Modes, Fragmentation, and Inventor Agency: An Actor-Centered Analysis of Sri Lanka's Innovation System

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In contrast to innovation models derived from advanced economies, lagging regions often exhibit unique innovation dynamics. Analyzing 35 years of patent application data (1989–2023), we map the contributions of key actors—individual inventors, firms, universities, and government—to uncover the system's underlying structure. The findings reveal a dualistic and fragmented system. Domestic innovation is overwhelmingly driven by individual inventors, whose activities reflect a "Doing-Using-Interacting" (DUI) mode reliant on experiential and practice-based knowledge rather than formal research and development (R&D). This grassroots activity is disconnected from a corporate-led international system focused on market protection. A profound lack of collaboration among all actors highlights systemic fragmentation, constraining interactive learning and economic upgrading. Our analysis contributes to the literature by empirically demonstrating the prevalence of the DUI mode in a lagging region and provides policy insights, suggesting that support must be tailored to the system's actual, rather than assumed, innovation dynamics. JEL Classification: O31, O33, O10, O53 innovation systems lagging regions innovation modes DUI patents Sri Lanka Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 INTRODUCTION 1.1 Background Innovation is a key driver of economic development, yet its dynamics vary significantly across space. While advanced economies often rely on robust Science, Technology, and Innovation (STI) systems, structurally lagging regions face persistent challenges in translating inventive potential into sustainable growth (Rodríguez-Pose, 2013). These regions are frequently characterized by weak institutions, limited research and development (R&D) investment, and fragmented networks, making traditional innovation models poor descriptors of their reality (Tödtling & Trippl, 2005). Understanding the actual, on-the-ground innovation modes in these contexts is crucial for designing effective policy support and fostering positive economic dynamics. This paper addresses this challenge by examining the national innovation system of Sri Lanka, a quintessential example of a lagging region. We focus on identifying the dominant innovation modes by analyzing the system's micro-foundations—the behaviors and interactions of its key actors. The literature suggests that in such contexts, innovation may rely less on formal R&D and more on a "Doing-Using-Interacting" (DUI) mode, which emphasizes experiential, practice-based learning (Jensen et al., 2007; Thomä, 2017). However, there is a need for large-scale empirical evidence that maps the prevalence of these modes and their systemic implications. Traditional innovation theories, largely conceptualized in advanced economies, often presume well-developed R&D infrastructures and strong university-industry linkages (Freeman, 1987; Lundvall, 1992). Such assumptions do not hold in many developing countries, which typically feature fragmented systems and weak institutions (Crespi & Dutrénit, 2014; Lundvall et al., 2009). This study leverages a unique, 35-year dataset of patent applications in Sri Lanka to conduct an actor-centered analysis. Patents, despite their limitations, provide a valuable proxy for formal inventive activity, allowing us to map the contributions of different actors—individual inventors, firms, universities, and government—and the collaborative networks between them (Griliches, 1990). By analyzing this landscape, we aim to answer critical questions for the study of lagging regions: What are the dominant innovation modes as revealed by actor behavior? What does the structure of the innovation system tell us about its potential for economic upgrading? And what are the implications for innovation policy? Our findings reveal a dualistic and fragmented system, offering crucial insights for both theory and policy concerning innovation in lagging regions. 1.2 Sri Lankan Context Sri Lanka presents a compelling case for studying innovation in a lagging region. Despite a national ambition to transition to a knowledge-based economy, its innovation performance has consistently trailed its regional peers (IPS, 2012). This is symptomatic of low innovation inputs, including minimal R&D investment (GERD remains around 0.10% of GDP), and weak cooperation between universities, research institutions, and the private sector (NSF, 2024; Weerasinghe, Jayewardane, & Deshani, 2016). Despite a high literacy rate, enrollment in higher education, particularly in STEM fields, is low, limiting the human capital required for a dynamic innovation ecosystem (ADB, 2020). Consequently, Sri Lanka ranked 89th in the 2024 Global Innovation Index (WIPO, 2024). Addressing these constraints is essential for the country's economic aspirations (Ramanayake, 2024). The Sri Lankan experience offers valuable lessons on the interplay between institutional constraints and the potential for bottom-up innovation. Yet, a significant research gap persists regarding the specific roles and interactions of actors within the system. Most studies focus on aggregate measures, neglecting the longitudinal dynamics of patenting behavior and the individual-level actions that constitute the system's micro-foundations (Amaradasa, De Silva & Pathirage, 2002; Wickramasinghe & Ahmad, 2011). By addressing this gap, this research provides actionable insights for fostering a more resilient innovation environment. 1.3 Research Objectives and Research Questions The primary objective of this study is to identify and characterize the main features of Sri Lanka’s national innovation system by examining the roles and interactions of its key actors—individual innovators, firms, universities, and government organizations—as reflected in patent application data. The analysis aims to provide an in-depth understanding of how the agency of these actors contributes to the innovation ecosystem. To achieve this objective, the study addresses the following research questions: (a.) What are the key characteristics of Sri Lanka's innovation system as revealed by the contributions of its principal actors? (b.) How do individual inventors, firms, universities, and government organizations interact with and contribute to the national innovation system? (c.) What do the patterns of cooperation between these actors reveal about the structure and inclusiveness of the innovation system? (d.) How do the observed roles and relationships reflect the broader institutional and developmental environment of Sri Lanka? By focusing on these questions, this study seeks to develop an actor-specific portrait of the Sri Lankan innovation system, contributing to the literature on the micro-foundations of innovation in developing economies. 2 Literature Review Innovation is a critical determinant of a country's economic growth (Lundvall, 1992; Nelson, 1993). However, there is a significant disparity in the benefits that economies derive from their innovation systems. While extensive research exists on the innovation systems of advanced economies, less attention has been paid to how innovation functions in structurally underdeveloped or lagging regions (Hädrich, Reher, & Thomä, 2024; Radosevic, 1999; Intarakumnerd, Chairatana & Tangchitpiboon, 2002). It is crucial to focus on these regions, where traditional R&D-based innovation systems are often hampered by issues such as weak institutions, inadequate infrastructure, a lack of human capital, and disjointed networks. Consequently, there is a growing recognition that innovation in these settings may take different forms and follow alternative paths. This section reviews prior studies on innovation systems in lagging regions, with a special focus on theoretical constructs and empirical insights pertinent to the Sri Lankan context. The review emphasizes contributions from prominent scholars and is organized around several key themes: the conceptualization of innovation in lagging regions, the role of alternative innovation modes, the measurement of innovation using patent analysis, and the contextualization of innovation in Sri Lanka. The aim is to build a theoretical and methodological foundation for examining patent data as a window into the structure and development of Sri Lanka's national innovation system. 2.1 Innovation in Lagging Regions Lagging regions, typically characterized by lower GDP per capita, limited industrial diversification, and less innovative ecosystems, have attracted considerable scholarly interest, particularly within European regional studies (Hädrich, Reher, & Thomä, 2024; Tödtling & Trippl, 2005; Intarakumnerd, Chairatana & Tangchitpiboon, 2002). These regions often suffer from structural disadvantages, including geographic peripherality, inadequate infrastructure, lower levels of tertiary education, and weaker institutional quality (Camagni & Capello, 2013). These issues are often aggravated by economic factors such as macroeconomic instability, political uncertainty, and limited access to global markets (Rodríguez-Pose, 2013). Unlike their counterparts in innovation-leading areas, lagging regions may not follow the traditional linear model of innovation, which proceeds from R&D through to development, commercialization, and diffusion. Instead, they often adopt more context-specific innovation paths that rely on indigenous knowledge, informal networks, and pragmatic problem-solving (Reher et al., 2024; Coenen & Morgan, 2020; Chataway, Hanlin, & Kaplinsky, 2014). These alternative forms of innovation are often underrepresented in traditional metrics like R&D spending or high-tech exports, calling for new analytical frameworks that capture the diversity of innovation processes (Lundvall et al., 2009). Cantner and Pyka (2001) argue for a departure from firm-centric models when studying innovation in lagging regions. They propose a systemic approach where innovation emerges from co-evolutionary processes between heterogeneous actors within a specific institutional embedding. This is particularly relevant for contexts like Sri Lanka, where formal R&D systems are weak, and systemic interdependencies may manifest differently. Similarly, Fritsch and Graf (2010) explain how path-dependency and regional actor constellations influence innovation potential. Conceptualizing regional innovation typologies, Sternberg (2011) provides a framework for classifying how spatial and institutional conditions shape a region's innovation potential. He emphasizes that structural weaknesses, rather than just firm-level actions, are critical for interpreting the regional heterogeneity of innovation outcomes, arguing that local knowledge spillovers, social capital, and policy accommodations are crucial factors in explaining why some regions succeed while others fail. Thomä and Bizer (2013) build on these arguments by incorporating institutional and cognitive perspectives. Their empirical research suggests that firms in lagging regions often adopt informal, knowledge-based innovation strategies that are bounded by the local institutional environment. This is highly relevant to developing countries in the lagging regions, where such informal patterns may be prevalent. While these scholars have offered rich conceptualizations, there remains a scarcity of empirical studies testing these theories in non-European developing nations (Hädrich, Reher, & Thomä, 2024). Furthermore, how actor roles, institutional arrangements, and knowledge modes interact in low-R&D, low-patenting environments are subjects that remain underexplored. This study addresses this gap by examining Sri Lanka's patenting context through a systemic and contextual framework, thereby aiming to widen the generalizability of existing regional innovation theories. 2.2 Alternative Innovation Modes in Lagging Regions Innovation in lagging regions often does not follow the formalized, systematic processes common in technologically advanced areas. Instead, it frequently emerges from necessity, indigenous adaptation, or unconventional knowledge streams. Researchers have identified various types of innovation that occur outside of conventional R&D structures, including grassroots innovation, frugal innovation, user-driven innovation, and practice-based innovation (Gupta, 2012; Bessant & von Stamm, 2013; Jensen et al., 2007). In this sense, innovation in lagging regions is often characterized by a "Doing-Using-Interacting" (DUI) mode, rather than a conventional Science, Technology, and Innovation (STI) mode. As explored by scholars such as Jensen et al. (2007), Thomä (2017), and Hädrich, Reher, and Thomä (2024), the DUI mode emphasizes learning through "doing, using, and interacting" as key innovation processes. This mode highlights experiential knowledge, trial-and-error problem-solving, and collective learning among firms, users, and other actors. Thomä's (2017) empirical work illustrates that small firms in lagging areas often rely on DUI routines due to limited access to scientific research and institutional support. They innovate through incremental improvements, user feedback, and the recombination of existing knowledge within localized, trust-based networks. The DUI mode, therefore, provides an essential lens for observing innovation amidst weak formal R&D infrastructure, offering a more realistic and comprehensive account of how innovation occurs in structurally lagging settings like Sri Lanka. Thomä and Bizer (2013) suggested that the innovation strategies of actors in lagging regions are not based on formal R&D norms but on embedded, practice-based knowledge created out of necessity. This reinforces the argument that traditional innovation indicators, such as patents, may underestimate the true level of innovation in such regions. Empirical studies on small and medium enterprises highlight how informal learning, imitation, and the recombination of existing knowledge dominate innovation processes where formal R&D is scarce. Alhusen et al. (2021) emphasize the institutional embeddedness of innovation practices, contending that regional identities, informal institutions, and localized learning environments can significantly shape the direction and type of innovation. This is echoed by Sternberg and Arndt (2001), who observe that even in regions with low innovation potential, firms and individual inventors can exhibit innovative behavior by tapping into local knowledge systems and tacit know-how. Understanding these alternative modes of innovation is crucial for both policy and academic research, as it shifts the focus from R&D-led, high-tech innovation toward more inclusive and context-sensitive models. It also suggests the need for broader measures of innovation that can capture non-technological and informal activities (Mytelka & Smith, 2002). 