This study addresses a key gap in the entrepreneurial finance and institutional theory literature by examining how signals - resource mobilization and digital affordances not sex, shape access to equity, debt, and grant funding in digitally-driven firms in disruptive industries under turbulence. While prior research has highlighted persistent gender disparities in access to finance, particularly under economic uncertainty, limited attention has been paid to whether such disparities persist in digitally-intensive sectors where digital affordances as well as access to internal assets and liquidity may neutralize traditional gender bias in financing. Drawing on an institutional perspective and digital entrepreneurship theory, we use an original panel dataset of 3034 digitally driven firms across 35 disruptive industries in the United Kingdom during 2015-2019, a period characterized by distinct economic, political, and institutional shocks. We find that gender neutrality persists in access to external finance under different types of macroeconomic shocks. Digital affordances significantly enhance access to equity and grant funding, working capital and tangible assets improve access to both debt and grant funding and intangible assets signal innovation potential during institutional and structural shocks. The study contributes to the field of digital entrepreneurship in turbulent times by demonstrating the differentiated role of resources and digitalization in shaping access to three types of entrepreneurial finance under turbulence in digitally-driven firms. We offer policy and managerial implications for investors, banks, financial institutions and policymakers seeking to support digitally driven firms.

Democracy is increasingly viewed as a core institutional condition for entrepreneurship, yet evidence remains mixed on what types of entrepreneurial activity it shapes and how. This study develops and tests a differentiated framework linking improvements in electoral democracy to two outcomes: total early-stage entrepreneurial activity (TEA) and high-tech entrepreneurship activity. Using data on 81 developing and developed countries over 2000–2022 we extend the democracy–entrepreneurship literature by moving from the general question of whether democracy fosters entrepreneurship to whether it is TEA or high-tech entrepreneurship which democracy affects. We also argue that democracy shapes entrepreneurship activity through institutional mechanisms of property-rights protection and government size. Our findings demonstrate that linear improvements in democracy are not directly associated with TEA and high-tech entrepreneurship. Property rights are positively associated with high-tech entrepreneurship, but that they do not moderate the democracy–high-tech entrepreneurship relationship.

Artificial Intelligence (AI) has emerged as a key technology that small and medium businesses (SMBs) utilize to process big data, use robots for industrial and service objectives and be able to grow, innovate and collaborate given the paucity of resources. This study examines how investments in organizational, technological and external (environmental) knowledge shape AI adoption following the Technology – Organizational – Environment (TOE) theoretical framework for technology adoption. We investigate the effect of adoption of two types of AI: application-oriented AI (robotics) and learning- and invention-oriented AI (machine learning and big data analysis). We evaluate the interplay between an SMB’s investment in internal R D, digital technologies and external knowledge in the form of R D purchase, knowledge spillovers and collaboration with external partners altogether explaining propensity to adopt AI. We use micro-level data from three combined surveys from the SMBs in the UK during 2010–2020 using regression analysis and selected qualitative data. Our findings demonstrate that investment in internal and external knowledge including spillovers and knowledge collaboration directly affects the propensity of SMBs’ to adopt AI for both robotics and big data analysis. We also find that recombination of internal and external knowledge reduces AI adoption propensity and discuss why. Small and medium-sized businesses (SMBs) that invest in both R D and digital tools are far more likely to adopt AI, but trying to do both at once may not always pay off. This study examines how investments in organizational, technological and external (environmental) knowledge shape AI adoption following the Technology – Organizational – Environment (TOE) theoretical framework for technology adoption. We investigate the effect of adoption of two types of AI: application-oriented AI (robotics) and learning- and invention-oriented AI (machine learning and big data analysis). We find that while investment in internal knowledge such as R D and digital technologies (ICT) strongly supports AI adoption, firms often must choose between building internal capabilities or accessingexternal knowledge through partnerships and spillovers or buying R D. Combining all these sources can be costly and complex, meaning that knowledge strategies must be carefully aligned with SMBs’ limited resources. The key implication for practice is that SMBs should focus on building a tailored mix of internal investment and external collaboration—rather than pursuing all options at once—to adopt AI effectively and sustainably. This helps managers make smarter choices about technology strategies in resource-constrained environments.

