Thematic Landscape Research Articles

A Bibliometric Exploration of Multiple Criteria Decision Aid and Clustering—A Conceptual Taxonomy

ABSTRACTThis work explores the intersection of Multiple Criteria Decision Aid (MCDA) and clustering techniques, revealing unexploited potential and novel perspectives arising from their integration, challenging their conventional separation. It serves as a compass, guiding researchers through a bibliometric exploration and a conceptual taxonomy consolidating existing knowledge. Employing a two‐fold methodology, we first sketch the field's contours through a bibliometric lens, uncovering its intellectual structure, thematic landscape, and social dynamics. Then, using science mapping techniques like co‐word analysis, historiography, and collaboration network analysis, we examine patterns, revealing an interconnected mosaic of concepts. Our findings unveil a natural grouping into three categories: (1) Mixed‐yet‐not‐integrated approaches, explores sequential applications—clustering followed by MCDA or vice versa—where one method precedes and informs the other. (2) ‘Relational/ordered clustering’ leveraging criteria dependency to refine structures. (3) Using MCDA to improve clustering mechanics through similarity metrics, domain knowledge incorporation, and robustness. We conclusively propose a taxonomy along three axes: Units of Analysis, Instrumentalisation, and Objective. The key takeaway emphasises the collaborative potential of MCDA, envisioning a landscape where the integration of MCDA and clustering not only enhances existing methodologies but also spawns innovative paradigms, fostering a symbiotic relationship that transcends conventional boundaries.

Mapping the Landscape of Environmental Taxation Studies with a Bibliometric Approach

This study presents a comprehensive bibliometric analysis of environmental taxation research, aiming to map the thematic landscape, identify research trends, and highlight potential areas for future investigation. Utilizing VOSviewer, the analysis encompasses 980 papers published between 1983 and 2024, revealing key themes such as economic impacts, sustainable development, emission control, and policy optimization. Temporal trends indicate a growing emphasis on integrating innovation and sustainability into environmental tax policies. Potential research areas identified include optimizing tax rates, exploring behavioral responses, and addressing equity considerations. The co-authorship network analysis highlights influential authors and collaborative clusters, suggesting opportunities for enhancing interdisciplinary research. This study provides valuable insights for policymakers, academics, and practitioners aiming to design effective environmental tax policies that address global environmental challenges.

Unraveling the Phenomenon of Construction Labor Productivity: A Cutting-Edge Bibliometric Analysis

Construction Labor Productivity (CLP) is a critical factor in the construction industry that can significantly influence the success of a project. The lack of comprehensive knowledge and proficiency in CLP and its substantial impact on project outcomes is a significant concern. CLP is a highly effective concept that can significantly improve the overall efficiency of construction projects. While it has received considerable academic attention, it is still relatively underutilized in practice. This academic analysis aims to identify trends within the CLP as revealed by a comprehensive review of existing academic research. A bibliometric analysis, complemented by a descriptive quantitative statistical methodology, was utilized to evaluate the performance metrics and delineate the thematic landscape about the subject matter of CLP. Employing distinct keywords pertinent to the CLP phenomenon and applying specific criteria for metadata exploration facilitated a comprehensive search within the Scopus and Web of Science databases. The PRISMA flowchart was employed as a systematic approach for the identification, screening, and eligibility evaluation of metadata to be incorporated into this study. The study highlights growing CLP research, led by the US and the University of Alberta. Key trends include “improvement” and “construction equipment,” with future focus on “machine learning” and “artificial intelligence.” Despite their potential, data challenges limit their use. More research is needed in developing countries to enhance construction labor productivity

Bibliometric Analysis of Studies on Sustainability in Education

This research aimed to analyze the bibliometric properties of literature on sustainability within the educational sphere. Utilizing a descriptive survey approach alongside bibliometric analysis, the study evaluated the scholarly outputs and foundational dynamics of this area. Data sourced from the Web of Science (WoS) database facilitated the examination of 1,587 articles on sustainability in education. Employing descriptive statistical methods, the study mapped out the thematic landscape of sustainability in education. It encompassed distribution assessments of scholarly works by geographical location, identified leading scholars, pivotal publications, and key journals, and conducted co-authorship evaluations to delineate the scholarly network. Moreover, analyses of trending topics and strategic diagrams, coupled with word cloud visualizations, were executed. The research unveiled those scholarly discussions on sustainability in education commenced in 1995, expanding over the ensuing three decades to encompass 1,587 articles authored by 4,169 contributors across 492 distinct outlets. The United States emerged as the foremost contributor to this body of research. Drawing on these insights, the study offered directions for future inquiries and practical applications in the field. .

