Explaining the national-level emergence of tech scaleups: the systemic role of knowledge stock from a configurational perspective

Purpose For two decades, the Global Entrepreneurship Monitor (GEM) has collected survey and national expert data to better understand entrepreneurial activity and the country context within which this occurs. In this paper, we re-envision GEM’s country groupings, positing a novel approach to more fully understanding the nuances of entrepreneurial activity. Design/methodology/approach Using data from the GEM’s Entrepreneurial Framework Conditions (EFCs) (2017–2020), we employ an unsupervised machine learning method (clustering) to classify countries into distinct groups according to country-specific government policies, education, sociocultural, and entrepreneurship infrastructure support. Then, building on the identified two sets of distinct economies (termed as “matured” and “maturing” entrepreneurial economies) and using the GEM’s data on Entrepreneurial Behaviour and Attitudes (EBAs), fuzzy-set Qualitative Comparative Analysis (fsQCA) is applied to highlight the complex nature of entrepreneurial intentions and to identify configurations of possible conditions that confirm intention pathways in entrepreneurial activities in each cluster of economies. Findings Our key findings suggest that in “matured” economies, where entrepreneurship is well-supported, people are driven by opportunity and a supportive environment. Moreover, in “maturing” economies, where there is less support, factors like personal status and overcoming fear of failure play a bigger role in their motivations. This new perspective is crucial not just for understanding entrepreneurship but also for shaping policies that truly support budding entrepreneurs. The results suggest that governments should tailor their support for entrepreneurship based on their maturity level. Originality/value Historically, GEM grouped countries based on the level of economic development (efficiency, innovation and factor economies) and, more recently, used the level of income (high, medium and low). Both categorisations are essentially outcome factors reflecting economic progress. While it is useful to compare countries based on these dimensions, we propose grouping based on entrepreneurial framework or contextual conditions, enabling scholars and policy makers alike to better understand how context influences entrepreneurial activity.

According to the central hypothesis of the knowledge spillover theory of entrepreneurship – the more knowledge is produced in a region, the more entrepreneurial opportunities are available in it. Recent research extended the theory further, showing that the level of entrepreneurial activities, depends on the configuration of the local knowledge base not only on its size. This paper is aimed at discovering which knowledge profiles are more (and which less) supportive of creating entrepreneurial opportunities. It is motivated by disagreements and conflicting evidence on fundamental matters across all three frequently used dimensions - the type of knowledge source that contributes to new knowledge within a region (i.e., universities or private incumbent firms); the presence/absence of a dominant source of new knowledge within a region (i.e., an anchor tenant); and the specialization/diversity of technological knowledge that is created within a region. We analyze data from 33 regions using statistics on patent filings between 2011 and 2015 and a number of created startups in these regions. Using fuzzy-set Qualitative Comparative Analysis (fsQCA) we confirm that a region’s potential for knowledge spillovers, and, thus, entrepreneurial activities, depends on the configuration of the local knowledge base, specifying what configurations are antecedent to creating more entrepreneurial opportunities. Our analysis also shows low synergy from the simultaneous presence of knowledge created by universities and industry in a given area, as these two are, under some conditions, substituting each other in stimulating knowledge-intensive entrepreneurship at the local level. Third, we show that the specialization/diversity of technological knowledge that is created within a region does not play an important role in creating a high number of entrepreneurial opportunities. These findings bring a new perspective and contribute to settling down some of the lasting debates, opening opportunities for further research and rethinking policy measures.

The factors driving industrial integration: A fuzzy set qualitative comparative analysis

