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Businesses increasingly rely on online platforms to engage with their customers, comprehending the nuances of the digital customer journey (DCJ) becomes paramount for developing effective marketing strategies. This research aims to investigate the trends and themes in the DCJ literature from 2009 to 2024 through a bibliometric approach. This study seeks to provide insights into the evolution of research in this domain and the implications of emerging trends for practitioners and scholars alike. The theoretical foundations of this research are anchored in the interplay between consumer behavior theories and the advancements in ICT. A total of 1,275 articles were retrieved from the Scopus citation database, following the PRISMA protocol to ensure a rigorous selection process. After applying inclusion and exclusion criteria, 462 relevant articles authored by 1,429 individuals across 261 sources were identified for analysis. The study utilized VOSViewer and R Studio, to conduct a comprehensive analysis of publication trends, citation networks, and co-authorship patterns. The findings reveal several prominent themes, including the impact of mobile technology on customer engagement, the role of personalization in enhancing user experience, and the significance of social media interactions in shaping consumer perceptions. Additionally, the study identifies key authors and institutions that have contributed notably to the field, highlighting patterns of collaboration and knowledge dissemination. The evolution of research topics reflects broader technological advancements, indicating a dynamic interaction between academic inquiry and practical marketing applications.The findings underscore the necessity for marketers to adapt their strategies in line with emerging digital trends and consumer behaviors.

This research was conducted with the aim of citation analysis of the achievement of scientific theoretical foundations of articles published in the period from 2000 to 2024 and overview of articles in the period from 2019 to 2024 in the Scopus database on the topic of the global value chain. The present research was conducted using the citation analysis method and the number of 1985 articles that mentioned global value chain in the title, abstract and keyword of the articles were selected from the Scopus database. Also, the number of 20 articles with the term global value chain only in their titles were selected for overview. In this research, the data was extracted from the Scopus database for citation analysis. Database selection is the main and most important part of bibliometric analysis The results of citation analysis show the increasing trend of studies in the field of global value chain. The results of the overview emphasize the change of research directions along with the growing path of global value chains. Also, the concepts gathered in reviewing the articles of the last 5 years in a systematic way can be placed in three major categories: the facilitating role of the government, the fourth industrial revolution, and the company level strategy. This research has tried to familiarize researchers and students with this category and the need to examine its various dimensions by introducing authors, sources, authentic articles and up-to-date topics in this field. The position of Iran with the number of 5 articles in the field of the global value chain and the citation rate of 616 among the selected countries indicates that the researchers of our country can produce more scientific productions by studying the capacities and advantages in the framework of the global value chain.

Medical tourism has considerably developed in recent years. Many patients travel to other countries to receive healthcare services. In this regard, medical tourists’ positive experiences of the services they receive make them loyal to the destination, being influenced by the prestige and reputation of the target destination and the patient’s perceived value of the healthcare centers’ brands. Therefore, as Tehran possesses the most advanced medical centers, including hospitals, clinics, and specialty clinics, this applied descriptive-correlational study sought to investigate the influence of medical tourists’ experience on destination loyalty, taking the intervening role of prestige and perceived value of the target medical centers’ brands into account. To this end, the required data were collected using a researcher-developed questionnaire. The population consisted of medical tourists who visited medical centers in District 1 of Tehran, out of whom 384 individuals were selected through convenience sampling. Finally, the collected data were analyzed via SPSS (Version 25) and Smart pls3 software using the Structural Equation Modeling. The study’s findings indicated that medical tourists’ experience exerted a positive significant influence on the destination’s prestige, perceived value, and loyalty. Moreover, it was found that the loyalty to the destination increased by an increase in medical tourists’ experience. Therefore, the prestige and perceived value of the destination’s medical centers must be greatly attended to.

The aim of the current research is to study the research process around the concept of dynamic capabilities and identify its components in knowledge-based companies, using bibliometric analysis method. Bibliometric analysis provides a critical review to identify the main themes and basic concepts of the subject. The data collection tool is the databases resulting from the search of WOS articles, and the analysis method is bibliometric tools using R. The number of reviewed articles is 2242 published in the period from 1991 to 2023. In the first step, the descriptive statistics of the extracted researches were stated, the growth rate of approximately 15% in this period of time indicates the importance of the research subject from the researchers' point of view. In the next step, the most influential people, works and publications were identified. In order to investigate contemporary trends and research flows in the field of dynamic capabilities, six clusters were obtained based on the clustering method through bibliographic pairing. The results of this clustering showed the centrality of knowledge in all these thought processes. After extracting and clustering the articles, the naming of each cluster was done based on the important parameters of the most frequent keywords of each, which are the seven components of "identifying, interpreting and exploiting opportunities", "creativity, innovation and agility", "leadership", "learning", " Organizational capitals, "adaptability" and "organizational culture" were identified. Stating the two components of "leadership" and "organizational culture" as aspects of dynamic capabilities is one of the innovative aspects of this research.