Pacific accounting review in 2013–2023: a bibliometric analysis

PurposeThis literature review aims to portray the thematic landscape of the Pacific Accounting Review (PAR) from 2013 to 2023. This paper also synthesises the special issues in PAR and identifies the main research streams that facilitate contemplating the dialogic interactions between PAR and real-world challenges. Furthermore, this paper aligns these streams with the emerging concerns in Sustainable Development Goals (SDGs) and technological disruptions to propose impactful future directions for publications in PAR.Design/methodology/approachThis review adopts bibliometric analysis to establish the main research streams and objective measures for directing future publications. This paper acquires the data of 310 PAR articles from the Web of Science and ensure the data integrity before the analysis. Based on this technique, this paper also analyses PAR’s productivity, authorship and local and global impacts.FindingsOur bibliometric analysis reveals three key research streams: (1) ESG practices and disclosures, (2) informal institutions in accounting and (3) accounting in transition. This finding affirms PAR’s relevance to real-world accounting challenges. Using a thematic map, this paper portrays the current state of PAR’s topics to identify potential directions for future publications. Further, this paper proposes three future paths for PAR: (1) the research agenda for non-financial reporting, (2) research relating to and from diverse countries considering both formal and informal contemporary contextual factors and (3) the future of the evolving accounting profession.Originality/valueThis study adds value to the existing PAR reviews by extending our knowledge with the latest publications, demonstrating an objective and replicable approach, and offering future directions for PAR publications.

Key trends in the development of global public health: 2021–2023

The purpose of the study was to create a list of key thematic trends in the subject area “public health” that had taken shape by the end of 2023. Achieving the goal involved solving two tasks: a review of foreign publications devoted to the analysis of key topics in public health in 2021–2023; and the generation and analysis of a sample of the most cited publications in the internationalized public health segment over the same period.Materials and methods. The formation of a collection of foreign publications devoted to the analysis of trends in the subject area “public health” for the period 2021–2023 was carried out using the PubMed search engine and the query (“TREND*”) AND (“PUBLIC HEALTH”). 59 most relevant publications were selected for review. To create a collection of highly cited publications in the internationalized segment in the field of public health, recorded in research fronts based on the results of 2023, the Clarivate analytical resource – Essential Science Indicators (ESI) was used.Research results. Integration of the results of two stages of the study (expert assessments and the thematic landscape of a sample of the most cited publications in the field of public health) revealed a complete coincidence of 7 out of 10 trends in the development of public health at the present stage. The frontiers of the thematic area under study included the following thematic areas: the sustainability of national health systems (1), the increase in the number of mental disorders (2), the increase in the use of psychoactive substances (3), the impact of climate change on morbidity (4), the impact of environmental pollution on morbidity (5), healthy eating and food safety (6), aging population (7), sexual and reproductive health disorders (8), road traffic injuries (9), digital transformation of health (10), cancer (11), diseases of the cardiovascular system (12), an increase in infectious morbidity (13).

Exploring Federated Learning Tendencies Using a Semantic Keyword Clustering Approach

This paper presents a novel approach to analyzing trends in federated learning (FL) using automatic semantic keyword clustering. The authors collected a dataset of FL research papers from the Scopus database and extracted keywords to form a collection representing the FL research landscape. They employed natural language processing (NLP) techniques, specifically a pre-trained transformer model, to convert keywords into vector embeddings. Agglomerative clustering was then used to identify major thematic trends and sub-areas within FL. The study provides a granular view of the thematic landscape and captures the broader dynamics of research activity in FL. The key focus areas are divided into theoretical areas and practical applications of FL. The authors make their FL paper dataset and keyword clustering results publicly available. This data-driven approach moves beyond manual literature reviews and offers a comprehensive overview of the current evolution of FL.

A Bibliometric Analysis of the Challenges and Opportunities of Fintech in Promoting Access to Sharia Finance

The convergence of financial technology (fintech) and Sharia finance has garnered significant attention in recent years, promising enhanced accessibility and inclusivity in Islamic financial practices. This bibliometric analysis delves into the challenges and opportunities presented by fintech in promoting access to Sharia finance. Spanning from 2017 to 2024, the analysis encompasses 991 papers, revealing a high level of collaboration and a diverse thematic landscape. Key findings highlight the centrality of regulatory frameworks, regional dynamics, and the compatibility of fintech innovations with Sharia principles. Emerging trends, such as the exploration of innovative lending practices and regulatory oversight, underscore the evolving nature of research in this domain. The insights derived from this analysis provide valuable guidance for stakeholders invested in advancing Islamic finance and fintech innovation.