The literature emphasizes that interactions between biotic (the individual) and abiotic entities (the institutional environment) are central to entrepreneurial ecosystems. However, despite the importance of digital entrepreneurial ecosystem (DEE) elements, it might be questioned if all elements are equally necessary. Furthermore, different outputs might require different conditions. The same can happen with different levels of a given output. The answer to these questions is of particular concern from a policy perspective. By using necessary condition analysis (NCA) alongside with fuzzy-set qualitative comparative analysis (fs/QCA), this study advances understanding of the entrepreneurial ecosystems. While fs/QCA identifies only one necessary condition to produce digitally-enabled unicorns – market conditions – and none to unicorns and new business creation, NCA shows that all elements of DEE are necessary to produce digitally-enabled unicorns, and most of them are also necessary for producing unicorns. NCA also identifies formal institutions, regulations, and taxation and finance as necessary conditions for new business creation. Moreover, NCA shows that necessary conditions do not have the same degree of importance, and the necessity of a given condition does not automatically imply its highest level is required. For researchers, these results emphasize the importance of using NCA as a complement of fs/QCA. For practitioners, these findings can be used to optimize the allocation of policy resources, particularly targeting the elements that constitute bottlenecks.Plain English SummaryPolicymakers should target different levels of entrepreneurial ecosystem pillars performance to produce unicorns. Ambitious entrepreneurship is important for country competitiveness in the digital age. Digital entrepreneurial ecosystems can facilitate the rise of digitally-enabled unicorns, an extreme case of ambitious entrepreneurship. This study shows which conditions are necessary to produce this output; these conditions can be required at different levels. The comparison of country’s performance on each condition shows which of them constitute bottlenecks. Although all elements of digital entrepreneurial ecosystems are relevant for digitally-enabled unicorns, policymakers should target the ones that constrain the emergence of this output. This study identifies the levels that should be reached in each condition, not only for digitally-enabled unicorns, but also for unicorns in general. The results show relevant differences between the levels needed for these outputs. For example, knowledge creation and dissemination seem to be more important to boost digitally-enabled unicorns rather than unicorns in general. Thus, policymakers should consider specific levels of the conditions to optimize resource allocation.

PurposeThe aim of this research is to unravel how the entrepreneurial ecosystem (EE) elements can be configured to generate a higher density of knowledge-intensive entrepreneurship (KIE) dedicated to blended value creation (BVC).Design/methodology/approachBased on two asymmetric techniques, necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA), we conducted a quantitative analysis with Brazilian projects participating in the Innovative Research in Small Businesses Program, an initiative dedicated to nurturing KIE in the State of São Paulo, Brazil.FindingsThe results show six paths related to EE elements driving BVC with adequate consistency and coverage. No EE dimension appeared as a necessary condition to promote higher levels of BVC. On the other hand, findings highlight the “market” and “innovation” dimensions as core causal conditions in three of six configurational paths. Surprisingly, the absence of the “regulatory environment” and “human capital” dimensions appeared as a core condition in three alternative configurations associated with improved BVC levels.Research limitations/implicationsThe study contributes to the literature on EE and BVC in the context of a developing country. However, our sample’s specificity may limit our findings’ generalizability to EE embedded in different macro-level contexts.Practical implicationsThe paper is addressed to academicians, practitioners, policy decision-makers and educators. Given the regulatory environment’s low significance, practitioners can leverage government initiatives and programs that support small companies with environmental and social significance. Additionally, the human capital shortage underscores the potential to implement more flexible work arrangements to facilitate BVC in entrepreneurial firms.Originality/valueThis is the first study that analyzes the interaction between KIE, EE and BVC. The findings suggest that creating social, environmental and economic value is loosely associated with several key pillars of EE within the examined sample, highlighting low levels of ecosystem “readiness” to support knowledge-intensive ventures.

Entrepreneurial ecosystems (EEs) are receiving greater attention both in the academic world and in the field of government action. Recently, many studies have used a configuration perspective in the analysis of EEs. However, many of these studies have not specifically addressed whether different EE configurations can produce similar outputs; that is, they do not properly explore the concept of equifinality. Our main purpose was to fill this theoretical and empirical gap by exploring and demonstrating the patterns of performance of EEs (e.g., configurations) along a bundle of entrepreneurial outcome indicators. Using the Entrepreneurship Framework Conditions (EFCs) indicators provided by the Global Entrepreneurship Monitor (GEM) from 60 countries and applying exploratory factor analysis and cluster analysis, we identified and developed five distinctive EE configurations. Later, by applying analysis of variance (ANOVA) to compare these EE configurations across the entrepreneurial outcome indicators, we were able to show distinctive (dis)similarities with respect to the outcome indicators investigated. The results contribute to the understanding that there is not only one type of successful EE. In other words, the equifinality of EEs was empirically evidenced by our analysis. This is a significant theoretical contribution to the field, emphasizing the need for a broader view of how EEs may be configured and denying the relevance of searching for an ideal EE.

What makes an Entrepreneurial Ecosystem more conductible to Entrepreneurial Dynamics than another ? Entrepreneurial Ecosystem research raised as a hot topic, leading to progresses on its elements, network, actors components, or levels of analysis. However, some scholars regret the absence of empirical analysis of EE as a whole to understand how EE configuration operates. To open this perspective we propose an unexplored inter-organizational ties analysis among all Entrepreneurial Ecosystem actors, at a country level scale. Nested in Network Theory perspective, we run an exploratory research in five low income African countries, using innovative research methods (Quantitative Graph Theory, web scraping, fuzzy-set Qualitative Comparative Analysis) to understand the organisational patterns in these Entrepreneurial Ecosystem having an impact on their outcomes. At the core of this perspective we develop the impact of the central actor role of these Entrepreneurial Ecosystems, which is a key causal condition of their outcomes, in our case entrepreneurial dynamics levels and trends in those low income countries. This research underlines how important are Entrepreneurial Ecosystem network attributes to facilitate the efficient distribution of entrepreneurial nurturing components to entrepreneurs. It highlights also the importance of a financial central actor to sustain high Entrepreneurial Dynamics levels.

