Journal of Behavioral and Experimental Finance: A bibliometric overview

Behavioral science has made a considerable contribution to finance. To gain an understanding of the scientific contributions emerging from all fields of finance with a behavioral perspective, this paper reviews the content of the major journal dedicated to behavioral finance, the Journal of Behavioral and Experimental Finance (JBEF), since its foundation 8 years ago. For this purpose, we employ bibliometrics and content analysis to shed light on the publication trends and intellectual structure of the JBEF, obtaining numerous intriguing findings. First, the JBEF is still a young journal, and its numbers of publications and citations have grown significantly since its inception. Second, though there are contributions from all parts of the world, the United States is acknowledged as contributing the most to the JBEF. Diverse authors have contributed to the journal, but those affiliated with the University of Innsbruck and Macquarie University lead the list. Third, most of the studies have used the theoretical underpinnings of behavioral theory and prospect theory. Methodologically, most of the studies are empirical and primarily based on quantitative research designs, archival data and regression analysis. Fourth, the JBEF’s contributions concern eight intellectual clusters—namely personal characteristics and national cultures; psychological factors, financial literacy and robo-advising; investor sentiment and stock market volatility; asset market experiments; overconfidence and the disposition effects in the stock market; externalities (COVID-19) and financial markets; socially responsible investing; and herding behavior in financial markets. Finally, “behavioral finance” is the most prominently used author keyword in the JBEF’s publications, followed by “financial literacy”. All in all, these findings should offer readers a retrospection of scholarly contributions from the JBEF.


Introduction
The ascent of behavioral finance over the last three decades has been palpable in the area of finance and economics. Several scholars have captured the effects of either rational or irrational facets of human decision making (Hirshleifer, 2015). Nevertheless, a contemporary understanding of the domain of finance requires a grounding in psychological and rational mechanisms. The growth of behavioral finance research has been bolstered by the inability of the traditional models to decipher many empirical trends in fundamental topics such as financial behavior, money management, corporate investment and stock market bubbles (Ritter, 2003). Though finance is an independent field, psychology has primarily driven its growth. Psychology has pointed out various biases that can influence financial decision making. Psychological bias is a distinctive element in the paradigm of behavioral finance.
Thus, behavioral finance has grown out of its infancy and is now widely recognized as a core discipline in mainstream finance. A robust novel trend in behavioral economics and finance has been to carry out laboratory and field experiments similar to the decision context assumed in the financial model. Indeed, the investigation of imperfect rationality and its effects, such as noise trading or sentiment, is nothing but the scrutiny of human beings' psyche, which sheds light on the meaningful contributions of psychology to finance. Such contributions are most apparent in journals committed to the knowledge dissemination of behavioral finance.
The Journal of Behavioral and Experimental Finance (JBEF) is a prominent interdisciplinary peer-reviewed journal with a focus on the rapid dissemination of high-impact research in the area of behavioral finance and experimental finance. The JBEF epitomizes how we can view financial decision making. It is a leading outlet that usually covers investigations of biases, the role of various neurological markers in financial decision making, the impact on financial decision making of the national and organizational culture, sentiment and asset pricing, the design and implementation of experiments to investigate financial decision making and trading, methodological experiments and natural experiments. It also encourages the innovative ideas of young minds in finance research informed by psychology. Since commencing publication in 2014, the JBEF has progressed as a well-recognized and prominent outlet for groundbreaking research in behavioral and experimental finance.
The JBEF ranks high on discipline-based journal ranking lists (JRLs), with a rank of "A" in the Australian Business Deans Council (ABDC) JRL 2019 and a rating of "1" in the Chartered Association of Business Schools (CABS) Academic Journal Guide (AJG) 2018. An "A" ranking is the second-highest quality ranking, applying to 15 to 20% of business and management journals. According to Scopus, the JBEFʼs CiteScore is 3.0, meaning that its articles published between 2017 and 2020 received, on average, 3.0 citations.
As the field gained momentum and the journal progressed, researchers' natural curiosity has prompted them to investigate periodically the scholarly trends of the journal and its intellectual structure (García-Lillo et al., 2019). Retrospective studies using available data can provide state-of-the-art knowledge in the research field (Chan et al., 2009;Martínez-López et al., 2018). There have been numerous attempts to offer systematic retrospections, generally using bibliometrics (Baker, Kumar, Goyal and Sharma, 2021;Donthu, Kumar, Mukherjee, Pandey and Lim, 2021;Donthu, Kumar, Pattnaik and Lim, 2021;Kumar, Pandey, Burton and Sureka, 2021;Mukherjee et al, 2022;Rialp et al., 2019).
A retrospect of one journal in the field of behavioral finance, the Journal of Behavioral Finance (JBF), provides a snapshot of the behavioral finance field (Calma, 2019). The JBEF is close to the JBF as both journals publish research on behavioral finance. Although both are fairly new journals, it is noteworthy that, while they deal with similar topics, they are dissimilar.
This increases the need for retrospection on the variety of research undertaken in this area.
Against this backdrop, we conduct a retrospective review of the JBEF, with the intention of mapping its scientific work and bringing to light the most promising avenues for behavioral finance research. To the best of our knowledge, this is the first comprehensive review mapping the overall knowledge structure of the JBEF to date. Based on a pool of 441 documents published between 2014 and 2021, we conducted a bibliometric analysis coupled with a manual content analysis (Donthu, Kumar, Pandey, Pandey and Mishra, 2021b) to gain a comprehensive insight into the JBEF's scientific performance to date while also unfolding its knowledge structure. To this end, we shed light on its publication trends, the major theories used, the intellectual structure, prominent studies, the authorship network and important keywords. In sum, our primary goal is to provide a review of the JBEF between 2014 and 2021. This fundamentally descriptive study focuses on the journal's progression, current standing and trajectory. Thus, we base our inquiry on the following research questions (RQs), which will be approached through bibliometrics and manual content analysis: RQ1. What are the publication trends over time, citation records and authorship patterns in the JBEF?
RQ2. What are the major theories, sample countries/regions and research methodologies employed in JBEF studies? RQ3. What is the intellectual structure of the JBEF?
RQ4. What are the JBEF's prominent research topics based on keywords?
Hence, our study contributes to the literature in the multiple ways. First, this bibliometric analysis is supplemented by content analysis which is a value adding aspect of this study and offers insights into prominent theories and methodologies for research on behavioral and experimental finance. Further, it identifies the JBEF's publication, citation and authorship records between 2014 and 2021. Knowledge of such trends can be pivotal in discerning the overall research portrait of behavioral finance. We find that the JBEF, a young journal, had published 441 articles by 2021, signaling a high growth trajectory in the years to come. Its citations have also increased substantially over time. Identifying the topics and trends may provide scholars with an insight into the domain of behavioral finance microscopically and target the JBEF as a publication outlet. In this review, we analyze publications, collaboration, and thematic patterns over time, which provide additional insights into JBEFʼs growth. The JBEF is one of emerging journals in the field of behavioral finance and is one of few journals that stand at the confluence of finance and behavioral science research areas. This uniquely positions the JBEF to influence the research in many areas of finance and economics, psychology, management, and behavioral science, among others.
The remainder of this article is structured as follows. We begin with a description of the publication trends in the JBEF, its citation records and its authorship patterns, followed by an assessment of the major theories and research methodologies applied in JBEF articles.
Subsequently, we highlight the intellectual themes based on the clusters of scholarly work of the JBEF. Next, we delineate the crucial topics of interest based on the keywords used in JBEF literature. Finally, we conclude the study.

