Abstract
Purpose
The study aims to investigate the influence of FinTech (Financial Technology) determinants such as crowdfunding, mobile payment and blockchain as potential facilitators in an entrepreneurial ecosystem for undertaking decisions in Tunisia, as an example of emerging economy.
Design/methodology/approach
Quantitative research was carried out with data collection based on a questionnaire that has been sent via email to young Tunisian entrepreneurs (potential or actual). A following regression was calculated on 93 respondents.
Findings
Analysis of the data showed that most of the relationships under investigation were confirmed. Statistical tests highlighted that knowledge, availability and access about crowdfunding and blockchain had a positive and significant impact on entrepreneurial intention. Regarding mobile payment, there was a negative and insignificant effect on entrepreneurial intention.
Originality/value
From the evidence of the research, Fintech ecosystems may positively influence the decision to undertake, with relevant implications at institutional, industrial and individual level. More specifically, demonstrating a positive and significant relationship between some main dimensions of FinTech and entrepreneurial intention and emphasizing the contribution of related knowledge to intellectual capital accumulation through entrepreneurial education, this study seems to be unique in examining and verifying this potential effect.
Keywords
Citation
Festa, G., Elbahri, S., Cuomo, M.T., Ossorio, M. and Rossi, M. (2023), "FinTech ecosystem as influencer of young entrepreneurial intentions: empirical findings from Tunisia", Journal of Intellectual Capital, Vol. 24 No. 1, pp. 205-226. https://doi.org/10.1108/JIC-08-2021-0220
Publisher
:Emerald Publishing Limited
Copyright © 2022, Giuseppe Festa, Sihem Elbahri, Maria Teresa Cuomo, Mario Ossorio and Matteo Rossi
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcodea
1. Introduction
Nowadays, interest in financial technology (FinTech) has increased. The world that has witnessed the emergence of more than 12,000 large established companies globally. They invested US$19bn in 2015 (Lee and Shin, 2018), and this explains the adoption of FinTech in the world. This growth has also impacted emerging economies, stimulating entrepreneurs to use advanced technologies to attain a market competitive edge. A vast series of innovative solutions have emerged that have propelled increasing progress in entrepreneurship. In this respect, FinTech represents a powerful element of the global entrepreneurial ecosystem, both for developed and emerging economies (Berman et al., 2021).
In fact, FinTech is a combination of innovative technological platforms and new business models that facilitate everyday financial services. In this respect, it has enormously impacted the e-economy all over the world (Campanella et al., 2020). Common products for FinTech include e-wallet, cryptocurrency and peer-2-peer (P2P) lending. Also, InsurTech has become the leading financial alternative for consumers and businesses in the insurance sector. Although FinTech is still in its nascent stage in the Tunisian market, it is at the perimeter of the investigation in the current research as example of an emerging economy. The costs and benefits of FinTech for consumers and businesses remain vastly unexplored in this region. At the same time, there is a relevant ferment of start-ups in this industry who implement e-payments, e-trading, e-crowdfunding and so on (Festa et al., 2019); thus offering great opportunities to potential new entrepreneurs.
Incumbent financial service operators, as well as established technology companies, also play an important role in the FinTech ecosystem. Financial service firms spent over US$480bn on information technology in 2018 (IDC, 2018), and many have engaged in FinTech innovation. However, the digital economy offers many opportunities for small and large companies to innovate, and these opportunities extend to the financial sector where FinTech start-ups continue to enter the market with new, smarter and more user-friendly financial services and products than incumbents. They are applying new technologies, such as blockchain, smart contracts, artificial intelligence and other impactful technologies (Haddad and Hornuf, 2019; Di Vaio et al., 2020).
In this respect, Dapp (2014) pointed out that FinTech is generally not derived from finance. Instead, it shows more characteristics of its technological background. The trend toward FinTech appears to be continuing as the constant progress of mobile devices, cloud processing and big data collection through social networks and other web applications continues, and new opportunities for simplification, adaptability and individualization are evolving (Dapp, 2014). This provides evidence for the enabling role of knowledge management to feed new and innovative entrepreneurial ecosystems (Autio et al., 2018; Rossi et al., 2020, 2021b; Caputo et al., 2021; Gomes et al., 2021).
In this respect, intellectual capital, a complex mixture of intangible assets, is essential because it is widely recognized as one of the most relevant resources for companies to generate competitive advantages (Edvinsson and Sullivan, 1996; Paoloni et al., 2020). In the information society, knowledge derived from inside and outside the company (“ecosystem”) is strategic for business survival, growth and development (Ferraris et al., 2017; Santoro et al., 2018; Scuotto et al., 2020a), especially with respect to human capital (Inshakova et al., 2020).
In this direction, entrepreneurship education can play a major role in developing undertaking intentions, especially of young people (Anwar and Saleem, 2019). Supporting entrepreneurship by teaching skills increases the potential for future entrepreneurial activities, foraging human capital and then intellectual capital accumulation. This reinforces the need for entrepreneurship education for young potential undertakers (Murray and Palladino, 2020).
