Firm growth and scaling are inherently multi-dimensional, time-sensitive, and complex phenomena. Yet, the scholarship investigating them overwhelmingly relies on either quantitative or qualitative methods in isolation. We argue that this methodological singularity produces a fragmented and incomplete understanding, and that mixed methods research offers a more powerful lens for capturing the processual, contextual, and dynamic character of growth and scaling. In this paper, we provide a first cross-disciplinary narrative synthesis of the personal, firm-level, and contextual determinants of firm growth and a second synthesis of the relationship between entrepreneurship and economic growth. Drawing on these syntheses, we develop an illustrative cross-disciplinary and mixed methods agenda on the digital entrepreneurship–growth and scaling relationship, highlighting how the porous boundaries and distributed agency characteristic of digital entrepreneurship call for longitudinal, policy-sensitive research designs that combine both statistical and narrative inquiry. Taking an ‘applied’ perspective, we also focus on two sequential designs and provide examples. Across our illustrations, we show how mixed methods can generate insights into the how, how much, how fast, and why of growth and scaling that neither method alone can produce. We conclude with recommendations for scholars navigating the conceptual and measurement challenges of this research domain and a call for more interdisciplinary, processual, and methodologically pluralistic investigation.
Supply chains are increasingly central to converting scientific discoveries and technological knowledge into operational, commercial, and societal value. Yet supply chain management (SCM) scholarship, like adjacent fields, has approached technology transfer (TT) as a transfer event in which value is presumed to follow once rights or knowledge change hands. We reconceptualize TT as a discovery-to-deployment supply chain process: five recursive stages (discovery, development and protection, scaling and commercialization, deployment and use, and renewal) coordinated by distributed, co-specialized capabilities. A review of 67 articles in eight core SCM journals demonstrates that the field, constrained by the transfer-event framing, has concentrated on sourcing, IP governance, licensing, and commercialization, while leaving operational assimilation, downstream deployment, use support, and feedback-based renewal underdeveloped. Reading these tendencies as the footprint of a shared assumption, we develop a research agenda around four shifts: from technology transactions to capability coordination, isolated events to longitudinal processes, upstream sourcing to network-wide deployment, and one-way transfer to feedback-based renewal. This reconceptualization integrates two literatures that have developed apart. First, we give technology transfer research a process-and-coordination lens that helps explain why some technologies scale and endure while others stall at the license or pilot stage. Second, we extend SCM’s domain from coordinating materials, products, and information to coordinating technological knowledge and capabilities.
Although business incubators are one of the main public policy instruments for promoting entrepreneurship and regional development, after nearly 30 years of research, there is still no consensus on their value, with several studies presenting contradictory findings on the performance of incubated companies. A review of the previous literature identified several methodological biases that may overestimate the outcome of these organisations. In a robust approach, this study paired a total of 442 incubated companies, spread over four periods, during and after incubation, with a corresponding sample of non-incubated twin companies. The association between incubation and performance was tested on a total of five metrics. The influence of the type of incubation (physical vs. virtual) and the quality of the incubator was also analysed. The results show that the performance advantage associated with incubation is not absolute but contingent, depending on the period of analysis and the quality of the incubator. Specifically, positive associations are concentrated during the first three years of incubation but dissipate in the post-incubation period. High-quality incubators are associated with positive performance outcomes, whereas for low-quality incubators, no evidence of such positive associations is found. Combined with the methodological biases identified, these results provide empirical grounding for future research aimed at reaching a clearer consensus on the specific circumstances in which the association with incubators is positive and when it is not.
Despite extensive investment in entrepreneurial support organisations (ESOs), ostensibly similar support arrangements often generate markedly different outcomes for micro, small, and medium-sized enterprises (MSMEs). Existing research explains support through programme architectures, governance arrangements, network structures, and performance outcomes, yet offers limited insight into how support is actually accomplished in everyday practice, particularly in resource-constrained environments characterised by institutional fragmentation and limited organisational slack. Drawing on the recent turn to practice in contemporary social theory, this study examines how business support becomes workable under such conditions. We analyse 58 interviews with scientists, technology transfer officers, policymakers, financiers, and entrepreneurs across six ESOs in the Global South, complemented by observations and documentary evidence. Our findings identify four interrelated organising practices through which support is accomplished: parsing resource needs, entrepreneurial framing of academic work, prioritising appropriate technologies, and orchestrating relational ties. Rather than operating as discrete interventions, these practices function as mutually reinforcing accomplishments through which actors align materials, meanings, and competencies in situ. We contribute by re-theorising business support as a situated organising accomplishment rather than a programmatic intervention, organisational capability, or support architecture. This perspective opens the black box of support enactment, explains why ostensibly similar support arrangements generate heterogeneous outcomes, and reveals how resource constraints actively shape the forms of organising through which support becomes workable. In doing so, we extend scholarship on ESOs and technology transfer while offering practitioners a diagnostic vocabulary for strengthening support under conditions of constraint.