Drawing on agglomeration theory, embeddedness theory, and the community assembly metaphor, this study examines how regional industrial ecosystems (RIEs) shape firm performance in China's manufacturing sector. Using longitudinal data on 1012 listed manufacturing firms across China between 2008 and 2019, we combine input-output analysis with geographic distance measures across low-, medium-, and high-tech manufacturing industries to assess the effects of specialized (intra-industry) and diversified (inter-industry) agglomeration externalities on firm performance and technological innovation. We find that intra-industry externalities are negatively associated with firm performance in RIEs, particularly through lower innovation and profitability, whereas inter-industry externalities improve innovation, productivity, and market advantage. We argue that, in ecosystems shaped by market coordination and government industrial policy, specialized agglomerations do not necessarily enhance firm performance and may instead generate lock-in, knowledge redundancy, and resource congestion, especially in low-tech manufacturing. Our findings suggest that policymakers and firm managers should place greater emphasis on inter-industry collaboration than on intra-industry concentration in order to reduce resource competition and strengthen innovation within RIEs. These implications are particularly relevant for low- and medium-tech firms, where resources are more constrained.

Knowledge collaboration is recognized as a major source of innovation and competitive advantage for firms, especially for mall-and medium-sized enterprises (SMEs). Drawing on the open innovation and management literatures and using micro-level data from the U.K. most innovative firms, we demonstrate that innovation output is conditional on knowledge homophily collaboration and partner location. We also find that SMEs benefit to a greater extent from knowledge collaboration with external partners than large firms. Collaboration with customers and suppliers is more beneficial than collaborations with universities or government for SMEs. We develop implications for scholars, entrepreneurs and managers in innovative firms.

This study develops a theory-driven typology of entrepreneurial ecosystems (EEs) to better understand heterogeneity in entrepreneurial activity across places. We identify four ecosystem types — embedding, emerging, exploring, and extreme growth — based on two dimensions: structural thickness (the interdependency and density of connections among ecosystem actors and institutional factors) and locus of focus (the spatial orientation of ecosystem actors). Together, these dimensions provide a conceptual framework for understanding why ecosystems that may appear similar in their ecosystem attributes can nevertheless generate different forms of productive entrepreneurship. In addition, we provide an illustrative empirical application using data from 748 cities across 102 countries that approximates the typology and explores how ecosystem attributes are associated with the likelihood that a city exhibits a given type. By theorizing EE heterogeneity beyond resource- or scale-based perspectives, we advance research on the structural and spatial dimensions of entrepreneurship and provide a foundation for future comparative and longitudinal research. Entrepreneurial ecosystems (EEs) do not just differ in size and scale. This study introduces four ecosystem types — embedding, emerging, exploring, and extreme growth — based on how strongly local actors and institutions are connected and whether entrepreneurial activity is locally or globally oriented. Rather than assuming ecosystems differ only in size or resources, the typology shows how connections among actors and spatial orientation shape ecosystem differences. In addition, we provide an illustrative empirical application using data from 748 cities across 102 countries to approximate these types and explore how ecosystem attributes relate to them. The key implication is that policymakers should avoid one-size-fits-all approaches and instead tailor policies to the specific structural and spatial characteristics of their local EE, because ignoring these dimensions of heterogeneity can lead to ineffective policies.

