The innovation capability equation: A systematic review of global determinants of SME's success
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Tsakalerou, Mariza; Abil, Akmaral; Ribiere, Vincent; Lukhmanov, Yevgeniy; Tynybayeva, Narkes Article The innovation capability equation: A systematic review of global determinants of SME's success Journal of Innovation & Knowledge (JIK) Provided in Cooperation with: Elsevier Suggested Citation: Tsakalerou, Mariza; Abil, Akmaral; Ribiere, Vincent; Lukhmanov, Yevgeniy; Tynybayeva, Narkes (2025) : The innovation capability equation: A systematic review of global determinants of SME's success, Journal of Innovation & Knowledge (JIK), ISSN 2444-569X, Elsevier, Amsterdam, Vol. 10, Iss. 4, pp. 1-17, https://doi.org/10.1016/j.jik.2025.100757 This Version is available at: https://hdl.handle.net/10419/327652 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/
The innovation capability equation: A systematic review of global determinants of SME’s success Mariza Tsakalerou a,* , Akmaral Abil a , Vincent Ribiere b , Yevgeniy Lukhmanov a , Narkes Tynybayeva a a Department of Civil and Environmental Engineering, Nazarbayev University, Astana, Kabanbay Batyr ave. 53, Kazakhstan b Institute for Knowledge and Innovation Southeast Asia (IKI-SEA), Bangkok University, Bangkok, Thailand ARTICLE INFO JEL Classification: O310 Innovation and Invention: Processes and Incentives O320 Management of Technological Innovation and R&D O330 Technological Change: Choices and Consequences Diffusion Processes O340 Intellectual Property and Intellectual Capital O360 Technological Change: Open Innovation L250 Firm Performance: Size, Diversification, and Scope Keywords: Innovation Innovation capability SMEsc Systematic literature review Determinants of innovation ABSTRACT Competitiveness and long-term sustainability are closely tied to the innovation capability of small and mediumsized enterprises (SMEs). However, a systematic understanding of the key determinants of this capability remains limited and fragmented. While prior studies have examined individual innovation factors, few have comprehensively integrated the internal and external dimensions that shape the innovation capacity of SMEs across diverse contexts. In response to recent global disruptions and rapid technological transformations, this study addresses a critical gap by conducting a systematic literature review (SLR) and bibliometric analysis of 122 highquality empirical studies published between 2020 and 2024. Guided by the central question—what are the most influential determinants of innovation capability in SMEs, and how do these vary over time and across regions—this review synthesizes various empirical findings. Six major determinants are identified: Knowledge and Learning Capabilities (r =0.98), Organizational Structure and Culture (r =0.96), Innovation Management and Strategy (r =0.81), External Networks and Collaborations (r = 0.70), Market Orientation and Customer Insights (r =0.47), and Technology and Digitalization (r =0.05). Additionally, the analysis identifies cross-cutting cited factors, such as Entrepreneurial Orientation and Absorptive Capacity that emerge as enablers. SME innovation capability is thus shaped by strategic, cultural, and knowledge-based determinants, alongside these aforementioned factors. This study adopts a hybrid method that combines a structured SLR with bibliometric coupling using VOSviewer to map thematic clusters and publication trends. The review reveals notable geographical and temporal patterns in SME innovation research, highlighting China’s consistent leadership in technology-oriented studies. Moreover, Knowledge Management, External Networks, and Digital Transformation emerge as an interconnected foundation for sustainable innovation in SMEs. Compared to earlier frameworks, this study offers a key advantage by explicitly incorporating geographical and temporal dynamics into the analysis. This contextual approach deepens our understanding of how the relevance of innovation capability determinants shifts across regions and periods, enabling more targeted and adaptive strategies. Thus, this research provides a systemsoriented foundation for future longitudinal studies that examine how interconnected determinants collectively drive sustainable innovation outcomes. Introduction Amid accelerating technological disruption, systematic innovation has become a cornerstone of organizational resilience for firms striving to compete and grow, irrespective of their size (Agrawal et al., 2021; Khyareh & Rostami, 2021). Although SMEs are often recognized for their entrepreneurial spirit, they frequently encounter challenges stemming from limited resources and expertise. Additionally, intense market pressures, ongoing geopolitical instability, and climate-related disruptions introduce further complexity to innovation (Sinani & Zilja, 2024). However, these limitations do not necessarily hinder innovation; rather, they serve to * Corresponding author. E-mail addresses: [email protected] (M. Tsakalerou), [email protected] (A. Abil), [email protected] (V. Ribiere), yevgeniy.lukhmanov@nu. edu.kz (Y. Lukhmanov), [email protected] (N. Tynybayeva). Contents lists available at ScienceDirect Journal of Innovation & Knowledge journal homepage: www.elsevier.com/locate/jik https://doi.org/10.1016/j.jik.2025.100757 Received 23 December 2024; Accepted 18 June 2025 Journal of Innovation & Knowledge 10 (2025) 100757 Available online 27 June 2025 2444-569X/© 2025 The Author(s). Published by Elsevier España, S.L.U. on behalf of Journal of Innovation & Knowledge. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).