2.3 Measuring Innovation in Lagging Regions through Patent Analysis Despite their limitations, patent statistics remain a widely used indicator of technological innovation. Patents provide measurable, standardized, and internationally comparable data that can be tracked over time to study trends in innovation output (Griliches, 1990; Jaffe & Trajtenberg, 2002). In the context of lagging regions and emerging economies, patent analysis can offer rich insights into the formation of innovation paths, sectoral patterns, and the roles of different actor types in knowledge production. However, it is well-established that official patent indicators tend to over-represent formal, science-based innovation while under-reporting the types of innovation prevalent in lagging regions, such as process innovations, informal sector activities, and adaptations of existing technologies (de Rassenfosse et al., 2013). This necessitates a careful and context-specific interpretation of patent statistics, particularly for countries like Sri Lanka where formal R&D infrastructures are not robust. Studies have shown that even in low-patenting environments, patent data can reveal important structural and evolutionary features of innovation systems. For instance, research by Bernardes and da Motta e Albuquerque (2003) on developing countries demonstrates how the profile of patent applicants (e.g., firm, university, or individual inventors) can indicate the maturity and inclusivity of a national innovation system. Similarly, Balzat and Hanusch (2004) stress the fact that innovation indicators must be interpreted in conjunction with institutional and socio-economic characteristics to uncover the determinants of technological change. Beyond simple patent counts, an examination of patent titles, technology classifications, and applicant types allows researchers to trace sectoral and actor-specific patterns of innovation (Dernis et al., 2015). Longitudinal analysis, in particular, can capture changes over time in innovation fields, such as shifts from agriculture-based innovations toward manufacturing or service-based ones. This methodology is particularly relevant to Sri Lanka, given its historical dependencies, policy shifts, and economic transformations, which have likely influenced patenting behavior. Furthermore, national patent offices in emerging countries, such as Sri Lanka's National Intellectual Property Office (NIPO), provide an authentic source of localized innovation data that complements international patent databases. Although these national datasets may have limitations, they are often more reflective of local innovation activity than international filings, which are typically dominated by multinational firms (de Rassenfosse et al., 2013). By leveraging disaggregated Sri Lankan patent data, this study aims to test the applicability of systemic and cognitive innovation theories in a structurally lagging national context. In doing so, it seeks to contribute to expanding the geographical and empirical scope of these theories, which have thus far been predominantly applied to advanced economies. 2.4 Innovation Support Mechanisms in Sri Lanka As discussed in the introduction, the impact of innovation in lagging regions is highly influenced by the policy environment and the functioning of institutional support systems (Lundvall, 1992; Nelson, 1993). As a developing economy, Sri Lanka's innovation system has undergone a series of policy reforms aimed at strengthening its STI capabilities. The country's first steps toward a national innovation policy emerged in the late 1990s, though these early efforts focused primarily on economic liberalization and infrastructure development (NASTEC, 2018). A more significant milestone was the National Science and Technology Policy of 2003, which aimed to mainstream STI into the national development strategy by stimulating research activity, private sector innovation, and human capital development (Abeytunga et al., 2023). Building on this, the National Science, Technology & Innovation Strategy (NASTEC, 2018) articulated a more integrated approach, focusing on institutional coordination, university-industry linkages, technology transfer, and entrepreneurship. The strategy explicitly recognized the need to align innovation policy with Sri Lanka's structural realities, including the prevalence of Small and Medium Enterprises (SMEs) and the necessity of fostering inclusive innovation. Various institutions play vital roles in facilitating innovation. The National Science Foundation (NSF) and the Ministry of Technology provided policy guidance, capacity development, and research grants. A recent step toward institutionalizing commercialization has been the establishment of technology transfer offices, known as University-Business Linkage (UBL) Cells, in all state universities and selected private higher education and research organizations (Abeytunga et al., 2023). Additionally, innovation centers and business incubators, such as those launched by the Information and Communication Technology Agency (ICTA) and the Colombo Science and Technology Cell at the University of Colombo, have emerged as key institutions for nurturing startups and providing venture capital, mentorship, and networks (IPS, 2020; Colombo Science and Technology Cell, 2023). Nevertheless, these institutions still face challenges related to sustainability, scalability, and connectivity with mainstream industrial sectors. Despite these policy advancements, various systemic challenges persist. Institutional fragmentation, with overlapping mandates, inadequate coordination among agencies, and limited stakeholder engagement, remains a major hurdle (Weerasinghe, Jayewardane, & Deshani, 2016). Budgetary limitations and administrative bureaucracies also hinder the effectiveness of innovation programs, as reflected in the low GERD as a percentage of GDP (Abeytunga et al., 2023). Furthermore, innovation policy has tended to favor formal R&D and high-tech sectors, often neglecting the informal innovators and SMEs that dominate Sri Lanka's economic landscape. This disconnection may limit the impact of support mechanisms on prevailing patterns of innovation, particularly in lagging areas (Radosevic, 1999). The country's relatively low patenting intensity compared to other middle-income nations indicates that policy impacts are still constrained by these structural factors. Improving innovation performance will likely require more holistic approaches that combine policy actions with sector development, human capacity enhancement, and the promotion of diverse innovation modes. The studies reviewed above highlight the multidimensional and intricate nature of innovation in lagging regions like Sri Lanka. Traditional innovation theories, largely derived from advanced economies, often fail to capture the institutional, cognitive, and socio-economic contours that shape innovation in structurally peripheral regions. As scholars like Thomä and Bizer (2013), Reher et al. (2024), Coenen and Morgan (2020), and Hädrich, Reher, and Thomä (2024) have pointed out that innovation in these regions tends to take alternative forms, deeply rooted in local knowledge systems and institutional frameworks. Patent analysis, while limited in its ability to fully represent non-R&D and informal innovations, offers a valuable quantitative lens for identifying structural patterns, actor roles, and collaboration networks within innovation systems. Existing work demonstrates the potential of longitudinal patent data to document evolutionary trends and interactions among firms, universities, and government institutions. However, significant gaps remain in the literature, particularly in empirical research using patent data to study the innovation systems of developing countries, and in understanding how actor networks and institutional environments stimulate innovation in catch-up regions. There is a need for research that combines systemic innovation theory with empirical evidence tailored to the developing economy context. This study addresses this deficiency by examining Sri Lanka's national innovation system through longitudinal patent data, tracing innovation routes, actor contributions, and cooperation networks. By using patent application data from 1989 to 2023 from Sri Lanka's NIPO, this study will provide valuable insights into how innovation activities are distributed among firms, universities, government organizations, and individual inventors, both domestically and internationally. In doing so, it aims to extend the application of systemic and cognitive innovation theories to a developing country context and provide insights for the broader debate on advancing innovation-led development in structurally disadvantaged areas. This study draws upon the principles of two influential theories: evolutionary economics and innovation systems. Synthesizing these perspectives provides a powerful analytical lens for analyzing structurally lagging regions like Sri Lanka, whose innovation trajectories are shaped by unique historical legacies, institutional arrangements, and actor interactions (Kayal, 2008; OECD, 1997). 3 Methodology 3.1 Research Design This study employed a descriptive research design to explore the main features of Sri Lanka’s national innovation system, with a focus on the roles and interactions of its key actors as reflected in patent application data. Given the focus on system-level characteristics and the constraints of the available data, the approach is primarily exploratory and descriptive, aiming to provide a rich, actor-based understanding of the Sri Lankan innovation system. 3.2 Data Sources and Collection The dataset comprises patent applications submitted to the National Intellectual Property Office (NIPO) of Sri Lanka from 1989 to 2023. This dataset was chosen for its comprehensiveness and official status, as NIPO is the sole authority responsible for patent registration and administration in Sri Lanka (NIPO, 2025; WIPO, 2017). The data, obtained directly from NIPO, cover both domestic and international filings over a 35-year period. The dataset includes the following variables for each application: application number, application date, applicant name, applicant type (coded to distinguish between local and international individual inventors, firms, universities, and government organizations, and their combinations), and the patent title. While the dataset does not include information on patent family size, citations, or commercial outcomes, it provides a robust foundation for analyzing the evolution of patenting activity, the distribution and typology of innovation actors, and patterns of collaboration as reflected in joint applications. 3.3 Rationale for Using Patent Application Data Patent data are frequently used as a reliable proxy for formal innovation and inventive activity, especially in contexts where other measures like R&D expenditure or innovation surveys are limited or unavailable (OECD, 2009; Crespi & Dutrénit, 2014). Granted-patent data from Sri Lanka have been used previously to study the country's innovation profile (Amaradasa, De Silva & Pathirage, 2002; Perera, 2014; Weerasinghe & Jayawardane, 2019). Nevertheless, it is important to acknowledge the limitations of patent data. Not all innovations are patented, and not all patents correspond to commercially significant or technologically advanced inventions; therefore, patent information does not represent the entire innovation ecosystem (Griliches, 1990; OECD, 2009). In developing economies in lagging regions like Sri Lanka, a significant portion of innovation occurs through informal modes that are not captured by formal patent applications. In this context, using patent application data is advantageous for observing the intentions and capabilities of key actors, as it captures even smaller-scale innovation activities. 