This introductory paper for this special issue links prior knowledge on technology transfer ecosystems with recent critiques on the ecosystem concept as a research tool, examining how university actors navigate their ecosystems by investigating who is involved, how processes are navigated and where this takes place. We put forward that researchers should ‘drill down’ rather than ‘close down’ the ecosystem concept and regard the ambiguity surrounding it as a valuable analytical starting point rather than as a problem to be solved. The five articles in this Special Issue contribute to this conversation and expand our understanding of the micro-foundations of “navigating university ecosystems”. We conclude with a research agenda and several implications for university actors and policymakers.
University spin-off (USO) creation is typically associated with Science, Technology, Engineering and Mathematics (STEM) disciplines. This study shifts the focus to the Social Sciences and Humanities (SSH). Drawing on institutional theory, we argue that SSH-based USOs constitute a peculiar object: they conform neither to prevailing modes of knowledge transfer in SSH, nor to the established, STEM-centric commercialization routines of technology transfer offices (TTOs). To explore how this particular institutional context shapes the development of SSH-based USOs, the study relies on a multiple-case study of 14 SSH-based USOs, primarily informed by interviews with SSH academic entrepreneurs and TTO staff members. The results demonstrate that SSH-based USOs face specific institutional constraints hindering their development. Most are normative and cognitive, rooted in disciplinary values and mental models that sustain distinct models of knowledge transfer—that of SSH versus a dominant STEM-based model, enacted respectively by SSH academic entrepreneurs and TTO staff members. Additional regulative constraints arise from formal procedures and resource allocation policies. Nonetheless, our findings also indicate that these constraints are not static. Drawing on the concept of institutional work, our results show that these constraints constitute instead spaces of active boundary work, where SSH academic entrepreneurs and TTO staff members change, redefine, or maintain the boundaries of university knowledge transfer. Importantly, our findings reveal that TTO staff members’ efforts to adapt established practices as they expand into SSH are fraught with internal tensions, as they contend with resource constraints and entrenched disciplinary norms privileging STEM-based models of USO creation.
This study integrates the embedded perspective of entrepreneurship with institutional logics theory to theorise AE as an embedded phenomena, sitting at the intersection of individuals within surrounding contexts. Drawing on qualitative data from STEM academics at three research-intensive universities—in the UK (23), Australia (32), and Italy (26)—we develop the concept of the academic entrepreneurial space, as the arena within which AE unfolds, structured by a constellation of four logics: profession, discipline, impact, and resource culture. We show how each logic shapes individual attitudes and motivations through three socio-cognitive mechanisms—signification, legitimation, and domination—and how the logics interact through four cross-level mechanisms—filtering, resistance, refraction, and compounding. By conceptually defining the logics underpinning AE, foregrounding the mechanisms through which multiple logics shape academics’ attitudes and motivations for AE, and how logics interact, the study contributes understanding on the embedded nature of AE, providing theoretical and practical insight.
University Entrepreneurial Ecosystems (UEE) have become increasingly influential within their respective regional and national entrepreneurial ecosystems, significantly impacting innovation levels in societies, particularly through patenting and University Spin-offs (USO). Against this background, this study takes a novel perspective by identifying the elements of UEE that are necessary to produce high levels of these outcomes, specifically patent grants and USO turnover. Instead of focusing on average effects, our study aims to identify what should be in place in order to attain higher levels of UEE performance. To do so, we resorted to data from Higher Education Business and Community Interaction (HE-BCI) in the United Kingdom (UK) employing Necessary Condition Analysis (NCA). The results showed that the necessity of each UEE element is contingent to the target level of the outcomes to be achieved. The total number of academics, patent stock and income from contract research emerge as important bottlenecks on the way to high levels of UEE performance. The findings expand knowledge about the university-specific characteristics that are bottlenecks for UEE development. Thereby, the study brings about a new perspective that has not only theoretical but also managerial and policy implications, which are developed in the body of the text. The importance of Higher Education Institutions (HEIs) size in producing high levels of the aforementioned outcomes suggests HEIs should pursue strategies to increase their scale, if they intend to fulfil the third mission. A possible strategic response could be to negotiate mergers and partnerships.