redefine the process. Such constraints encourage creative problem-solving, prompting SMEs to develop innovation strategies tailored to their specific contexts (Codini et al., 2023; Merín-Rodrig´ a˜ nez et al., 2024; Saunila, 2020). To overcome these barriers, SMEs require more than spontaneous creativity; they need deliberate, structured innovation strategies. As highlighted in Business Insights on Emerging Markets by OECD (2024), firms in developing economies increasingly rely on digital and sustainability-oriented innovation to compete and build long-term resilience. Echoing this shift, Carrasco–Carvajal and García-P´ erez-De-Lema (2021) argued that the strategic adoption of emerging technologies has become essential, rather than optional, for SMEs aiming to grow or merely survive. Market orientation presents a critical strategic approach, as attention to customer needs enables SMEs to develop more relevant products and services (Dogbe et al., 2020a). Simultaneously, "open innovation" has emerged as a compelling alternative to the insularity of traditional closed innovation models. Cardoso et al. (2024) reported that smaller firms access new knowledge, expand their resource base, and improve adaptability through collaboration with customers, suppliers, and research institutions. Such transitions mark a fundamental shift from siloed innovation toward a collaborative ecosystem where value is co-produced rather than confined. Innovation does not arise in a vacuum; rather, it is shaped at the intersection of market dynamics and technological frontiers. Customer demands pull firms to evolve, while scientific breakthroughs push the boundaries of what is technologically possible, often preceding explicit market demand. These competing forces generate a complex environment for strategic decision-making, as observed in both recent studies (Bate et al., 2023) and foundational research (Freeman, 1979). Understanding this dynamic is essential to developing innovation capability, defined in this study as a firm’s capacity to leverage knowledge and ideas to improve products, processes, or systems in ways that improve competitiveness and stakeholder value (Saunila, 2017). These capabilities are typically categorized into two types: codified capabilities, such as tools, procedures, and software codes that can be readily transferred across contexts; and tacit capabilities, which are embedded in individuals and are inherently difficult to articulate or formalize. SMEs exhibit codified capabilities through the adoption of formal systems such as ISO 9001. Psomas et al. (2010) identified core enablers, ranging from process documentation and standard operating procedures to infrastructure improvements and targeted employee training, that embedded standardized knowledge into daily operations. These mechanisms rendered innovation systematic and traceable, creating a blueprint for replication and scalability. Conversely, tacit capabilities evolve through experimental learning and interpersonal relationships. Yani et al. (2024) illustrated how mentorship cultivated these intangible, softer dimensions by promoting strategic intuition, emotional resilience, and decision-making abilities through close interpersonal engagement. Despite their invisibility, the informal pathways remain essential for navigating uncertainty and sustaining innovation despite resource constraints. Building on these foundational capabilities, prior research has focused on identifying the specific factors influencing innovation outcomes in SMEs. Saunila (2020) highlighted the crucial role of leadership, knowledge development, and entrepreneurial orientation. Other studies (Dogbe et al., 2020b; Pomegbe et al., 2020; Tian et al., 2020) have highlighted the significance of external networks in facilitating resource access, while employee experience and education were consistently associated with successful product innovation. Investments in advanced technologies and continuous learning boost innovativeness, while collaborations with research institutions facilitate both incremental improvements and breakthrough innovations. Despite such insights, a comprehensive understanding of the core drivers of SME innovation remains elusive (S´ a et al., 2023). Several existing studies continue to focus narrowly on isolated factors, such as organizational culture or market dynamics, without adequately considering the relationship between internal and external influences (Reischl et al., 2022). Furthermore, although innovation has been extensively examined in general contexts, few frameworks systematically classify the capabilities most critical