Configurations of institutional enablers that foster inclusive entrepreneurship: A fuzzy-set qualitative comparative analysis

Vargas-Zeledon, Aaron A.; Lee, Su-Yol Article Configurations of institutional enablers that foster inclusive entrepreneurship: A fuzzy-set qualitative comparative analysis Journal of Innovation & Knowledge (JIK) Provided in Cooperation with: Elsevier Suggested Citation: Vargas-Zeledon, Aaron A.; Lee, Su-Yol (2024) : Configurations of institutional enablers that foster inclusive entrepreneurship: A fuzzy-set qualitative comparative analysis, Journal of Innovation & Knowledge (JIK), ISSN 2444-569X, Elsevier, Amsterdam, Vol. 9, Iss. 4, pp. 1-14, https://doi.org/10.1016/j.jik.2024.100549 This Version is available at: https://hdl.handle.net/10419/327451 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. 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Vargas-Zeledon a , Su-Yol Lee b, * a Doctoral student, College of Business Administration, Chonnam National University, Yongbong-ro 77, Buk-gu, Gwangju, South Korea b College of Business Administration, Chonnam National University, Yongbong-ro 77, Buk-gu, Gwangju, South Korea ARTICLE INFO Article History: Received 20 November 2022 Accepted 19 August 2024 Available online 23 August 2024 ABSTRACT Inclusive entrepreneurship, which represents an integrated approach to entrepreneurship and social inclusion, has increasingly received attention for its expected capacity to simultaneously foster economic growth and mitigate inequality. This study examines how the configuration of institutional enablers, which encompass several characteristics involving markets, finance, policy, education, and knowledge, fosters inclusive entrepreneurship outcomes. The results of a fuzzy-set qualitative comparative analysis using 69 country cases indicate that institutional enablers—excluding market openness—jointly affect inclusive entrepreneurship outcomes. This study provides evidence that such effects vary depending on the level of a country’s economic development. As one of the first to explore the topic of inclusive entrepreneurship, this study has significant implications for academics, practitioners, and policymakers. © 2024 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/) Keywords: Inclusive entrepreneurship, Institutional enablers Fuzzy-set qualitative comparative analysis (fsQCA) Global entrepreneurship monitor (gem) World economic forum (WEF) JEL classification: M13 O17 O57 Introduction Entrepreneurship has always been encouraged for its long-term effects on job creation and economic development (Welter et al., 2017;Acs et al., 2016;Dabla-Norris et al., 2015;Arshed et al., 2014). However, it remains unclear how it influences inequality (Bruton et al., 2021). Furthermore, entrepreneurial activity may be limited to those who can easily access basic infrastructure and public goods, such as education and healthcare (Bruton et al., 2021). It may be restricted in some areas where access to public goods is less equitable and where the barriers to starting a business are more severe (Pilkova et al., 2016). As economic inequality has risen dramatically worldwide in recent years (Piketty, 2014), inclusive entrepreneurship has increasingly received attention as an alternative type of entrepreneurship (OECD, 2016). It represents the involvement of underrepresented or disadvantaged groups in entrepreneurial activities for their economic self-sufficiency, which is beneficial not only to themselves but also to society, as it addresses and provides equal opportunities and participation and eliminates the difficulties and social exclusion of vulnerable groups (OECD, 2013;Weidner et al., 2010; Prahalad, 2009). Research on inclusive entrepreneurship remains limited, as it is a relatively novel phenomenon (Wu et al., 2022). Two research streams are relevant to the literature on inclusive entrepreneurship: inclusive growth and social entrepreneurship. First, inclusive growth provides a theoretical and research foundation to explore the relationship between social inclusion and economic development (Hall et al., 2012;McMullen, 2011). Research on this topic focuses on how institutions should be designed to encourage underprivileged people to start their businesses (Chataway et al., 2014;Cozzens & Sutz, 2014;George et al., 2012;McMullen, 2011). It is concerned with relevant policies—i.e., from the government’s perspective—that foster sustainable growth and reduce poverty in emerging economies (Qiang et al., 2016;Joseph, 2014), seldom addressing the entrepreneur’s perspective (Wu et al., 2022). Second, research on social entrepreneurship employs the logic of business to improve the situation of socially excluded and marginalized groups and presents theoretical and practical foundations for poverty reduction, minority empowerment, and inclusive growth to drive social transformation and institutional change (Saebi et al., 2019;Ghauri et al., 2014;Datta & Gailey, 2012; Alvord et al., 2004). However, this strand of the literature focuses * Corresponding author. E-mail address: [email protected] (S.-Y. Lee). https://doi.org/10.1016/j.jik.2024.100549 2444-569X/© 2024 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/) Journal of Innovation & Knowledge 9 (2024) 100549 Journal of Innovation &Knowledge https://www.journals.elsevier.com/journal-of-innovation-and-knowledge on “social purpose”and therefore tends to overlook the general entrepreneurial purpose of underrepresented groups. In general, inclusiveness is unquestionably a multidisciplinary issue comprising the entrepreneurial approach and other academic disciplines (Pilkova & Rehak, 2017;OECD, 2020b). Considerable gaps remain in the otherwise adequate conventional theories of entrepreneurship and the study of the new domain of inclusive entrepreneurship from a localized perspective. Previous studies have yet to articulate the dynamic nature of inclusive entrepreneurship from an institutional perspective and are therefore yet to identify what precisely promotes it (Rodrigues et al., 2022). Prompted by the gaps in the literature, the present study explores the enablers of inclusive entrepreneurship from an institutional perspective. We present a research framework that deploys the category of entrepreneurial atmosphere as a mediator that depicts the relationships between the enablers—market openness, financial accessibility, policy affability, knowledge