Innovation in emerging economies increasingly depends on university-industry collaboration, yet how innovation partner selection occurs under institutional constraints remains poorly understood. Drawing on a two-sided matching framework and patent data from Zhejiang (2016–2020), we examine how institutional logic reorders the hierarchy of capability signals, reshaping partner selection in collaboration markets. Our findings reveal that scholars’ publishing capability functions as the dominant innovation signal across the collaboration market. It exhibits a robust complementary relationship with firms’ knowledge base breadth. In contrast, the matching value of patenting capability is contingent on institutional legitimacy: complementary to firms’ knowledge base breadth when scholars are from high-reputation universities, but substitutive in low-reputation contexts. These results indicate that university reputation operates as an institutional gatekeeper, determining whether ambiguous signals such as patents can enter firms’ matching evaluations, thereby reshaping the matching patterns of knowledge complementarity. This study extends two-sided matching research to non-Western institutional contexts and shows how institutional environments govern the interpretation of knowledge signals, contributing to signaling theory and university-industry collaboration research.
Amid intensifying global technological competition and China’s commitment to high-level technological self-reliance, government venture capital (GVC) has emerged as a core instrument for state intervention in the venture capital market and the implementation of innovation policies. Using a panel dataset of Chinese firms from 2012 to 2021, we innovatively employ a large language model to facilitate multi-level ultimate ownership tracing for the precise identification of GVC-backed firms. We then employ a staggered difference-in-differences approach to systematically examine the impact of GVC on firm innovation performance and its underlying mechanisms. We document four main findings: (1) GVC significantly increases both the quantity and quality of innovation in portfolio firms, boosting patent applications by approximately 12.3
Governments increasingly use public venture capital to address financing and commercialization gaps in technology-based firms, but non-random recipient selection complicates evaluation. We examine the relationship between government-backed technology equity investment and innovation in 190 science and technology firms in Qingdao, China. Using HC3-robust regressions and propensity-score overlap weighting, we distinguish innovation input, innovation output, and downstream firm performance. Government-backed investment is positively associated with innovation output, whereas its relationships with innovation input and performance are not statistically significant. Results are robust to overlap weighting. Investment intensity is correlated with all three outcomes but is treated as endogenous, and no moderator interaction survives false-discovery-rate adjustment. Survey evidence is consistent with financing, certification, governance, resource-access, and risk-sharing mechanisms, although the cross-sectional design does not permit causal or mediation claims. The study provides a cautious, measurement-explicit assessment of how public equity investment is associated with technology commercialization at the city level.
This paper examines how heterogeneous disruptions shape SME growth intentions and how adaptive capabilities influence firms’ responses across different disruption strands. Using five-year longitudinal data on UK small and medium-sized enterprises (SMEs) during the Brexit period, we show that disruptions are not homogeneous external shocks but differ in how they affect SME growth intentions. Disruptions to capital investment, leadership training, and working practice lowering growth intentions are associated with lower growth intentions, suggesting that they weaken the financial, organisational, and managerial resource environment supporting future growth. In contrast, disruptions affecting innovation, export, and workforce are not associated with lower growth intentions, indicating that these disruptions may leave scope for SMEs to reconfigure available resources and maintain growth ambitions. We further demonstrate that adaptive capabilities do not contribute uniformly to SME growth intentions because they support different knowledge processes under disruption. Innovation capability is consistently associated with growth intentions across disruption strands, while export and training capabilities contribute only under specific disruption conditions. These findings extend research on SME adaptation and knowledge transfer by demonstrating that adaptive capabilities create value not simply through their possession but by enabling SMEs to acquire, integrate, transfer, recombine, and exploit knowledge in ways that align with the resource demands of different disruption strands. By showing that the effectiveness of adaptive capabilities depends on the alignment between disruption-specific resource conditions and capability-specific knowledge processes, the study thus advances a disruption-induced knowledge alignment perspective and open new research avenues that require further investigation into the contingent value of adaptive capabilities across different disruption contexts.
Firms strategically manage their intellectual property rights through patent renewal decisions. Given the high uncertainty surrounding technology and innovation management, we suggest that firms are more likely to renew patents with greater technological opportunity or those technologically relevant to their existing patent portfolio. Moreover, an interaction effect between technological opportunity and relevance exists, such that firms are more inclined to renew their patents when both conditions are present. Further, the extent to which technological relevance influences the likelihood of patent renewal is amplified when a firm’s technology portfolio is more fragmented. Analyzing a sample of 4,685 firms that made renewal decisions from 1985 to 2024 and over 1.4 million patents granted in the U.S., this study provides novel insights into the factors driving strategic technology management.