to SMEs operating in the digitally transformed and globally diverse environment today. The lack of integrative synthesis across regions and timeframes constitutes a major research gap, warranting further investigation. To address the research gap, this study presents a systematic review of SME innovation capabilities by analyzing 122 rigorously selected, peer-reviewed, high-quality articles published between 2020 and 2024. Although systematic reviews do not depict empirical reality, they capture the evolving consensus of the research community. Accordingly, this review identifies and categorizes key determinants of innovation capability, maps their geographic distribution and evolution over time, and analyzes their alignment with existing conceptual frameworks. This approach examines the mechanisms behind SME innovation and how these drivers vary across contextual and temporal dimensions. The findings hold practical implications for business leaders seeking context-sensitive strategies to stimulate innovation and scholarly value by integrating fragmented knowledge research while highlighting emergent patterns. By examining innovation capability through both spatial and temporal lenses, this review lays a conceptual foundation for more adaptive and evidence-based approaches to building sustainable innovation ecosystems within SMEs globally. Research approach This study adopts a hybrid methodology that integrates a systematic literature review (SLR) with quantitative bibliometric analysis. In the first stage, relevant literature on SME innovation capabilities is identified. In the second stage, the selected articles are systematically analyzed to extract innovation capability factors, which were subsequently grouped into thematic dimensions. In the third stage, a bibliometric analysis is conducted to generate an objective mapping of research clusters and thematic structures. These three methodological stages are described in Sections 2.1, 2.2, and 2.3, respectively. Selection process This section outlines a step-by-step methodology for conducting a literature review on innovation capabilities within SMEs. The method proposed by Saunila (2020) was adopted for this review owing to its clarity and reproducibility in guiding article selection. Literature search was conducted using the Scopus database to identify relevant studies. Although other databases such as Google Scholar and Web of Science cover a wider range of sources, including working papers, conference proceedings, and student theses, Scopus was selected owing to its emphasis on high-quality, peer-reviewed journal articles. Additionally, only English-language, peer-reviewed articles containing empirical data or evidence were included, based on the rationale that such sources provide the most rigorous and relevant evidence for the topic. The search employed specific title-based keywords including "innovation capabilit*", "innovation potenti*", "innovation abili*", and "innovation capacit*" in the titles, along with "sme", "small busines*", "small compan*", "small enterp*", "small fir*", or "small and mediu*" in titles, abstracts, and keywords. The search was limited to publications from January 2020 to April 2024, yielding an initial sample of 1127 articles. The full search string implemented in Scopus is as follows: (TITLE ("innovat* capabilit*" OR "innovat* potential*" OR "innovat* abilit*" OR "innovat* capacit*" OR "innovat* performance*" OR "innovat* manag*" OR "technolog* adoption*" OR "business innovation*") AND (TITLE-ABS-KEY ("sme*" OR "small business*" OR "small compan*" OR "small enterprise*" OR "small firm*" OR "small and medium-sized enterprise*" OR "micro enterprise*" OR "medium-sized business*"))) The procedure for selecting relevant studies followed a multi-stage M. Tsakalerou et al. Journal of Innovation & Knowledge 10 (2025) 100757 2
process, where articles were systematically included or excluded based on specific, predefined criteria (Fig. 1). In the first stage, the scope was restricted to articles published in Q1 and Q2 journals within the "Business, Management, and Accounting" domain. This strategic criterion ensured the inclusion of high-quality, peer-reviewed literature. Subsequently, the initial filtering yielded a subset of 183 articles. In the second stage, article titles were reviewed to exclude papers that did not meet the inclusion parameters, refining the pool to 164 articles. The third stage involved a detailed analysis of abstracts. This stage served two primary purposes: to confirm the presence of empirical evidence and to ensure an explicit focus on innovation capability factors within