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Find support for a specific problem in the support section of our website. Get Support FeedbackPlease let us know what you think of our products and services. Give Feedback InformationVisit our dedicated information section to learn more about MDPI. Get Information clear JSmol Viewer clear first_page settings Order Article Reprints Font Type: Arial Georgia Verdana Font Size: Aa Aa Aa Line Spacing: Column Width: Background: Open AccessArticle A Bibliometric and Visualization Analysis of Knowledge Mapping in Digital Economy Research, 1992–2022 byShaolun Zeng 1,* and Huili Yang 2
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School of Economics and Finance, Guizhou University of Commerce, Guiyang 550014, China
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School of Business Administration, Guizhou University of Finance and Economics, Guiyang 550025, China
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Sustainability 2023, 15(8), 6565; https://doi.org/10.3390/su15086565
Received: 5 March 2023
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Revised: 9 April 2023
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Accepted: 11 April 2023
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Published: 12 April 2023
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Abstract: Digital economy is a vital driving force for countries to promote economic recovery, rebuild competitive advantages and enhance governance capacity. Extensive research has been conducted in this field. In this paper, the text analysis tool of Bicomb2.04 and the knowledge graph visualization tool of CiteSpace are applied to analyze the digital economy research from 1992 to 2022, and a total of 7874 articles retrieved from the SSCI and SCI of the WOS core database are collected as the research data. The analysis provides a comprehensive overview of the research status of the digital economy, including the distribution of literature, research institutions and regions, research funds and publications, research authors, and cooperation networks. The core progress and frontier of international research are further analyzed according to the evolution of hot keywords, core system clustering, and the hot emergent words frontier. The results show that (1) the academic circle has a good overall research trend on the digital economy, which can be divided into three steadily rising research stages. The researchers take digital innovation as the core and extend it to the application of digital innovation, which has made groundbreaking theoretical contributions, but has not yet formed a team with field influence. (2) The evolution of hot keywords can be divided into four stages. Through hot clustering analysis, a basic theoretical system is constructed with digital technology and innovation as the core and digital governance, digital application, and digital path as the means. (3) The analysis of frontier areas also identified the digital platform economy, big data technology innovation, digital economy statistics, and the gig economy as potential research directions for the future. This study provides a guide for researchers to promote further research on the digital economy and is of great significance for promoting digital development level and constructing global digital ecosystem. Keywords: digital economy; knowledge graph; visual analysis; bibliometric; text analysis 1. IntroductionThe digital economy, with digital technologies as its primary driving force, is critical to promoting the high-quality development of the global economy. By 2021, the value added to the digital economy in 47 countries reached US $38.1 trillion, accounting for 45 percent of the global GDP [1]. As a new economic form, it promotes the global economy’s digital transformation along three paths: technologies to form new sectors, industries to foster new models, and new technologies to empower traditional industries [2]. Faced with the combined challenges, how to seize digital economy development opportunities and effectively allocate digital resources have emerged as a key research topic for long-term economic and social development.The G20 Initiative on Digital Economic Development and Cooperation proposed a more authoritative definition, adopted at the G20 Summit in 2016, which is “digital economy”, and refers to a set of economic activities that use digital knowledge and information as critical production factors, modern information networks as essential carriers, and effective use of information and communication technology as a driving force for the optimization of economic structure with improved efficiency. X. Chen approaches data elements as critical resources from the theoretical system’s perspective [3]. Lane asserts that the digital economy, driven by the integration of information and communication technologies, results in the development of new competitive strategies and the evolution of business organizational structure [4]. Data information is the critical resource of the digital economy, and resource allocation of data elements is the focus [5]. Digital-driven innovation, digital transformation, and industrial structure modernization are also at the forefront of the digital economy’s development [6,7,8]. From the standpoint of practical analysis, X. Xu [9] measures the digital economy’s development scale and determines the international digital frontier level. From the perspective of the digital economy, T. Zhao [10] demonstrates that enhancing entrepreneurial activity has positive impact on the high-quality development of urban economy. The digital economy also has the functional characteristics of spatial effect, regional link-age, and productivity improvement [11,12,13]. J. Sun [14] also investigates the connotation characteristics and influence mechanism of “digital trade” derived from the digital economy. The digital economy also has specific influence mechanisms regarding enterprise internationalization performance, level of sustainable development, and industrial toughness [15,16]. From the standpoint of long-term economic and social development, humans are entering the digital age, which necessitates the creation of a new digital ecosystem to adapt to it [17], and a benign digital ecology must begin with “digital production relations” [18]. As