**1. Introduction**

An entrepreneurial ecosystem is a dynamically balanced system consisting of interdependent subjects and an entrepreneurial environment (Lu et al. 2021). Its input layer is based on attributes—conditions that allow or restrict entrepreneurship (Stam 2018). Productive entrepreneurship forms the output of an entrepreneurial ecosystem (Stam 2015). It refers to the innovation activity of entrepreneurs that contributes to the commercialisation of new ideas and knowledge and leads to economic growth in a certain territory (Aidis 2005; Acs and Szerb 2007).

The entrepreneurial ecosystem approach has gained prominence among scholars and practitioners in understanding an environment for productive entrepreneurship (Feld 2020; Szerb et al. 2019). However, the link between ecosystem attributes and productive entrepreneurship remains relatively unclear (Nicotra et al. 2018). Understanding this link is important to ensure the most favourable conditions for developing productive entrepreneurship, which can lead to economic growth in a particular territory.

This paper focuses on FinTech ecosystems (FEs); they are considered a type of entrepreneurial ecosystem that supports the development of FinTech companies (FinTechs), which are high-growth companies that disrupt or contribute to the provision of traditional financial services (Laidroo et al. 2021). FEs are characterised by the proliferation of FinTechs

**Citation:** Koroleva, Ekaterina. 2022. FinTech Entrepreneurial Ecosystems: Exploring the Interplay between Input and Output. *International Journal of Financial Studies* 10: 92. https://doi.org/10.3390/ijfs10040092

Academic Editors: Thanh Ngo, Aviral Kumar Tiwari and Tu Le

Received: 25 July 2022 Accepted: 27 September 2022 Published: 2 October 2022

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**Copyright:** © 2022 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

(Alaassar et al. 2021), which are often presented by start-ups and apply innovation in the financial sector. In the first half of 2019, 48 FinTech unicorns, start-ups valued at over USD 1 billion, accounted for 1% of the global financial industry (CBInsights 2019). This emphasises the high entrepreneurial activity in a FinTech ecosystem (FE) and allows one to perceive it as an entrepreneurial ecosystem.

Previous studies on FEs have either analysed the interplay between its actors (Hendrikse et al. 2020; Lee and Shin 2018; Yazici 2019) or focused on measuring their attributes (Ernst and Young 2014; Findexable 2021; Gagliardi 2018; Laidroo et al. 2021; Sinai Lab 2020). The disadvantage of most suggested measurement tools is that they focus on official statistics or the views of experts. The early stages of an FE's development and a lack of accumulated statistics (Diemers et al. 2015) have led to not including significant attributes or relying on a mix of information covering different territory levels. In addition, the number of studies is focused on the risks related to FinTechs (Vasenska et al. 2021; Morales et al. 2022) or the efficient use of digital technologies (Popova 2021; Lewandowska et al. 2021).

Nevertheless, to our knowledge, there is no measurement tool for FE attributes based on a survey that would allow us to aggregate the opinions of the FinTech community about the entrepreneurship environment in the financial sector. This study attempts to fill these gaps in the context of Russian regions.

Therefore, the goal of the study is measuring FE attributes and productive entrepreneurship, investigating the relationship between them and determining territories with more productive entrepreneurship.

The context of Russia is an interesting case for investigation for the following reasons. In 2021, Russia emerged as a TOP-20 country in the Global FinTech Index, rising 13 positions from the previous year (Findexable 2021). Russia has also been ranked in the TOP-3 countries for applying innovative solutions in the financial sector (Kuhn 2021). According to Ernst and Young (2019), the FinTech Adoption Index in Russia amounted to 82% in 2019, exceeding the global average rate. The above-mentioned achievements indicate that Russia has cultivated a favourable climate for FinTech development.

In this study, we developed a survey tool for measuring FE attributes: the FE index. This index extends previous conceptual and empirical work on entrepreneurial and FE ecosystems (Feld 2020; Isenberg 2011; Neck et al. 2004; Spigel 2017; Stam and van de Ven 2019; Szerb et al. 2019; Findexable 2021; Sinai Lab 2020; Laidroo et al. 2021). Two approaches—additive and multiplicative—were used to calculate the FE index.