3.4 Data Preparation and Coding The raw dataset was cleaned and standardized to ensure consistency in applicant names and types. Applicant type codes were cross-verified using external databases such as Google Scholar, Research Gate, WIPO Patentscope, Google Patents, and Espacenet to accurately distinguish between local and international applicants, as well as between individual inventors, companies, universities, and government organizations. In cases of joint applications involving multiple applicant types (e.g., a local university and an international company), the codes were disaggregated to allow for the analysis of collaborative patterns. Application dates were converted to a standard format, and patent titles were reviewed for completeness. No content analysis of patent titles was performed in this study, as the focus was on structural and actor-based characteristics rather than technological domains. 3.5 Analytical Methods To explore and characterize Sri Lanka’s innovation system, the following descriptive analyses were conducted: Mapping Key Actors : The patent application data were used to identify the dominant categories of actors in the system. The relative frequency and importance of each actor category (local and international individual inventors, firms, universities, and government organizations) were analyzed to describe the composition of the innovation system. Further analysis was conducted on the role and mode of participation of each actor category (e.g., the extent to which individual inventors act as primary inventors, or universities are active in patenting) (Weerasinghe & Jayawardane, 2019). Defining Collaboration and Interactions : Joint applications were examined to identify patterns of collaboration among actors. The prevalence of multi-actor applications (e.g., university–industry, local–international) was used as a proxy for formal collaborations and network formation. The analysis focused on describing the structure and frequency of these collaborations. Interpreting System Characteristics : Based on the mapping of actor roles and interactions, the study interpreted the prevailing features of the Sri Lankan innovation system. This included describing the relative dominance of certain actor types, levels of institutional diversity, cross-border and cross-sector cooperation, and the implications for the country's developmental context. 3.6 Ethical Considerations All data used in this study were gathered from open-source official records provided by NIPO. No personal or confidential information about individual inventors or institutions was used beyond what is publicly available in the patent registry. The analysis adhered to ethical guidelines for the use of administrative data in research, ensuring the privacy and integrity of the involved parties was maintained. 4 Results This section presents the main findings from the analysis of Sri Lankan patent application data from 1989 to 2023. The results are organized around the mapping of key actors, the characterization of their roles, and the description of collaboration patterns. Table 1 provides the actor codes used in the analysis. Table 1 Actor Codes and their Combinations Code Identification 1 Local Individual 2 Local Firm 3 Local University 4 Local Government Organizations 1, 2 Local Individual, Local Firm 1, 3 Local Individual, Local University 1, 4 Local Individual, Local Government Organizations 2, 3 Local Firm, Local University 2, 3, 4 Local Firm, Local University, Local Government Organizations 2, 4 Local Firm, Local Government Organizations 3, 4 Local University, Local Government Organizations 5 International Individual 6 International Firm 7 International University 8 International Government Organizations 5, 6 International Individual, International Firm 5, 8 International Individual, International Government Organizations 6, 7 International Firm, International University 6, 7, 8 International Firm, International University, International Government Organizations 6, 8 International Firm, International Government Organizations 7, 8 International University, International Government Organizations 1, 5 Local Individual, International Individual 1, 6 Local Individual, International Firm 1, 8 Local Individual, International Government Organizations 2, 6 Local Firm, International Firm 3, 7 Local University, International University 3, 8 Local University, International Government Organizations 4, 6 Local Government Organizations, International Firm 4.1 Mapping Key Actors in the Sri Lankan Innovation System The analysis reveals a distinctive composition of actors within Sri Lanka’s innovation system (Fig. 1 ). The most prominent feature is the dominance of local individual inventors, who account for the largest share of domestic patent applications (4,248 applications). This pattern is consistent with the broader context of innovation in developing economies, where formal institutional participation is often limited and inventive activity is frequently driven by individual initiative (Ferdinands, Azam, & Khatibi, 2022; Weerasinghe & Jayawardane, 2019). Local firms and universities also contribute to patenting activity, but at significantly lower levels, with 427 and 560 applications, respectively. Their collaborations appear to be minimal. The participation of local government organizations is also marginal, with only 314 applications over the entire period. In contrast, among international filers, firms (businesses and corporations) are dominant, with 6,094 applications. This reflects the strategic imperative for multinational corporations to secure IP protection for their technological assets in emerging markets (OECD, 2009). Similar to the local context, international universities (88 applications) and government organizations (201 applications) are marginal compared to firms. This divergence highlights a key structural element of Sri Lanka's innovation system: while local inventive efforts are largely person-driven, foreign activity is characterized by the institutional strength and resources of corporate actors. This suggests that Sri Lanka's innovation system is shaped by two parallel dynamics: indigenous, grassroots innovation and the global strategies of multinational firms, each with distinct implications for knowledge transfer and commercialization. Furthermore, patent applications filed collaboratively between local and international parties are extremely rare (only 10 applications in total), underscoring a lack of international R&D partnerships. Figure 2 presents the annual trends in patent applications. Figure 2a illustrates the fluctuations for local actors. Following modest growth in the 1990s, a steady increase began in the early 2000s, with sharp peaks around 2015 and 2019. The post-2019 period shows a significant downturn, suggesting a potential disruption in local innovation activity. While other local actors show stable but low trends, university applications have increased since 2018, hinting at a positive development for formal R&D. Figure 2b shows the trends for international applicants, with a sharp rise beginning in the late 1990s. Pronounced peaks are visible around 2007 and 2016, followed by a dip in 2019 and a subsequent recovery. These fluctuations suggest a strong responsiveness to global or regional factors, such as the COVID-19 pandemic, trade agreements, or shifts in the investment climate. Compared to local trends, international application trends appear more volatile. While aggregate trends provide a broad overview, examining the most frequent applicants offers deeper insight into the intensity of engagement (Figs. 3 and 4 ). Although individual inventors collectively account for the highest number of local applications, Fig. 3 shows that the most prominent single applicants are local universities, with the University of Sri Jayewardenepura (132 patents) and the University of Moratuwa (99 patents) leading the list. This indicates that while the base of individual inventors is wide, institutional applicants from the university sector exhibit more sustained engagement over time. Local firms also contribute a substantial number of applications, though generally less than universities. Government organizations, including research institutes, appear less prominently. The overall distribution suggests a local innovation landscape where universities serve as key hubs of formal knowledge production, while individuals contribute a wide but fragmented range of inventive activity. The list of top international applicants (Fig. 4 ) is clearly dominated by multinational corporations. Firms such as Janssen, Pfizer, and Novartis each filed over 190 patents, significantly surpassing any local actor in volume. The majority of top international applicants are from the pharmaceutical, chemical, and consumer goods sectors, indicating a strong interest in protecting proprietary technologies in these areas within Sri Lanka. In contrast to the local context, individual inventors and universities are absent from the top 50 international applicants, suggesting that international patenting is driven largely by commercial motives. The distribution is heavily skewed, with a small number of firms accounting for the majority of applications, reinforcing the view that global corporations use the Sri Lankan patent system primarily as a mechanism for market protection rather than collaborative innovation. 4.2 Collaboration and Interaction Patterns The analysis of joint patent applications reveals that formal collaboration is relatively rare compared to single-entity applications. Where collaborations do occur, they are most common between universities and companies or between local and international organizations, but these remain exceptions. Figure 5 depicts these patterns. Local Collaborations Collaborative activity was minimal in the early years but saw a noticeable increase in the late 1990s (Fig. 5a). However, overall local collaboration has not shown substantial growth. The most predominant partnerships are between local universities and government organizations, underscoring the role of the public sector in fostering academic knowledge production. International Collaborations International collaborations show a higher level of activity (Fig. 5b). From the mid-2000s onward, a more consistent pattern emerges. The most frequent partnerships are between international universities and firms, highlighting the importance of global industry-academia linkages. While collaborations between firms and individuals also appear, these individuals are likely employees rather than external partners. Local–International Collaborations Co-patenting activities involving both local and international actors are infrequent (Fig. 5c). Joint filings were almost non-existent until 2013, underscoring a pronounced lack of sustained cross-border partnerships. The observed instances appear to be isolated and irregular, likely reflecting individual projects rather than institutionalized networks. This highlights a significant gap in the integration of Sri Lanka’s national innovation system with global innovation networks. 5 DISCUSSION AND THEORETICAL IMPLICATIONS 5.1 Interpreting System Characteristics of Sri Lanka’s Innovation Ecosystem The findings illuminate the micro-foundations of Sri Lanka's innovation system, revealing a landscape defined by actor asymmetries and persistent fragmentation (Fagerberg & Srholec, 2008). The predominance of local individual inventors is not merely a statistical artifact; it reflects a fundamental structural dynamic wherein the agency of individual actors drives a DUI mode of innovation (Jensen et al., 2007). This DUI mode is intrinsically linked to individual agency. It signifies that innovation is propelled by experiential learning, tacit knowledge, and pragmatic problem-solving, rather than by formal R&D within organizations. The inventions of these individuals showcase human ingenuity responding to local needs and resource constraints, empirically grounding the idea that in the absence of strong institutional support, a nation's innovative capacity rests heavily on the skills and initiative of its people (Ferdinands, Azam, & Khatibi, 2022; Weerasinghe & Jayawardane, 2019). The limited role of formal organizations further emphasizes this point. While universities are emerging as important institutional innovators, their output is dwarfed by that of individuals. This suggests a bottleneck in translating academic knowledge into patented innovations. Domestic firms, constrained by limited resources, appear to engage in formal innovation even less, reinforcing the notion that the national innovation system has yet to effectively harness collective and organizational innovative capabilities. The profound lack of formal collaboration reveals another critical micro-foundation: a system of isolated actors. This fragmentation is not just an institutional failure; it is a barrier to the interactive learning, trust-building, and knowledge-sharing that is fundamental to collaborative innovation. This isolation prevents the formation of social capital and networks that could help individual inventors scale their creations (Mowery & Sampat, 2005; OECD, 2009). The disconnectedness between local innovators and international firms further illustrates this, suggesting that local talent and global corporate strategy exist in separate spheres. 