Content Analysis of the Financial Literature Over Time in the World

Abstract

The paper offers a conceptualization of the phenomena of financial illiteracy and its relationships with digital skills in a rapidly changing landscape driven by technology. It proposes a bibliometric analysis of the issue from the perspectives of individuals and households, entrepreneurs and firms and financial intermediaries and authorities. The aim of this chapter is to analyse the stream of the worldwide FL literature in order to shed a light on the conceptual structure of the research field, with an emphasis on its evolution over time and its future developments. We are interested in FL themes and in analytical perspectives from different disciplines, and consequently, our focus is more on thematic evolution and approaches than on authors’ productivity, authors’ influence, networks, research centres and journals.

1. Introduction

Financial literacy is a topic widely studied in many geographical areas under the light of different disciplines. The aim of this chapter is to analyse the stream of the worldwide FL literature in order to highlight the conceptual structure of the research field, with an emphasis on its trends. We are interested in FL themes and in analytical perspectives from different disciplines, and consequently, we are not adopting the conventional research methods that focus on author productivity, author influence, networks, research centres and journals.

As well known, bibliometrics is a quantitative method which uses scientific literature as data (i.e. citation statistics and number of articles) for its analyses mainly aimed at assessing researchers’ productivity and influence through publishing. They provide maps of the state of the art in a given area of scientific knowledge, and they help identify different structures within a research field, hot topics and evolving research frontiers. These tools have been recently used in the domain of financial literacy [1, 2, 3, 4, 5] or in specific financial domains such as banking [6, 7], insurance [8], Islamic insurance [9], consumer credit [2], ITC and financial education [10] and green finance [11].

In this paper, we explore the thematic structure of the field of financial literature through the analysis of the occurrences and co-occurrences of authors’ keywords. To do this, we move from OECD’s definition of financial literacy, as a combination of knowledge, attitude and behaviour [12]. These elements are part of a wider wealth of knowledge, abilities and skills, behavioural conducts and habits of individuals. Their specific economic and financial components jointly contribute to determining financial literacy. Figure 1 graphically shows this concept at the intersection of the three mentioned components.

Figure 1.

Financial Literacy: authors’ conceptual scheme.

The structure of the chapter is as follows: Section 2 illustrates the research design and tools, Section 3 discusses the software and methodology used, and Section 4 presents the results considering the keywords used and the related topics, the linkages among subthemes, the interest for the issue (the stream of published papers), the analytical perspective of different disciplines and the geographical research focus. Finally, Section 5 suggests some concluding remarks.

2. Research design and tools

For our cognitive purposes, we first identified the database for the search of publications, selected and refined the search criteria, chose the bibliographic software and performed our analysis selecting some bibliographic representation paths.

In order to create our database, the first step of our analysis was to choose the database for the search of publications that contained the term “financial literacy” in the title, keywords or abstract.

There are different databases for scientific publications (Scopus, Web of Science [WoS], Google Scholar, Dimension, Crossref and Microsoft Academic), with differences in the coverage of the data sources, the completeness and accuracy of citation links and the speed of updating. Our database choice was initially between Web of Science or Scopus, which are the best databases for scientific purposes, have a wide coverage of research publications and are widely used by researchers.

Some authors [13, 14] suggested that WoS and Scopus can be considered complementary databases because they are not “mutually exclusive”. Besides other differences [15], the content indexed in Scopus and in WoS is highly overlapping, but the extent of content overlap varies across disciplines with some disciplines covered more extensively than others and others disciplines underrepresented [16]. That is the reason why we decided to use both of them by creating a combined database.

For the merging procedures, we followed the user-friendly three-step procedure suggested by Caputo and Kargina [13], rather than the four-step ones proposed by Echchakoui [14].

In the two above-mentioned databases, the subject areas (social sciences, economics, finance, business, management and accounting and education) were similar but not identical, due to the different categories in the two databases.

As for the time span, we chose the period from 2000 to 2023, since the pre-2000 literature is extremely scanty.

As for the document types, we included articles, books, books chapters, reviews, conference papers and early access.

We had no refinement for the language.

Our search queries initially resulted in 4158 publications in Scopus and 4011 in WoS.¹ Our efforts were aimed at creating one uniform dataset with a unique format with the same criteria for data representation.