availability, and entrepreneurial readiness—and inclusive entrepreneurship outcomes. While this study’s approach is rooted in the perspective of institutional and policy design for general entrepreneurship, it also addresses similarities and differences between general and inclusive entrepreneurship. This study contributes to the existing literature in three distinct ways. First, this study is one of the earliest of its kind to incorporate inclusiveness into entrepreneurship. Inclusive entrepreneurship—a concept first proposed by the OECD in 2013 to refer to the equality of opportunities made available to everyone in society—has increasingly gained scholarly attention (OECD, 2013;Amaro da Luz & Albuquerque, 2014). This study sheds light on this concept in both theoretical and practical terms. Second, this study explores the connection between institutional drivers and inclusive entrepreneurship outcomes. Although previous studies on underrepresented groups— the youth, women, the elderly, etc.—examine the enablers of entrepreneurial activities (Pilkova et al., 2016;Sharma & Madan, 2013;Holienka & Holienkova, 2014), they limit their analysis to personal traits, including individual attitudes, competencies, and skills. The present study examines the effects of institutional enablers on inclusive entrepreneurship outcomes as mediated by entrepreneurial atmosphere. Third, this study, one of the first to employ fuzzy-set qualitative comparative analysis (fs-QCA) in the research area of inclusive entrepreneurship, corroborates previous evidence of the methodological efficacy of fs-QCA in the field. It presents fine-grained and plausible explanations for the antecedents and consequences of inclusive entrepreneurship, identifying conditions where different configurations result in the same outcomes. As a whole, this study explores an advanced research stream of inclusive entrepreneurship and avoids over-simplification to fit a linear−additive explanation. The rest of this paper is organized as follows: Section 2 provides a comprehensive review of the literature on inclusive entrepreneurship and presents the study’s research framework and hypotheses. Section 3 articulates the research method, including the variables and fs-QCA. Section 4 presents the results and discussion, and Section 5 concludes with academic and policy implications and suggestions for future research. Theoretical background and research framework Inclusive entrepreneurship Inclusive entrepreneurship was first proposed by the OECD and the European Commission in The Missing Entrepreneurs: Policies for Inclusive Entrepreneurship in Europe in 2013. It was conceived in response to the debate on the relationship between entrepreneurship and inequality, which emerged and spread in the early 2010s. Conventionally, entrepreneurship has been encouraged to drive economic growth and shape how each nation distributes the benefits of growth (Dabla-Norris et al., 2015;Lloyd-Ellis & Bernhardt, 2000). However, the last three decades have witnessed the persistence of economic inequality and wide dispersion of economic outcomes. Moreover, levels of economic inequality around the world have dramatically risen (Bapuji et al., 2020;Piketty, 2014;OECD, 2011), despite entrepreneurship becoming a worldwide phenomenon. Economies are understood to consist of two distinct sectors—the formal and the informal—each with its distinct institutional characteristics. Entrepreneurship that occurs primarily in the formal sector, the conventional domain, may result in more exclusionary institutions and increase inequality. This has led to an increased awareness of the need for an alternative entrepreneurship model that belongs in the informal sector, results in more inclusive institutions, and helps decrease inequality (Bruton et al., 2021). Inclusive entrepreneurship is complex, dynamic, and multidimensional, with various actors interconnected in new forms of longstanding ventures (Pilkova et al., 2016). Its concepts and definitions derive from the work of various scholars and institutions and subtly differ according to their emphasis and context. However, a common ground from which to understand inclusive entrepreneurship is the engagement of underrepresented groups in entrepreneurial activities. In particular, the OECD proposes the conception of inclusive entrepreneurship as an entrepreneurial philosophy that gives all people equal opportunities to start a business and support its development, targeting marginalized and vulnerable groups, including the youth, women, the elderly, ethnic minorities, immigrants, and the disabled (OECD, 2017;Qiang et al., 2016). Based on previous studies, we conceptualize inclusive entrepreneurship as the engagement of the underrepresented or disadvantaged actors of society in entrepreneurial processes, by eliminating their social exclusion and unleashing their creative potential for self-employed work, facilitating their participation in opportunities in venture creation, and helping their start-ups become long-standing, innovative, and employable ventures. The ultimate end of inclusive entrepreneurship is to relieve and solve the social problems of exclusion and inequality. Inclusive entrepreneurship opens up a venue for civil society to help reduce inequality and social exclusion, whether through start-ups, microbusinesses, or small enterprises. In this vein, inclusive businesses are an essential economic and social value because they are not solely for profit(de Sousa & Comini, 2012). In general, they enable the linkage of the low-income sector, particularly under-represented actors, to the market to improve their living conditions. Research framework: institutional enablers of inclusive entrepreneurship Although very few studies examine the factors that facilitate inclusive entrepreneurship, there is a consensus that institutional support, such as policies, is a significant external force for achieving it (OECD, 2016;Qiang et al., 2016;Ren & Huang, 2016). Engaging underrepresented actors in entrepreneurial activities requires institutional and structural changes to mitigate the conditions of inequality, in which opportunities are unevenly allocated across the economy. This study presents a research framework for exploring the enablers that promote inclusive entrepreneurship from an institutional viewpoint. Taking entrepreneurial atmosphere as a mediator, this study specifically posits the following enablers of inclusive entrepreneurship outcomes: market openness, financial accessibility, policy affability, knowledge availability, and entrepreneurial readiness (Fig. 1). First, this study argues that the market structure of an economy is vital in fostering inclusive entrepreneurship. Inclusive entrepreneurship involves the accessibility of products and services, mainly because entrepreneurs from the informal sector may find it challenging to obtain official market support (Bruton et al., 2021). Nonetheless, entrepreneurs form a wide range of social associations that help them counteract prevalence criteria. The products or services offered A.A. Vargas-Zeledon and S.