*4.2. Centrality of Publications*

Bibliometric analysis can also determine the relationship between publications. Node sizes are determined by the number of citations and a network is created by attributing the degree of the node to each citation. The size of the node indicates the degree of centrality. The links show the direction of information flow of direct citations between nodes from the former to the new. Node tags include the degree of total centrality as well as definitions of publications. Figure 7 presents the network structure for nodes with a degree of centrality of more than 10.

**Figure 7.** Network visualization of the centrality of countries' citations. Note(s): This figure was created with a dataset from Scopus via VOSviewer.

#### *4.3. Centrality of Keywords*

Figure 8 shows the network of keywords. The lines connecting the nodes represent the relationship between the most commonly used keywords in the articles in the study. These can be grouped into four sets: financial technology, China, financial services, and blockchain. On the left, crowdfunding, blockchain, and machine learning appear to be grouped around FinTech. The high frequency of these terms shows the interest and up-to-datedness of the researchers.

**Figure 8.** Network visualization of the centrality of keywords. Note(s): This figure was created with a dataset from Scopus via VOSviewer.

Regarding the distribution of the scientific fields that the sampled studies come from, business management comes first with 22.7%, followed by computer science with 18.2%, economics (16.7%), and social sciences (13.3%). Thus, a variety of disciplines are conducting research into FinTech (Figure 9).

**Figure 9.** Distribution of disciplines for studies of FinTech. Note(s): This figure represents the distribution of disciplines in FinTech studies between 2015 and 2021. The data were taken from the Scopus database using the keyword "FinTech".

Figure 10 shows the betweenness centrality, which measures the number of times a node intersects the shortest path between two other nodes. This indicates an author's importance in connecting with other authors (Milian et al. 2019). The minimum number of citations in the figure is 10. Of the 60 sampled publications, 21 with links to each other were mapped, with a centrality between 0 and 10. Gomber et al. (2018), Shim and Shin (2016), and Schueffel (2016) have the highest centrality.

**Figure 10.** Intermediation as betweenness centrality. Note(s): This figure was created with a dataset from Scopus via VOSviewer.

#### *4.4. Lotka's Law*

Lotka's Law (Lotka 1926) predicts the number of publications published by each author in a particular field. That is, 60% of the authors will write one article, 15% will write two, 7% will write three, 4% will write four, etc. Figure 11 presents the results for papers on FinTech alongside the predicted distribution according to Lotka. It shows that 88.6% of authors have just one publication, 7.6% have two, and 2.5% have three. This indicates that FinTech authorship does not currently comply with Lotka's Law. The dashed line in the graph represents the graph that should be according to Lotka's Law.

**Figure 11.** Lotka's Law of productivity, and actual authorship distribution. Note(s): This figure was created with a dataset from Scopus via R Studio.

#### *4.5. Bradford's Law*

Bradford's Law (Bradford [1929] 1985) measures whether journals have a core effect by dividing the journals in a specific field into three groups as outlined earlier. In the present study, 636 studies were published by 387 different journals and books. As Figure 12 shows, 40 journals and books accounted for 212 papers, 148 journals and books published 215 papers, and 199 journals and books published 209 articles. This suggests that FinTech research publishing is in line with Bradford's Law.

**Figure 12.** Bradford's Law of core publications and actual distribution by publications. Note(s): This figure was created with a dataset from Scopus via R Studio.

#### **5. Results and Discussion**

RQ1. How has the literature developed over time?

This question was answered by sub-questions RQ1.1, RQ1.2, and RQ1.3.

RQ1.1. What are the most influential studies and authors?

When the publications in 2018 are examined in Table 5, Gomber et al. (2018) with 47%, Lee and Shin (2018) with 41%, Buchak et al. (2018) with 60%, and Gai et al. (2018) with 35% received the most citations for 2021, while Gomber et al. (2017) with 37%, Gabor and Brooks (2017) with 40%, Haddad and Hornuf (2019) with 57%, and Shim and Shin (2016) with 30% received the most citations again in 2021. As the subject is still very new, researchers' interest is increasing continuously as indicated by the growing number of citations.