The combination process (defined as “the data wrangling”) could not be fully automated, as noted by Ullah et al. [18], and it implied a manual work of comparing (using DOI reference and/or titles and/or authors’ names) and removing duplicates, checking (i.e. cases with authors’ names in a different order or with different or absent abbreviation), unifying and fixing “broken” data (e.g. spelling errors). We then manually checked and evaluated the remaining articles to find the “borderline articles” and to assess if they corresponded to our study focus. In this step, the evaluation of the articles’ inclusion/exclusion was based on the article title and abstract. This was the most time- and effort-consuming in the process of literature data gathering.

The final aggregated database was of 3991 publications.

3. The software and methodology

As for software, we used two bibliometric software: Vosviewer [19], which offers a clear thematic network visualisation, with a possible focus on specific clusters, and the open-source web-based interface of the R package, Biblioshiny [20], which provides other processing and visualisations such as lines charts for temporal trend growth, trend topic analysis visualisations and thematic analysis that plots clusters of keywords along two dimensions (density vs. centrality).

The same dataset was then expressed in Scopus format for Vosviewer and in WoS format for Biblioshiny as they were the formats more easily uploaded into the two bibliometric software. For Vosviewer we used a simplified database that included only the relevant information for thematic network map visualisation, and we exported them into .csv format, while for Biblioshiny we used, in WoS format (following the process suggested by [13]), a wider spectrum of metadata.

As for methodology, our analysis aimed at shedding light on the conceptual structure of the research field, its evolution and its recent trends; as previously mentioned, it is based on the use of keywords and their connections (occurrences and co-occurrences). We consider keywords as proxies of the issues studied regarding financial literacy in various papers from different disciplines and areas of interest. Financial literacy is indeed a multifaceted, complex topic, and bibliometric techniques allow us to explore this complexity in depth.

As a matter of fact, the two databases which originated our dataset include two categories of keywords: “author keywords,” chosen by authors, and keywords suggested by the database providers, named “KeyWord Plus” (in WoS) or “Index Keywords” (in Scopus). However, just the first type of keywords is always present in both databases. Consequently, our methodological choice fell on the author keyword.²

In order to test our methodology, we initially set the number of keyword co-occurrences at the minimum level of 1, which produced a large number—equal to 6187—of terms qualified and whose preliminary visualization is given in Figure 2.

Figure 2.

Vosviewer map visualization using authors’ original keywords—1 co-occurrency.

We noticed that there is a very large number of different words used as keywords which makes the map unreadable and that spelling mistakes or singular/plural for the same terms affect the frequency of co-occurrence of keywords, reducing the efficacy of the network map visualization.³ The number of authors’ keywords was still very high due to the wide number of different synonyms for the same concept. We then increased the minimum number of co-occurrences to 10, in order to reduce the number of keywords in the network and have a better visualization: unfortunately, the map did not help to clearly identify thematic networks in financial literacy. Furthermore, the number of clusters, the number of links and the total links’ strengths were not satisfactory for our purpose.

We operated the methodological choice to construct a new thesaurus file by aggregating similar keywords (i.e. same meaning but with a different specification) and also aggregating some terms whose specifications were not providing a useful visualisation (i.e. names of specific research methods). As for countries’ names, in general, we aggregated them using their continent name with the exception of India and China, due to their high number of occurrences.

In choosing appropriate and standardized keywords, for some terms, we inspired ourselves with the conceptual framework and keywords proposed by Zaimovic et al. [5] and shown in Figure 3.

Figure 3.

Financial literacy -conceptual framework (adapted from Zaimovic et al.).

4. The results

The described methodology, sharpened step by step, allowed us to build the final dataset and perform the analysis considering occurrences, co-occurrences and clusters. First of all, our aim is to perform a co-occurrence analysis centered on author keywords. As previously said, our use of co-word analysis is based on the assumption that a paper’s keywords adequately and synthetically describe both its content and its connections between issues. The presence of many co-occurrences around the same word may help to identify a research theme central to the studies of different authors.

In a Keyword Co-occurrence Network (KCN) each keyword is represented as a node: the size of the nodes is proportional to the frequency of keyword occurrence (i.e. the number of times that the keyword occurs) [21]. The link between the nodes represents the co-occurrence between keywords in different publications (i.e. keywords that co-occur or occur together). The thickness of the link identifies the occurrence or co-occurrences between keywords (i.e. the number of times that the keywords co-occur or occur together).