-Y. Lee Journal of Innovation & Knowledge 9 (2024) 100549 2 must be competitive and sufficient to ensure the survival of underrepresented groups’start-ups. When entry barriers are low and markets are open to new entrants, informal actors are encouraged to engage in entrepreneurial ventures. Fear of unfair competition hinders inclusivity, as it discourages entrepreneurs from participating in a wider network (World Economic Forum −WEF, 2017;Melo et al., 2013). Encouraging employability in the entrepreneurial process, particularly in underprivileged regions, brings more inclusive opportunities through market potential and information accessibility channels (Ma et al., 2021;OECD, 2016). Second, financial accessibility refers to the provision of inclusive financial and administrative advisory support to underrepresented groups. In this respect, opportunity-based entrepreneurship implies that entrepreneurs can acquire the necessary resources. However, underrepresented groups, which usually consist of informal actors, typically face constraints in obtaining such resources. As such, new forms of entrepreneurial financing are crucial for entrepreneurs seeking to start a business; moreover, their ability to access a range of financial products and services is essential, particularly at certain stages of their ventures (Karim et al., 2021;Nizam et al., 2020;Fan & Zhang, 2017;Bruton et al., 2014). Third, inclusive entrepreneurship should be an emphasis of governments in general because inequality is detrimental to well-being and economic development (Bruton et al., 2021). Legislation, policies, and government programs are factors that foster venture creation among underrepresented actors; as such, they should be transparent, accessible, and favorable to them. This is especially important in emerging markets, where the promotion of inclusive entrepreneurship is closely associated with national policies and institutional and resource advantages, increasingly encouraging the public, especially vulnerable groups, to participate in inclusive entrepreneurship (Choe & Lee, 2020; Dodaro, 2019;OECD, 2017). Fourth, inclusive entrepreneurship involves creating the conditions for forming partnerships, disseminating knowledge, and popularizing the most acceptable practices of sustainable and inclusive development at the national level. In sustainable entrepreneurship, which involves start-ups, small ventures, and larger companies, entrepreneurs rely on various sources (Belz & Binder, 2017). Any strategy of economic development must be concerned with people and sustainability to address the needs of a vast number of vulnerable and marginalized people. As such, skills, knowledge, networks, and creativity development are valuable to any country-wide environment that allows the emergence and fosters the development of sustainable entrepreneurship (Argade et al., 2021;Johnson & Horisch, 2021). Fifth, we present entrepreneurial readiness as one of the most critical institutional enablers of inclusive entrepreneurship. It encompasses institutional and infrastructural factors that cultivate human capital and the capabilities of underrepresented groups. Its key components include human capital, particularly the improvement of the capabilities and skills of current high-growth entrepreneurs and venture businesses and demand-oriented educational, technical, and vocational training services. In particular, entrepreneurship education focuses on individuals who may not be interested in starting a business. However, once they recognize an entrepreneurial opportunity and a sense of prospect, they may ultimately decide to start a business any time (Burch et al., 2019). Following the discussion above, this study proposes the first proposition on the enablers of inclusive entrepreneurship. Proposition 1.Market openness, financial accessibility, policy affability, knowledge availability, and knowledge readiness are the institutional enablers that play a critical role in fostering inclusive entrepreneurship. In other words, these enablers are positively associated with inclusive entrepreneurship outcomes. Entrepreneurs may rise and fall, or assume fluid roles, permitting their ventures to incorporate materiality that may play a critical role in shaping the venture creation process (Gehman & Soubliere, 2017). In this sense, understanding this process and the social perspective of entrepreneurship leads to a better comprehension of performance in entrepreneurship (Gruber & McMillan, 2017). From this perspective, culture is an essential aspect of the entrepreneurial domain, regardless of how entrepreneurs might deploy cultural resources to legitimate their new ideas and ventures (Gehman & Soubliere, 2017). In this study, we argue that the entrepreneurial culture and atmosphere of a society influence inclusive entrepreneurship outcomes. For example, entrepreneurial culture is cultivated through a dynamic process of disseminating entrepreneurial success stories and how entrepreneurship ranks as a career choice among young entrepreneurs. Accordingly, entrepreneurial culture is affected by risks and the possibility of failure, indifferent social attitudes toward entrepreneurship, and the existence of an informal economy. This is where the pathway to decent work intersects with entrepreneurial culture. Where social and cultural norms on entrepreneurship matter, underrepresented entrepreneurs become more willing to transform their Fig. 1. Research framework: Institutional enablers of inclusive entrepreneurship. A.A. Vargas-Zeledon and S.