Technological Catching-up and Forging Ahead in 5G: A Patent Data Analysis

Technological Catching-up and Forging Ahead in 5G: A Patent Data Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Technological Catching-up and Forging Ahead in 5G: A Patent Data Analysis Euler Daltro, Marilia Bassetti Marcato, Julia Torracca This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7502679/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper empirically examines technological leadership and the existence of countries in technological catching-up with the potential to become forging ahead at the 5G technological frontier. The analysis is based on a bibliometric approach for the qualitative study of the technologies that comprise 5G, and for the quantitative and qualitative construction of a dictionary of keywords representing such technologies. Following, patent families were taken as a proxy for the countries’ inventive performance, and a lexicographic search based on this dictionary was applied to identify 5G-related patent families, covering the period from 2010 to 2018. The results suggest a possible geopolitical and knowledge-base reconfiguration of the 5G architecture, with a tripartite and technologically specialized leadership shared by South Korea, United States, and China. While Japan and the United Kingdom are losing relevance in this architecture, our results suggest that India, Sweden, and Finland are undergoing a process of technological catching-up. Overall, the identification of forging-ahead and follower countries supports the understanding that catching-up is not a possibility for all but only for those that already possess a minimum level of technological development. JEL: B40, L16, L96, O33, O57 Catch-up Technological catching-up Development 5G Telecommunications Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Mobile communication technologies have transformed social, productive, and commercial relations over the past few decades, with effects on countries’ technological development and implications for technological and geopolitical disputes between nations. It is no coincidence that policymakers in various countries show great interest in the mobile communications sector, given that communication infrastructure is recognized as a cornerstone of economic development (Lemstra, 2018). This interest can be observed in the intense international competition for the development of new generations of these technologies. Since their first commercial uses in the 1970s and 1980s, mobile communication technologies have evolved through approximately five generations, with average commercial lifespans of ten years (Farias, 2021). The competition to develop these technologies has been dynamic, with the rise and decline of competitors in relatively short periods. The development of the first generation was led by Japan (Farias, 2021), the second generation (2G) was led by Japan, the United States, and the European Community, the third generation (3G) was marked by competition between the European Community, Japan, the United States, and South Korea—the latter being a latecomer in the field of computer numerically controlled tools (Sung and Carlsson, 2003) but also the pioneer in the commercial implementation of 3G (Lemstra, 2018)—and the fourth generation (4G) saw the rise of Asian countries in the technological race, with South Korea in the lead, closely followed by China (Kang et al., 2014; Kim et al., 2020). Currently, several countries are competing to develop and define the standard for 5G architecture, the latest generation of mobile communication technologies. Despite South Korea’s technological leadership in the 4G standard, the United States and the European Union have published and implemented industrial and technological policy plans aimed at becoming leaders in developing this standard, seeking to regain their forging ahead 3 position (Parliament, 2015). Meanwhile, China has emerged as a rising competitor, moving from a follower position toward leadership in developing these technologies (Kim et al., 2020). The telecommunications sector has been a ground for historical processes of technological catching-up , as demonstrated by South Korea, which became a leader in the 4G standard, and China, which emerged as a follower in 4G and appears to be in a forging ahead position in 5G architecture (Ariad, 2020). We contribute to the field by identifying and discussing follower countries in technological development with the potential to achieve future leadership in the mobile communications sector, considering 5G architecture as a window of opportunity. In doing so, the study aims to answer the following question: based on invention patent applications related to 5G architecture, which countries are acting as leaders, and which are in the process of technological catching-up? We aim to identify countries that were not leaders in previous technological generations but are in the process of technological catching-up in 5G architecture, with the potential to achieve a forging ahead position in future technological generations. This is done through, first, defining 5G by using bibliometric methodological tools, constructing a keyword dictionary, and conducting lexicographic searches in patent databases for complex technologies. Second, our analysis is based on evidence about the quantity and evolution over time of patent application shares, technological specialization, and the development of inventive capabilities. Building on 5G architecture patent families, we assess countries' comparative inventive performance and identify their positions in the technological race, classifying them into the dynamics of forging ahead , catching-up , and falling behind . Consistent with previous findings about forging ahead nations in the telecommunications sector, the present study confirms that the forging ahead position is held by the triad of South Korea, the United States, and China. Our results suggest that Japan and the United Kingdom are follower countries losing relevance in the development of this technological generation. More importantly, our findings reveal that India, Sweden, and Finland are in the process of technological catching-up in 5G architecture, with the potential to become forging ahead in future technological generations. The paper is structured as follows. Section 2 presents the theoretical framework discussing the process of technological catching-up . Section 3 focuses on data sources and our empirical strategy. Section 4 presents empirical results. Section 5 concludes, discusses the main findings regarding international inventive dynamics in 5G, and highlights the limitations of the study. [3] We use the terms forging ahead and falling behind in the sense presented by Abramovitz (1986), referring, respectively, to leading countries that push the technological frontier and to countries that are falling further behind it. 2. Theoretical Framework According to technological gap theorists, technological differences account for cross-country disparities in per capita income; international convergence cannot be assumed as a natural trend, and catching-up is not an automatic process (Abramovitz, 1986 ; Antonelli and Feder, 2019; Fagerberg, 1994 ; Fagerberg, 1995 ; Gerschenkron, 1962 ). Abramovitz ( 1986 ) offers a dynamic perspective on growth rate differentials: lagging countries possess greater growth potential than leaders, but this potential materializes only if their social capabilities are sufficiently developed to exploit existing technologies. His framework focuses on relative position changes among nations, which may be forging ahead, catching-up, or falling behind. Catching-up, in Abramovitz's terms, can be understood as a race toward a moving frontier, where the initial objective is parity before competing for leadership. Gerschenkron ( 1962 ) argues that success cannot be achieved by imitating a leading country's economic structure and demonstrates that following developed nations' trajectories does not guarantee success. Chang ( 2004 ) reinforces this argument highlighting that catching-up depends on institutional context, with no clear conditions under which "good institutions" would lead to development. Lee and Lim ( 2001 ) distinguish between market catching-up (increasing market share) and technological catching-up (enhancing technological capabilities). While sustained market share growth is difficult without corresponding technological advancement, technological catching-up reinforces market catching-up by supporting long-term productivity and income growth. This process is not a possibility for everyone, as it requires minimum thresholds of productive and innovative capabilities (Lee & Lim, 2001 ), with innovative performance determining the transition from catching-up to forging ahead (Lee, 2019 ). Lee ( 2019 ) argues that countries must abandon imitation and pursue alternative paths to reach productivity and income frontiers, emphasizing the fundamental importance of knowledge generation capacity. Lall ( 1992 ) stresses the importance of synergies in catching-up: physical capital accumulation without corresponding skills or knowledge yields inadequate development. Even when targeting the frontier, catching-up is not generalized - while leaders exhibit high productivity and income levels, their economic structures differ significantly (Fagerberg & Godinho, 2005 ; Lee, 2019 ; Malerba & Lee, 2021 ). The catching-up process - both technological and market-oriented - is not generalized because there is no causal chain demonstrating that all sectors can simultaneously increase productivity. Literature suggests catching-up is sector-specific (Fagerberg & Godinho, 2005 ; Perez et al., 1988 ) and cannot be achieved by investing generically across sectors, as leadership in one sector doesn't imply overall dominance (Lee, 2019 ). This reflects the evolutionary perspective on knowledge cumulativeness and locality as characteristics of technical change. Building on the premise that firms don't explore all production possibilities (Dosi & Egidi, 1991 ) and that economies are complex, evolving systems (Nelson & Winter, 1982 ), leadership in specific technologies does not constitute a timeless global optimum transferable across activities. While Chang ( 2004 ) concludes that leading nations "kicked away the ladder" of development, Lee ( 2019 ) argues that catching-up is possible if the country ignores the ladder, deviates from established paths, and "fly by balloon", leveraging latecomer advantages (Gerschenkron, 1962 ; Lee, 2019 ) to leapfrog developmental stages. According to Perez et al. ( 1988 ), catching-up requires strategic investments in key sectors, aiming to be forging ahead, though sectoral leadership only translates to global leadership if the sector has spillover potential for the broader economy. This literature seeks to identify characteristics of sectors and moments that present windows of opportunity for catching-up (Lee, 2013 ; Perez et al., 1988 ). Following Lee ( 2019 ), we define windows of opportunity as contexts where catching-up is feasible - requiring precise timing for entry. Antonelli and Feder ( 2020 ) emphasize that directing technological knowledge generation to fit local structures is crucial for successful catch-up. Lee ( 2019 ) notes that periods of technological maturity and stability are unfavorable for catching-up, as knowledge cumulativeness creates greater barriers for lagging countries. In catching-up processes, laggards don't follow leaders' trajectories but frequently skip stages or create new paths (Mu & Lee, 2005 ). This approach aligns with the leapfrogging thesis (Perez et al., 1988 ) which posits that new techno-economic paradigms give developing countries initial advantages in catching-up. Within new paradigms, leaders and followers start from similar positions, with leaders often constrained by technological lock-in (Lee, 2019 ), while followers face fewer such barriers. Leapfrogging involves adopting and innovating emerging technologies while circumventing investments in obsolete paradigms, aiming for leadership in new eras (Lee & Ki, 2017 ). All countries are beginners when new paradigms emerge, enabling laggards to leapfrog (Lee, 2019 ). Since the equipment to produce the new goods hasn't been developed, generic machinery can be used for small-scale initial production, minimizing barriers. While technology performance is neither stable nor known, human resources capable of knowledge creation facilitate market entry. The optimal timing for leapfrogging coincides with techno-economic paradigm shifts, while short-cycle technology sectors offer the best venues due to more concentrated opportunity windows (Lee, 2021 ; Malerba and Lee, 2021 ; Lee et al., 2021). Yu et al. ( 2020 ) demonstrate that during periods of technological disruptions, greater technological opportunities combined with low appropriability, and demand heterogeneity are vital for technological catching-up. Lee ( 2019 ) identifies two developing-country specificities that make catching-up rare. First, "capability failures", associated with difficulties in building innovative capacity, and their existence justify government activism in capability development. Second, "size failures" - challenges in creating large firms that typically drive innovation, while smaller firms often generate only subsistence-level wages and profits. For Lundvall ( 1992 ), this process doesn't occur in isolation: catching-up decisions are made at firm level but are influenced by their institutional environment. Firms operate within systems, embedded in historical, social and economic networks that shape their decisions. Absent, underdeveloped, or poorly developed institutions and organizations impair firms' decision-making capacities (Lee, 2019 ; Malerba and Nelson, 2011; Malerba and Lee, 2021 ). Lee ( 2013 ) sought to measure innovation system performance using USPTO patent data at country, sector and firm levels, showing that East Asian countries that achieved catching-up specialized in short-cycle technologies. Lee and Lee ( 2020 ) employed indicators of local knowledge creation and diffusion - including patent self-citation coefficients - to evaluate the performance of countries, finding robust evidence for the importance of knowledge localization. 3. Data and empirical strategy Given the objective of identifying countries undergoing technological catching-up in the context of 5G, the analysis is conducted based on indicators of technological performance. There are various ways to measure such performance, for example, through R&D investment; however, this variable is more suitable for a broad analysis of technological performance (Silva, 2019 ). Other approaches include analysis through productivity variables and institutional quality metrics (Manca, 2009 ), though these better reflect technology adoption rather than inventive performance; and innovation surveys (Caria Junior, 2015 ), which are limited by difficulties in cross-country comparison and analysis of specific technologies. The approach chosen here is analysis based on patent application statistics, following an extensive body of literature (Archibugi and Pianta, 1994 , Lee, 2013 ; Lee & Lim, 2001 ; Miranda, 2014 ; Niosi et al., 2012 , Park & Lee, 2006 ; Prodi et al., 2020 ). According to Macedo and Barbosa ( 2010 ), over 70% of technological information available worldwide can only be found in patent documents, and there are numerous reasons why the technological information contained in such documents is superior to other information systems: (i) technology par excellence: patent documents store technological knowledge intended for goods production; (ii) technological classification: it is the only system configured to organize technical information by knowledge areas; (iii) complementarity: the documents contain state-of-the-art surveys; (iv) standardization and uniformity: the collections have standardized information available for long periods, enabling comparative analysis; and (v) breaking language barriers, as the information is provided in standardized and coded form, facilitating information retrieval. A patent is a right granted by the state that gives the holder exclusive rights to exploit a technology (Barbosa, 2010 ). In exchange for public access to this knowledge, the law grants the patent holder a time-limited right. As a state prerogative, this right is restricted to the region covered by the office that granted it. To obtain property rights in different territories, the patent application must be filed with the national offices of those territories or validated by an international office. The set of filings covering the same or similar inventions are called families. Each family has one or more filings as members, and each filing belongs to exactly one family (OECD, 2009). Furthermore, all filing applications are classified according to knowledge areas. The main international classification of knowledge areas is the International Patent Classification (IPC) (OECD, 2009), which assigns hierarchical symbols to knowledge areas. In filing applications, at least one symbol is assigned to each filing. The delimitation of the right's scope is based on a descriptive report contained in the filing document. This includes a characterization of the state of the art, made through citations to granted patents and scientific articles. Using these citations, it is possible to establish links between the inventive activity, materialized in the patent application, and the knowledge considered as the relevant basis for the development of this invention, materialized in the cited documents. There are three major possibilities for analyzing the territorial dimension of patents: (i) based on the region covered by the offices (EPO, 2020), which allows analysis of the regions where applicants seek legal protection; (ii) based on the applicant's country of residence (Chiarini and Callari, 2019), which reflects ownership of inventions; and (iii) based on the inventors' country of residence (de Rassenfosse et al., 2014), serving as an indicator of the location of technological activity. Despite the advantages of using patent statistics, this is not a perfect source of information about inventive performance because not all technological efforts result in patents. There are two reasons for this: (i) because they do not result in something patentable; or (ii) due to the firm's strategic decision when considering the costs and benefits of patenting (Miranda, 2014 ). Although patent performance - measured by the number of filing applications - does not perfectly reflect technological efforts, patent applications can be understood as a proxy for technological activities as they represent a significant portion of technological effort (Barbosa, 2010 ). For this research, we used patent applications filed in all offices during the period 2010–2018, with data extracted from the April 2020 edition of the Worldwide Patent Statistical Database (PATSTAT 2020). We considered filed patent applications rather than just granted patents, as this option allows inclusion of the most recent years, since the publication and granting process can take up to 10 years (Miranda, 2014 ). Given the complexity of the technology in question, there are no IPC symbols capable of exclusively circumscribing 5G architecture. Under this condition of lacking a set of IPCs, we proceeded with the selection of patent applications through lexicographic search. The lexicographic search imposes its own biases on the analysis: (i) the dictionary of keywords may either underestimate or overestimate the number of filings related to a technology, either due to the choice of terms that are too broad, causing the lexicographic search to return filings unrelated to this technology, or terms that are too narrow, resulting in fewer filings than the true total; (ii) the choice of terms is affected by the researcher's prior knowledge and may therefore be biased by their beliefs about what constitutes a good dictionary; and (iii) language bias, where searching for key terms in fewer than all existing languages could underestimate the number of filings. To address the first two types of biases, the keyword dictionary was constructed through bibliometric analysis of specialized literature. This technique allows for structured literature review through computational text selection, enabling observation of the development of central concepts, themes, and most relevant authors, with the bibliometric result interpreted as a quantitative image of the qualitative knowledge structure (Aria and Cuccurullo, 2017 ). We used the Scopus database, from which we selected publications containing the terms "5G" and "IEEE" (Institute of Electrical and Electronics Engineers) in the title, abstract, keywords, or keyword-plus fields. The use of these terms is justified by the importance of this organization in publishing scientific knowledge in engineering and defining internationally accepted standards in various fields. The selection, conducted on March 18, 2022, contains 1,524 documents published between 1961 and 2022. From this, we constructed an Article (row) × Reference (column) matrix, where a value of 1 for a given combination means that the article in the row cites the reference in the column, and 0 otherwise. The articles in the Article dimension represent the literature discussing 5G (set A), and the articles in the Reference dimension are the knowledge base used to form the Article dimension (set B). Assuming that an article's importance is directly related to its citation count, the fact that an article in set A is highly cited by the total literature is not sufficient to claim that it is central to the study and understanding of the subject, as it may be generic material. An element of set B that is highly cited by the literature is not sufficient to claim that it is central to understanding the subject, as it may simply be common background knowledge, but a member of set B that is highly cited by set A can be understood as the relevant knowledge base for the formation of set A. We define C = A ∩ B, as the articles that form the relevant knowledge base for the literature's formation and discuss the subject in question. This set C best represents the core of the discussion, as they address the topic and substantiate its knowledge base. From C, we selected the 30 most internally cited articles by this literature for qualitative study. From set A, we computed the absolute frequency of n-grams present in the textual fields of title, abstract, keywords, and keyword-plus. By ordering the frequency of n-gram appearance, we hypothesized that the highest-ranked n-grams are the key central terms of this literature and are relevant for characterizing 5G. Together with the qualitative study defined above, we separated the n-grams into lower forms (unigrams, bigrams, and trigrams) and extracted their roots. From this new list, we removed (i) terms with no semantic value; (ii) terms that, even in the context of 5G, may not refer exclusively to it, or that even when combined with the name "5G" may refer to a different and unrelated technology; and (iii) generic terms that may be related to other technologies. For these cleaning steps, we used knowledge gained from the previous qualitative study and asked the auxiliary question: "In a patent search containing exclusively the technology's name and this n-gram in question, would it be possible for the search to select many patents that are not truly related to this technology? If so, what types of technologies?" As a result, we defined that the key terms that best represent 5G are: 5G, mobile, communication, ieee, wireless, milimetre wave, mmwave, network, bandwidth, mimo, internet, orthogonal frequency division multiplexing, ofdm, beamform, cellular, celular, radio . The third bias - language bias - is a complex issue to address. It would be necessary to conduct the lexicographic search in all languages, which requires significant processing time. Additionally, there is no information about the standardization of encoding textual fields in the database. For example, Lee and Lee ( 2020 ) used USPTO data - one of the offices contained in Patstat - and a lexicographic search mechanism for selecting patent applications, while Prodi et al. ( 2020 ) used EPO office data to understand Chinese inventive performance. Although encoding has little effect on searches conducted in Latin encoding systems, they would not be able to locate filings written in logograms. To resolve the language bias, it would be necessary to have the dictionary perfectly translated into all languages and writing systems, with all encoding variations. As a possible strategy to overcome this obstacle, we calculated the coverage rate of patent applications that could be retrieved through lexicographic search, by office, if the lexicographic search were conducted only in English in abstracts, for filings made between 2010 and 2018 (see results in Table 1 ). Table 1 Degree of coverage of information contained in Patstat 2020, by office. Office Has abstract in English Has abstract in English in the family Has IPC Has IPC in the family Has inventors Has inventors in the family China 98% 98% 99% 99% 98% 98% USPTO 72% 73% 72% 72% 78% 78% Japan 67% 82% 85% 85% 71% 83% WIPO 99% 99% 99% 99% 99% 99% South Korea 68% 86% 95% 95% 88% 90% EPO 43% 91% 94% 94% 94% 94% Germany 11% 59% 94% 94% 75% 81% Taiwan 68% 71% 99% 99% 98% 98% Russia 60% 67% 99% 99% 61% 69% Canada 95% 99% 86% 86% 86% 95% Australia 88% 89% 76% 76% 76% 82% UK 48% 65% 49% 65% 48% 65% Brazil 0% 72% 96% 96% 100% 100% France 14% 71% 98% 98% 98% 98% Spain 0% 73% 99% 99% 98% 99% Mexico 100% 100% 99% 100% 100% 100% Ukraine 57% 60% 99% 99% 60% 63% Italy 0% 34% 26% 48% 82% 83% Poland 0% 52% 99% 100% 100% 100% Singapore 32% 94% 60% 93% 96% 96% India 47% 48% 47% 47% 48% 48% Italy 0% 88% 94% 97% 23% 91% Denmark 7% 81% 86% 86% 86% 87% Hong Kong 1% 91% 98% 98% 93% 97% Turkey 1% 29% 83% 84% 87% 87% South Africa 0% 73% 27% 77% 82% 83% Argentina 0% 75% 90% 96% 65% 92% EM 0% 0% 0% 0% 0% 0% Chile 0% 77% 82% 85% 99% 99% Eurasia 43% 92% 100% 100% 47% 93% Portugal 0% 84% 93% 96% 95% 96% Total 82% 90% 93% 93% 90% 92% Source: Author’s elaboration based on Patstat 2020 data. Table 1 shows that 82% of filings have abstracts in English (column 1). For the offices of China, WIPO, and Mexico, English lexicographic searches can correctly locate nearly all filings. There are offices with incomplete coverage, such as the USPTO, South Korea, and Russia, but there are also extreme cases, such as Brazil, Spain, Italy, South Africa, and Argentina, where there are no English abstracts, which would bias the selection. This result demonstrates that lexicographic search could underestimate the number of 5G-related filings, in different extent on each office. As an alternative to building a dictionary in all languages, we also calculated the coverage of filings that have at least one family member with an English abstract (column 2). In this case, there is a significant improvement in coverage for most offices, increasing from 82–90% of the total. However, we still observe low coverage for several offices, particularly Germany, Russia, the UK, Ukraine, Italy, Poland, India, and Turkey. Given the improved coverage when considering that most filings have at least one family member in English, and that filings in a family refer to the same invention, lexicographic search remains a viable strategy, and even if an office has no filings in English, we will likely locate filings from the same family in other offices with English abstracts. We proceeded with English lexicographic searches, aware of the extent of incomplete coverage and considering this in our analysis. It should be noted that we must be cautious when interpreting results from these lower-coverage offices, as their data may be underestimated. For the final objective of this research, the necessary information from the filings are (i) application year, which defines the temporal dimension of the invention; (ii) IPCs, which define the knowledge areas; and (iii) the territories of inventor locations, which define the geographical dimension of the knowledge. We calculated the coverage rate of Patstat 2020 in the registration information of IPCs and inventors in patent applications, as well as the coverage in at least one family member (Table 1 ). This calculation is justified because if there is no IPC listed in the family, this would result in lower participation of the original countries of these offices in the total of inventions related to each knowledge area. We found improvements in the absence of coverage when considering the entire family, but the problem persists in families with filings made in the UK, Italy, and India offices. The IPC results for these countries should be interpreted with caution. We observed a similar pattern regarding the existence of inventor registration listed in the family versus inventors listed in the filing. In this case, we again observed low coverage for the offices of Russia, the UK, and India. Therefore, although we see improvements in coverage level when analyzing the family, we need to be particularly careful when analyzing filings made in countries where we found some form of lack of information. With these considerations, we proceeded with the English lexicographic search using the previously constructed dictionary. To avoid double counting, we used the family concept as the unit of analysis. From PATSTAT, we selected the set of 5G-related patent applications through the combinatorial search of the terms "5G", "5-G", "5 G" or "fifth gen" with each of the previously defined root keywords, in the combination of Title and Abstract fields, regardless of the order of term appearance, position, distance, and presence of suffixes or prefixes, without case sensitivity. The search resulted in 16,661 applications, from which we filtered filings of type 'A' (Direct filing) and 'W' (PCT application) that contained at least one IPC in section H (Electricity). From these deposits, we selected its families and then selected all the members of this families. Limiting the timespan of the oldest deposit to between 2010 and 2018, we obtained 5,219 families related to 5G architecture. We chose to characterize the patent family based on the characteristics of all its members. The family's filing year was given by the oldest filing's year. Following Prodi et al. ( 2020 ), the territory of origin of the family's knowledge was given by the average of the fractional counts of the territories of origin of the family's filings. At the filing level, the fractional count of territory is defined as follows: for each filing, for each territory of inventor location, the total number of inventors from that country in that filing is divided by the total number of inventors. The purpose of this calculation is to apply a weighting of the number of inventors to the knowledge required to obtain this invention. For example, if a filing has 9 inventors located in China and 1 located in Germany, we considered that China has greater relative importance in generating this invention and therefore classified this filing as 90% Chinese and 10% German. To aggregate these values to the family level, we assumed that if all filings in a family refer to the same invention, they should have the same inventors listed in all filings, and consequently, the average of the fractional counts by country per filing should equal the individual fractional count of each filing. However, given the possibility of registering different inventors in different filings in the family, the average fractional count will differ from the individual result. In this case, the average fractional count will weigh the territories of origin of the filings. For example, in a family with 2 filings, where filing 1 is 50% Chinese and 50% German, and filing 2 is 75% Chinese and 25% German, there is divergence in the fractional count. Applying the average fractional count, the family will be (50% + 75%) / 2 = 62.5% Chinese and (50% + 25%) / 2 = 37.5% German. 4. Results Table 2 presents the number of patent families per year of filing. Given the presence of incomplete information in patent application records, the 5,219 families identified through the lexicographic search were reduced to 3,628 analyzable families. The three-year period 2010–2012 accounts for 3% of filings, 2013–2015 for 23%, and 2016–2018 for 74%. An increase in the share of 5G architecture-related patent applications within total patenting is also observed, indicating that the growth in filings is not the result of a generalized increase in patenting but rather by increase in propensity to patent in 5G. Table 2 Count of 5G architecture families, by year of oldest deposit Year Number of families Share Share in total patenting 2010 44 1,21% 0,01% 2011 53 1,46% 0,01% 2012 44 1,21% 0,01% 2013 84 2,32% 0,01% 2014 276 7,61% 0,04% 2015 455 12,54% 0,07% 2016 808 22,27% 0,12% 2017 1,212 33,41% 0,19% 2018 652 17,97% 0,18% Total 3.628 100,00% 0,07% Source: Author’s elaboration based on Patstat 2020 data. Figure 1 shows the distribution of patent families by inventor territory, based on the fractional count of inventors' countries of origin. Approximately 44% of the families originate from South Korea, 21% from the United States, and 16% from China, collectively accounting for 81% of the total. Given that these three countries were also the main developers of 4G, this reinforces the phenomenon of knowledge cumulativeness. The next seven most significant countries - Japan, the United Kingdom (underestimated), India (underestimated), Taiwan, Sweden, Germany, and Finland - collectively account for 13%, while the rest of the world (48 countries with some participation in filings) sums 6%. Thus, the leadership of South Korea, the United States, and China in 5G architecture development is evident. Comparing the distribution of family origins by three-year periods for the top ten countries (Fig. 2 ), the first period (2010–2012) shows unclear leadership in 5G architecture. By the second period (2013–2015), South Korea emerges as the leader, a position maintained in the third period (2016–2018). In the latter, the United States and China show strong participation in 5G-related patent applications. This suggests that the U.S. and China gained prominence in 5G development only in the third period. Analyzing the relative distribution of families from the three leading countries versus the rest of the world (Fig. 3 ), the first period shows a significant share from other countries (60%), consistent with the lack of clear leadership observed in Fig. 2 . However, this period represents only 3% of total filings, suggesting that 5G architecture and technological leadership was not yet well-defined. In the second period, South Korea’s technological leadership emerges, accounting for over 50% of families, followed by the U.S. (~ 20%) and China, with these three representing 80% of filings. In the third period, their dominance remains unchallenged, maintaining an 80% share, though China’s relative importance grows at the expense of South Korea, while the U.S. remains stable. This indicates that leadership is not equally tripartite and that China is becoming increasingly significant. To assess follower positions, the distribution of family origins was analyzed excluding the top three countries (Fig. 4 ). Among the remaining 55 countries, four (Japan, the U.K., India, and Taiwan) account for 51% of filings, while ten countries (including Sweden, Denmark, Finland, France, Canada, and Russia) represent 87%. The remaining 45 countries contribute only 13%. Given their marginal relevance compared to the three leaders, these ten countries are preliminarily classified as the follower group in 5G development, while the remaining 45 are considered falling behind or minimally relevant. The evolution of these ten countries’ relative participation in 5G-related filings was also examined (Fig. 5 ). There is a decline in share of Japan and in the group of the rest of the world (falling behind). The Japanese decline does not imply it is falling behind, as it remains the leader among the followers. This reinforces the idea that maintaining a leadership position does not occur automatically and is possible that Japan may further decline in innovative positioning without new strategies. The U.K. shows consistent growth, though its results may be underestimated due to Patstat coverage limitations. India emerges as a relevant competitor, though its performance is mixed, and its data may also be underestimated. Sweden gains prominence in 2016–2018, likely driven by established telecom firms like Telia and Ericsson (Andonian et al., 2018 ). Taiwan, though declining, remains significant among followers, and its numbers are potentially underestimated, and its share is higher than that of the remaining five countries – Germany, Finland, Frange, Canada and Russia – which show no substantial growth, reinforcing that catching-up is not automatic, and innovation disparities persist in 5G development. At this stage, the analysis allows us to state that: (i) South Korea, the U.S., and China are the leaders in 5G architecture; (ii) Japan, the U.K., India, and Taiwan are the primary followers; (iii) Sweden may be rising as a competitor, supported by its established telecom sector; (iv) The U.K., India, Taiwan, and Sweden have the highest potential to become forging ahead due to their advanced positions among followers; (v) Japan shows signs of declining prominence, though it remains relevant; and (vi) While Germany, Finland, France, Canada, and Russia contribute to 5G-related inventions, there is no evidence suggesting they could become forging ahead. Having identified the technological leadership of South Korea, the United States, and China in patent applications related to 5G architecture, as well as distinguishing between follower countries with catching-up potential and those without evidence of such potential, we sought to analyze the factors determining these countries' positions. To this end, we examined whether the standing of these three stems from their higher patenting activity compared to the rest of the world, as a country might emerge as a leader in 5G architecture simply due to filing more patents overall, regardless of the technological field. As previously noted, the literature on technological gap theory conceptualizes catching-up as a typically sectoral process (Fagerberg & Godinho, 2005 ; Perez et al., 1988 ), wherein a country strives to become a leader in a specific sector, leveraging the benefits of technological leadership while generating spillover effects for the broader economy. Building on this perspective, we can correlate - without establishing causality - a country's technological specialization in a sector with its pursuit of technological leadership in that sector. In this sense, while specialization may facilitate technological catch-up, it does not guarantee it. Accordingly, we employed the Revealed Technological Advantage (RTA) indicator (Guellec and De La Potterie, 2001 ; Sung and Carlsson, 2003 ), calculated as follows: $$\:{RTA}_{ij}=\frac{\left(\frac{{X}_{ij}}{{X}_{j}}\right)}{\left(\frac{{Y}_{ij}}{{Y}_{j}}\right)}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(1\right)$$ Where: \(\:{X}_{ij}\) = number of patent families from country i in period j in 5G; \(\:{X}_{j}\) = number of patent families from all countries in period j on 5G; \(\:{Y}_{ij}\) = number of patent families from country i in period j across all technological fields; and \(\:{Y}_{j}\) = number of patent families from all countries in period j across all fields. The relative importance of each country in patenting 5G architecture families is weighted by the relative importance of this country in total patenting. An RTA greater than 1 indicates a revealed technological advantage in 5G. If a country’s capacity to develop patentable inventions in the 5G architecture exceeds its general patenting capacity, this reflects relative specialization in 5G. It is important to emphasize the mathematical effect of selection bias arising from asymmetric coverage in Patstat across patent offices and countries. Unless only one country files patents in 5G architecture, \(\:{X}_{ij}<\:{X}_{j}\) and the expression \(\:\frac{{X}_{ij}}{{X}_{j}}\) is increasing for values of \(\:{X}_{ij}\) . Therefore, if a country i has underestimated data on 5G patent families and denoting \(\:{X}_{ij}^{*}\) as the value of \(\:{X}_{ij}\) if the information was complete, given that values of \(\:{X}_{ij}\) do not affect values of \(\:{Y}_{ij}\) , we have \(\:{RTA}_{ij}<\:{RTA}_{ij}^{*}\) . We calculated RTA by country and three-year period for the 13 countries with the highest number of patent families (Table 3 ). In 2010–2012, none of these countries exhibited a technological advantage in 5G (RTA > 1), which is expected given the nascent stage of these technologies. In 2013–2015, among the forging ahead countries, only South Korea had an RTA above 1, while the U.S. and China had RTAs below 1. This suggests that the higher relative participation of the U.S. and China in 5G development during this period may stem from their strong overall patenting activity or a broader propensity to patent, rather than specialization in these technologies, whereas South Korea's leadership likely derives from specialized technological advancement. Among follower countries, only India (the third-largest filer) had an RTA above 1 (1.54), indicating specialization. This result is particularly significant given potential data underestimation; with complete data, India's RTA might have been even higher, reflecting stronger technological specialization in telecom. The other potential catching-up followers (Japan, the U.K., Taiwan, and Sweden) did not exhibit RTA > 1, and it is not possible to say whether if there were no underestimation of the data the RTA would be greater than 1, precluding preclude definitive conclusions. Among followers without catching-up potential, Germany, France, and Russia had low RTAs, making it unlikely that complete data would reveal a technological advantage. Finland and Canada also showed no signs of specialization or data underestimation in this period. In 2016–2018, South Korea and India (already specialized) showed further RTA growth. For India, this result is especially notable given potential data underestimation. Among leaders, the U.S. reached an RTA of 1.01, barely exceeding the threshold and thus indicating minimal specialization, while China surged to 2.07, solidifying its position as a specialized leader. Among potential catching-up followers, the U.K. and Sweden joined India as specialized countries (with the U.K.'s data likely still underestimated). Japan and Taiwan remained unspecialized, with Japan, historically a leader in 1G and 2G, showing the lowest RTA in this group despite being the top follower in 5G patenting (see Fig. 2 ). Finland was the only non-specialized follower to achieve RTA > 1 in this period, while others (Germany, France, Canada, and Russia) maintained their positions due to general patenting capacity rather than specialization. Table 3 Revealed Technological Advantage (RTA) of the top 13 fillers in 5G, by three-year period. Country/Period 2010–2012 2013–2015 2016–2018 South Korea 0,07 1,24 2,30 US 0,12 0,30 1,01 China 0,10 0,57 2,07 Japan 0,26 0,09 0,13 UK 0,09 0,46 1,47 India 0,32 1,54 1,74 Taiwan 0,13 0,11 0,22 Sweden 0,08 0,08 2,59 Germany 0,03 0,05 0,16 Finland 0,27 0,81 3,19 France 0,10 0,09 0,43 Canada 0,11 0,31 0,82 Russia 0,13 0,08 0,24 Source: Authors’ elaboration based on Patstat 2020 data. At this point we can conclude that, for the 2016–2016 period in 5G: (i) South Korea and China are specialized forging ahead countries; (ii) The U.S. is a weakly specialized forging ahead country; (iii) Japan is an unspecialized follower; (iv) India and the U.K. are specialized followers with catching-up potential (likely underestimated), potentially challenging Japan's position; (v) Sweden is a rising specialized follower, possibly joining India and the U.K. as catching-up candidates; (vi) Taiwan is an unspecialized follower; and (vii) Germany, France, Canada, and