a result, some scholars have expressed their views from the viewpoint of developing “digital ecology” [19,20]. Many academics have developed a research and analysis framework for the digital economy based on four factors: research methods, connotation, characteristics, and driving mechanism.As of May 2022, some scholars have conducted a visual analysis of digital economy research. X. Dong [21] addresses the evolution of digital economy research from 1992 to 2018 and arranges the frontiers using a map of scientific knowledge. Some scholars examined the research fields of international digital economy from various angles [22,23]. In short, the literature on knowledge graph visualization is scant, and it is rare to combine CiteSpace, Bicomb, and SPSS to analyze the “digital economy”. This paper makes a statistical analysis of the core works of literature in the field of the digital economy as a whole. This study is based on the latest data and by using the visualization analysis of a knowledge graph, which visualizes the hot spots and fraught areas. The goal is to synthesize the evolution trend of the digital economy research field, provide international frontier development experience for the development of the digital economy, highlight the direction to promote the further study of the digital economy, and improve the sustainable development of the economy and society from the point of digital ecosystem.The paper’s structure is as follows: First, a thorough description of the data sources and research methods is provided. Next, bibliometric and visualization analysis tools are utilized to examine the global research status of the “digital economy”, including research institutions and regional distribution, research funds and publications, research authors and collaboration networks, evolution of hot keywords, core system clustering, and frontier of hot outburst words. Ultimately, the paper presents its research conclusions and future research trends to offer theoretical support and recommendations for the advancement of the digital economy and digital ecosystem. 2. Materials and Methods 2.1. Data SourcesWeb of Science (WOS) is a large, multi-disciplinary database, containing information from hundreds of national and regional institutions in the world, and has three of the most authoritative citation index databases. Therefore, it can be said that the literature on digital economy included in the WOS database can be used as a representative of this field to some extent. The data used in this paper comes from the core database of WOS and employs “digital economy” as the theme. The document type is ARTICLE, the advanced retrieval of Social Science Index (SSCI) and Science Citation Index Extended Library (SCI-E) is used, and a manual method to sort out and clean the data is adopted. After sifting relevant documents such as conferences and newspapers, 7874 valid articles were obtained. 2.2. Research MethodCiteSpaceV5.8R3 visual analysis tool and BicombV2.04 and SPSSV20.0 text analysis software are used to carry out visual research in the literary journals of digital economy research. The knowledge graph method can visualize the development process, evolutionary logic, and the internal research mechanism in a particular field, and then uncover its development law and vein [24,25]. CiteSpace is a popular bibliometric analysis tool that combines citation and co-citation analysis [26,27], and Bicomb adopts the current mature and popular database language development. It can quickly read bibliographic information in a literature database, and it accurately extracts fields, classifies, stores, and creates statistics. In addition, it can generate the co-occurrence matrix of bibliographic data, so as to provide comprehensive, accurate, and authoritative basic data for further research. By integrating the three analysis tools and taking the characteristics of the literature system and bibliometrics as the research object, these Both CiteSpace and Bicomb can not only quantitatively measure the contour distribution and the relationship and cluster among objects, but also describe and predict the development of specific research fields, analyze different countries, institutions, journals and scholars, compare their contributions, and creatively combine citation analysis and co-citation analysis, making the research more scientific and intuitive. First, the research status of the digital economy is sorted out holistically, and the development context is obtained. Then, using keyword clustering, evolution graph analysis, and emergent word detection, as well as other methods, an analysis of the international digital economy research trends, core systems, and hot evolutionary paths was performed to determine the digital economy research frontier trends and development trends. The main steps are as follows:Firstly, the amount of literature related to the digital economy was counted, retrieved, downloaded, and recorded in WOS. RefWorks and NoteFirst were selected according to different software regulations during downloading. The sections of the literature were saved as a plain text format and named “download_X”. Secondly, the txt file was imported into Bicomb2.04 to extract key fields, including “keywords”, “author”, “author unit”, “age”, “journal”, “fund”, “country” and “research institution” of the source literature. The text matrix and co-occurrence matrix obtained from Bicomb2.04 were imported into SPSS20.0 for word frequency statistics, co-word analysis, and sample clustering of high-frequency keywords in different dimensions. Then, the txt file named “download_X” was converted into the Data of CiteSpace V5.8R3, and “New” was selected to establish a new project. The literature time was set from 1992 to 2022, and the time Node was 1 year. The “Node Types” were analyzed by taking Author, Institution, Term, and Keyword as the nodes for analysis. The keyword clustering, core system, hot frontier, and other aspects of the research results during a specific period were used to make an overall and objective analysis. As a result, the substance hidden behind the data was found, and the research process is shown in Figure 1. 