Data identification and retrieval
We retrieved the metadata for this study from Scopus, a voluminous pool of peer-reviewed research data for quantitative analysis (Baker, Kumar, Goyal and Sharma, 2021;Bartol et al., 2014;Donthu, Kumar, Mukherjee et al., 2021;Donthu, Kumar, Pattnaik and Lim, 2021;Norris and Oppenheim, 2007). There has been ample discussion comparing the suitability of different platforms, such as Scopus, Web of Science and Google Scholar, for carrying out bibliometric analysis (Franceschet, 2010;Levine-Clark and Gil, 2008). Of course, each platform has its advantage. Following a rule of thumb, all the platforms should be used, but doing so would demand huge data cleaning and merging of all the databases .
There are several reasons for our choice of Scopus over Web of Science and Google Scholar as our database source. First, the breadth of coverage in Scopus is relatively greater, with citation data on over 15,000 peer-reviewed titles (Levine-Clark and Gil, 2008). Second, Scopus allows a more extensive investigation than Google Scholar. For example, Google Scholar offers limited bibliometric information execution of the bibliometric study. Third, several bibliometric studies have used Scopus as their data source (Baker, Kumar and Pandey, 2021;Baker, Kumar and Pandey, 2021a;Kumar, Lim, Pandey and Westland, 2021;Kumar, Marrone, Liu and Pandey, 2020).
We searched for the "Journal of Behavioral and Experimental Finance" using source title Scopus in December 2021, identifying 453 documents published between 2014 and 2021.
Including only articles and reviews reduced the final number of JBEF documents used for our analysis to 441. We typically refer to these documents as articles throughout the paper.

