 Research during the Pandemic in 2020. Sustainability 2021, 13, 7618. [Google Scholar] [CrossRef]
  23. Oleksak, P.; Nepovimova, E.; Chrienova, Z.; Musilek, K.; Patocka, J.; Kuca, K. Contemporary mTOR inhibitor scaffolds to diseases breakdown: A patent review (2015–2021). Eur. J. Med. Chem. 2022, 238, 114498. [Google Scholar] [CrossRef]
  24. Carneiro, D.C.; Fernandez, L.G.; Monteiro-Cunha, J.P.; Benevides, R.G.; Cunha Lima, S.T. A patent review of the antimicrobial applications of lectins: Perspectives on therapy of infectious diseases. J. Appl. Microbiol. 2022, 132, 841–854. [Google Scholar] [CrossRef] [PubMed]
  25. Magrioti, V.; Kokotos, G. Phospholipase A2 inhibitors for the treatment of inflammatory diseases: A patent review (2010–present). Expert Opin. Ther. Pat. 2013, 23, 333–344. [Google Scholar] [CrossRef] [PubMed]
  26. Devarapalli, P.; Kumari, P.; Soni, S.; Mishra, V.; Yadav, S. Patent intelligence of RNA viruses: Implications for combating emerging and re-emerging RNA virus based infectious diseases. Int. J. Biol. Macromol. 2022, 219, 1208–1215. [Google Scholar] [CrossRef] [PubMed]
  27. Alshrari, A.S.; Hudu, S.A.; Imran, M.; Asdaq, S.M.B.; Ali, A.M.; Rabbani, S.I. Innovations and development of COVID-19 vaccines: A patent review. J. Infect. Public Health 2022, 15, 123–131. [Google Scholar] [CrossRef]
  28. Ko, Y. An economic analysis of biotechnology patent protection. Yale LJ 1992, 102, 777. [Google Scholar] [CrossRef]
  29. Berks, A.H. Patent information in biotechnology. Trends Biotechnol. 1994, 12, 352–364. [Google Scholar] [CrossRef]
  30. Thumm, N. Strategic patenting in biotechnology. Technol. Anal. Strateg. Manag. 2004, 16, 529–538. [Google Scholar] [CrossRef]
  31. Liu, C.; Zhou, Q.; Li, Y.; Garner, L.V.; Watkins, S.P.; Carter, L.J.; Smoot, J.; Gregg, A.C.; Daniels, A.D.; Jervey, S.; et al. Research and Development on Therapeutic Agents and Vaccines for COVID-19 and Related Human Coronavirus Diseases. ACS Cent. Sci. 2020, 6, 315–331. [Google Scholar] [CrossRef]
  32. Kadam, R.U.; Wilson, I.A. Structural basis of influenza virus fusion inhibition by the antiviral drug Arbidol. Proc. Natl. Acad. Sci. USA 2017, 114, 206–214. [Google Scholar] [CrossRef]
  33. Mifsud, E.J.; Hayden, F.G.; Hurt, A.C. Antivirals targeting the polymerase complex of influenza viruses. Antivir. Res. 2019, 169, 104545. [Google Scholar] [CrossRef]
  34. Rutschman, A.S. The intellectual property of vaccines: Takeaways from recent infectious disease outbreaks. Mich. Law Rev. Online 2019, 118, 170. [Google Scholar] [CrossRef]
  35. Roberts, M.; Wall, I.B.; Bingham, I.; Icely, D.; Reeve, B.; Bure, K.; Brindley, D.A. The global intellectual property landscape of induced pluripotent stem cell technologies. Nat. Biotechnol. 2014, 32, 742–748. [Google Scholar] [CrossRef]
  36. Morita, Y.; Okura, H.; Matsuyama, A. Patent application trends of induced pluripotent stem cell technologies in the United States, Japanese, and European Applications. BioRes. Open Access 2019, 8, 45–58. [Google Scholar] [CrossRef] [PubMed]
  37. Banyal, S.; Dwivedi, R.; Gupta, K.D.; Sharma, D.K.; Al-Turjman, F.; Mostarda, L. Technology Landscape for Epidemiological Prediction and Diagnosis of COVID-19. Comput. Mater. Contin. 2021, 67, 1679–1696. [Google Scholar] [CrossRef]
