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Small Business Economics

Erschienen in:

26.03.2020

Entrepreneurial fintech clusters

verfasst von: Marco Gazel, Armin Schwienbacher

Erschienen in: Small Business Economics | Ausgabe 2/2021

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Abstract

We study the formation and dynamics of entrepreneurial clusters in the emerging fintech industry. Using detailed data on the almost 1000 fintech startups in France to date, we find that most fintechs are geographically clustered and that the location of new fintech startups is affected, among other things, by the size of clusters and the presence of incubators. Larger clusters attract more new fintech startups, and incubators are shown to be an effective mechanism to attract new fintech startups. We further examine entrepreneurial exits of fintechs and find that being located in a larger cluster reduces the risk of failure but increases the likelihood of being acquired. Increased competition within a given segment of fintech increases failure rates. Moreover, the risk of failure is significantly lower for fintech startups that have been developed in an incubator.

Vorheriger Artikel The entrepreneurial finance markets of the future: a comparison of crowdfunding and initial coin offerings

Nächster Artikel Crowdinvesting in entrepreneurial projects: disentangling patterns of investor behavior

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For instance, the UK alone counted 390 incubators and accelerators in 2017 (Bone et al. 2017). For France, we identified for our study 298 incubators and accelerators. However, it is not always possible to unambiguously disentangle incubators from accelerators since most programs combine characteristics of both.

Industry statistics for France indicate a sharp decrease in total employment in the banking and insurance sectors in the last several years. While the decrease is apparent well before the financial crisis, the trend is particularly strong since 2010, with a decrease in total employment of 22% during the period of 2010–2016. (Source: Institut Sapiens, https://www.institutsapiens.fr/wp-content/uploads/2018/08/Note-impact-digital-sur-lemploi.pdf; last seen on September 11, 2018)

Wennberg and Lindqvist (2010) wrote that “new entrepreneurial firms are attracted to clusters by the pool of skilled and specially trained personnel, access to risk capital, favorable demand conditions, reduced transaction costs, and motivational factors, such as prestige and priorities”. Many of these factors will be included in our analysis as socioeconomic variables driving demand by and supply to entrepreneurial firms.

Entrepreneurs may also exit the firm without seeing it leave the market. This happens when the entrepreneur sells his/her equity stakes to someone else who then runs the firm. We do not consider this type of “entrepreneurial exit” here since it does not alter the firm’s participation in the cluster.

The notion of externalities has links to the one on network effects that are used to explain agglomerations and benefits that vary with the participation of more individuals and firms within the network. These benefits may increase or decrease with network size, similar to platform-based markets (Belleflamme and Peitz 2016).

Incubators are programs targeted to very early-stage startups, while accelerators focus on scaling up these startups. In practice, most programs combine features of both since there is no clear boundary between the two types, and most programs are too small to specialize in a single type of startup (although there are some exceptions, such as the accelerator Y Combinator in the USA). In our study, we therefore use the term “incubator” for both.

Data regarding the presence of incubators is manually collected by the authors. We do not restrict our list of incubators to those explicitly targeting fintechs. However, we exclude from our sample specialized incubators for sectors that are not oriented towards high growth, innovative startups, such as agriculture, sports, food, press, media, arts and culture. However, all the results presented in this paper are sustained when considering all incubators.

In unreported analyses, we find very similar patterns over time using a traditional concentration measure, such as the one described in Marcon and Puech (2009). Since fintech startups are a tiny fraction of all the startups in an economy, these concentration measures are not easy to interpret. Additionally, these measures do not give an intuitive picture of cluster sizes. This issue explains why we use the number of fintechs in our multivariate analysis below.

IRR values in negative binomial regressions are more useful than raw coefficients in interpreting economic significance. Values are compared to 1. Thus, a coefficient larger (smaller) than 1 means a positive (negative) effect of the considered variable. For instance, an IRR = 1.1 means a unit increase in the variable increases cluster size by a factor of 1.1.

Note that we do not use the number of incubators as a control variable but instead use a categorization of no incubators and low and high numbers of incubators. This approach is due to the severe multicollinearity between the number of incubators and the variable Fintech stock. The three level categorization further enables us to capture non-linear effects, which are present in our data.

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Titel: Entrepreneurial fintech clusters
verfasst von: Marco Gazel
Armin Schwienbacher
Publikationsdatum: 26.03.2020
Verlag: Springer US
Erschienen in: Small Business Economics / Ausgabe 2/2021
Print ISSN: 0921-898X
Elektronische ISSN: 1573-0913
DOI: https://doi.org/10.1007/s11187-020-00331-1

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