In this regard, this study examines the importance of knowledge availability and access to information about FinTech solutions (namely crowdfunding, mobile payment and blockchain) as potential determinants, at the level of the entrepreneurial ecosystem, together with opportune entrepreneurial education, for the carriers of innovative projects of young entrepreneurs in emerging economies, adopting the following structure. A review of the literature is presented hereafter to provide support for the research hypotheses. The sections that follow explain the methodology and report on data collection, analysis and discussion, with related implications. Finally, concluding remarks and the limitations of the study are debated.
2. Environmental background and theoretical perspective
2.1 Entrepreneurial education in the entrepreneurial ecosystems
In general, the act of undertaking physiologically includes several dimensions of analysis, implying that the related investigation could start from different perspectives. For example, from the point of view that highlights innovation, entrepreneurship is the invention of different products, processes (Abdulkader et al., 2020) or models (Schumpeter, 1934). From the point of view that highlights creativity, entrepreneurship is substantially a business invention (Gartner and Carter, 2003).
In the perspective of the entrepreneurial ecosystem as a set/network of factors and actors that may stimulate to undertake, particularly in a specific region (Cohen, 2006; Stam, 2015; Spigel, 2017), the study of entrepreneurial intentions requires an advanced research approach to go beyond descriptive research (Bird, 1988; Hussain et al., 2021). Potential entrepreneurs must be prepared to face any business obstacle or possible risk in general. Although they can learn from failure, extreme failure can demotivate entrepreneurs to move forward because of the financial and psychological costs and the negative perception of society (Liu et al., 2020).
From another perspective, the entrepreneurial intention could also depend on the difference in potential income that could be earned as an employee or freelance. Science, technology, engineering or math (STEM) graduates particularly are believed to be mostly well paid simply by being employees, a circumstance that may discourage them from being self-employed (Cai and Winters, 2017).
Ginanjar (2016) defines entrepreneurship education with specific regard to university courses about entrepreneurship. The supposed effect of the education to undertake on actual undertaking derives from the assumption that entrepreneurial skills can be taught and/or learned in such environments (Scuotto et al., 2020a, b).
In general, education about entrepreneurship contributes to the development of human capital and then the intellectual capital of a potential business. However, so far, few studies have considered the contribution of the entrepreneurial competence derived from entrepreneurial education to entrepreneurial intention, meaning that this relationship seems, so far, to be mainly supported from a theoretical more than an empirical point of view.
2.2 Human capital as the accumulation of entrepreneurial education in entrepreneurial ecosystems
The concept of the intangible assets that can flow into the accumulation of intellectual capital has different definitions with dual effects. From one side, they constitute evidence about the relevance of intellectual capital in the scientific literature (due to the increasing volume of studies in the field). From the other one, they manifest the absence of a common definition. Nonetheless, many researchers (Sullivan, 1999; Hormiga et al., 2011; Festa et al., 2020; Rossi et al., 2021a) assume that intellectual capital is substantially made up of three components, that is, human, structural and relational capital.
Adopting an entrepreneurial perspective, one of the most relevant factors that new entrepreneurs can activate for undertaking is their entrepreneurial knowledge, which should be physiologically transformed, after starting the business, into the human capital and then the intellectual capital, of the enterprise (Mariano and Walter, 2015; Matricano, 2016; Passaro et al., 2018). In this respect, individual and then corporate intellectual capital represents a dynamic engine of business knowledge creation. It operates as an intangible asset that evolves continuously, and thus it is required in order to capture the tacit knowledge accumulated and/or created to turn it into explicit knowledge. On the one hand, knowledge management (KM) becomes a theoretical and practical framework to guarantee the contribution of intellectual capital to achieve creation, innovation and improvement of business performance (Papa et al., 2021). On the other hand, intellectual capital can be used to further implement KM strategies by examining its benefit, from an entrepreneurial perspective, in successfully improving financial and operational performance and, when possible, activating the entrepreneurial education that the potential undertakers may have received directly via the academic system or indirectly via the entrepreneurial ecosystem (Bontis et al., 1999; Nonaka et al., 2000; Carayannis et al., 2014; Schiavone et al., 2014; Rossi et al., 2020).
2.3 FinTech opportunities in the entrepreneurial ecosystems
Innovative business platforms on which financial companies, exploiting and exploring incremental and disruptive innovations, develop new products, services, processes and models constitute the fundamental concepts that may represent the FinTech environment (Puschmann, 2017). For instance, the use of emerging technologies, such as decentralized distributed ledgers (“blockchains”) or P2P systems, to radically change the state of the art of the financial sector and accurately leverage new capabilities (Gozman et al., 2018) are examples in this respect.