Innovation in the field of emerging technologies outside the public sector has changed citizens' expectations of governments' ability to provide high-value digital services, and digital transformation has emerged as an important phenomenon in strategic information systems research. In recent years, research on digital transformation and its applications in various fields has expanded, leading to the creation of extensive, diverse, and scattered knowledge in this area. In recent years, digital transformation has been identified as a research priority for managers and researchers in the public and government sectors. The importance of this research area and attention to it in digital government studies has made it necessary to identify its sub-domains and research trends. This study aims to review research in the field of digital transformation in government and public organizations, identify core articles, recognize sub-domains, and research trends.

In recent years, with the expansion of the concept of sustainable development in the life cycle of construction projects and the dynamic and eventful nature of these projects, the issue of sustainable risk management has garnered increasing attention from researchers. However, the lack of systematic reviews and bibliometric analyses of published research in this field has obscured the future perspectives and evolution of this area of study. This study aims to evaluate and synthesize the existing body of literature to identify potential research gaps and delineate the boundaries of knowledge in the risk management of sustainable construction projects (SCPs).

This study is descriptive-analytical and is classified as a systematic review in terms of implementation method. The PRISMA guidelines were adopted for the systematic review of the literature, including descriptive and content analysis. In this process, 1,630 articles published in the Scopus and Web of Science databases from 2015 to 2023 were retrieved and screened, resulting in 113 eligible articles for analysis. To complete the systematic literature review, a bibliometric analysis encompassing co-authorship and keyword co-occurrence analysis was conducted using VOSviewer software for a more comprehensive evaluation of the field of risk management in sustainable construction projects (SCPs).

Regarding the descriptive analysis of the retrieved papers based on the year of publication and their frequency in various journals, it was found that research on risk management in sustainable construction projects (SCPs) has increased in recent years. The content analysis of the articles, based on research themes, indicated that the articles were classified into five main themes: general risks of sustainability, sustainable procurement, supply chain, technology adoption, and human resources. A deeper exploration of the papers revealed that SCPs' risks were primarily categorized into eight dimensions: financial and economic; social; executive, managerial, and organizational; knowledge and skills; governmental and legal; stakeholders/employers; environmental; and technology, equipment, and resources. According to the research methods, experimental and applied research contributions in SCPs' risk management were less prevalent compared to descriptive and review research. This highlights opportunities for conducting applied research that addresses various problems and assumptions. In terms of strategy, a significant number of papers employed the survey method, with some based on case studies. Given that the accuracy and generalizability of survey research results are typically higher than those of case studies, there is a noticeable preference for the survey strategy among researchers. Additionally, researchers often used statistical analysis methods to assess SCPs' risks. According to the bibliometric analysis and the keyword co-occurrence results in the field of SCPs' risk management, it is anticipated that future researchers will focus more on concepts, approaches, and fields such as the circular economy, recycling, risk assessment, factor analysis, leadership in energy and environment, developing countries, and questionnaire surveys.

According to the findings, future articles are expected to focus on completing the puzzle of sustainability risk management systems in sustainable construction projects (SCPs), specifically addressing identification, evaluation, control, and response to risk. This focus should be particularly prominent in developing countries and should be approached through experimental and applied studies utilizing mixed methods and hybrid approaches under uncertainty. Various studies have examined barriers and risks in construction projects from different sustainability perspectives, such as economic, environmental, and social. However, the economic dimension has received more attention from researchers than others, which does not provide a comprehensive assessment of the risks associated with sustainable projects. Such comprehensive studies are crucial for the efficient allocation of resources. The primary contribution of this research to the bibliometric analysis of SCPs' risk management lies in its unique approach to determining the direction of future research.

The objective of this study is to conduct a systematic review and meta-analysis of mutual fund performance evaluation studies, focusing on the historical evolution of performance assessment methods based on fund style.

This research is divided into two main sections. The first section involves a quantitative analysis of prominent ISI-listed studies on mutual fund performance from 1900 to 2023, using bibliometric software such as HistCite™ and VOSviewer. This bibliometric analysis identifies and categorizes key studies based on citation counts. The second section reviews the evolution of mutual fund performance measurement criteria and various approaches used in the literature, critically analyzing the strengths and limitations of these methods.