3. Research Trends of the Digital Economy 3.1. Chronological Distribution of ArticlesAccording to the preliminary statistical results of Bicomb and SPSS, the publication trend in the international research field is drawn in Figure 2, and the overall development shows an inverted L-shaped trend. The term “digital economy” first appeared in a journal paper in 1992, which originated from the development of electronic communication technology and related hardware in the 1990s, which established the technical basis for the digital economy. The changing trend can be broken down into three distinct phases. The embryonic stage, spanning from 1992 to 2000, was characterized by a scarcity of literature, a limited number of notable literary achievements, and sluggish growth, with an annual publication rate of less than 20. The subsequent stage, running from 2001 to 2015, marked a period of stable growth, despite occasional dips, resulting in an overall increase in the number of publications. The third phase, from 2016 to 2021, was a time of rapid expansion, with publications multiplying at an exponential rate compared to the preceding stage. This phenomenon can be linked to the global consensus reached at the G20 Hangzhou Summit in 2016, which emphasized the importance of the digital economy and led to its inclusion in the development strategies of various nations. The steady growth of international journals devoted to the digital economy, which totaled 7874 publications with an average annual rate of 263, demonstrates the sustained interest of the global academic community in this subject.Upon further analysis, it has been found that the research trend during the first stage of exploration and pioneering in the academic circle of the digital economy was flat and slow. The early research level of the international digital economy served as a guide for all countries. During the second stage, research results steadily increased, laying the groundwork for explosive output in the next period through expansion, accumulation, digestion, and interpretation of research results. The world then entered a third stage marked by widespread penetration of the digital economy and a surge in research. The exponential increase in annual literature output signifies the continual improvement of international academic attention and rapid progress at the research level. This aligns with the digital economy development strategies of many countries, the rapid advancement of digital technology and industrial structures, and a series of supporting development levels. 3.2. Research Institutions and Regional DistributionThe results of the Bicomb analysis and the statistical function of SPSS software were used for statistical analysis of literature in the WOS database. The main distribution of publishing institutions in international journals was obtained as shown in Table 1. Among the publishing institutions, Elsevier was found to have published the most papers (1532 articles), accounting for nearly one-fifth of the total number of papers. This finding underscores the significance of research achievements in the field of the digital economy. The next five institutions have roughly 700 articles, equivalent to half of Elsevier’s volume. In addition, there is also a lot of cooperation between publishing institutions. For example, Springer Nature has signed a contract with Science Press in China on more than 100 topics, which has attracted wide attention and good response around the world. Overall, the study indicates that research on the international digital economy is primarily concentrated in various scientific research institutes and universities. Moreover, the research output is published by academic publishing groups, indicating that the research status is relatively active.Table 2 illustrates the distribution of the top ten countries/regions based on the number of publications on the digital economy in international journals. The United States and Spain lead the list with the highest number of publications (1601), followed by the United Kingdom (1429), China (1033), and Australia (899). The majority of the countries with the highest number of publications are situated in Europe, North America, and certain parts of Asia. However, China, as a developing nation, has also secured a top position on the list of international publications, owing to its extensive user base and digital scenario application market. In conclusion, a country’s digital technology development level, both horizontally and vertically, should align with the theoretical research depth of its digital economy. The more a country advances in economic development and national modernization, the more importance it attaches to digital economy research. Consequently, the ranking of the number of articles published in English journals is consistent with a country’s economic size and level of modernization development. 3.3. Research Fund and JournalResearch funds refer to academic funds established by the state or relevant institutions to promote research in various disciplines and provide theoretical and practical support to solve relevant problems in economic and social development. As shown in Table 3, a total of 7874 articles were analyzed. The fund with the highest number of publications in digital economy research was the Spanish Government (833), which is consistent with Spain, the country with the highest number of publications. The UK Research and Innovation UKRI (795 articles) and the European Commission (693 articles), located in Europe, also had many publications. In Australia, the “Australian Research Council” and “Australian Government” published 903 articles, while other funds published less than or equal to 500 articles. In Asia, the top 10 publications were the Ministry of Knowledge Economy MKE Republic of Korea (490) and the National Natural Science Foundation of China (385 articles), which have produced fruitful research results. SPSS statistical analysis results indicate that the number of papers published by most funds on the “digital economy” has been increasing year by year in recent years, demonstrating that the “digital economy” field has gradually attracted the attention of academic circles worldwide.Descriptive statistics on fund distribution and institutional areas of digital economy research fall short of exploring the knowledge structure of the literature. To address this, we have identified the top 10 core journals of digital economy research in terms of publication volume (Table 4). Among