-Y. Lee Journal of Innovation & Knowledge 9 (2024) 100549 3 business ideas into reality (Wang & Richardson, 2021;Wry et al., 2011;Lounsbury & Glynn, 2001). This argument leads to our next proposition. Proposition 2.The institutional enablers positively influence inclusive entrepreneurship outcomes by cultivating an entrepreneurial atmosphere.. From an institutional perspective, institutions are the primary drivers of the key differences between economies, particularly emerging and mature economies (Acemoglu & Robinson, 2012; Webb et al., 2010). Institutional contexts vary widely across emerging economies, each with its characteristics, which in turn constitute differences in the foundations of inclusive entrepreneurship (Bruton et al., 2021;Prahalad, 2004). For instance, the formal and informal sectors, which are widely used to characterize economies, typically shape entrepreneurial activities. The formal sector is characterized primarily by market-supporting institutions inhabited by privileged actors, whereas the informal sector represents disadvantaged and vulnerable groups whose economic activities focus primarily on subsistence (Bruton et al., 2021). The structures of the formal and informal sectors vary across countries and economies, which may affect the pathway of effects between institutions and inclusive entrepreneurship outcomes because they shape not only a person’s work, but also such factors as where someone lives and with whom he/she interacts. The OECD’s Global Entrepreneurship Monitor (GEM) claims that there is a linkage between entrepreneurship dynamics and an economy’s institutional conditions and level of development, which either support or hinder new business creations in terms of both general and inclusive entrepreneurship (2020). GEM reports differences in inclusive entrepreneurship in economies with various levels of development: factor-driven, efficiency-driven, and innovation-driven economies (OECD, 2020a;Pilkova et al., 2016;Bosma & Levie, 2010). The level of economic development directly influences entrepreneurial opportunities, capacity, and preferences, which in turn determine business dynamics (Singer et al., 2015). Based on this argument, we put forward the next proposition on the effect of an economy’s level of development on inclusive entrepreneurship. Proposition 3.The effects of institutional enablers on inclusive entrepreneurship outcomes vary according to the level of economic development. Inclusive entrepreneurship is a dynamic and multidimensional phenomenon consisting of complex causalities and multiple interactions between actors in the development of new forms of long-standing ventures (Pilkova et al., 2016). The institutional causal factors for inclusive entrepreneurship can be configured in different ways. First, the dynamic nature of inclusive entrepreneurship is conditional rather than deterministic, as different configurations can lead to the same outcomes (Yao & Li, 2023). Thus, traditional linear−additive models cannot explain the causalities between the enablers and outcomes of inclusive entrepreneurship. Some institutional enablers may be necessary or sufficient to promote inclusive entrepreneurship, implying that interaction patterns and institutional conditions influence the direction of the final and desirable policy outcomes (Choi & Lee, 2020). The entrepreneurship literature has provided evidence of configurational causal conditions for fostering entrepreneurial activity. Lewellyn and Muller-Kahle (2016) demonstrate the value of using a configurational analytical technique in simultaneously exploring the micro and macro complexities of what drives women globally to engage in entrepreneurial activity. The result of their study shows that the micro-level attributes of entrepreneurial self-efficacy and opportunity recognition, combined with the macrolevel formal business environment institutions and national culture, create configurations of conditions that lead to high levels of entrepreneurial activity. Zhao et al. (2023) identify an entrepreneurial ecosystem consisting of market, finance, human capital, internet access, transportation, and government, and employ fs-QCA to analyze the combined effects of multiple elements underpinning urban innovation. Their study finds the complex causal mechanism of multiple factors in the entrepreneurial ecosystem, which clarifies the equivalent driving path of a high level of urban innovation. Xie et al. (2021) explore possible configurations of entrepreneurial cognition, culture, policy, finance, and education to increase female entrepreneurship. Using fs-QCA, they identify three configurations for high female entrepreneurship: the cognition−culture−dominant path, the culture−finance−dominant path, and the cognition−policy −dominant path. Douglas et al. (2021) also present configurations of antecedent conditions that constitute alternative pathways to entrepreneurial intention, and these pathways accommodate the different entrepreneurial types observed in the literature. Second, previous studies provide evidence of configurational causal conditions leading to the same outcome in related research domains. Apetrei et al. (2019) present evidence indicating that the fundamental basis for sustainable development through entrepreneurial attitudes is closely associated with the presence of inclusive institutions and the avoidance of extractive ones. They posit that the mitigation of inequality through entrepreneurship is contingent upon a complex relationship between the entrepreneurial attitudes, institutional frameworks, and cultural variables of a given society. Cervello-Royo et al. (2022) identify a simultaneous association between a country’s entrepreneurial activity and its innovation level, country risk factor, and sustainable development goals (SDG3 and SDG11). Their study emphasizes the casual combinations of innovation and financial and sustainable conditions that enhance a country’s entrepreneurship level. This implies that different configurations can lead to the same outcome, rather than a single factor operating in a linear manner. In a recent study, Yu and Huarng (2024) examine the causal complexity of the achievement of sustainable development goal. They posit a threefold proposition comprising a set of antecedents, including digital technology, transparency and integrity, innovation, entrepreneurship, economic growth, and financial technology. They claim that these factors can collectively enhance a country’s sustainability level. Mu~ noz and Kibler (2016) employ fsQCA to investigate the impact of institutional factors on social entrepreneurship. Their