The bibliometric analysis revealed significant trends in mutual fund performance evaluation, with a clear evolution in methodologies over time. The study identified two primary approaches: asset-based analysis and return-based analysis. Key findings indicate that while both approaches have their merits, asset-based analysis offers a more accurate assessment of managerial skill by considering the composition of the fund’s holdings. Additionally, the analysis highlighted the most cited studies and influential journals in the field, providing a comprehensive overview of the research landscape.

The study concludes that mutual fund performance evaluation has significantly evolved, with increasing complexity and sophistication in methodologies. The findings underscore the importance of selecting appropriate performance measurement criteria based on the specific characteristics of the mutual fund.

The goal of the current research is to study the research process around the concept of leadership and leadership style, using the method of analysis and Scientometrics mapping. This research is descriptive-analytical and has been carried out with a Scientometrics approach. The tool of data collection was the databases resulting from searching and cataloging, and the method of analysis was scientific tools and maps using R software. The number of reviewed articles is 2178 published in the Web of Science database between 1992 and 2022. The extracted articles were classified into six clusters based on the clustering method of bibliographic pairs. The naming of the clusters was done based on the important parameters of the frequent keywords of each, and based on this, clusters one to six, which were sorted based on the average age of the articles, were named "leadership styles based on growth and learning", "leadership styles based on The general roles of the leader", "leadership styles based on power distribution", "leadership styles based on the welfare of followers", "leadership styles based on ethics" and "leadership styles based on unethical pro-organizational behaviors" were named.

Today, we are witnessing the widespread use of artificial intelligence in various fields of marketing. For example, Prime Air Amzon.com uses drones to automate transportation. Domino's Pizza is experimenting with self-driving cars and delivery robots to deliver pizzas to customers' doorsteps. Lexus uses IBM Watson to script its "Intuition Drive" TV commercials. Based on emotional analysis, affective detects the emotions of consumers while watching advertisements. Replica is a chatbot based on machine learning that provides emotional comfort to customers by imitating their communication styles. It has even been claimed that artificial intelligence will fundamentally change the future of marketing. However, academic marketing research to date has not provided sufficient guidance on how best to leverage the benefits of AI for marketing impact. Artificial intelligence systems and programs have become widespread in different industries and different sectors of companies and organizations and have led to close competition between them and have also provided various opportunities for marketing strategy and process. However, research on the application of artificial intelligence in marketing planning has been scattered, and there is a need for a comprehensive research on the past research trend and the future trend of this issue. The current study aims to identify the antecedents and consequences of the application of artificial intelligence in the develop a marketing plan.

This study was conducted with a mixed approach, in the quantitative section by using bibliometric network analysis of existing research background published between 2010 and 2022 and in the qualitative section by using the meta synthesis strategy. A comprehensive review of 115 articles indexed in the Scopus database helped to identify the performance of scientific actors such as the most appropriate authors and the most appropriate sources. In addition, co-authorship and co-occurrence analysis using VOSviewer software suggested a conceptual and rational network. By applying the meta synthesis method to investigate the dimensions of the marketing plan based on artificial intelligence, 59 articles out of 115 indexed articles were analyzed.

