Keyword Co-occurrence Network Research Articles

Do ESG Practices Promote Financial Performance? Comparison of English, Chinese, and Korean Papers Through Bibliometric and Meta-Analysis

Companies engaged in ESG practices to enhance financial performance and demonstrate a commitment to sustainable development. However, the relationship between ESG and financial performance remained unclear, as prior studies were replete with contradictory paradoxes. This study aimed to comprehensively analyze the evolution of ESG practices and their impact on financial performance by comparing English, Chinese, and Korean papers. This study employed a mixed-methods approach and conducted a bibliometric analysis on 2659 ESG-related papers to unveil temporal trends and conduct a meta-analysis. Stratifying by language, linguistic and cultural nuances influencing the relationship were identified. The bibliometric analysis revealed a significant turning point in ESG research around 2019, marked by a surge in publications across languages. Keyword co-occurrence networks highlighted distinct focal points, with financial performance appearing in all the research themes. The meta-analysis indicated a low overall positive correlation between ESG and financial performance. However, Chinese and Korean papers demonstrated a moderate correlation, while English papers showed no significant correlation. This study informed scholarly, managerial, and policy discourse on sustainable business practices, contributing to the evolving ESG landscape.

Mindfulness at Work: A Bibliometric Analysis of Key Authors, Themes, and Trends

Background: Mindfulness in the workplace has gained significant attention for its potential to enhance well-being, reduce stress, and improve productivity. As interest in workplace mindfulness has grown, a need arises to systematically analyze the influential studies, key authors, themes, and trends shaping this field. Objectives: This study aims to map the intellectual landscape of "mindfulness at work" through a bibliometric analysis, identifying key contributions, collaboration networks, thematic clusters, and publication trends over time. Methods: Utilizing data from Lens.org, we conducted a bibliometric analysis using VOSviewer and WordSift tools to examine co-authorship, keyword co-occurrence, and citation networks, as well as keyword frequency and thematic trends. Findings: The analysis identifies central figures such as Jochen Reb and Christopher J. Lyddy and highlights prominent themes including well-being, stress management, and engagement, with a peak in publication interest around 2019. The study also reveals isolated research clusters, suggesting limited interdisciplinary integration within the field. Conclusion: While mindfulness research at work is growing, opportunities exist for deeper cross-disciplinary collaboration and broader integration of themes. Novelty: This study provides a comprehensive overview of the field’s development, offering insights into emerging trends, key influencers, and areas for future exploration, making it a valuable resource for researchers, practitioners, and policy-makers interested in advancing workplace mindfulness.

A bibliometric analysis of research on physical activity and fitness among preschool children in Asia (2020-2024)

Background: Physical activity (PA) and physical fitness (PF) are essential for preschool children's development. However, rising childhood obesity and sedentary lifestyles are concerning. A comprehensive analysis of the research landscape is necessary to inform better interventions and policies. Research Objectives: This study aims to conduct a bibliometric analysis of research on physical activity and physical fitness among preschool children in Asia from 2020 to 2024. Methods: The analysis was based on publications from Scopus and Web of Science, focussing on keyword co-occurrence, citation analysis, and co-authorship networks. We used tools like ScientoPy and VOSviewer to assess key metrics such as the number of publications, citations, and influential contributors. Findings/Results: The study reveals significant trends, with a peak in research productivity in 2022, reflecting heightened global attention on early physical health. China, Japan, and Iran led contributions, with China dominating in publication volume. Notable researchers included Saeed Ghorbani and emerging contributors Ahmad Chaeroni and Amir Dana. Leading journals, such as the International Journal of Environmental Research and Public Health and Frontiers in Public Health, were prominent sources. Conclusion: Despite a decline in productivity post-2022, PA and PF research for preschoolers remains important. These shifting trends provide opportunities for researchers to explore new areas or innovate approaches. Significant contributions from Asian researchers also indicate a geographic shift in the global research focus. This study also highlights the importance of physical activity in preschoolers and how trends in scientific publications can help policymakers formulate more effective interventions to improve children's fitness.

Visual analysis of postmortem interval estimation trends and collaborative networks: a 15-year study (2006-2020).