these, “Sustainability” stands out with the highest number of publications, totaling 309 articles. This journal covers a broad range of submissions and diverse research directions, capturing both theoretical research and practical results in various fields of the digital economy. As a result, it has gained significant recognition among scholars across multiple research fields. Following “Sustainability”, the journals with the next highest cumulative number of publications are Monthly Notices of the Royal Astronomical Society, Astronomy Astrophysics, and Astrophysical Journal. Since these journals’ research direction is primarily in astronomy and physics, it suggests a higher degree of correlation between digital economy research and these fields. The study of digital economy involves a wide range of fields, with a significant number of articles published in electrical engineering (952 articles), environmental science (680 articles), economics (611 articles), computer science information system (557 articles), management (547 articles), commercial finance (463 articles), and so on. This interdisciplinary research topic emphasizes the importance of information and communication technology as the basis for the digital economy, with digital knowledge and information as crucial production factors. Moreover, modern information networks play a significant role as an essential carrier of various economic activities that promote economic development optimization. The research findings also indicate that the digital economy is closely intertwined with national economic and social development, as well as management decision-making and determining the coordinated development of different regions and industries. 3.4. Author’s Publication and Cooperation NetworkAccording to the statistical analysis results of SPSS, the top 10 authors and their H-index were sorted out (Table 5). Table 6 displays the three cooperative teams that were identified based on this analysis. Among them, H-index is a measurement method that Hirsch, an American physicist, proposed for evaluating individual academic achievements. H-index stands for “high citation times”. The higher the H-index of a scholar, the greater the influence of his paper.Garcia-Hernandez and Domingo Anibal, both from the United States, have the highest number of articles published, with a remarkable total of 51. Moreover, their H-index stands at 54, indicating a high level of research influence. Among the top 10 authors in terms of the number of published papers, Steven R. Majewski, also from the United States, has the highest H-index with 32 published papers. Additionally, Majewski’s collaboration with other authors is highly correlated. From the perspective of collaboration, CALIFA Collaboration, whose research direction is astrophysics, has published the most papers, which is significantly higher than other teams. It has published 14 papers, which are of great influence. In addition, from the perspective of the region of the researcher’s institution, its distribution characteristics are consistent with the regional distribution characteristics of the digital economy. As some developed countries are at the leading level in the field of digital economy development, and under the influence of a series of national strategies such as “Digital Britain Action”, most of the top 10 scholars in terms of publication volume are from developed countries in Europe and the United States. In combination with the above collation and analysis of authors and cooperative teams, CiteSpace is used to further construct the author cooperative network, as shown in Figure 3. The figure highlights three major cooperative groups: a cooperative network composed of Korean scholars with the core of Lee S., Kim Y., Park S., etc. The cooperation network comprises European and American scholars with Sanchez S., Falcon-Barroso J., et al. as the core, and Garcia-Hernandez D., Zamora O., Majewski S., et al. as the core, as seen in Table 5. Several core members of the major cooperative network ranked in the top 10 in terms of individual publication volume, whereas the other authors had relatively weak cooperative relationships. Overall, the number of papers published by digital economy research teams is limited, the cooperation situation is weak, and the scale of researchers included in the team is not large. Additionally, influential researchers in the field and the cooperation network have yet to be established. It is imperative to further develop and expand these networks in the future. 3.5. Hot Keywords and Their EvolutionCiteSpace utilizes word frequency analysis to extract keywords from international journal articles. Obtaining a time-domain perspective on the shifts in popular keywords is possible by arranging words in order of frequency, from highest to lowest. High-frequency keywords can reflect the current research hotspots in the academic field. Additionally, the centrality measurement of points can help identify connection points between different disciplines or key nodes in the mutual citation network. Therefore, nodes with high centrality are likely to become key nodes in the network [28].Table 7 shows minimal variation in word frequency among popular terms in academic research on the digital economy in other countries. The word “model” has the highest degree of centrality, with up to 368 instances of its use. In contrast, the key term “digital economy” is only used 220 times, ranking 11th in frequency. Other commonly used keywords include “system” (334), “technology” (309), “effect” (286), “innovation” (274), “digital sky survey” (269), “performance” (248), “information” (239), “economy” (227), and “management” (224). These results indicate that international research on the digital economy is thorough and in-depth, with a focus on hotspots, theoretical innovation, and pioneering in the field.According to Table 7, the international digital economy research’s keyword evolution path (Figure 4) may be separated into the following four stages: The first stage, which spans from 1992 to 2000, is commonly referred to as the pioneering period. During this stage, scholars began to view the digital economy from the standpoint of technological progress [29]. During this period, the fundamental theories of narrow network economics were established, which includes network