According to the results, only one paper was published in 1985 in the field of "Artificial Intelligence and Marketing". Until 2010, when this issue has been gradually noticed by researchers, and the trend of publishing articles from 2010 to 2022 had an upward trend. In 2021, 50 articles have been published, and in 2022, 21 articles have been published until today. Most of the articles related to artificial intelligence and marketing have been published in the Australian Journal of Marketing. To understand the most effective source, 5 of the most suitable sources were compared in terms of H index and SJR index. Journal of Business Research in terms of H index and Journal of Marketing Science Academy in terms of SJR index have the most points and are the most suitable sources. "Liu Wai" won the highest rank among all researchers with 3 articles published in the field of artificial intelligence and marketing. "Liu Wei" has an H-index of 8 and 16 published articles, while "Huang" has an H-index of 75 and 328 published articles, which has more citation records than the rest of the authors. Among the analyzed articles, the highest percentage of studies related to the product/consumer factor (38%) and the lowest The percentage of studies conducted is related to the price/cost factor (14%). Based on the results of the meta synthesis study, it is possible to use mechanical artificial intelligence for standardization, intellectual artificial intelligence for personalization, and emotional artificial intelligence for relationalization. Based on the results, the antecedents of the use of artificial intelligence in developing a marketing plan include technological, organizational, environmental, behavioral and individual factors and the consequences include customer experience, customer journey management, profitability, competitive advantage, customer satisfaction, customer loyalty, customer relationship management and customer engagement.4. Discussion and coclusion: The research findings of the review of all scientific sources conducted from 2010 to 2022 show that so far no comprehensive research has been done for the integration of the Rabazi program stage. Therefore, the most important finding of this research is the review, analysis and classification of the planning phase of artificial intelligence based on metacombination. In this research, 59 articles that directly examined the issue of marketing planning based on artificial intelligence were selected for analysis. The selected studies were coded and finally, 152 distinct primary codes were identified. In the next step, the codes were categorized in the form of 35 concepts or sub-categories, and finally, based on the results of the analysis, concepts in 4 main categories as dimensions of the evaluation program based on artificial intelligence, 5 main categories as antecedents of the evaluation program based on The basis of artificial intelligence and 7 main categories were identified as suffixes of the marketing program based on artificial intelligence, and their quality test was also confirmed. Finally, based on the analysis, a model for the use of artificial intelligence in developing a marketing plan is proposed, which consists of the three dimensions of artificial intelligence, mechanical, intellectual, and emotional, and their benefits include standardization, personalization, and relationship building. It uses marketing mix dimensions.

This study set out to investigate the trend of studies conducted on tourist experience using bibliometric analysis. To this end, the study analyzed 2683 articles published in the Web of Science database from 1980 to 2020 using the VOS Viewer software to visualize and analyze the results. In this regard, two analysis levels were considered. At the first level, the publication trend and the impact factor of authors, journals, and articles were examined. At the second level, the structure of the co-occurrence network of keywords and the co-authorship network of authors, institutions, and countries were analyzed. The findings of the study indicated a significantly growing trend of studies (most of which were published in 2019) conducted on tourism experience in recent years, which is expected to continue to grow in the future. On the other hand, hospitality and leisure, management, and environmental studies were found as the highly researched areas, with most articles being published on tourism experience. Moreover, social media, trust, user opinions, and competitiveness are among the emerging research areas in the relevant literature. In this regard, health tourism, culinary tourism, social experience, shared value creation, authenticity, cultural experience, destination experience, backpackers, information technology, cultural differences, cultural heritage, students’ experiences, sustainable management, and transportation are among the main topics addressed in the literature. On the other hand, the analysis of the authors' co-authorship network revealed that thirty-five research groups are currently working in this field worldwide, with the Hong Kong Polytechnic University exerting the highest influence on the international collaboration network.

Disruptive technologies such as the internet of things, big data analytics, blockchain, and artificial intelligence have changed the ways businesses operate. Of all the disruptive technologies, artificial intelligence (AI) is the lat- est technological disruptor and holds immense marketing transformation potential. Practitioners worldwide are trying to figure out the best fit AI solutions for their marketing functions. However, a systematic literature review can highlight the importance of artificial intelligence (AI) in marketing and chart future research directions. The present study aims to offer a comprehensive review of AI in marketing using bibliometric, conceptual and intel- lectual network analysis of extant literature published between 1982 and 2020. A comprehensive review of one thousand five hundred and eighty papers helped to identify the scientific actors’ performance like most relevant authors and most relevant sources. Furthermore, co-citation and co-occurrence analysis offered the conceptual and intellectual network. Data clustering using the Louvain algorithm helped identify research sub-themes and future research directions to expand AI in marketing.

Digitalization affects many organizational strategies of a company, including the development of market opportunities, and is known as an element that strengthens the internationalization of small and medium-sized enterprises. However, the use of digital technologies requires investment and changes in the internal procedures of a company through the mobilization of new resources based on digitalization and the use of special capabilities for their management. Research on the impact of digitalization on the export maturity of SMEs is scattered and there is a need for a comprehensive research on the past research trend and the future trend of this topic. This study is a bibliometric analysis using Vosviewer software, with the aim of reviewing published scientific products and drawing a scientific map in the field of digitization and export maturity of small and medium companies, which investigated this field using 240 articles indexed between 1984 and 2022. To conduct this study, co-authorship analysis, co-citation analysis and co-occurrence analysis were used for network analysis. In the end, according to the analyzes carried out, five main topic clusters were identified, which include organizational resources based on digitalization, organizational capabilities based on digitalization, dimensions of export maturity, export and internationalization, and sustainable development; According to the trend of the articles, we can expect the field of sustainable development to attract more attention in the coming years.