This paper extends the knowledge spillover theory of entrepreneurship and innovation to explain how firms of different ages (startups vs. incumbents) and sizes (small vs. medium/large) benefit differently from external knowledge collaboration. Drawing on the distinction between active (formal) and passive (informal) spillovers, we examine how the intensity of knowledge collaboration influences two key innovation outcomes: product innovation and new market entry. Using a panel dataset of 27,685 UK firms (2005–2015), we show that the gains from knowledge spillovers for all types of firms are subject to diminishing marginal returns as collaboration intensity increases, while the findings between startups and incumbents are more nuanced than between small and medium/large firms. The benefits from knowledge spillover of innovation vary by knowledge spillover type, intensity, and mode of engagement, as well as innovation outcome. These findings refine the knowledge spillover theory by emphasizing the importance of firm age over size (entrepreneurial difference) in moderating innovation outcomes.

The rapid adoption of artificial intelligence and robotics as emergent technologies has made their application a strategic priority for businesses, especially in the most innovative small and medium-sized enterprises (SMEs) that continually invest in research and development (R&D), innovation, and digital technologies. Despite the growing use of artificial intelligence (AI) robotics, the factors that influence its adoption in innovative firms are not well understood. This study addresses this gap by exploring the differential contribution of internal and external sources of knowledge. Using micro-level data from 15,231 innovative SMEs observed during 2004-2020 in the United Kingdom, we apply the make-buy-ally framework to examine how investment in internal knowledge (make) and acquiring external knowledge (buy) and co-creating knowledge via collaboration with external partners (ally) shape AI robotics adoption in the most innovative firms.

Knowledge collaboration and investment in people are two important mechanisms for transforming knowledge into innovation. Yet, little research has examined the differences in knowledge collaboration strategies and investment in people between innovative startups and incumbent firms in high-cost developed economies. Drawing on the knowledge spillover of innovation theory and the geography of innovation literature, this study investigates (1) how the geographical locus of knowledge collaboration shapes innovation outcomes and (2) under conditions of investment in Research and Development and human capital, to what extent regional, national and international knowledge collaboration affect the propensity for product innovation in startups vis-& agrave;-vis incumbent firms. Using two data samples of innovative startups and incumbents in the UK from 2004 to 2020, we find that regional knowledge collaboration disproportionately benefits startups, while incumbents gain more from national partnerships, challenging existing assumptions about the geographical locus of knowledge spillovers in these two groups. We identify an 'innovation paradox' in which combining R&D investments with external collaborations reduces innovation propensity; however, combining investment in human capital with external collaborations serves as a key conduit for innovation in national and more diverse international contexts, with startups benefiting more. Implications for managers, regional development agencies and entrepreneurs are discussed.

Do entrepreneurial ecosystems (EEs) in cities facilitate nascent, emergent, and hypergrowth entrepreneurial activity, and what configurations of city EE quality and technological development correspond to distinct types of entrepreneurial activity? The answer to these questions is not straightforward. Building new space for EE theory, we use rigorous research methodology to provide compelling empirical evidence identifying how EE quality and city-level technological development shape nascent, emergent, and hypergrowth stages of entrepreneurship. Using fixed effects in generalized least squares estimation, we analyze data from 762 cities worldwide in 2019 to explore the direct and indirect effects of city-level technological development in alpha, beta, gamma, delta and insufficient cities, as well as the impact of improvements in EE elements on the three stages of entrepreneurship. Our findings from rigorous research methods clearly demonstrate that nascent, emergent, and hypergrowth entrepreneurship all benefit from an increased quality of EE elements. Nascent and hypergrowth entrepreneurship are facilitated by a combination of high EE quality and high technological development (alpha cities). In contrast, emergent entrepreneurship is facilitated in cities with high EE quality but, on average, lower city-level technological development, where there remains room for technological improvement. We also challenge traditional clustering arguments and suggest that digital technologies allow scale-ups and unicorns to transcend local ecosystem boundaries.