externalities and lock-in effects. These concepts explain how enterprises can utilize information technology and user networks to lock their business and operational channels [21]. The era of the Internet has swept across the world, bringing with it the widespread adoption of information technology across various industries. Although the term “digital economy” has become a popular buzzword during this period, it is primarily focused on industry-based transformation and signifies that the concept is still in its nascent stages within the academic realm. Another crucial issue that gained traction during the second phase (2001–2007) was the “digital divide”, which laid the groundwork for the development of the digital economy and the integration of new models with existing businesses. The emergence of IT and e-commerce led to the rise of the first wave of Internet giants in different countries, causing ripple effects across the traditional industrial model. The groundwork laid by scholars’ research on the “information economy” and “network economy” concepts paved the way for the eventual emergence of the “digital economy” [30] and developed the preliminary research on the theoretical and practical application of digital economy imperceptibly. During the third phase (2008–2015), the global financial crisis devastated the digital economy, and academic research has changed significantly. In the fourth stage (2015–2022), the international hot keywords have not emerged in large numbers. Still, a series of technologies and algorithms such as “artificial intelligence”, “blockchain” and “5G technology” have penetrated extensively in the economic field, leading the digital economy to fully blossom in the direction of theoretical innovation, industrial chain remodeling, digital transformation, globalization, and green development [31]. The digital economy has been impacted by the COVID-19 pandemic’s opposing force on its growth engine. However, the integration and advancement of previous theoretical and practical innovations have driven development across various domains.Based on changes in popular keywords in global digital economies over time, there have been three distinctive phases: pure digital technology application, digital innovation management, and digital collaborative innovation development. Among these, the finance and innovation sectors are the young blood that propels the digital economy’s continuous emission of new business models. Innovation topics begin from the outside and gradually move towards the core, starting with model construction, technological exploration of theoretical innovation, platform construction of e-commerce and mobile payment, and finally re-construction of digital systems such as blockchain and bitcoin. China’s social and economic development status limits the early stage of the digital economy’s evolution at a speed that is slightly slower than the global average. Nonetheless, it eventually caught up to the level of the global frontier once the mid-term technological basis consolidation and scale innovation were overcome. With the help of the massive Internet user population brought by the demographic dividend, the industry is undergoing digital transformation through the application of “industry 4.0”. In summary, the development of the digital economy has four stages, each with its breakthroughs and innovations that reflect the synchronicity and support of the digital economy’s development with the level of digital technology. 3.6. Cluster Analysis of Core SystemsCiteSpace’s cluster analysis revealed that the LLR algorithm outperformed LSI, LLR, and MI in generating results that accurately reflect the actual situation. Consequently, the Log-likelihood rate (LLR), which is more significant in the evolution of subjects in the research field of digital economy [32], is the algorithm utilized in this grouping. The co-occurrence keyword clustering map is shown in Figure 5. The study period covered 1992–2022, with a slice size of one year, resulting in 84 clusters. To increase focus and exclude clusters with less obvious effects, seven modules were obtained by sequential screening based on clustering scale. Furthermore, the Modularity Q value of 0.4056, which exceeds the critical value of 0.4, indicates that the network modules in the clustering results are closely correlated, and the clustering structure is significant. The Mean Silhouette value of 0.7528, exceeding the critical value of 0.7, confirms that the clustering modules are highly related to the “digital economy” research subjects, lending credibility to the clustering result. The international hotspots cover a broad range, with a prominent thematic nature of technology.The keywords that clustered the results of digital economy research (Table 8) can be classified into three categories: digital innovation and theory, digital governance and pathways, and digital markets and applications. 3.6.1. Digital Innovation and TheoryThe keywords include #0 Remote sensing, #4 Galaxies: evolution, and #6 Digital technology. To begin with, digital innovation has become a driving force for economic and social development, facilitating a shift towards a more advanced form of the economy, with a precise division of labor and reasonable structure [33]. The theory and expansion of the digital market, which primarily encompasses remote sensing, image acquisition, biological research, and other theory models, are the focus of international digital economic research. The innovation of the technology paradigm under the digital economy not only promotes the transformation of the industrial–organizational mode, but also broadens the scope of cyberspace function and resource allocation, leading organizational modes towards networking, collaboration, and ecology [34]. Simultaneously, data elements enter the market as production factors, increasing the value of digital products and their related penetration fields. The high frequency of keywords such as “galaxy evolution” and “digital technology” also conforms to the current development status of digital economy globalization penetration and extensive construction of digital technology. 