Russia are unspecialized followers with lesser relevance among the analyzed countries. We sought to analyze the countries of origin of knowledge contributing to inventions related to 5G architecture by examining the countries of residence of inventors cited in patent families. Following a methodology like Kang et al. ( 2014 ), this exercise aims to understand the relevance of different countries as knowledge bases for advancements in these technologies - interpreted as a reflection of knowledge internationalization - and the importance of domestic knowledge for subsequent technological developments - understood as reflecting cumulativeness and the ability to transform internal knowledge into technological progress. By considering the patents cited by each 5G architecture patent family as representing the relevant knowledge base for its development, we can infer that the countries of residence of inventors listed in these cited patents indicate the geographic origins of the foundational knowledge. For example, if a patent with German origin exclusively cites patents whose inventors reside in China, we may assume that Chinese-originated knowledge formed the basis for developing that patent family. Following the same approach as in previous analyses, we applied fractional counting to determine the national origins of cited patents for each of the 3,628 5G patent families. From this fractional counting of cited patents, we calculated each country's proportion as a knowledge base for 5G patent families, organized by three-year periods based on the filing date of the citing family (Table 4 ). For families first filed in 2010–2012, 50% of cited patents in references were of U.S. origin, meaning American knowledge constituted 50% of the knowledge base for these inventions. Japanese knowledge also proved highly significant, ranking second with 15% of the knowledge base, which aligns with Japan's position as a forging ahead country during 1G to 3G generations (Farias, 2021 ), making it a standard knowledge base for telecom developments. South Korea ranked third, accounting for 9% of the knowledge base. Although South Korea was forging ahead in 4G (Kim et al., 2020 ), its relatively modest share as a knowledge base during this period may reflect the early global development stage of 5G architecture, where initial developments likely relied more on the generalized knowledge bases of the U.S. and Japan rather than South Korea's highly specialized 4G expertise. Since 5G architecture knowledge partially derives from 4G and previous technological generations and given these three countries' historical importance in earlier generations, these findings align with expectations. In the 2013–2015 period, we observe a decline in the U.S. (from 50–41%) and Japanese (from 15–7%) shares of the knowledge base, with their combined contribution falling from 65–48%. Simultaneously, South Korea's knowledge base increased from 9–21%, while China's rose from 3–7%. This demonstrates that China and South Korea are becoming more significant knowledge bases for 5G development at the expense of knowledge originating from the U.S. and Japan. This trend intensified in 2016–2018, with the U.S. share declining further to 35% (a 15-point total decrease between the first and last periods). Japan similarly continued its downward trajectory, losing 9 points in importance. Meanwhile, South Korea and China increased their knowledge base importance by 13 and 9 points respectively. Notably, between the first and third periods, the combined share of South Korea and China rose from 12–34%, while the U.S. and Japan's combined share fell from 65–41%. These new levels suggest a decline in U.S. knowledge hegemony and a potential multipolarisation of the global knowledge base centered around South Korea and China. Among specialized follower countries (UK, India, Sweden, and Finland), none achieved significant or prominent participation as knowledge bases in any three-year period. India showed a modest 1-point increase across periods but remained marginal at 2%. Sweden demonstrated slightly stronger growth, increasing 3 points to reach 5% of the knowledge base by 2016–2018, becoming the fourth most important base. The UK and Finland maintained low participation (2% each) without growth. These four countries' results indicate substantial challenges in achieving technological leadership positions. Among non-specialized follower countries (Taiwan, Germany, France, Canada, and Russia), we found no evidence of increasing relevance as a group. The rest of the world, classified as falling behind, declined by 3-points in knowledge base participation across periods, confirming their falling behind status in knowledge production. Table 4 Knowledge base composition for 5G architecture patent families (%)s Country/Triennium 2010–2012 2013–2015 2016–2018 Change in 2010–2018 South Korea 9% 21% 22% + 13 p.p. US 50% 41% 35% -15 p.p. China 3% 7% 12% + 9 p.p. Japan 15% 7% 6% -9 p.p. UK 2% 2% 2% 0 India 1% 1% 2% + 1 p.p. Taiwan 3% 2% 2% -1 p.p. Sweden 2% 4% 5% + 3 p.p. Germany 3% 3% 3% 0 Finland 2% 3% 2% 0 France 1% 1% 1% 0 Canada 3% 4% 5% + 2 p.p. Russia 1% 0% 0% -1 p.p. Other 45 countries 7% 5% 4% -3 p.p. Total 100% 100% 100% 0 Source: Authors’ analysis based on Patstat 2020 data. We sought to understand the importance of each country's native knowledge for technological development in 5G. To this end, we constructed a self-citation indicator to observe each country's share in the nationality of cited patent families, by three-year period of 5G family filings. We interpret this coefficient as a potential proxy for internal capabilities (Kang et al., 2020), in the sense that a high self-citation coefficient indicates the country possesses more accumulated knowledge in related technologies and can generate new knowledge from native knowledge, being less dependent on external knowledge sources. Conversely, a low self-citation coefficient demonstrates the country's dependence on external knowledge to create its patentable inventions. Table 5 presents the self-citation coefficient by country and three-year period for 5G families. For South Korea, we observe a coefficient of 36% in 2010–2012, a decline between 2010–2012 and 2013–2015, but a recovery in 2016–2018, with a net result of -1 percentage point. In all periods, this country's coefficient aligns with those of the other three major patent filers (United States, China, and Japan), remaining above values observed for the rest of the world. The loss of self-citation between the first two periods may relate to the initial development stage of 5G in the first period, where South Korea likely utilized its 4G knowledge to develop its inventions. For the second period, the reduced domestic base may be associated with the growth of main competitors (United States and China), bringing new knowledge that South Korea used for its developments, possibly also explained by deepening international cooperation for 5G development. With 5G foundations established, the importance of South Korea's internal knowledge grew again in the third period. Table 5 – Self-citation coefficient of 5G families Country/Triennium 2010–2012 2013–2015 2016–2018 South Korea 36% 29% 35% US 66% 59% 46% China 18% 16% 34% Japan 37% 49% 38% UK 4% 12% 5% India 0% 2% 4% Taiwan 25% 11% 4% Sweden 0% 0% 10% Germany 5% 3% 10% Finland 11% 8% 14% France 7% 9% 5% Canada 16% 11% 16% Russia 26% 0% 15% Source: Authors' analysis based on Patstat 2020 data. We observe a high self-citation coefficient for the United States across all periods compared to other countries, demonstrating that this country bases its 5G-related inventions primarily on internal knowledge. However, we note a decline from 66% in 2010–2012 to 59% in 2013–2015 and 46% in 2016–2018, indicating growing dependence on knowledge from external sources. China showed a small decrease in its coefficient between the first two periods, from 18–16%, but recovered its self-citation coefficient in the third period, increasing it to 34%. China is increasingly developing based on its own knowledge base. This may provide evidence supporting the success of China's current and previous development initiatives, particularly the Made in China 2025 plan - an ambitious industrial modernization strategy to reduce dependence on imported technology, where China seeks to close its technological gap and promote large-scale modernization. This plan is guided by the understanding that a country's core competitive strength lies in its innovative capacity (Marcato, 2022 ). Additionally, Chinese companies acquire knowledge through mergers and acquisitions, startup foundations, and research and development centers (State Council, 2015 apud Marcato, 2022 ), obtaining external knowledge through overseas investments supported by state intervention. Among followers, Japan maintains high self-citation indicators across all periods, exceeding South Korea - the 5G technological leader - in each one, demonstrating its strong capacity to transform internal knowledge into patentable inventions. However, Table 4 shows Japan lost share as a knowledge base and Table 3 reveals it lacks RTA in 5G. Japan's propensity for domestic innovation may be preventing it from maintaining its past forging ahead position. According to Andonian et al. ( 2018 ), by pioneering its own standards rather than collaborating internationally, Japan created a fragile ecosystem, placing it in technological lock-in reflected in average 4G speeds below developed world average. Currently, Japan shows forging ahead status in signal adoption and availability. The United Kingdom, a specialized follower, shows no clear trend in its self-citation coefficient, maintaining values in all periods below those of the four leading knowledge base countries and close to coefficients of other follower countries. India, a specialized follower, has the lowest self-citation coefficient in two of three periods among followers but shows continuous growth, indicating developing capacity to use internal knowledge to generate new knowledge. Sweden, another specialized follower, showed zero self-citation in the first two periods but median values among followers in the third period, suggesting absence of past specialization in 5G technologies, though this doesn't preclude possible 4G specialization, reinforced by its telecom giants Telia and Ericsson. Finland shows median self-citation among followers in this period with no clear upward or downward trend. Taiwan demonstrated a decline in self-citation, showing increasing dependence on non-native knowledge for its development. For other followers, no clear patterns in self-citation coefficient evolution were identified. The analysis demonstrates that major countries responsible for 5G architecture-related inventions show different innovative performances, as shown in Fig. 1 . South Korea holds a technological forging ahead position: the country is an undisputed leader in invention patenting, was (along with India) among the first to show RTA, has growing share in the knowledge base supporting new inventions, and maintains high, stable self-citation coefficients, indicating the importance of cumulative internal knowledge for developing new patentable inventions. Table 6 - Summary analysis of patent applications, RTA and self-citations Country Patents Evolution RTA Knowledge base Self-citations South Korea Forging ahead Contested forging ahead Specialized forging ahead on second period High relevance and growing importance High and stable US Forging ahead Maintainer forging ahead Weakly specialized forging ahead on third period High relevance and decreasing importance High but declining China Forging ahead Forging Ahead in ascension Specialized forging ahead on third period High relevance and growing importance High and growing Japan Potential follower Contested follower Non-specialized contested follower Decreasing importance and currently of less relevance High and stable UK Potential follower Potential follower in rise, underestimated Follower in rise, underestimated and specialized on third period Low relevance and stable importance Average along followers, no trend India Potential follower Potential follower in rise, underestimated Follower in rise, underestimated and specialized on second period Low relevance and increasing importance Low but rising Taiwan Potential follower Contested follower, underestimated Non-specialized follower Low relevance and decreasing importance Decreasing Sweden Potential follower Potential follower in rise Follower in rise, specialized on third period Low relevance and increasing importance On average with followers Germany Potential follower Maintainer follower, of lesser relevance Follower of lesser relevance, non-specialized Low relevance and stable importance No clear pattern Finland Potential follower Maintainer follower, of lesser relevance Follower of lesser relevance, specialized on third period Low relevance and stable importance On average with followers France Potential follower Maintainer follower, of lesser relevance Follower of lesser relevance, non-specialized Low relevance and stable importance No clear pattern Canada Potential follower Maintainer follower, of lesser relevance Follower of lesser relevance, non-specialized Low relevance and increasing importance No clear pattern Russia Potential follower Maintainer follower, of lesser relevance Follower of lesser relevance, non-specialized Low relevance and decreasing importance No clear pattern Other countries Falling behind Falling behind - - Not analyzed Caption: When comparing countries within categories: Purple – very positive highlight; Light purple - positive highlight; White - neutral; Orange - negative highlight. Source: Authors' analysis based on Patstat 2020 data. The United States, while also in a forging ahead position, shows weaker leadership than South Korea. The country maintains its position as central competitor in patenting but developed its RTA more slowly, reaching only 1.01 in 2016–2018, indicating weak specialization. Moreover, its knowledge base faces challenges, both externally through reduced importance as a knowledge base and internally through declining self-citation coefficients. China, third in patenting, should be understood as a country that achieved technological catching-up and now competes with growing strength in a forging ahead position. The country shows growing relevance in patenting and strong RTA. As a reflection of its policies (Marcato, 2022 ), China has become relevant as a knowledge base for global 5G development and is rapidly increasing its self-citation coefficient, demonstrating capacity to use accumulated knowledge to generate new 5G-related inventions, challenging U.S. hegemony as a knowledge base for new technological developments. Japan, despite strong capacity to transform internal knowledge into patentable inventions, struggles internationally as Japanese knowledge base is increasingly less used by the rest of the world as a base for 5G development. While losing relevance, Japan remains the fourth largest filer of 5G-related inventions; however, given the absence of RTA, we understand this relevance for 5G architecture may result more from general innovative capacity and patenting propensity than specialization. We consider that Japan, while maintaining high innovative performance, is neither in a forging ahead position nor in catching-up process, but rather in a position likely to become falling behind from its past forging ahead status, as analysis indicates the country is losing momentum and international relevance. The United Kingdom shows enviable innovative performance as fifth largest 5G patent filer with growing relative share among follower countries. Despite potentially underestimated data, results indicate this country developed strong RTA, entering the group of specialized countries in 2016–2018. However, knowledge originating from this country has little relevance as a knowledge base. Moreover, there's no evidence its relevance as knowledge base is increasing, nor increased use of internal knowledge as driver for new inventions. Thus, even given evidence about its performance, we couldn't classify the UK as having potential for technological catching-up since this country was previously a major economic and technological power (Freeman and Soete, 1997 ) and there are no indications that UK knowledge base is relevant for 5G architecture developments. Therefore, we classify it alongside Japan as a country losing international relevance. India presents a peculiar situation: it's the sixth country by share in patenting 5G-related inventions. Along with South Korea, it was among the first countries to develop RTA in these technologies, showing even greater relative specialization than South Korea as early as 2012–2015. However, India couldn't follow the three leading countries in deepening RTA, increasing its indicator less than leaders did. Assuming uniform distribution of lexical search coverage absence across all technologies, this would mean our analysis captures approximately half of filings of 5G in this office, and since normally a patentable invention seeks intellectual property protection in its original territory, India's actual results would likely be higher than found here, and the country would be much more relevant in 5G than this analysis suggests. On the other hand, India wasn't a relevant knowledge base for 5G development in any period. The country doesn't use internal knowledge in developing its inventions, having one of the lowest self-citation coefficients. This indicator also showed an upward trend but remains quite modest. India likely acts as an executor in developing 5G technologies, using almost exclusively external knowledge for its inventions, though this scenario is gradually changing. We classify India as a country in technological catching-up stage, but with considerable progress needed in building its internal knowledge base and external reputation so the rest of the world begins using Indian knowledge as base. Sweden emerges as a 5G competitor only in the third period, but already shows RTA, demonstrating rapid specialization. This specialization may result from past 4G specialization (Andonian et al., 2018 ), with technologies patented by this country only entering 5G category in 2016–2018. This country's share in global knowledge base is somewhat more relevant and growing than follower peers, constituting 5% of global knowledge base in 2016–2018 versus modal value of 2% among peers. Since the country didn't patent in 5G architecture in first two periods, its self-citation indicator was zero but aligns with follower average in third period. Although Sweden's innovative performance is inferior to India's, we consider this country also in technological catching-up process, supported by its relevance as knowledge base. Finland shows slight growth in its 5G patenting share, specializing in the third period but nearly specialized in the second period (RTA 0.81). This country's knowledge base share is modest and has a stable self-citation indicator. Thus, Finland can be considered a follower country in 5G architecture, but evidence is weaker for catching-up, as we cannot confirm this country is approaching technological frontier performance or building relevant knowledge base for new technology development, whether for external or internal use. The rest of the world shows no relevant participation or growth in 5G-related patenting, technological advantage, or relevance as knowledge base. Therefore, based on the last period's snapshot, it seems implausible that any other country is in 5G technological catching-up process with potential to became forging ahead in subsequent technological generations. 