Trade openness and economic development are intrinsically connected. This study examines the relationship between trade openness and various aspects of economic performance of integration blocs using a sample of seven integration initiatives, including the European Union. Altogether, seven integration blocs represent 77 countries with macroeconomic data spanning 48 years, from 1974 to 2019. In this study, we apply a mixed-effect panel data regression analysis to empirically evaluate and discuss the effects of two trade openness strategies on a country’s economic performance—unilateral trade liberalization with the one-sided opening of market access, and reciprocal regional integration when both partners open up to each other. Our results demonstrate that trade openness is a key enabler or impediment for economic performance of countries, with nuanced variations in how specific performance indicators are affected across different integration blocs. We find that trade openness matters, with unilateral trade liberalization strengthening the effect of regional integration on the economic performance of regional blocs. At the same time, bilateral regional integration aiming at market access liberalization consistently outperforms unilateral approaches, enhancing various aspects of economic performance.

While prior research suggests that family ownership can significantly facilitate sales and innovation, empirical findings often overlook the nuanced differences in innovation inputs between family and non-family firms. We address this gap by examining the extent to which family firms are able to use absorptive capacity by creating knowledge internally and collaborating with external partners to enhance their innovation. Utilizing micro-level data from 9266 of the most innovative UK firms from 2006 to 2016, we employ a multi-level analysis to examine how different knowledge inputs-such as internal investments in knowledge and external collaborations at the regional and international levels-influence innovation outputs in family and non-family firms. Our findings contribute to the innovation and family business literature by providing a clearer understanding of the innovation dynamics within family firms compared to their non-family counterparts. Additionally, we offer managerial insights and outline policy implications that could foster knowledge transfer in family firms. These recommendations take into account that regional and international knowledge collaboration serves as a boundary condition for family firms to outperform their non-family counterparts.

Despite extensive research on institutions and firm internationalisation, the joint firm and macro-level effects of informal relationships, that is, corruption, on firm internationalisation, particularly within specific industrial contexts (resource-based vs. non-resource industries), remain underexplored. To investigate how firms internationalise under 2 boundary conditions - resource dependency and variations in institutional quality - we apply the Heckman-type selection bias and use 186,027 firms spread across 137 countries, with data collected through multiple firm surveys conducted by the World Bank Enterprise Surveys between 2006 and 2024. Our empirical findings demonstrate the double-edged sword of corruption. While it positively affects firm exports by mitigating bureaucratic procedures at the managerial level, the effect on exports turns negative as it increases uncertainty and operational costs at the macro-level. The effects are accelerated for firms in resource-based sectors. We highlight the interplay between corruption, resource dependencies and internationalisation and provide targeted policy and practical implications.

What matters for economic growth? How we can facilitate economic growth via entrepreneurship? Policy makers needs to invest in culture for creativity, better education, physical capital, digital technologies to create more conducive environment for growth and entrepreneurship. We apply endogenous growth theory to understand how investment into knowledge can and should be translated into productivity, growth, society, creating a better economy. We also discuss why some assumptions of endogenous growth models fail, talking about the European paradox of knowledge - high investment in human capital, training, cultural awareness but this does not translate into growth, jobs and startups. It is not enough to have those investments, but there is a missing link for knowledge to spill over and this is entrepreneurship activity and creating a well-functioning entrepreneurial ecosystems.

Research on entrepreneurial ecosystems has seen significant growth in the last decade, with a focus on the key elements of entrepreneurial ecosystem (EE) structure, stakeholders, and interactions between them. However, the literature linking these three elements within the entrepreneurial ecosystem has yet to reach a consensus regarding how interactions between stakeholders occur within the ecosystem and beyond. We apply the jazz jam session model used by jazz musicians for improvisation to demonstrate that within a given structure of improvisation, stakeholders may improve their level and intensity of engagement, increasing the quality of the entire entrepreneurial ecosystem. The jazz jam session model explains how and why the interactions can matter and how to organize them effectively between stakeholders.