Evolução do uso de agentes conversacionais na educação empresarial: Passado, presente e futuro

Abstract Purpose: The primary objective of this article is to answer the proposed research questions by analyzing the publications on artificial intelligence (AI), education, business, and conversational agents (CAs) or chatbots within the Scopus database to identify the most frequent terms used by scholars over the years, as well as to classify the research evolution based on the most important thematic trends. Originality/value: The study contributes to the literature by offering insights into the thematic landscape of AI-related research across multiple domains. By employing a comprehensive methodology, the article provides a nuanced understanding of the intersection between AI, education, business, and CAs. Design/methodology/approach: The methodology comprises two main components. Firstly, topic modeling is applied by the year of publication to summaries of articles meeting the search criteria. Secondly, grounded theory coding was used to categorize generated themes into more meaningful classifications. This dual approach ensures a rigorous data analysis and facilitates the identification of overarching thematic trends. Findings: The results reveal five thematic trends investigated in the analyzed publications: 1. student-centered learning in higher education; 2. interactive methods using the natural language processing (NLP) approach; 3. technological solutions and ChatGPT in a university context; 4. enhancing education through intelligent platforms; and 5. challenges for social and academic integration of AI tools. Additionally, the study proposes a research agenda with some questions as future avenues of inquiry.

Landscape research: from paradigm through GIS technology to monitoring (on the example of the territory of the Slobozhansky National Nature Park)

For 10 years, a group of specialists from the department of physical geography and cartography has been exploring the territories of national parks consistently using information technology tools, improving their use in combination with ground test landscape surveys. This article reflects the experience of such scientific and applied development in relation to the territory of Slobozhansky National Nature Park. The purpose of this development is to improve the existing technologies of complex interpretation of geodata for the design and monitoring of the territory in their systematic combination with the methods of online mapping and in-depth meaningful interpretation for the scientific support of the organization of the territory and the administration of the national parks. This article covers currently known and possible scientific approaches and measures that rely on scientific and applied measures used by the national parks administration in management processes. The most recent issues highlighted in this article compared to the previous published works of the authors are the formulation of the trinity paradigm of the process of creating a landscape model of the territory. A set of individual tasks is defined, the consistent implementation of which ensures the achievement of the goal: selection of appropriate types, scales and optical ranges of remote sensing, taking into account the landscape conditions inherent in the location of the territory of the national park; development, on these grounds, of the technology of thematic landscape mapping, geoecological assessment and control of results on test areas of the terrain; peculiarities of drawing legends of applied landscape maps using GIS technologies; making corrections and additions to the existing defining documents of projects of the national park organization and developing recommendations for their improvement; design of the monitoring system of Slobozhansky National Nature Park. In the paradigm of applied landscape research, the national park should be designed based on the trinity of remote sensing and human intelligence: a) the technical level of providing remote sensing; b) taking into account the ambiguity of the optical image of the area depending on the purpose of geodata interpretation; c) tasks that are also solved ambiguously: the selection of certain ranges and scales of soundings, the selection of test areas and even the compilation of legends of a large-scale landscape map. The specified ambiguity is manifested in the variability of constructions and creates the subjectivity of applied landscape research. Methodological basis. The system-structural approach is manifested in the identification and identification of those spatial connections between visually significant and hidden from direct observation properties (mainly water-heat balance indicators) of the landscape, which change in an ambiguous dependence on regional background indicators, therefore must be taken into account in design and monitoring. Scientific results. In addition to theoretical generalizations, the article briefly presents the implementation of the highlighted approach in the study of landscapes of the Slobozhansky National Nature Park.