5. Conclusion This research contributes to the literature by developing and applying a methodology for mapping the qualitative structure of academic literature, grounded in quantitative performance; by selecting highly relevant publications for qualitative analysis; by constructing a dictionary of keywords; by acknowledging the issue of language bias in the selection of information on patent applications; and by employing family-level patent application analysis as a strategy to mitigate language-related challenges in lexicographic searches. We expect the proposed methodology to be replicable in studies of inventive performance across different technologies or sectors, offering a tool to identify areas in which a given country may shift from a catching-up to a forging-ahead position. The limitations of this study are acknowledged, particularly the short time frame of the data, which, if extended, may yield different results. Methodological biases are also present, notably in the selection of key terms for lexicographic selection and in the choice of literature for qualitative analysis - both of which may be subject to critique. Additionally, the use of a lexicographic approach based solely on English-language queries may underestimate the contribution of certain countries. Suggestions for improving the methodology and ensuring its replicability across other technologies are more than welcome. This research has identified a set of evidence, based on patent data, that points to a scenario of geopolitical and knowledge base reconfiguration in the context of 5G. Japan, which led technological development in the 1G and 2G generations and remained relevant in subsequent generations, is losing momentum in 5G architecture. The technological leadership in 5G architecture has already been established. There are currently no countries capable of rivaling the triad of South Korea, the United States, and China in the development of these telecommunications technologies. South Korea is the undisputed leader in patenting inventions in this architecture. The United States, while also in a forging ahead position, holds weaker leadership than South Korea. The country maintains its position as a central competitor but with lower technological specialization, and its relevance as a knowledge base is being challenged. Alongside Japan, the United States is losing its hegemony as a knowledge base for new technological developments. The third seat of technological leadership is occupied by China, which is seen as a country that has achieved technological catching-up in telecommunications and now competes in a forging ahead position. As a result of its policies, China has become relevant as a knowledge base, challenging U.S. hegemony as the global knowledge base for new technological developments. A shift in the geopolitical landscape can be observed, as the development of these technologies is marked by multipolarisation. Evidence was also found of high knowledge cumulativeness, with countries that led previous technological generations maintaining significant relevance as knowledge bases for 5G development. It is expected that future 5G development will likely remain in the hands of the current leaders. This does not mean that the inventive dynamics in the telecommunications sector are so rigid as to prevent movement among actors. In this regard, this research has presented evidence of strong shifts among follower countries, particularly the United Kingdom, India, Sweden, and Finland, which have specialized in 5G architecture. The United Kingdom, as an old power, remains relevant in inventive performance and has technological advantage. However, no evidence was found that this country is significant as a knowledge base for developments in 5G. For a country to be forging ahead, it is not enough to have strong inventive performance; it must also exert influence and shape technological development, contributing to the definition of technological trajectories and standards. In this sense, given its low relevance as a knowledge base, the United Kingdom is now in a situation like Japan and can be understood as an empire losing its strength. India and Sweden are seen as countries in the process of technological catching-up with the potential to become forging ahead in future technological generations, possibly displacing the "Three Kingdoms." However, these countries have distinct dynamics: India shows early specialization, ranks sixth in inventive performance, and has growing - albeit modest - relevance as a knowledge base, meaning it still has little influence on 5G technological trajectory. Sweden, on the other hand, have late specialization in these technologies - possibly due to lock-in in 4G - and appears as a more relevant knowledge base than India and the United Kingdom. However, its inventive performance is inferior to these rivals, ranking eighth in patent filings. Thus, while India’s challenge in becoming forging ahead in future generations is more related to improving its internal capabilities, Sweden’s challenge lies in enhancing its inventive performance, having already overcome the "size failure" barrier (Lee, 2019 ). Finally, Finland is highly specialized in these technologies but has limited inventive performance and low relevance as knowledge base. We place it as a follower country in 5G with no evidence of being in a catching-up process with the potential to become forging ahead in future generations. Among these four specialized follower countries, none has a significant or prominent role as a knowledge base, signaling real difficulty in achieving technological leadership. The evidence from this analysis also indicates that the phenomenon of cumulativeness is relevant for catching-up and that a prerequisite for entering this process is a minimum level of productive and innovative capabilities. The identification of forging ahead and follower countries supports the understanding that catching-up is not a possibility for all but only for those that already possess a minimum level of technological development. Similarly, the identification of many countries in the falling behind group suggests that catching-up does not occur automatically and requires significant effort to achieve. Declarations Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author Contribution E.D. wrote the main manuscript text. All authors worked in the conception of the work and analysis of data. M.B. worked in the acquisition of data for the work. All authors reviewed the manuscript. M.B and J.T. worked on final approval of the version. Data Availability The data used in this study are available in the PATSTAT 2020 Spring Edition database, distributed by the World Intellectual Property Organization on a paid basis. 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(2021). Economics of technological leapfrogging. SSRN. Lee, K. (2019). The art of economic catch-up: Barriers, detours and leapfrogging in innovation systems. Cambridge University Press. Lee, K. (2013). Schumpeterian analysis of economic catch-up: Knowledge, path-creation, and the middle-income trap. Cambridge University Press. Lee, K., & Lee, J. (2020). National innovation systems, economic complexity, and economic growth: country panel analysis using the US patent data. Journal of Evolutionary Economics, 30, 897-928. https://doi.org/10.1007/s00191-019-00612-3 Lee, K., & Ki, J. H. (2017). Rise of latecomers and catch-up cycles in the world steel industry. Research Policy, 46(2), 365-375. https://doi.org/10.1016/j.respol.2016.09.010 Lee, K., & Lim, C. (2001). Technological regimes, catching-up and leapfrogging: findings from the Korean industries. Research policy, 30(3), 459-483. https://doi.org/10.1016/S0048-7333(00)00088-3 Lemstra, W. (2018). 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(2014) A internacionalização das atividades tecnológicas e a inserção dos países em desenvolvimento: uma análise baseada em dados de patentes. Doctoral dissertartion, Universidade Estadual de Campinas Mu, Q., & Lee, K. (2005). Knowledge diffusion, market segmentation and technological catch-up: The case of the telecommunication industry in China. Research policy, 34(6), 759-783. https://doi.org/10.1016/j.respol.2005.02.007 Nelson, R. R., & Rosenberg, N. (1993). Technical innovation and national systems. National innovation systems: A comparative analysis, 1, 3-21. Nelson, R. R., & Winter, Sl. (1982). An evolutionary theory of economic change. Belknap Press, Cambridge Niosi, J., Hanel, P., & Reid, S. (2012). The international diffusion of biotechnology: the arrival of developing countries. Journal of Evolutionary Economics, 22, 767-783. https://doi.org/10.1007/s00191-012-0284-2 Organization for Economic Cooperation and Development (OECD) (2009). Patent Statistics Manual Park, K. H., & Lee, K. (2006). Linking the technological regime to the technological catch-up: analyzing Korea and Taiwan using the US patent data. Industrial and corporate change, 15(4), 715-753. https://doi.org/10.1093/icc/dtl016 Parliament, E. U. (2015). Industry 4.0. Digitalisation for productivity and growth. European Parliament Think Tank Briefing. https://www.europarl.europa.eu/thinktank/en/document/EPRS_BRI(2015)568337. Accessed June 2022. Perez, C., Soete, L., Dosi, G., Freeman, C., Nelson, R., & Silverberg, G. (1988). Technical change and economic theory. Laboratory of Economics and Management (LEM), Sant’Anna School of Advanced Studies: Pisa, Italy. Prodi, G., Nicolli, F., & Frattini, F. (2020). Embeddedness and local patterns of innovation: evidence from Chinese prefectural cities. Journal of Evolutionary Economics, 30(4), 1219-1242. https://doi.org/10.1007/s00191-020-00667-7 da Silva, S. T. (2019). A tecnologia como vetor e bússola no processo de desenvolvimento chinês. Doctoral dissertarion, Universidade Estadual de Campinas. Sung, T. K., & Carlsson, B. (2003). The evolution of a technological system: the case of CNC machine tools in Korea. Journal of Evolutionary Economics, 13, 435-460. https://doi.org/10.1007/s00191-003-0160-1 Worldwide Patent Statistical Database (PATSTAT Global) (2020) 2020 Spring Edition Yu, P., Shi, J., Sadowski, B. M., & Nomaler, Ö. (2020). Catching up in the face of technological discontinuity: exploring the role of demand structure and technological regimes in the transition from 2G to 3G in China. Journal of Evolutionary Economics, 30, 815-841. https://doi.org/10.1007/s00191-020-00673-9 Additional Declarations No competing interests reported. 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13:22:57","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":183112,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7502679/v1/ac7023c8fed6ef5336c42c25.html"},{"id":92597272,"identity":"e2af642e-4506-4cc9-af28-ebc6892e01e1","added_by":"auto","created_at":"2025-10-01 13:30:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":113516,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of the number of families by inventors’ territory\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7502679/v1/d615044f6cfede7ba812f420.png"},{"id":92596430,"identity":"0117a692-b316-437f-b25d-e7e6cafedc45","added_by":"auto","created_at":"2025-10-01 13:22:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":83824,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNumber of 5G families, of the ten countries with the highest number of families\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7502679/v1/480daa90471203732d425464.png"},{"id":92596434,"identity":"8ced4b8b-5645-4545-937a-666dbaf89798","added_by":"auto","created_at":"2025-10-01 13:22:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":61801,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of patent applications by inventor’s territory, by three-year period: top three countries versus the rest of the world\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7502679/v1/4b5486bef598efc0520f678b.png"},{"id":92597275,"identity":"d51c02d3-ed6f-4715-89bb-f6a17e362797","added_by":"auto","created_at":"2025-10-01 13:30:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":80662,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of filings by inventor territory, excluding the top three countries\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7502679/v1/b770d95915d16e49717c4d5c.png"},{"id":92596435,"identity":"e310ec8d-d203-475a-b708-08fd0c56b5c3","added_by":"auto","created_at":"2025-10-01 13:22:57","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":77567,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvolution of relative country participation in total 5G-related patent families, by three-year period (excluding South Korea, the U.S., and China)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7502679/v1/a04a0f427789242c1e594171.png"},{"id":99798033,"identity":"1d1ec6f9-5c69-4e4b-8773-36229453e35a","added_by":"auto","created_at":"2026-01-08 13:47:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1599771,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7502679/v1/76431b7f-7847-4676-b467-d386f0f6c85f.pdf"},{"id":92597268,"identity":"577b3844-259f-451e-854d-2b7e3e54d626","added_by":"auto","created_at":"2025-10-01 13:30:57","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":45947,"visible":true,"origin":"","legend":"","description":"","filename":"5GCatchUpFigures.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7502679/v1/02939aaf3b96ff1ba61a9d75.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Technological Catching-up and Forging Ahead in 5G: A Patent Data Analysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMobile communication technologies have transformed social, productive, and commercial relations over the past few decades, with effects on countries\u0026rsquo; technological development and implications for technological and geopolitical disputes between nations. It is no coincidence that policymakers in various countries show great interest in the mobile communications sector, given that communication infrastructure is recognized as a cornerstone of economic development (Lemstra, 2018). This interest can be observed in the intense international competition for the development of new generations of these technologies.\u003c/p\u003e\n\u003cp\u003eSince their first commercial uses in the 1970s and 1980s, mobile communication technologies have evolved through approximately five generations, with average commercial lifespans of ten years (Farias, 2021). The competition to develop these technologies has been dynamic, with the rise and decline of competitors in relatively short periods. The development of the first generation was led by Japan (Farias, 2021), the second generation (2G) was led by Japan, the United States, and the European Community, the third generation (3G) was marked by competition between the European Community, Japan, the United States, and South Korea\u0026mdash;the latter being a latecomer in the field of computer numerically controlled tools (Sung and Carlsson, 2003) but also the pioneer in the commercial implementation of 3G (Lemstra, 2018)\u0026mdash;and the fourth generation (4G) saw the rise of Asian countries in the technological race, with South Korea in the lead, closely followed by China (Kang et al., 2014; Kim et al., 2020).\u003c/p\u003e\n\u003cp\u003eCurrently, several countries are competing to develop and define the standard for 5G architecture, the latest generation of mobile communication technologies. Despite South Korea\u0026rsquo;s technological leadership in the 4G standard, the United States and the European Union have published and implemented industrial and technological policy plans aimed at becoming leaders in developing this standard, seeking to regain their \u003cem\u003eforging ahead\u003c/em\u003e\u003ca href=\"#_ftn1\" name=\"_ftnref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e3\u003c/sup\u003e position (Parliament, 2015). Meanwhile, China has emerged as a rising competitor, moving from a follower position toward leadership in developing these technologies (Kim et al., 2020).\u003c/p\u003e\n\u003cp\u003eThe telecommunications sector has been a ground for historical processes of technological \u003cem\u003ecatching-up\u003c/em\u003e, as demonstrated by South Korea, which became a leader in the 4G standard, and China, which emerged as a follower in 4G and appears to be in a \u003cem\u003eforging ahead\u003c/em\u003e position in 5G architecture (Ariad, 2020). We contribute to the field by identifying and discussing follower countries in technological development with the potential to achieve future leadership in the mobile communications sector, considering 5G architecture as a window of opportunity. In doing so, the study aims to answer the following question: \u003cem\u003ebased on invention patent applications related to 5G architecture, which countries are acting as leaders, and which are in the process of technological catching-up?\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe aim to identify countries that were not leaders in previous technological generations but are in the process of technological \u003cem\u003ecatching-up\u003c/em\u003e in 5G architecture, with the potential to achieve a \u003cem\u003eforging ahead\u003c/em\u003e position in future technological generations. This is done through, first, defining 5G by using bibliometric methodological tools, constructing a keyword dictionary, and conducting lexicographic searches in patent databases for complex technologies. Second, our analysis is based on evidence about the quantity and evolution over time of patent application shares, technological specialization, and the development of inventive capabilities. Building on 5G architecture patent families, we assess countries\u0026apos; comparative inventive performance and identify their positions in the technological race, classifying them into the dynamics of \u003cem\u003eforging ahead\u003c/em\u003e, \u003cem\u003ecatching-up\u003c/em\u003e, and \u003cem\u003efalling behind\u003c/em\u003e. Consistent with previous findings about forging ahead nations in the telecommunications sector, the present study confirms that the \u003cem\u003eforging ahead\u003c/em\u003e position is held by the triad of South Korea, the United States, and China. Our results suggest that Japan and the United Kingdom are follower countries losing relevance in the development of this technological generation. More importantly, our findings reveal that India, Sweden, and Finland are in the process of technological \u003cem\u003ecatching-up\u003c/em\u003e in 5G architecture, with the potential to become \u003cem\u003eforging ahead\u003c/em\u003e in future technological generations.\u003c/p\u003e\n\u003cp\u003eThe paper is structured as follows. Section 2 presents the theoretical framework discussing the process of technological \u003cem\u003ecatching-up\u003c/em\u003e. Section 3 focuses on data sources and our empirical strategy. Section 4 presents empirical results. Section 5 concludes, discusses the main findings regarding international inventive dynamics in 5G, and highlights the limitations of the study.\u003c/p\u003e\n\u003cp\u003e[3] We use the terms \u003cem\u003eforging ahead\u003c/em\u003e and \u003cem\u003efalling behind\u003c/em\u003e in the sense presented by Abramovitz (1986), referring, respectively, to leading countries that push the technological frontier and to countries that are falling further behind it.\u0026nbsp;\u003c/p\u003e"},{"header":"2. Theoretical Framework","content":"\u003cp\u003eAccording to technological gap theorists, technological differences account for cross-country disparities in per capita income; international convergence cannot be assumed as a natural trend, and catching-up is not an automatic process (Abramovitz, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Antonelli and Feder, 2019; Fagerberg, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Fagerberg, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Gerschenkron, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1962\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAbramovitz (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1986\u003c/span\u003e) offers a dynamic perspective on growth rate differentials: lagging countries possess greater growth potential than leaders, but this potential materializes only if their social capabilities are sufficiently developed to exploit existing technologies. His framework focuses on relative position changes among nations, which may be forging ahead, catching-up, or falling behind. Catching-up, in Abramovitz's terms, can be understood as a race toward a moving frontier, where the initial objective is parity before competing for leadership.\u003c/p\u003e\u003cp\u003eGerschenkron (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1962\u003c/span\u003e) argues that success cannot be achieved by imitating a leading country's economic structure and demonstrates that following developed nations' trajectories does not guarantee success. Chang (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) reinforces this argument highlighting that catching-up depends on institutional context, with no clear conditions under which \"good institutions\" would lead to development.\u003c/p\u003e\u003cp\u003eLee and Lim (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) distinguish between market catching-up (increasing market share) and technological catching-up (enhancing technological capabilities). While sustained market share growth is difficult without corresponding technological advancement, technological catching-up reinforces market catching-up by supporting long-term productivity and income growth. This process is not a possibility for everyone, as it requires minimum thresholds of productive and innovative capabilities (Lee \u0026amp; Lim, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), with innovative performance determining the transition from catching-up to forging ahead (Lee, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eLee (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) argues that countries must abandon imitation and pursue alternative paths to reach productivity and income frontiers, emphasizing the fundamental importance of knowledge generation capacity. Lall (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1992\u003c/span\u003e) stresses the importance of synergies in catching-up: physical capital accumulation without corresponding skills or knowledge yields inadequate development.\u003c/p\u003e\u003cp\u003eEven when targeting the frontier, catching-up is not generalized - while leaders exhibit high productivity and income levels, their economic structures differ significantly (Fagerberg \u0026amp; Godinho, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Lee, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Malerba \u0026amp; Lee, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The catching-up process - both technological and market-oriented - is not generalized because there is no causal chain demonstrating that all sectors can simultaneously increase productivity. Literature suggests catching-up is sector-specific (Fagerberg \u0026amp; Godinho, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Perez et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) and cannot be achieved by investing generically across sectors, as leadership in one sector doesn't imply overall dominance (Lee, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This reflects the evolutionary perspective on knowledge cumulativeness and locality as characteristics of technical change. Building on the premise that firms don't explore all production possibilities (Dosi \u0026amp; Egidi, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) and that economies are complex, evolving systems (Nelson \u0026amp; Winter, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1982\u003c/span\u003e), leadership in specific technologies does not constitute a timeless global optimum transferable across activities.\u003c/p\u003e\u003cp\u003eWhile Chang (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) concludes that leading nations \"kicked away the ladder\" of development, Lee (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) argues that catching-up is possible if the country ignores the ladder, deviates from established paths, and \"fly by balloon\", leveraging latecomer advantages (Gerschenkron, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1962\u003c/span\u003e; Lee, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) to leapfrog developmental stages. According to Perez et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1988\u003c/span\u003e), catching-up requires strategic investments in key sectors, aiming to be forging ahead, though sectoral leadership only translates to global leadership if the sector has spillover potential for the broader economy.