5.2 Implications for Theory: Innovation in Lagging Regions The findings from this study offer significant contributions to the theoretical understanding of innovation in lagging regions, particularly by centering the analysis on the human actor and the system's micro-foundations. DUI Mode as a Dominant Innovation Pathway The Sri Lankan case provides strong empirical support for the DUI mode as a dominant innovation pathway in contexts with weak STI infrastructure (Jensen et al., 2007; Crespi & Dutrénit, 2014). It reframes the DUI mode not just as an alternative process, but as a direct expression of human agency and problem-solving capability in the face of systemic constraints. This challenges innovation models that are overly reliant on formal R&D and institutional metrics, arguing for a perspective that values experiential and practice-based knowledge (Smith, 2005; Chaminade et al., 2009). Institutional Fragmentation and the Limits of Systemic Integration Our findings illustrate how institutional fragmentation directly impacts the system's micro-foundations by limiting interaction and collaboration among actors. This aligns with innovation systems theory, which posits that system effectiveness depends on strong networks and knowledge flows (Lundvall, 1992; Edquist, 1997). The Sri Lankan case demonstrates that when these networks are weak, innovation becomes an individualized and isolated activity. This has profound implications for policy, suggesting that building "soft infrastructure"—such as trust, networks, and collaborative platforms—is as important as funding formal R&D. Connecting Micro-Level Agency to Macro-Level Outcomes This study provides a clear link between micro-level behavior (the agency of individual inventors) and macro-level development patterns. The reliance on individual, often informal, innovation helps explain why Sri Lanka, despite its human potential, struggles to translate inventive activity into broad-based economic upgrading. This supports the call to connect the actions and characteristics of individuals to the innovation and development trajectories of regions and nations. In summary, the Sri Lankan experience confirms that any theory of innovation for lagging regions must be grounded in an understanding of the human actors who navigate and shape their institutional environments. It highlights the need for research approaches that can capture both formal and informal innovative activities and the complex interplay between human agency and systemic constraints. 5.3 Limitations and Directions for Future Research While this study offers novel insights, several limitations must be acknowledged. First, the exclusive reliance on patent applications inherently overlooks a substantial portion of innovative activity. The informal, practice-based contributions that constitute a core micro-foundation of innovation in this context—driven by the agency of individuals and communities—are not formally patented and thus remain invisible to this analysis (Smith, 2005; Crespi & Dutrénit, 2014). Second, the dataset does not capture the full spectrum of collaborative arrangements. Many university–industry or firm–firm partnerships that do not result in joint patent filings, such as exclusive licensing or informal knowledge exchange, are not reflected. As such, the prevalence of collaboration, a key actor-level activity, may be systematically underestimated (Colombo Science and Technology Cell, 2023; Abeytunga et al., 2023). Third, patent data provide limited information about the technological content, novelty, or commercial value of inventions. The study cannot distinguish between high-impact and incremental filings, nor can it assess the downstream economic or societal effects of the ingenuity captured in these patents (OECD, 2009; Smith, 2005). Fourth, the analysis is descriptive, focusing on mapping actors and relationships rather than establishing causal links. While this approach is appropriate for the study's exploratory objectives, it limits the generalizability of findings and the ability to make precise policy prescriptions. Future research should address these limitations by incorporating mixed methods. Innovation surveys, case studies, and interviews with key stakeholders (innovators, entrepreneurs, policymakers, etc.) are needed to capture non-patented and informal innovation activities. Such qualitative approaches would provide a richer understanding of the motivations, networks, and challenges that define the micro-foundations of innovation in Sri Lanka. Comparative studies with other developing economies would also help situate the Sri Lankan experience within broader regional patterns. Finally, research on the impact of recent policy initiatives, such as technology transfer offices and innovation hubs, would be valuable for assessing their effectiveness in supporting and integrating the country's diverse innovators. 6 Conclusion This actor-centered analysis of Sri Lanka's patent landscape reveals that the national innovation system is fundamentally shaped by its micro-foundations, particularly the agency of its human actors. The findings highlight a distinctive dual character. On one hand, domestic inventive activity is dominated by individual inventors, whose work exemplifies a "Doing-Using-Interacting" (DUI) mode of innovation grounded in practical experience rather than formal R&D (Jensen et al., 2007; Weerasinghe & Jayawardane, 2019). This underscores the resilience and creativity of individuals within a constrained institutional environment. While universities are emerging as important institutional players, the overall system struggles to bridge the gap between individual human capital and organized, collaborative innovation. On the other hand, the international dimension is led by multinational corporations using the patent system primarily for market protection, with little interaction with local actors (OECD, 2009). This creates a structural disconnect between the bottom-up, agency-driven innovation of locals and the top-down, strategic behavior of global firms. A critical finding is the profound lack of formal collaboration, which points to a fragmented system where the potential for interactive learning is not fully realized. This isolation hinders knowledge transfer and systemic integration, features consistent with the literature on lagging regions (Fagerberg & Srholec, 2008; Crespi & Dutrénit, 2014). These findings directly address our research questions by painting a portrait of the Sri Lankan innovation system as one defined by the predominance of individual actors, a growing but still secondary role for universities, and weak collaborative networks. This picture, however, is based on formal patent data and thus only reveals part of the story. The vibrant, unpatented, and informal innovative activities driven by human agency across the country remain largely "invisible" but are no less important. While systemic constraints are evident, Sri Lanka's innovation system possesses significant latent potential rooted in its people. To unlock this potential, policy must evolve beyond a narrow focus on formal STI metrics. It must recognize, support, and integrate the diverse human actors who are the true engines of innovation. This requires building "soft infrastructure" to foster trust and collaboration, creating platforms that connect individual inventors with firms and markets, and valuing the informal and practice-based knowledge that drives development from the ground up. Future research must continue to explore these micro-foundations to build a more complete and nuanced understanding of Sri Lanka’s innovation landscape. Declarations Author Contribution All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Gnei Shuraiya Amath, Yasushi Hara. The first draft of the manuscript was written by Gnei Shuraiya Amath and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgement This work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number 25K00660. The author also acknowledges the financial support received from the Japanese Government (MEXT) Scholarship. Data Availability The datasets generated during and/or analysed during the study are available from the corresponding author on reasonable request. References Abeytunga, D. T. U., Aturupane, H., Madhusanka, P. N., Liyanage, P. A. M., & Cooray, N.G. (2023). Strengthening technology and knowledge transfer from Sri Lankan universities by the establishment of University Business Linkage Cells. Sri Lanka Journal of Social Sciences , 46(2), 177-196. https://doi.org/10.4038/sljss.v46i02.8574 Alhusen, H., Bennat, T., Bizer, K., Cantner, U., Horstmann, E., Kalthaus, M., Proeger, T., Sternberg, R., & Töpfer, S. (2021). A new measurement conception for the ‘Doing-Using-Interacting’ mode of innovation. 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Proceedings of the International Conference on Business Management , University of Sri Jayewardenepura. Retrieved on May 14, 2025 from https://journals.sjp.ac.lk/index.php/icbm/article/view/2980/2051 Wickramasinghe, C. N., & Ahmad, N. (2011). Influence of demographic and technical profile on success of independent inventors in Sri Lanka. The Journal of World Intellectual Property , 15(5), 365-378. https://doi.org/10.1111/jwip.12000 World Intellectual Property Organization (WIPO). (2017). Overview of the patent system and procedure in Sri Lanka . Retrieved on June 03, 2025 from https://www.wipo.int/edocs/mdocs/aspac/en/wipo_ip_cmb_17/wipo_ip_cmb_17_1.pdf World Intellectual Property Organization (WIPO). (2024). Sri Lanka Ranking in the Global Innovation Index 2024 . Retrieved on June 05, 2025 from https://www.wipo.int/gii-ranking/en/sri-lanka Additional Declarations No competing interests reported. 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5","display":"","copyAsset":false,"role":"figure","size":137259,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFrequency of Joint Patent Applications by Actor Combinations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(Source: developed by Author)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7000389/v1/582ca552879e50b0fa03da90.png"},{"id":94473875,"identity":"4691a93f-52e5-42fe-b6e7-e4b2e0f8040a","added_by":"auto","created_at":"2025-10-27 15:46:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1696557,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7000389/v1/b9533b05-a2d8-4f02-86c4-d3be400a3099.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Modes, Fragmentation, and Inventor Agency: An Actor-Centered Analysis of Sri Lanka's Innovation System","fulltext":[{"header":"1 INTRODUCTION","content":"\u003ch2\u003e1.1\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Background\u003c/h2\u003e\n\u003cp\u003eInnovation is a key driver of economic development, yet its dynamics vary significantly across space. While advanced economies often rely on robust Science, Technology, and Innovation (STI) systems, structurally lagging regions face persistent challenges in translating inventive potential into sustainable growth (Rodríguez-Pose, 2013). These regions are frequently characterized by weak institutions, limited research and development (R\u0026amp;D) investment, and fragmented networks, making traditional innovation models poor descriptors of their reality (Tödtling \u0026amp; Trippl, 2005). Understanding the actual, on-the-ground innovation modes in these contexts is crucial for designing effective policy support and fostering positive economic dynamics.\u003c/p\u003e\n\u003cp\u003eThis paper addresses this challenge by examining the national innovation system of Sri Lanka, a quintessential example of a lagging region. We focus on identifying the dominant innovation modes by analyzing the system's micro-foundations—the behaviors and interactions of its key actors. The literature suggests that in such contexts, innovation may rely less on formal R\u0026amp;D and more on a \"Doing-Using-Interacting\" (DUI) mode, which emphasizes experiential, practice-based learning (Jensen et al., 2007; Thomä, 2017). However, there is a need for large-scale empirical evidence that maps the prevalence of these modes and their systemic implications. Traditional innovation theories, largely conceptualized in advanced economies, often presume well-developed R\u0026amp;D infrastructures and strong university-industry linkages (Freeman, 1987; Lundvall, 1992). Such assumptions do not hold in many developing countries, which typically feature fragmented systems and weak institutions (Crespi \u0026amp; Dutrénit, 2014; Lundvall et al., 2009).\u003c/p\u003e\n\u003cp\u003eThis study leverages a unique, 35-year dataset of patent applications in Sri Lanka to conduct an actor-centered analysis. Patents, despite their limitations, provide a valuable proxy for formal inventive activity, allowing us to map the contributions of different actors—individual inventors, firms, universities, and government—and the collaborative networks between them (Griliches, 1990). By analyzing this landscape, we aim to answer critical questions for the study of lagging regions: What are the dominant innovation modes as revealed by actor behavior? What does the structure of the innovation system tell us about its potential for economic upgrading? And what are the implications for innovation policy? Our findings reveal a dualistic and fragmented system, offering crucial insights for both theory and policy concerning innovation in lagging regions.