3.6.2. Digital Governance and PathwaysHere, there are two keywords: #2 Circular economy and #5 Economy growth. The development of digital globalization also brings certain risks and crises, such as digital monopoly, digital divide, digital security, digital polarization, and digital privacy. As a result, digital governance and economic growth have become a global issue. Scholars have discussed the digital governance issues in the development of the digital economy from the perspectives of digital security, divide, rules, and ethics. Numerous studies have been conducted on how to reach digital economy growth. Based on research on digital technology innovation and diffusion, a better understanding of the factors influencing the development of the digital economy can be obtained, as well as insight into its development trajectory. This knowledge provides a theoretical basis for guiding countries in supporting the development of digital technology. The mature development path of the digital economy includes several key steps, such as seizing the commanding heights of ICT innovation, promoting the deep integration of ICT and the real economy, accelerating the supply-side structural reform of high-end information consumption, streamlining the policy management system of digital economy development, and building a safe and reliable system for supervising data application [35,36]. In addition, circular economy is also one of the core keywords after clustering. Digital economy innovatively promotes the growth of circular economy through the burst of new industries, new business forms, and new models, so as to achieve the goal of digital governance [37]. The objectives for the future development of the global digital economy are to create a comprehensive strategy for global digital governance, safeguard national digital security and interests, and promote fairness, efficiency, and openness in the digital economy development process [38]. 3.6.3. Digital Markets and ApplicationsIn the context of the digital economy, technological advances such as smartphones, mobile applications and online platforms have massively spawned many new economic forms, including the #1 Gig economy, #3 Sharing economy, and #7 News. For example, digital labor platforms have enabled the gig economy to flourish by providing a cheaper and quicker means of recruitment from anywhere in the world. This has allowed clients to access specialized workers globally at a lower cost, while employers and freelancers can both benefit from gig work [39]. Among them, the keyword News has a weak correlation with the digital economy, which may be a non-core keyword or caused by the error of keyword extraction in some articles. By extension, future research can be based on the resource sharing of digital economy development among countries and carry out a comparative study on the spatial growth of digital economy among countries to provide inspiration and experience for the development of the digital economy for latecomer countries and realize the balanced development of the digital economy. 3.7. Frontier AnalysisThis study aims to identify burst terms—keywords with high-frequency change rates. The degree of burst is used to calculate the frequency change rate of burst words over a period of time. A higher degree of burst indicates greater popularity. This word’s emerging year is known as the starting year. The emergence year of this word is called the beginning year. The frontier keywords in Table 9 exhibit the emergence’s ending year, indicating that they are still in a high-frequency occurrence period and are expected to become the frontier direction.Table 9 shows that worldwide digital economy study subjects include digital technology innovation and implementation. Digital technology innovation involves the development of new algorithms that utilize pure digital communication technologies such as blockchain and big data. It encompasses various stages of data processing, including acquisition, storage, transmission, and decision support. Technical support and application are driven by the fitting of digital technology and specific practice. Exponential finance, fintech, and new infrastructure include the application of technology in other fields oriented to the high-quality development and derivative of the digital economy. Big data and digital platforms are two emerging phrases in digital technology innovation and development. The integration of the digital economy in supply chain management and the gig economy, on the other hand, falls under the area of digital economy application. International research focuses on the application level instead of the technological level, that is, the use of big data and digital platforms to promote and drive supply chain management, the gig economy, and other new kinds of business. Furthermore, the development and implementation of digital technologies such as supercomputing and deep learning encourage the emergence of new production resources and the growth of society. The academic community gradually recognizes that data socializing is the only method to achieve data capitalization and that data capitalization is the driving force behind data socialization. In the future, the information infrastructure system will be more sophisticated, the digital transformation of traditional industries will become the focus, and the artificial intelligence field will be a new growth point. With the extensive penetration of the digital economy, the integration of the virtual economy with the real economy, the Internet and the manufacturing industry will be further deepened [40]. Simultaneously, a slew of creative technologies, new goods, and models formed in the digital economy are dual-sided. The evolution of their achievements and functions may have far-reaching consequences for the social system, such as technological risk, moral risk, social risk, and national risk.Scholars have generally recognized the significance of “data elements” in unlocking the potential of traditional production forces such as capital and labor. This can lead to the realization of digital value in enterprise product innovation, business model transformation, and improvements in operational efficiency—across micro-enterprises as well as the macro-industrial economy. Furthermore, the development of digital finance has piqued the interest of many academics. Digital finance is not only the vein that connects the digital economic system, but is also a powerful driving force in real economy revitalization. Digital inclusive finance should be the crucial route for an optimized macroeconomy’s development trend in the future. 