Spillovers constitute the fundamental rationale for public investment in innovation. Unfortunately, it is difficult to directly measure and evaluate spillovers, so we can determine how to most effectively target public investment in innovation in the private sector. This study provides new empirical evidence on spillovers, simultaneously examining the role of geography, internationalization and collaborative R&D. Collaborative R&D is an important mechanism for the transmission of such spillovers. Based on comprehensive longitudinal firm-level UK data, including detailed information on different types of collaborative R&D, we find that access to public finance is a key determinant of a firm's ability to innovate and generate sales. Another key finding is that a firm's returns to international collaborative R&D are conditional on its productivity and access to public funding. It also appears that high-productivity firms benefit more from public funding than low-productivity firms, in terms of stimulating innovation. Should they secure public funding, firms also benefit more from regional and international collaboration than they do without such funding. In general, our findings are consistent with the view that the social returns to public investment in private sector R&D are high.

This article explores two different types of entrepreneurial ecosystem (EE) - emergent and growing - using the institutional logics perspective. Fields of entrepreneurship within EEs are analysed empirically in two U.K. cities, and the institutional orders that inform the dominant entrepreneurial institutional logic in each ecosystem are uncovered. The study reveals that, in an emergent ecosystem, entrepreneurs notice institutional voids and take part in institutional entrepreneurship to strengthen the institutional order of 'Profession' and 'Community' institutional orders. In a growing EE, the strength of 'Community' and 'Market' institutional orders and overlapping activity-based fields helps to strengthen the entrepreneurial institutional logic. This perspective develops and enriches our understanding of EEs as localised contexts in which embedded fields of entrepreneurship are sensitive to local institutional conditions, particularly highlighting divergent institutional logics in different ecosystem contexts. This represents a novel approach to analysing EEs through the lens of the institutional logics perspective, by utilising a framework to understand the interinstitutional system-based institutional orders as influencers that shape the dominant institutional logic in a field of entrepreneurship.

This study explores the effect of bailout capital and digital diversification by small- and medium-sized enterprises (SMEs) on their propensity to survive during and after the COVID-19 pandemic. Using a random sampling of 5469 SMEs from 16 European countries, collected by the World Bank Enterprise Survey in May 2020, January 2021, and May 2021, we conduct a two-stage estimation to examine factors that first affected the propensity of SMEs to access bailout capital, and second, factors that increased the propensity of SMEs to survive longer during and after crises. Two key findings emerge. Diversification of government financial aid and the adoption of various digital tools to leverage the effect of shock by SMEs increase their propensity to survive by sized firms. Moreover, government financial aid does not moderate the effect of digital tool adoption on the propensity to survive. Policy insights and implications are also discussed. We find that resource mobilization through government financial aid, particularly access to liquidity, significantly increases the likelihood of survival, with the effects being more pronounced for small-sized firms than medium-sized ones. Digital tool adoption matters to decrease SMEs risk of failure. However, combining government financial aid with digital tool adoption did not necessarily improve survival outcomes, possibly due to regional constraints on effectively using both resources together. This may indicate potential regional constraints for SMEs that impede the effectiveness of government support. We contribute to the literature on strategic responses to crises by SMEs, showing that while government financial aid and digital transformation are beneficial, the optimal use of these resources may depend on regional and firm-specific factors. Our insights provide valuable recommendations for research and policy to enhance SME resilience during future crises.

Effective technological innovation relies on having ample knowledge resources to enhance firm performance and knowledge creation. Innovators seek both internal and external knowledge, actively engaging in a continuous search for these valuable resources. Knowledge collaboration is a specific strategy that innovative firms can follow during Artificial Intelligence (AI) adoption processes. This study investigates the role of AI and knowledge collaboration in firm innovation. Using data from 14,143 firms in the UK between 2004 and 2020, we explore how AI adoption impacts knowledge spillover of innovation. Our findings suggest that firms adopting AI can enhance their innovation performance if it complements firm's own investment in R&D. AI adoption can substitute knowledge collaboration with certain external partners. The results help us to rethink resource allocation for knowledge spillover of innovation in the era of AI and digital technologies.