results indicate the existence of multiple causal paths in both formalized and less formalized contexts, thereby reinforcing the idea of multiple conjunctional causation. To illustrate, even though less formalized institutional structures appear to be more influential than formal regulations and support, a single informal institutional condition is inadequate to offset the central impact of the perceived influence capacity of local bodies on the opportunity confidence of social entrepreneurs. Third, the specific configurations of institutions that encourage inclusive entrepreneurial activity may vary according to the country’s context. Using regression and fs-QCA, Velilla and Ortega (2017) demonstrate the existence of disparate configurations of the requisite and sufficient entrepreneurial determinants in developed and developing countries. For example, whereas the principal determinants in developed countries are education and technological equity, individuals in developing countries are inclined to become entrepreneurs irrespective of their macroeconomic context. Beynon et al. (2016) employ fs-QCA with data from the GEM 2011 survey to investigate entrepreneurial attitudes and activity. Their findings identify discrepancies in the potential combinations of factors influencing entrepreneurship across individual countries at varying stages of economic development. For example, growth-enhancing policies may be the most relevant institutional enabler in innovationdriven countries. Beynon et al. (2020) also provide evidence of the potential impact of combinations of several factors on entrepreneurial activity in different types of national economies over time. They present the heterogeneous experiences of developing and developed economies as two distinct groups experiencing changes in total early-stage entrepreneurial activity (TEA) and associated causal configurations over time. A.A. Vargas-Zeledon and S.-Y. Lee Journal of Innovation & Knowledge 9 (2024) 100549 4 Based on this argument, we propose the following proposition on the interactions of the institutional enablers of inclusive entrepreneurship. Proposition 4.The effects of institutional enablers on inclusive entrepreneurship outcomes form configurations according to their interactions. Research methodology fs-QCA This study employs fs-QCA—a method that is still in its early stages but which has recently received more attention in the fields of innovation and entrepreneurship (Chen & Tian, 2022;Du et al., 2021; Kraus et al., 2018)—for several reasons. First, QCA is suitable for studying complex causalities and multiple interactions because it is a configurational approach based on set theory and fuzzy algebra (Ragin, 2008;Fiss, 2011;Pappas & Woodside, 2021). In particular, it can be used to articulate complexities and explain how the interactions of conditions result in expected outcomes (Huang et al., 2023). This approach comprehends the complexities of managerial and organizational phenomena and facilitates the examination of the configuration of lower-level characteristics that constitute higher-level constructs (Misangyi et al., 2017), as in the case of inclusive entrepreneurship. Second, based on an asymmetric data analysis technique, this approach has the advantages of both qualitative and quantitative analysis methods. QCA combines the logic and empirical strength of qualitative approaches, which are rich in contextual information, with quantitative approaches, which can deal with sizable numbers and generalize from specific cases (Ragin, 2008;2006). Third, QCA is outcome-oriented and can determine whether specific conditions are necessary to achieve desirable outcomes (Du & Kim, 2021;Misangyi et al., 2017). In particular, fs-QCA can efficiently handle the exponentially cumulative complexity of a configurational perspective by deriving fuzzy sets. Overall, it is suitable for examining whether institutional enablers are necessary or sufficient to achieve a higher level of inclusive entrepreneurship using sizable numbers of national-level cases from the OECD’s GEM. Measurement and sample This study proposes five independent variables as institutional enablers of inclusive entrepreneurship, one mediator, and four dependent variables as inclusive entrepreneurship outcomes. Institutional enablers include market openness, financial accessibility, policy affability, knowledge readiness, and knowledge availability. First, market openness refers to the ease with which entrepreneurs enter the market. It indicates the existence of a free and open market where no single entity exerts too much influence, as well as the level of burdens and regulations entrepreneurs encounter upon entering markets. In particular, two items—“ease of entry: market dynamics” and “ease of entry: market burdens and regulations”—are used to measure market openness based on the expert ratings of the entrepreneurial framework conditions of Global Entrepreneurship Monitor GEM (2022). Second, financial accessibility characterizes an economy’sfinancial channels and infrastructure that support entrepreneurs. It is measured using two indicators: experts’ranking of access to entrepreneurial financing based on GEM and financing based on the World Economic Forum’s Inclusive Development Index (WEF IDI). Third, policy affability refers to the relevance of policies implemented to support potential entrepreneurs and ensure their social safety. Three items are used to measure policy affability: experts’ranking of government policy and entrepreneurship programs based on GEM and the social safety net protection indicator of WEF IDI. Fourth, knowledge readiness indicates how a society cultivates latent entrepreneurs through education and training. It is measured using three items: experts’ranking of entrepreneurial education at school and post-school settings based on GEM, and the availability of high-quality training services indicator of WEF IDI. Fifth, knowledge availability denotes how entrepreneurs can easily access and utilize relevant and necessary knowledge. It is measured using two items: experts’ranking of R&D transfer and commercial and professional infrastructure, both based on GEM. The dependent variables of inclusive entrepreneurship outcomes consist of four constructs. First, entrepreneurial activity is measured using two items: the entrepreneurial intention indicator and TEA of the adult population surveys of GEM (GEM