Methods of study
Bibliometric analysis has captured the attention of scholars recently (Donthu, Kumar, Pandey, Pandey and Mishra, 2021;Donthu, Kumar, Pattnaik and Campagna, 2020;Kumar, Lim, Pandey and Westland, 2021). Such attention can be attributed first to its ability to handle a vast amount of data and second to its suitability for various types of software, such as Gephi and VOSviewer, and different data sources, such as Scopus and Web of Science. Researchers use bibliometric analysis to unfold the current trends of a journal or a topic, its authorship patterns and its citation trends and to portray the intellectual structure of a specific field (Donthu, Kumar, Mukherjee, Pandey and Lim, 2021;Donthu, Kumar, Pattnaik and Lim, 2021).
Bibliometrics uses statistical techniques to investigate the scientific contributions in books, articles and other publications (Pritchard, 1969). The bibliometric methodology helps in investigating the performance of a research field (Cobo et al., 2011;Ramos-Rodríguez and Ruíz-Navarro, 2004), undertaking a retrospective review of a journal's literature (Baker, Kumar and Pandey, 2021;Donthu, Kumar, Pattnaik and Lim, 2021;Kumar et al., 2022;Mukherjee et al., 2021 andViglia, Kumar, Pandey andJoshi, 2022) and presenting the state of the art of specific research topics (Goodell et al., 2021;Mukherjee et al., 2022;Sureka et al, 2022). This study employed bibliometrics to determine the publication trends, citation records, co-authorship patterns, intellectual structure and keyword network (Hoffman and Holbrook, 1993;Martínez-López et al., 2018). Bibliometric analysis was performed on 441 articles, enabling us to identify their publication trends, citation records, most influential articles, authorship patterns, intellectual thematic clusters and main keywords.
The nature of literary work can be ascertained through the thematic map, and an analysis of intellectual structure can exhibit studies' referencing patterns (Donthu, Kumar, Mukherjee, Pandey and Lim, 2021;Donthu, Kumar, Pattnaik and Lim, 2021). Therefore, we applied bibliographic coupling (Kessler, 1963), using VOSviewer and Gephi applications (Baker, Kumar and Pandey, 2021a;Donthu, Kumar, Pattnaik and Campagna, 2020), to establish the magnitude of intellectual connections among cited documents based on the degree of their common references (Kessler, 1963). Bibliographic coupling relies on associations or overlaps between the cited documents. Additionally, we conducted keyword analysis to map the main author keywords present in the JBEF's literature and the most significant group of keywords within the network. We used VOSviewer and Gephi applications for this purpose.
In addition to examining the intellectual structure and keyword networks, we performed a co-authorship analysis to highlight co-authorship trends in the JBEF (Baker, Kumar, Goyal and Sharma, 2021). We discerned the authors who had contributed most frequently to the JBEF. Measuring the collaboration among researchers indicates the scientific association (Cisneros et al., 2018;. We used the VOSviewer and Gephi applications for this purpose (Baker, Kumar and Pandey, 2021;Donthu, Kumar, Pattnaik and Campagna, 2020;Donthu, Kumar, Pattnaik and Lim, 2021).
Further, we complemented the bibliometric analysis with manual content analysis to synthesize the literature available in the JBEF. An exploration of the theoretical nuances in behavioral finance and the methodological nature of the scholarly work published in the JBEF was not possible using bibliometrics. Following Donthu, Kumar, Pandey, Pandey and Mishra's (2021) approach, the classification of literature based on the sample and methodology was performed using manual content analysis. Accordingly, the authors reviewed each article to find the theories, the country of the sample and the research methodology used, identifying the research methodology (empirical, literature review/conceptual, field experiments and laboratory experiments), research design (qualitative, quantitative and mixed), data collection methods (case study, survey, archival, etc.) and data analysis method (descriptive, correlation, regression, etc.).

Citation record
Secondly, our first research question (RQ1) pertains to the citation records and the most influential articles of the JBEF. Table 1  [Insert Table 2 here]

Authorship trends
Our first research question (RQ1) also concerns the authorship trends in the JBEF. Table 3 shows the authors with the most JBEF publications between 2014 and 2021. Andreas Hellmann has the most publications, with seven, Kelmara Mendes Vieira has six, and Kiridaran Kanagaretnam has five. An exciting finding from Table 3 Table 3 reveals that the JBEF has attracted some authors whose work has gained influence over time. Table 3 here] Table 4 presents the institutions most affiliated with JBEF authors between 2014 and 2021. Authors from the University of Innsbruck have the most publications (13), followed by authors from Macquarie University (12) and York University (7). Authors affiliated with the University of Innsbruck also have the most citations (497), followed by authors from Linköping University (111) and Tilburg University (80).

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[Insert Table 4 here] Table 5 presents a list of countries with which JBEF authors are most often affiliated between 2014 and 2021. US-affiliated authors have the most publications (91) and citations (392). Germany follows, with 48 and 205, respectively. As Table 4 shows, however, the top institution with which JBEF authors are affiliated, namely the University of Innsbruck, is not from the United States. Nevertheless, many top institutions are from the US. This finding suggests that the US-affiliated authors come from many institutions, not just a few. Other prominent countries associated with JBEF authors are Australia, China and the UK. Thus, USaffiliated authors dominate those from other countries regarding publications and citations.
Therefore, Table 5 suggests that the JBEF welcomes contributions from authors around the globe.
[Insert Table 5  represents the degree of co-authorship (Baker, Kumar, Goyal and Sharma, 2021). Although many prominent JBEF authors are visible in the network, they are not necessarily the most frequent contributors. Thus, an author's number of JBEF publications may not always imply the author's importance in the collaboration network. As Fig. 2 illustrates, however, based on node size, Andreas Hellmann is one of the network's most influential authors and most frequent contributors. Conversely, Mei Wang appears to be just as influential as Andreas Hellmann in the network but has fewer JBEF publications.

