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Unlocking the potential of Big Data Analytics (BDA) has proven to be a transformative factor for the Architecture, Engineering and Construction (AEC) industry. This has prompted researchers to focus attention on BDA in the AEC industry (BDA-in-AECI) in recent years, leading to a proliferation of relevant research. However, an in-depth exploration of the literature on BDA-in-AECI remains scarce. As a result, this study seeks to systematically explore the state-of-the-art review on BDA-in-AECI and identify research trends and gaps in knowledge to guide future research.

This state-of-the-art review was conducted using a mixed-method systematic review. Relevant publications were retrieved from Scopus and then subjected to inclusion and exclusion criteria. A quantitative bibliometric analysis was conducted using VOSviewer software and Gephi to reveal the status quo of research in the domain. A further qualitative analysis was performed on carefully screened articles. Based on this mixed-method systematic review, knowledge gaps were identified and future research agendas of BDA-in-AECI were proposed.

The results show that BDA has been adopted to support AEC decision-making, safety and risk assessment, structural health monitoring, damage detection, waste management, project management and facilities management. BDA also plays a major role in achieving construction 4.0 and Industry 4.0. The study further revealed that data mining, cloud computing, predictive analytics, machine learning and artificial intelligence methods, such as deep learning, natural language processing and computer vision, are the key methods used for BDA-in-AECI. Moreover, several data acquisition platforms and technologies were identified, including building information modeling, Internet of Things (IoT), social networking and blockchain. Further studies are needed to examine the synergies between BDA and AI, BDA and Digital twin and BDA and blockchain in the AEC industry.

The study contributes to the BDA-in-AECI body of knowledge by providing a comprehensive scope of understanding and revealing areas for future research directions beneficial to the stakeholders in the AEC industry.

This paper tries to retrospect the mounting application of machine learning (ML) and artificial intelligence (AI) in the human resource management area. The document applies bibliometric analysis and uses relational techniques to explore dimensions of documents in the field. The results highlight publication trends, most impactful authors, countries and institutes in the research area. The science mapping along with co-citation and bibliometric coupling analysis revealed major developments in the field. The thematic mapping and trend analysis highlighted the past and emerging trends towards significant and impactful research in the areas of robotics, big data, AI and data analytics. This paper sets the base for future researchers by coordinating and combining various past researches to help in understanding the evolution of ML and AI in human resource management and expansion of knowledgebase.

The purpose of this study is to conduct a bibliometric analysis to discover the published information on the effects of e-learning technologies on innovative competency development of university librarians and smart library services.

This study is based on bibliometric research methodology. The data were retrieved from the leading database Web of Science to analyze the scholarly publications on the topic during 1965–2023. VOSviewer and Biblioshiny software were used to analyze the bibliometric data on the subject.

Results displayed that the topic of e-learning technologies in the domain of librarianship has been greatly used by several authors as a title to publish their research work. The dominance of countries such as the USA, China and the UK in research output reveals their leadership in advancing research and innovation in the field of e-learning technologies for university libraries.

To the best of the authors’ knowledge, this is the first bibliometric study that has been conducted to measure the productivity of literature at the international level on the effects of e-learning technologies on innovative competency development of university librarians and smart library services.

Text classification is a widely accepted and adopted technique in organizations to mine and analyze unstructured and semi-structured data. With advancement of technological computing, deep learning has become more popular among academicians and professionals to perform mining and analytical operations. In this work, the authors study the research carried out in field of text classification using deep learning techniques to identify gaps and opportunities for doing research.

The authors adopted bibliometric-based approach in conjunction with visualization techniques to uncover new insights and findings. The authors collected data of two decades from Scopus global database to perform this study. The authors discuss business applications of deep learning techniques for text classification.

The study provides overview of various publication sources in field of text classification and deep learning together. The study also presents list of prominent authors and their countries working in this field. The authors also presented list of most cited articles based on citations and country of research. Various visualization techniques such as word cloud, network diagram and thematic map were used to identify collaboration network.

The study performed in this paper helped to understand research gaps that is original contribution to body of literature. To best of the authors' knowledge, in-depth study in the field of text classification and deep learning has not been performed in detail. The study provides high value to scholars and professionals by providing them opportunities of research in this area.

The purpose of this study is to offer insight into present dynamics and study diversification in the field of organizational psychology. This research study offers an organized and critical examination of the construct of psychological detachment using bibliometric analysis.

This study was done using the Scopus database based on studies published between 2006 and 2024. The significance of the research is evaluated by looking at the distribution volume, the trajectory of the publication, statistics techniques, extremely cited articles, journals, most frequently used keywords, research themes, subthemes clusters and thematic overview of the psychological detachment corpus created based on bibliographic coupling. Furthermore, content analysis of recent publications to identify new developments and potential gaps in the existing literature.

This research first tracked the development of this discipline’s body of literature through time and discovered a continuous rise starting in 2015. The results also highlighted crucial concepts that were studied with psychological detachment, such as work-life balance, employment outcomes, emotional exhaustion and various other demographic variables. Researchers chose to concentrate on those subtopics throughout time.

This research relied solely on Scopus data, which, despite being the largest abstract and citation database covering articles from a wide range of fields, does not include Impact Factor or Social Science Citation Index (SSCI) data, which is one of the limitation.

The findings of this research study will assist organizations and practitioners in comprehending the implications of psychological detachment construct at their workplace and give them direction on how they come out from negative job-related outcomes (employee job stress, turnover intention and burnouts at their respective workplaces).

