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Improving construction projects' performance through innovative approaches such as lean construction (LC) and offsite construction (OSC) methods are at the centre of various debates. However, there is a limited understanding of the current link between LC and OSC approaches. This study aims to conduct a scientometric analysis on LC and OSC research to unpack and establish the nexus and suggest future research focus.

Scientometric analysis was used to systematically examine existing literature on LC and OSC to identify possible connections. Relevant publications were extracted from the Scopus database, using inclusion and exclusion criteria. VOSviewer software was used as a visualisation technique to analyse and map the interrelations and connections of the concepts being studied. Bibliograhic data on the 68 selected papers were extracted from the Scopus database.

The search results cover the period between 2003 and 2021. Descriptive statistics show that the number of published papers has increased yearly. Researchers in the USA and Canada are the most productive authors regarding the number of published papers. The directions for future research suggested are the need to identify best practices for integrating LC and OSC methods, the need for more interdisciplinary and cross-country collaboration among researchers, the use of alternative research methods will provide a better understanding of the benefit of integrating LC and OSC techniques and more research is needed to showcase how the use of lean and offsite construction can facilitate the attainment of net-zero in the construction industry.

This study provides insights into the trends and gaps in knowledge on integrating LC and OSC methods and offers valuable insights to scholars and practitioners in integrating LC and OSC principles. This knowledge is vital for identifying strategies to improve the outcome of construction projects and contribute to the sustainable socio-economic development of cities across the globe.

This study provides a comprehensive analysis of the transition from Building Information Modelling (BIM) to digital twins (DT) in the construction industry. Specifically, the research explores the current state (themes and trends) and future directions of this emerging research domain.

A multi-stage approach was employed that combines scientometric and systematic review approaches. The scientometric analysis involves quantitative assessment of scientific publications retrieved from the Web of Science database – using software tools like VOSviewer and HistCite. The systematic review involved a rigorous synthesis and evaluation of the existing literature to identify research gaps, themes, clusters and future directions. Clusters obtained from the scientometric analysis of the co-occurrence network were then used as a subject base for a systematic study.

Emergent findings reveal a rapidly growing interest in BIM-DT integration, with over 90% of publications since 2020. The United Kingdom, China and Italy are the leading contributing countries. Five prominent research clusters identified are: (1) Construction 4.0 technologies; (2) smart cities and urban environments; (3) heritage BIM and laser scanning; (4) asset and facility management; and (5) energy and sustainability. The study highlights the potential of BIM-DT integration for enhancing project delivery, asset management and sustainability practices in the built environment. Moreover, the project’s life cycle operation phase has garnered the most attention from researchers in this field compared to other phases.

This unique study is comprehensive in its approach by combining scientometric and systematic methods to provide a quantitative and qualitative evaluation of the BIM-DT research landscape. Unlike previous reviews that focused solely on facility management, this study’s scope covers the entire construction sector. By identifying research gaps, challenges and future directions, this study establishes a solid foundation for researchers exploring this emerging field and envisions the future landscape of BIM-DT integration in the built environment.

This study aims to present state-of-the-art research on circular economy (CE) implementation in construction and demolition waste management (CDWM) within the construction sector.

A mixed-method (scientometric and critical analysis) review strategy was adopted, involving scientometric and critical analysis to uncover the evolutionary progress within the research area, investigate key research themes in the field, and explore ten issues of CE in CDWM. Moreover, avenues for future research are provided for researchers, practitioners, decision-makers, and planners to bring innovative and new knowledge to this field.

A total of 212 articles were analyzed, and scientometric analysis was performed. The critical analysis findings reveal extensive use of surveys, interviews, case studies, or mixed-method approaches as study methodologies. Furthermore, there is limited focus on the application of modern technologies, modeling approaches, decision support systems, and monitoring and traceability tools of CE in the CDWM field. Additionally, no structured framework to implement CE in CDWM areas has been found, as existing frameworks are based on traditional linear models. Moreover, none of the studies discuss readiness factors, knowledge management systems, performance measurement systems, and life cycle assessment indicators.

The outcomes of this study can be utilized by construction and demolition sector managers, researchers, practitioners, decision-makers, and policymakers to comprehend the state-of-the-art, explore current research topics, and gain detailed insights into future research areas. Additionally, the study offers suggestions on addressing these areas effectively.

This study employs a universal approach to provide the current research progress and holistic knowledge about various important issues of CE in CDWM, offering opportunities for future research directions in the area.

Industries throughout the world have gone through four phases of the industrial revolution. Today, the authors are encountering the Fourth Industrial Revolution (Industry 4.0 or 4IR), which is characterized by the application of information and communication technologies in the industry. This study aims to evaluate the growth of literature in the context of libraries and the Fourth Industrial Revolution and then identify the active research actors, countries, affiliations and sources and the status of collaboration across various geographical locations.