[Insert Fig. 2 here]
The co-authorship network provides an understanding of the collaboration dynamics of what some researchers have referred to as "invisible collages" (Crane, 1969). A visual collage refers to the networks established when authors combine their intellectual attributes with quality work. Fig. 2 shows that an author's prominence within the network does not necessarily rest on that person's productivity but instead relies on the person's ability to collaborate with other authors. The thickness of the edges represents the link strength between individual JBEF authors. The network also shows that Kelmara Mendes Vieira and Ani Caroline Grigion Potrich have worked together more frequently than others in the network, as have Gustav Tinghög and Daniel Västfjäll.

JBEF
Our second research question (RQ2) deals with the contextual characteristics of JBEF literature. To delve into the scholarly work of the JBEF to identify its significant characteristics in terms of the theories used, the countries/regions from which samples are taken and the research methodology employed, we reviewed each study through manual content analysis.

Theoretical perspectives adopted
Throwing light on the various theories applied and tested in a particular research domain may be helpful in creating new contextual theories or extending the current theories (Whetten, 1989). Table 6 lists the theories that have been applied, though the list is inexhaustive. Instead, it provides a snapshot of the significant theories that can be traced to the extant studies. Our content analysis of 441 studies shows that authors have applied diverse theories to build a ground for empirical inquiry in the field of behavioral and experimental finance. Behavioral and behavioral finance theories are the most prominent, having been applied in 121 research papers; these are followed by prospect theory, which was used in 62 papers. The theory of behaviorism or behavioral psychology aims to explain human behavior by investigating the antecedents and consequences present in one's environment and the learned connections that one has acquired through experience (Angell, 2013). It is a theory of learning that states that all behaviors are learned through interaction with the environment through conditioning. Thus, behavior is simply a response to environmental stimuli. This theory, to a large extent, explains investment behavior (Bouteska, 2019), risk preferences (Ranganathan and Lejarraga, 2021), herding behavior (Babalos et al., 2015), stock market volatility (Bash and Alsaifi, 2019), financial behavior (Strömbäck et al., 2017) and financial market behavior, particularly during the outbreak of COVID-19 (Haroon and Rizvi, 2020). Several scholars have used experimental approaches to investigate differences in individuals' financial behavior and their response to financial literacy (Hermansson and Jonsson, 2021). Thus, our study provides a synthesis of academic events that substantiate the presence of behavioral biases, their underlying psychology and their effect on financial markets and financial behavior.
Experimental evidence has suggested that individuals do not obey the expected utility axioms (Tversky and Kahneman, 1974). Prospect theory is based on a two-level choice process: framing and valuation. In the framing phase, the decision maker constructs a representation of the acts, uncertainties and outcomes relevant to the decision. In the valuation phase, the decision maker assesses the value of each prospect and chooses accordingly. Best and Grauer (2016) explored the relationship between prospect theory and portfolio selection.
Prospect theory also explains the preference for gold over risk-free assets (Baur and McDermott, 2016). The novel coronavirus disease (COVID-19) rapidly evolved from a health crisis into a global financial meltdown. In this regard, prospect theory could investigate the impact of this colossal health crisis on major stock markets and commodity markets to gain a better understanding of investors' responses (Ali et al., 2020).
Another emerging theory found in the literature of the JBEF is a standard economic theory. It is based on the assumption that consumers make decisions rationally and aim to maximize their utility. A rational person will know what is best for them (selfish motive) and will not be influenced by emotions or other external factors while making a decision (Neurath, 1987). Various studies have tested the theoretical framework based on economic theory relating to asset markets , household investment behavior (Fajardo and Dantas, 2018) and betting behavior (Buhagiar et al., 2018). Our findings also reveal that the most prominent theories draw their intellectual roots from the allied fields of behavioral science, psychology, economics and finance, and sociology.

Sample country/region
The analysis revealed that, of the total number of studies under review (n=441), 296 studies derived their samples from single countries. Furthermore, 67 studies were based on data collected from multiple countries, and 78 were not country-specific (see Table 7), meaning that the studies were either purely conceptual or reviews or did not use a country-specific sample.
After delving further into the geographical location of the sample used in each study (n=441), it was found that most of the studies were conducted in the American region (n=112) followed by the European region (n=93) and the Asian region (n=79). This finding also indicates that the research in behavioral finance is slightly skewed toward developed countries, like the US and the United Kingdom (UK). Less attention has been paid to Asia, Australia and Africa. The results highlight the need to study behavioral finance in developed and developing economies as the subject holds importance across the globe.