the SME context. Following this step, 126 articles remained. The final stage of the selection process involved a full-text review of the studies identified as eligible for in-depth screening. Each article was assessed to confirm its direct relevance to the investigation of innovation capability factors in SMEs. This rigorous filtering process yielded a final set of 122 articles. These selected articles formed the foundation for the subsequent analysis and synthesis of literature on SME innovation capabilities. Further details of the selection process are presented in Table 1. Categorization approach To structure a categorization framework, the approaches proposed by Saunila (2020) and Mendoza–Silva (2020) were adopted to develop a comprehensive classification of SME innovation capability determinants. While the framework by Saunila offered insights into firm-level capabilities, Mendoza–Silva introduced a protocol-based categorization system for distinguishing between internal drivers (e.g., leadership, organizational culture) and external enablers (e.g., policy environment, market access). Building upon this foundation, this study refined the framework proposed by Mendoza–Silva through contextual analysis incorporation and potential interpretational bias mitigation in data classification. Specifically, this study expanded the framework for reviewing and analyzing innovation capability factors by adopting the literature review methodology proposed by Mendoza–Silva (2020). In the original study, each factor that contributed to innovation was detailed based on its description in the source documents, along with its definition and specificity. This protocol was mirrored in this review to minimize the risk of interpretive bias. According to Mendoza–Silva (2020), their protocol-based approach applied contextual analysis to increase the accuracy of data categorization. This procedure enabled both the clustering of factors into coherent groups and the allocation of shared characteristics across categories, thereby creating a comprehensive profile of their influence on SME innovation capability. Accordingly, frequency-based categorization was performed, followed by the identification of additional, less frequently mentioned factors. To systematically organize the 233 identified factors into six dimensions, the process commenced by sorting the factors according to their frequency of occurrence in the reviewed literature. The most frequently cited and conceptually distinct factors were selected as the foundational dimensions. Once these six overarching groups (hereafter referred to as “determinants”) were established, the remaining factors were allocated to the most relevant category. This assignment was based on analyzing the definitions provided in the source articles (original) and evaluating their conceptual alignment with the dominant factors. Given that some factors could plausibly fit into multiple categories, a rigorous cross-checking and comparison process was conducted to ensure consistency and minimize subjectivity. After finalizing the groupings, the determinants were re-examined to determine the most appropriate label for each dimension. The naming process was guided by extracting the most frequently occurring keywords from the original definitions to ensure that the final labels accurately reflected the thematic essence of each group. This methodological approach enabled the construction of a transparent and analytically meaningful categorization framework for studying the determinants of SME innovation capability. Fig. 1. PRISMA-style flowchart of the literature selection procedure (adapted from Bakker, 2010, and Saunila, 2020). M. Tsakalerou et al. Journal of Innovation & Knowledge 10 (2025) 100757 3
Bibliometric analysis SLR was complemented by a bibliometric analysis. Bibliometric methods have gained increasing popularity in management research, as evidenced by recent studies (Akbari et al., 2021; Malacina & Teplov, 2022; Tandon et al., 2021). The bibliographic data of the 122 articles identified in Section 2.1 were analyzed using the Visualization of Similarities (VOS) technique (Van Eck & Waltman, 2014). VOS was selected due to its capacity to process large datasets and reveal the structural properties of research domains. To measure relatedness between the analyzed papers, bibliographic coupling was employed. This method assessed the degree of similarity between two papers based on the overlap in their reference list. Boyack and Klavans (2010) argued that bibliographic coupling was more suitable than co-citation analysis for mapping recent literature because newer