4. Research Conclusions and ProspectsWith text analysis statistical tools and knowledge graph visualization software, this study sorted out the core literature in digital economy research in the WOS database. Through examining various factors such as research status, publication institutions, regional distribution, research funds and publications, research authors and cooperation network, evolutionary path, core clustering, and hot frontiers, the study has found that the “digital economy” research trend is generally positive. Many scholars have explored the mode and trajectory of the “digital economy” from various perspectives and disciplines, and both theoretical and practical systems need to be further developed and improved. It was found that international research begins with digital innovation and then expands to digital finance, digital sharing, digital intelligence, and other digital markets and digital path innovation applications, which has made a significant contribution to theory. Within the framework of theoretical knowledge of the digital economy, an entire academic system has been formed, with digital technology and innovation at the core and digital governance, digital application, and digital path as supporting pillars.The study presented here has both theoretical and management significance. The theoretical significance lies in the thorough review and categorization of the existing literature on the digital economy, as well as the analysis of current research trends and hot topics, as well as frontiers in the last three years. This provides a valuable contribution to the current body of knowledge on the subject and offers insights into future research directions. The management significance of this study is equally important. As the digital economy continues to expand rapidly, there is a growing need to enrich the theoretical system that underpins it. By combining practical experience with cutting-edge theories, countries can accelerate the development of their digital economies and promote the balanced growth of the global digital ecosystem. Furthermore, through research on the development frontier of the digital economy, this paper identifies several key areas for future investigation, including the internal mechanisms of digital economy development and its linkage with other fields, the integration of international approaches and experiences with national economic and social situations, and the consolidation of influential research institutes and literary accomplishments in the field. Looking ahead, it is likely that future research will focus on several important areas, including the digital platform economy, big data technology innovation, digital economy statistics, the gig economy, and digital space growth.Some limitations of this study should be acknowledged. Firstly, the study relied solely on the use of Bicomb, a statistical tool for text analysis, and Citespace, a visual analysis software, which means that the limitations inherent to these tools cannot be ignored. In future research, it would be beneficial to incorporate other tools for comparison measurement. Secondly, the literature data samples used in this study were only taken from the WOS data core. As a result, the sample coverage may have been insufficient. To address this, future research should include an increase in the sample size from other databases for analysis. Furthermore, the study only examined international publications, and as such, there is room for improvement in investigating practical applications and related categories. Author ContributionsWriting–original draft, H.Y.; Writing–review and editing, S.Z. 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Figure 1.
The research process.
Figure 1.
The research process.
Figure 2.
Distribution of digital economy research trends from 1992 to 2022.
Figure 2.
Distribution of digital economy research trends from 1992 to 2022.
Figure 3.
The author and the academic cooperation network. Note: The yellow dots indicates the node position of the author in the network map.
Figure 3.
The author and the academic cooperation network. Note: The yellow dots indicates the node position of the author in the network map.
Figure 4.
Evolution of international hot keywords from 1992 to 2022.
Figure 4.
Evolution of international hot keywords from 1992 to 2022.
Figure 5.
Clustering of hot keywords of the digital economy during 1992–2022. Note: # indicates a flag for the cluster name.
Figure 5.
Clustering of hot keywords of the digital economy during 1992–2022. Note: # indicates a flag for the cluster name.
Table 1.
The institutions of the world’s top 10 digital economy research publications.
Table 1.
The institutions of the world’s top 10 digital economy research publications.
SortInstitutionArticlesSortInstitutionArticles1Elsevier15326IEEE6062Springer Nature7607Wiley4753Taylor & Francis7488Oxford Univ Press2934Sage6859Emerald Group Publishing1805MDPI63910IOP Publishing Ltd.175
Table 2.
The regional distributions of the top 10 digital economy research publications.
Table 2.
The regional distributions of the top 10 digital economy research publications.
SortCountry/RegionArticlesSortCountry/RegionArticles1Spain16016South Korea6952USA16017Germany6603England14298Italy4294Peoples R China10339France3945Australia89910Canada316
Table 3.
Fund distributions of top 10 digital economy research publications.
Table 3.
Fund distributions of top 10 digital economy research publications.
SortFundArticles1Spanish Government8332UK Research Innovation UKRI7953European Commission6934Ministry of Knowledge Economy MKE Republic of Korea4905Engineering Physical Sciences Research Council EPSRC4856Australian Research Council4797Australian Government4248National Natural Science Foundation3859CGIAR34510National Science Foundation337
Table 4.
Statistics of the top 10 journals in digital economy research.
Table 4.
Statistics of the top 10 journals in digital economy research.
SortJournalArticles1Sustainability3092Monthly Notices of the Royal Astronomical Society1673Astronomy Astrophysics1514Astrophysical Journal765Technological Forecasting and Social Change746IEEE Access647Environment and Planning an Economy and Space618New Media Society619PLOS ONE6010Sensors54
Table 5.