Utilizing a visual analysis of the literature on postmortem interval (PMI) estimation indexed by Web of Science (WOS), this study investigates developmental trends and research hot points across each 5-year period from 2006 to 2020. Additionally, collaborative efforts among authors, countries, and institutions were examined. Research hot points, high-frequency keywords, authors, countries and institutions in relevant papers were analyzed using CiteSpace.5.7.R2 information visualization analysis software over the past 15 years. The literature related to PMI estimation has witnessed consistent growth over time. In the keyword co-occurrence network, several impactful terms stand out, including blowfly, mitochondrial DNA, and emerging concepts like virtual autopsy. Technological advancements, such as RNA stability analysis and virtual autopsy tools, have played a pivotal role in shaping the direction of PMI research. Scientific research institutions dominate the high-frequency affiliations within the institutional cooperative network. Additionally, the country cooperative network exhibits a trend of co-occurrence and multi-clustering. As science and technology continue to advance, traditional PMI estimation methods mature while novel interdisciplinary approaches drive innovation. By identifying emerging trends and research hotspots, this study provides a roadmap for future investigations, guiding researchers toward new opportunities in PMI estimation.

The carrot cyst nematode Heterodera carotae: a major plant-parasitic nematode requiring more investigation

Summary The present study reviews the knowledge to date on the carrot cyst nematode Heterodera carotae, which has become the primary threat to the carrot sector following the withdrawal of the last chemical soil fumigants in Europe. A keyword co-occurrence network was used to structure this review into five research areas: i) biology and epidemiology of H. carotae; ii) molecular identification and phylogeny; iii) population genetics and genomics; iv) control methods and strategies; and v) root exudates and hatching stimulation. Our findings indicate that H. carotae is an under-studied plant-parasitic nematode species, with several identified alternative control methods that require further investigation.

A Review on Machine Learning-Aided Hydrothermal Liquefaction Based on Bibliometric Analysis

Hydrothermal liquefaction (HTL) is an effective biomass thermochemical conversion technology that can convert organic waste into energy products. However, the HTL process is influenced by various complex factors such as operating conditions, feedstock properties, and reaction pathways. Machine learning (ML) methods can utilize existing HTL data to develop accurate models for predicting product yields and properties, which can be used to optimize HTL operation conditions. This paper presents a bibliometric review on ML applications in HTL from 2020 to 2024. CiteSpace, VOSviewer, and Bibexcel were used to analyze seven key bibliometric attributes: annual publication output, author co-authorship networks, country co-authorship networks, co-citation of references, co-citation of journals, collaborating institutions, and keyword co-occurrence networks, as well as time zone maps and timelines, to identify the development of ML in HTL research. Through the detailed analysis of co-occurring keywords, this study aims to identify frontiers, research gaps, and development trends in the field of ML-aided HTL.

Identifying and Visualizing Global Research Trends and Hotspots of Artificial Intelligence in Medical Ultrasound: A Bibliometric Analysis.

Applications of artificial intelligence (AI) in medical ultrasound have rapidly grown in recent years. Therefore, it is necessary to identify and visualize global research trends and hotspots of AI in medical ultrasound to provide guidance for further exploitation. This study aims to highlight the global research trends and hotspots of the top 100 most-cited papers related to AI in medical ultrasound by combining quantitative and visualization methods. Articles on AI in medical ultrasound were selected from the WoSCC database and ranked by citation count. After identifying the 100 most-cited papers, we conducted a quantitative and visualized analysis of bibliometric characteristics, including leading research countries, prominent institutions, key authors and journals, author clusters and collaborations, and keyword co-occurrence network analysis. The top 100 highly cited papers from the WoSCC database were published between 1999 and 2021, with total citations ranging from 91 to 1580. The most cited article was published in IEEE Transactions on Medical Imaging. The top three most prolific countries/regions were the United States, mainland China, and the United Kingdom. The most published institutions and journals were Idaho University and IEEE Transactions on Medical Imaging. Twelve authors published more than four papers, with Suri, JS being the most productive author. The most studied topics were "ultrasound", "computer-aided diagnosis", and "segmentation". Ultrasonography of Superficial Organs was the main site that was studied the most. This study provides comprehensive insights into the characteristics of AI in medical ultrasound through quantitative and visualized analysis of the most highly cited literature. It serves as a valuable reference for the development and applications of AI, fostering potential collaborations within this domain.