Mapping intellectual structures and research trends of translation studies: a bibliometric analysis from 2007 to 2021

ABSTRACT This article reports on the intellectual structures and research trends in the field of Translation Studies (TS). Co-citation analysis and keyword analysis were conducted based on research articles in eleven prestigious TS journals indexed in Web of Science-Social Science Citation Index (WoS-SSCI) database from 2007 to 2021. In general, results indicate that TS has continued to flourish over the examined 15 years, evidenced by annual research outputs, number of publications per journal, countries/regions active in TS, as well as institutions and authors producing TS research. Meanwhile, the co-citation analysis not only unveils the intellectual structures that constitute TS, but also maps several relatively clear-cut research sub-areas within TS. Furthermore, a diachronic and comparative analysis of high-frequency keywords reveals that the thematic landscape of TS has undergone profound changes, with some early-dominant topics or concepts gradually losing their initial appeal; while a series of newly developed or borrowed concepts, methods and issues have gained increased popularity. The data confirms the multidisciplinary nature and continuous ‘paradigm shifts’ of TS. Based on these results, we discuss the achievements that TS has made as well as its drawbacks, before reflecting on the implications of the analysis for the direction of future research.

AI AND THE SYMBOLIC PORTRAYAL OF MAGICAL DOORS: AN EXPLORATION OF TECHNOLOGY AND TRANSITION IN MOHSIN HAMID’S NOVEL ‘EXIT WEST’

The use of technology and symbolism in the era of contemporary literature has given rise to unique possibilities for narrative writing. ‘Exist West’ by Mohsin Hamid is one of the captivating example of this technique i.e. portraying the use of magical doors in the novel as a symbol of Artificial Intelligence (AI). This amalgamation into the storyline transcends the mundane and let the readers enter into the world of today’s digital era. The purpose of this research paper is to delve deep into the thematic landscape of ‘Exist West’ revealing the fundamental relevance of AI and the symbolism embedded in the magical doors by Mohsin Hamid. Symbolically, the use of magical doors offer an enriched narrative not only as physical gateways that leads to different locations around the globe and symbols for transition but also the role of AI associated with these magical doors. These doors also represent the essence of migration as a symbol of optimism, uncertainty and personal development. This paper goes beyond the cultural and literary framework of Mohsin Hamid’s novel ‘Exist West’ by analysing the symbolism used and the AI aspects to current world challenges.

Coverage of the Russian armed aggression against Ukraine in scientific works: Bibliometric analysis

The barbaric war of Russia against Ukraine is accompanied by the death of tens of thousands of people. Millions of Ukrainians were forced to leave their places of residence, hundreds of thousands had their homes completely destroyed, and a large part of the country's enterprises, energy and transport infrastructure was disabled. This war violates all international laws and, in fact, is a challenge to the entire civilized world. Its causes and consequences are discussed, analyzed, and considered by society and experts. Scientists do not ignore it either. The increase in publications on the topic of war and the uniqueness of this kind of research caused the desire to map the corresponding thematic landscape and identify the main trends. The methodological basis of analysis in the presented study was in-built Scopus instruments, Bibliometrix R package and Biblioshiny App, InfraNodus. The study includes two sections, namely, time section (compares publications for the entire period of the Russian armed aggression against Ukraine (2014–2023), as well as before and after the full-scale invasion (2020–2021 and 2022–2023), and geographical section (compares publications of international and Ukrainian scientific communities). The dynamics of publications, their structure by subject areas, countries, affiliations, authors, and sponsors were analyzed. According to the results of cluster, sentiment and narrative analysis, there is a shift in substantive emphasis after February 24, 2022 towards the interpretation of events as a full-scale war (52% of publications as a whole and 60% of publications by authors with Ukrainian affiliation), taking into account the consequences for the global energy, food, and other types of security. The identified structural gaps in the analyzed works create the basis for developing directions for overcoming the consequences of the war in various areas and post-war reconstruction of Ukraine.

Trends in the thematic landscape of HR analytics research: a structural topic modeling approach

PurposeThe growth of the global labor force and business analytics has significantly impacted human resource management (HRM). Human resource (HR) analytics is an emerging field that creates value for employees and organizations. By examining the existing studies on HR analytics, the paper systematically reviews the literature to identify active research areas and establish a roadmap for future studies in HR analytics.Design/methodology/approachA portfolio of 503 articles collected from the Scopus database was reviewed. The study has adopted a Latent Dirichlet allocation (LDA) topic modeling approach to identify significant themes in the literature.FindingsThe HR analytics research domain is classified into four categories: HR functions, statistical techniques, organizational outcomes and employee characteristics. The study has also developed a framework for organizations adopting HR analytics. Linking HR with blockchain technology, explainable artificial intelligence and Metaverse are the areas identified for future researchers.Practical implicationsThe framework will assist practitioners in identifying statistical techniques for optimizing various HR functions. The paper discovers that by implementing HR analytics, HR managers and business partners can run reports, make dashboards and visualizations and make evidence-based decision-making.Originality/valueThe previous studies have not applied any machine learning techniques to identify the topics in the extant literature. The paper has applied machine learning tools, making the review more robust and providing an exhaustive understanding of the domain.