Secondarily, in the cluster analysis, keywords/nodes are grouped into clusters. Inside a cluster, the theme’s coverage of topics is identified by the cluster’s nodes and the relationships between the topics of that theme are identified by the cluster’s links [22]. Clusters, in general, are represented in different colours. Each colour identifies a topical cluster.⁴

We chose not to take into account, when building the map, the commonly used keyword “financial literacy” to provide a clearer visualisation of clusters.⁵ A preliminary result—setting at 10 the minimum number of co-occurrences to consider—is the map provided in Figure 4.

Figure 4.

Vosviewer map of authors’ keyword after keyword substitution and without the keyword “financial literacy”—10 co-occurrences.

We identified clusters of author keywords co-occurrences using both Vosviewer map and Biblioshiny’s factorial analysis map⁶ (Figure 5). The results, in terms of cluster composition, were quite similar but not identical, and they provided us with food for thought about links among topics. The clusters in the maps, on the contrary, had a different representation. The following remarks, however, will be referred to the Vosviewer map as it enables us to provide useful graphical details.

Figure 5.

Clusters in Biblioshiny factorial map.

From a preliminary view of the Vosviewer map emerges the prevailing position, in terms of size of nodes, of keywords such as education, behaviour, followed by financial planning, pensions/retirement, research methods and then attitudes and financial inclusion, entrepreneurs, investments and risk.⁷ As previously said, the size of the node shows the relevance of the theme among researchers.

Links and nodes of the same colour define a unique cluster in which the distance among components and the thickness of links derive from the strong or weak association of topics: keywords are close to each other because a large proportion of articles treat them together, as investments and risk (the two blue nodes one next to the other in the upper part of the map in Figure 4) or as education and financial education (the two tangent yellow nodes in the lower right part of the map). On the contrary, they are distant from each other when only a small fraction of articles uses these keywords together.

The node of a cluster generally has several links with nodes of other clusters, as further illustrated for education and behaviours (Figure 6) where the topic education, in yellow, is connected with many topics of other clusters (expressed in different colours). The same for the topic behaviour (in purple). The wider the spectrum of “external links,” as shown for the two keywords in the map, the more the theme is an essential and fundamental cross-cutting theme in the financial literacy research area.

Figure 6.

Vosviewer map: education and behaviors—links with other nodes.

In the red cluster of Figure 4, there are three main topics which deserve to be mentioned: financial inclusion, digital and entrepreneurs. Financial inclusion is connected to themes related to poverty, migrants, women, unbanked (Figure 7). This node is very near to the nodes digital and technologies and to the nodes Africa and India, attesting to the relevance that researchers give to the use of digital instruments for improving the financial and socioeconomic conditions of disadvantaged people, especially in the poorest areas of the world.

Figure 7.

Vosviewer map: financial inclusion—links with other nodes.

Additionally, the red cluster is home to topics such as digital, fintech, IT, mobile and technologies that demonstrate how the digital world—which has seen advancements like chatbots, mobile technology, peer-to-peer lending and e-banking—is seen as a means of hastening financial inclusion but also may have significant developments in the investments (blue nodes) and the pension/retirement and financial planning/management topics, the green nodes (Figure 8).

Figure 8.

Vosviewer map: digital—links with other nodes.

Entrepreneurs is another topic that deserves some reflections: compared to digital, it has a narrower spectrum of links with other internal and external nodes; it has a natural and close proximity to banking (or banks and financial intermediaries) and to sustainability and green/environment, which, at the moment, are very small nodes. At a longer distance, there is a connection with the financial inclusion node. Financial inclusion might foster the birth and growth of entrepreneurs and vice versa (Figure 9).

Figure 9.

Vosviewer map: entrepreneurs—links with other nodes.

The blue cluster in Figure 10 is made of topics such as investments (and investors), risks, finance, financial decision-making, stock markets and financial markets, performance, money, insurance and financial products, information, and critical issues such as overconfidence, emotions, often analysed under psychological or attitudinal perspectives. As mentioned before, the proximity between investment and risk is very strong, while the distance with other themes of the cluster is wider. Two themes external to the cluster are instead very near as strictly connected: pensions/retirements and financial planning/management. Clearly, this cluster is linked, although with a long distance, to education and financial education, behaviour and financial behavior and attitudes.

Figure 10.

Vosviewer map: investment—links with other nodes.