Recent Global Trends and Hotspots in Occipitocervical Fusion: A Bibliometric Analysis and Visualization Study

Occipitocervical arthrodesis has a variety of indications to treat craniocervical and atlantoaxial pathologies for which a selective cervical fusion would not provide sufficient stability. Over time, the indications for occipitocervical fusions (OCF) have evolved, as new technologies and surgical techniques were developed. In this bibliometric analysis, we aim to explore the progression of OCF literature over time, analyzing the trends in publications and citations, publishing countries and authors, keywords and topics. The Web of Science database was used for data retrieval on July 3rd, 2024, with the search "occipitocervical fusion" OR "occipito-cervical fusion" OR "occipitocervical arthrodesis" OR "occipital cervical fusion" OR "occipital cervical arthrodesis" OR ("OCF" AND "spine surgery"). Excel was used to create the citation analysis and publication trend figures, along with the publishing countries and author analysis. The bibliometric software VosViewer was used to generate the keyword co-occurrence network visualizations. Overall, 762 articles were extracted. The number of pertinent publications and citations increased until 2020 before beginning to decrease. We found that Ehlers Danlos syndrome (EDS) has become a more prevalent topic, as the association between EDS and craniocervical instability has received further scrutiny. "Dysphagia" continues to be a commonly cited topic, while, conversely, rheumatoid arthritis has decreased in publication frequency, possibly related to advances in medical management and surgical techniques. Overall, the United States of America, China, and Japan are the top publishing countries. This analysis of OCF literature provides a helpful overview of emerging trends and clinician concerns, especially as seen through the perspective of time.

The Research Development Track of Internet of Things in the Application Area of Communication Technology

Computer networks, mobile media, and information and communication technology (ICT) have grown progressively, and the development of communication technology is closely connected with that of ICT. This study explored the role played by the Internet of Things as ICT develops. Accordingly, through main path analysis and keyword co-occurrence network analysis, this study was designed to learn the major research development track, cluster status, and future research and development of the Internet of Things in the application area of communication technology.

A Review of Renewable Energy Investment in Belt and Road Initiative Countries: A Bibliometric Analysis Perspective

Since the proposal of the “Belt and Road” initiative (BRI) in 2013, China’s renewable energy investments in the countries along the route have shown rapid growth and diversification. These investments have shifted from initial product exports and engineering contracts to deeper equity investments and financing cooperation. They not only promote a global energy structure transformation towards green and low-carbon development but also bring significant economic growth and social progress to the participating countries. This study aims to systematically review the research status and trends of renewable energy investments in “Belt and Road” countries through comprehensive bibliometric analysis. Utilizing the Web of Science database and VOS viewer 1.6.17 software for visualization, this research reveals the publication trends, high-impact articles, institutional collaborations, and author networks in this field. Additionally, through keyword co-occurrence network analysis, three core research themes are identified: investment motivations, synergy effects, renewable energy consumption, and international cooperation. This systematic bibliometric analysis not only outlines the current research landscape but also provides important insights for identifying emerging research directions, thereby supporting more in-depth investigations into renewable energy investments within the “Belt and Road” initiative.

Bibliometric analysis of Indian research trends in air quality forecasting research using machine learning from 2007–2023 using Scopus database

Machine-learning air pollution prediction studies are widespread worldwide. This study examines the use of machine learning to predict air pollution, its current state, and its expected growth in India. Scopus was used to search 326 documents by 984 academics published in 231 journals between 2007 and 2023. Biblioshiny and Vosviewer were used to discover and visualise prominent authors, journals, research papers, and trends on these issues. In 2018, interest in this topic began to grow at a rate of 32.1 percent every year. Atmospheric Environment (263 citations), Procedia Computer Science (251), Atmospheric Pollution Research (233) and Air Quality, Atmosphere, and Health (93 citations) are the top four sources, according to the Total Citation Index. These journals are among those leading studies on using machine learning to forecast air pollution. Jadavpur University (12 articles) and IIT Delhi (10 articles) are the most esteemed institutions. Singh Kp's 2013 "Atmospheric Environment" article tops the list with 134 citations. The Ministry of Electronics and Information Technology and the Department of Science and Technology are top Indian funding agency receive five units apiece, demonstrating their commitment to technology. The authors' keyword co-occurrence network mappings suggest that machine learning (127 occurrences), air pollution (78 occurrences), and air quality index (41) are the most frequent keywords. This study predicts air pollution using machine learning. These terms largely mirror our Scopus database searches for "machine learning," "air pollution," and "air quality," showing that these are among the most often discussed issues in machine learning research on air pollution prediction. This study helps academics, professionals, and global policymakers understand "air pollution prediction using machine learning" research and recommend key areas for further research.