A systematic literature review was conducted. The data were extracted from the Scopus database incorporating scientometric and altmetric indicators. The search terms were TITLE-ABS-KEY “Industry 4.0” OR “4IR” OR “Fourth Industrial Revolution” AND “Library 4.0” OR “librarian 4.0” OR “libraries” OR “library” OR “library service” without any limitation. The results identified 218 documents out of which 67 core documents are related to libraries. Analysis was performed using MS Excel and VOSviewer.

South Africa, Nigeria and South Korea were the three most productive countries in the field. Library Hi Tech News is the most productive journal. Collaboration among African countries like South Africa, Nigeria and Zimbabwe seems to be good and they constituted the largest share of documents. The research on the Fourth Industrial Revolution in the context of libraries still lacks social media attention.

This study is the first systematic review in this area using a combination of scientometrics and altmetrics. The results will serve as a valuable reference for future researchers and policymakers.

Recent emerging information technologies like digital twin (DT) provide new concepts and transform information management processes in the architecture, engineering and construction (AEC) industry. Although numerous articles are pertinent to DT applications, existing research areas and potential future directions related to the state-of-the-art DT in project operation and maintenance (O&M) are yet to be studied. Therefore, this paper aims to review the state-of-the-art research on DT applications in project O&M.

The current review adopted four methodological steps, including literature search, literature selection, science mapping analysis and qualitative discussion to gain a deeper understanding of DT in project O&M. The impact and contribution of keywords and documents were examined from a total of 444 journal articles retrieved from the Scopus database.

Five mainstream research topics were identified, including (1) DT-based artificial intelligence technology for project O&M, (2) DT-enabled smart city and sustainability, (3) DT applications for project asset management, (4) Blockchain-integrated DT for project O&M and (5) DT for advanced project management. Subsequently, research gaps and future research directions were proposed.

This study intends to raise awareness of future research by summarizing the current DT development phases and their impact on DT implementation in project O&M among researchers and practitioners.

The All India Institute of Medical Sciences (AIIMS) is a premier medical institution in India that has significantly contributed to cancer research. This study aims to highlight the cancer research productivity of AIIMS by assessing the impact and reach of the institution’s research output.

The study was based on 2,078 published papers on cancer of AIIMS indexed in the Web of Science (WoS) database from 1989 to 2021. A combination of tools such as Microsoft Excel, Biblioshiny, BibExcel and VOSviewer was used to evaluate and visualize the selected data.

The analysis revealed the interdisciplinary nature of research outputs, which have collaborative contributions from various fields such as oncology, pathology, radiology and surgery. The most productive research area within cancer was found to be breast cancer. In terms of international collaboration, the analysis revealed that AIIMS has a strong presence in the global cancer research community, with collaborations with researchers from more than 50 countries.

This study has some limitations. First, the study is limited to using only the WoS Core Collection database. Other databases, such as Scopus and PubMed, were excluded. Second, there is ambiguity in author names and nonuniformity in the institutions’ names, which can significantly affect the study’s outcomes.

Identifying research productivity in cancer at AIIMS aids resource allocation, collaboration and strategic planning, enhancing India’s overall cancer research impact and patient outcomes.

To the best of the authors’ knowledge, this study is to use scientometric indicators to evaluate AIIMS’s research productivity with particular reference to cancer for the first time. This detailed analysis provides a deeper understanding of AIIMS’s contribution to cancer research and its potential implications.

This study aims to contribute to the understanding of Entrepreneurship and Resource-Based View (RBV) by investigating the research landscape of Innovation Determinants (ID). Through an extensive bibliometric analysis and knowledge mapping, we explore intellectual structures, emerging trends, research hotspots, and future prospects in the field from 1990 to December 2022. Additionally, we focus on identifying top research organizations, authors, collaboration patterns, and commonly used keywords to advance knowledge and awareness in this area.

A comprehensive retrieval strategy was employed to gather 2359 articles on ID from Web of Science, covering the period from 1990 to 2022. Utilizing CiteSpace as a visualization tool, we visually represent authors, institutions, and keywords. By examining knowledge maps using various indicators, we showcase the intellectual foundation and current research frontiers within the domain of ID.

Our findings reveal significant progress in academic research on ID over the past three decades, with a substantial number of 2359 published articles in the field. This signifies considerable advancement in exploring ID. The analysis of the co-authorship network presents a network of 406 authors represented as nodes and 112 collaborative interactions as links. The network's density indicates that only a minute 0.14% of the potential connections in the ID network have been established, highlighting the need for more cohesive and extensive global collaborations in this field.

This paper's originality lies in its temporal and dynamic examination of the past thirty years, utilizing CiteSpace for co-citation and co-occurrence network analysis. Additionally, the scientometric analysis reveals key co-occurring keywords, providing insights into the conceptual characteristics within the research field.

The purpose of this study is to examine the Google Scholar (GS) and Scopus citations profiles of library and information science (LIS) faculty members employed in central universities in India to determine their research online visibility.

The data was collected through manual searches conducted on GS and Scopus profiles by the end of August 2023, using the names of the faculty members along with their affiliations. The determination of the minimum sample size for each was calculated based on Cochran’s formula.