In general, Leong and Sung (2018) defined FinTech as an innovative ecosystem that improves financial services by using technology in a business scenario and adopting disruptive concepts and models that change the entire business. Bofondi and Gobbi (2017) affirmed that FinTech offers all of the services that banks previously offered, but with a minimal margin.
With specific reference to FinTech as factor of the entrepreneurial ecosystem, Santoso (2016) stated that the use of information technology greatly influenced entrepreneurial intention. They found that Indonesian students who understand and use information technology show more entrepreneurial intentions than students who do not understand and access information technology. Also, this is true for those who have financial capital (in the form of money) and a strong entrepreneurial intention. The lack of capital is one of the main causes that prevents students from undertaking (Aragon-Sanchez et al., 2017).
2.4 A combined focus on young entrepreneurs
By mixing entrepreneurial education and subsequent potential intention, intellectual capital accumulation and FinTech opportunities, it is possible to determine a multifaceted profile of investigation, that is, young entrepreneurs in FinTech with entrepreneurial education. According to several regulations around the world, youth refers to a varying interval of age. Young people may be considered to be between the ages of 15 and 30, and young entrepreneurs can be defined as individuals under the age of 25 who wish to pursue entrepreneurial activities as a career (Hulsink and Koek, 2014). For the purposes of the current research, young entrepreneurs in FinTech are defined as young individuals between the ages of 18 and 25 that created their own business or planned to set up a business in this specific sector.
3. Hypotheses development
Based on the previous considerations, the following hypotheses have been formulated. They aim at investigating the impact of knowledge, availability and the accessibility of the FinTech ecosystem (in the form of crowdfunding, mobile payment and blockchain) as potential influencers of entrepreneurial intention, working in combination with entrepreneurial education (at an individual level) as a contextual intellectual capital factor (at the environmental level).
3.1 Crowdfunding and entrepreneurial intention
Achieving accumulation, via electronic platforms, of a quantity of capital in the form of large, medium or usually small contributions is the essential meaning of the concept of crowdfunding (Festa et al., 2019), even in terms of additional integration with respect to common entrepreneurial finance (Short et al., 2017). A recurring schematization of crowdfunding configures it as an Internet call for collecting the financial means to support specific projects (Bellefamme et al., 2010; Mollick, 2014).
For some authors, crowdfunding has emerged as an important force in corporate finance and nonprofit businesses (Vealey and Gerding, 2016; Li et al., 2017). In general, crowdfunding seems to have enormously impacted entrepreneurial potentiality (Del Sarto and Magni, 2018). It has emerged as an interesting opportunity, especially in emerging economies (Nisar et al., 2020).
Research suggests that the relationship between capital seekers and capital providers depends on the context and the intent of the campaign (Bellefamme et al., 2010). The behavior of the funder is influenced by the potential of the project, the duration of the campaign and the geographical proximity (Agrawal et al., 2010; Burtch et al., 2013; Gleasure and Feller, 2016). However, for many countries, several studies have highlighted the relevance of many operators, at an institutional more than an individual level, which may influence crowdfunding evolution (Mollick, 2014; Jegelevičiūtė and Valančienė, 2015), highlighting the impact of the entrepreneurial ecosystem in stimulating new entrepreneurship in this field.
Although crowdfunding was born as a solution for collecting funds in the creative and social sectors, usually having nonmonetary rewards in return (Hemer, 2011), the more intense diffusion of crowdfunding in the economic systems has evolved toward entrepreneurship (Vasileiadou et al., 2016; Bento et al., 2019). In general, this has happened in the concept of a social enterprise, especially when it is technological (Del Giudice et al., 2019). To test this expectation, the following hypothesis has been formulated.
Crowdfunding has a positive impact on entrepreneurial intention.
3.2 Mobile payment and entrepreneurial intention
The evolution of the Internet, most of all when accessible from smartphones, has vastly impacted the financial system, in particular as regards the mobile payments, as in truth has happened for any other field of the digital economy (Del Giudice et al., 2021). There has been a rapid development in the part of telecom operators, financial institutions and merchants to increase the adoption of mobile services using the Internet, most of all via mobile phone usage (Humbani and Wiese, 2019; Kumar et al., 2020, 2021).
Other relevant studies in the field have emphasized the necessity for common technological standards (Dahlberg et al., 2008), confidence on behalf of the users (Lu et al., 2011) and the maturity of some psychological and social factors (Yang et al., 2012). All of these aspects are strictly related to the concept of the risk that is connected to mobile payments, which somehow should discourage one from conceptualizing it as a positive relationship. Instead, to test this specific expectation, the following hypothesis has been formulated.
Mobile payment has a positive impact on entrepreneurial intention.