APS). Second, opportunity-based TEA (OTEA) is measured using the motivational indicator of GEM APS. Third, general entrepreneurship performance is a composite of two items: the baby business owner indicator of GEM and the new business register indicator of WEF IDI. Fourth, inclusive entrepreneurship performance is measured using three items: the female ratio of new ventures, female ratio of TEA, and female ratio of OTEA from GEM APS. This study employs entrepreneurial atmosphere as a mediator between institutional enablers and outcomes. This construct is measured using five items: the social-cultural norms indicator of GEM, the perceived opportunity indicator, the entrepreneur status indicator, the promising career choice perception indicator of GEM APS, and the attitude toward failure indicator of WEF IDI. A sample was compiled from the WEF IDI, GEM, and GEM APS datasets. This study used the 2017 index of WEF IDI, the 2018 index of GEM, and the 2018, 2019, and 2020 indices of GEM APS. We only included samples that record measures of at least one item for each construct within the sample period. Thus, a total of 69 observations at country level were used. We categorized sample countries into four groups according to their level of economic development: advanced (number of cases = 24), second-advanced (number of cases = 15), upper-middle-income (number of cases = 16), and lowincome countries (number of cases = 14). Table A1 in the Appendix details the constructs and measures used in this study. Calibration Calibration involves transforming variables into a set membership, ranging from full non-membership that equals 0 to full membership that equals 1; 0.5 is the crossover point and indicates maximum ambiguity (Ragin, 2008;Schneider & Wagemann, 2012; Kraus et al., 2018). This calibration method employed in this study is based on the sample maximum, mean, and minimum (Fiss, 2011; Misangyi et al., 2017). Fs-QCA captures two types of conditions: those that are sufficient or necessary to explain an outcome and those that are insufficient on their own but are necessary to explain the results (Fiss, 2011). The actual sample distribution deviated from the scale anchors, so we reconciled the conceptual anchors with the actual distribution of the sample (Fiss, 2011;Misangyi et al., 2017). We set three anchor points—fully in, crossover point, and fully out—according to the sample maximum, mean, and minimum values. For example, we calibrated the 95 % for the “fully in”set of high performance and the 5 % for the “fully out”set. The crossover point was 50 %. To avoid theoretical difficulties at maximum ambiguity (0.5), we added a small constant of 0.001, following established practices (Fiss, 2011; Ragin, 2008). Table 1 presents a summary of this study’s statistics and calibration. Results Analysis strategy We used the fs-QCA3.0 software to analyze the standardized data. This instrument is capable of capturing (1) conditions that are sufficient or necessary to explain outcomes and (2) those that are insufficient on their own, but (3) are necessary parts of the solutions that A.A. Vargas-Zeledon and S.-Y. Lee Journal of Innovation & Knowledge 9 (2024) 100549 5 can explain the results. Following previous studies, we analyzed sufficiency using the minimum case frequency benchmark ≥1(De Crescenzo et al., 2020;Schneider & Wagemann, 2012) and raw consistency benchmark ≥0.8 (Du & Kim, 2021;Fiss, 2011). We also applied proportional reduction in inconsistency (PRI) to further filter out the truth table rows, which are reliably linked to the outcome (Greckhamer et al., 2018;Du & Kim, 2021). We followed three steps in conducting fs-QCA. First, using set measures (i.e., independent and mediating variables), fs-QCA generated the data matrix of a truth table with 2krows, where kis the number of causal conditions (i.e., combinations of variables) used in the analysis. Each row is associated with a specific combination of variables, and the full table lists all the possible combinations. In the second step, fs-QCA eliminated the rows according to sufficient, necessary, and insufficient solutions. In the third step, a Boolean algebra algorithm logically reduced the truth table rows and yielded the simplified and most potent combinations. Derived from a counterfactual analysis of causal conditions, the algorithm was used to classify the causal conditions representing the core and peripheral causes of the variables (Ragin, 2008). This study used a truth table algorithm to distinguish between parsimonious and intermediate solutions based on “easy”and “difficult”counterfactuals (Ragin, 2008). “Easy”counterfactuals refer to situations where a redundant causal condition is added to a set of extant conditions. “Difficult”counterfactuals indicate situations where a certain condition is removed from a set of causal conditions. Causal conditions are classified into three categories: core, conditional, and peripheral. Core and conditional conditions are part of both parsimonious and intermediate solutions, and a peripheral condition is eliminated in the parsimonious solution and therefore appears only in the intermediate solution (Fiss, 2011). Results of the analysis This study applied fs-QCA to a sample of 69 countries to examine whether or not institutional enablers affect inclusive entrepreneurship outcomes. The sample was classified into four distinct country contexts: advanced, second-advanced, upper-middle-income, and low-income economies. Table 2 summarizes the results of the fuzzy-set solution for the total sample. The evidence derived from the fs-QCA solution is not strong enough to indicate that institutional enablers have significant relationships with entrepreneurship outcomes. For instance, financial accessibility (FA), policy affability (PA), knowledge readiness (KR), and knowledge availability (KA) are conditional causal conditions, implying that their effects may be significant—but not always—to entrepreneurial activity (ENA) and opportunity-based TEA (OTEA) (see 1a in Table 2). However, FA and PA are critical to fostering entrepreneurship performance (ENP) (see 1b in Table 2). This result also indicates that PA, KR, and KA are crucial in facilitating inclusive entrepreneurship performance (IEP) (see 1c in Table 2). Significantly, entrepreneurial atmosphere (EA) affects entrepreneurship performance. In addition, PA, KR, and KA on IEP emerge as core causal conditions in which