Types of research methods applied in the JBEF corpus
To perform the manual segregation of studies based on their research methodology, we used a similar classification approach to that adopted by . This section manually classifies the studies according to the research method, research design, data collection method and data analysis approach (Table 8). Appendix 1 offers the definitions of these classifications.
Of the 441 studies in our sample, 402 are empirical and 39 are conceptual or reviews.
This finding reveals that the preference has been given to empirical work that uses field data, qualitative and quantitative surveys and other evidence-based data types. Behavioral finance research has primarily focused on empirical evidence showing how real humans behave (Illiashenko, 2017). Extant theoretical works have revealed that isolated behavioral bias could result from an interplay of different factors (Nickerson, 1998). Some biases are not unitary but represent a collection of different effects and vice versa. Despite most empirical studies focusing on one behavioral phenomenon or a small population sample, there is growing evidence that certain groups of individuals are more prone to exhibit behavioral biases than others. This is the probable reason for researchers' increasing interest in conducting empirical studies. Of 402 empirical studies, 364 used quantitative research designs, 36 used qualitative methods and two adopted a mixed-method approach (qualitative and quantitative methods).
We note the dearth of conceptual studies and reviews in the JBEF corpus.
Through further comprehensive analysis, we found that most empirical studies drew on archival data (n=202), followed by laboratory experimentation (n=93) and survey data (n=57).
Considering the primary focus on quantitative, rather than qualitative, research designs, it is recommended that more qualitative studies are carried out based on primary data to understand the paradigm of behavioral finance.
Classifying articles according to data analysis approaches, we found that regression [Insert Table 8 here]

Intellectual structure of the JBEF
We proceed to our next research question (RQ3), which is pertinent to mapping the intellectual structure of the JBEF. In addition to investigating data concerning influential JBEF studies, we explored their prominent themes by applying the bibliographic coupling proposed by Kessler (1963). Using VOSviewer and Gephi tools, we segregated the JBEF themes into thematic clusters. In a network, nodes can be segregated into clusters in which the weight of edges is greater between the nodes in a cluster than those of other clusters (Leydesdorff, 2017). The articles in the same cluster share a common theme and differ from articles in other clusters.
Clustering enables a thematic analysis of the network (Xu et al., 2018). The most cited work in this cluster is by Gonzalez and Loureiro (2014), who explored the effects of lender and borrower personal characteristics (perceived attractiveness, age and gender) on online peer-to-peer lending decisions. Baur and McDermott (2016) argued that the decision to buy gold is rooted in behavioral biases linked with gold's history as a currency, a store of value and a haven. Zheng and Ashraf (2014) provided empirical evidence that banks in countries with high uncertainty avoidance, high long-term orientation and low masculinity pay lower dividends and are less likely to pay dividends. The fourth most cited article is by Aggarwal and Goodell (2014) and pointed to an important gap in the literature in that both the accounting and the finance field make limited use of cultural dimensions in scholarship. It is followed by Nawrocki and Viole's (2014) study, which reviewed behavioral finance's consistent role in portfolio theory and market theory through utility theory.

Cluster 2: Psychological factors, financial literacy and robo-advising
This cluster contains 72 articles, which have been cited 404 times. These studies have primarily focused on the effects of behavioral factors such as self-control, materialism, risk perception, money values and financial literacy on financial behavior and financial well-being. The authors have mainly explored the gender differences in financial literacy. Another prominent theme of this cluster is the role of robo-advising and fin-tech in enhancing consumers' financial literacy.
A highly cited article in this cluster is that of Strömbäck et al. (2017), which explored differences in self-control and other non-cognitive factors in financial behavior and financial well-being. Following this are the articles by Potrich et al. (2018), which analyzed the gender differences in financial literacy and found that the proportion of men is larger among those with a high level of financial literacy, and Potrich et al. (2015), which developed a model to measure financial literacy and compared the level of financial literacy among genders. The fourth most cited study in the cluster is by , who offered an in-depth understanding of the ability of robo-advising to mitigate behavioral biases from the perspective of experts. This study is followed by , who investigated whether robo-advisors reduce investors' demand for human financial advice offered by financial service providers.

Cluster 3: Investor sentiment and stock market volatility
This cluster contains 67 articles with 378 citations to date. The articles in this cluster have primarily focused on the influence of investor sentiment on stock market volatility. The authors have explored the momentum effects on the stock market, the influence of worship intensity in the form of a holy day on stock market returns and the Friday the 13th effect on stock returns.
The most highly cited article in this cluster is by Bukovina (2016), who investigated whether investors' sentiment or the public mood in social media influences asset pricing and capital market volatility. Following this is  article, which probed the influence of investor sentiment, like noise traders' pessimism, on the predictability of Indian stock market volatility. Hudson and Green (2015) explored sentiment's tendency to be a more significant factor determining returns in the run-up to a crisis than at other times. The fourth most cited article in the cluster is that by Al-Ississ (2015), which used Muslim holy days to explore the underlying mechanism behind the holiday effect. Following it is the study by , which investigated whether market-wide measures of investor sentiment and arbitrage constraints affect the performance of cross-country stock market anomalies.