3.3 Blockchain and entrepreneurial intention
To ensure the integrity of whatever utility (product, process or other) is possible to enable its tokenization, using a decentralized network that can be called a blockchain, these tokens can be sold not only to gain access to the abovementioned product and/or process but also, for example, to enter the capital of a business. In fact, even equity investments are nowadays possible. For example, with the implementation of the 2012 “Jumpstart Our Business Start-ups (JOBS)” law in the USA (Goulding et al., 2013), entrepreneurs and small business owners have the opportunity to seek stock or bond investments from the public, often in the form of crowdfunding (Stemler, 2013). In this vein, crypto entrepreneurship tokens may accelerate the harmonization among the several operators that may act in an ecosystem (Bakos and Halaburda, 2018) with a blockchain that may enable relationships that are more transparent, reliable and fluent among entrepreneurs and potential investors (Cong et al., 2021).
Most probably, the better the performance of the blockchain, the better the vitality of the entrepreneurial ecosystem (Li and Mann, 2018). To test this expectation, the following hypothesis has been formulated.
Blockchain has a positive impact on entrepreneurial intention.
3.4 Entrepreneurial education and entrepreneurial intention
Undertaking is a complex activity, with several elements that may condition the related spirit (Autio and Ács, 2010). In many cases, these elements discourage potential entrepreneurs, above all when young, from starting a business (Van Gelderen et al., 2015). In addition, entrepreneurial education is one of the most important investments that people can implement. By accessing this kind of training, people can not only develop knowledge and skills but can also have more ideas, solutions and then opportunities (Wu and Wu, 2008).
Thus, education about undertaking is a relevant enabler of the entrepreneurial ecosystem because it can improve the performance of young people in starting their own businesses and augment the possibilities and the probabilities of potential positive results for entrepreneurship trainees (Duval-Couetil, 2013; Brockman et al., 2021). To test this expectation, the following hypothesis has been formulated.
Entrepreneurial education has a positive impact on entrepreneurial intention.
3.5 Favored regions and entrepreneurial intention
Entrepreneurship is emerging as one of the most important pillars of economic growth and development. There is widespread consensus that entrepreneurial ecosystems necessarily represent the humus for dynamic, productive and job-creating economies, despite the diversity of definitions of entrepreneurship (Stam, 2015; Nicotra et al., 2018; Olutuase et al., 2018; Stam, 2018; Clark et al., 2021; Stam and Van de Ven, 2021). In this respect, awareness of the importance of an entrepreneur in economic activity has evolved, and several emerging economies, such as Argentina, Chile or Tunisia, have developed specific programs that aim to strengthen the creation of jobs by granting financial and fiscal advantages to those who launch their projects in favored areas (Cruz del Rio Rama et al., 2014).
However, most of the projects have been carried out in the favored areas. To test this expectation, the following hypothesis has been formulated.
Favored regions have a positive impact on entrepreneurial intention.
3.6 Gender and entrepreneurial intention
Most research about potential differences concerning entrepreneurial behavior related to gender has been framed in a comparative fashion (Eddleston and Powell, 2008). To put it briefly, there seems to exist the underlying presumption that men and women behave differently, even though there is substantial difficulty in proving that unequivocally (Wilson and Tagg, 2010).
Yet, “… the notion that women and men entrepreneurs are essentially different seems to retain a firm grip and thus, continues to inform research efforts and policy development” (Ahl and Marlow, 2012, p. 545). To test this expectation, with specific reference to young entrepreneurs, the following hypothesis has been formulated.
Male gender has a positive impact on entrepreneurial intention.
4. Research structure
This section has been provided to describe the sample, the instruments and the methodology that was adopted for data collection and analysis. Afterward, the empirical model and its engineering are explained.
4.1 Sample
The data were collected through an online survey from all over Tunisia, which was selected as a common example for emerging economies (Othmani, 2021; Akrout and Damak Ayadi, 2022; Sghaier et al., 2021). The questionnaire of the investigation was sent via Google Forms to all young entrepreneurs who had registered with the Junior Chamber International (JCI) in Tunis, Tunisia. The respondents were assured that no personal detail or information was required for the survey so that their identity would remain anonymous.
The survey was globally conducted in the period from April 2020 (first submission) to July 2020 (last responses). Finally, the sample contains a total of 93 people (respondents on a convenience basis) registered with the Tunisian JCI (respondents on a judgment basis).
4.2 Instruments
The survey questions were developed starting from previous investigations in the background context of this research (namely entrepreneurial intentions in entrepreneurial ecosystems and FinTech). A pilot test was conducted on young entrepreneurs to check the validity and reliability of the questionnaire. To help people understand the concepts of crowdfunding, mobile payment and blockchain, a brief description, for clarification, was given at the beginning of the questionnaire.
As reported in Table 1, the questionnaire was subdivided into four main distinct parts: entrepreneurial intention, crowdfunding, mobile payment and blockchain (entrepreneurial education. favored regions and gender were investigated as secondary factors). A five-point Likert scale was used to assess the items, where 1 = strongly disagree and 5 = strongly agree.
