Volume 63, Issue 2-4 - Special issue: Entrepreneurial ecosystems

The editorial for the special issue on entrepreneurial ecosystems summarizes the ongoing debate on the entrepreneurial ecosystem concept and portrays the backgrounds of founding figures of the concept. It traces the unique contribution of this issue with regard to recently published research. The contributions deal with the measurement of and the role of specific actors and institutions in entrepreneurial ecosystems.

Contemporary works on entrepreneurial ecosystems (EEs) suffer from a lack of theorization. We address this problem by conceptualizing EEs as institutional fields, which is an analytical construct that is already well-elaborated on in neo-institutional theory. This theory provides a processual lens that is sensitive to the role of both institutions and agency in field structuration. Additionally, understanding EEs as fields can help to capture dynamics within EEs as well as their relationships with other fields. Following this approach, entrepreneurial issue fields mainly focus on debates around entrepreneurship and new venture creation, whereas entrepreneurial exchange fields focus on products and services produced by and offering support for a set of mainly industry-specific new ventures. In addition, we discuss mechanisms for transformations between both types of fields.

Relational theory has been a key advancement in understanding how entrepreneurial ecosystems work. However, the theory has not yet been operationalised through measurement methodologies. This study proposes an indicator-based framework and composite index methodology which builds on relational ecosystem theory. Starting from the premise that common aggregation methods like the arithmetic mean fail to convey the interdependence of ecosystem components (such as complementarity vs. substitution), this study explores the potential of geometric mean as an alternative approach. Our analysis shows that geometric mean methods render more plausible results than simple arithmetic mean; they operationalise complementarity between components more directly by introducing heftier penalties for imbalances in the ecosystem. Additionally, our methodology identifies the less-explored city-level as the most meaningful unit of analysis of entrepreneurial ecosystems. To test the index, we use a unique set of quantitative data for eleven middle-income cities, namely Accra, Amman, Bangkok, Beirut, Bengaluru, Cairo, Jakarta, Manila, Nairobi, Rabat, and Tunis. As most previously conducted measurements have targeted either mature or country ecosystems, our goal is not limited to methodological advancements in measuring entrepreneurial ecosystems, but it also relates to expanding the current status of research to less explored world regions.

The term ‘entrepreneurial eco-system’ (EES) currently belongs to the most popular ones in economic geography – and in the practice of start-up support policies in many countries, too. Due to its exclusively positive connotations the usage of this term creates unrealistic hopes among entrepreneurship support practitioners. Scholars may be reminded to previous supposed panaceas of regional economic policies like clusters, ‘creative class’ members or high-tech industries. As for these predecessors as well, the concept is “fuzzy” (Markusen 1999), the available empirics are “scanty” (ibid.) and its perception among policymakers is oversimplified, exclusively positive and partially naïve. To a degree, this is a consequence of an extremely unclear definition of what is meant by an EES. The undertheorization of the EES discourse, as observed by some scholars, is not due to a lack of conceptual approaches per se, but due to a lack of convincing, theoretically strong approaches. In fact, the majority of the EES publications is conceptual or even theoretical, usually without any serious empirical underpinning. From our perspective the latter has one important consequence: EES theory is weak because there is a lack of representative, comprehensive and sophisticated empirical studies, indicators and methods to measure EES. This paper provides a unique attempt to measure EES at the sub-national level of regions, that is, from our perspective, the most appropriate spatial level to identify and measure (and theorize) EES as the regional entrepreneurship literature provides striking evidence in favor of entrepreneurship as being primarily a regional (or local) event. Our paper contributes to the current EES debate by arguing that a robust empirical measurement of various EES at the sub-national level may help to improve the quality of EES theory. We propose to start with Erik Stam’s interpretation of an EES based upon ten “conditions” for whom we develop specific variables for application in concrete data collection exercises in different regions. We develop an overall EES index as well as subnational indices for each of the ten conditions. We also propose a method to care for the various weighting problems to be solved. Our attempt has been successfully pretested in Germany and Spain and has meanwhile entered a more ambitious pilot phase in 2018. One of this paper’s aims is to get feedback from scholars studying EES regarding our proposed method.

In spatial terms, entrepreneurial ecosystems are mostly conceptualized as confined to a specific territory. At the same time, the growing relevance of entrepreneurship in digital fields is underlined. This paper argues that this is contradictory since territorial thinking underestimates the disruptive qualities of new entrepreneurial practices in the digital economy. Using process-based, qualitative case studies on seed accelerators from four regions: Amsterdam, Berlin, Detroit and Hamburg, this study seeks to explore knowledge brokering in entrepreneurship ecosystems and analyzes the corresponding spatial dynamics. Our findings imply that startups in digital fields share knowledge about business models and technologies in a way that is unattainable in classical knowledge clusters. Moreover, we show that most of the observed entrepreneurial practices in seed accelerators crucially rely on extra-regional resources and thus remain only incompletely embedded into the respective regions. Against the background of these results, we suggest that entrepreneurial ecosystems should not be primarily viewed as territorial phenomena. Instead, we suggest that the territorial view on entrepreneurship ecosystems should be complemented with a topological view that foregrounds entrepreneurship as a trans-locally shared practice that is tangent to different regions in different ways.

Similar to natural ecosystems, entrepreneurs and other entrepreneurial actors are locally interdependent and affect the performance of each other. Mostly economically larger and more successful regions have been studied by using the framework of entrepreneurial ecosystems (EEs). The current study aims at further developing the theoretical understanding of EEs and applying the proposed EE model in the context of Estonia. In the study, a conceptual model of an EE is proposed, the uniqueness of which lies in merging three aspects into a single framework: the nine components of an EE, its value-added, and its phase of development. The model was applied for analysing by means of a qualitative methodology four sector-based subEEs in Estonia. The study showed that even in a small country like Estonia the components of the EE were partly similar, but also partly unique for the subEEs. This was not due to the location, but because of sectoral differences. The difference of the development phase seemed to be related to the knowledge base of the sector. The policy relevance of the model is that it allows looking at the elements of an EE as well as its economic value-added and development prospects. The EE approach allows addressing jointly the difficulties and challenges in the development of EEs, including the issues of digitalisation, skilled labour, and production costs, which would allow the subEEs to develop into mature and resilient networks. Not all the components of an EE have to be equally strong, but their interconnectedness determines the strength of an EE. Policy solutions need to be tailored to the needs of specific subEEs based on the knowledge base and inner dynamics of the sectors.