This study offers a diversity of study topics across the psychological detachment literature by applying a variety of bibliographical mapping techniques, making it the first of its type on the topic of psychological detachment. It also indicates promising avenues for further investigation.

This research aims to provide a comprehensive understanding of the evolution and trends in psychological capital (PsyCap) research and related issues.

This research uses bibliometric analysis. A total of 2,244 journal articles were extracted from the Scopus database using relevant keywords, covering the period from 1997 to 2023. The data analysis was conducted utilizing VOSviewer software, Microsoft Excel, and an online text analysis tool.

There is a rapid rise in the quantity of PsyCap publications, especially from 2017, with significant contribution of research from Chinese scholars with 577 articles in the period 2019–2023. The antecedents of PsyCap have a stagnation of leadership-related topics and increased focus on social support and perceived organizational support. The attention has been specifically directed toward well-being and mental health, with special emphasis on work engagement, job satisfaction, and job performance.

The exclusion of certain publications in this research may overlook emerging trends. Thus, future research endeavors should adopt a multifaceted approach that combines bibliometric analysis with qualitative and quantitative methods to glean comprehensive insights into PsyCap research.

PsyCap research is growing rapidly, with more publications in the last three years than in all the previous years combined. This study, updating data until the end of 2023, provides the most up-to-date insights on research trends in PsyCap to aid scholars in discerning suitable avenues for their research endeavors.

The purpose of this study focused on a global longitudinal bibliometric mapping of research in the field of health biotechnology between 1990 and 2023 to determine who is leading this field of knowledge and to estimate the sub-disciplines that are emerging and project those that will prevail in the future.

The study identified the most relevant countries, institutions and researchers, as well as the type of scientific collaborations. The applied steps applied in the study were the following: identification and selection of keyword terms by a panel of experts; design and application of an algorithm to identify these selected keywords in titles, abstracts and keywords using Web of Science terms to contrast them; performance of JCR data processing during 2023 using R, Python and VOSviewer.

Among the most relevant conclusions of the study are the following exponential growth has been observed in the study period; new branches of knowledge have emerged in which the subjects have been acquiring their own autonomous capabilities; and R&D in this field is still concentrated in a small group of core countries, and the trend is for it to remain so due to the capacity needs required.

This contribution seeks to systematize the existing scientific knowledge in the field of biotechnology, specifically in the area of health, using the technique of scientific mapping based on a logical model of indicators that aims to determine potential thematic ramifications.

The maritime industry, a linchpin of global trade, has embarked on a transformative journey catalysed by the relentless advance of digitalisation. There is a discernible gap in the literature concerning the specific consequences of digitalisation within the maritime sector. This research aims to examine the current body of literature on the influence of digitalisation in human resource development (HRD) on the competitive advantage of organisations and its potential within the maritime industry.

This research paper conducts a comprehensive bibliometric analysis.

The findings of this research explore the literature landscape encompassing digitalisation in HRD, its influence on HR operations, learning and development, performance management, employee experience and strategic alignment within maritime organisations.

This research provides valuable recommendations for maritime organisations and HRD practitioners seeking to leverage digitalisation to gain a competitive edge. Thus, the maritime industry can adopt digital HRD practices to streamline operations, improve performance and align HR strategies with broader organisational goals.

Although intellectual capital (IC) and human dynamic capabilities (HDCs) play a significant role in decarbonization processes, their measurement and reporting is under-researched. Hence, this study aims to identify the link between HDCs, carbon accounting and integrated reporting (IR) in the transition processes, investigating IC and HDCs in decarbonization processes to achieve net-zero business models (n-ZBMs).

A systematic literature review with a concise bibliometric analysis is conducted on 229 articles, published from 1990 to 2023 in Scopus database and Google Scholar. Reviewing data on publications, journals, authors and citations and analysing the article content, this study identifies the main search trends, providing a new conceptual model and future research propositions.

The results reveal that the literature has rarely focussed on carbon accounting in terms of IC and HDCs. Additionally, firms face pressure from institutions and stakeholders regarding legitimacy and transparency, necessitating a response considering IR and requiring n-ZBMs to be developed through IC and HDCs to meet social and environmental requirements.

Not only does this study link IC with HDCs to address carbon emissions through decarbonization practices, which has never been addressed in the literature to date, but also provides novel recommendations and propositions through which firms can sustainably transition to being net-zero emission firms, thereby gaining competitive advantage and contributing to the nation’s sustainability goals.

The wine market has witnessed intensified competition across all aspects. However, there is a limited systematic assessment of wine marketing literature. This study employs bibliometric and thematic content evaluation methodologies to present a comprehensive summary and trend of the existing research in wine marketing.

This integrates bibliometric and thematic content analytical techniques to trace the evolutionary arc of wine marketing research, underpinned by a framework-based evaluation - the 4 Ws (what, where, why, and how) to give a thorough overview of wine marketing literature. We draw on the thematic structure of wine marketing research by conducting keyword co-occurrence, thematic, social network, and cluster-based content analyses. A total of 291 publications from peer-reviewed journals, spanning the years 2001–2023, were examined in the present study.

The bibliometric analysis is used to determine the most notable journals, authors, nations, articles, and themes, thereby offering a comprehensive understanding of the publication trends within the sphere of wine marketing. Based on the findings, this study advocates a research agenda to extend further contributions to the field of wine marketing.

The study performs a comprehensive analysis of the publication patterns, influential authors, and emerging trends within the wine marketing research field. It provides a unique insight into the evolution and development of wine marketing as a scholarly discipline, facilitating future research directions and knowledge advancement.