publications typically lack sufficient citation count. Thus, bibliographic coupling uncovered the intellectual foundations shared across studies. Individual articles were selected as the unit of analysis to maintain focus on discrete research contributions. Fractional counting was applied as the weighting method (Perianes-Rodriguez et al., 2016) to prevent overrepresenting highly collaborative publications. A citation threshold of 20 per document was maintained to isolate influential contributions, resulting in a refined subset of 48 articles for final synthesis. Based on the strengths of bibliographic coupling, the VOSviewer algorithm (version 1.6.20) identified five distinct clusters within the literature. Fig. 2 presents the resulting research domain visualization generated from VOS mapping. Each node represented a single publication, with node size indicating citation frequency. Connections between nodes represented bibliographic coupling, while link thickness reflected the strength of the relationship. Articles from each cluster are presented in Table 2. Cluster names were assigned based on the overlapping themes shared by most articles within each cluster. Results Publication trends The systematic review revealed a distinct pattern in the distribution of research on innovation capabilities in SMEs. The highest number of publications occurred in 2020, followed by a decline in 2021, a modest rebound in 2022 and 2023, and another decrease in 2024 (Table 3). As shown in Table 3, China consistently emerged as a leading contributor to research on SME innovation, particularly in 2020 and 2021. In subsequent years, European countries, including Italy, France, and Portugal, demonstrated increasing engagement, indicating sustained regional interest in the topic. From an institutional perspective, Jiangsu University stood out as the most prolific contributor, while Universiti Utara Malaysia and Link Campus University made notable contributions to the literature (Fig. 3). Fig. 4 illustrates that a substantial number of papers fall under the category of Business, Management, and Accounting. Thus, the central focus of the research was highlighted, which served as a primary inclusion criterion for the analysis. However, the articles also spanned other subject areas, including Economics, Social Sciences, Engineering, and even Psychology. Fig. 4 demonstrates that the selected papers provide a comprehensive overview of innovation practices and capabilities within SMEs, highlighting a wide range of contexts and analytical perspectives. The diversity of research broadens the understanding of innovation capabilities in small businesses across various countries and academic environments. Furthermore, keyword analysis facilitated the identification of major themes within SME innovation capability research. Fig. 5 illustrates these themes based on their centrality and density. Centrality reflected the strength of a connection between the research theme and other themes in the field, while density represented the internal cohesion within a theme (Murgado–Armenteros et al., 2015). The thematic mapping, conducted using the bibliometric package in R (Dervis¸, 2019), categorized the themes into four quadrants: Motor Themes, Basic Themes, Niche Themes, and Emerging or Declining Themes. The Motor Themes quadrant (upper-right) comprised welldeveloped and conceptually central research areas that actively promoted field development, including external knowledge, absorptive capacity, developing countries, technology adoption, and digital technologies. Additionally, the presence of COVID-19 in this quadrant indicated the significant impact of the pandemic on innovation research priorities during the study period. The Basic Themes quadrant (lower-right) comprised fundamental concepts characterized by high centrality but lower development density, including innovation performance, commerce, and competition. These themes formed the conceptual foundation of SME innovation research but were less extensively developed than Motor Themes. The Niche Themes quadrant (upper-left) encompassed specialized research areas with strong internal development but limited relevance to the broader fields, such as information and communication technology, personnel, and policy makers. These topics represented specialized research niches that were well-developed within specific contexts but were yet to attain mainstream prominence. Finally, the Emerging or Declining Themes quadrant (lower-left) featured topics such as patents and inventions, research and development, knowledge management, and engineering. These represented areas