Gomber et al. (2018), Lee and Shin (2018), Gomber et al. (2017), and Gabor and Brooks (2017) all received at least 140 citations during the review period. Gomber et al. (2018) reported that the long-standing dominance of leading companies is at risk because they cannot effectively connect with the FinTech revolution. They presented a new FinTechinnovation-mapping approach that enables the assessment of the degree of changes and transformations in four financial services areas: operations management in financial services, technological innovations, multiple innovations, and issues related to investments. Lee and Shin (2018) examined FinTechs from a historical perspective and focused on various FinTech business models and investment types with their game-changing features. Gomber et al. (2017) introduced the institutions related to the digital finance cube, which includes three basic dimensions of digital finance and FinTech, related business functions, applied technologies, and technological concepts. Gabor and Brooks (2017) examined the increasing importance of digital-based financial inclusion in the form of development interventions through FinTechs, government agencies, and other organizations. They concluded that FinTech-philanthropy development (FPD) creates ecosystems that map, expand, and monetize digital footprints. They also noted that the vision of the irrational client combines behavioral economics with predictive algorithms to accelerate access to finance and monitor adherence to them, while the digital revolution proposes new forms of profiling with financial(ized) inclusion that makes poor households new generators of financial assets.

#### RQ1.2. What are the main studies in FinTech?

As shown in Figure 6, Buchak et al. (2018) was one of the most influential works, followed by Gomber et al. (2018), Lee and Shin (2018), and Gomber et al. (2017). Buchak et al. (2018) studied how two forces, regulatory differences and technological advantages, contributed to this growth, due to the fact that shadow-bank market share in residentialmortgage origination nearly doubled from 2007 to 2015, with particularly dramatic growth among online "FinTech" lenders. Gai et al. (2018) surveyed FinTech by collecting and reviewing contemporary achievements that theoretically proposed a data-driven FinTech framework. The survey included five technical topics: security and privacy, data techniques, hardware and infrastructure, applications, and management and service models. They demonstrated the basics of creating active FinTech solutions. Schueffel (2016) offered a definition that is distinct as well as succinct in its communication, yet sufficiently broad in its range of application. Leong et al. (2017) examined the development of a FinTech company that gives micro-lending to university students in China. They showed how digital technology offers a firm strategic capability, how an alternative credit score can be calculated with unconventional data, and how financial coverage of market segments that are not previously covered can be realized. Haddad and Hornuf (2019) investigated the economic and technological determinants inducing entrepreneurs to establish ventures with the purpose of reinventing FinTech and found that the more difficult it is for companies to access loans, the higher is the number of FinTech startups in a country. Shim and Shin (2016) used Actor–Network Theory (ANT) to conduct a multi-level analysis of the historical development of China's FinTech industry as a stepping stone for investigating the interaction between it and the emerging social and political context. They also discussed policy implications of China's FinTech industry, focusing on the state's changing role in driving the growth of the national sector inside and outside.

## RQ1.3. What are the distributions and effects of publications over time?

The sample included 636 studies focusing on FinTech applications, by 1445 different authors, from 387 different journals and books. The journals and books with the most publications (see Table 2) were as follows: Sustainability Switzerland with 15 publications, Perspectives in Law, Business and Innovation with 8 publications, and Impact of Financial Technology (Fintech) on Islamic Finance and Financial Stability with 7 publications. The top 10 journals and books include Industrial Management and Data Systems with 33.2 CPP, Financial Innovation with 15.28 CPP, Lecture Notes in Computer Science including subseries with 5 CPP, Journal of Open Innovation: Technology, Market, and Complexity with 4.12 CPP, and Finance Research Letters with 4 CPP. Thus, despite the novelty of this field, there are already many periodicals regularly publishing research on FinTech.

RQ2. What are the important topics in the FinTech literature?

Figure 9, which was developed according to Figure 8, showed the research disciplines of the sampled articles and the relationships between the most-frequently used words. The most common keywords in the papers were financial technology, blockchain, financial services, and financial inclusion. These keywords most often appeared in businessmanagement sources (22.7%), followed by computer science (18.2%), economics (16.7%), and social science (13.3%). Thus, these four disciplines account for approximately 71% of

all publications on FinTech, which indicates that this field is currently confined to a few disciplines rather than being evenly dispersed across many.

From the analysis of the relationships between groups in the coding scheme, a framework has emerged for the literature summary, whose main axis is the FinTech activity sector, as shown in Figure 8. FinTech is most strongly connected to financial inclusion, China, and financial services, whereas blockchain has more connections with bitcoin, cryptocurrency, and smart contracts. Figures 8 and 9 formed the main backbone of the analysis for addressing RQ2.

#### RQ3. Are the results compatible with Lotka's Law?

Unsurprisingly, the vast majority of authors (88.6% of 1445) have just one publication, since FinTech has only recently entered the literature. Lotka's Law, however, predicts that only 60% of authors should have a single publication. Similarly, while 7.6% of authors examined had two publications, Lotka's Law predicts this should be around 15%. While just 2.5% of authors had three publications, Lotka's Law predicts 7%. Consequently, the distribution of authorship in FinTech does not conform to Lotka's Law.