There is no consensus in the ecosystem literature on the level of analysis—city, region, country, or other levels. This study is based on the regional level, like other empirical research on ecosystems (DeFries and Nagendra 2017; Leendertse et al. 2021; Stam 2018). The suggested tool for measuring FE attributes was tested for 10 Russian regions where most FinTechs are located.

The FE index recognises a similar environment in the analysed regions for financial sector entrepreneurship. These regions have high estimates of physical infrastructure, demand, and talent. New knowledge and networks appear to be this environment's weak sides in terms of financial sector entrepreneurship. Among these regions, Moscow has the most favourable environment for entrepreneurship in the financial sector. Such attributes as finance and leadership mostly determine Moscow's superiority over other regions. At the same time, the Chelyabinsk region has the lowest FE index value.

The correlation analysis showed a positive link between FE attributes and productive entrepreneurship, as measured by the number of FinTechs. Data envelopment analysis (DEA) indicated territories with productive entrepreneurship. With the additive FE index, Moscow was recognised as a region that has effectively created an environment for productive entrepreneurship. Regarding the multiplicative FE index, the Chelyabinsk region achieved the best results. The contrary results can be explained by the features of the FE index calculation and highlight the importance of choosing an adequate measure of FE attributes. The results of the DEA analysis also indicate that the physical infrastructure and demand in Russian regions are underutilised by entrepreneurs. In addition, the results highlight finance, intermediate services, and formal institutions as attributes maximally used by entrepreneurs and require additional attention from policymakers for entrepreneurship development. Improving the understanding of FE attributes and their links to productive entrepreneurship would benefit both policymakers and entrepreneurs.

This paper contributes to the literature on entrepreneurial ecosystems (Stam 2018; Stam and van de Ven 2019; Mateos and Amorós 2019; Villegas-Mateos 2020; Leendertse et al. 2021) by supporting a positive link between an ecosystem's attributes and productive entrepreneurship. Based on this link, this current research provides a tool for identifying territories with productive entrepreneurship.

This paper contributes to the FinTech literature in several respects. It extends the literature on measuring FE attributes (Ernst and Young 2014; Gagliardi 2018; Findexable 2021; Sinai Lab 2020; Alaassar et al. 2021; Laidroo et al. 2021) by developing a surveybased approach. It also contributes to the FinTech literature in Russia (Kleiner et al. 2020; Koroleva et al. 2021; Vaganova et al. 2020) by being the first to measure FE attributes.

This article is structured as follows. The theoretical and empirical backgrounds are summarised in Section 2. The methodology and data are presented in Section 3. Section 4 concentrates on the results of this study. Finally, Section 5 provides a discussion and conclusion.

#### **2. Literature Review**

#### *2.1. Entrepreneurial and FinTech Ecosystems*

Several studies (Spigel 2017; Stam 2015) indicate that an entrepreneurial ecosystem approach can be used for synthesising academic research on entrepreneurship and its regional developments. This approach supposes the analysis of two main layers: the attributes of an ecosystem (input) and productive entrepreneurship (output). The connection between attributes and productive entrepreneurship is difficult to explain due to their interdependence. Attributes influence productive entrepreneurship, but over time, output also feedbacks into input (Stam 2015).

The main challenge in identifying attributes arises from entrepreneurial ecosystems' diverse origins and complexity (Spigel 2017). Although there is no universal approach to classifying the attributes of entrepreneurial ecosystems, different scholars and practitioners have attempted to create classifications and tools for measuring them. Table 1 summarises the classifications of entrepreneurial ecosystem attributes found in the literature. The relevant articles were collected from the 2004–2020 Scopus database using the keywords 'attributes of entrepreneurial ecosystem' and 'elements of entrepreneurial ecosystem'.

**Table 1.** Overview of entrepreneurial ecosystem attributes.


Note: + means the research includes the attribute and - means that it does not include it.