Mapping Research Trends in Global Climate Change Adaptation to Flood Disasters: A Bibliometric Analysis using VOSviewer

Using a bibliometric analysis, this study aims to map the research trends and thematic developments in climate change adaptation to flood disasters. Data from 812 publications, spanning from 1996 to 2023, were retrieved from the Scopus database and analyzed using VOSviewer software to visualize keyword co-occurrence networks. The analysis identified five key thematic clusters: adaptation strategies and resilience (180 publications), urban planning and green infrastructure (150 publications), flood risk management (85 publications), early warning systems (60 publications), and socio-economic impacts such as health and displacement (100 publications). Over time, research output has significantly increased, particularly after 2015, with publications peaking at 150 in 2023. Regionally, Asia leads the research output with 200 publications, followed by Europe (180 publications) and North America (120 publications). The findings highlight a shift toward sustainable, nature-based solutions and the integration of advanced technologies such as machine learning in flood management. The increasing focus on the socio-economic dimensions of flood adaptation, particularly in vulnerable communities, underscores the need for more inclusive approaches. Future research should prioritize underrepresented regions, such as Africa and Latin America, and foster interdisciplinary collaboration to address the complex challenges of climate-induced floods.

A Latent Space Model for Weighted Keyword Co-occurrence Networks with Applications in Knowledge Discovery in Statistics

Keywords are widely recognized as pivotal in conveying the central idea of academic articles. In this article, we construct a weighted and dynamic keyword co-occurrence network and propose a latent space model for analyzing it. Our model has two special characteristics. First, it is applicable to weighted networks however, most previous models were primarily designed for unweighted networks. Simply replacing the frequency of keyword co-occurrence with binary values would result in a significant loss of information. Second, our model can handle the situation where network nodes evolve over time, and assess the effect of new nodes on network connectivity. We utilize the projected gradient descent algorithm to estimate the latent positions and establish the theoretical properties of the estimators. In the real data application, we study the keyword co-occurrence network within the field of statistics. We identify popular keywords over the whole period as well as within each time period. For keyword pairs, our model provides a new way to assess the association between them. Finally, we observe that the interest of statisticians in emerging research areas has gradually grown in recent years. Supplementary materials for this article are available online

Critical care in older adults: Research landscape and hotspots from a bibliometric perspective.

As the population ages, there will be an increasing demand for health care resources, particularly in intensive care. Therefore, critically ill older adults are receiving increasing attention and have been extensively studied. However, the research landscape, dynamic patterns, and emerging topics in this area have scarcely been reviewed. This study aimed to delve into the current status and emerging trends (publication volume and research topics) in critical care for older adults (including interventions, outcomes, and complications) using bibliometric analysis. We retrieved original articles and reviews focusing on critical care for older adults published between 2013 and 2022 from the Web of Science core database. To examine and present the research trends, we employed VOSviewer and CiteSpace software for analysis and visualization. The cooperative network of countries and institutions, cocited authorship network, cocited references, and cooccurrence network of keywords were analyzed. Overall, 6356 articles and reviews published between 2013 and 2022 were analyzed, revealing a noticeable upward trend in the number of publications focused on critical care for older adults. In total, 34,654 authors from 7989 institutions across 131 countries collaborated to publish 6356 papers related to critical care for older adults in 1715 academic journals. The United States of America and China were the top contributors in terms of research studies, while Bertrand Guidet was the most prolific author with the highest number of articles. A dual-map overlay of the literature revealed that research papers published in Molecular/Biology/Genetics and Health/Nursing/Medicine journals were frequently referenced in Medicine/Medical/Clinical journals. Older patients with coronavirus disease 2019, delirium, and frailty were new trends and developing areas of interest. This is the first bibliometric study focusing on critical care in older adults. The research topics indicate that a comprehensive geriatric assessment, tailored interventions, and specific therapeutic algorithms among older adults are recommended to improve outcomes. Furthermore, this study provides valuable insights for clinical decision-making, guideline development, and resource allocation in critical care settings.