The green cluster in Figure 11 aggregates terms related to households or consumers and to the financial activity to grant a better life during retirement years. Keywords with the highest occurrences are financial planning/management and pensions/retirement, which share a strict proximity, savings, debt and personal finance. Financial planning/management shares links with some external nodes of the investment cluster, with the behavioural and attitudes cluster and with the education one. There also are links with items of the red cluster, such as financial inclusion, digital and entrepreneurs.

Figure 11.

Vosviewer map: financial planning/management—links with other nodes.

The yellow cluster (in the map on the left side in Figure 6) is relative to educational themes, with education, financial education and young as main nodes but also teachers, learning, other literatures, mathematics and training. As previously noted, education has pervasive connections with other clusters’ nodes, but in particular, it shows many links with the nodes of the red cluster, from financial inclusion to entrepreneurs, women, poverty, and with nodes of the digital world and geographic areas such as Africa, India and South Asia.

It also deserves to be noted that research methods and theory are important nodes inside this yellow cluster. Research methods is a keyword we introduced to generally define specific statistical/economic/mathematical methods and tools used for obtaining empirical evidence in the researched topics. The large size of this node (Figure 12) evidences the pervasive adoption of rigorous research approaches in the financial literacy thematic area.

Figure 12.

Vosviewer map: research methods—links with other nodes.

The purple cluster (Figure 13) is relative to behavioural and attitudinal topics with a financial focus or with a general perspective, to skills, to goals such as well-being, financial socialization, financial satisfaction and financial resilience. It also includes topics such as personality, anxiety, vulnerability and stress control. The stricter proximity inside the cluster regards behavior and attitudes. There is also a strict proximity with debt and saving, which belong to other clusters.

Figure 13.

Vosviewer map: behaviour— links with other nodes.

The light blue cluster (Figure 4), for which we do not provide a detailed visualisation, contains a variety of different topics related to individual issues, such as aging, gender, health, financial fragility and financial keywords related to financial decisions such as credit, loans, wealth and homeownership. There are also themes which introduce a psychological perspective for the mentioned issues, such as psychology, personality traits, financial confidence, cognition and assessment.

The last cluster, the orange one, is a very small one with few nodes of small sizes, such as demographic, crime (with an external link to digital), financial crime and geographical area of East Asia and Pacific, which has links with a wide spectrum of external nodes.

Vosviewer maps have given us a first idea of the spectrum and composition of subthemes inside the financial literacy research area, but the Biblioshiny software helped us to have other information for deepening our analysis. The following considerations and statements will be then based on the Biblioshiny statistical output.

For a better understanding of topics’ relevance and trends, it is useful to start analysing the number of documents published over the years. The higher the scientific production of articles, the higher the researchers’ attention to the central themes of research. The scientific production of financial literacy in the time span from 2000 to the beginning of 2023 is shown in Figure 14: up to 2015, the production is moderate, while from 2016 to the end of 2022 it increases sharply, with a very steep curve after 2021, evidencing keen attention to financial literacy themes in the very last years.

Figure 14.

Cumulative scientific production from 2000 to 2022.

The quantitative analysis of journals and editors publishing research studies on financial literacy issues provides us with interesting insights connected to the emergence of one theme over others.

The variety of journals publishing researchers’ findings demonstrates the multidisciplinary nature of financial literature studies in which financial, behavioural and family counselling issues are involved (Figure 15).

Figure 15.

Most relevant sources (year 2023).

The journals that started publishing articles in the field of financial literacy were journals focused on household needs: such as the Journal of Financial Counseling and Planning, which in the years has consolidated its position as the more prolific journal for financial literature, followed by the Journal of Family and Economic Issues and by the International Journal of Consumer Studies (Figure 16). After 10 years, journals dealing with economic and financial issues (Journal of Pension Economics and Finance, International Journal of Bank Marketing) showed a greater interest in the financial literacy themes. The growing number of publications from journals focused on social/psychological/behavioural issues appeared from 2013 to 2014 and sharply rose just in the last years (Frontiers in Psychology), and their success sheds light on the quantitative data of keywords such as education and behaviors.

Figure 16.

Sources production over time.

In the recent time span, there has been a widening of financial journals interested in financial literacy themes (Managerial finance, Finance research letters, Journal of Risk and Financial Management), and there is also a bursting activity of the journal Sustainability (Switzerland), whose articles cover analysis in a wide number of countries. The International Handbook of Financial Literacy is the exception as it limited its publishing activity in a single year.