  38. Nascimento Junior, J.A.C.; Santos, A.M.; Oliveira, A.M.S.; Guimarães, A.G.; Quintans-Júnior, L.J.; Coutinho, H.D.M.; Serafini, M.R. Trends in MERS-CoV, SARS-CoV, and SARS-CoV-2 (COVID-19) diagnosis strategies: A patent review. Front. Public Health 2020, 8, 563095. [Google Scholar] [CrossRef] [PubMed]
  39. Arun, K.; Rhema, E.T.; Sukumaran, A.; Paul, J.K.; Vasudevan, D.M. COVID-19: Current trends in invitro diagnostics. Indian J. Clin. Biochem. 2020, 35, 285–289. [Google Scholar]
  40. Acs, Z.J.; Audretsch, D.B. Patents as a Measure of Innovative Activity. Kyklos 1989, 42, 171–180. [Google Scholar] [CrossRef]
  41. Smith, K. Measuring Innovation. In The Oxford Handbook of Innovation; Fagerberg, J., Mowery, D.C., Nelson, R.R., Eds.; Oxford University Press: Oxford, UK, 2005; pp. 148–177. [Google Scholar] [CrossRef] [Green Version]
  42. Jeong, S.; Kim, J.C.; Choi, J.Y. Technology convergence: What developmental stage are we in? Scientometrics 2015, 104, 841–871. [Google Scholar] [CrossRef]
  43. Yun, N.; Ji, I. An Analysis of Patent Co-Classification Network for Exploring Core Technologies of Firms: An Application to the Foldable Display Sector. J. Korea Acad. Ind. Coop. Soc. 2019, 20, 382–390. [Google Scholar]
  44. Barragán-Ocaña, A.; Merritt, H.; Sánchez-Estrada, O.E.; Méndez-Becerril, J.L.; del Pilar Longar-Blanco, M. Biorefinery and sustainability for the production of biofuels and value-added products: A trends analysis based on network and patent analysis. PLoS ONE 2023, 18, e0279659. [Google Scholar] [CrossRef]
  45. Zanella, G.; Liu, C.Z.; Choo, K.K.R. Understanding the trends in blockchain domain through an unsupervised systematic patent analysis. IEEE Trans. Eng. Manag. 2021, 70, 1991–2005. [Google Scholar] [CrossRef]
  46. Vaishya, R.; Haleem, A.; Vaish, A.; Javaid, M. Emerging technologies to combat the COVID-19 pandemic. J. Clin. Exp. Hepatol. 2020, 10, 409–411. [Google Scholar] [CrossRef]
  47. Hau, Y.S.; Chang, M.C. Healthcare information technology convergence to effectively cope with the COVID-19 crisis. Health Policy Technol. 2021, 10, 27. [Google Scholar] [CrossRef] [PubMed]
  48. Kim, G.; Bae, J. A novel approach to forecast promising technology through patent analysis. Technol. Forecast. Soc. Change 2017, 117, 228–237. [Google Scholar] [CrossRef]
  49. Choi, J.Y.; Jeong, S.; Kim, K. A study on diffusion pattern of technology convergence: Patent analysis for Korea. Sustainability 2015, 7, 11546–11569. [Google Scholar] [CrossRef] [Green Version]
  50. Choi, J.Y.; Jeong, S.; Jung, J.K. Evolution of technology convergence networks in Korea: Characteristics of temporal changes in R&D according to institution type. PLoS ONE 2018, 13, e0192195. [Google Scholar]
  51. Hafeez, A.; Ahmad, S.; Siddqui, S.A.; Ahmad, M.; Mishra, S. A review of COVID-19 (Coronavirus Disease-2019) diagnosis, treatments and prevention. EJMO 2020, 4, 116–125. [Google Scholar]
  52. Le, T.T.; Andreadakis, Z.; Kumar, A.; Román, R.G.; Tollefsen, S.; Saville, M.; Mayhew, S. The COVID-19 vaccine development landscape. Nat. Rev. Drug Discov. 2020, 19, 305–306. [Google Scholar] [CrossRef]
  53. WIPO. World Intellectual Property Organization. Available online: https://www.wipo.int/about-wipo/en/ (accessed on 19 April 2023).