4.3 Methodology
A deductive quantitative approach, structured in predefined assumptions and variables (Dana and Dana, 2005), was adopted, considering that the quantitative research method in empirical investigations uses numerical data to achieve the research objective (Zikmund et al., 2013). Despite some criticism regarding the use of quantitative methods (Dana and Dumez, 2015), this approach is often considered to lead to reliable and generalizable results because it contains information with a higher level of precision (Easterby-Smith et al., 2008). In this study, the data passed the validity and reliability check before running the T-test, and regressions were calculated using SPSS 25.
4.4 Regression model
To analyze the determinants of the potential influence of knowledge, availability and accessibility of the FinTech ecosystem (as subsystem of the more general entrepreneurial ecosystem) on the entrepreneurial intention, with the contextual contribution of entrepreneurial education, the following regression model was estimated.
EIN = entrepreneurial intention
CRW = crowdfunding
MOB = mobile payment
BCH = blockchain
EDU = entrepreneurial education
FAV = favored region
GEN = gender
AGE = entrepreneur's age
COV = coronavirus
STA = start-up
In this model, CRW, MOB and BCH are supposed to act as determinants for EIN (as primary factors of investigation) together with EDU, FAV and GEN (as secondary factors of investigation). Whereas AGE, COV and STA work as control variables.
5. Results analysis
As shown in Table 2, the gender of most of the respondents was masculine (78.5%), the age of most of the respondents was between 25 and 29 years (58.1%), and most of the respondents led projects in favored regions of Tunisia (68.8%). More than half of the respondents (62.4%) had management education.
The collected data was then subjected to principal component analysis (PCA) and scale purification. Item reduction was undertaken based on the removal of items showing factor loads less than 0.5, insisting on four distinct factors (Table 3 presents the results of the analysis). The criteria used to identify the charges were that each element should charge 0.50 or more (Igbaria et al., 1995). Thus, before submitting the data to the PCA, the Kaiser–Meyer–Olkin (KMO) test was performed to determine if the data were suitable for PCA.
For the entrepreneurial intention dimension, a single item (EI3) did not present factorial weights of at least 0.5, so it was removed to support a specific factor structure. Subsequently, the total variance explained by the three items was 70.683% (cf. Table 3). The Cronbach's alpha coefficient is 0.792, which certifies the reliability of the “entrepreneurial intent” measurement scale. Finally, the results show that the value of KMO is equal to 0.669, which is respectable because it is greater than 0.500.
After eliminating the items CRW1, CRW4, CRW8, CRW9 and CRW10, a second analysis was carried out for “crowdfunding,” and one-dimensionality was sufficiently strong given the existence of a single factor that makes it possible to recover over 89% of the information. The value of KMO is equal to 0.797, which is respectable, and the quality of the item representation is satisfactory because it is greater than 0.5. The five elements considered altogether as a single element explain the 70.434% of the total variance.
Similar considerations were developed for “mobile payment” (deleting MOB3 and MOB5) and “blockchain” (deleting BCH5). The following calculations are satisfactory as well, and Table 4 shows the correlation coefficients between the various explanatory variables used in the model.
According to Gujarati (2004), significant multicollinearity occurs if the couple between two independent variables is greater than 0.8. The maximum value per pair in this study is 0.619, and therefore, multicollinearity should not be a concern for the regression analysis. The null hypothesis of autocorrelation can be accepted, that is, the explanatory variables are weakly correlated with each other.
The Durbin–Watson statistic (2.320) indicates that autocorrelation is not a problem. This is shown in Table 5 which summarizes the results obtained from the regression estimation. This table contains β coefficients, T-student's coefficients and significance coefficients.
The results of the multiple regression, shown in Table 5, support several indications. Fisher's statistic (F), measuring the overall significance of the model, is equal to 10.621 This confirms the validity and the reliability of the model at a significance level lower than 1%. R2 is equal to 0.535, meaning that the independent variables explain 53.5% of the variation in the entrepreneurial intention variable. In other words, the model demonstrates an explanatory power equal to 53.5%, a quite significant percentage.
6. Results, discussion and related potential scientific and managerial implications
The first hypothesis (H1) was used to verify whether crowdfunding positively influences entrepreneurial intention. Table 5 indicates that crowdfunding is positively (0.473) and significantly related to entrepreneurial intention (the associated value is 4.873 with p = 0.000); this allows acceptance of H1.
The results confirm the study of Abdalhakeem and Mostafa (2018), which shows that crowdfunding, as a new concept, requires more attention and reporting to the entrepreneurial community, especially in poor regions where unemployment is high and where work opportunities are few. In addition, microfinance has become a tool for democratizing the financing of entrepreneurship, and crowdfunding potentially opens the financing of entrepreneurship to the masses; then, combining crowdfunding and microfinance can lead to accelerate poverty eradication. Naturally, this consideration is probably even more evident for emerging economies, but crowdfunding is also expected to positively influence entrepreneurial intention in general (Fanea-Ivanovici and Baber, 2021).
