Why do some migrant entrepreneurs succeed while others, equally embedded in the same structural conditions, do not? We argue that the answer lies partly in psychology: in how migrants identify with their home and host countries, and in whether, in the migrant’s opinion, the host society recognizes and accepts this self-identification. Drawing on role transition theory and survey data from 364 migrant entrepreneurs across four Western European countries, we find that home-country attachment positively predicts business performance, but the strength of this relationship depends on perceived social inclusion in the host society. When migrants feel socially included, strong home-country identification becomes a significant performance asset. When they feel excluded, this advantage disappears and may even turn into a liability. Perceived inclusion itself has no direct effect on performance; rather, it shapes whether and to what extent identity orientation translates into performance outcomes. These findings reveal that entrepreneurial success among migrants is shaped not only by structural conditions but also by how migrants identify themselves and how they perceive that identity being received. Migrant entrepreneurs who feel at home in their adopted country get more out of their cultural roots, while those who feel excluded get less. Using survey data from 364 migrant business owners across Spain, France, Italy, and the UK, we find that strong attachment to one’s country of origin is linked to better business performance, especially when entrepreneurs also feel socially accepted in the host society. For migrants who experience exclusion, the same home-country identification offers little benefit and can even become a drag on performance. These findings suggest that integration policy has economic as well as social benefits: inclusive host environments unlock the entrepreneurial potential embedded in migrants’ cultural identities, while exclusionary ones suppress it. Policymakers and support organizations seeking to maximize the economic contribution of migrant entrepreneurship should therefore invest as seriously in perceived social inclusion as in business development programs.
Why do some regions achieve higher levels of economic development while others do not? This paper introduces the Agglomeration-Clustering-Knowledge Spillovers (AC-KS) model, a conceptual framework for better understanding the nature of such differences. We argue that the missing piece of this puzzle is the process by which localized anchors ignite dynamic triangular forces between agglomeration, clustering, and knowledge spillovers, setting in motion a life cycle of first- and second-generation knowledge spillover effects. In this framework, we conceptualize that the spread and positive effects related to knowledge spillovers are governed by the strength-length-completeness triad of the triangularity relationship among agglomeration, clustering, and knowledge spillovers. These interactions then result in conical shapes whose base area and height, respectively, capture decaying effects of geographic reach and local intensity of knowledge-spillover entrepreneurship. The model’s originality lies in its geometric characterization of knowledge spillovers and in integrating fragmented literatures on the relationship among agglomeration, clusters, and knowledge spillovers. Its value is both theoretical and practical: the framework predicts when benefits concentrate or diffuse, offering diagnostic guidance for balancing reach (base) and intensity (height) across the knowledge spillover lifecycle stages of spark, expansion, and decline. Why do some regions achieve higher levels of economic development while others do not? This paper introduces the Agglomeration–Clustering–Knowledge Spillovers (AC-KS) model to explain how an initial spark—such as new research, an innovation, or an unexpected discovery—can set off a chain reaction that shapes a region’s long-term growth. The model shows how this initial knowledge first spreads directly through nearby firms and workers, and how that first wave then triggers a second, broader wave of knowledge spillovers that sustains growth well beyond the initial spark. We measure these spillovers by their strength, length, and completeness—how powerful the effect is, how far it travels, and how widely it is shared—and show that these three factors combine into different cone-like shapes, some narrow and concentrated, others broad and far-reaching. Building on this, we develop a framework that predicts new business creation, skilled employment, wage growth, and differences across industries. By combining ideas from entrepreneurship, clusters, and regional development, the AC-KS model gives researchers and policymakers a practical way to understand when knowledge stays concentrated versus spreads throughout a region, helping strengthen innovation and economic development.
Why do people quit the startup process before a business is formed? We treat withdrawal from new venture creation as a test of Evans and Jovanovic’s (1989) model of liquidity constraints at the pre-entry margin. In the model, constraints bind when desired capital deployment exceeds what personal finances can support. We test three predictions with Entrepreneurship in the Population (EPOP) Survey data from 2023 to 2025, comparing 3980 responses from continuing nascent entrepreneurs with 6903 responses from people who considered or pursued a business and then stopped. Experienced founders report deploying more than twice the startup capital of novices. The association between pre-existing financial constraints and stopping is stronger for experienced founders. The experience gap in stopping odds is large at one financial constraint, marginal at two, and no longer detectable at three. A further implication, that funding-rationed seekers stop at higher rates, is directionally positive but not robust across years. The results are consistent with liquidity constraints binding at the pre-entry margin and help reconcile weak wealth-entry relationships with evidence that constraints matter. Most Americans who consider or work toward starting a business stop before the business exists. Using 3 years of a national survey, we ask who stops and why. People who had previously started businesses put more than twice as much money into their attempts as first-timers. Because they put more money in, the same financial weaknesses, thin savings, poor credit, or no banking relationship, weigh on them more heavily. Experienced founders otherwise have much lower odds of stopping than first-timers, but that gap narrows as financial problems stack up, and among people facing all three problems we can no longer detect it. Founders with these problems are especially likely to name money as the main reason they stopped. Aspiring founders should judge financial readiness against the size of the business they want to build. For policymakers, financial capacity matters most for experienced founders, who put in the most money.
This paper examines how regional economic complexity is associated with entrepreneurial outcomes in German labor market regions. Drawing on entrepreneurial ecosystem research, we conceptualize economic complexity as one structural dimension of the regional capability base and distinguish between industrial, technological, and occupational complexity. We relate these dimensions to the regional share of high-growth firms, gazelles, venture-capital-backed firms, and venture capital volume per capita, while also considering broader regional performance indicators. Using panel models with region and year fixed effects, we find that the relationship between complexity and entrepreneurial outcomes is selective and heterogeneous across dimensions and outcomes. Industrial and technological complexity are more consistently associated with high-growth firms and broader regional growth indicators, whereas occupational complexity appears more relevant for gazelles. Venture-capital-related outcomes also display positive associations with regional complexity, with industrial complexity showing the most robust relationship. These findings contribute to entrepreneurial ecosystem research by showing that regional capability structures are related to growth-oriented and venture-oriented entrepreneurship in distinct ways across different dimensions of complexity. More broadly, the paper demonstrates how economic complexity can be incorporated into the analysis of entrepreneurial ecosystems without treating it as a comprehensive measure of ecosystem quality. Regions with more sophisticated economies host more fast-growing firms — but the more genuinely entrepreneurial the outcome, the weaker the link. Using data on German labor market regions, we measure how sophisticated each region’s industries, technologies, and occupations are, and relate this to the share of high-growth firms, the share of young fast-growing “gazelles,” and venture capital activity. Industrial and technological sophistication go together with high-growth firms and stronger regional growth; the regional skill mix matters more for gazelles; and venture capital follows industrial sophistication above all. Economic complexity therefore captures one structural layer of an entrepreneurial ecosystem, not its overall quality. The principal implication is for policy: strategies that build industrial, technological, and skill capabilities should not assume all of them support the same kind of entrepreneurship, and support for young ventures and venture capital must target ecosystem conditions that complexity does not measure.