Interest in industrial policy has intensified in recent years, calling for renewed conceptual understanding and more robust analytical tools. However, existing industrial policy frameworks remain insufficient to capture the complexity and dynamics of contemporary industrial systems and policies. To address this gap, this study proposes a novel industrial policy analysis framework comprising four analytically distinct yet interrelated dimensions: drivers shaping policy, value-chain segments, product types, and policy instrument mixes. The framework was developed through theory synthesis by integrating key dimensions identified in prior industrial policy research and was subsequently adapted to the semiconductor sector through policy document analysis of 108 policy interventions and 22 in-depth interviews. The sector was selected due to heightened policy salience arising from geopolitical tensions and supply-chain vulnerabilities. The analytical utility of the framework is demonstrated through two empirical case studies comparing (1) Japan’s semiconductor policies pre- and post-COVID-19, and (2) Japan–U.S. semiconductor policies. The first case study reveals a marked strategic reorientation in Japan’s semiconductor policy after COVID-19, characterised by clearer policy direction, expanded interventions and larger budgets, and a broader R D scope. The second case study identifies a strategic convergence in policy instrument choices, with both countries prioritising industrial grants to support the manufacturing segment of advanced logic chips as a core competitive domain. This study demonstrates that the proposed framework can serve as a robust analytical tool not only for systematic comparison but also for identification of opportunities and threats within national industrial systems, thereby enabling more strategic industrial policy design.
Green technology innovation requires integrating highly dispersed knowledge across multiple technical domains, yet how institutional arrangements alter firms’ knowledge acquisition structures to advance green innovation remains insufficiently understood. Drawing on panel data from Chinese A-share manufacturing listed firms spanning 2013–2023, this paper adopts the exploration-exploitation duality as its organizing framework and exploits the staggered establishment of national technology transfer demonstration institutions across regions to estimate the effect of technology transfer policy on firms’ green technology innovation. The policy is associated with an increase in green invention patent applications. It widens the breadth of firms’ patent portfolios across IPC classifications by activating cross-domain exploration, and it deepens resource concentration along core green technological trajectories through focused exploitation. Which process carries the effect depends on a firm’s knowledge distance from the green technology domain. Firms whose knowledge bases are distant from green technology benefit mainly through the exploration channel, whereas firms with an established green foundation gain more through exploitation, so that policy and firm knowledge structure fall into a selective match. Policy effectiveness is also stronger in regions with denser knowledge networks, indicating that regional knowledge ecology shapes how far technology transfer institutions can activate either process. These findings suggest that technology transfer platforms work less as direct providers of resources than as restructurers of the knowledge firms acquire, and they offer reference value for other emerging economies and for the platforms themselves when knowledge-based green innovation policy is being designed.
Although innovation policies are widely implemented to stimulate regional development, their effects on interregional collaborative innovation and how intergovernmental network structures shape such effects remain understudied. This research investigates the impact of China’s National Innovative City Pilot Policy (NICPP) on intercity collaborative innovation (ICI), with a specific focus on the moderating roles of different types of intergovernmental networks. Using a dyadic data set of 210 city-pairs in Guangdong (2004–2022) and a dynamic difference-in-differences design, we found that the NICPP significantly enhanced ICI, a pattern consistent with the policy acting as a coordination mechanism. This effect was primarily driven by incentivizing cross‑jurisdictional collaboration among industrial firms. Further moderating analyses revealed that hierarchical leadership transfer networks and self-organized learning networks significantly enhanced the policy’s impact, while counterpart-assistance networks exerted no significant moderating effect; moreover, the policy’s impact varied by collaboration type, with self-organized networks facilitating firm-to-firm collaboration, and hierarchical networks supporting university-industry collaborations. These findings underscore the importance of network-aware and context-sensitive policy design in governance for innovation.
Academic spin-offs (ASOs) are key vehicles for commercializing university research, yet theoretical and empirical insights on their performance relative to new technology-based firms (NTBFs) remain inconclusive. Drawing on a novel, hand-collected dataset of ASOs and independent NTBFs across 99 regions in ten European countries, we examine differences in their growth outcomes and the moderating role of regional human capital. Using entropy balancing to facilitate causal inference, we find that ASOs outperform comparable NTBFs in both employment and sales growth. The employment growth “premium” for ASOs is especially pronounced in regions with higher shares of business graduates, but not with STEM graduates. Our findings provide evidence that ASOs outperform similar NTBFs, which is important given the social costs of academics leaving universities, and highlight the importance of regional labor markets in shaping these outcomes. The results have important implications for policy-makers, universities, and academic entrepreneurs.
Our contribution fits within the broader trajectory from traditional econometrics to predictive machine learning and advanced AI-driven decision support, focusing on a distinct niche in digital entrepreneurial finance: the application of interpretable machine learning to predict post-campaign outcomes of equity crowdfunded firms. Specifically, we combine prediction with explainability to identify which features are most associated with transitions to external post-campaign scenarios. This is enabled by a hand-collected dataset of 708 post-initial and seasoned campaign scenarios across multiple platforms, spanning 2012–2024, including high-dimensional and multi-category features. This yields more representative samples and more generalizable predictive insights. Firm valuation and campaign characteristics are strong predictors. Additional features, including firm age, core team size and female representation also matter beyond mechanical campaign-related outcomes. Moreover, the model’s predictions show that synergistic interactions between firm valuation and campaign indicators yield higher predicted probabilities than any single predictor alone, highlighting the importance of multidimensional interactions.
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.