Unveiling the Thematic Landscape of Generative Pre-trained Transformer (GPT) Through Bibliometric Analysis

Introduction: the Generative Pre-trained Transformer (GPT) is a deep learning language model architecture developed by OpenAI. Aim: to describe the knowledge networks (both at the theoretical and country levels) of the Generative Pre-trained Transformer (GPT) as an emerging technology. Results: 222 Documents were identified, of which 69 were articles, 50 were conference papers, 36 were editorials, 29 were notes, 19 were letters, 14 were reviews, 3 were conference reviews, and 2 were short surveys. In terms of the number of documents per year, 2 were found in 2019, 10 in 2020, 22 in 2021, 44 in 2022, and 144 in 2023. The year-on-year growth rate was over 100 % in all years. The subject area with the highest number of documents was Computer Science with 90 documents. The most productive countries in relation to GPT were the United States with 60 documents, followed by China with 19, the United Kingdom with 18, India with 15, and Australia with 12. Co-occurrence illustrated the centrality of Artificial Intelligence, Natural Language Processing, Deep Learning, and the term Human around ChatGPT and GPT. Conclusions: this bibliometric study aimed to describe the knowledge networks of the Generative Pre-trained Transformer (GPT) as an emerging technology. Although only 222 documents were found, this study revealed a high level of international scientific collaboration in the field. The results suggest that GPT is a highly relevant technology with a wide range of potential applications in natural language processing, artificial intelligence, and deep learning. Moreover, the study was able to qualitatively characterize the main thematic areas surrounding GPT, including its applications in chatbots, text generation, machine translation, sentiment analysis, and more.

Industry 4.0 Technologies in Maternal Health Care: Bibliometric Analysis and Research Agenda.

Industry 4.0 (I4.0) technologies have improved operations in health care facilities by optimizing processes, leading to efficient systems and tools to assist health care personnel and patients. This study investigates the current implementation and impact of I4.0 technologies within maternal health care, explicitly focusing on transforming care processes, treatment methods, and automated pregnancy monitoring. Additionally, it conducts a thematic landscape mapping, offering a nuanced understanding of this emerging field. Building on this analysis, a future research agenda is proposed, highlighting critical areas for future investigations. A bibliometric analysis of publications retrieved from the Scopus database was conducted to examine how the research into I4.0 technologies in maternal health care evolved from 1985 to 2022. A search strategy was used to screen the eligible publications using the abstract and full-text reading. The most productive and influential journals; authors', institutions', and countries' influence on maternal health care; and current trends and thematic evolution were computed using the Bibliometrix R package (R Core Team). A total of 1003 unique papers in English were retrieved using the search string, and 136 papers were retained after the inclusion and exclusion criteria were implemented, covering 37 years from 1985 to 2022. The annual growth rate of publications was 9.53%, with 88.9% (n=121) of the publications observed in 2016-2022. In the thematic analysis, 4 clusters were identified-artificial neural networks, data mining, machine learning, and the Internet of Things. Artificial intelligence, deep learning, risk prediction, digital health, telemedicine, wearable devices, mobile health care, and cloud computing remained the dominant research themes in 2016-2022. This bibliometric analysis reviews the state of the art in the evolution and structure of I4.0 technologies in maternal health care and how they may be used to optimize the operational processes. A conceptual framework with 4 performance factors-risk prediction, hospital care, health record management, and self-care-is suggested for process improvement. a research agenda is also proposed for governance, adoption, infrastructure, privacy, and security.

Trends in the thematic landscape of corporate social responsibility research: A structural topic modeling approach

This study provides a bird’s eye view of research on corporate social responsibility (CSR) by text-mining 14,523 articles published in reputed scholarly journals spanning the period from 1991 to 2020. This is the first study on CSR to use an unsupervised text-mining method (structural topic modeling) thereby overcoming several limitations of methods used in previous analyses. Aside from the methodological novelty, this study contributes to three distinct but related strands of literature. First, it contributes to efforts made in the prior literature to characterize the CSR concept in a novel way. Second, this study contributes to the debate on the dimensions that constitute CSR. Additionally, it provides evidence of how the focus on particular dimensions has varied over time. Third, it contributes to the debate on instrumental versus injunctive CSR by providing concrete evidence that the literature has shifted from injunctive to instrumental CSR.

