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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.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.

This paper aimed to develop a participatory methodology to analyze the disaster risk creation in coastal cities, based on an approach that combines social, urban, environmental and disaster risk elements.

The methodology uses some aspects of three theoretical approaches in a complementary way: i) the Pressure and Release (PAR) framework for the identification of dynamic pressures that contribute to disaster risk creation; ii) the application of Drivers, Pressure, State, Impact, Response (DPSIR) framework to analyze environmental dimensions; and iii) urban analysis, applying the Strengths, Weaknesses, Opportunities and Threats (SWOT) tool to classify urban processes. The methodology combined the use of satellite remote sensing data to analyze the urban sprawl and citizen science methods to collect social and environmental data, using the case study of the watershed of the Juqueriquerê River in the coastal city of Caraguatatuba, Brazil. The pilot project was part of a local university extension project of the undergraduate course on Architecture and Urban Planning and also engaged residents and city hall representatives.

The satellite remote sense data analysis indicated a continuous urban sprawl between 1985 and 2020, especially in the south of the Juqueriquerê watershed, reducing urban drainage and increasing the extension and water depth of urban flooding and riverine floods. Using citizen science methods, undergraduates identified settlements with limited economic resources to elevate houses and a lack of infrastructure to promote a resilient coastal city. After identifying the dynamic pressures that contribute to disaster risk creation and the weaknesses and strengths of a resilient city, undergraduate students proposed urban planning interventions and gray and green infrastructure projects to mitigate disaster risks.

The paper identifies urban sprawl in disaster-prone areas as one of the risk factors contributing to disaster. It also comprehensively analyzes differences between different zones in the Juqueriqere River, which will be useful for policy-making.

The method presented an interdisciplinary approach that used satellite remote sensing data and citizen science techniques to analyze disaster risks in coastal cities. The multidimensional approach used to evaluate risks is useful and can be replicated in other similar studies to gain a more comprehensive understanding of disaster risks.

This research aims to explore perceptions of subjective well-being (SWB) in public relations (PR) practitioners, focusing on dimensions of job satisfaction, networking, relationships and work–life balance, while addressing the under-researched area of gender and age – related to stages of life – disparities in SWB within the PR industry.

Employing a mixed-methods sequential explanatory design, this study utilised a survey, followed by semi-structured interviews to investigate SWB among PR professionals in Portugal, considering gender and stages of life differences.

Using a gendered and stages of life lens, this study found nuanced perceptions of SWB among Portuguese PR professionals. Older women showed higher emotional well-being but lower work evaluations than men, while young professionals exhibited less gender disparities in SWB. Men reported greater job satisfaction, emphasising passion, while women faced challenges like work overload and valued recognition. Gender differences were seen in networking, with men favouring teamwork and women valuing friendships for career advancement. Work–life balance issues, especially among older women, related to mental health.

This study contributes to filling the research gap regarding SWB in the PR industry, particularly in Portugal, offering insights into gender and stages of life dynamics that influence SWB perceptions, thereby informing strategies for enhancing well-being and productivity in PR workplaces.