The top 10 authors and their H index.
Table 5.
The top 10 authors and their H index.
SortAuthorH-indexArticles1Garcia-Hernandez, Domingo Anibal54512Zamora Olga41413Galbany Lluis52384Prieto Carlos Allende81385Falcon-Barroso, Jesus58346Anderson, Brian D O72327Majewski, Steven R.83328Cunha, Katia50309Cristobal-Hornillos, D.193010Garcia-Benito, Ruben4130
Table 6.
The top 3 teams in terms of publication volume.
Table 6.
The top 3 teams in terms of publication volume.
SortTeam NameArticles1CALIFA Collaboration142CALIFA Team23TRB2
Table 7.
Analysis results of international hot keywords from 1992 to 2022.
Table 7.
Analysis results of international hot keywords from 1992 to 2022.
SortKeywordsFrequencySortKeywordsFrequency1Model3686Digital sky survey2692System3347Performance2483Technology3098Information2394Impact2869Economy2275Innovation27410Management224
Table 8.
Keywords clustering of the digital economy research from 1992 to 2022.
Table 8.
Keywords clustering of the digital economy research from 1992 to 2022.
SortCluster NamesSizeKeyword Enumeration (LLR Algorithm Results)#0Remote sensing152Machine learning; Digital elevation model; Design; Behavior algorithm; Classific energy;#1Gig economy142Gender; Digital media; Community; Labor;#2Circular economy139Industry 4.0; Sustainable Development; Integration;#3Sharing economy126Galaxies: structure; Stellar content; Formation; Knowledge;#4Galaxies: evolution124Galaxies: evolution; Evolution; Galaxies: stellar content;#5Economy grown92Power amplifier; Performance; Environment; Digital sky survey;#6Digital technology48Energy consumption; Efficiency; Economic development;#7News11Mobile; Awareness; Journalism; Age;
Table 9.
Hot spots and frontiers of the international digital economy from 1992 to 2022.
Table 9.
Hot spots and frontiers of the international digital economy from 1992 to 2022.
SortPop WordsAbruptnessStarting Year Big data analytics720202Supply chain management6.120203Digital platform5.720204Supply chain5.620205Gig economy5.32020
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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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Zeng, S.; Yang, H. A Bibliometric and Visualization Analysis of Knowledge Mapping in Digital Economy Research, 1992–2022. Sustainability 2023, 15, 6565. https://doi.org/10.3390/su15086565 AMA StyleZeng S, Yang H. A Bibliometric and Visualization Analysis of Knowledge Mapping in Digital Economy Research, 1992–2022. Sustainability. 2023; 15(8):6565. https://doi.org/10.3390/su15086565 Chicago/Turabian StyleZeng, Shaolun, and Huili Yang. 2023. "A Bibliometric and Visualization Analysis of Knowledge Mapping in Digital Economy Research, 1992–2022" Sustainability 15, no. 8: 6565. https://doi.org/10.3390/su15086565 Find Other Styles Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here. Article Metrics No No Article Access Statistics For more information on the journal statistics, click here. Multiple requests from the same IP address are counted as one view. Zoom | Orient | As Lines | As Sticks | As Cartoon | As Surface | Previous Scene | Next Scene Cite Export citation file: BibTeX | EndNote | RIS MDPI and ACS StyleZeng, S.; Yang, H. A Bibliometric and Visualization Analysis of Knowledge Mapping in Digital Economy Research, 1992–2022. Sustainability 2023, 15, 6565. https://doi.org/10.3390/su15086565 AMA StyleZeng S, Yang H. A Bibliometric and Visualization Analysis of Knowledge Mapping in Digital Economy Research, 1992–2022. Sustainability. 2023; 15(8):6565. https://doi.org/10.3390/su15086565 Chicago/Turabian StyleZeng, Shaolun, and Huili Yang. 2023. "A Bibliometric and Visualization Analysis of Knowledge Mapping in Digital Economy Research, 1992–2022" Sustainability 15, no. 8: 6565. https://doi.org/10.3390/su15086565 Find Other Styles Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here. clear Sustainability, EISSN 2071-1050, Published by MDPI RSS Content Alert Further Information Article Processing Charges Pay an Invoice Open Access Policy Contact MDPI Jobs at MDPI Guidelines For Authors For Reviewers For Editors For Librarians For Publishers For Societies For Conference Organizers MDPI Initiatives Sciforum MDPI Books Preprints.org Scilit SciProfiles Encyclopedia JAMS Proceedings Series Follow MDPI LinkedIn Facebook Twitter
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