\u003c/p\u003e\u003cp\u003eThis literature seeks to identify characteristics of sectors and moments that present windows of opportunity for catching-up (Lee, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Perez et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). Following Lee (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), we define windows of opportunity as contexts where catching-up is feasible - requiring precise timing for entry. Antonelli and Feder (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) emphasize that directing technological knowledge generation to fit local structures is crucial for successful catch-up. Lee (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) notes that periods of technological maturity and stability are unfavorable for catching-up, as knowledge cumulativeness creates greater barriers for lagging countries.\u003c/p\u003e\u003cp\u003eIn catching-up processes, laggards don't follow leaders' trajectories but frequently skip stages or create new paths (Mu \u0026amp; Lee, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). This approach aligns with the leapfrogging thesis (Perez et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) which posits that new techno-economic paradigms give developing countries initial advantages in catching-up. Within new paradigms, leaders and followers start from similar positions, with leaders often constrained by technological lock-in (Lee, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), while followers face fewer such barriers. Leapfrogging involves adopting and innovating emerging technologies while circumventing investments in obsolete paradigms, aiming for leadership in new eras (Lee \u0026amp; Ki, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAll countries are beginners when new paradigms emerge, enabling laggards to leapfrog (Lee, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Since the equipment to produce the new goods hasn't been developed, generic machinery can be used for small-scale initial production, minimizing barriers. While technology performance is neither stable nor known, human resources capable of knowledge creation facilitate market entry. The optimal timing for leapfrogging coincides with techno-economic paradigm shifts, while short-cycle technology sectors offer the best venues due to more concentrated opportunity windows (Lee, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Malerba and Lee, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lee et al., 2021). Yu et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) demonstrate that during periods of technological disruptions, greater technological opportunities combined with low appropriability, and demand heterogeneity are vital for technological catching-up. Lee (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) identifies two developing-country specificities that make catching-up rare. First, \"capability failures\", associated with difficulties in building innovative capacity, and their existence justify government activism in capability development. Second, \"size failures\" - challenges in creating large firms that typically drive innovation, while smaller firms often generate only subsistence-level wages and profits.\u003c/p\u003e\u003cp\u003eFor Lundvall (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1992\u003c/span\u003e), this process doesn't occur in isolation: catching-up decisions are made at firm level but are influenced by their institutional environment. Firms operate within systems, embedded in historical, social and economic networks that shape their decisions. Absent, underdeveloped, or poorly developed institutions and organizations impair firms' decision-making capacities (Lee, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Malerba and Nelson, 2011; Malerba and Lee, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eLee (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) sought to measure innovation system performance using USPTO patent data at country, sector and firm levels, showing that East Asian countries that achieved catching-up specialized in short-cycle technologies. Lee and Lee (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) employed indicators of local knowledge creation and diffusion - including patent self-citation coefficients - to evaluate the performance of countries, finding robust evidence for the importance of knowledge localization.\u003c/p\u003e"},{"header":"3. Data and empirical strategy","content":"\u003cp\u003eGiven the objective of identifying countries undergoing technological catching-up in the context of 5G, the analysis is conducted based on indicators of technological performance. There are various ways to measure such performance, for example, through R\u0026amp;D investment; however, this variable is more suitable for a broad analysis of technological performance (Silva, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Other approaches include analysis through productivity variables and institutional quality metrics (Manca, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), though these better reflect technology adoption rather than inventive performance; and innovation surveys (Caria Junior, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), which are limited by difficulties in cross-country comparison and analysis of specific technologies. The approach chosen here is analysis based on patent application statistics, following an extensive body of literature (Archibugi and Pianta, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1994\u003c/span\u003e, Lee, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Lee \u0026amp; Lim, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Miranda, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Niosi et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Park \u0026amp; Lee, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Prodi et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to Macedo and Barbosa (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), over 70% of technological information available worldwide can only be found in patent documents, and there are numerous reasons why the technological information contained in such documents is superior to other information systems: (i) technology par excellence: patent documents store technological knowledge intended for goods production; (ii) technological classification: it is the only system configured to organize technical information by knowledge areas; (iii) complementarity: the documents contain state-of-the-art surveys; (iv) standardization and uniformity: the collections have standardized information available for long periods, enabling comparative analysis; and (v) breaking language barriers, as the information is provided in standardized and coded form, facilitating information retrieval.\u003c/p\u003e\u003cp\u003eA patent is a right granted by the state that gives the holder exclusive rights to exploit a technology (Barbosa, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In exchange for public access to this knowledge, the law grants the patent holder a time-limited right. As a state prerogative, this right is restricted to the region covered by the office that granted it. To obtain property rights in different territories, the patent application must be filed with the national offices of those territories or validated by an international office. The set of filings covering the same or similar inventions are called families. Each family has one or more filings as members, and each filing belongs to exactly one family (OECD, 2009). Furthermore, all filing applications are classified according to knowledge areas. The main international classification of knowledge areas is the International Patent Classification (IPC) (OECD, 2009), which assigns hierarchical symbols to knowledge areas. In filing applications, at least one symbol is assigned to each filing.\u003c/p\u003e\u003cp\u003eThe delimitation of the right's scope is based on a descriptive report contained in the filing document. This includes a characterization of the state of the art, made through citations to granted patents and scientific articles. Using these citations, it is possible to establish links between the inventive activity, materialized in the patent application, and the knowledge considered as the relevant basis for the development of this invention, materialized in the cited documents.\u003c/p\u003e\u003cp\u003eThere are three major possibilities for analyzing the territorial dimension of patents: (i) based on the region covered by the offices (EPO, 2020), which allows analysis of the regions where applicants seek legal protection; (ii) based on the applicant's country of residence (Chiarini and Callari, 2019), which reflects ownership of inventions; and (iii) based on the inventors' country of residence (de Rassenfosse et al., 2014), serving as an indicator of the location of technological activity.\u003c/p\u003e\u003cp\u003eDespite the advantages of using patent statistics, this is not a perfect source of information about inventive performance because not all technological efforts result in patents. There are two reasons for this: (i) because they do not result in something patentable; or (ii) due to the firm's strategic decision when considering the costs and benefits of patenting (Miranda, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Although patent performance - measured by the number of filing applications - does not perfectly reflect technological efforts, patent applications can be understood as a proxy for technological activities as they represent a significant portion of technological effort (Barbosa, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFor this research, we used patent applications filed in all offices during the period 2010\u0026ndash;2018, with data extracted from the April 2020 edition of the Worldwide Patent Statistical Database (PATSTAT 2020). We considered filed patent applications rather than just granted patents, as this option allows inclusion of the most recent years, since the publication and granting process can take up to 10 years (Miranda, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGiven the complexity of the technology in question, there are no IPC symbols capable of exclusively circumscribing 5G architecture. Under this condition of lacking a set of IPCs, we proceeded with the selection of patent applications through lexicographic search. The lexicographic search imposes its own biases on the analysis: (i) the dictionary of keywords may either underestimate or overestimate the number of filings related to a technology, either due to the choice of terms that are too broad, causing the lexicographic search to return filings unrelated to this technology, or terms that are too narrow, resulting in fewer filings than the true total; (ii) the choice of terms is affected by the researcher's prior knowledge and may therefore be biased by their beliefs about what constitutes a good dictionary; and (iii) language bias, where searching for key terms in fewer than all existing languages could underestimate the number of filings.\u003c/p\u003e\u003cp\u003eTo address the first two types of biases, the keyword dictionary was constructed through bibliometric analysis of specialized literature. This technique allows for structured literature review through computational text selection, enabling observation of the development of central concepts, themes, and most relevant authors, with the bibliometric result interpreted as a quantitative image of the qualitative knowledge structure (Aria and Cuccurullo, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). We used the Scopus database, from which we selected publications containing the terms \"5G\" and \"IEEE\" (Institute of Electrical and Electronics Engineers) in the title, abstract, keywords, or keyword-plus fields. The use of these terms is justified by the importance of this organization in publishing scientific knowledge in engineering and defining internationally accepted standards in various fields.\u003c/p\u003e\u003cp\u003eThe selection, conducted on March 18, 2022, contains 1,524 documents published between 1961 and 2022. From this, we constructed an Article (row) \u0026times; Reference (column) matrix, where a value of 1 for a given combination means that the article in the row cites the reference in the column, and 0 otherwise. The articles in the Article dimension represent the literature discussing 5G (set A), and the articles in the Reference dimension are the knowledge base used to form the Article dimension (set B). Assuming that an article's importance is directly related to its citation count, the fact that an article in set A is highly cited by the total literature is not sufficient to claim that it is central to the study and understanding of the subject, as it may be generic material. An element of set B that is highly cited by the literature is not sufficient to claim that it is central to understanding the subject, as it may simply be common background knowledge, but a member of set B that is highly cited by set A can be understood as the relevant knowledge base for the formation of set A. We define C\u0026thinsp;=\u0026thinsp;A \u0026cap; B, as the articles that form the relevant knowledge base for the literature's formation and discuss the subject in question. This set C best represents the core of the discussion, as they address the topic and substantiate its knowledge base. From C, we selected the 30 most internally cited articles by this literature for qualitative study.\u003c/p\u003e\u003cp\u003eFrom set A, we computed the absolute frequency of n-grams present in the textual fields of title, abstract, keywords, and keyword-plus. By ordering the frequency of n-gram appearance, we hypothesized that the highest-ranked n-grams are the key central terms of this literature and are relevant for characterizing 5G. Together with the qualitative study defined above, we separated the n-grams into lower forms (unigrams, bigrams, and trigrams) and extracted their roots. From this new list, we removed (i) terms with no semantic value; (ii) terms that, even in the context of 5G, may not refer exclusively to it, or that even when combined with the name \"5G\" may refer to a different and unrelated technology; and (iii) generic terms that may be related to other technologies. For these cleaning steps, we used knowledge gained from the previous qualitative study and asked the auxiliary question: \u003cem\u003e\"In a patent search containing exclusively the technology's name and this n-gram in question, would it be possible for the search to select many patents that are not truly related to this technology? If so, what types of technologies?\"\u003c/em\u003e As a result, we defined that the key terms that best represent 5G are: \u003cem\u003e5G, mobile, communication, ieee, wireless, milimetre wave, mmwave, network, bandwidth, mimo, internet, orthogonal frequency division multiplexing, ofdm, beamform, cellular, celular, radio\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThe third bias - language bias - is a complex issue to address. It would be necessary to conduct the lexicographic search in all languages, which requires significant processing time. Additionally, there is no information about the standardization of encoding textual fields in the database. For example, Lee and Lee (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) used USPTO data - one of the offices contained in Patstat - and a lexicographic search mechanism for selecting patent applications, while Prodi et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) used EPO office data to understand Chinese inventive performance. Although encoding has little effect on searches conducted in Latin encoding systems, they would not be able to locate filings written in logograms. To resolve the language bias, it would be necessary to have the dictionary perfectly translated into all languages and writing systems, with all encoding variations. As a possible strategy to overcome this obstacle, we calculated the coverage rate of patent applications that could be retrieved through lexicographic search, by office, if the lexicographic search were conducted only in English in abstracts, for filings made between 2010 and 2018 (see results in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDegree of coverage of information contained in Patstat 2020, by office.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOffice\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHas abstract in English\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHas abstract in English in the family\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHas IPC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHas IPC in the family\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHas inventors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHas inventors in the family\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUSPTO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e72%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e78%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e78%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e85%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e85%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e71%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e83%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWIPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e88%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e90%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e94%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e94%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e94%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGermany\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e94%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e75%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e81%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTaiwan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e71%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRussia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e61%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e69%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCanada\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e95%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e89%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e76%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e76%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e82%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e65%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e48%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e65%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBrazil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e96%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e96%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e71%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMexico\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUkraine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e60%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e63%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItaly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e48%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e82%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e83%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingapore\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e93%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e96%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e96%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e47%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e48%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e48%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItaly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e97%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e91%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDenmark\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e87%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHong Kong\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e93%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e97%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTurkey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e84%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e87%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e87%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth Africa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e77%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e82%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e83%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e90%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e96%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e65%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e92%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e82%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e85%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e99%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEurasia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e47%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e93%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePortugal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e93%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e96%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e96%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e82%\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e90%\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e93%\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e93%\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e90%\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e92%\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eSource: Author\u0026rsquo;s elaboration based on Patstat 2020 data.