The visualisation known as the tree field plot (Figure 17) shows the statistical links among researchers’ countries, topics and sources.⁸ Most scientific outputs pertain to the USA, followed by a bunch of Asian countries (India, Malaysia, Indonesia and China). These results are based on statistics from 2023, but they are also corroborated by consistent trends in worldwide output over time.

Figure 17.

Three field plots: authors’ countries, authors’ keywords, sources.

The theme’s size in the graph of Figure 17 reflects the number of occurrences for single topics in 2023, evidencing their relevance inside the financial literacy research area. What is important to point out is the massive production of studies, from the USA, in the fields of education, financial education, pensions/retirement, financial planning/management and behaviour, whereas the commitment of American researchers to the other themes is quantitatively weaker. In the group of Indian studies, there is a relative predominance of those focused on financial inclusion/access followed by those on behaviour and financial planning/management. In Chinese studies, there are not winning themes, but the researches are spread all over the range of financial literacy topics. In Indonesia prevails the interest in behaviours and topics related to entrepreneurship.

If we adjust our point of view from themes towards nations, it emerges that studies on education are produced from all nations, without a specific qualification, whereas other subthemes seem to have distinct patterns of geographical beginning. For instance, the behaviour theme is prominently produced from the USA, Malaysia, India and Indonesia, while pensions/retirement stems prominently from the USA, Australia, Germany and Malaysia; financial inclusion/access has more contributions from India and, with small numbers, from the USA, China, Malaysia, Indonesia and South Africa; digital themes and, with lower occurrences, also entrepreneurs themes stem from both industrialized countries and PVS.

The right side of the graph illustrates what we have already observed regarding the distribution of articles among sources. Biblioshiny does not give us the possibility of analysing the dispersion of themes among sources; however, the already-seen journals’ specialization helps to hypothetically identify the themes’ publishers.

Another step of analysis concerns the themes most frequently chosen by researchers. The size of the nodes in Vosviewer map has already given us such information, but it is useful to see it with a more effective visual representation.

The graph entitled “Most relevant words” in Figure 18 shows the cumulated frequency, in the time span 2020–2023, of the author’s keywords. Education and behaviour are the most used words over time as well as research methods, pensions/retirement, financial planning/management, financial inclusion/access, investments and entrepreneurs are frequent keywords.

Figure 18.

Most relevant words.

But it is by analysing the annual frequencies of keywords (we considered the first 20 keywords; Figure 19) that it is possible to pinpoint the uneven topics’ preferences among authors, starting from 2010s on, with some themes more analysed than others. The two central themes, education and behaviours, became highly popular after 2014, with growing numbers of research studies every year, and this information can be linked with the already-seen trend of psychological journals’ production. Other themes had significantly lower popularity with the exceptions, in the last few years, of topics connected to entrepreneurs and financial inclusion/access.

Figure 19.

Word’s frequency in every single year.

The limited number of 20 for the most used keywords, useful for clear visualisations, does not capture the emergence of new topics which have, necessarily, lower frequencies. For this scope we used another Biblioshiny visualisation, named “Trend topics” (Figure 20) which easily shows since when and how long some topics became more popular and which gives evidence of the emerging themes in the very last years.⁹ Consequently, it is possible to say that researchers have focused their attention, since the early years of our time span, on a “stable” group of themes such as pensions/retirement, savings, followed by young, education in general and financial education, credit and financial planning. The focus on behavior, financial behavior, investments, entrepreneurs and financial inclusion/access emerged in more recent years.

Figure 20.

Trend topics.

New and emerging topics with lower frequencies but growing appealing are: (1) entrepreneurs, sustainability and green/environment and (2) technologies and the digital world, as shown in Figures 21 and 22. The former has an increased frequency of contributions in the last few years but has a weaker attraction force compared to those linked to the technologies and the digital world, with the exception of topics linked to the entrepreneurs’ perspective. The relation between technology and financial literacy [23] is going to be a strong one both in terms of number of articles published and in terms of subthemes chosen (digital, fintech, technologies, payments, money, crypto).

Figure 21.

Entrepreneurs topics in financial literacy over time.

Figure 22.

Digital world topics in financial literature over time.

A closer look at the inter-linkages among the themes separated by various time spans, namely the periods from 2000 to 2010, 2011–2015, 2016–2020 and 2021–2023, underscores the thematic evolution (Figure 23)¹⁰ in the domain of financial literacy.