The second hypothesis (H2) states that the presence of mobile payment has a positive impact on entrepreneurial intention. Table 5 indicates that mobile payment is positive (0.066) but not significant (Student's t = 0.815 with p = 0.417), meaning that this variable has no effect on entrepreneurial intention in this observation.
This result confirms previous studies (Antovski and Gusev, 2003); other research has suggested that security could be a reason for nonuse (Nambiar et al., 2004). In truth, the Covid-19 pandemic has meant that mobile payments, by keeping economies running and helping people reduce contact with the virus, have received strong interest during the coronavirus crisis. It is not strange that young entrepreneurs feel familiar with mobile payments and ready for undertaking in this regard. At the same time, they could feel that potential users are still unfamiliar and then be discouraged from undertaking (Mustafa et al., 2021).
The third hypothesis (H3) states that blockchain influences entrepreneurial intention, showing a positive effect. The coefficient relating to this variable is positive (0.344) and significant (Student's t = 3.477 with p = 0.001).
This result is consistent with the study of Morkunas et al. (2019), which shows that blockchain is promising in many organizational applications with a direct impact on business models and value chains. Related applications such as supply chain, Internet of Things, digital identity, electronic records, digital currency, digital payments and electronic voting (Deloitte.Com, 2018) are very powerful, and a Credit Suisse survey (CreditSuisse.Com, 2016) identified the main objectives of blockchain technology pilot projects as reduced operational costs, shorter payment times, reduced risk, new revenue opportunities and reduced costs of capital, all factors motivating entrepreneurship. In addition, according to some research, blockchain technologies represent several opportunities for entrepreneurship (Akbarpour, 2019; Morkunas et al., 2019) because entrepreneurs may reduce their transaction costs by collecting funds with a secure process (Mahto and Khanin, 2013; Mahto et al., 2018a, b).
The fourth hypothesis (H4) indicates that entrepreneurial education influences entrepreneurial intention. In fact, the coefficient relating to this variable is positive (0.312) and significant (Student's t = 1.892 with p = 0.062).
This result specifically seems consistent with the study of Ferreira et al. (2017); entrepreneurial education initiatives are specific and measurable as concerns productivity and development of entrepreneurial spirit. Therefore, the expertise of entrepreneurs and employees is quite likely to be very powerful for stimulating entrepreneurial decisions (Shi and Weber, 2021). In general, several studies have revealed the strong influence of entrepreneurial education on entrepreneurial intention, particularly in emerging economies (Guerrero et al., 2017; Doan and Hien Phan, 2020; Polbitsyn et al., 2021) where it impacts the prestige and the status/career of the entrepreneur (Orlando et al., 2021).
The fifth hypothesis (H5) specifies that the (favored) region has a positive impact on entrepreneurial intention. The results show that the coefficient for this variable is positive (0.280) and significant (Student's t = 1.694 with p = 0.094).
This result expresses a physiological connection and more specifically confirms the study of Fayolle and Gailly (2015), who highlighted the importance of the environment and externalities on entrepreneurial movement and business creation (Arias-Pérez et al., 2021). With specific reference to unfavored regions, however, other research emphasizes the possibility that less-favored conditions could stimulate alternative forms of entrepreneurship, which might have been disregarded in other contexts (Sá et al., 2019), also alternative motivations could be considered (Usai et al., 2020; Sharma et al., 2021).
The sixth hypothesis (H6) states that male gender has a positive impact on entrepreneurial intention. From Table 5, the coefficient relating to the gender variable is positive (0.098) but not significant (Student's t = 0.530 with p = 0.598), meaning that this variable has no effect on the entrepreneurial intention in this observation.
These results seem compatible with the studies of Wilson et al. (2007) and Hamidi et al. (2008); although, in general, female propensity to entrepreneurship still seems less common (Zhao et al., 2005). Entrepreneurial ecosystems should be governed in this direction at an institutional level, that is, to stimulate female entrepreneurship by virtue of entrepreneurial education (Ferrandiz et al., 2018; Meeralam and Adeinat, 2022; Pelegrini and Moraes, 2022). From the current survey, male gender does not have a primary impact on entrepreneurial intentions. However, the study found some interaction effect, although not significant, probably highlighting the complex impact of gender on entrepreneurial intentions (Hamidi et al., 2008). Also, similar impacts, with a validating negative sign, emerged for age, coronavirus and startup variables.
7. Conclusion
FinTech is a hot topic nowadays, and there is a lot of speculation about its potential to replace existing business models. In this respect, this study intended to analyze the potential impact of some FinTech determinants, namely crowdfunding, mobile payments and blockchain, together with entrepreneurial education, on young entrepreneurs' intention in the Tunisian context, as example for emerging economies.
The results of the research revealed that knowledge, availability and accessibility of crowdfunding and blockchain have an impact on young entrepreneurial intention. FinTech acts as a powerful contributor to the more general entrepreneurial ecosystem to help young Tunisian entrepreneurs focus on related applications for improving financing for start-ups and innovative projects. Instead, mobile payment seems to generate no significant stimulus on entrepreneurial intention. Further research could be developed using more advanced FinTech applications to generate entrepreneurial activities, customer satisfaction and financial performance.
