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Facility management gained profound importance due to the increasing complexity of different systems and the cost of operation and maintenance. However, due to the increasing complexity of different systems, facility managers may suffer from a lack of information. The purpose of this paper is to propose a new facility management approach that links segmented assets to the vital data required for managing facilities.

Automatic point cloud segmentation is one of the most crucial processes required for modelling building facilities. In this research, laser scanning is used for point cloud acquisition. The research utilises region growing algorithm, colour-based region-growing algorithm and Euclidean cluster algorithm.

A case study is worked out to test the accuracy of the considered point cloud segmentation algorithms utilising metrics precision, recall and F-score. The results indicate that Euclidean cluster extraction and region growing algorithm revealed high accuracy for segmentation.

The research presents a comparative approach for selecting the most appropriate segmentation approach required for accurate modelling. As such, the segmented assets can be linked easily with the data required for facility management.

Lean construction (LC) consists of very effective techniques; however, its implementation varies considerably from one industry to another. Although numerous lean initiatives do exist in the construction industry, the research topic related to LC implementation is still unexplored due to the scarcity of validated assessment frameworks. This study aims to provide the first attempt in developing a structural model for successful LC implementation.

This study developed a Lean construction model (LCM) by critically reviewing seven previous LC frameworks from different countries, defining 18 subprinciples grouped into 6 major principles and formulating testable hypotheses. The questionnaire was pre-tested with 12 construction management experts and revised by 4 specialized academics. A pilot study with 20 construction units enhanced content reliability. Data from 307 Moroccan construction companies were collected to develop a measurement model. SPSS V. 26 was used for Exploratory Factor Analysis, followed by confirmatory factor analysis using AMOS version 23. Finally, a structural equation model statistically assessed each construct's contribution to the success of LC implementation.

This work led to the development of an original LCM based on valid and reliable LC constructs, consisting of 18 measurement items grouped into 6 LC principles: Process Transparency, People involvement, Waste elimination, Planning and Continuous improvement, Client Focus and Material/information flow and pull. According to the structural model, LC implementation success is positively influenced by Planning and Scheduling/continuous improvement (β = 0.930), followed by Elimination of waste (β = 0.896). Process transparency ranks third (β = 0.858). The study demonstrates that all these factors are mutually complementary, highlighting a positive relationship between LC implementation success and the holistic application of all LC principles.

To the best of the authors’ knowledge, this study is the first attempt to develop a statistically proven model of LC based on structural equation modelling analysis, which is promising for stimulating construction practitioners and researchers for more empirical studies in different countries to obtain a more accurate reflection of LC implementation. Moreover, the paper proposes recommendations to help policymakers, academics and practitioners anticipate the key success drivers for more successful LC implementation.

This study aims to evaluate patterns, trends and knowledge networks within social security research. By using bibliometric analysis, the research seeks to provide a comprehensive perspective on the evolution of global social security research. The purpose extends to identifying significant contributors, collaborative clusters and multifaceted issues addressed in the field.

This study uses bibliometric analysis to assess social security research trends and knowledge networks from 2015 to 2023. Using the Web of Science database, 6,152 relevant articles are analyzed. Quantitative techniques such as coauthorship network analysis, institutional productivity rankings and keyword clustering are applied for a comprehensive understanding.

The findings indicate a rising trajectory of publications in social security research, with the USA, China and Europe emerging as top contributors. Coauthorship patterns reveal collaborative clusters with focused research interests. Prominent authors emphasize key aspects like public policy, economics, health and labor dynamics related to social security. Keyword clustering identifies nine thematic clusters, ranging from inequality and poverty to retirement and disability reforms. A thematic map visualizes overarching categories, including motor themes, basic themes, niche themes and emerging themes.

This bibliometric study offers original insights into global social security research, providing a comprehensive understanding of its evolution, significant contributors and diverse thematic issues addressed. The originality lies in the application of quantitative techniques, including coauthorship network analysis and keyword clustering, to reveal collaborative patterns and thematic clusters. The study’s value extends to facilitating evidence-based decision-making for advancing the critical domain of social security through international collaboration and impactful research aligned with societal needs.

This empirical research investigates the impact of board nationality diversity on the efficiency of banks. Additionally, our analysis examines the interacting impact of women's representation on bank boards in the correlation between nationality diversity on board and bank efficiency.