The comparison of entrepreneurial ecosystem attributes was based on Stam's (2015) model because it provides the most comprehensive view of an entrepreneurial ecosystem, including institutional arrangements and resource endowment elements. This model consists of 10 attributes: formal institutions, entrepreneurship culture, networks, physical infrastructure, finance, leadership, talent, new knowledge, demand, and intermediate services.

Formal institutions reflect the regulation and role of the government in ecosystem formation. Entrepreneurship culture characterises the value of entrepreneurship. It consists of an entrepreneur's innovativeness, willingness to take risks, self-organisation, and motivation. Physical infrastructure includes transport and digital infrastructure, which support the development of entrepreneurship. Demand reflects the readiness of customers to buy products or use services. Networks reflect collaboration between actors and their readiness for equal dialogue. Finance reflects access to different financial resources. Leadership characterises actors taking a leadership role in an entrepreneurial ecosystem. Talent covers the labour market and higher education. This represents the availability of highly qualified training of entrepreneurs or specialists in the market who support entrepreneurs in the process of starting a business. R&D investments are included in the attributes of the entrepreneurial ecosystem as new knowledge. Intermediate services characterise support by informal institutions, such as incubators or accelerators. In this paper, we also relied on Liguori et al. (2018) while developing a survey covering FE attributes.

Most attempts to measure FE attributes have been made by analytical companies. Sinai Lab (2020) created the Global FinTech Hub Index as an expansion of applying another index—the China FinTech Hub Index. This index is based on three perspectives, enterprise, consumer, and government, and ensures the cross-comparability of data from different countries. The Global FinTech Index (Findexable 2021) consists of three metrics, the number of FinTechs, the number of unicorns, and the environment, and ignores quality information about FE attributes. The developers of this index explained the choice of metrics using their own and their partners' experiences. According to Ernst and Young (2014), it is adequate to highlight four main FE attributes—talent, capital, policy, and demand—and estimate them from the opinions of experts. The report by Gagliardi (2018), based on 15 interviews with renowned experts, followed FE attributes: demand drive, systemic linkages, and regulatory oversight.

Practitioners' indices determine an FE's key attributes. First, it is an activity of formal institutions. Developing FinTech-friendly regulations and special state programmes contributes to developing entrepreneurship in the financial sector. Then, demand reflects the popularity of FinTech services among customers. Finance, talent, and networks are used at least once in calculating corresponding indices. Nevertheless, the indices suffer from a lack of theoretical background and are based on developers' experience. This means that indices may ignore the significant attributes and complexity of a FinTech ecosystem. A lack of accumulated statistical resources leads to basing these indices on a mixture of information covering different territories (country versus region).

Academics have suggested alternative approaches to measuring FE attributes. Based on the ecosystem index by Stam and van de Ven (2019), Laidroo et al. (2021) developed the additive FE index at the country level. We highlight the importance of IT infrastructure and FinTech regulation and reveal these elements as separate attributes of an FE. The disadvantage of this index is the unequal weight of the attributes. To our knowledge, no further attempts have been made to measure FE attributes.

A healthy entrepreneurial ecosystem generates productive entrepreneurship as an output. The term productive entrepreneurship lacks a single agreed-upon definition. Productive entrepreneurship reflects any activity that contributes to the net output of an economy. For Aidis (2005), this refers to innovative actions that result in an economically productive business. Acs and Szerb (2007) emphasise that productive entrepreneurship enables the creation and commercialisation of valuable knowledge.

Considering these definitions, it is possible to determine the main characteristics of productive entrepreneurship. First, productive entrepreneurship contributes to economic growth, including job creation. Then, it generates innovation. Finally, it is a way of commercialising new ideas and knowledge. In the framework of this current research, productive entrepreneurship is understood as an innovation activity that contributes to the commercialisation of new ideas and knowledge and leads to economic growth in a certain territory. In Section 3.2 of this paper, a measure of productive entrepreneurship is suggested based on the proposed definition.

#### *2.2. Developing the Conceptual Framework*

In line with previous research, applying the ten attributes of an entrepreneurial ecosystem may require adjustments when considering an FE (see Table 2).