entrepreneurial atmosphere (EA) joins the solution (i.e., 1a !1c), indicating that social norms and culture can mediate the effects of institutional enablers on entrepreneurship outcomes. However, this result indicates that market openness (MO) is a peripheral condition: it does not have a direct and significant relationship with entrepreneurship outcomes. Overall, this result provides partial support for the first and second propositions. Table 3 presents the results of a fuzzy-set solution for an advanced economy. This result indicates that FA, PA, and KR are essential to entrepreneurship outcomes, specifically ENA, OTEA, ENP, and IEP. The solution (2b in Table 3) in which FA, PA, and KR are core causal conditions (i.e., noted as *FA*PA*KR) implies that inclusive entrepreneurship can be promoted through accessible financing for micro, small, and medium enterprises (MSMEs), supportive government policy and programs, and entrepreneurial education and training, a result that is in line with our expectation. Furthermore, these institutional enablers emerge as a core causal condition when EA joins the solution (i.e., 2a !2b), indicating the latter’s mediating role. However, MO is a peripheral condition in the advanced country context. Moreover, KA is shown to be a conditional causal condition, implying that it may have an effect, but not always, on entrepreneurship outcomes. This study analyzes the fuzzy-set solution by classifying country contexts based on their GDP per capita; the second-advanced economy context has a GDP per capita ranging from USD 17,000 to 30,000. Table 4 summarizes the results of the fuzzy-set solution for the second-advanced country context. For the ENA and OTEA outcomes, PA, KR, and EA are core causal conditions, with the absence of MO and KA. For this group, MO may be better when it is absent. The results for the upper-middle-income economies show that the institutional enablers have significant relationships only with Table 2 Configurations strongly related to inclusive entrepreneurship outcomes in a global context. Antecedent condition ENA OTEA ENP IEP 1a 1a 1b 1a 1c Market openness (MO) »»»»» Financial accessibility (FA)  Policy affability (PA)  Knowledge readiness (KR)  Knowledge availability (KA)  Entrepreneurial atmosphere (EA)  Raw coverage 0.136 0.136 0.014 0.110 0.016 Unique coverage 0.136 0.136 0.010 0.106 0.012 Consistency 1.000 1.000 1.000 0.909 1.000 Overall solution coverage 0.136 0.555 0.758 Overall solution consistency 1.000 0.979 0.986 Note: 1a represents a solution of [»MO*»FA*»PA*»KR*»KA*EA]; 1b represents a solution of [»MO*FA*PA*»KR*»KA*EA]; 1c represents a solution of [»MO*»FA*PA*KR*KA*EA] 1 ;= core causal condition; = conditional causal condition; »= peripheral causal condition. Table 1 Summary of statistics and calibration. Variable (code) Mean S.D. Min. Max. No. of cases Missing Market openness (MO) 0.39 0.47 0.03 1 69 0 Financial accessibility (FA) 0.90 0.28 0.03 1 69 0 Policy affability (PA) 0.90 0.29 0.03 1 69 0 Knowledge readiness (KR) 0.90 0.28 0.03 1 69 0 Knowledge availability (KA) 0.40 0.47 0.03 1 69 0 Entrepreneurial atmosphere (EA) 0.99 0.08 0.03 1 69 0 Entrepreneurial activity (ENA) 0.55 0.48 0.03 1 69 0 Opportunity-based TEA (OTEA) 0.54 0.47 0.03 1 69 0 Entrepreneurship performance (ENP) 0.72 0.41 0.03 1 69 1 Inclusive entrepreneurship performance (IEP) 0.62 0.44 0.03 1 69 0 Note: The table shows the numerical scores for the measures, which range from 0 to 100, following the Baldrige criteria. That is, we set the scores 95, 50, and 5 as the anchors for full membership, crossover, and full non-membership, respectively, for the high-performance set. 1 In a solution of fs-QCA, “»”denotes peripheral, “*”denotes core causal, and “*»” denotes conditional causal. A.A. Vargas-Zeledon and S.-Y. Lee Journal of Innovation & Knowledge 9 (2024) 100549 6 ENP. In particular, FA, PA, and KR influence ENP; however, KA and MO do not seem to foster entrepreneurship outcomes since they are conditional and peripheral causal conditions, respectively (see 4b in Table 5). The results show that EA is a core causal condition, indicating that the social and cultural norms and perceptions of entrepreneurship play a dominant role in fostering entrepreneurship performance in upper-middle-income countries (Table 5). Table 6 presents the results of the fuzzy-set solution for the lowincome economy group. The results are similar to those for the upper-middle-income economy group. FA, PA, KA, and KR are core causal conditions for the ENP outcome. MO is the absence of a solution in this configuration, implying that it may be better when this enabler is absent. These four variables are conditional causal conditions for the ENA and OTEA outcomes, indicating a possible significant but contingent impact. As in other economic contexts, the results confirm that EA significantly impacts entrepreneurship performance. Summary of the results and discussion The results of fs-QCA provide evidence of how institutional enablers foster inclusive entrepreneurship outcomes. Table 7 summarizes the results of the analysis. First, in the global context (the general model), the results partially support our first and second propositions. Some, but not all, institutional enablers significantly affect some of the outcomes. FA and PA are core causal conditions that foster entrepreneurship performance; and PA, KR, and KA are significantly associated with inclusive entrepreneurship performance. At the same time, MO is a peripheral causal condition. EA, the most influential factor in inclusive entrepreneurship, also plays a mediating role through which PA, KR, and KA enhance IEP. The results of fs-QCA across the four groups of economies illustrate that the effects of institutional enablers on entrepreneurship outcomes Table 3 Configurations strongly related to inclusive entrepreneurship outcomes in advanced countries. Antecedent condition ENA OTEA ENP IEP 2a 2b 2a 2b 2a 2b 2a 2b Market openness (MO) »»»»»»»» Financial accessibility (FA)  Policy affability (PA)  Knowledge readiness (KR)  Knowledge availability (KA)  Entrepreneurial atmosphere (EA)  Raw coverage 0.319 0.319 0.319 0.319 0.319 0.319 0.319 0.319 Unique coverage 0.295 0.295 0.295 0.295 0.295 0.295 0.295 0.295 Consistency 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 Overall solution coverage 0.991 Overall solution consistency 0.948 Note: 2a represents a solution of [»MO*»FA*»PA*»KR*»KA*»EA]; 