This chapter introduces the conceptual framework and data underpinning the entrepreneurial ecosystem diagnostics. The diagnostics include measures of ten entrepreneurial ecosystem inputs, each summed up in a composite index derived from approximately 40 indicators. Ecosystem output measures capture levels of entrepreneurial activity. Ecosystem variation measures reflect social and regional concentration in entrepreneurship outcomes. The chapter also discusses the time periods and aggregation methods to develop the data.
Entrepreneurial Ecosystem Diagnostics
Abstract
The entrepreneurial ecosystem diagnostics have been built following the approach of (Stam and Spiegel, 2018[1]; Stam, 2015[2]), which has benefitted from inputs from OECD and has been used in previous OECD work, including the OECD’s local entrepreneurial ecosystem analyses across various countries, and notably the case of Cambridgeshire and Peterborough, UK (OECD, 2021[3]).
The underlying model is presented in Figure 2.1. It is characterised by four important features. First, it separates inputs (entrepreneurial ecosystem elements) from outputs (productive entrepreneurship). Second, among the entrepreneurial inputs, it distinguishes between institutional arrangements and resource endowments. Third, although analytically independent, inputs are linked to other inputs as well as to outputs. Inputs interact and influence one another, which means that a gap in one element can act as a bottleneck for the overall capacity of the ecosystem to generate productive entrepreneurship. Fourth, inputs and outputs recursively feed back into each other. Thus, an improvement in productive entrepreneurship outcomes can improve the quality of entrepreneurial ecosystem elements, for instance through re-investments of income from successful ventures into the ecosystem. However, modelling these feedback loops is complex, and from an analytical perspective it is important to keep the measurement of inputs and outputs separate.
Conceptual visualisation of the elements and interactions driving entrepreneurship in an entrepreneurial ecosystem
Source: Adapted from (Stam and van de Ven, 2021[4])
Ten entrepreneurial ecosystem elements (ecosystem inputs) are selected and defined through an assessment of the existing research evidence, as reviewed for example by (Wurth, Stam and Spigel, 2023[5]) and (OECD, 2022[6])).
Based on this literature, the ten entrepreneurial ecosystem elements are:
1. Institutions. This refers to formal institutions, including business regulations. These are a fundamental influence on economic growth and development. They affect the allocation of entrepreneurial talent into productive and unproductive activities, reduce uncertainty for long-term investments and determine incentives and conditions to channel knowledge, capital and labour towards productive entrepreneurship (Djankov, 2009[7]; Granovetter, 1992[8]).
2. Culture. Entrepreneurial culture is an informal institution that reflects how entrepreneurship is perceived in society. A cultural context that values entrepreneurs influences the aspirations of people and their willingness to try to become an entrepreneur (Wyrwich, Stuetzer and Sternberg, 2016[9]). Another key element of culture is trust. Trust is a critical component of "social capital” and matters for measurable economic performance (Knack and Keefer, 1997[10]). Societies where people trust others tend to have greater economic interactions and investments, hence favouring productive entrepreneurship (Zak and Knack, 2001[11]).
3. Networks. Information and labour flows allow firms to access human resources, financial resources, and knowledge. For start-ups, access to networks is an important way to build social capital (Malecki, 2018[12]).
4. Infrastructure. Digital and physical (transport) connectivity is essential to enable entrepreneurs to access markets, exchange information, trade and interact with other people and organisations (Audretsch, Heger and Veith, 2015[13]).
5. Markets. Access to competitive markets and strong consumer and business demand for innovative products and services is a key condition for entrepreneurial success (Sato, Tabuchi and Yamamoto, 2012[14]).
6. Finance. Capital constraints hinder investments in the creation and growth of start-ups and scale-ups (Kerr and Nanda, 2009[15]). Access to credit and venture capital are particularly important for these firms.
7. Knowledge. This refers to the knowledge base that entrepreneurs can exploit through start-ups and scale-ups. In particular, technological know-how and scientific discoveries are important sources of new business opportunities, and can be developed in universities and corporations (Kim, Kim and Yang, 2012[16]). This technological knowledge is a key output of research with potential commercialisation possibilities (Acs et al., 2009[17]). A deep knowledge base also increases the possibility of using such knowledge in new ways.
8. Talent. Human capital and talent provide knowledge, know-how and capabilities for start-up creation and development (Acs and Armington, 2004[18]). This includes talented and mobile entrepreneurs. It also includes skilled workers needed to support the development of start-ups and scale-ups such as in digital skills, technology development or marketing.
9. Leadership. This involves the presence of actors that can develop a leadership for the ecosystem in terms of creating a shared vision among ecosystem actors on how different public, private and non-profit players can develop the ecosystem (Feldman and Zoller, 2012[19]). Ideally this should include the role of public-private partnerships and collective action organisations in stimulating entrepreneurial ecosystem development. Leadership of an ecosystem can also be spearheaded by highly visible and influential serial entrepreneurs.
10. Intermediate Services. The presence of entrepreneurship-targeted business services – such as legal support, accountancy, and consultancy and advice – lower entry barriers for new projects and innovative ideas (Howells, 2006[20]).
To operationalise these concepts into quantitative measures, a summary score for each element is produced through a composite index. The indicators within each element were selected based on their fit with the underlying literature and data availability. The complete list and definitions of the indicators used to measure each element is provided in Table 2.1. More details on the indicator definitions and the methods used to select, standardise and aggregate the variables are given in Annex A.
As shown in Figure 2.1, the entrepreneurial ecosystems inputs are seen to drive productive entrepreneurship outputs, which in turn feed back into the ecosystem. Our output focus is on productive entrepreneurship, i.e. entrepreneurship with job creation beyond the proprietor, innovation, survival, and growth potential (OECD, 2020[21]). Although non-employer firms (enterprises with no employees except working proprietors or partners) make up more than half of all enterprises in OECD countries, they often carry little innovation, have low productivity and bring only the founder into employment (OECD, 2017[22]). However, we adopt a broad view of productive entrepreneurship, spanning from high-growth scale-ups (such as gazelles and unicorns) to small employer start-ups that are less innovative yet have the potential to hire employees and increase productivity. Moreover, the definition, by design, captures all former non-employer firms as soon as they hire their first employee. The set of metrics used to capture productive entrepreneurship is detailed in Part A of Table 2.2.
Our diagnostic tool also tracks the extent to which countries’ entrepreneurship outcomes are homogenous or uneven across regions and social groups, including women and men. Tracking ecosystem diversity helps policy makers to be aware of potential entrepreneurship policy issues that are not picked up in national averages. The information on homogeneity and heterogeneity of entrepreneurship outcomes within countries is also useful for judging how far national measures need to be complemented with additional regional and social group data. The set of metrics used to capture entrepreneurial ecosystem variation is detailed in Part B of Table 2.2.
The data presented in this report are for three data periods: the most recent data period presented uses moving averages of data within the years 2020-2023, the intermediate period uses moving averages for the years 2018-2022, and earliest data period presented uses moving averages of data within the years 2016-2020. The data used are the latest available up to December 2024. More detail is offered in the Annex, including rationale for selecting indicators, detailed descriptions of indicators, methods of computing indicator scores, and method of aggregating values to give element level summary scores. The full methodology is presented in a companion OECD working paper (Crotti et al., 2025 (forthcoming)[23]).This provides full statistical details, methodological rationales and sensitivity analyses.
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