**Table 2.** Attributes of an FE.

The classification of FE attributes includes the attributes mentioned in previous research and ensures a comprehensive FE view.

Formal institutions identify the rules of organising a business and of government supporting FinTech entrepreneurship. The FinTech sector is connected to applying innovations, which are often restricted by compliance with certain regulations (Bromberg et al. 2017). Entrepreneurship culture covers the propensity for entrepreneurship, including its popularity and the attitudes of the society. It is also based on the history of successful FinTechs, among other aspects. It can provide benefits and resources for potential entrepreneurs regarding how to best organise a business in the FinTech sector. Physical infrastructure reflects the possibility of customers receiving FinTech services, which require the use of web resources. This would be impossible without the creation of certain physical infrastructure. Demand is critical to the health of any sector, especially the nascent FinTech sector (Ernst and Young 2014), and is identified by customers' readiness to use FinTech services.

Spigel (2017) insisted on the different emphases of actors and their roles in an ecosystem framework. However, it is necessary to ensure equal access to actors and terms for a network to develop entrepreneurship in the financial sector (Brush et al. 2019). Leadership guides collective action (Stam and van de Ven 2019) and identifies trends in the financial sector. This leadership is critical in building and maintaining a healthy ecosystem (Feldman 2014). The ease of creating a team to start a FinTech project or to find a suitable candidate for an employment vacancy also contributes to developing entrepreneurship in the financial sector. Talent emphasises the relevance of the availability of potential employees with suitable IT and business skills and adequate experience in the financial sector.

Within an FE, access to financing is a critical attribute that ensures the growth of individual companies and the entire industry. That is why it is relevant to develop bank credits and alternative financing (e.g., venture capital, business angels, etc.). To apply innovative solutions, it is necessary to invest in and develop them. Therefore, new technological knowledge is highlighted as one FE attribute. Intermediate services include support from informal institutions, such as incubators and accelerators. Organisations create accelerator

programmes and coworking spaces (Block et al. 2018). They also connect investors to promising FinTechs, which broadens their financing possibilities (Alaassar et al. 2021).

#### *2.3. Level of Analysis*

There is no consensus in the entrepreneurial ecosystem literature regarding the level of analysis of entrepreneurial ecosystems—city, region, country, or other levels. Relevant boundaries of an entrepreneurial ecosystem are difficult to identify due to their openness. Each attribute of an ecosystem can have its own boundaries (Leendertse et al. 2021). Government support is limited by the governmental level (i.e., municipal, regional, or national). The development of physical infrastructure is identified by localities. The training of qualified personnel for entrepreneurship depends on an educational institution's location. New knowledge can be identified by the location of the innovation centres.

Kuckertz (2019) distinguished between the administrative, spatial, and conceptual boundaries of an entrepreneurial ecosystem. DeFries and Nagendra (2017) insisted on the necessity of going beyond administrative boundaries to involve stakeholders in an entrepreneurial ecosystem. Leendertse et al. (2021) focused on the analysis of entrepreneurial ecosystems at the regional level (i.e., between the municipal and national levels). However, entrepreneurs' activities are not restricted by cities or regions and can go beyond a specific country. Entrepreneurs can also be actors in several entrepreneurial ecosystems or connectors of ecosystems on a global scale (Malecki 2011). Nevertheless, ecosystem management is place-based (Roundy et al. 2018), which is why, in the framework of this current research, the defining of entrepreneurial ecosystem boundaries is possible.

Experience in measuring FE attributes also shows different levels of analysis. Laidroo et al. (2021) concentrated on the country level. Ernst and Young (2014) and Sinai Lab (2020) focused on the city level. Findexable (2021) published the Global FinTech Index on two levels simultaneously: country and cities.

In this current study, the theoretical background is the entrepreneurial ecosystem approach. Based on the results of highly cited research on entrepreneurial ecosystems (DeFries and Nagendra 2017; Leendertse et al. 2021; Stam 2018), we focused on a regionallevel analysis of FEs.

#### **3. Data and Methodology**