Entrepreneurial ecosystem and urban innovation: Contextual findings in the lens of sustainable development from China

Purpose As innovative household products, social home robots have a significant impact on the interactive consumer experience. However, prior research on consumer intentions to use such robots has rarely considered the configuration perspective. The present study examines how consumers balance the key benefits and risks created by these robots and explores how key influential factors jointly influence usage intention from a configuration perspective. Design/methodology/approach We adopted a hybrid research design. In Study 1, a thematic analysis was conducted to derive a conceptual framework reflecting the interplay of key factors influencing usage intention. In Study 2, a fuzzy set qualitative comparative analysis (fsQCA) was applied to reveal how these factors jointly shape usage intention. Findings Equifinal configurations of antecedent conditions (i.e. emotional and instrumental support beliefs, concerns about informational and relational privacy risks, self-construal and anthropomorphic design) led to usage intention. Additionally, four distinct benefit-risk trade-off patterns emerged across individuals. Research limitations/implications This study highlights the need to examine robot adoption in interactive marketing, particularly in the service domain. It has implications in the context of commercializing social home robots, emphasizing the potential of leveraging social home robots to enhance interactive consumer experiences and foster close connections with consumers. Originality/value We developed a neoconfigurational model to obtain a comprehensive understanding of social home robot acceptance in domestic settings, highlighting its implications for consumer–robot interactions and advancing research in interactive marketing.

Institutional environment is the most fundamental soil for the survival and development of industries, and the synergistic effect of institutional environment factors can help the development of rural industries. The article uses the marketization index related data of 31 provinces (autonomous regions, municipalities directly under the central government) in China in the year of 2019, and adopts the fuzzy set qualitative comparative analysis method (fsQCA) to explore the path of institutional environment driving rural industrial development from the perspective of configuration. The results of the study show that: (1) One single institutional environment factor is not a necessary condition for generating high efficiency of rural industries. (2) The development of rural industries is influenced by multiple institutional environment factors, which are “multiple and concurrent” to form diverse groupings, that is, to promote the development of rural industries in the way of “different paths to the same destination.” (3) There are two types of institutional environment groupings that can enhance the efficiency of rural industries: legal environment-driven type and product market-driven type. The significance of this study is that analyzes the impact of the interaction of various institutional environment factors on rural industrial development, enriches the research on rural industrial development, and reveals the complex causal mechanism of the institutional environment in promoting rural industrial development.

As key players in innovation and entrepreneurial ecosystems, Higher Education Institutions (HEI) assume a position as catalysts in creating and disseminating knowledge with repercussions in the societal, economic, political and innovation environments. In this scenario, HEI are facing the need to balance the performance of their traditional missions—teaching and research—with the pursuit of entrepreneurial performance. This brings awareness of the need to pay particular attention to HEI entrepreneurial performance (HEIEP) and how to measure it. Based on HEInnovate, a self‐assessment tool resulting from a joint effort of the European Community and the OECD, this study aims to explore the benefits of university entrepreneurial metrics, analysing HEIEP as a discriminant function of the HEInnovate dimensions complemented with a qualitative approach using Fuzzy Set Qualitative Comparative Analysis (fsQCA). The analysis provides valuable details, presenting recipes based on the HEInnovate dimensions or combinations of dimensions to achieve a mission legitimation. This research brings awareness to the use of the HEInnovate scale, where it is possible to highlight the importance of the digital transformation and capability dimension to entrepreneurial performance (EP) and university mission legitimation.

