This paper investigates whether local institutional quality is associated with firm-level innovation from an economic geography perspective. Focusing on Italian manufacturing firms, we examine whether cross-province differences in institutional quality are related to firms’ patenting activity and whether this relationship varies by firm size. Drawing on a longitudinal dataset of more than 125,000 manufacturing firms observed from 2011 to 2019, we combine firm-level patent data with a province-level measure of institutional quality. Our results show that higher local institutional quality is positively associated with firms’ patenting activity. Moreover, the relationship varies across firms and institutional dimensions, as improvements in control of corruption, government effectiveness, regulatory quality, and voice and accountability are associated with larger increases in patenting among smaller firms. By contrast, we find no evidence that the association between the rule-of-law dimension and patenting varies by firm size. Why do some firms innovate more than others? This study shows that local institutions matter. Using data on over 125,000 Italian manufacturing firms between 2011 and 2019, we examine whether firms located in provinces with better institutions generate more patent publications. The answer is yes: firms in provinces with higher local institutional quality tend to publish more patents. Importantly, this association is stronger for smaller firms, which often have fewer internal resources and capabilities and may depend more on their external environment. The results suggest that improvements in local governance—such as stronger control of corruption, more effective public administration, better regulation, and greater civic participation—can help smaller firms innovate. By contrast, we find no evidence that the association with the Rule of Law dimension with patenting varies by firm size. Overall, a key implication for policymakers is that strengthening local institutions can foster firm innovation and narrow territorial innovation gaps.
A substantial literature explores workers’ transitions into entrepreneurial business ownership, while freelance, on-demand self-employment, a distinct and increasingly prevalent mode of labour market participation, remains comparatively understudied. Using an original large survey conducted in 16 countries, we investigate the determinants of workers’ intentions to leave their main salaried job to engage in freelance, on-demand self-employment. We find that socio-demographic characteristics, job conditions, and behavioural traits are systematically associated with these intentions, though several patterns diverge from those documented in the entrepreneurship literature. A detailed heterogeneity analysis substantiates variation across occupations, task types, and individual characteristics. Workers in more vulnerable positions exhibit higher intentions to transition into freelance, on-demand self-employment, a form of work often associated with lower protection and higher income risk. Are the right people going into freelancing? Using survey data from 16 countries, we examine socioeconomic, demographic, psychological and labour market factors driving interest in freelancing (on-demand work). This unique international dataset enables us to disentangle shared and differing determinants of the wider self-employment form from the literature, calling for greater distinction between forms of self-employment in academia, practice, and labour law. We also identify unprotected vulnerable cohorts with higher interests in freelancing, underlining the need for targeted policy interventions in a world of growing freelance presence.
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.