#### RQ4. Are the results compatible with Bradford's Law?

Bradford's Law predicts that publications can be divided into three groups according to diminishing impact. The 40 journals that constitute the first group of publications in the study published 212 publications, 148 journals in the second group published 215, and 199 journals published 209 articles. The results of the study show that the first few journals published a third of the studies, followed by a large group that published the second third, and the largest number of journals published the remaining third. Thus, the distribution of publications by journals on FinTech is in line with Bradford's Law.

## **6. Conclusions**

This study contributes to the understanding of the FinTech research phenomenon in five different ways in the scope of 636 publications obtained from Scopus between 2015 and 2021. First, FinTechs, which are increasingly influential globally, are also increasingly attracting attention in the scientific literature. Despite this growing interest, the research areas of publications on FinTechs are still not fully determined. The scarcity of mapping studies on FinTechs, as well as the lack of systematic reviews, suggests the need for a comprehensive analysis. The present study reveals the rapidly increasing interest in FinTech over the past six years as reflected in 636 publications from 387 journals and books predominantly representing four academic disciplines: business management, computer science, economics, and social science.

Second, this study identified the sub-topics and trends in publications on FinTechs along two axes. The first is financial services, financial inclusion, and financial technologies, where FinTech is centered. The access of investors and researchers to financial services, their involvement in financial business and transactions, and the use of financial technology are issues that have a significant impact on society. Research on the subject also shows that people of all levels are influenced by FinTech applications represented by these concepts and that traditional applications are quickly losing ground to FinTech applications. The second axis concerns the links to FinTech of cryptocurrency, bitcoin, and smart contracts, with blockchain as the hub. These new technological tools, in which information security is crucial, play an important role in making the individual and society freer. These technologies also demonstrate important security and privacy requirements that are needed in commercial life by opening the way for unmediated secure trade.

Thirdly, in order to make a complete definition of FinTech, this study investigated whether there is a consensus regarding the framework needed to describe FinTech. Research indicates the existence of a structure in which internet-based financial work and transactions can be conducted securely and privately, that facilitates access to information and finance, and that replaces the traditional financial structure with innovative companies.

Fourth, the study assessed the contributions and support of universities to academic research on FinTech. Universities in Asian countries receive more sponsorship and produce more articles, although their impact scores are lower. While the US and Europe have higher impact scores due to their current superiority in science and technology, Asian countries, especially China, are now focusing heavily on the issue and want to capture the trend of development in this area. The US leads in international cooperation between academics researching FinTech, followed by China, the United Kingdom, and Australia.

Fifth, while the distribution of authorship in this field conflicts with Lotka's Law, Bradford's Law was supported. The results of the study show that the first few journals published a third of the studies, followed by a large group that published the second third, and the largest number of journals published the remaining third. Given that FinTech is a very new field, it is possible that patterns of research publications will converge more with these laws in the future.

This study reflected the opinions and practices of all segments of FinTech research, as it included a wide range of articles, from traditional financial institutions to the FinTech ecosystem. As with similar studies adopting such a broad framework, however, the present study has limitations due to databases and search directories. The fact that databases such as Web of Science and ScienceDirect are not included in the study is a research limitation. In future studies, it is recommended to conduct comparative studies between Scopus, Web of Science, and ScienceDirect databases to expand the literature. The studies sampled here were also unique as they are some of the first in the field. This study examined research publications on FinTech based on four main research questions, which made it possible to deepen the study. FinTech research is predominantly conducted within business management, computer science, economics, and social science, thus paving the way for more in-depth research in these areas. In addition, several issues emerged that need to be examined more deeply, particularly FinTech's relationship with financial inclusion and financial services, and Blockchain's relationship with cryptocurrency and smart contracts. Examining these relationships to reveal their strength, causes, and effects would fill an important gap in the literature.

**Author Contributions:** Conceptualization, G.T. and U.B.G.; methodology, G.T.; software, G.T.; validation, G.T., U.B.G. and F.M.S.; formal analysis, G.T.; investigation, G.T., U.B.G. and F.M.S.; resources, G.T., U.B.G. and F.M.S.; data curation, G.T.; writing—original draft preparation, U.B.G.; writing—review and editing, G.T., U.B.G. and F.M.S.; visualization, G.T.; supervision, U.B.G.; project administration, G.T.; funding acquisition, F.M.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data are contained within the article or available from referenced sources.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