Endometriosis and Infertility: A Bibliometric Analysis of the 100 Most-Cited Articles from 2000 to 2023

Objectives: This study aimed to conduct a bibliometric analysis of research on endometriosis and infertility, focusing on the 100 most-cited (TOP100) articles in the literature. Design: The design of this study is a bibliometric analysis. Participants/Materials, Setting, Methods: The SCOPUS database was searched using the terms “endometriosis” and “infertility.” The productivity and impact of research publications by authors, countries, and journals were assessed using the following indicators: total number of publications, total number of citations (TNC), journal impact factor, and journal citation indicator. The bibliometric analysis was conducted from January 1, 2000, to December 31, 2023, using IBM SPSS™ for Windows and VOSviewer 1.6.20. VOSviewer was used to evaluate the TNC, total number of authors/coauthors, and collaboration network between countries of the TOP100 articles. VOSviewer was also used to create keyword co-occurrence networks. Results: Of the TOP100 articles, 69 were literature review articles, with a mean of 448.97 ± 513.5 citations (range: 191–2,705). The TOP100 articles were published by 479 authors (mean 5.8 ± 7.3 per study) from 40 countries in 39 high-impact journals. The keyword co-occurrence network revealed a grouping of four clusters, with terms related to pathophysiology, clinical management, assisted reproductive technology, and hormonal treatment of endometriosis. Limitations: The main limitation of our study is the use of only one database and TNC as the main bibliometric indicator. Studies need at least 2–3 years after publication to accumulate sufficient citations for bibliometric indicators to be reliable. This means that large number of recent studies were not included in this bibliometric analysis. Conclusions: This study revealed trends in endometriosis and infertility research, especially in the fields of immunology and genetics. It also highlights the importance of global collaboration to improve diagnostics, treatments, and outcomes.

Scientometric analysis of cover crop management: Trends, networks, and future directions

This research paper presents a comprehensive scientometric analysis of English articles from the Scopus database regarding the topic of cover crop management from 1956 to March 2024. Through the analysis of the annual production trend, total production, a co-occurrence network of keywords, co-authorship networks, and co-citation networks, the data was mapped and visualized using VOSviewer and Bibliometrix software. There was an exponential increase in publications from 1991 onwards. The predominant subject was Agricultural and Biological Sciences and the most relevant journals, authors, and documents were related to this topic. Additionally, the most productive country was the United States, but in terms of article production per surface area, other countries, such as Switzerland and The Netherlands, evidence the great weight of cover crop management in these countries. The identified research topics were related to the application of different crops as cover crops and the effects on different cultivars, also soil quality improvement, and fertilization and nutrient efficiency. An emerging research topic was found to be the usefulness of cover crops as effective tools for climate change adaptation and mitigation strategies in agriculture. Future research in the field of cover crop management could be directed towards climate-adaptive cover crop species and varieties, the use of technological innovations for cover crop monitoring, and management and analysis of the economic and social impacts of cover crop adoption.

Exploring research trends and hotspots on oxidative stress and bronchopulmonary dysplasia: Insights from bibliometric and visualized study.