A Bibliometric Analysis of Outdoor Education

The aim of this study is to map the thematic landscape of studies on outdoor education. Our process focuses on the following research question: What are the emerging topics in studies on outdoor education? Bibliometric data retrieved from the WOS database, which consists of 555 scientific publications with the keyword "outdoor education” and indexed in SCI-Expended, SSCI, A&HCI, CPCI-S, CPCISSH, BKCI-S, BKCI-SSH or ESCI, was analysed using the descriptive analysis technique. Analysis of the results revealed that there are 10 different types of publications on outdoor education and the most frequently used type is scientific articles, with 365 examples. Keyword network mapping showed that “outdoor education, environmental education and outdoor learning” were terminologies that stood out the most. The analysis of the data was visualized by VOSviewer (Version 1.6.9) visual mapping program and presented with tables and density maps in the findings section. As a conclusion, the study puts forward the main concepts that require particular attention from the outdoor educators. In addition, we hope and expect that the thematic concepts, country distribution of articles and outlining the highly cited studies of this field will contribute to paving the way for future research and identifying the gaps in the literature. This study aims to pinpoint the leading and emerging topics within the outdoor education research field, which has great importance both for the theory and practice of outdoor education.

Archive, Photography and the Language of Administration

Jane Birkin’s recently published Archive, Photography and the Language of Administration approaches one of the most critical topics in digital humanities: archives. Organized in a series of separate but connected essays, rather than formal chapters, it covers themes from the history of image archives to the social component of archives, cataloging and descriptions, technical data, performativity and finally opens up the theme of postdigital archives. Many types of archives are covered by this book, from methodical ones from natural sciences and controlling Secret Service archives to random digital snapshot archives. The book covers the history of photography and its memory, ranging in interest from glass plates and paper items to poor images such as thumbnails. It refers to original artworks and reproductions.The book’s specific focus is on the distinction but also the relationship between image and text, which Ronald Barthes introduced in his analysis of image theory, showing how text nails down the polyvalent meaning and ambiguity of the image by its precision. Moving between the formality of Foucault’s disciplinary discourse to the narrativity of Derrida, but also the rigid dualism of Barthes, Birkin sees more practical purpose in using text in both conceptual and descriptive writing, in a variety of forms, as label, tag, ekphrasis, iconographic reading, narrative, etc. Thus, the text has a triple function; it is used to “reveal, classify and to reproduce” (p. 42) the image as a document.Archive, Photography and the Language of Administration is a substantial read. Bringing up information, theories and references in significant density, it supplements and updates both previous knowledge on archives and its theories, hardly omitting any important detail in capturing the entire thematic landscape. As such, it would be a valuable source for archivists of all kinds, but furthermore it would be a great handbook for studies in the domain.

A scientometric view at real estate issues in risk management: Management research versus finance research

PURPOSE: The aim of the paper is to map the thematic landscape of real estate research in the context of risk management and to contribute to the identification and exploration of relationships between specific constructs in the management versus finance research. DESIGN/METHOD: This article applies some scientometric techniques. A combination of topic mapping has been used, as well as the author’s and journal co-citation analyses, and overlay visualisation of main and new topics in these fields. For the purposes of bibliometric analysis, the following tools and techniques have been used: trend analysis of the number of publications, citation analysis, the word co-occurrence method, and clustering (cluster analysis). The VOSviewer software and the data analysis tools available in the SCOPUS database were used for the analysis. RESULTS/FINDINGS: The main findings of this study are: the study of real estate issues in the context of risk management is a relatively new trend in academic research, which has been intensified over the past 10 years; the problems are studied mainly from the point of view of management research, financial research and engineering research; most of the leading researchers in this field combine aspects of management with aspects of finance in their studies; a relatively new trend in the study of the real estate issues in the context of risk management is the research on the use of artificial intelligence and the analysis of the impact of climate change on these processes. ORIGINALITY/VALUE: This article makes the important contribution to real estate research in the context of risk management in management research and finance research. The analyses revealed some patterns of convergence and divergence and the diversity of topics, specialisation, and interdisciplinary engagement in the context of real estate issues in the context of risk management in management and finance research, thus offering the latest insights into the state-of-the-art of the fields. KEYWORDS: real estate, risk management, scientometric analysis. JEL: G32, R39