  54. WIPO. Patentscope. Search International and National Patent Collections. 2021. Available online: https://patentscope.wipo.int/search/en/advancedSearch.jsf/ (accessed on 19 April 2023).
  55. WIPO. International Patent Classification (IPC). 2021. Available online: https://www.wipo.int/classifications/ipc/en/ (accessed on 19 April 2023).
  56. Hwang, I. The effect of collaborative innovation on ICT-based technological convergence: A patent-based analysis. PLoS ONE 2020, 15, e0228616. [Google Scholar] [CrossRef] [Green Version]
  57. Jun, S. IPC Code Analysis of Patent Documents Using Association Rules and Maps–Patent Analysis of Database Technology. In Database Theory and Application, Bio-Science and Bio-Technology; Springer: Berlin/Heidelberg, Germany, 2011; pp. 21–30. [Google Scholar]
  58. Tijssen, R.J. A quantitative assessment of interdisciplinary structures in science and technology: Co-classification analysis of energy research. Res. Policy 1992, 21, 27–44. [Google Scholar] [CrossRef]
  59. Xing, W.; Ye, X.; Kui, L. Measuring convergence of China’s ICT industry: An input–output analysis. Telecommun. Policy 2011, 35, 301–313. [Google Scholar] [CrossRef]
  60. Balilla, J. Assessment of COVID-19 mass testing: The Case of South Korea (18 March 2020). Available online: https://ssrn.com/abstract=3556346 (accessed on 14 June 2023).
  61. Shaw, R.; Kim, Y.K.; Hua, J. Governance, technology and citizen behavior in pandemic: Lessons from COVID-19 in East Asia. Prog. Disaster Sci. 2020, 6, 100090. [Google Scholar] [CrossRef] [PubMed]
  62. Her, M. How is COVID-19 affecting South Korea? What is our current strategy. Disaster Med. Public Health Prep. 2020, 14, 684–686. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Gallego, V.; Nishiura, H.; Sah, R.; Rodriguez-Morales, A.J. The COVID-19 outbreak and implications for the Tokyo 2020 Summer Olympic Games. Travel Med. Infect. Dis. 2020, 34, 101604. [Google Scholar] [CrossRef]
  64. Krastev, I.; Leonord, M. Europe’s invisible divides: How COVID-19 is polarising European politics. JSTOR 2021. Available online: https://www.jstor.org/stable/resrep36091 (accessed on 14 June 2023).
  65. Washington Post. The Health 202: A Fight over Vaccine Affordability Threatened the Coronavirus Spending Package. Available online: https://www.washingtonpost.com/news/powerpost/paloma/the-health-202/2020/03/05/the-health-202-a-fight-over-vaccine-affordability-threatened-the-coronavirus-spending-package/5e6004cd602ff10d49ac2aca/ (accessed on 23 April 2023).
  66. NIH. Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV). Available online: https://www.nih.gov/research-training/medical-research-initiatives/activ (accessed on 15 April 2023).
  67. NIH. Promising Interim Results from Clinical Trial of NIH-Moderna COVID-19 Vaccine. Available online: https://www.nih.gov/news-events/news-releases/promising-interim-results-clinical-trial-nih-moderna-covid-19-vaccine (accessed on 15 April 2023).