Cluster 4: Asset market experiments
This cluster comprises 67 articles with 955 citations. The articles in this cluster delved into the literature on online software like oTree, used for implementing interactive experiments, or Prolific.ac, as a platform for online experiments. The cluster also includes reviews based on asset market experiments.
The most frequently cited article in this cluster is by , who presented www.prolific.ac and discussed its suitability for recruiting subjects for social and economic science experiments. Following this is Chen et al.'s (2016) article, which discussed the usefulness of oTree as open-source and online software for implementing interactive experiments in a laboratory, and  study results from an asset market experiment, in which they inquired into the relationship between traders' risk aversion, loss aversion and cognitive ability and their trading behavior and market outcomes. The fourth most cited article in this cluster is by , who reviewed the latest research on experimental asset markets, and this is followed by , who used the concept of numeraire independence to identify a unique measure of mispricing.

Cluster 5: Overconfidence and the disposition effects in the stock market
This cluster consists of 58 articles with 235 citations and focuses on the relationship between investors' confidence and trading, overconfidence among individual stock investors and the investor's disposition effect.
The most often cited article in this cluster is the article by , which revealed that more confident investors change their beliefs more firmly, providing more reason to trade. Following this is Tekçe and Yilmaz's (2015) article, which investigated how common overconfidence is, which factors affect overconfidence and how overconfidence relates to investor return performance, and the study by , who conducted an experiment and suggested that the risk attitude in losses, together with wishful thinking and misperception of the price process, such as gambler's fallacy, may contribute to the observed disposition effect. The fourth most cited article is the article by , which examined prospect theory portfolios in asset allocation settings that include risk-free lending and borrowing, subject to margin constraints, and short-sales restrictions on risky assets. Aspara and Hoffmann (2015) follow it; their article tested the role of factors related to personal responsibility in reversing individuals' susceptibility to the disposition effect.

Cluster 6: Externalities (COVID-19) and financial markets
This cluster contains 46 articles with 1107 citations, making it the most influential theme. The articles in this cluster focused on the impact of coronavirus (COVID-19) on stock market returns.
Al-Awadhi et al.'s (2020) article, which investigated the impact of contagious infectious diseases on the Chinese stock market, is the most often cited article in this cluster. This is followed by Ali et al.'s (2020) article, which examined the reaction of financial markets worldwide in terms of their decline and volatility as the coronavirus epicenter moved from China to Europe and then to the US, and Haroon and Rizvi's (2020) article, which analyzed the relationship between the sentiment generated by coronavirus-related news through media coverage and the volatility of equity markets. The fourth most cited article is that of Ashraf (2020), which examined the expected economic impact of government actions by analyzing the effect on stock market returns. Next is Salisu's (2020) article, which considered the global fear index (GFI) for the COVID-19 pandemic to investigate its predictive power in predicting commodity price returns during the pandemic.

Cluster 7: Socially responsible investing
This cluster consists of 27 articles with 191 citations and focuses on the effects of social preferences on investment behavior and decision making and the relevance of the theory of planned behavior to investment intentions.
The most often cited article in this cluster is that by Borgers and Pownall (2014), which investigated the variation in attitudes toward proposed social investment. They found that individuals have difficulties making financial decisions while simultaneously taking their non-financial preferences into account. Following this is Warsame and Ireri's (2016) article, which explored the significance of the theory of planned behavior and revealed that attitude has a significant and positive effect on the behavioral intention relating to investment decisions, and Warsame and Ireri's (2018) article, which aimed to investigate the impact of M-Shwari financial services on small-scale traders in Kenya and concluded that the interaction between behavioral intention, age and gender influences the use of M-Shwari loan services. The fourth most cited article is the article by Apostolakis et al. (2016), which examined the linkage between attitudes toward impact and socially responsible investments and willingness to pay for socially responsible choices. The article by Königstorfer and Thalmann (2020) follows it; this article reviewed the applications of artificial intelligence (AI) in commercial banks and the challenges of implementing AI.