This research utilizes a dataset comprising banks operating in the MENA countries over an eight-year period. We apply diverse statistical methodologies, with Ordinary Least Squares (OLS) being the primary econometric analysis, alongside several robustness tests.

The research results offer important insights into the importance of board nationality diversity, as well as its interaction with the inclusion of women on boards. The findings indicate that having foreign directors on bank boards enhances efficiency. Furthermore, they suggest that increased women representation on boards improves the positive correlation between presence of foreign directors in boardrooms and efficiency of banks, thereby mitigating agency problems and enhancing governance practices.

These results carry substantial implications for legislators across the MENA countries. Advocating for diversity policies within banks to encourage the inclusion of foreign directors on their boards could lead to efficiency enhancements. Furthermore, policymakers might explore the implementation of quotas or directives to bolster gender heterogeneity within board appointments, ultimately fostering improved bank efficiency and bolstering competitiveness within the region.

This study breaks new ground by investigating how board nationality diversity affects efficiency of banking sector in the MENA countries. It stands out for examining the moderating role of women representation on boards, offering novel insights into how these factors interact.

Work–family conflict (WFC) is rife among construction professionals, leading to a significant negative impact on their work engagement. Building on an extant body of research, this study provides nuanced insights into the link between WFC, work–life balance (WLB) and work engagement and identifies the boundary conditions of these relationships.

Data were collected from 257 dyads of construction professionals and their immediate supervisors from a sample of five construction firms based in India using an online survey.

The results found that WLB mediates the relationship between WFC and work engagement, and the relationship is controlled by professionals' gender and perceptions of psychological contract breach (PCB). An important finding is that PCB accentuates the negative influence of WFC on work engagement via WLB. The study also reveals that the negative impact of WFC on WLB is stronger for women.

The findings are relevant for construction firms since they are primarily dominated by men and continue to struggle to attract more women professionals. The study insights provide avenues to expand existing research on the relationship between WFC and work engagement and offer managerial implications for improving construction professionals' work engagement in the high-pressure context of the construction industry.

The study significantly advances the underdeveloped literature on work–family interface, especially in the unique work settings of the construction industry, by establishing WFC as a predictor and revealing how engagement at work is affected. It highlights the importance of boundary conditions such as gender and PCB. It is one of the first to assess the relationship between WFC, WLB, PCB and work engagement among construction professionals in India.

This study aims to explore the relationships between knowledge management (KM) enablers, employee innovativeness (EI) and market development performance (MDP) in architecture, engineering and construction (A/E/C) firms.

A questionnaire survey is conducted to collect empirical data from A/E/C practitioners in Vietnam. First, factor analysis is used to identify KM enablers in A/E/C firms. Then, a framework which shows the links between KM enablers, EI and MDP is proposed. Structural equation modeling (SEM) is used to examine the proposed relationships.

This study identifies five constructs which can enable A/E/C firms to achieve effective KM implementation, including mutual trust and collaboration, organizational values and norms, information and communication systems, organizational policies and empowerment. Furthermore, the SEM results show that except for organizational policies, four remaining KM enablers significantly affect EI. It is also found that EI has a significant impact on MDP.

The findings could help A/E/C firms to know which KM enablers are critical to EI and provide a better understanding of the link between EI and MDP. Hence, they could make appropriate investments in KM practices to improve both EI and MDP.

The results of this study fill the gap in knowledge by empirically structuring the relationships between KM enablers, EI and MDP. Such results may provide A/E/C firms with useful information to enhance EI and MDP in today’s intensively competitive construction environments.

The purpose of this paper is to investigate whether audit committee characteristics, in particular audit committee size, audit committee activity and audit committee gender diversity, are associated with financial performance in Egyptian banks. The second purpose of this paper is to explore the moderating role of board gender diversity on the relationship between audit committee characteristics and financial performance.

A multiple regression analysis is used to estimate the moderating role of board gender diversity on the relationship between audit committee characteristics and financial performance of a sample of Egyptian banks during the period between 2018 and 2022.

The results indicate that audit committee size has a negative and insignificant effect impact on return on assets (ROA) and return on equity (ROE), respectively. The results also indicate that the audit committee gender diversity has a significant positive impact on ROA and ROE, respectively. Regarding audit committee activity, the number of board meetings has a negative and insignificant effect on ROA and ROE, respectively. Regarding gender diversity as a moderating variable, in general there is a positive effect of gender diversity on the relationship between audit committee characteristics and financial performance.