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that 82% of filings have abstracts in English (column 1). For the offices of China, WIPO, and Mexico, English lexicographic searches can correctly locate nearly all filings. There are offices with incomplete coverage, such as the USPTO, South Korea, and Russia, but there are also extreme cases, such as Brazil, Spain, Italy, South Africa, and Argentina, where there are no English abstracts, which would bias the selection. This result demonstrates that lexicographic search could underestimate the number of 5G-related filings, in different extent on each office.\u003c/p\u003e\u003cp\u003eAs an alternative to building a dictionary in all languages, we also calculated the coverage of filings that have at least one family member with an English abstract (column 2). In this case, there is a significant improvement in coverage for most offices, increasing from 82\u0026ndash;90% of the total. However, we still observe low coverage for several offices, particularly Germany, Russia, the UK, Ukraine, Italy, Poland, India, and Turkey. Given the improved coverage when considering that most filings have at least one family member in English, and that filings in a family refer to the same invention, lexicographic search remains a viable strategy, and even if an office has no filings in English, we will likely locate filings from the same family in other offices with English abstracts. We proceeded with English lexicographic searches, aware of the extent of incomplete coverage and considering this in our analysis. It should be noted that we must be cautious when interpreting results from these lower-coverage offices, as their data may be underestimated.\u003c/p\u003e\u003cp\u003eFor the final objective of this research, the necessary information from the filings are (i) application year, which defines the temporal dimension of the invention; (ii) IPCs, which define the knowledge areas; and (iii) the territories of inventor locations, which define the geographical dimension of the knowledge. We calculated the coverage rate of Patstat 2020 in the registration information of IPCs and inventors in patent applications, as well as the coverage in at least one family member (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This calculation is justified because if there is no IPC listed in the family, this would result in lower participation of the original countries of these offices in the total of inventions related to each knowledge area. We found improvements in the absence of coverage when considering the entire family, but the problem persists in families with filings made in the UK, Italy, and India offices. The IPC results for these countries should be interpreted with caution. We observed a similar pattern regarding the existence of inventor registration listed in the family versus inventors listed in the filing. In this case, we again observed low coverage for the offices of Russia, the UK, and India. Therefore, although we see improvements in coverage level when analyzing the family, we need to be particularly careful when analyzing filings made in countries where we found some form of lack of information.\u003c/p\u003e\u003cp\u003eWith these considerations, we proceeded with the English lexicographic search using the previously constructed dictionary. To avoid double counting, we used the family concept as the unit of analysis. From PATSTAT, we selected the set of 5G-related patent applications through the combinatorial search of the terms \"5G\", \"5-G\", \"5 G\" or \"fifth gen\" with each of the previously defined root keywords, in the combination of Title and Abstract fields, regardless of the order of term appearance, position, distance, and presence of suffixes or prefixes, without case sensitivity. The search resulted in 16,661 applications, from which we filtered filings of type 'A' (Direct filing) and 'W' (PCT application) that contained at least one IPC in section H (Electricity). From these deposits, we selected its families and then selected all the members of this families. Limiting the timespan of the oldest deposit to between 2010 and 2018, we obtained 5,219 families related to 5G architecture.\u003c/p\u003e\u003cp\u003eWe chose to characterize the patent family based on the characteristics of all its members. The family's filing year was given by the oldest filing's year. Following Prodi et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), the territory of origin of the family's knowledge was given by the average of the fractional counts of the territories of origin of the family's filings. At the filing level, the fractional count of territory is defined as follows: for each filing, for each territory of inventor location, the total number of inventors from that country in that filing is divided by the total number of inventors. The purpose of this calculation is to apply a weighting of the number of inventors to the knowledge required to obtain this invention. For example, if a filing has 9 inventors located in China and 1 located in Germany, we considered that China has greater relative importance in generating this invention and therefore classified this filing as 90% Chinese and 10% German.\u003c/p\u003e\u003cp\u003eTo aggregate these values to the family level, we assumed that if all filings in a family refer to the same invention, they should have the same inventors listed in all filings, and consequently, the average of the fractional counts by country per filing should equal the individual fractional count of each filing. However, given the possibility of registering different inventors in different filings in the family, the average fractional count will differ from the individual result. In this case, the average fractional count will weigh the territories of origin of the filings. For example, in a family with 2 filings, where filing 1 is 50% Chinese and 50% German, and filing 2 is 75% Chinese and 25% German, there is divergence in the fractional count. Applying the average fractional count, the family will be (50% + 75%) / 2\u0026thinsp;=\u0026thinsp;62.5% Chinese and (50% + 25%) / 2\u0026thinsp;=\u0026thinsp;37.5% German.\u003c/p\u003e"},{"header":"4. Results","content":"\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e presents the number of patent families per year of filing. Given the presence of incomplete information in patent application records, the 5,219 families identified through the lexicographic search were reduced to 3,628 analyzable families. The three-year period 2010\u0026ndash;2012 accounts for 3% of filings, 2013\u0026ndash;2015 for 23%, and 2016\u0026ndash;2018 for 74%. An increase in the share of 5G architecture-related patent applications within total patenting is also observed, indicating that the growth in filings is not the result of a generalized increase in patenting but rather by increase in propensity to patent in 5G.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCount of 5G architecture families, by year of oldest deposit\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of families\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eShare\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eShare\u003c/em\u003e in total patenting\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,01%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,01%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,01%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,32%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,01%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,04%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,07%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22,27%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,12%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33,41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,19%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17,97%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,18%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.628\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e100,00%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,07%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eSource: Author\u0026rsquo;s elaboration based on Patstat 2020 data.\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the distribution of patent families by inventor territory, based on the fractional count of inventors\u0026apos; countries of origin. Approximately 44% of the families originate from South Korea, 21% from the United States, and 16% from China, collectively accounting for 81% of the total. Given that these three countries were also the main developers of 4G, this reinforces the phenomenon of knowledge cumulativeness. The next seven most significant countries - Japan, the United Kingdom (underestimated), India (underestimated), Taiwan, Sweden, Germany, and Finland - collectively account for 13%, while the rest of the world (48 countries with some participation in filings) sums 6%. Thus, the leadership of South Korea, the United States, and China in 5G architecture development is evident.\u003c/p\u003e\n\u003cp\u003eComparing the distribution of family origins by three-year periods for the top ten countries (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), the first period (2010\u0026ndash;2012) shows unclear leadership in 5G architecture. By the second period (2013\u0026ndash;2015), South Korea emerges as the leader, a position maintained in the third period (2016\u0026ndash;2018). In the latter, the United States and China show strong participation in 5G-related patent applications. This suggests that the U.S. and China gained prominence in 5G development only in the third period.\u003c/p\u003e\n\u003cp\u003eAnalyzing the relative distribution of families from the three leading countries versus the rest of the world (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), the first period shows a significant share from other countries (60%), consistent with the lack of clear leadership observed in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. However, this period represents only 3% of total filings, suggesting that 5G architecture and technological leadership was not yet well-defined. In the second period, South Korea\u0026rsquo;s technological leadership emerges, accounting for over 50% of families, followed by the U.S. (~\u0026thinsp;20%) and China, with these three representing 80% of filings. In the third period, their dominance remains unchallenged, maintaining an 80% share, though China\u0026rsquo;s relative importance grows at the expense of South Korea, while the U.S. remains stable. This indicates that leadership is not equally tripartite and that China is becoming increasingly significant.\u003c/p\u003e\n\u003cp\u003eTo assess follower positions, the distribution of family origins was analyzed excluding the top three countries (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Among the remaining 55 countries, four (Japan, the U.K., India, and Taiwan) account for 51% of filings, while ten countries (including Sweden, Denmark, Finland, France, Canada, and Russia) represent 87%. The remaining 45 countries contribute only 13%. Given their marginal relevance compared to the three leaders, these ten countries are preliminarily classified as the follower group in 5G development, while the remaining 45 are considered falling behind or minimally relevant.\u003c/p\u003e\n\u003cp\u003eThe evolution of these ten countries\u0026rsquo; relative participation in 5G-related filings was also examined (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). There is a decline in share of Japan and in the group of the rest of the world (falling behind). The Japanese decline does not imply it is falling behind, as it remains the leader among the followers. This reinforces the idea that maintaining a leadership position does not occur automatically and is possible that Japan may further decline in innovative positioning without new strategies.\u003c/p\u003e\n\u003cp\u003eThe U.K. shows consistent growth, though its results may be underestimated due to Patstat coverage limitations. India emerges as a relevant competitor, though its performance is mixed, and its data may also be underestimated. Sweden gains prominence in 2016\u0026ndash;2018, likely driven by established telecom firms like Telia and Ericsson (Andonian et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). Taiwan, though declining, remains significant among followers, and its numbers are potentially underestimated, and its share is higher than that of the remaining five countries \u0026ndash; Germany, Finland, Frange, Canada and Russia \u0026ndash; which show no substantial growth, reinforcing that catching-up is not automatic, and innovation disparities persist in 5G development.\u003c/p\u003e\n\u003cp\u003eAt this stage, the analysis allows us to state that: (i) South Korea, the U.S., and China are the leaders in 5G architecture; (ii) Japan, the U.K., India, and Taiwan are the primary followers; (iii) Sweden may be rising as a competitor, supported by its established telecom sector; (iv) The U.K., India, Taiwan, and Sweden have the highest potential to become forging ahead due to their advanced positions among followers; (v) Japan shows signs of declining prominence, though it remains relevant; and (vi) While Germany, Finland, France, Canada, and Russia contribute to 5G-related inventions, there is no evidence suggesting they could become forging ahead.\u003c/p\u003e\n\u003cp\u003eHaving identified the technological leadership of South Korea, the United States, and China in patent applications related to 5G architecture, as well as distinguishing between follower countries with catching-up potential and those without evidence of such potential, we sought to analyze the factors determining these countries\u0026apos; positions. To this end, we examined whether the standing of these three stems from their higher patenting activity compared to the rest of the world, as a country might emerge as a leader in 5G architecture simply due to filing more patents overall, regardless of the technological field.\u003c/p\u003e\n\u003cp\u003eAs previously noted, the literature on technological gap theory conceptualizes catching-up as a typically sectoral process (Fagerberg \u0026amp; Godinho, \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e; Perez et al., \u003cspan class=\"CitationRef\"\u003e1988\u003c/span\u003e), wherein a country strives to become a leader in a specific sector, leveraging the benefits of technological leadership while generating spillover effects for the broader economy. Building on this perspective, we can correlate - without establishing causality - a country\u0026apos;s technological specialization in a sector with its pursuit of technological leadership in that sector. In this sense, while specialization may facilitate technological catch-up, it does not guarantee it. Accordingly, we employed the Revealed Technological Advantage (RTA) indicator (Guellec and De La Potterie, \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e; Sung and Carlsson, \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e), calculated as follows:\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:{RTA}_{ij}=\\frac{\\left(\\frac{{X}_{ij}}{{X}_{j}}\\right)}{\\left(\\frac{{Y}_{ij}}{{Y}_{j}}\\right)}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(1\\right)$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eWhere: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{ij}\\)\u003c/span\u003e\u003c/span\u003e = number of patent families from country \u003cem\u003ei\u003c/em\u003e in period \u003cem\u003ej\u003c/em\u003e in 5G; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{j}\\)\u003c/span\u003e\u003c/span\u003e = number of patent families from all countries in period \u003cem\u003ej\u003c/em\u003e on 5G; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Y}_{ij}\\)\u003c/span\u003e\u003c/span\u003e = number of patent families from country \u003cem\u003ei\u003c/em\u003e in period \u003cem\u003ej\u003c/em\u003e across all technological fields; and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Y}_{j}\\)\u003c/span\u003e\u003c/span\u003e = number of patent families from all countries in period \u003cem\u003ej\u003c/em\u003e across all fields.\u003c/p\u003e\n\u003cp\u003eThe relative importance of each country in patenting 5G architecture families is weighted by the relative importance of this country in total patenting. An RTA greater than 1 indicates a revealed technological advantage in 5G. If a country\u0026rsquo;s capacity to develop patentable inventions in the 5G architecture exceeds its general patenting capacity, this reflects relative specialization in 5G.\u003c/p\u003e\n\u003cp\u003eIt is important to emphasize the mathematical effect of selection bias arising from asymmetric coverage in Patstat across patent offices and countries. Unless only one country files patents in 5G architecture, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{ij}\u0026lt;\\:{X}_{j}\\)\u003c/span\u003e\u003c/span\u003e and the expression \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{X}_{ij}}{{X}_{j}}\\)\u003c/span\u003e\u003c/span\u003eis increasing for values of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{ij}\\)\u003c/span\u003e\u003c/span\u003e. Therefore, if a country \u003cem\u003ei\u003c/em\u003e has underestimated data on 5G patent families and denoting \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{ij}^{*}\\)\u003c/span\u003e\u003c/span\u003e as the value of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{ij}\\)\u003c/span\u003e\u003c/span\u003e if the information was complete, given that values of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{ij}\\)\u003c/span\u003e\u003c/span\u003e do not affect values of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Y}_{ij}\\)\u003c/span\u003e\u003c/span\u003e, we have \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{RTA}_{ij}\u0026lt;\\:{RTA}_{ij}^{*}\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eWe calculated RTA by country and three-year period for the 13 countries with the highest number of patent families (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In 2010\u0026ndash;2012, none of these countries exhibited a technological advantage in 5G (RTA\u0026thinsp;\u0026gt;\u0026thinsp;1), which is expected given the nascent stage of these technologies. In 2013\u0026ndash;2015, among the forging ahead countries, only South Korea had an RTA above 1, while the U.S. and China had RTAs below 1. This suggests that the higher relative participation of the U.S. and China in 5G development during this period may stem from their strong overall patenting activity or a broader propensity to patent, rather than specialization in these technologies, whereas South Korea\u0026apos;s leadership likely derives from specialized technological advancement.\u003c/p\u003e\n\u003cp\u003eAmong follower countries, only India (the third-largest filer) had an RTA above 1 (1.54), indicating specialization. This result is particularly significant given potential data underestimation; with complete data, India\u0026apos;s RTA might have been even higher, reflecting stronger technological specialization in telecom. The other potential catching-up followers (Japan, the U.K., Taiwan, and Sweden) did not exhibit RTA\u0026thinsp;\u0026gt;\u0026thinsp;1, and it is not possible to say whether if there were no underestimation of the data the RTA would be greater than 1, precluding preclude definitive conclusions. Among followers without catching-up potential, Germany, France, and Russia had low RTAs, making it unlikely that complete data would reveal a technological advantage. Finland and Canada also showed no signs of specialization or data underestimation in this period.\u003c/p\u003e\n\u003cp\u003eIn 2016\u0026ndash;2018, South Korea and India (already specialized) showed further RTA growth. For India, this result is especially notable given potential data underestimation. Among leaders, the U.S. reached an RTA of 1.01, barely exceeding the threshold and thus indicating minimal specialization, while China surged to 2.07, solidifying its position as a specialized leader. Among potential catching-up followers, the U.K. and Sweden joined India as specialized countries (with the U.K.\u0026apos;s data likely still underestimated). Japan and Taiwan remained unspecialized, with Japan, historically a leader in 1G and 2G, showing the lowest RTA in this group despite being the top follower in 5G patenting (see Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Finland was the only non-specialized follower to achieve RTA\u0026thinsp;\u0026gt;\u0026thinsp;1 in this period, while others (Germany, France, Canada, and Russia) maintained their positions due to general patenting capacity rather than specialization.\u003c/p\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRevealed Technological Advantage (RTA) of the top 13 fillers in 5G, by three-year period.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCountry/Period\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2010\u0026ndash;2012\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2013\u0026ndash;2015\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2016\u0026ndash;2018\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSouth Korea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1,24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2,30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1,01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2,07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJapan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1,47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1,54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1,74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTaiwan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSweden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2,59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGermany\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFinland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFrance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCanada\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRussia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Authors\u0026rsquo; elaboration based on Patstat 2020 data.