Cluster 8: Herding behavior in financial markets
In this cluster, there are 22 articles with 178 citations. These articles focus on the herding behavior and contagion in the cryptocurrency market and the real estate and equity markets.
The most often cited article in this cluster is the article by da Gama Silva (2019), who investigated herding behavior and contagion phenomena in the cryptocurrency market.
Following this is Babalos et al.'s (2016) article, which provided novel evidence on the herding behavior of US-listed real estate investment trusts (REITs) and revealed a shift from negative herding behavior during low-and high-volatility regimes to positive herding behavior under the crash regime for almost all REITs sectors, and Stavroyiannis and Babalos's (2019) article, which offered new insights into the herding behavior of cryptocurrencies and identified the asymmetric nature of cryptocurrencies' returns due to such behavior. The fourth most cited article is by Vo and Phan (2017), who provided evidence of herding behavior in the Vietnamese stock market. The article by Youssef and Mokni (2018) follows it; this article tested whether herding behavior affects the dependence structure between stock markets and found a negative effect in low herding regimes and a positive effect in high herding periods.

Thematic progression of the JBEF based on keyword analysis
Our last research question (RQ4) deals with the thematic progression of the JBEF based on keywords used in the extant literature between 2014 and 2021. We conducted keyword cooccurrence analysis for this purpose with the help of the VOSviewer and Gephi software.
Author keywords signify the intellectual topics in scholarly studies (Strozzi et al., 2017). Such an analysis can appropriately explore the themes, structures and development of research fields (Callon et al., 1983) by mapping the co-occurrence of keywords to examine the content of an article. Table 10 presents the most frequently used keywords between 2014 and 2021. Fig. 6 presents a graphical visualization of JBEF author keywords between 1993 and 2020 to delineate the journal's research topics based on the interconnectedness between the articles.
During the first 8 years of the JBEF's journey, the article keyword used the most frequently was "behavioral finance." This finding is in line with the aim and scope of the journal to publish scientific works on behavioral finance. The next most frequently used keyword is "financial literacy." The centrality of financial literacy in rational decision making is justified (Rodrigues et al., 2019). New theoretical approaches to behavioral finance are changing the conceptual understanding and the subject area of financial literacy (Loerwald and Stemmann, 2016). Therefore, there is an emerging body of literature on the consequences of current behavioral finance research for financial education. The third most often used keyword is "COVID-19". The COVID-19 pandemic vastly disrupted financial markets and the real economy worldwide. Recognizing the unprecedented nature of the shock, the academic community has produced an impressive amount of research during the last year (Djalilov and Ülkü, 2021;Goldstein et al., 2021). Researchers have widely examined the impact of the pandemic on stock markets (Al-Awadhi et al., 2020), financial behavior and financial well-being (Barrafrem et al., 2021) and the suddenly increased adoption of Fin-tech in the era of COVID-19 (Daragmeh et al., 2021). Another primary keyword used in the JBEF's articles is "behavioral biases", which are a distinctive feature of behavioral finance. Behavioral finance refers to the application of psychology to finance, focusing on individual-level cognitive biases (Hirshleifer, 2015). Next, "experiment" is a frequently used keyword by the authors of articles published in the JBEF. Since it is an experimental finance journal, it publishes a wide array of experiment-based research . The emerging themes in the JBEF based on author keywords are overconfidence, disposition effect, stock market returns and so on.
As shown in Fig. 6, which provides a visualization of the connectedness between the keywords (themes), the most prominent link exists between "oTree" and "experimental economics". oTree has been discussed as an essential online platform for experimentation . Thus, behavioral and experimental finance takes advantage of insights from varied research fields.

Discussion and conclusion
In 2021, the JBEF completed its eighth year of publication. The current study aimed to analyze the progression of the JBEF as an essential outlet for behavioral finance scholarship. During its journey, the JBEF, though young, has shaped itself into one of the foremost journals in behavioral and experimental finance. We employed bibliometric analysis and manual content analysis to analyze the JBEF.
Our study contributes to the literature in the following ways. First, it identifies the JBEF's publication, citation and authorship records between 2014 and 2021. Knowledge of such trends can be pivotal in discerning the overall research portrait of behavioral finance. We find that the JBEF, a young journal, had published 441 articles by 2021, which signals a high growth trajectory in the years to come. Its citations have also increased substantially over time.
We further identified the most influential JBEF articles and the most prominent contributing authors. US authors are its most frequent contributors. Various authors have contributed to the journal, but those affiliated with the University of Innsbruck and Macquarie University lead the list. Second, we distinguished the significant theories applied in JBEF articles. We found that the majority of the studies have used the theoretical underpinnings of behavioral theory and prospect theory. Based on the sample, the majority of the studies have been conducted in the context of a single country, and most of the samples have been taken from the US. While delving into the research methodology of each of the JBEF's published articles, we observed that most of the studies were empirical and primarily based on quantitative research designs, archival data and regression analysis. Third, we determined the intellectual structure of the JBEF. We concluded that the main themes of interest among the JBEF's contributors are (1) the role of personal characteristics and national cultural dimensions in behavioral finance scholarship; (2) the role of psychological factors, financial literacy and robo-advising in financial behavior; (3) investor sentiment and stock market volatility; (4) asset market experiments; (5) overconfidence and the disposition effect in the stock market; (6) the impact of COVID-19 on financial markets; (7) attitudes toward socially responsible investment; and (8) herding behavior in financial markets. Finally, we identified the primary keywords used in JBEF articles based on keyword analysis. We found that behavioral finance is the most prominently used author keyword in the JBEF's publications, followed by financial literacy. RQ1 focused on the publication trends in the JBEF during the last three decades. We discovered that the journal has made impressive progress in terms of publications and has received publications from all over the world. RQ1 also explored the citation record of the JBEF and the most influential studies based on citations. The most impactful study discussed the advantages and challenges of online experiments and advocated the suitability of www.prolific.ac for the requirements of social and economic science experiments. Dealing with the authorship trends in the JBEF, we discovered that, although significant contributions have come from the US, the shares of UK and Asian authors have also seen modest growth over the years. The collaboration culture has seen a progressive trend over the years across the globe. The research also showed that pairs of authors have frequently authored IBR articles together. Among the countries represented, the US, China and Australia have collaborated most often to contribute authorship to the journal. RQ4 dealt with the JBEF research topics based on the keywords used by authors in the JBEF articles. There are various topics of JBEF scholarship, as signaled by our keyword analysis. While "behavioral finance" was the most prominent topic of JBEF research from 2014 to 2021, "financial literacy" and "COVID-19" are other topics that are significantly visible. Nonetheless, the JBEF has produced emerging topics that add to its novelty in contributions with each passing year.