In recent years, studies on the paradigm of social Manufacturing and its applications have been developed as a new production paradigm and have led to the production of diverse and scattered knowledge in this field. Knowing the sub-fields, new topics and the research process of the social production paradigm can be of great help to researchers in this field. The current research has been carried out with the aim of identifying and categorizing research in the field of social Manufacturing, recognizing sub-fields and achieving a coherent view of its research process.This research has investigated the research field of social Manufacturing using bibliometric analysis. The data of this research was collected from 200 articles of the Scopus database and an analysis of the co-occurrence analysis of key words and bibliographic pairs was performed on them, and in this way the sub-fields and the research process of this field were identified.Based on the findings of this study, the research in the field of social Manufacturing has been categorized into 5 clusters and it has also been determined that in recent years, topics such as cloud computing, smart production, blockchain, Internet of Things, social physical cyber systems, innovation systems, society 5.0 and Digital twins have received more attention in research in this field. This research provides a framework of concepts and main topics of interest in the research field of social production, which provides a comprehensive perspective for researchers in this field that can help in choosing their research path.

Tourism is often accused of providing unequal benefits and marginalizing disadvantaged and vulnerable groups for reasons such as ethnicity, gender, geographic region, poverty, disability, etc. Inclusive tourism as an approach based on the UN Sustainable Development Goals has been suggested in response to the exclusive nature of tourism development. This study aims to systematically review the literature on inclusive tourism using bibliometric analysis and quantitative content analysis. One hundred four documents indexed in the Scopus database were analyzed to understand the research's social and conceptual structure, the frequency of research methods and target groups. The findings revealed that research in this nascent field can be categorized into four clusters, namely:  "sustainability," "social entrepreneurship," "social inclusion," and "accessible tourism." In addition, based on the content analysis results, most of the research conducted in this field has been qualitative and conceptual, focused on the physically disabled from the demand side and on local communities from the supply side. The literature in this field is not yet well developed and requires research focusing on the diverse needs of different groups. The results of this study will help researchers and tourism activists understand trends in inclusive tourism and future research directions.

Conducting research with a theoretical contribution, reviewing the theoretical background without bias, and identifying emerging research areas are one of the most important concerns of every researcher in conducting academic research. The abundance of useless and scientifically worthless research in the country doubles the need to pay attention to these issues. One of the existing strategies to solve these problems is the approach of academic social networks analysis. Considering research areas as social structures, these networks are drawn based on bibliometric criteria such as co-citation, citation, bibliographic pairing, co-occurrence of vocabulary, and co-authorship, each of which has its uses and are used to answer special questions. In this article, the approach to social networks analysis will be introduced first, and then the bibliometric criteria used in drawing these networks will be examined. It is also stated that each of the drawn networks is suitable for answering what questions. Then, the step-by-step stages of implementing a social network analysis are introduced. Also, the most important databases used to collect the necessary meta-data are introduced and some existing tools to analyze and illustrate academic social networks are briefly reviewed. Examples of applications of this approach are also shown.     In order to conduct academic social network analysis, a 5-step process must be performed. In the first step, the research design should be determined. The analysis is done to answer what questions and what method is suitable to answer those questions. In the second step, it is necessary to collect bibliographic data. First, you have to choose the right database and then, by choosing the right search keywords in a specific time frame, search and collect the necessary metadata for network drawing and analysis. In the third step, the collected data should be analyzed. In this step, the appropriate bibliographic software should be selected and the data should be prepared for analysis. Illustration of the networks is done in the fourth step, in which the appropriate method and tool of the illustration should be determined by the researcher. In the final step, the drawn networks should be described and interpreted.     Each of the networks drawn by metadata collected from scientific databases has a specific application. Citation networks are used to identify the most important and influential works, authors, and publications. Also, based on the citation networks drawn based on the timeline, it is possible to identify the development process of a research field, its theoretical foundation, and theoretical fields affecting the research field. Co-citation networks that are drawn based on the cited references of the selected documents provide the most relevant sources for research. Also, the clusters obtained from this analysis show the historical streams of the research field. The bibliographic coupling networks which are the reverse of co-citation examine the cited documents and the clusters obtained from them showing the contemporary streams of the research field under investigation. Co-authorship networks are a measure of cooperation between authors, institutions, publications, and countries. Word co-occurrence networks identify important themes in a domain, and as a content analysis technique, they are the only network that uses the actual content of documents. The output of the word co-occurrence network is a network of themes and shows the conceptual space of a field.      Conducting targeted and useful research is one of the important issues faced by researchers and students, especially graduate students who have to conduct research in the form of a thesis or dissertation. From choosing new topics to reviewing literature and theoretical background in an appropriate way, all of them are problems that researchers have to overcome, and in this way, they need a clear strategy and roadmap. The social network analysis approach based on bibliographic criteria is one of the strategies proposed to help solve these problems. The analysis of academic social networks that are formed based on bibliographic criteria such as citation, co-citation, co-authorship, word co-occurrence, and bibliographic coupling, by adding an objective and quantitative accuracy, reduces the consequences of personal reviews and subjective biases of researchers and It helps to get a more comprehensive understanding of research areas. Each of these networks is suitable for answering specific questions. Using the approach of social network analysis can have a significant help in guiding researchers in conducting targeted research. The use of this method helps researchers, especially newcomers to a field, to get a better understanding of that field, get acquainted with important sources for study, and helps them determine their research position and advance research flows in a specific field. For this reason, getting familiar with this approach and using it is one of the topics that researchers and higher education institutions should pay attention to in order to reduce the amount of aimless and useless research.