Bronchopulmonary dysplasia (BPD) is a severe chronic lung disease primarily affecting premature infants, often resulting from prolonged mechanical ventilation and oxygen therapy. Oxidative stress plays a critical role in the pathogenesis of BPD, contributing to lung injury, inflammation, and impaired lung development. Despite extensive research, there is a need to systematically map out the research trends and hotspots in this field to inform future studies and therapeutic strategies. This study utilized bibliometric and visualized analysis to explore global research trends and hotspots on oxidative stress and BPD from 2004 to 2024. A comprehensive literature search was conducted in the Web of Science Core Collection, focusing on publications related to oxidative stress and BPD. Tools such as VOSviewer, Citespace, and the R package Bibliometrix were employed to analyze Coauthorship, co-citation, and keyword co-occurrence networks, as well as to identify emerging research fronts and influential studies. The analysis identified 597 relevant publications, showing a steady increase in research output over the 20-year period, with a significant surge in the last decade. The United States led in research contributions, followed by China and Germany, with notable collaborations among these countries. Coauthorship analysis highlighted key research institutions, such as Harvard University and the University of California, as central nodes in the research network. Thematic clustering revealed five major research areas: antioxidant mechanisms, inflammation, molecular pathways, lung development, and therapeutic interventions. The keyword co-occurrence analysis showed a shift in research focus over time. Early studies concentrated on basic pathophysiological mechanisms, while recent research has increasingly focused on advanced molecular techniques, such as gene expression and targeted therapies. Notably, the study identified emerging research hotspots, including the role of extracellular vesicles and cellular senescence in BPD, as well as the potential therapeutic applications of antioxidants like superoxide dismutase mimetics. This bibliometric study provides a comprehensive overview of the research landscape on oxidative stress and BPD, identifying key trends, influential authors, and emerging research topics. The findings underscore the importance of continued research in this field, particularly in translating basic scientific insights into clinical applications to improve outcomes for infants affected by BPD. The study also highlights potential areas for future investigation, including the development of novel therapeutic strategies targeting oxidative stress in BPD.

Bibliometrics Analysis of Event Management in the Digital Era: Challenges and Opportunities for Event Planners

To remain competitive, event planners must stay current with the latest trends and technologies, such as virtual and augmented reality, artificial intelligence and the Internet. This paper presents a comprehensive bibliometric analysis using VOSviewer software to provide insight into the intellectual structure of knowledge using citation and co-citation networks, as well as key concepts using a keyword co-occurrence network, on the topic of opportunities and challenges faced by event planners when managing events in the digital era. The investigation begins by examining the Scopus database for articles published with keywords relevant to the topic. VOSviewer software was used for science mapping and network analysis of extracted data. This systematic field mapping helps graphically illustrate the publication evolution between 2015 and 2024 and identify the current research interests and potential directions for future research. A total of 125 articles were included comprising 44 conference papers, 39 original articles, 9 book chapters, 5 books, and 2 reviews. The United States, United Kingdom and Germany were the principal countries of origin of publications. The most frequently appearing keywords were “information management” with 116 occurrences and “network security” with 68 occurrences. The top five keywords with the greatest total link strength were information management, network security, security information and event management, cybersecurity, and intrusion detection. It is imperative that stakeholders, including funding agencies, event management organizations, researchers, and event managers, collaborate to ensure that the volume of quality research in this area keeps pace with the rapid advancements transforming the industry.

Study on the Theme Evolution and Synergy Assessment of China’s New Energy Vehicle Policy Texts

Drawing on data from 133 Chinese New Energy Vehicle (NEV) policy documents from 2007 to 2023, this study utilizes Dynamic Topic Modelling (DTM), social network analysis and a quantitative model to investigate the evolutionary path of policy themes and the coordination effects. The following results were obtained. (1) A thematic cross-sectional analysis identified six core policy themes, namely, coordinated promotion of technology and finance, industry development and safety standardisation, market service and technical support systems, promotion strategy and urban cluster development, industrial capital and safety supervision mechanisms, and policy support and market expansion. The analysis also mapped the distribution of hot spots within these themes. (2) The keyword co-occurrence network of the NEV policy indicated that the network structure evolved from an initial ‘overall dispersion–theme concentration’, comprising 16 policy themes, to an ‘overall stability–theme coordination’, consisting of 14 policy themes. (3) The coordination degrees across the three types of policies exhibited a consistent upward spiral, with the comprehensive coordination index surging from 30 in 2007 to 951 in 2023, underscoring the complementary effects among policy instruments. These conclusions offer valuable insights for government departments to understand NEV development trends and dynamically adjust policy themes accordingly.

Critical success criteria for construction projects: a systematic literature evaluation

PurposeEvaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.Design/methodology/approachThe researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.FindingsUsing the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.Research limitations/implicationsConsidering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.Originality/valueThis study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.