PurposeThis study explores configurations that promote the development of collective economies in China's rural villages and reveals the multiple development pathways that otherwise remain relatively unexamined in the literature.Design/methodology/approachThe authors obtained first-hand representative case data from 20 villages in 12 counties in 5 provinces in East, West and Central China via fieldwork and applied fuzzy set qualitative comparative analysis (fsQCA) to conduct a configurational comparative study of the development of village collective economies.FindingsThis paper identifies five factors in the current literature that affect the development of village collectives, based on an “entrepreneur–situation” analytical framework. Using the fsQCA method, this study further obtains two main configurations of conditions that culminate in the growth of rural collective economies in China. The first solution is the “top-down path”: When entrepreneurial leadership (EL), resource endowment (RE) and government assistance (GA) are present, a village collective economy will experience a high level of development, irrespective of policy support (PS) and villagers' participation (VP). The second solution is the “bottom-up path”: When EL, VP and PS are present and GA is not present, a village collective economy will experience a high level of development, irrespective of RE. In both situations, EL stands out as the core condition for the development of village collective economies, implying the need for the government to vigorously cultivate the entrepreneurial skills and aspirations of village cadres.Originality/valueTaking a configurational perspective and using an fsQCA approach, this research constructs an “entrepreneur–situation” analytical framework to investigate the key combinations of factors and pathways involved in the high level of development of Chinese village collective economies.

Existing research has emphasized that public sector knowledge is conducive to stimulating entrepreneurship. This article shifts the focus and extends the Knowledge Spillover Theory of Entrepreneurship (KSTE) by introducing a theoretical framework for reverse knowledge spillovers (RKS), which explores how private sector knowledge catalyzes entrepreneurial activity within the public sector. Drawing on KSTE, open innovation theory, and public sector entrepreneurship literature, we delineate key elements of RKS (such as actors, types of innovation, dimensions of proximity, and transfer mechanisms), and examine the relationships between these elements. This study highlights the practical and policy implications of RKS, advocating for more dynamic interactions between private and public sectors. By fostering these interactions, this research aims to inform strategic management and policy-making, ultimately strengthening and enhancing entrepreneurial ecosystems.

Aim/purpose – In this paper, we explore the contribution of Human Resource Manage- ment Systems (HRMS) to innovation in SMEs. We consider two HRMS with different orientations: Commitment HRMS (focusing on long-term career development to in- crease employees’ creativity) and Collaboration HRMS (focusing on the use of external human capital to achieve innovation). We believe that SMEs’ radical and incremental innovation follow different paths from a configurational perspective. We want to under- stand how the two HRMS influence radical and incremental innovation, consequently, we explore the contributions of Commitment HRMS and Collaboration HRMS. Design/methodology/approach – We apply a set-theoretic method, an analytic quanti- tative and qualitative technique to approach data – fuzzy-set Qualitative Comparative Analysis (fsQCA) – to test our models. We use a sample of 377 Portuguese SMEs from across industries. Findings – Results show there are two pathways that lead SMEs to high levels of incre- mental innovation and three alternative paths that originate high levels of radical innova- tion. By contrast, there are ways that lead to lower levels of incremental (two options) and radical innovation (three options). Research implications/limitations – We provide propositions for theory development on the contribution of HRMS to innovation. Managerial contributions regard the several options provided to SME managers in search of innovation. Limitations regard the lack of generalization power of results due to the cross-sectional nature of the work. However, the research design is replicable without restrictions. Originality/value/contribution – We suggest that SMEs’ radical and incremental inno- vation follow different paths from a configurational perspective. With this study, we contribute to showing the diversity of ways to reach higher innovation levels at SMEs, so that managers know the alternatives they have at their disposal. Additionally, we reveal the ways that lead to lower innovation levels at SMEs, so we alert managers to the undesired pathways they should be cautious about. Keywords: Human Resources Management Systems, incremental innovation, radical innovation, SME, fsQCA. JEL Classification: M12, O15, O31.

Policy-makers are seeking to build vibrant entrepreneurial ecosystems (EEs) to promote innovative entrepreneurship. However, the role of government policy in EEs, especially in the emerging economy context, is poorly understood, lacking a systematic concept of policy and theoretical framework, clear policy classification, and empirical research considering distinctive characteristics of policy mixes in EEs. This paper introduces the concept of EE policy mixes and classifies them into seven policy instruments. Using data from 21 national high-tech zones (NHZs) in China, fuzzy-set qualitative comparative analysis (fsQCA) is applied to identify effective configurations of EE policy mixes that support early-stage and late-stage technology start-ups to produce high entrepreneurial performance. The configurational analysis shows that EE policy mixes present causal complexity and stage differences. Based on interpreting multiple policy interactions, we reveal the differentiated support mechanisms of EE policy mixes in NHZs and draw out their implications for research, policy, and practice. This study contributes to the EE literature by adopting a policy-mix perspective to examine the role of policy, exploring the specific emerging economy context of China, suggesting further extensions of the research to other contexts, and applying a methodology that reveals causal mechanisms. It also supports better-informed EE policy and governance.