\u003c/p\u003e\n\u003cp\u003eAt this point we can conclude that, for the 2016\u0026ndash;2016 period in 5G: (i) South Korea and China are specialized forging ahead countries; (ii) The U.S. is a weakly specialized forging ahead country; (iii) Japan is an unspecialized follower; (iv) India and the U.K. are specialized followers with catching-up potential (likely underestimated), potentially challenging Japan\u0026apos;s position; (v) Sweden is a rising specialized follower, possibly joining India and the U.K. as catching-up candidates; (vi) Taiwan is an unspecialized follower; and (vii) Germany, France, Canada, and Russia are unspecialized followers with lesser relevance among the analyzed countries.\u003c/p\u003e\n\u003cp\u003eWe sought to analyze the countries of origin of knowledge contributing to inventions related to 5G architecture by examining the countries of residence of inventors cited in patent families. Following a methodology like Kang et al. (\u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e), this exercise aims to understand the relevance of different countries as knowledge bases for advancements in these technologies - interpreted as a reflection of knowledge internationalization - and the importance of domestic knowledge for subsequent technological developments - understood as reflecting cumulativeness and the ability to transform internal knowledge into technological progress.\u003c/p\u003e\n\u003cp\u003eBy considering the patents cited by each 5G architecture patent family as representing the relevant knowledge base for its development, we can infer that the countries of residence of inventors listed in these cited patents indicate the geographic origins of the foundational knowledge. For example, if a patent with German origin exclusively cites patents whose inventors reside in China, we may assume that Chinese-originated knowledge formed the basis for developing that patent family. Following the same approach as in previous analyses, we applied fractional counting to determine the national origins of cited patents for each of the 3,628 5G patent families.\u003c/p\u003e\n\u003cp\u003eFrom this fractional counting of cited patents, we calculated each country\u0026apos;s proportion as a knowledge base for 5G patent families, organized by three-year periods based on the filing date of the citing family (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). For families first filed in 2010\u0026ndash;2012, 50% of cited patents in references were of U.S. origin, meaning American knowledge constituted 50% of the knowledge base for these inventions. Japanese knowledge also proved highly significant, ranking second with 15% of the knowledge base, which aligns with Japan\u0026apos;s position as a forging ahead country during 1G to 3G generations (Farias, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), making it a standard knowledge base for telecom developments. South Korea ranked third, accounting for 9% of the knowledge base. Although South Korea was forging ahead in 4G (Kim et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), its relatively modest share as a knowledge base during this period may reflect the early global development stage of 5G architecture, where initial developments likely relied more on the generalized knowledge bases of the U.S. and Japan rather than South Korea\u0026apos;s highly specialized 4G expertise. Since 5G architecture knowledge partially derives from 4G and previous technological generations and given these three countries\u0026apos; historical importance in earlier generations, these findings align with expectations.\u003c/p\u003e\n\u003cp\u003eIn the 2013\u0026ndash;2015 period, we observe a decline in the U.S. (from 50\u0026ndash;41%) and Japanese (from 15\u0026ndash;7%) shares of the knowledge base, with their combined contribution falling from 65\u0026ndash;48%. Simultaneously, South Korea\u0026apos;s knowledge base increased from 9\u0026ndash;21%, while China\u0026apos;s rose from 3\u0026ndash;7%. This demonstrates that China and South Korea are becoming more significant knowledge bases for 5G development at the expense of knowledge originating from the U.S. and Japan. This trend intensified in 2016\u0026ndash;2018, with the U.S. share declining further to 35% (a 15-point total decrease between the first and last periods). Japan similarly continued its downward trajectory, losing 9 points in importance. Meanwhile, South Korea and China increased their knowledge base importance by 13 and 9 points respectively. Notably, between the first and third periods, the combined share of South Korea and China rose from 12\u0026ndash;34%, while the U.S. and Japan\u0026apos;s combined share fell from 65\u0026ndash;41%. These new levels suggest a decline in U.S. knowledge hegemony and a potential multipolarisation of the global knowledge base centered around South Korea and China.\u003c/p\u003e\n\u003cp\u003eAmong specialized follower countries (UK, India, Sweden, and Finland), none achieved significant or prominent participation as knowledge bases in any three-year period. India showed a modest 1-point increase across periods but remained marginal at 2%. Sweden demonstrated slightly stronger growth, increasing 3 points to reach 5% of the knowledge base by 2016\u0026ndash;2018, becoming the fourth most important base. The UK and Finland maintained low participation (2% each) without growth. These four countries\u0026apos; results indicate substantial challenges in achieving technological leadership positions.\u003c/p\u003e\n\u003cp\u003eAmong non-specialized follower countries (Taiwan, Germany, France, Canada, and Russia), we found no evidence of increasing relevance as a group. The rest of the world, classified as falling behind, declined by 3-points in knowledge base participation across periods, confirming their falling behind status in knowledge production.\u003c/p\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eKnowledge base composition for 5G architecture patent families (%)s\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCountry/Triennium\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2010\u0026ndash;2012\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2013\u0026ndash;2015\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2016\u0026ndash;2018\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChange in 2010\u0026ndash;2018\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSouth Korea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;13 p.p.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-15 p.p.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;9 p.p.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJapan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9 p.p.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;1 p.p.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTaiwan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1 p.p.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSweden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;3 p.p.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGermany\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFinland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFrance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCanada\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;2 p.p.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRussia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1 p.p.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther 45 countries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3 p.p.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e100%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e100%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e100%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Authors\u0026rsquo; analysis based on Patstat 2020 data.\u003c/p\u003e\n\u003cp\u003eWe sought to understand the importance of each country\u0026apos;s native knowledge for technological development in 5G. To this end, we constructed a self-citation indicator to observe each country\u0026apos;s share in the nationality of cited patent families, by three-year period of 5G family filings. We interpret this coefficient as a potential proxy for internal capabilities (Kang et al., 2020), in the sense that a high self-citation coefficient indicates the country possesses more accumulated knowledge in related technologies and can generate new knowledge from native knowledge, being less dependent on external knowledge sources. Conversely, a low self-citation coefficient demonstrates the country\u0026apos;s dependence on external knowledge to create its patentable inventions.\u003c/p\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e presents the self-citation coefficient by country and three-year period for 5G families. For South Korea, we observe a coefficient of 36% in 2010\u0026ndash;2012, a decline between 2010\u0026ndash;2012 and 2013\u0026ndash;2015, but a recovery in 2016\u0026ndash;2018, with a net result of -1 percentage point. In all periods, this country\u0026apos;s coefficient aligns with those of the other three major patent filers (United States, China, and Japan), remaining above values observed for the rest of the world. The loss of self-citation between the first two periods may relate to the initial development stage of 5G in the first period, where South Korea likely utilized its 4G knowledge to develop its inventions. For the second period, the reduced domestic base may be associated with the growth of main competitors (United States and China), bringing new knowledge that South Korea used for its developments, possibly also explained by deepening international cooperation for 5G development. With 5G foundations established, the importance of South Korea\u0026apos;s internal knowledge grew again in the third period.\u003c/p\u003e\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u0026ndash; Self-citation coefficient of 5G families\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCountry/Triennium\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2010\u0026ndash;2012\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2013\u0026ndash;2015\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2016\u0026ndash;2018\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSouth Korea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJapan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTaiwan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSweden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGermany\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFinland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFrance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCanada\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRussia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Authors\u0026apos; analysis based on Patstat 2020 data.\u003c/p\u003e\n\u003cp\u003eWe observe a high self-citation coefficient for the United States across all periods compared to other countries, demonstrating that this country bases its 5G-related inventions primarily on internal knowledge. However, we note a decline from 66% in 2010\u0026ndash;2012 to 59% in 2013\u0026ndash;2015 and 46% in 2016\u0026ndash;2018, indicating growing dependence on knowledge from external sources. China showed a small decrease in its coefficient between the first two periods, from 18\u0026ndash;16%, but recovered its self-citation coefficient in the third period, increasing it to 34%. China is increasingly developing based on its own knowledge base. This may provide evidence supporting the success of China\u0026apos;s current and previous development initiatives, particularly the Made in China 2025 plan - an ambitious industrial modernization strategy to reduce dependence on imported technology, where China seeks to close its technological gap and promote large-scale modernization. This plan is guided by the understanding that a country\u0026apos;s core competitive strength lies in its innovative capacity (Marcato, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, Chinese companies acquire knowledge through mergers and acquisitions, startup foundations, and research and development centers (State Council, 2015 \u003cem\u003eapud\u003c/em\u003e Marcato, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), obtaining external knowledge through overseas investments supported by state intervention.\u003c/p\u003e\n\u003cp\u003eAmong followers, Japan maintains high self-citation indicators across all periods, exceeding South Korea - the 5G technological leader - in each one, demonstrating its strong capacity to transform internal knowledge into patentable inventions. However, Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e shows Japan lost share as a knowledge base and Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e reveals it lacks RTA in 5G. Japan\u0026apos;s propensity for domestic innovation may be preventing it from maintaining its past forging ahead position. According to Andonian et al. (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), by pioneering its own standards rather than collaborating internationally, Japan created a fragile ecosystem, placing it in technological lock-in reflected in average 4G speeds below developed world average. Currently, Japan shows forging ahead status in signal adoption and availability.\u003c/p\u003e\n\u003cp\u003eThe United Kingdom, a specialized follower, shows no clear trend in its self-citation coefficient, maintaining values in all periods below those of the four leading knowledge base countries and close to coefficients of other follower countries. India, a specialized follower, has the lowest self-citation coefficient in two of three periods among followers but shows continuous growth, indicating developing capacity to use internal knowledge to generate new knowledge. Sweden, another specialized follower, showed zero self-citation in the first two periods but median values among followers in the third period, suggesting absence of past specialization in 5G technologies, though this doesn\u0026apos;t preclude possible 4G specialization, reinforced by its telecom giants Telia and Ericsson. Finland shows median self-citation among followers in this period with no clear upward or downward trend. Taiwan demonstrated a decline in self-citation, showing increasing dependence on non-native knowledge for its development. For other followers, no clear patterns in self-citation coefficient evolution were identified.\u003c/p\u003e\n\u003cp\u003eThe analysis demonstrates that major countries responsible for 5G architecture-related inventions show different innovative performances, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. South Korea holds a technological forging ahead position: the country is an undisputed leader in invention patenting, was (along with India) among the first to show RTA, has growing share in the knowledge base supporting new inventions, and maintains high, stable self-citation coefficients, indicating the importance of cumulative internal knowledge for developing new patentable inventions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6 - Summary analysis of patent applications, RTA and self-citations\u003c/strong\u003e\u003c/p\u003e\n\u003ctable style=\"width:102.32%;border-collapse:collapse;border:none;\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cstrong\u003e\u003cspan style='font-size:11px;font-family: \"Times New Roman\",serif;'\u003eCountry\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:7.78%;border:solid windowtext 1.0pt;border-left: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cstrong\u003e\u003cspan style='font-size:11px;font-family: \"Times New Roman\",serif;'\u003ePatents\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border:solid windowtext 1.0pt;border-left:none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cstrong\u003e\u003cspan style='font-size:11px;font-family: \"Times New Roman\",serif;'\u003eEvolution\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border:solid windowtext 1.0pt;border-left:none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cstrong\u003e\u003cspan style='font-size:11px;font-family: \"Times New Roman\",serif;'\u003eRTA\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border:solid windowtext 1.0pt;border-left:none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cstrong\u003e\u003cspan style='font-size:11px;font-family: \"Times New Roman\",serif;'\u003eKnowledge base\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border:solid windowtext 1.0pt;border-left:none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cstrong\u003e\u003cspan style='font-size:11px;font-family: \"Times New Roman\",serif;'\u003eSelf-citations\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eSouth Korea\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:7.78%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#D86DCB;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eForging ahead\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eContested forging ahead\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#D86DCB;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cem\u003e\u003cspan style='font-size:11px;font-family: \"Times New Roman\",serif;color:black;'\u003eSpecialized forging ahead\u003c/span\u003e\u003c/em\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;on second period\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#D86DCB;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eHigh relevance and growing importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eHigh and stable\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eUS\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:7.78%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#D86DCB;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eForging ahead\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eMaintainer forging ahead\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cem\u003e\u003cspan style='font-size:11px;font-family: \"Times New Roman\",serif;color:black;'\u003eWeakly specialized forging ahead\u003c/span\u003e\u003c/em\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;on third period\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eHigh relevance and decreasing importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eHigh but declining\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eChina\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:7.78%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#D86DCB;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eForging ahead\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#D86DCB;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eForging Ahead in ascension\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#D86DCB;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cem\u003e\u003cspan style='font-size:11px;font-family: \"Times New Roman\",serif;color:black;'\u003eSpecialized forging ahead\u003c/span\u003e\u003c/em\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;on third period\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#D86DCB;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eHigh relevance and growing importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#D86DCB;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eHigh and growing\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eJapan\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:7.78%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePotential follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eContested follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eNon-specialized contested follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F6C5AC;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eDecreasing importance and currently of less relevance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eHigh and stable\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eUK\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.78%;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;height: 8.5pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePotential follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003ePotential follower in rise, underestimated\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eFollower in rise, underestimated and specialized on third period\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eLow relevance and stable importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eAverage along followers, no trend\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eIndia\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.78%;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;height: 8.5pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePotential follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003ePotential follower in rise, underestimated\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eFollower in rise, underestimated and specialized on second period\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eLow relevance and increasing importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eLow but rising\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eTaiwan\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.78%;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;height: 8.5pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePotential follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eContested