  68. Science Business. Commission Changes Horizon Work Programme to Reflect Its Global Coronavirus R&D Pledge. Available online: https://sciencebusiness.net/covid-19/news/commission-changes-horizon-work-programme-reflect-its-global-coronavirus-rd-pledge (accessed on 15 April 2023).
  69. Der Spiegel. Corona-Virus. Wenn die Globalisierung zur Tödlichen Gefahr Wird. Available online: www.spiegel.de/spiegel/print/index-2020-6.html (accessed on 15 April 2023).
  70. Biddlestone, M.; Green, R.; Douglas, K.M. Cultural orientation, power, belief in conspiracy theories, and intentions to reduce the spread of COVID-19. Br. J. Soc. Psychol. 2020, 59, 663–673. [Google Scholar] [CrossRef]
  71. Kang, M.H.; Jeong, C.; Na, J. COVID-19 and face masks: East-west cultural differences in wearing face masks in public. Korean J. Soc. Pers. Psychol. 2021, 35, 77–103. [Google Scholar]
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Figure 1. Research framework.
Figure 1. Research framework.
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Figure 2. Research framework.
Figure 2. Research framework.
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Figure 3. Technology distribution of international COVID−19 related patents from IP5 countries. Section A–H explanation refers to Table 1.
Figure 3. Technology distribution of international COVID−19 related patents from IP5 countries. Section A–H explanation refers to Table 1.
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Figure 4. Section distribution of single (A) and converging (B) technology patents by countries.
Figure 4. Section distribution of single (A) and converging (B) technology patents by countries.
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Figure 5. US converged patent network.
Figure 5. US converged patent network.
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Table 1. Technological field definitions of the IPC code sections.
Table 1. Technological field definitions of the IPC code sections.
IPC Code (Section)Technological Field Description
AHuman Necessities
BPerforming Operations; Transporting
CChemistry; Metallurgy
DTextiles; Paper
EFixed Constructions
FMechanical Engineering; Lighting;
Heating; Weapons; Blasting
GPhysics
HElectricity
Table 2. Examples of single and converging technologies.
Table 2. Examples of single and converging technologies.
CategoryIPC Code Classification
SectionSubclass
Single technologyAA61K
AA61K, A45B
Converging technologiesA, GA61K, GO1N
Table 3. Status of international patent applications related to COVID-19.
Table 3. Status of international patent applications related to COVID-19.
CountryNo. of Patents (%)Single
/Converging		CountryNo. of Patents (%)Single
/Converging
US4937 (55.6%)64%/36%Israel6 (0.1%)40%/60%
Korea1721 (19.4%)49%/51%Spain4 (0.0%)100%/0%
China683 (7.7%)28%/72%Poland4 (0.0%)75%/25%
Japan663 (7.5%)69%/31%Eurasian3 (0.0%)100%/0%
Europe606 (6.8%)67%/33%France2 (0.0%)100%/0%
Russia78 (0.9%)55%/45%Slovenia2 (0.0%)50%/50%
Australia73 (0.8%)48%/52%Denmark1 (0.0%)100%/0%
Taiwan53 (0.6%)60%/40%Switzerland1 (0.0%)100%/0%
Germany17 (0.2%)28%/72%Portugal1 (0.0%)100%/0%
Philippines14 (0.2%)59%/41%Austria1 (0.0%)100%/0%
Colombia10 (0.1%)50%/50%Total8880 (100%)
Table 4. Technology sectors of the US patents.
Table 4. Technology sectors of the US patents.
SectionAGCBHFDE
(%)42%26%12%8%8%2%1%1%
Table 5. The patent status of companies that developed COVID-19 vaccines.
Table 5. The patent status of companies that developed COVID-19 vaccines.