\u003c/p\u003e\n\u003ch2\u003e1.2\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Sri Lankan Context\u003c/h2\u003e\n\u003cp\u003eSri Lanka presents a compelling case for studying innovation in a lagging region. Despite a national ambition to transition to a knowledge-based economy, its innovation performance has consistently trailed its regional peers (IPS, 2012). This is symptomatic of low innovation inputs, including minimal R\u0026amp;D investment (GERD remains around 0.10% of GDP), and weak cooperation between universities, research institutions, and the private sector (NSF, 2024; Weerasinghe, Jayewardane, \u0026amp; Deshani, 2016). Despite a high literacy rate, enrollment in higher education, particularly in STEM fields, is low, limiting the human capital required for a dynamic innovation ecosystem (ADB, 2020). Consequently, Sri Lanka ranked 89th in the 2024 Global Innovation Index (WIPO, 2024).\u003c/p\u003e\n\u003cp\u003eAddressing these constraints is essential for the country's economic aspirations (Ramanayake, 2024). The Sri Lankan experience offers valuable lessons on the interplay between institutional constraints and the potential for bottom-up innovation. Yet, a significant research gap persists regarding the specific roles and interactions of actors within the system. Most studies focus on aggregate measures, neglecting the longitudinal dynamics of patenting behavior and the individual-level actions that constitute the system's micro-foundations (Amaradasa, De Silva \u0026amp; Pathirage, 2002; Wickramasinghe \u0026amp; Ahmad, 2011). By addressing this gap, this research provides actionable insights for fostering a more resilient innovation environment.\u003c/p\u003e\n\u003ch2\u003e1.3\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Research Objectives and Research Questions\u003c/h2\u003e\n\u003cp\u003eThe primary objective of this study is to identify and characterize the main features of Sri Lanka’s national innovation system by examining the roles and interactions of its key actors—individual innovators, firms, universities, and government organizations—as reflected in patent application data. The analysis aims to provide an in-depth understanding of how the agency of these actors contributes to the innovation ecosystem.\u003c/p\u003e\n\u003cp\u003eTo achieve this objective, the study addresses the following research questions:\u003c/p\u003e\n\u003cp\u003e(a.)\u0026nbsp;\u0026nbsp;What are the key characteristics of Sri Lanka's innovation system as revealed by the contributions of its principal actors?\u003c/p\u003e\n\u003cp\u003e(b.)\u0026nbsp;\u0026nbsp;How do individual inventors, firms, universities, and government organizations interact with and contribute to the national innovation system?\u003c/p\u003e\n\u003cp\u003e(c.)\u0026nbsp;\u0026nbsp;What do the patterns of cooperation between these actors reveal about the structure and inclusiveness of the innovation system?\u003c/p\u003e\n\u003cp\u003e(d.)\u0026nbsp;\u0026nbsp;How do the observed roles and relationships reflect the broader institutional and developmental environment of Sri Lanka?\u003c/p\u003e\n\u003cp\u003eBy focusing on these questions, this study seeks to develop an actor-specific portrait of the Sri Lankan innovation system, contributing to the literature on the micro-foundations of innovation in developing economies.\u003c/p\u003e"},{"header":"2 Literature Review","content":"\u003cp\u003eInnovation is a critical determinant of a country's economic growth (Lundvall, 1992; Nelson, 1993). However, there is a significant disparity in the benefits that economies derive from their innovation systems. While extensive research exists on the innovation systems of advanced economies, less attention has been paid to how innovation functions in structurally underdeveloped or lagging regions (H\u0026auml;drich, Reher, \u0026amp; Thom\u0026auml;, 2024; Radosevic, 1999; Intarakumnerd, Chairatana \u0026amp; Tangchitpiboon, 2002). It is crucial to focus on these regions, where traditional R\u0026amp;D-based innovation systems are often hampered by issues such as weak institutions, inadequate infrastructure, a lack of human capital, and disjointed networks. Consequently, there is a growing recognition that innovation in these settings may take different forms and follow alternative paths. This section reviews prior studies on innovation systems in lagging regions, with a special focus on theoretical constructs and empirical insights pertinent to the Sri Lankan context. The review emphasizes contributions from prominent scholars and is organized around several key themes: the conceptualization of innovation in lagging regions, the role of alternative innovation modes, the measurement of innovation using patent analysis, and the contextualization of innovation in Sri Lanka. The aim is to build a theoretical and methodological foundation for examining patent data as a window into the structure and development of Sri Lanka's national innovation system.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Innovation in Lagging Regions\u003c/h2\u003e\u003cp\u003eLagging regions, typically characterized by lower GDP per capita, limited industrial diversification, and less innovative ecosystems, have attracted considerable scholarly interest, particularly within European regional studies (H\u0026auml;drich, Reher, \u0026amp; Thom\u0026auml;, 2024; T\u0026ouml;dtling \u0026amp; Trippl, 2005; Intarakumnerd, Chairatana \u0026amp; Tangchitpiboon, 2002). These regions often suffer from structural disadvantages, including geographic peripherality, inadequate infrastructure, lower levels of tertiary education, and weaker institutional quality (Camagni \u0026amp; Capello, 2013). These issues are often aggravated by economic factors such as macroeconomic instability, political uncertainty, and limited access to global markets (Rodr\u0026iacute;guez-Pose, 2013).\u003c/p\u003e\u003cp\u003eUnlike their counterparts in innovation-leading areas, lagging regions may not follow the traditional linear model of innovation, which proceeds from R\u0026amp;D through to development, commercialization, and diffusion. Instead, they often adopt more context-specific innovation paths that rely on indigenous knowledge, informal networks, and pragmatic problem-solving (Reher et al., 2024; Coenen \u0026amp; Morgan, 2020; Chataway, Hanlin, \u0026amp; Kaplinsky, 2014). These alternative forms of innovation are often underrepresented in traditional metrics like R\u0026amp;D spending or high-tech exports, calling for new analytical frameworks that capture the diversity of innovation processes (Lundvall et al., 2009).\u003c/p\u003e\u003cp\u003eCantner and Pyka (2001) argue for a departure from firm-centric models when studying innovation in lagging regions. They propose a systemic approach where innovation emerges from co-evolutionary processes between heterogeneous actors within a specific institutional embedding. This is particularly relevant for contexts like Sri Lanka, where formal R\u0026amp;D systems are weak, and systemic interdependencies may manifest differently. Similarly, Fritsch and Graf (2010) explain how path-dependency and regional actor constellations influence innovation potential.\u003c/p\u003e\u003cp\u003eConceptualizing regional innovation typologies, Sternberg (2011) provides a framework for classifying how spatial and institutional conditions shape a region's innovation potential. He emphasizes that structural weaknesses, rather than just firm-level actions, are critical for interpreting the regional heterogeneity of innovation outcomes, arguing that local knowledge spillovers, social capital, and policy accommodations are crucial factors in explaining why some regions succeed while others fail. Thom\u0026auml; and Bizer (2013) build on these arguments by incorporating institutional and cognitive perspectives. Their empirical research suggests that firms in lagging regions often adopt informal, knowledge-based innovation strategies that are bounded by the local institutional environment. This is highly relevant to developing countries in the lagging regions, where such informal patterns may be prevalent.\u003c/p\u003e\u003cp\u003eWhile these scholars have offered rich conceptualizations, there remains a scarcity of empirical studies testing these theories in non-European developing nations (H\u0026auml;drich, Reher, \u0026amp; Thom\u0026auml;, 2024). Furthermore, how actor roles, institutional arrangements, and knowledge modes interact in low-R\u0026amp;D, low-patenting environments are subjects that remain underexplored. This study addresses this gap by examining Sri Lanka's patenting context through a systemic and contextual framework, thereby aiming to widen the generalizability of existing regional innovation theories.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Alternative Innovation Modes in Lagging Regions\u003c/h2\u003e\u003cp\u003eInnovation in lagging regions often does not follow the formalized, systematic processes common in technologically advanced areas. Instead, it frequently emerges from necessity, indigenous adaptation, or unconventional knowledge streams. Researchers have identified various types of innovation that occur outside of conventional R\u0026amp;D structures, including grassroots innovation, frugal innovation, user-driven innovation, and practice-based innovation (Gupta, 2012; Bessant \u0026amp; von Stamm, 2013; Jensen et al., 2007). In this sense, innovation in lagging regions is often characterized by a \"Doing-Using-Interacting\" (DUI) mode, rather than a conventional Science, Technology, and Innovation (STI) mode.\u003c/p\u003e\u003cp\u003eAs explored by scholars such as Jensen et al. (2007), Thom\u0026auml; (2017), and H\u0026auml;drich, Reher, and Thom\u0026auml; (2024), the DUI mode emphasizes learning through \"doing, using, and interacting\" as key innovation processes. This mode highlights experiential knowledge, trial-and-error problem-solving, and collective learning among firms, users, and other actors. Thom\u0026auml;'s (2017) empirical work illustrates that small firms in lagging areas often rely on DUI routines due to limited access to scientific research and institutional support. They innovate through incremental improvements, user feedback, and the recombination of existing knowledge within localized, trust-based networks. The DUI mode, therefore, provides an essential lens for observing innovation amidst weak formal R\u0026amp;D infrastructure, offering a more realistic and comprehensive account of how innovation occurs in structurally lagging settings like Sri Lanka.\u003c/p\u003e\u003cp\u003eThom\u0026auml; and Bizer (2013) suggested that the innovation strategies of actors in lagging regions are not based on formal R\u0026amp;D norms but on embedded, practice-based knowledge created out of necessity. This reinforces the argument that traditional innovation indicators, such as patents, may underestimate the true level of innovation in such regions. Empirical studies on small and medium enterprises highlight how informal learning, imitation, and the recombination of existing knowledge dominate innovation processes where formal R\u0026amp;D is scarce.\u003c/p\u003e\u003cp\u003eAlhusen et al. (2021) emphasize the institutional embeddedness of innovation practices, contending that regional identities, informal institutions, and localized learning environments can significantly shape the direction and type of innovation. This is echoed by Sternberg and Arndt (2001), who observe that even in regions with low innovation potential, firms and individual inventors can exhibit innovative behavior by tapping into local knowledge systems and tacit know-how. Understanding these alternative modes of innovation is crucial for both policy and academic research, as it shifts the focus from R\u0026amp;D-led, high-tech innovation toward more inclusive and context-sensitive models. It also suggests the need for broader measures of innovation that can capture non-technological and informal activities (Mytelka \u0026amp; Smith, 2002).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Measuring Innovation in Lagging Regions through Patent Analysis\u003c/h2\u003e\u003cp\u003eDespite their limitations, patent statistics remain a widely used indicator of technological innovation. Patents provide measurable, standardized, and internationally comparable data that can be tracked over time to study trends in innovation output (Griliches, 1990; Jaffe \u0026amp; Trajtenberg, 2002). In the context of lagging regions and emerging economies, patent analysis can offer rich insights into the formation of innovation paths, sectoral patterns, and the roles of different actor types in knowledge production.\u003c/p\u003e\u003cp\u003eHowever, it is well-established that official patent indicators tend to over-represent formal, science-based innovation while under-reporting the types of innovation prevalent in lagging regions, such as process innovations, informal sector activities, and adaptations of existing technologies (de Rassenfosse et al., 2013). This necessitates a careful and context-specific interpretation of patent statistics, particularly for countries like Sri Lanka where formal R\u0026amp;D infrastructures are not robust.\u003c/p\u003e\u003cp\u003eStudies have shown that even in low-patenting environments, patent data can reveal important structural and evolutionary features of innovation systems. For instance, research by Bernardes and da Motta e Albuquerque (2003) on developing countries demonstrates how the profile of patent applicants (e.g., firm, university, or individual inventors) can indicate the maturity and inclusivity of a national innovation system. Similarly, Balzat and Hanusch (2004) stress the fact that innovation indicators must be interpreted in conjunction with institutional and socio-economic characteristics to uncover the determinants of technological change.