Contributions of the study
Our comprehensive bibliometric analysis contributes to the scholarship in multiple ways. First, we carried out a retrospective analysis of the journal. This could help the editorial team to track the journal's productivity. The mapping analysis of the journal's performance may aid the editorial team in discovering ideas for the journal's global expansion. Studying the methodologies and theories used in journal articles may assist the editorial board in diversifying the issues on which the journal publishes contributions. The authorship analysis showed that the journal has been expanding toward greater collaboration. As the JBEF is one of the leading journals in its domain, these results may apply to the entire field. Future researchers can explore this question. Moreover, the article's contribution lies in its analysis of central themes and the journal's development regarding the research topics covered. Future behavioral finance scholars will be able to identify the current issues and receive guidance on the way forward in their research.
Through the thematic analysis, we recommend the direction of future research in JBEF.
First, the field of cultural finance has already made a significant contribution (Aggarwal and Goodell, 2014). This is evidenced by the number of cultural-finance-related papers published in international business publications. However, cultural finance is now prepared to launch fresh groundbreaking investigations. We conclude that by exposing and supporting the relevance of national culture in finance research, the Journal of Behavioral and experimental finance can play an essential role in financial research. Second, when examining economic theories, researchers are frequently confronted with a large quantity of behavioral heterogeneity. The purpose of behavioral and experimental economics is to better understand human behavior via observation so that economic theories can be improved (Strömbäck et al., 2017). One method to handle this heterogeneity is to realize that decision makers differ fundamentally from one another, and that these differences contribute to observable financial behavior differences. Therefore, future research must be directed towards understanding differences in behavior. Behavioral finance theories also bring other intriguing topics for further research where individual investor behavior is evident or societal opinion can influence institutional investors (. Initial public offerings, mergers and acquisitions, or the consequences of social connections on investing (e.g., herding behavior) are examples of issues where sentiment is inherent and social media big data can be a valuable source of information (Bukovina, 2016). More research is also needed to identify the underlying mechanism explaining the relationship between investor confidence and trading . As keyword analysis suggests, the emerging topics of research are "financial crisis", "financial knowledge", "financial well-being", "stock markets", etc. Thus, future researchers may focus on such topics as well.

Limitations
Like all other studies, our study is not free from limitations. The first limitation is related to the source of data extraction. This study retrieved its data only from Scopus, making the source data susceptible to errors. However, we tried to minimize the mistakes through data cleaning, but mistakes that are inbuilt in the source could still have affected the study to some extent. It is suggested that future researchers use multiple databases to retrieve data for their studies.
Moreover, while we have analyzed methodologies and theories, there is still room for further theme-based systematic literature reviews and topic-based bibliometric reviews to gain a better understanding of each behavioral and experimental finance topic separately and independently.       and 2021. TP = total publications, CTP = cumulative total of publications, TCP = total cited publications, TC = total citations, TC/ CTP = total cites per publication, TC/TCP = total cites per cited publication. The total cited publications and the citations are for a given year.   Notes. This table reports the top institutions affiliated with JBEF authors. TP = total publications, TCP = total cited publications, TC = total citations, TC/TP = total cites per publication, TC/TCP = total cites per cited publication. 12.00 Notes. This table reports countries most often affiliated with JBEF authors between 2014 and 2021. TP = total publications, TCP = total cited publications, TC = total citations, TC/TP = total cites per publication, TC/TCP = total cites per cited publication. The sum of citations in the table is greater than shown in Table 1. When authors of co-authored articles have affiliations with more than one country, each country receives a citation.