In addition, entrepreneurial education exerts a relevant influence. The results show that young entrepreneurs in Tunisia are interested in new technological platforms and that knowledge building, with respect to accumulating related intellectual capital, may enhance their decision to undertake, as this emerged from the preference for favored regions. If accordingly supported, young entrepreneurs want to launch their projects in a context characterized by strong environmental and even health disturbances such as the Covid-19 pandemic by taking advantage of new financial technologies, without regard to the gender of the entrepreneur.
Finally, all of the main components of intellectual capital seem to be represented in the possible scenario under investigation in the current study: human capital (with regard to the entrepreneurial education), structural capital (with regard to the Fintech ecosystem) and relational capital (with regard to the attractiveness of the favored regions). In this direction, intellectual capital can arrive at generating, at the environmental level, a sort of widespread social capital that is potentially able to impact the psychological and emotional motivations of young entrepreneurs, especially in emerging economies.
8. Research limits and future directions
This research has a few limitations, which may consequently act as indicators for future investigations. First, further investigation should be considered to gather more information regarding the ample impact of FinTech determinants on entrepreneurial intent by increasing the number of determinants under investigation. Second, the study used a sample based on judgment (the Tunisian context) and convenience (the first respondents). Therefore, it is suggested to enlarge and diversify the sample for better results and for a better understanding of potential cross-cultural bias. Third, further effort could be concentrated on studying which kind of entrepreneurial education initiatives would be more powerful for leveraging technology for undertaking.
At last, we should mention that mainly attitudes and motivations were under investigation. Although these are potentially exposed to the influence of a more general knowledge ecosystem, even qualitative analysis can be useful. In this respect, mixed methodologies could be quite interesting to adopt in order to highlight with more emphasis the abovementioned psychological and emotional factors at the basis of the undertaking decisions, even in such technological environments as Fintech ecosystems.
The questionnaire: constructs and measures
| Constructs | Measures | Sources |
|---|---|---|
| Entrepreneurial intention | (1) I am currently spending time growing my business with new online platforms (2) I am looking for opportunities to use financial technology to start a business (3) I fully intend to start a business on technological platforms | Ács et al. (2014) |
| Crowdfunding | (1) The crowdfunding platforms are integrated (2) Crowdfunding helps in marketing and promoting entrepreneurship (3) Crowdfunding is suitable for financing small emerging projects (4) Crowdfunding is a short (one year) funding method for an existing business (5) Crowdfunding reduces the cost of financing channels (6) Crowdfunding increases the efficiency of funding channels (7) Crowdfunding platforms are trustworthy (8) Anti-terrorism laws diminish the chances of success of crowdfunding (9) Crowdfunding offers the freedom to use the appropriate payment method (10) Crowdfunding leads to efficient payments | Malhotra et al. (2004) Sharma and Lertnuwat (2016) |
| Mobile payment | (1) Mobile payment is easy to use (2) Mobile payment gives me up-to-date information (3) People whose opinions I value prefer that I use mobile payment (4) Mobile payment is convenient because I can use it anytime (5) Compared to traditional payment methods, mobile payment methods are more convenient | Chen et al. (2020) |
| Blockchain | (1) Blockchain technology improves transparency (2) Blockchain technology increases trust (3) Blockchain technology reduces risk (4) Blockchain technology reduces transaction costs (5) Blockchain technology ensures a fast and secure payment process | Bentler and Chou (1987) Bryant and Yarnold (1995) Chen (2018) |
Source(s): Authors' elaboration
Profile of the respondents
| Demographic items | Frequency | % |
|---|---|---|
| Gender | ||
| Male | 73 | 78.5 |
| Female | 20 | 21.5 |
| Age | ||
| Under 25 | 16 | 17.2 |
| 25–29 | 54 | 58.1 |
| 30–34 | 2 | 2.2 |
| 35–45 | 13 | 14.0 |
| over 45 | 8 | 8.6 |
| Region | ||
| Favored region | 64 | 68.8 |
| Nonfavored region | 29 | 31.2 |
| Education | ||
| Management education | 58 | 62.4 |
| No management education | 35 | 37.6 |