Figure 23.

Thematic evolution.

The left side shows some of the themes that were widely used from 2000 to 2010 in which a wide group of subthemes converge. They are financial decision making, pensions/retirement, behaviour, entrepreneurs, banking, education, other literacy, digital and migrants. The second or middle part shows some of the themes that were widely used from 2011 to 2015. Some of the themes that have emerged during this period are an evolution of the previously used themes and have a connection in their content, but there also is a clear shift in research fields. Education is an extension of previous studies on education, other literacies, digital, entrepreneurs and behaviour. The topic relative to entrepreneurs is a further development of the same theme, but it also attracted studies from migrants, other literacies and banking. The topic of pensions/retirement evolved by attracting studies previously dealing with banking and entrepreneurs. In the behaviour themes many studies previously pertaining to different themes converge. South Asia and credit evidence a new and independent interest in their thematic area of research.

In the subsequent period (2016–2020) in the financial inclusion/access area of research converge studies previously targeted as entrepreneurs, South Asia and credit, while the other thematic areas of research are stable in their development.

5. Conclusions

This study analyses the conceptual structure of the financial literacy research area. We collected our dataset from Scopus and Web of Science, in order to benefit from their differences in disciplines and the contents’ coverage. We made a necessary merge among Scopus and WoS data, eliminating duplications and articles not related to our scope of analysis. We also uniformed the data format and created a homogeneous single dataset.

We performed a thematic content analysis focused on authors’ keywords, with the assumption that they adequately and synthetically describe both a paper’s content and its connections among issues. We operated the methodological choice to construct a new thesaurus file by aggregating similar keywords and also aggregating some terms whose specifications were not providing a useful visualization. In choosing appropriate and standardised keywords, for some terms, we inspired ourselves with the conceptual framework and keywords proposed in other studies on financial literature. In our analysis we did not include the keyword “financial literature,” as our dataset was obtained looking for articles on this theme and as we wanted to have a clear visualisation of results pertaining to financial literacy conceptual structure.

We performed a network analysis based on the author keywords occurrences and co-occurrences. We identified thematic clusters, with the help of Vosviewer software, and highlighted internal and external cluster links for specific themes. We also used the automated workflow in Biblioshiny software, focused on prominent journals, countries, themes and evolutionary paths to deepen our analysis and identify possible future developments.

Results show that there has been a quantitative and qualitative evolution of the research domain of financial literacy over a period of time of more than 20 years. There has been a gradual increase in publications over the years with significant growth in the last decade and in particular in the last two years. The growing number of publications is a consequence both of the broadening interest of researchers and journals for the themes of financial literacy and of the entry of new authors, in particular from emerging economies, who contributed to fostering the growth of the financial Literacy domain and to influence its conceptual structure.

Financial Literacy has evolved as an interdisciplinary research field: this observation stems from the gradual emergence of journals with different scopes and perspectives of analysis and from themes and specific topics chosen by authors over time. Initial publications, from sources on consumer and family, services marketing and social psychology domains, have been followed by a growing number of publications in journals dealing with economic and financial issues and, later, in journals dealing with social/psychological/behavioural issues.

The growth of the articles’ number and the expanding role of psychological journals paved the path for the journey from a domain-specific approach, initially focused on demographic, economic or financial variables, towards an interdisciplinary approach considering the behaviorual and psychological variables and their influence on financial decision. Behavioural topics gradually attracted greater attention, merged with other themes and became a central and developed theme. Education evolved from mere financial knowledge to its application in various, and in some cases “new,” decision-making areas such as the entrepreneurs issues, the digital ones, the ones related to other literacies, the banking ones and, in the very last years, the financial inclusion/access ones. This last theme, highlighted by the growing interest of PVS researchers, is becoming an emergent theme whose borders are gradually broadening to include innovative topics related to entrepreneurs, such as green/environment or sustainability, and digital and technology issues, such as mobile, crypto and peer to peer. Vosviewer detailed node maps on these themes clearly showed the interdisciplinary connections among topics and the proximity of some themes traditionally belonging to different domains.

As for the prospective areas for research, we think that some themes deserve more attention and deeper analysis, such as the links between financial literacy and digital literacy, between financial literacy and entrepreneurs’ issues, and financial literacy links with (and effects on) sustainable development goals and inclusion.