that Table 1 Exclusion criteria. Phase Exclusion Criteria Reason N◦of papers excluded N◦ papers left 0 Initial search on Scopus 1127 1 Papers not categorized under "Business, management, and accounting" topics Limit the scope for practical application 422 705 Conference proceedings, reviews, and books Do not ensure peerreviewed accuracy and detailed focus 177 528 Documents not in their final form of publication Do not ensure the reliability of the findings 21 507 Literature not published in the English language Do not ensure uniformity of language for analysis purposes 13 494 Articles from journals outside the upper quartiles (Q1 and Q2) of academic journal rankings Do not verify the academic integrity of the articles 311 183 2 Titles that focus on national or individual levels, rather than the SME context Do not focus on the research scope 19 164 3 Research not focused on the identification or assessment of innovation capability factors in SMEs Do not empirically study innovation capability factors in SMEs 36 128 Papers with a theoretical or conceptual framework (no empirical evidence) Lack of data-based evidence 2 126 4 Papers focusing on irrelevant factors Do not assess relevant innovation capability factors for this particular study 4 122 M. 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were either gaining traction as new directions or losing relevance within the evolving research landscape. Key determinants of innovation capability In this comprehensive review, a total of 233 distinct factors influencing SME innovation capability were identified and systematically categorized into six broad determinants: 1. Innovation Management and Strategy (IMS) 2. Knowledge and Learning Capabilities (KLC) 3. Market Orientation and Customer Insights (MOCI) 4. Technology and Digitalization (TD) 5. Organizational Structure and Culture (OSC) 6. External Networks and Collaborations (ENC) Each determinant encompassed a specific set of factors that were critical to cultivating an innovative environment within SMEs. This structured classification facilitated the management of complex data and demonstrated the multidimensional nature of innovation capability. Moreover, it improved clarity in understanding how individual factors collectively contributed to strengthening the innovative potential of SMEs. Fig. 2. VOS mapping of innovation capability research in SMEs (2020-2024). Table 2 Innovation capability research clusters according to VOS analysis. Cluster Color Size Articles Entrepreneurial Orientation Strategies Red 15 articles Bahta et al., 2020; Borah et al., 2022; Didonet & Diaz-Villavicencio, 2020; Fang et al., 2022; Freixanet et al., 2021; Hanaysha et al., 2022; Kolbe et al., 2021; Ndubisi et al., 2020; Rhee & Stephens, 2020; Rubio-Andr´ es et al., 2022; Sawaean & Ali, 2020; Singh et al., 2022a; Singh et al., 2022b; Tang et al., 2020; Zhang & Merchant, 2020 Knowledge Management Strategies Green 11 articles AlMulhim, 2020; Ferraris et al., 2021; Hanifah et al., 2022; Hayajneh et al., 2022; K˝ o et al., 2022; Parwita et al., 2022; Srisathan et al., 2020; V˘ at˘ am˘ anescu et al., 2020; Wongsansukcharoen & Thaweepaiboonwong, 2023; Yao et al., 2020; Zia, 2020 Network Embeddedness Strategies Blue 8 articles Ato Sarsah et al., 2020; Dogbe et al., 2020a, 2020b; Hanifah et al., 2020; Mazzucchelli et al., 2021; Pomegbe et al., 2020; Tian et al., 2020; Tian et al., 2021 Digital Transformation Strategies Yellow 7 articles Ardito et al., 2021; Du et al., 2020; H. Jiang et al., 2023; Z. Jiang et al., 2022; Jun et al., 2022; Lashitew, 2023; Veronica et al., 2020 Open Innovation Strategies Purple 7 articles Andersson et al., 2020; Cabrilo et al., 2020; Gimenez-Fernandez et al., 2020; Lu et al., 2021; Naruetharadhol et al., 2022; Pedota et al., 2023; Ur Rehman et al., 2022 Table 3 Publication trends and leading countries in SME innovation research (2020–2024). Year Relevant Publications Leaders by Publications Count 2020 42 China (6), Indonesia (4), Ghana (4), Kuwait (3) 2021 12 China (3), Italy (2), Indonesia (2) 2022 26 Pakistan (4), China (3), Thailand (3) 2023 32 Italy (4), Pakistan (4), China (3) 2024 10 France (1), Portugal (1), Switzerland (1), etc. M. Tsakalerou et al. Journal of Innovation & Knowledge 10 (2025) 100757 5