The study was limited to 20 banks in one country, but it sets the tone for future empirical research on this subject matter. The study also relied on one moderating variable, which is board gender diversity. This study provides an avenue for future research in the area of corporate governance and financial performance in other emerging countries, especially other African countries.

This study provides useful insights for managers and policymakers to better understand which audit committee characteristics can best encourage a company to improve financial performance. Furthermore, regulators should ensure that banks strictly adhere to corporate governance principles to build a strong banking industry capable of achieving economic development.

Banks will benefit equally from valuable qualities across demographic groupings in society by having females on the audit committee and appropriate audit committee meetings. Additionally, if audit committee members are correctly selected, banks with more females in audit committee and suitable audit committee meetings can successfully contribute to strengthening financial performance and social welfare of diverse segments of society. A culture of good banking governance must emerge to improve bank financial stability and, as a result, greater stability and economic growth.

To the best of the authors’ knowledge, the study is, perhaps, the first to examine the moderating role of board gender diversity on the relationship between audit committee characteristics and financial performance in Egyptian banks. This study adds to the literature by investigating such an issue in a developing economy that operates in a different context than those in developed countries.

The purpose of this paper is to understand the level of corruption in Somalia and the causes that lead to corruption that in turn hampers good governance.

The paper relies on the data collected from Somali’s public institutions, international actors, newspaper articles and peer-reviewed literature. The degree of corruption is assessed with the Corruption Perceptions Index by Transparency International and the Control of Corruption provided by the World Bank.

The finding shows that the level of corruption in Somalia is high and complex because of the following reasons: weak governance and poverty, culture and tradition which include favoritism based on clan membership, lack of accountability mechanism and absence political will. Measures undertaken for anti-corruption, for instance, the establishment of the National Anti-Corruption Commission and legislation for its support face barriers and challenges that include political influence, lack of capacities among the undertaking institution and lack of participation by the public.

This research adds value to the knowledge of corruption in Somalia by identifying the concrete socio-political antecedents for corruption and the problems of fighting it. This paper further presents the following detailed strategies to address corruption: enhancing the operational and financial integrity of the Independent Anti-Corruption Commission; restructuring the civil service and merging it into a merit-based system; enhancing Public Financial Management (PFM) reforms; independence of the judiciary; and sustaining development in digital technology adoption in governance and procurement.

With the rapid diffusion of the metaverse into all aspects of businesses and the education industry, scholars have predominantly focused on examining its projected benefits and harms, yet have overlooked to empirically explore its unpredictable nature, which offers an exciting realm of unexplored challenges and opportunities.

This research adopts a qualitative research design in the form of 24 interviews from a single EdTech to investigate the possibility of unexpected developments resulting from the integration of the metaverse into its solutions.

Three noteworthy observations have emerged from the analysis: technological obsolescence, resource allocation imbalance, and monoculturalism.

This research pioneers an empirical exploration of the latent outcomes stemming from metaverse adoption within EdTechs, while also introducing a novel theoretical framework termed “meta-governance,” which extends the Edu-Metaverse ecosystem.

The purpose of this study is to forecast the mechanical properties of ternary blended concrete (TBC) modified with oyster shell powder (OSP) and shea nutshell ash (SNA) using deep neural network (DNN) models.

DNN models with three hidden layers, each layer containing 5–30 nodes, were used to predict the target variables (compressive strength [CS], flexural strength [FS] and split tensile strength [STS]) for the eight input variables of concrete classes 25 and 30 MPa. The concrete samples were cured for 3–120 days. Levenberg−Marquardt's backpropagation learning technique trained the networks, and the model's precision was confirmed using the experimental data set.

The DNN model with a 25-node structure yielded a strong relation for training, validating and testing the input and output variables with the lowest mean squared error (MSE) and the highest correlation coefficient (R) values of 0.0099 and 99.91% for CS and 0.010 and 98.42% for FS compared to other architectures. However, the DNN model with a 20-node architecture yielded a strong correlation for STS, with the lowest MSE and the highest R values of 0.013 and 97.26%. Strong relationships were found between the developed models and raw experimental data sets, with R² values of 99.58%, 97.85% and 97.58% for CS, FS and STS, respectively.

To the best of the authors’ knowledge, this novel research establishes the prospects of replacing SNA and OSP with Portland limestone cement (PLC) to produce TBC. In addition, predicting the CS, FS and STS of TBC modified with OSP and SNA using DNN models is original, optimizing the time, cost and quality of concrete.