\u003c/p\u003e\u003cp\u003eBeyond simple patent counts, an examination of patent titles, technology classifications, and applicant types allows researchers to trace sectoral and actor-specific patterns of innovation (Dernis et al., 2015). Longitudinal analysis, in particular, can capture changes over time in innovation fields, such as shifts from agriculture-based innovations toward manufacturing or service-based ones. This methodology is particularly relevant to Sri Lanka, given its historical dependencies, policy shifts, and economic transformations, which have likely influenced patenting behavior.\u003c/p\u003e\u003cp\u003eFurthermore, national patent offices in emerging countries, such as Sri Lanka's National Intellectual Property Office (NIPO), provide an authentic source of localized innovation data that complements international patent databases. Although these national datasets may have limitations, they are often more reflective of local innovation activity than international filings, which are typically dominated by multinational firms (de Rassenfosse et al., 2013). By leveraging disaggregated Sri Lankan patent data, this study aims to test the applicability of systemic and cognitive innovation theories in a structurally lagging national context. In doing so, it seeks to contribute to expanding the geographical and empirical scope of these theories, which have thus far been predominantly applied to advanced economies.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Innovation Support Mechanisms in Sri Lanka\u003c/h2\u003e\u003cp\u003eAs discussed in the introduction, the impact of innovation in lagging regions is highly influenced by the policy environment and the functioning of institutional support systems (Lundvall, 1992; Nelson, 1993). As a developing economy, Sri Lanka's innovation system has undergone a series of policy reforms aimed at strengthening its STI capabilities. The country's first steps toward a national innovation policy emerged in the late 1990s, though these early efforts focused primarily on economic liberalization and infrastructure development (NASTEC, 2018).\u003c/p\u003e\u003cp\u003eA more significant milestone was the National Science and Technology Policy of 2003, which aimed to mainstream STI into the national development strategy by stimulating research activity, private sector innovation, and human capital development (Abeytunga et al., 2023). Building on this, the National Science, Technology \u0026amp; Innovation Strategy (NASTEC, 2018) articulated a more integrated approach, focusing on institutional coordination, university-industry linkages, technology transfer, and entrepreneurship. The strategy explicitly recognized the need to align innovation policy with Sri Lanka's structural realities, including the prevalence of Small and Medium Enterprises (SMEs) and the necessity of fostering inclusive innovation.\u003c/p\u003e\u003cp\u003eVarious institutions play vital roles in facilitating innovation. The National Science Foundation (NSF) and the Ministry of Technology provided policy guidance, capacity development, and research grants. A recent step toward institutionalizing commercialization has been the establishment of technology transfer offices, known as University-Business Linkage (UBL) Cells, in all state universities and selected private higher education and research organizations (Abeytunga et al., 2023). Additionally, innovation centers and business incubators, such as those launched by the Information and Communication Technology Agency (ICTA) and the Colombo Science and Technology Cell at the University of Colombo, have emerged as key institutions for nurturing startups and providing venture capital, mentorship, and networks (IPS, 2020; Colombo Science and Technology Cell, 2023). Nevertheless, these institutions still face challenges related to sustainability, scalability, and connectivity with mainstream industrial sectors.\u003c/p\u003e\u003cp\u003eDespite these policy advancements, various systemic challenges persist. Institutional fragmentation, with overlapping mandates, inadequate coordination among agencies, and limited stakeholder engagement, remains a major hurdle (Weerasinghe, Jayewardane, \u0026amp; Deshani, 2016). Budgetary limitations and administrative bureaucracies also hinder the effectiveness of innovation programs, as reflected in the low GERD as a percentage of GDP (Abeytunga et al., 2023). Furthermore, innovation policy has tended to favor formal R\u0026amp;D and high-tech sectors, often neglecting the informal innovators and SMEs that dominate Sri Lanka's economic landscape. This disconnection may limit the impact of support mechanisms on prevailing patterns of innovation, particularly in lagging areas (Radosevic, 1999). The country's relatively low patenting intensity compared to other middle-income nations indicates that policy impacts are still constrained by these structural factors. Improving innovation performance will likely require more holistic approaches that combine policy actions with sector development, human capacity enhancement, and the promotion of diverse innovation modes.\u003c/p\u003e\u003cp\u003eThe studies reviewed above highlight the multidimensional and intricate nature of innovation in lagging regions like Sri Lanka. Traditional innovation theories, largely derived from advanced economies, often fail to capture the institutional, cognitive, and socio-economic contours that shape innovation in structurally peripheral regions. As scholars like Thom\u0026auml; and Bizer (2013), Reher et al. (2024), Coenen and Morgan (2020), and H\u0026auml;drich, Reher, and Thom\u0026auml; (2024) have pointed out that innovation in these regions tends to take alternative forms, deeply rooted in local knowledge systems and institutional frameworks. Patent analysis, while limited in its ability to fully represent non-R\u0026amp;D and informal innovations, offers a valuable quantitative lens for identifying structural patterns, actor roles, and collaboration networks within innovation systems. Existing work demonstrates the potential of longitudinal patent data to document evolutionary trends and interactions among firms, universities, and government institutions.\u003c/p\u003e\u003cp\u003eHowever, significant gaps remain in the literature, particularly in empirical research using patent data to study the innovation systems of developing countries, and in understanding how actor networks and institutional environments stimulate innovation in catch-up regions. There is a need for research that combines systemic innovation theory with empirical evidence tailored to the developing economy context. This study addresses this deficiency by examining Sri Lanka's national innovation system through longitudinal patent data, tracing innovation routes, actor contributions, and cooperation networks. By using patent application data from 1989 to 2023 from Sri Lanka's NIPO, this study will provide valuable insights into how innovation activities are distributed among firms, universities, government organizations, and individual inventors, both domestically and internationally. In doing so, it aims to extend the application of systemic and cognitive innovation theories to a developing country context and provide insights for the broader debate on advancing innovation-led development in structurally disadvantaged areas.\u003c/p\u003e\u003cp\u003eThis study draws upon the principles of two influential theories: evolutionary economics and innovation systems. Synthesizing these perspectives provides a powerful analytical lens for analyzing structurally lagging regions like Sri Lanka, whose innovation trajectories are shaped by unique historical legacies, institutional arrangements, and actor interactions (Kayal, 2008; OECD, 1997).\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Methodology","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Research Design\u003c/h2\u003e\u003cp\u003eThis study employed a descriptive research design to explore the main features of Sri Lanka\u0026rsquo;s national innovation system, with a focus on the roles and interactions of its key actors as reflected in patent application data. Given the focus on system-level characteristics and the constraints of the available data, the approach is primarily exploratory and descriptive, aiming to provide a rich, actor-based understanding of the Sri Lankan innovation system.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Data Sources and Collection\u003c/h2\u003e\u003cp\u003eThe dataset comprises patent applications submitted to the National Intellectual Property Office (NIPO) of Sri Lanka from 1989 to 2023. This dataset was chosen for its comprehensiveness and official status, as NIPO is the sole authority responsible for patent registration and administration in Sri Lanka (NIPO, 2025; WIPO, 2017). The data, obtained directly from NIPO, cover both domestic and international filings over a 35-year period. The dataset includes the following variables for each application: application number, application date, applicant name, applicant type (coded to distinguish between local and international individual inventors, firms, universities, and government organizations, and their combinations), and the patent title. While the dataset does not include information on patent family size, citations, or commercial outcomes, it provides a robust foundation for analyzing the evolution of patenting activity, the distribution and typology of innovation actors, and patterns of collaboration as reflected in joint applications.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Rationale for Using Patent Application Data\u003c/h2\u003e\u003cp\u003ePatent data are frequently used as a reliable proxy for formal innovation and inventive activity, especially in contexts where other measures like R\u0026amp;D expenditure or innovation surveys are limited or unavailable (OECD, 2009; Crespi \u0026amp; Dutr\u0026eacute;nit, 2014). Granted-patent data from Sri Lanka have been used previously to study the country's innovation profile (Amaradasa, De Silva \u0026amp; Pathirage, 2002; Perera, 2014; Weerasinghe \u0026amp; Jayawardane, 2019).\u003c/p\u003e\u003cp\u003eNevertheless, it is important to acknowledge the limitations of patent data. Not all innovations are patented, and not all patents correspond to commercially significant or technologically advanced inventions; therefore, patent information does not represent the entire innovation ecosystem (Griliches, 1990; OECD, 2009). In developing economies in lagging regions like Sri Lanka, a significant portion of innovation occurs through informal modes that are not captured by formal patent applications. In this context, using patent application data is advantageous for observing the intentions and capabilities of key actors, as it captures even smaller-scale innovation activities.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Data Preparation and Coding\u003c/h2\u003e\u003cp\u003eThe raw dataset was cleaned and standardized to ensure consistency in applicant names and types. Applicant type codes were cross-verified using external databases such as Google Scholar, Research Gate, WIPO Patentscope, Google Patents, and Espacenet to accurately distinguish between local and international applicants, as well as between individual inventors, companies, universities, and government organizations. In cases of joint applications involving multiple applicant types (e.g., a local university and an international company), the codes were disaggregated to allow for the analysis of collaborative patterns. Application dates were converted to a standard format, and patent titles were reviewed for completeness. No content analysis of patent titles was performed in this study, as the focus was on structural and actor-based characteristics rather than technological domains.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Analytical Methods\u003c/h2\u003e\u003cp\u003eTo explore and characterize Sri Lanka\u0026rsquo;s innovation system, the following descriptive analyses were conducted:\u003c/p\u003e\u003cp\u003e\u003cb\u003eMapping Key Actors\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eThe patent application data were used to identify the dominant categories of actors in the system. The relative frequency and importance of each actor category (local and international individual inventors, firms, universities, and government organizations) were analyzed to describe the composition of the innovation system. Further analysis was conducted on the role and mode of participation of each actor category (e.g., the extent to which individual inventors act as primary inventors, or universities are active in patenting) (Weerasinghe \u0026amp; Jayawardane, 2019).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDefining Collaboration and Interactions\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eJoint applications were examined to identify patterns of collaboration among actors. The prevalence of multi-actor applications (e.g., university\u0026ndash;industry, local\u0026ndash;international) was used as a proxy for formal collaborations and network formation. The analysis focused on describing the structure and frequency of these collaborations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInterpreting System Characteristics\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eBased on the mapping of actor roles and interactions, the study interpreted the prevailing features of the Sri Lankan innovation system. This included describing the relative dominance of certain actor types, levels of institutional diversity, cross-border and cross-sector cooperation, and the implications for the country's developmental context.