Defining and analyzing determinants of innovation factors An analysis of the frequency of each determinant from 2020 to 2024 (Fig. 6) revealed that Innovation Management and Strategy remained the most prevalent focus in global SME innovation research. The findings were consistent with expectations, given their direct and strategic relevance to the innovation capabilities of SMEs. The prominence of the determinant was established by examining the number of papers that addressed at least one of its constituent factors, thereby emphasizing its central role in the scholarly discourse. Knowledge and Learning Capabilities and Organizational Structure and Culture jointly occupied the second position in terms of frequency. Their substantial representation highlighted their importance in shaping SME innovation and their widespread relevance across different studies. These determinants were further analyzed based on at least one of their respective factors in the reviewed papers, illustrating their broad relevance and impact on SME innovation. Conversely, Market Orientation and Customer Insights emerged as the least frequently examined determinant. The underrepresentation signaled the need for further investigation to uncover the reasons behind its comparatively limited presence in existing literature. As shown in Fig. 7, in 2020, determinants such as Knowledge and Learning Capabilities, Organizational Structure and Culture, and Innovation Management and Strategy attained their peak frequencies, while the remaining three determinants were less prominent. In 2021, all determinants experienced a dramatic decline, with Organizational Structure and Culture experiencing the most significant decrease (-91 %). This downturn was associated with the COVID-19 quarantine, which disrupted numerous industries and research areas (Feyisa, 2020). Over the following years, most determinants gradually regained frequency, excluding Market Orientation and Customer Insights, which declined by 85 %, although their presence notably increased in 2023. When comparing the extent of these fluctuations, all determinants experienced substantial variations, excluding Technology and Digitalization, which remained relatively stable, with an average annual percentage change of 17.9 %. The correlation coefficients (Table 4) provided deeper insights into the influence of general publishing trends on the prominence and focus on specific innovation determinants. High correlation coefficients for Knowledge and Learning Capabilities (0.98) and Organizational Structure and Culture (0.96) indicated that research activity in these areas closely mirrored the overall growth in publication studies. Conversely, the low correlation coefficient observed for Technology and Digitalization (0.05) suggested that publication fluctuations in this domain occurred independently of broader publishing trends. Thus, interest in Fig. 3. Publication count based on affiliation. Fig. 4. Publication based on subject area. M. Tsakalerou et al. Journal of Innovation & Knowledge 10 (2025) 100757 6
technology and digitalization among SMEs was attributed to other factors such as technological advancements or policy shifts, rather than general academic publishing trends alone. Moderate correlations for determinants such as Market Orientation and Customer Insights (0.47), External Networks and Collaborations (0.86), and Innovation Management and Strategy (0.81) reflected a balanced interplay between evolving business practices and emerging challenges in the SME sector. These findings suggested that although certain areas appeared to trend within academic literature primarily due to overall increases in publication, others represented genuine and substantial shifts in the SME innovation ecosystem, warranting focused attention and dedicated resources. Geographical distribution of key determinants Fig. 8 illustrates the geographical distribution of all innovation determinants worldwide. Market Orientation and Customer Insights exhibited relatively low research activity across the surveyed countries, with Iran, Ghana, and China leading but each contributing fewer than three publications. Conversely, Technology and Digitalization attractedbroader international interest, with Pakistan, China, and Italy being the most active (4–5 publications). For External Networks and Collaborations, China stood out with the highest frequency, suggesting a particular national emphasis or strategic initiative in this domain. Similarly, Organizational Structure and Culture received varied attention, with Fig. 5. Major research themes in SME innovation capability research (2020–2024). Fig. 6. Frequency of occurrence of published papers categorized by each determinant. M. Tsakalerou et al. Journal of Innovation & Knowledge 10 (2025) 100757 7