2b represents a solution of [»MO*FA*PA*KR*»KA*EA]; = core causal condition; = conditional causal condition; »= peripheral causal condition. Table 4 Configurations strongly related to inclusive entrepreneurship outcomes in secondadvanced countries. Antecedent condition ENA OTEA ENP IEP 3a 3b 3c 3a 3b 3c 3d 3e Market openness (MO)   » Financial accessibility (FA) »»»» Policy affability (PA)  Knowledge readiness (KR) »» Knowledge availability (KA)    Entrepreneurial atmosphere (EA)     Raw coverage 0.005 0.326 0.781 Unique coverage 0.000 0.312 0.781 Consistency 1.000 1.000 1.000 Overall solution coverage 0.020 0.990 0.781 Overall solution consistency 1.000 1.000 1.000 Note: 3a represents a solution of [»FA*PA]; 3b represents a solution of [»FA*KR]; 3c represents a solution of [»KR*EA]; 3d represents a solution of [»MO*FA*PA*KR*»KA*EA]; 3e represents a solution of [MO*FA*PA*KR*KA*EA]; = core causal condition; = conditional causal condition; »= peripheral causal condition; = absence of a solution. Table 5 Configurations strongly related to inclusive entrepreneurship outcomes in upper-middle-income countries. Antecedent condition ENA OTEA ENP IEP 4a 4a 4b 4a Market openness (MO) »»»» Financial accessibility (FA)  Policy affability (PA)  Knowledge readiness (KR)  Knowledge availability (KA)  Entrepreneurial atmosphere (EA)  Raw coverage 0.200 0.188 0.471 0.179 Unique coverage 0.194 0.181 0.450 0.174 Consistency 1.000 0.903 0.919 0.893 Overall solution coverage 0.673 0.663 0.999 0.736 Overall solution consistency 0.894 0.848 0.956 0.971 Note: 4a represents a solution of [»MO*»FA*»PA*»KR*»KA*EA]; 4b represents a solution of [»MO*FA*PA*KR*»KA*EA]; = core causal condition; = conditional causal condition; »= peripheral causal condition. Table 6 Configurations strongly related to inclusive entrepreneurship outcomes in low-income countries. Antecedent condition ENA OTEA ENP IEP 5a 5a 5b 5a Market openness (MO) »»» Financial accessibility (FA)  Policy affability (PA)  Knowledge readiness (KR)  Knowledge availability (KA)  Entrepreneurial atmosphere (EA)  Raw coverage 0.391 0.391 0.374 0.199 Unique coverage 0.391 0.391 0.374 0.191 Consistency 1.000 1.000 1.000 0.866 Overall solution coverage 0.391 0.391 0.374 0.778 Overall solution consistency 1.000 1.000 1.000 0.962 Note: 5a represents a solution of [»MO*»FA*»PA*»KR*»KA*EA]; 5b represents a solution of [MO*FA*PA*KR*KA*EA]; = core causal condition; = conditional causal condition; »= peripheral causal condition; = absence of a condition. A.A. Vargas-Zeledon and S.-Y. Lee Journal of Innovation & Knowledge 9 (2024) 100549 7 vary, which supports our third proposition regarding the contingent model. Applying the fs-QCA method extends the earlier findings on the enablers of inclusive entrepreneurship, reached through other methodological approaches, typically based on regression and structural equation models. Complex mechanisms underpin inclusive entrepreneurship through the interactions between institutional enablers —market openness, financial accessibility, policy affability, knowledge readiness, knowledge availability—and entrepreneurial atmosphere. Table 8 presents the study’sfindings, which suggest multiple paths toward inclusive entrepreneurship, with a single best solution leading to the equifinality phenomenon. First, in the global context (the general model), a single best solution is identified for improving ENA, OTEA, and ENP, while two different configurations of institutional enablers lead to the same desired outcome regarding IEP. The configuration consisting of a core causal condition of EA with conditional causal conditions of FA, PA, KR, and KA exerts the same influence on inclusive entrepreneurial performance, as that of the core causal conditions of PA, KR, KA, and EA with a conditional causal condition of FA. Second, the equifinality phenomenon becomes apparent in the context of an advanced economy. The two configurations both result in the same levels of ENA, OTEA, ENP, and IEP. Third, in the Table 7 Summary of the results and proposition test. Independent and mediating variable Dependent variable (Entrepreneurship outcome) Proposition ENA OTEA ENP IEP Global context (General) Market openness (MO) »» »»P1: Partial support Financial accessibility (FA)   Policy affability (PA)   Knowledge readiness (KR)   Knowledge availability (KA)   Entrepreneurial atmosphere (EA)   -Mediating role No No No Yes P2: Partial support Advanced economy context Market openness (MO) »» »» Financial accessibility (FA)  P1: Partial support Policy affability (PA)   Knowledge readiness (KR)   Knowledge availability (KA)   Entrepreneurial atmosphere (EA)   -Mediating role Yes Yes Yes Yes P2: Support P3: Support Second-advanced economy context Market openness (MO)  » Financial accessibility (FA) »» P1: Partial support Policy affability (PA)   Knowledge readiness (KR)   Knowledge availability (KA)   Entrepreneurial atmosphere (EA)   -Mediating role No No No No P2: No support P3: Support Upper-middle-income economy context Market openness (MO) »» »» Financial accessibility (FA)  P1: Partial support Policy affability (PA)   Knowledge readiness (KR)   Knowledge availability (KA)   Entrepreneurial atmosphere (EA)   -Mediating role No No No No P2: No support P3: Support Low-income economy context Market openness (MO) »» » Financial accessibility (FA)  P1: Partial support Policy affability (PA)   Knowledge readiness (KR)   Knowledge availability (KA)   Entrepreneurial atmosphere (EA)   -Mediating role No No No No P2: No support P3: Support Note: = core causal condition; = conditional causal condition; »= peripheral causal condition; = absence of a condition. Table 8 Summary of the results and configurations. ENA OTEA ENP IEP Proposition Global context (General) Single best solution Single best solution Single best solution Equifinal solutions Partial support Advanced economy context Equifinal solutions Equifinal solutions Equifinal solutions Equifinal solutions Support Second-advanced economy context Equifinal solutions Equifinal solutions Single best solution Single best solution Partial support Upper-middle-income economy context Single best solution Single best solution Single best solution Single best solution No support Low-income economy context Single best solution Single best solution Single best solution Single best solution No support A.A. Vargas-Zeledon and S.-Y. Lee Journal of Innovation & Knowledge 9 (2024) 100549 8