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Ethical Considerations\u003c/h2\u003e\u003cp\u003eAll data used in this study were gathered from open-source official records provided by NIPO. No personal or confidential information about individual inventors or institutions was used beyond what is publicly available in the patent registry. The analysis adhered to ethical guidelines for the use of administrative data in research, ensuring the privacy and integrity of the involved parties was maintained.\u003c/p\u003e\u003c/div\u003e"},{"header":"4 Results","content":"\u003cp\u003eThis section presents the main findings from the analysis of Sri Lankan patent application data from 1989 to 2023. The results are organized around the mapping of key actors, the characterization of their roles, and the description of collaboration patterns. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides the actor codes used in the analysis.\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\u003eActor Codes and their Combinations\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCode\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIdentification\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Individual\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Firm\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;University\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1, 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Individual, Local\u0026nbsp;Firm\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1, 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Individual,\u0026nbsp;Local\u0026nbsp;University\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1, 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Individual, Local\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2, 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Firm,\u0026nbsp;Local\u0026nbsp;University\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2, 3, 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Firm,\u0026nbsp;Local\u0026nbsp;University,\u0026nbsp;Local\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2, 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Firm,\u0026nbsp;Local\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3, 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;University, Local\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational\u0026nbsp;Individual\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational\u0026nbsp;Firm\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational\u0026nbsp;University\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5, 6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational\u0026nbsp;Individual, International\u0026nbsp;Firm\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5, 8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational\u0026nbsp;Individual, International\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6, 7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational\u0026nbsp;Firm,\u0026nbsp;International\u0026nbsp;University\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6, 7, 8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational\u0026nbsp;Firm,\u0026nbsp;International\u0026nbsp;University,\u0026nbsp;International\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6, 8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational\u0026nbsp;Firm,\u0026nbsp;International\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7, 8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational\u0026nbsp;University, International\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1, 5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Individual, International\u0026nbsp;Individual\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1, 6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Individual, International\u0026nbsp;Firm\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1, 8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Individual, International\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2, 6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Firm, International\u0026nbsp;Firm\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3, 7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;University, International\u0026nbsp;University\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3, 8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;University, International\u0026nbsp;Government Organizations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4, 6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocal\u0026nbsp;Government Organizations, International\u0026nbsp;Firm\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Mapping Key Actors in the Sri Lankan Innovation System\u003c/h2\u003e\u003cp\u003eThe analysis reveals a distinctive composition of actors within Sri Lanka\u0026rsquo;s innovation system (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The most prominent feature is the dominance of local individual inventors, who account for the largest share of domestic patent applications (4,248 applications). This pattern is consistent with the broader context of innovation in developing economies, where formal institutional participation is often limited and inventive activity is frequently driven by individual initiative (Ferdinands, Azam, \u0026amp; Khatibi, 2022; Weerasinghe \u0026amp; Jayawardane, 2019).\u003c/p\u003e\u003cp\u003eLocal firms and universities also contribute to patenting activity, but at significantly lower levels, with 427 and 560 applications, respectively. Their collaborations appear to be minimal. The participation of local government organizations is also marginal, with only 314 applications over the entire period.\u003c/p\u003e\u003cp\u003eIn contrast, among international filers, firms (businesses and corporations) are dominant, with 6,094 applications. This reflects the strategic imperative for multinational corporations to secure IP protection for their technological assets in emerging markets (OECD, 2009). Similar to the local context, international universities (88 applications) and government organizations (201 applications) are marginal compared to firms. This divergence highlights a key structural element of Sri Lanka's innovation system: while local inventive efforts are largely person-driven, foreign activity is characterized by the institutional strength and resources of corporate actors. This suggests that Sri Lanka's innovation system is shaped by two parallel dynamics: indigenous, grassroots innovation and the global strategies of multinational firms, each with distinct implications for knowledge transfer and commercialization. Furthermore, patent applications filed collaboratively between local and international parties are extremely rare (only 10 applications in total), underscoring a lack of international R\u0026amp;D partnerships.\u003c/p\u003e\u003cp\u003eFigure 2 presents the annual trends in patent applications. Figure\u0026nbsp;2a illustrates the fluctuations for local actors. Following modest growth in the 1990s, a steady increase began in the early 2000s, with sharp peaks around 2015 and 2019. The post-2019 period shows a significant downturn, suggesting a potential disruption in local innovation activity. While other local actors show stable but low trends, university applications have increased since 2018, hinting at a positive development for formal R\u0026amp;D.\u003c/p\u003e\u003cp\u003eFigure 2b shows the trends for international applicants, with a sharp rise beginning in the late 1990s. Pronounced peaks are visible around 2007 and 2016, followed by a dip in 2019 and a subsequent recovery. These fluctuations suggest a strong responsiveness to global or regional factors, such as the COVID-19 pandemic, trade agreements, or shifts in the investment climate. Compared to local trends, international application trends appear more volatile.\u003c/p\u003e\u003cp\u003eWhile aggregate trends provide a broad overview, examining the most frequent applicants offers deeper insight into the intensity of engagement (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Although individual inventors collectively account for the highest number of local applications, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that the most prominent single applicants are local universities, with the University of Sri Jayewardenepura (132 patents) and the University of Moratuwa (99 patents) leading the list. This indicates that while the base of individual inventors is wide, institutional applicants from the university sector exhibit more sustained engagement over time. Local firms also contribute a substantial number of applications, though generally less than universities. Government organizations, including research institutes, appear less prominently. The overall distribution suggests a local innovation landscape where universities serve as key hubs of formal knowledge production, while individuals contribute a wide but fragmented range of inventive activity.\u003c/p\u003e\u003cp\u003eThe list of top international applicants (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e) is clearly dominated by multinational corporations. Firms such as Janssen, Pfizer, and Novartis each filed over 190 patents, significantly surpassing any local actor in volume. The majority of top international applicants are from the pharmaceutical, chemical, and consumer goods sectors, indicating a strong interest in protecting proprietary technologies in these areas within Sri Lanka. In contrast to the local context, individual inventors and universities are absent from the top 50 international applicants, suggesting that international patenting is driven largely by commercial motives. The distribution is heavily skewed, with a small number of firms accounting for the majority of applications, reinforcing the view that global corporations use the Sri Lankan patent system primarily as a mechanism for market protection rather than collaborative innovation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Collaboration and Interaction Patterns\u003c/h2\u003e\u003cp\u003eThe analysis of joint patent applications reveals that formal collaboration is relatively rare compared to single-entity applications. Where collaborations do occur, they are most common between universities and companies or between local and international organizations, but these remain exceptions. Figure\u0026nbsp;5 depicts these patterns.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLocal Collaborations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCollaborative activity was minimal in the early years but saw a noticeable increase in the late 1990s (Fig.\u0026nbsp;5a). However, overall local collaboration has not shown substantial growth. The most predominant partnerships are between local universities and government organizations, underscoring the role of the public sector in fostering academic knowledge production.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInternational Collaborations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eInternational collaborations show a higher level of activity (Fig.\u0026nbsp;5b). From the mid-2000s onward, a more consistent pattern emerges. The most frequent partnerships are between international universities and firms, highlighting the importance of global industry-academia linkages. While collaborations between firms and individuals also appear, these individuals are likely employees rather than external partners.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLocal\u0026ndash;International Collaborations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCo-patenting activities involving both local and international actors are infrequent (Fig.\u0026nbsp;5c). Joint filings were almost non-existent until 2013, underscoring a pronounced lack of sustained cross-border partnerships. The observed instances appear to be isolated and irregular, likely reflecting individual projects rather than institutionalized networks. This highlights a significant gap in the integration of Sri Lanka\u0026rsquo;s national innovation system with global innovation networks.\u003c/p\u003e\u003c/div\u003e"},{"header":"5 DISCUSSION AND THEORETICAL IMPLICATIONS","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e5.1 Interpreting System Characteristics of Sri Lanka\u0026rsquo;s Innovation Ecosystem\u003c/h2\u003e\u003cp\u003eThe findings illuminate the micro-foundations of Sri Lanka's innovation system, revealing a landscape defined by actor asymmetries and persistent fragmentation (Fagerberg \u0026amp; Srholec, 2008). The predominance of local individual inventors is not merely a statistical artifact; it reflects a fundamental structural dynamic wherein the agency of individual actors drives a DUI mode of innovation (Jensen et al., 2007).