Pakistan, China, Fiji, and the USA showing the most frequency, indicating a possible regional focus on corporate culture and organizational dynamics. Innovation Management and Strategy was predominantly studied in Indonesia and Pakistan, followed closely by China and Iran, reflecting a growing trend in these regions to prioritize innovation within business strategies. Finally, Knowledge and Learning Capabilities demonstrated a wide dispersion of research frequency, with Pakistan, Indonesia, and China leading, possibly reflecting a national emphasis on knowledge and education as key drivers of economic growth. Both developing and developed countries were well represented across the determinants, highlighting a global commitment to advancing innovation within SMEs. Notably, countries such as China, Ghana, Indonesia, Pakistan, and several European nations frequently appeared, emphasizing the universal significance of these innovation topics. Regionally, Asian countries such as Indonesia, Pakistan, and China displayed a pronounced interest in multiple innovation determinants, reflecting the dynamic economic growth and strong focus of the region on increasing innovation capabilities. The trend indicated the strategic moves of Asia to establish itself as a leading hub for technological and business innovation. Moreover, developing countries frequently prioritized External Networks and Collaborations, attributable to a strategy for leveraging global knowledge and resources to strengthen local innovation capacities and accelerate economic development. China consistently ranked among the leading contributors in publication output (2020–2023) and dominated across several innovation determinants, particularly Technology and Digitalization, Innovation Management and Strategy, and External Networks and Collaborations. The pattern suggested a concerted national emphasis on infrastructure development, digital adoption, and cross-sector partnerships (Wang et al., 2023). Conversely, countries such as Italy and France, while contributing fewer total publications, exhibited more focused attention in determinants such as Knowledge and Learning Capabilities and Organizational Structure and Culture, indicating a strategic prioritization of human capital development and organizational resilience (Audretsch & Belitski, 2021). These patterns reflected how regional research strengths aligned with underlying economic strategies and policy agendas. Notably, high publication volume did not necessarily correlate with thematic diversity, highlighting the importance of tailoring SME innovation strategies to specific research and policy contexts of each country. Core factors in SME innovation success The analysis of the most frequently occurring factors of SME innovation capability, as shown in Table 5, provided a robust foundation for identifying the key drivers within the previously defined determinants. Factors such as Entrepreneurial Orientation, Absorptive Capacity, Innovation Openness, Market Orientation, and Intellectual Capital emerged as critical components that directly influenced the capacity of SMEs for effective innovation. Within the broader determinant of Innovation Management and Strategy, Entrepreneurial Orientation received the most emphasis, highlighting the importance of promoting innovation and engaging in strategic risk-taking. Absorptive Capacity and Innovation Openness warranted particular attention, as they reflected the willingness of SMEs to acquire external knowledge and adopt new technologies, factors associated with the Knowledge and Learning Capabilities determinant. Market Orientation played a critical role in enabling SMEs to respond effectively to market conditions and customer needs, aligning closely with the Market Orientation and Customer Insights determinant to drive targeted innovation. Moreover, Intellectual Capital reveals the utilization of internal knowledge, serving as an important component within Knowledge and Learning Capabilities that empowered SMEs to develop new products and improve innovation. Absorptive Capacity served as another crucial factor requiring attention. Both potential and realized absorptive capacity enabled SMEs to acquire and effectively utilize external information, thereby Fig. 7. Annual variations in determinants of SME innovation capabilities. Table 4 Correlation between annual total publications and determinant-specific papers (2020–2024). Determinant Correlation Coefficient Knowledge and Learning Capabilities 0.98 Organizational Structure and Culture 0.96 External Networks and Collaborations 0.86 Innovation Management and Strategy 0.81 Market Orientation and Customer Insights 0.47 Technology and Digitalization 0.05 M. Tsakalerou et al. Journal of Innovation & Knowledge 10 (2025) 100757 8
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