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Each territorial unit is characterized by a specific entrepreneurial ecosystem (EE) consisting of interdependent actors and contextual factors that support or limit entrepreneurial innovation. Access to and mobilization of entrepreneurial resources is facilitated by social networks within the entrepreneurial ecosystem. However, the degree and quality of these networks is determined by various characteristics of the particular ecosystem itself. Using fuzzy-set Qualitative Comparative Analysis (fsQCA), we explored the configurations of micro, meso and macro conditions of the entrepreneurial ecosystem of ICT firms in a Hungarian city (Pecs), which result in a high or very high-level networking performance. Our results show that certain ecosystems are capable of high-quality networking. In addition, we find that different ecosystem configurations are required for high informal, formal, or external networks.

This paper demonstrates how the Regional Entrepreneurship and Development Index (REDI) can be used to optimize local entrepreneurial discovery processes, in a manner which can support smart specialization strategies (S3). While S3 industry prioritization is based on the identification of local strengths, regional improvement can be achieved by improving the weakest features of the local entrepreneurial ecosystem. REDI based suggestions are place‐based and offer rationale for tailor‐made regional policy interventions. We found that without optimizing the entrepreneurial ecosystem, the industry specialization alone may not be successful because of the inability of the ecosystem to nurture high growth ventures. Este articulo demuestra que el Indice de Desarrollo e Iniciativa Empresarial Regional (IDIE) se puede utilizar para optimizar los procesos de descubrimiento de iniciativas empresariales locales, de manera que pueda servir de apoyo a las estrategias de especializacion inteligentes (S3, por sus siglas en ingles). Si bien la priorizacion de industrias de las S3 se basa en la identificacion de las fortalezas locales, la mejora regional se puede lograr mejorando las caracteristicas mas debiles del ecosistema local de iniciativas empresariales. Las sugerencias basadas en el IDIE estan ligadas a cada lugar y ofrecen una justificacion para realizar intervenciones formuladas a medida para las politicas regionales. Se descubrio que si no se optimiza el ecosistema de iniciativas empresariales, la especializacion de la industria por si sola puede no tener exito, debido a la incapacidad del ecosistema para fomentar empresas de alto crecimiento. 本稿では、スマート・スペシャリゼーション戦略(smart specialization strategies:S3)を支持する方法で、地域の起業家的発見のプロセスを最適化するために、Regional Entrepreneurship and Development Index (REDI:地域のアントレプレナーシップと発展の指数)をどのように利用することができるかを例示する。S3は地域の強みを特定することにより産業の優先順位付けを行っているものの、地域の改善は、地域の起業エコシステムの最たる弱点を改善して達成できるものである。REDIに基づく提案は、地域ベースのものであり、地域個別の地域政策の介入の根拠を提示するものである。エコシステムには急成長ベンチャーを育成する能力がないため、起業エコシステムの最適化なくしては、産業特化は成功しない可能性があると考えられる。

This paper presents a regional application of the Global Entrepreneurship and Development Index (GEDI) methodology of Acs et al. (2013) to examine the level of entrepreneurship across Hungary’s seven NUTS-2 level regions between 2006 and 2012. The Regional Entrepreneurship and Development Index (REDI) has been constructed for capturing the individual efforts, and their contextual features, of entrepreneurship across regions. The REDI method builds on a Systems of Entrepreneurship Theory and provides a way to profile Regional Systems of Entrepreneurship. Important aspects of the REDI method include the Penalty for Bottleneck analysis, which helps in identifying constraining factors in Regional Systems of Entrepreneurship, and Policy Portfolio Optimisation analysis, which helps policymakers consider trade-offs between alternative policy scenarios and associated allocations of policy resources. The paper describes the entrepreneurial disparities amongst Hungarian regions and provides public policy suggestions to improve the level of entrepreneurship and to optimise resource allocation over the 14 pillars of entrepreneurship in the seven Hungarian regions.

This paper aims to elaborate the role of Jacobs-type of agglomeration effects on countries’ competitiveness and entrepreneurial performance. Our research allows for a better understanding of the relationship that exists between a country’s urban system, characterized by spatial agglomeration (concentration) or deglomeration (deconcentration) processes, and its competitiveness and entrepreneurial performance.Urbanization economies refer to considerable cost savings generated through the locating together of people, firms and organizations across different industries. It has recently become an axiom that the better performance of global cities (as they are important nodes of innovation and creativity) is derived from agglomeration effects. This general assumption follows that the more concentrated an urban system of a country, the more competitive and better its entrepreneurial performance. Even though this notion has gained quick and ardent acceptance from practitioners, the related literature shows contradictory results; this has induced a heated debate in academic circles, because it has raised serious doubts about the “bigger is better” theory. We hope to contribute to this debate with our detailed analysis.To understand the impact of urban concentration, we selected 70 countries and calculated the so-called ROXY Index measuring the degree of agglomeration or deglomeration in their urban systems. To exemplify country-level competitiveness, we applied the Global Competitiveness Index (GCI) while the Global Entrepreneurship and Development Index (GEDI) was used to demonstrate country level entrepreneurial performance. Using these indexes correlation and cluster analysis were designed to obtain understanding of the relationship between them.Our analysis indicates that as urban concentration initially increases competitiveness, entrepreneurial performance also increases, but at a decreasing rate. Both of them eventually reaches a maximum, and then after a certain point decrease with further concentration. Therefore, the curve for this relationship is non-linear and folds back. This indicates that over- or under-concentration of the population within an urban system does not necessarily result in a better outcome. However, we should consider that a high concentration of population is only one important factor for competitiveness and entrepreneurial performance while other effects may exist.