The study revealed that out of 104 LIS faculty members from 19 central universities, 78 (75.0%) faculty members have profiles on GS, while 61 (58.6%) of them are on Scopus. The study found that the faculty members have a substantial number of publications on GS, while their publication count on Scopus appears comparatively lower. The results suggest that certain faculty members have produced a modest number of publications but have received a substantial number of citations compared to their colleagues. Consequently, it can be inferred that there is no straightforward correlation between the volume of publications and citation metrics.

As the study exclusively focused on LIS faculty members working within central universities in India who have profiles on GS and Scopus, the researchers did not reach all LIS faculty members in India.

The significance of this research lies in its potential of insights into research productivity and its impact, which are crucial aspects of academia. The study provides valuable insights for individual researchers, LIS departments, institutes and universities in India and other countries to enhance their research performance and foster collaboration by establishing new research guidelines.

There have been no published research studies regarding the GS and Scopus citation metrics concerning LIS faculty members across all central universities in India.

This paper aims to explore the global trends and status of drone journalism through a systematic bibliometric analysis, aiming to provide a comprehensive understanding of the field's evolution, impact and interdisciplinary nature.

This study uses established bibliometric tools and frameworks to systematically review scholarly publications related to drone journalism. Using the Dimensions.ai database, a systematic mapping of the intellectual landscape of drone journalism research is conducted. Bibliometrix package of R Studio was used in the study.

The analysis reveals a progressive growth in drone journalism research over the years. Although research output consistently increases, variations in impact, measured by citations and online engagement, are observed. Missing data and contextual factors necessitate careful interpretation, but trends suggest an evolving field with diverse interests and future exploration opportunities. Drone journalism research exhibits interdisciplinary characteristics, with impact varying across different research categories. The distribution of research across various publication types underscores the diversity of scholarly communication channels in the field.

This study acknowledges limitations in its data set, stemming from specific keyword criteria, potentially limiting the comprehensive capture of all drone journalism research.

This study offers valuable insights for researchers, practitioners and policymakers seeking to navigate the dynamic landscape of drone journalism. The understanding of publication patterns, influential authors and interdisciplinary intersections facilitates informed decisions regarding research dissemination and impact maximization.

This research contributes to the evolving field of drone journalism by providing a holistic view of its trends and status. The identification of prolific authors, influential publications and evolving research themes offers valuable context for understanding the multifaceted nature of drone journalism research.

The study aims to analyse the race towards green development and United Nations sustainable development goals (SDGs) in the cases of Huawei and Shell. Both companies are the leaders in their respective industries. Huawei is an example case study representing the information and communications technology (ICT) industry whereas Shell is an example case study representing the oil and gas industry. The research analyses of the races in achieving UN SDGs were undertaken based on the innovation diffusion framework with the use of machine learning algorithms trained to extract data on sustainability activities and initiatives.

The research analyses the two case studies of Huawei and Shell. The research was undertaken through the steps of training machine learning algorithms, industry benchmarking and evaluating the performance of the race. The analyses regarding the activities and initiatives of Huawei and Shell in contributing towards SDGs are based on the data in the past 10 years (Years 2010–2019) using machine learning to extract data on sustainability activities and initiatives. In the case of Huawei, 313 sustainability reports were fed to the unsupervised machine learning algorithms revealing 15,101 sustainability actions and initiatives related to UN SDGs in the ICT industry. In the case of Shell, 2,015 sustainability reports were fed to the unsupervised machine learning algorithms revealing 47,365 sustainability actions and initiatives related to UN SDGs in the oil and gas industry.

The analyses of findings revealed that Huawei and Shell performed very well in progressing towards the UN SDGs. Huawei had strong performance in the ICT industry with regard to SDGs No. 3, 4, 7, 8, 11, 12 and 16 while Shell had strong performance in the oil and gas industry with regard to SDGs No. 3, 4, 6, 7, 8, 12 and 16. Both companies had placed a focus on achieving SDG 12 responsible consumption and production, SDG 7 affordable and clean energy and SDG 4 quality education. The synthesised business model innovations of Huawei and Shell had shown their environmental, social and governance strategies – Huawei’s 2030 vision for green development and Shell’s 2050 vision for net zero emissions.

The five pillars of people, planet, prosperity, peace and partnership according to the UN 2030 agenda for sustainable development have shown the way a company operates to promote sustainable eco-systems. The extent to which both Huawei and Shell link corporate strategies to the UN SDGs has reflected their implementation progress. Furthermore, the business model innovations of Huawei and Shell provides a useful framework which can be applied to encourage other companies/organisations in various industries to undertake ESG activities in practice.

The main contribution of this research is the application of machine learning algorithms and the innovation diffusion model in analysing the SDGs performance. The study applies the innovation diffusion framework to explore strategic actions and initiatives of Huawei and Shell in transitioning towards sustainability. The use of machine learning algorithms has identified their sustainability approach in achieving the UN SDGs.