\u003c/p\u003e\u003cp\u003eThis DUI mode is intrinsically linked to individual agency. It signifies that innovation is propelled by experiential learning, tacit knowledge, and pragmatic problem-solving, rather than by formal R\u0026amp;D within organizations. The inventions of these individuals showcase human ingenuity responding to local needs and resource constraints, empirically grounding the idea that in the absence of strong institutional support, a nation's innovative capacity rests heavily on the skills and initiative of its people (Ferdinands, Azam, \u0026amp; Khatibi, 2022; Weerasinghe \u0026amp; Jayawardane, 2019).\u003c/p\u003e\u003cp\u003eThe limited role of formal organizations further emphasizes this point. While universities are emerging as important institutional innovators, their output is dwarfed by that of individuals. This suggests a bottleneck in translating academic knowledge into patented innovations. Domestic firms, constrained by limited resources, appear to engage in formal innovation even less, reinforcing the notion that the national innovation system has yet to effectively harness collective and organizational innovative capabilities.\u003c/p\u003e\u003cp\u003eThe profound lack of formal collaboration reveals another critical micro-foundation: a system of isolated actors. This fragmentation is not just an institutional failure; it is a barrier to the interactive learning, trust-building, and knowledge-sharing that is fundamental to collaborative innovation. This isolation prevents the formation of social capital and networks that could help individual inventors scale their creations (Mowery \u0026amp; Sampat, 2005; OECD, 2009). The disconnectedness between local innovators and international firms further illustrates this, suggesting that local talent and global corporate strategy exist in separate spheres.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e5.2 Implications for Theory: Innovation in Lagging Regions\u003c/h2\u003e\u003cp\u003eThe findings from this study offer significant contributions to the theoretical understanding of innovation in lagging regions, particularly by centering the analysis on the human actor and the system's micro-foundations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDUI Mode as a Dominant Innovation Pathway\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe Sri Lankan case provides strong empirical support for the DUI mode as a dominant innovation pathway in contexts with weak STI infrastructure (Jensen et al., 2007; Crespi \u0026amp; Dutr\u0026eacute;nit, 2014). It reframes the DUI mode not just as an alternative process, but as a direct expression of human agency and problem-solving capability in the face of systemic constraints. This challenges innovation models that are overly reliant on formal R\u0026amp;D and institutional metrics, arguing for a perspective that values experiential and practice-based knowledge (Smith, 2005; Chaminade et al., 2009).\u003c/p\u003e\u003cp\u003e\u003cb\u003eInstitutional Fragmentation and the Limits of Systemic Integration\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur findings illustrate how institutional fragmentation directly impacts the system's micro-foundations by limiting interaction and collaboration among actors. This aligns with innovation systems theory, which posits that system effectiveness depends on strong networks and knowledge flows (Lundvall, 1992; Edquist, 1997). The Sri Lankan case demonstrates that when these networks are weak, innovation becomes an individualized and isolated activity. This has profound implications for policy, suggesting that building \"soft infrastructure\"\u0026mdash;such as trust, networks, and collaborative platforms\u0026mdash;is as important as funding formal R\u0026amp;D.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConnecting Micro-Level Agency to Macro-Level Outcomes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study provides a clear link between micro-level behavior (the agency of individual inventors) and macro-level development patterns. The reliance on individual, often informal, innovation helps explain why Sri Lanka, despite its human potential, struggles to translate inventive activity into broad-based economic upgrading. This supports the call to connect the actions and characteristics of individuals to the innovation and development trajectories of regions and nations.\u003c/p\u003e\u003cp\u003eIn summary, the Sri Lankan experience confirms that any theory of innovation for lagging regions must be grounded in an understanding of the human actors who navigate and shape their institutional environments. It highlights the need for research approaches that can capture both formal and informal innovative activities and the complex interplay between human agency and systemic constraints.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e5.3 Limitations and Directions for Future Research\u003c/h2\u003e\u003cp\u003eWhile this study offers novel insights, several limitations must be acknowledged. First, the exclusive reliance on patent applications inherently overlooks a substantial portion of innovative activity. The informal, practice-based contributions that constitute a core micro-foundation of innovation in this context\u0026mdash;driven by the agency of individuals and communities\u0026mdash;are not formally patented and thus remain invisible to this analysis (Smith, 2005; Crespi \u0026amp; Dutr\u0026eacute;nit, 2014).\u003c/p\u003e\u003cp\u003eSecond, the dataset does not capture the full spectrum of collaborative arrangements. Many university\u0026ndash;industry or firm\u0026ndash;firm partnerships that do not result in joint patent filings, such as exclusive licensing or informal knowledge exchange, are not reflected. As such, the prevalence of collaboration, a key actor-level activity, may be systematically underestimated (Colombo Science and Technology Cell, 2023; Abeytunga et al., 2023).\u003c/p\u003e\u003cp\u003eThird, patent data provide limited information about the technological content, novelty, or commercial value of inventions. The study cannot distinguish between high-impact and incremental filings, nor can it assess the downstream economic or societal effects of the ingenuity captured in these patents (OECD, 2009; Smith, 2005).\u003c/p\u003e\u003cp\u003eFourth, the analysis is descriptive, focusing on mapping actors and relationships rather than establishing causal links. While this approach is appropriate for the study's exploratory objectives, it limits the generalizability of findings and the ability to make precise policy prescriptions.\u003c/p\u003e\u003cp\u003eFuture research should address these limitations by incorporating mixed methods. Innovation surveys, case studies, and interviews with key stakeholders (innovators, entrepreneurs, policymakers, etc.) are needed to capture non-patented and informal innovation activities. Such qualitative approaches would provide a richer understanding of the motivations, networks, and challenges that define the micro-foundations of innovation in Sri Lanka. Comparative studies with other developing economies would also help situate the Sri Lankan experience within broader regional patterns. Finally, research on the impact of recent policy initiatives, such as technology transfer offices and innovation hubs, would be valuable for assessing their effectiveness in supporting and integrating the country's diverse innovators.\u003c/p\u003e\u003c/div\u003e"},{"header":"6 Conclusion","content":"\u003cp\u003eThis actor-centered analysis of Sri Lanka's patent landscape reveals that the national innovation system is fundamentally shaped by its micro-foundations, particularly the agency of its human actors. The findings highlight a distinctive dual character. On one hand, domestic inventive activity is dominated by individual inventors, whose work exemplifies a \"Doing-Using-Interacting\" (DUI) mode of innovation grounded in practical experience rather than formal R\u0026amp;D (Jensen et al., 2007; Weerasinghe \u0026amp; Jayawardane, 2019). This underscores the resilience and creativity of individuals within a constrained institutional environment. While universities are emerging as important institutional players, the overall system struggles to bridge the gap between individual human capital and organized, collaborative innovation.\u003c/p\u003e\u003cp\u003eOn the other hand, the international dimension is led by multinational corporations using the patent system primarily for market protection, with little interaction with local actors (OECD, 2009). This creates a structural disconnect between the bottom-up, agency-driven innovation of locals and the top-down, strategic behavior of global firms. A critical finding is the profound lack of formal collaboration, which points to a fragmented system where the potential for interactive learning is not fully realized. This isolation hinders knowledge transfer and systemic integration, features consistent with the literature on lagging regions (Fagerberg \u0026amp; Srholec, 2008; Crespi \u0026amp; Dutr\u0026eacute;nit, 2014).\u003c/p\u003e\u003cp\u003eThese findings directly address our research questions by painting a portrait of the Sri Lankan innovation system as one defined by the predominance of individual actors, a growing but still secondary role for universities, and weak collaborative networks. This picture, however, is based on formal patent data and thus only reveals part of the story. The vibrant, unpatented, and informal innovative activities driven by human agency across the country remain largely \"invisible\" but are no less important.\u003c/p\u003e\u003cp\u003eWhile systemic constraints are evident, Sri Lanka's innovation system possesses significant latent potential rooted in its people. To unlock this potential, policy must evolve beyond a narrow focus on formal STI metrics. It must recognize, support, and integrate the diverse human actors who are the true engines of innovation. This requires building \"soft infrastructure\" to foster trust and collaboration, creating platforms that connect individual inventors with firms and markets, and valuing the informal and practice-based knowledge that drives development from the ground up. Future research must continue to explore these micro-foundations to build a more complete and nuanced understanding of Sri Lanka\u0026rsquo;s innovation landscape.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Gnei Shuraiya Amath, Yasushi Hara. The first draft of the manuscript was written by Gnei Shuraiya Amath and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number 25K00660. The author also acknowledges the financial support received from the Japanese Government (MEXT) Scholarship.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated during and/or analysed during the study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbeytunga, D. T. U., Aturupane, H., Madhusanka, P. N., Liyanage, P. A. M., \u0026amp; Cooray, N.G. (2023). 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(2024). \u003cem\u003eSri Lanka Ranking in the Global Innovation Index 2024\u003c/em\u003e. Retrieved on June 05, 2025 from https://www.wipo.int/gii-ranking/en/sri-lanka\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":"innovation systems, lagging regions, innovation modes, DUI, patents, Sri Lanka","lastPublishedDoi":"10.21203/rs.3.rs-7000389/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7000389/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the dominant innovation modes and systemic structure of a lagging region by providing an actor-centered analysis of Sri Lanka's national innovation system. In contrast to innovation models derived from advanced economies, lagging regions often exhibit unique innovation dynamics. Analyzing 35 years of patent application data (1989–2023), we map the contributions of key actors—individual inventors, firms, universities, and government—to uncover the system's underlying structure. The findings reveal a dualistic and fragmented system. Domestic innovation is overwhelmingly driven by individual inventors, whose activities reflect a \"Doing-Using-Interacting\" (DUI) mode reliant on experiential and practice-based knowledge rather than formal research and development (R\u0026amp;D). This grassroots activity is disconnected from a corporate-led international system focused on market protection. A profound lack of collaboration among all actors highlights systemic fragmentation, constraining interactive learning and economic upgrading. Our analysis contributes to the literature by empirically demonstrating the prevalence of the DUI mode in a lagging region and provides policy insights, suggesting that support must be tailored to the system's actual, rather than assumed, innovation dynamics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJEL Classification: O31, O33, O10, O53\u003c/strong\u003e\u003c/p\u003e","manuscriptTitle":"Modes, Fragmentation, and Inventor Agency: An Actor-Centered Analysis of Sri Lanka's Innovation System","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-11 07:55:24","doi":"10.21203/rs.3.rs-7000389/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":"81b335b6-d9fa-4d42-9a02-b13d993cff39","owner":[],"postedDate":"July 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T14:31:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-11 07:55:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7000389","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7000389","identity":"rs-7000389","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}