follower, underestimated\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eNon-specialized follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F6C5AC;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eLow relevance and decreasing importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F6C5AC;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eDecreasing\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eSweden\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.78%;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;height: 8.5pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePotential follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003ePotential follower in rise\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eFollower in rise, specialized on third period\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eLow relevance and increasing importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eOn average with followers\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eGermany\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.78%;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;height: 8.5pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePotential follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eMaintainer follower, of lesser relevance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eFollower of lesser relevance, non-specialized\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eLow relevance and stable importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eNo clear pattern\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eFinland\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.78%;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;height: 8.5pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePotential follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eMaintainer follower, of lesser relevance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eFollower of lesser relevance, specialized on third period\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eLow relevance and stable importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eOn average with followers\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eFrance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.78%;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;height: 8.5pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePotential follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eMaintainer follower, of lesser relevance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eFollower of lesser relevance, non-specialized\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eLow relevance and stable importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eNo clear pattern\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eCanada\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.78%;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;height: 8.5pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePotential follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eMaintainer follower, of lesser relevance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eFollower of lesser relevance, non-specialized\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F2CEED;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eLow relevance and increasing importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eNo clear pattern\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eRussia\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.78%;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;height: 8.5pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePotential follower\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eMaintainer follower, of lesser relevance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eFollower of lesser relevance, non-specialized\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F6C5AC;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eLow relevance and decreasing importance\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eNo clear pattern\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:9.68%;border:solid windowtext 1.0pt;border-top: none;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eOther countries\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:7.78%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F6C5AC;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eFalling behind\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:16.48%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;background:#F6C5AC;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;color:black;'\u003eFalling behind\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:24.46%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e-\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:22.04%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e-\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:19.56%;border-top:none;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;padding:0cm 5.4pt 0cm 5.4pt;height:8.5pt;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;font-size:11.0pt;font-family:\"Aptos\",sans-serif;text-align:center;line-height:normal;'\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eNot analyzed\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCaption: When comparing countries within categories: Purple \u0026ndash; very positive highlight; Light purple - positive highlight; White - neutral; Orange - negative highlight.\u003c/p\u003e\n\u003cp\u003eSource: Authors\u0026apos; analysis based on Patstat 2020 data.\u003c/p\u003e\n\u003cp\u003eThe United States, while also in a forging ahead position, shows weaker leadership than South Korea. The country maintains its position as central competitor in patenting but developed its RTA more slowly, reaching only 1.01 in 2016\u0026ndash;2018, indicating weak specialization. Moreover, its knowledge base faces challenges, both externally through reduced importance as a knowledge base and internally through declining self-citation coefficients.\u003c/p\u003e\n\u003cp\u003eChina, third in patenting, should be understood as a country that achieved technological catching-up and now competes with growing strength in a forging ahead position. The country shows growing relevance in patenting and strong RTA. As a reflection of its policies (Marcato, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), China has become relevant as a knowledge base for global 5G development and is rapidly increasing its self-citation coefficient, demonstrating capacity to use accumulated knowledge to generate new 5G-related inventions, challenging U.S. hegemony as a knowledge base for new technological developments.\u003c/p\u003e\n\u003cp\u003eJapan, despite strong capacity to transform internal knowledge into patentable inventions, struggles internationally as Japanese knowledge base is increasingly less used by the rest of the world as a base for 5G development. While losing relevance, Japan remains the fourth largest filer of 5G-related inventions; however, given the absence of RTA, we understand this relevance for 5G architecture may result more from general innovative capacity and patenting propensity than specialization. We consider that Japan, while maintaining high innovative performance, is neither in a forging ahead position nor in catching-up process, but rather in a position likely to become falling behind from its past forging ahead status, as analysis indicates the country is losing momentum and international relevance.\u003c/p\u003e\n\u003cp\u003eThe United Kingdom shows enviable innovative performance as fifth largest 5G patent filer with growing relative share among follower countries. Despite potentially underestimated data, results indicate this country developed strong RTA, entering the group of specialized countries in 2016\u0026ndash;2018. However, knowledge originating from this country has little relevance as a knowledge base. Moreover, there\u0026apos;s no evidence its relevance as knowledge base is increasing, nor increased use of internal knowledge as driver for new inventions. Thus, even given evidence about its performance, we couldn\u0026apos;t classify the UK as having potential for technological catching-up since this country was previously a major economic and technological power (Freeman and Soete, \u003cspan class=\"CitationRef\"\u003e1997\u003c/span\u003e) and there are no indications that UK knowledge base is relevant for 5G architecture developments. Therefore, we classify it alongside Japan as a country losing international relevance.\u003c/p\u003e\n\u003cp\u003eIndia presents a peculiar situation: it\u0026apos;s the sixth country by share in patenting 5G-related inventions. Along with South Korea, it was among the first countries to develop RTA in these technologies, showing even greater relative specialization than South Korea as early as 2012\u0026ndash;2015. However, India couldn\u0026apos;t follow the three leading countries in deepening RTA, increasing its indicator less than leaders did. Assuming uniform distribution of lexical search coverage absence across all technologies, this would mean our analysis captures approximately half of filings of 5G in this office, and since normally a patentable invention seeks intellectual property protection in its original territory, India\u0026apos;s actual results would likely be higher than found here, and the country would be much more relevant in 5G than this analysis suggests. On the other hand, India wasn\u0026apos;t a relevant knowledge base for 5G development in any period. The country doesn\u0026apos;t use internal knowledge in developing its inventions, having one of the lowest self-citation coefficients. This indicator also showed an upward trend but remains quite modest. India likely acts as an executor in developing 5G technologies, using almost exclusively external knowledge for its inventions, though this scenario is gradually changing. We classify India as a country in technological catching-up stage, but with considerable progress needed in building its internal knowledge base and external reputation so the rest of the world begins using Indian knowledge as base.\u003c/p\u003e\n\u003cp\u003eSweden emerges as a 5G competitor only in the third period, but already shows RTA, demonstrating rapid specialization. This specialization may result from past 4G specialization (Andonian et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), with technologies patented by this country only entering 5G category in 2016\u0026ndash;2018. This country\u0026apos;s share in global knowledge base is somewhat more relevant and growing than follower peers, constituting 5% of global knowledge base in 2016\u0026ndash;2018 versus modal value of 2% among peers. Since the country didn\u0026apos;t patent in 5G architecture in first two periods, its self-citation indicator was zero but aligns with follower average in third period. Although Sweden\u0026apos;s innovative performance is inferior to India\u0026apos;s, we consider this country also in technological catching-up process, supported by its relevance as knowledge base.\u003c/p\u003e\n\u003cp\u003eFinland shows slight growth in its 5G patenting share, specializing in the third period but nearly specialized in the second period (RTA 0.81). This country\u0026apos;s knowledge base share is modest and has a stable self-citation indicator. Thus, Finland can be considered a follower country in 5G architecture, but evidence is weaker for catching-up, as we cannot confirm this country is approaching technological frontier performance or building relevant knowledge base for new technology development, whether for external or internal use.\u003c/p\u003e\n\u003cp\u003eThe rest of the world shows no relevant participation or growth in 5G-related patenting, technological advantage, or relevance as knowledge base. Therefore, based on the last period\u0026apos;s snapshot, it seems implausible that any other country is in 5G technological catching-up process with potential to became forging ahead in subsequent technological generations.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis research contributes to the literature by developing and applying a methodology for mapping the qualitative structure of academic literature, grounded in quantitative performance; by selecting highly relevant publications for qualitative analysis; by constructing a dictionary of keywords; by acknowledging the issue of language bias in the selection of information on patent applications; and by employing family-level patent application analysis as a strategy to mitigate language-related challenges in lexicographic searches. We expect the proposed methodology to be replicable in studies of inventive performance across different technologies or sectors, offering a tool to identify areas in which a given country may shift from a catching-up to a forging-ahead position.\u003c/p\u003e\u003cp\u003eThe limitations of this study are acknowledged, particularly the short time frame of the data, which, if extended, may yield different results. Methodological biases are also present, notably in the selection of key terms for lexicographic selection and in the choice of literature for qualitative analysis - both of which may be subject to critique. Additionally, the use of a lexicographic approach based solely on English-language queries may underestimate the contribution of certain countries. Suggestions for improving the methodology and ensuring its replicability across other technologies are more than welcome.\u003c/p\u003e\u003cp\u003eThis research has identified a set of evidence, based on patent data, that points to a scenario of geopolitical and knowledge base reconfiguration in the context of 5G. Japan, which led technological development in the 1G and 2G generations and remained relevant in subsequent generations, is losing momentum in 5G architecture.\u003c/p\u003e\u003cp\u003eThe technological leadership in 5G architecture has already been established. There are currently no countries capable of rivaling the triad of South Korea, the United States, and China in the development of these telecommunications technologies. South Korea is the undisputed leader in patenting inventions in this architecture. The United States, while also in a forging ahead position, holds weaker leadership than South Korea. The country maintains its position as a central competitor but with lower technological specialization, and its relevance as a knowledge base is being challenged. Alongside Japan, the United States is losing its hegemony as a knowledge base for new technological developments.\u003c/p\u003e\u003cp\u003eThe third seat of technological leadership is occupied by China, which is seen as a country that has achieved technological catching-up in telecommunications and now competes in a forging ahead position. As a result of its policies, China has become relevant as a knowledge base, challenging U.S. hegemony as the global knowledge base for new technological developments.\u003c/p\u003e\u003cp\u003eA shift in the geopolitical landscape can be observed, as the development of these technologies is marked by multipolarisation. Evidence was also found of high knowledge cumulativeness, with countries that led previous technological generations maintaining significant relevance as knowledge bases for 5G development. It is expected that future 5G development will likely remain in the hands of the current leaders. This does not mean that the inventive dynamics in the telecommunications sector are so rigid as to prevent movement among actors. In this regard, this research has presented evidence of strong shifts among follower countries, particularly the United Kingdom, India, Sweden, and Finland, which have specialized in 5G architecture.\u003c/p\u003e\u003cp\u003eThe United Kingdom, as an old power, remains relevant in inventive performance and has technological advantage. However, no evidence was found that this country is significant as a knowledge base for developments in 5G. For a country to be forging ahead, it is not enough to have strong inventive performance; it must also exert influence and shape technological development, contributing to the definition of technological trajectories and standards. In this sense, given its low relevance as a knowledge base, the United Kingdom is now in a situation like Japan and can be understood as an empire losing its strength.\u003c/p\u003e\u003cp\u003eIndia and Sweden are seen as countries in the process of technological catching-up with the potential to become forging ahead in future technological generations, possibly displacing the \"Three Kingdoms.\" However, these countries have distinct dynamics: India shows early specialization, ranks sixth in inventive performance, and has growing - albeit modest - relevance as a knowledge base, meaning it still has little influence on 5G technological trajectory. Sweden, on the other hand, have late specialization in these technologies - possibly due to lock-in in 4G - and appears as a more relevant knowledge base than India and the United Kingdom. However, its inventive performance is inferior to these rivals, ranking eighth in patent filings. Thus, while India\u0026rsquo;s challenge in becoming forging ahead in future generations is more related to improving its internal capabilities, Sweden\u0026rsquo;s challenge lies in enhancing its inventive performance, having already overcome the \"size failure\" barrier (Lee, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFinally, Finland is highly specialized in these technologies but has limited inventive performance and low relevance as knowledge base. We place it as a follower country in 5G with no evidence of being in a catching-up process with the potential to become forging ahead in future generations. Among these four specialized follower countries, none has a significant or prominent role as a knowledge base, signaling real difficulty in achieving technological leadership. The evidence from this analysis also indicates that the phenomenon of cumulativeness is relevant for catching-up and that a prerequisite for entering this process is a minimum level of productive and innovative capabilities.\u003c/p\u003e\u003cp\u003eThe identification of forging ahead and follower countries supports the understanding that catching-up is not a possibility for all but only for those that already possess a minimum level of technological development. Similarly, the identification of many countries in the falling behind group suggests that catching-up does not occur automatically and requires significant effort to achieve.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eE.D. wrote the main manuscript text. All authors worked in the conception of the work and analysis of data. M.B. worked in the acquisition of data for the work. All authors reviewed the manuscript. M.B and J.T. worked on final approval of the version.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data used in this study are available in the PATSTAT 2020 Spring Edition database, distributed by the World Intellectual Property Organization on a paid basis. The authors will provide the script upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbramovitz, M. (1986). Catching Up, Forging Ahead, and Falling Behind. The Journal of Economic History, 46(2), 385-406. https://doi:10.1017/S0022050700046209 \u003c/li\u003e\n\u003cli\u003eAndonian, A., Karlsson, A., \u0026amp; Nonaka, K. (2018). Japan at a Crossroads: The 4G to 5G (R) evolution. McKinsey \u0026amp; Company.\u003c/li\u003e\n\u003cli\u003eAntonelli, C., \u0026amp; Feder, C. (2020). 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Journal of Evolutionary Economics, 30, 815-841. https://doi.org/10.1007/s00191-020-00673-9\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Catch-up, Technological catching-up, Development, 5G, Telecommunications","lastPublishedDoi":"10.21203/rs.3.rs-7502679/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7502679/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper empirically examines technological leadership and the existence of countries in technological catching-up with the potential to become forging ahead at the 5G technological frontier. The analysis is based on a bibliometric approach for the qualitative study of the technologies that comprise 5G, and for the quantitative and qualitative construction of a dictionary of keywords representing such technologies. Following, patent families were taken as a proxy for the countries’ inventive performance, and a lexicographic search based on this dictionary was applied to identify 5G-related patent families, covering the period from 2010 to 2018. The results suggest a possible geopolitical and knowledge-base reconfiguration of the 5G architecture, with a tripartite and technologically specialized leadership shared by South Korea, United States, and China. While Japan and the United Kingdom are losing relevance in this architecture, our results suggest that India, Sweden, and Finland are undergoing a process of technological catching-up. Overall, the identification of forging-ahead and follower countries supports the understanding that catching-up is not a possibility for all but only for those that already possess a minimum level of technological development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJEL:\u003c/strong\u003e B40, L16, L96, O33, O57\u003c/p\u003e","manuscriptTitle":"Technological Catching-up and Forging Ahead in 5G: A Patent Data Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-01 13:22:52","doi":"10.21203/rs.3.rs-7502679/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"742b75f3-0ace-41ea-a6f4-725b44b0ef22","owner":[],"postedDate":"October 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-08T10:09:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-01 13:22:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7502679","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7502679","identity":"rs-7502679","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}