Source(s): Authors' calculation
Rotated factor matrix
| Dimension | Items | Factor Loadings | Vp | α | KMO | |
|---|---|---|---|---|---|---|
| 70.683 | 2.120 | 0.792 | 0.669 | |||
| Entrepreneurial intention | EI1 | 0.792 | ||||
| EI2 | 0.620 | |||||
| EI3 | 0.493† | |||||
| 70.434 | 3.525 | 0.890 | 0.797 | |||
| Crowdfunding | CRW1 | 0.352† | ||||
| CRW2 | 0.741 | |||||
| CRW3 | 0.560 | |||||
| CRW4 | 0.400† | |||||
| CRW5 | 0.667 | |||||
| CRW6 | 0.696 | |||||
| CRW7 | 0.858 | |||||
| CRW8 | 0.254† | |||||
| CRW9 | 0.212† | |||||
| CRW10 | 0.313† | |||||
| 64.648 | 2.122 | 0.725 | 0.653 | |||
| Mobile payment | MOB1 | 0.673 | ||||
| MOB2 | 0.725 | |||||
| MOB3 | 0.236† | |||||
| MOB4 | 0.542 | |||||
| MOB5 | 0.322† | |||||
| 89.041 | 3.562 | 0.959 | 0.869 | |||
| Blockchain | BCH1 | 0.810 | ||||
| BCH2 | 0.903 | |||||
| BCH3 | 0.923 | |||||
| BCH4 | 0.925 | |||||
| BCH5 | 0.322† |
Note(s): † Deleted for further analysis
Source(s): Authors' calculation
Correlation coefficients
| MOB | BCH | CRW | STA | FAV | GEN | EDU | AGE | COV | |
|---|---|---|---|---|---|---|---|---|---|
| MOB | 1 | ||||||||
| BCH | −0.233 | 1 | |||||||
| CRW | −0.149 | 0.619 | 1 | ||||||
| STA | −0.097* | 0.086 | 0.015** | 1 | |||||
| FAV | −0.082 | 0.033** | 0.019** | 0.100 | 1 | ||||
| GEN | −0.051** | −0.054** | −0.141 | −0.044** | 0.026** | 1 | |||
| EDU | 0.188 | 0.108 | −0.009*** | 0.064 | 0.128 | 0.218 | 1 | ||
| AGE | 0.076 | 0.056** | 0.102 | −0.016** | 0.006 | 0.119 | −0.132 | 1 | |
| COV | −0.043** | 0.105 | 0.136 | 0.149 | 0.044** | −0.194 | −0.173 | 0.053** | 1 |
Note(s): *, **, *** represent significance at the 10, 5 and 1% levels, respectively
Source(s): Authors' calculation
Multiple regression results
| Items | β | T-student | Significance |
|---|---|---|---|
| (Constant) | 0.089 | 0.320 | 0.750 |
| CRW | 0.473*** | 4.873 | 0.000 |
| MOB | 0.066 | 0.815 | 0.417 |
| BCH | 0.344*** | 3.477 | 0.001 |
| EDU | 0.312 | 1.892 | 0.062 |
| FAV | 0.280* | 1.694 | 0.094 |
| GEN | 0.098 | 0.530 | 0.598 |
| AGE | −0.145** | −2.054 | 0.043 |
| COV | −0.025 | −0.161 | 0.872 |
| STA | −0.327** | −2.050 | 0.044 |
| Model statistics | F = 10.621 - p = 0.000 R2 = 0.535 - R2 adj = 0.485 D -W = 02.320 | ||
Note(s): *, **, *** represent significance at the 10, 5 and 1% levels, respectively
Source(s): Authors' calculation
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About the authors
Giuseppe Festa is an Associate Professor of Management at the Department of Economics and Statistics of the University of Salerno, Italy. He holds a PhD in Economics and Management of Public Organizations from the University of Salerno, where he is the Scientific Director of the Postgraduate course in Wine Business. He is also the Chairman of the Euromed Research Interest Committee on Wine Business. His research interests focus mainly on wine business, corporate venture capital, information systems and healthcare management.
Sihem Elbahri, PhD student in Finance at the University of Sfax, Tunisia.
Maria Teresa Cuomo, PhD, is an Associate Professor of Management at the University of Salerno, where she teaches “Management” and “Management and Innovation.” She teaches also at the Business School of the “Bicocca” University in Milan. She is a Member of several Editorial Committees of national and international journals and has published in top international journals about corporate reputation, consumer behavior, augmented retail and investment assessment. She has presented papers and research outcomes at numerous conferences all around the world and has carried out research, consultancy and training to various organizations (both public and private) on finance and performance, investment assessment, market research and marketing.
Mario Ossorio ias an Assistant Professor of Management at the “Luigi Vanvitelli” University of Campania, where he received his PhD in Entrepreneurship and Innovation. He earned his MSc in Economics and Finance at the “Federico II” University of Naples. His primary research interests include innovation, internationalization, family business and mergers and acquisitions. He has published in Management Decision, Journal of Management and Governance, International Journal of Managerial and Financial Accounting and EuroMed Journal of Business.
Matteo Rossi has PhD in Management from the University of Sannio, Benevento, Italy. He is currently an Associate Professor of Corporate Finance at the University of Sannio, an Adjunct Professor of Advanced Corporate Finance at LUISS, Rome (Italy) and a Research Assistant Professor at WSB University, Poznan (Poland). Dr. Rossi is the Editor-in-Chief for the International Journal of Managerial and Financial Accounting and the International Journal of Behavioural Accounting and Finance.