CompanyNo. of PatentsIPC Section
Pfizer3(single) A
9(converging) A and C
ModernaTX1(converging) A and C
Astrazeneca4(converging) C and G, A and C,
C and B
Janssen Pharmaceutical5(single) A, G
7(converging) A and C
Novavax3(single) A
Table 6. The COVID-19-related patents of major IT companies.
Table 6. The COVID-19-related patents of major IT companies.
Company No. of PatentsIPC Section
Samsung Electronics2(converging) G and H
G and A and H
5(single) G, A, H
Microsoft Technology 1(converging) H, G
1(single) G
Facebook1(converging) H and G
Apple1(single) G
Table 7. Top five influential technology sectors in IP5 countries.
Table 7. Top five influential technology sectors in IP5 countries.
RankUSDegree KoreaDegree ChinaDegree JapanDegreeEUDegree
1A61K499C07K273C07K273A61L77A61K83
2G16H459A61K153A61K153A61K63A61L65
3A61B395C12N151C12N151C12N51A61P59
4A61L357A61P131A61P131A61P41C07K56
5C07K320G01N80G01N80G01N40G01N52
Table 8. Betweenness and closeness centrality results for IP5 countries.
Table 8. Betweenness and closeness centrality results for IP5 countries.
RankUSKoreaChinaJapanEU
Betweeness Closness Betweeness Closness Betweeness Closness Betweeness Closness Betweeness Closness
1A61L12,338C04B1.0A61L6919C22C1.0G01N516F16K1.0A61L3711B01L1.0A61L3372A45D1.0
2G06Q3416D04B1.0A62B5902B62K1.0A61L485E03C1.0B32B781A61J1.0A61B1251B65D1.0
3A41D3388A41B1.0G06Q3225F16F1.0G01J428A61G1.0A61B716A61M1.0B64D1093A61L0.5
4G01N3349F27B0.7A61B2669C04B1.0A61B285F21V1.0A41D609F16L1.0B01D904B64D0.4
5G06F3238F27D0.7A41D2583E04G1.0A61F276D06M0.8A01N569A61L0.5A61K843G01N0.4
Table 9. Top three cases of technology convergence in each country.
Table 9. Top three cases of technology convergence in each country.
CodeUSKoreaChinaJapanEU
IPC
section		C and A
(C-A)		C and A
(C-A)		C and A
(C-A)		C and A
(C-A)		C and A
(C-A)
IPC
subclass		C07K-A61KC07K-A61KC07K-A61KA61K-C12NC07K-A61K
A61K-C12NC07K-C12NA61P-C07KA61L-F24FA61K-A61P
G16H-A61BA61P-C07KC07K-C12NA61K-A61PA61K-C12N
Subclass Index
A61BDiagnosisC07KPeptides
A61KMedical preparations C12NMicroorganisms
A61LAir purification G16HHealthcare informatics
A61PChemical compounds for therapeutic activity F24FAir-conditioning
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MDPI and ACS Style

Jeon, E.; Kim, K.; Park, H.; Cho, K. Global Collaboration in Technology Sectors during the COVID-19 Pandemic: A Patent Review. Sustainability 2023, 15, 11831. https://doi.org/10.3390/su151511831

AMA Style

Jeon E, Kim K, Park H, Cho K. Global Collaboration in Technology Sectors during the COVID-19 Pandemic: A Patent Review. Sustainability. 2023; 15(15):11831. https://doi.org/10.3390/su151511831

Chicago/Turabian Style

Jeon, Eunsook, Kyungkook Kim, Hyunjeong Park, and Keuntae Cho. 2023. "Global Collaboration in Technology Sectors during the COVID-19 Pandemic: A Patent Review" Sustainability 15, no. 15: 11831. https://doi.org/10.3390/su151511831

APA Style

Jeon, E., Kim, K., Park, H., & Cho, K. (2023). Global Collaboration in Technology Sectors during the COVID-19 Pandemic: A Patent Review. Sustainability, 15(15), 11831. https://doi.org/10.3390/su151511831

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