Tourism can, on the one hand, strengthen national and ethnic identities, and on the other hand, it can accelerate fading of these identities. In addition, national-ethnic identity is one of the obstacles against rapid cultural homogenization due to globalization. Considering more than five decades of research on tourism and national-ethnic identity, and the lack of a comprehensive review of literature, this study aims to conduct a quantitative literature review using bibliometric analysis. Performance analysis and science mapping of 383 documents indexed in the Scopus database were performed using VOSviewer_1.6.18 software in order to understand the social and conceptual structure of the research field. The findings revealed that in the last decade research on heritage tourism among diaspora and immigrants, outbound tourists’ representation of their national-ethnic identity, and the representation of the destinations’ national-ethnic identity through tourism have been among the hot topics that can also be considered in future studies.

Cause-related marketing is an attractive way for companies to gain a competitive advantage, where it evokes a sense of altruism and benevolence in customers. Companies and organizations use this method to achieve their business goals and respond to corporate social responsibility. However, research in cause-related marketing has been sparse, and there is a need for a comprehensive study of past research and current trends. This study is a bibliometric analysis using Vosviewer and Gephi software, which was selected to review this area using 454 articles conducted in Q1 and Q2 journals between 1987 and 2022; it has explored the field of cause-related marketing studies. First, the number of articles, citations, bibliographic coupling, co-word analysis, and Prestige analysis were examined for this study. Then, co-authorship analysis, co-citation analysis, and dynamic co-citation analysis were used for network analysis. Finally, according to the analysis, four main thematic areas were identified, which include planning and how benevolent marketing performs well, attitudes and views on cause-related marketing, the role of a cause-related marketing brand, and promotion interaction with cause-related marketing; The two areas of attitudes and views on cause-related marketing and promotion interaction with cause-related marketing according to the trend of their articles can be expected to attract more attention in the coming years.

 Despite the numerous exploratory, conceptual, and empirical investigations that have been conducted in the fields of economics, finance, business, and management on financial behavior and literacy, no comprehensive science mapping has been presented to date. Therefore, the purpose of this study is to identify trends in the research field through the synthesis of knowledge structures.

 A bibliometric investigation was conducted on a selection of 1,138 documents in the realm of financial literacy and financial behavior, utilizing a scientific search strategy implemented on the Web of Science database during the 1995-2022 period. The study was carried out using Biblioshiny, a web-based application that is part of the Bibliometrix package designed in R-language. The software's automated workflow facilitated the identification of distinguished journals, authors, countries, articles, and themes, and enabled the conduction of citation, co-citation, and social network analyses.

 The findings indicate that financial literacy and behavior have developed as an interdisciplinary domain over time. Initially, researchers concentrated on demographic and socioeconomic factors, but the domain later expanded to encompass themes such as behavioral and psychological constructs that impact financial behavior. This research not only unveils the conceptual framework of the domain but also its intellectual and social structure. The study offers valuable insights into areas that require further research.

Originality / Value: 

In the past, a great deal of theoretical and practical research has been carried out on financial literacy and behavior in various countries, covering diverse fields such as economics, finance, psychology, and consumer behavior. One of the major contributions of this study is that it integrates and unites scattered literature in this area, and identifies important sources, authors, and documents, while examining the link between financial literacy and financial behavior.