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Construction safety is a crucial aspect that has far-reaching impacts on economic development. But safety monitoring is often reliant on labor-based observations, which can be prone to errors and result in numerous fatalities annually. This study aims to address this issue by proposing a cloud-building information modeling (BIM)-based framework to provide real-time safety monitoring on construction sites to enhance safety practices and reduce fatalities.

This system integrates an automated safety tracking mobile app to detect hazardous locations on construction sites, a cloud-based BIM system for visualization of worker tracking on a virtual construction site and a Web interface to visualize and monitor site safety.

The study’s results indicate that implementing a comprehensive automated safety monitoring approach is feasible and suitable for general indoor construction site environments. Furthermore, the assessment of an advanced safety monitoring system has been successfully implemented, indicating its potential effectiveness in enhancing safety practices in construction sites.

By using this system, the construction industry can prevent accidents and fatalities, promote the adoption of new technologies and methods with minimal effort and cost and improve safety outcomes and productivity. This system can reduce workers’ compensation claims, insurance costs and legal penalties, benefiting all stakeholders involved.

To the best of the authors’ knowledge, this study represents the first attempt in Bangladesh to develop a mobile app-based technological solution aimed at reforming construction safety culture by using BIM technology. This has the potential to change the construction sector’s attitude toward accepting new technologies and cultures through its convenient choice of equipment.

Global construction has been affected by COVID-19 unprecedently. The construction sectors in the least developed countries are considered as vulnerable, but the covid made the countries experience the worst situation ever. To minimize the losses by effective measures, there needs to assess the COVID-19 impacts on the construction sector. So, the aim of this study is to investigate the most critical impacts of COVID-19 on construction in the least developed countries by considering the case study of Bangladesh.

The authors adopted multistep research methods, including (1) literature analysis and discussion with experts to establish a comprehensive list of COVID-19 impacts; (2) through a questionnaire survey, data were collected from 217 construction professionals by email, Google Form and Skype for quantifying the significance of covid impacts; (3) reliability of the survey checked by the Cronbach Alpha test; (4) Relative Importance Index (RII) to determine the ranks of the impacts based on their significance; (5) Interpretive Structural Model (ISM) to explore the corelations and the hierarchical structure; and (6) cross-impact matrix multiplication applied to classification (MICMAC) analysis to classify the COVID-19 impacts.

The study identified a total of 18 COVID-19 impacts on the construction sector. Among them, the job cuts, schedule delays, project suspension, cost overrun and effects on mental health are more influential and significant than others. Further, this study found that unpaid leave and job cuts are the two most fundamental impacts which influence other succeeding significant impacts. And ultimately all the impacts lead to hampering the national economy and development. Finally, MICMAC analysis suggested that unpaid leave and job cuts should be addressed first to resolve and effects on the national economy and development should be later.

This study does not consider all the COVID-19 impacts due to the relevant context and simplicity of the ISM method. Also, the respondent's attitude might be slightly different during the post-mass vaccination period.

This study will help the company's management, employees and government to develop effective strategies to understand the insight of their interrelations and ultimately overcome the identified covid effects. This will must contribute to the industry, its employees, the government and society by ensuring the national economy and development, construction operations, investment, employment and social security.

This study will contribute to the knowledge body (practitioners and researchers) by providing the list of significant covid impacts and insight into their interrelations for further deep analysis of the pandemic effects. This will also help the authorities and stakeholders in developing policies and strategies to minimize or avoid these effects and avoid future consequences due to any pandemic like covid.

The aim of this study is to gather and analyse the information regarding the level of awareness and commitment of the public as well as the organizations of Pakistan pertaining to sustainable development goals (SDGs).

A sample of 500 respondents in total including employs and general public is selected for their opinion regarding SDGs. The data was collected by personal administration of questionnaires in organizations and general public. The data has been collected from federal and provincial capitals of Pakistan. The data has been analysed using Smart PLS and the hypothesized relationships have been tested using regression analysis.

The level of awareness as well as level of commitment towards the fulfilment of SDGs varies across the cities of Pakistan according to the business volume and their affiliation with the United Nations.

This study has been conducted in Pakistan only however a cross-country implementation of the framework and comparison would have yielded more in-depth facts.

This study provides the policy makers with the ground-level data regarding the awareness and commitment of Pakistani organizations and public towards SDG fulfilment. A glance towards the attitudes of the people towards the subject could also be seen through this study. It could be further utilized and referred by other researchers for comparison with their own studies regarding SDGs.

This a comprehensive study conducted at federal and provincial level of Pakistan which has yielded ground realities towards the implementation of SDGs. The results could be used for policy making and planning at national level.

The main purpose of this study is to investigate the agriculture-induced environmental Kuznets curve (EKC) hypothesis in South Asian economies (SAE).

This study employs econometric techniques, including Westerlund cointegration tests, cross-sectional augmented distributive lag model (CS-ARDL) and Dumitrescu and Hurlin (DH) causality tests to investigate the relationship between renewable and non-renewable energy consumption, agriculture, economic growth, financial development and carbon emissions in SAE from 1990 to 2019.

The CS-ARDL test outcome supports the presence of the agriculture-induced EKC hypothesis in SAE. Additionally, through the application of the DH causality test, the study confirms a unidirectional causality running from renewable energy consumption (REC), fossil fuel consumption (FFC), economic growth (GDP) and squared economic growth (GDP²) to carbon dioxide (CO₂) emissions.

This study proposes that future research should extend comparisons to worldwide intergovernmental bodies, use advanced econometric methodologies for accurate estimates, and investigate incorporating the service or primary sector into the EKC. Such multidimensional studies can inform various methods for mitigating global climate change and ensuring ecological sustainability.

Environmental degradation has been extensively studied in different regions and countries, but SAE face significant constraints in addressing this issue, and comprehensive studies in this area are scarce. This research is pioneering as it is the first study to investigate the applicability of the agriculture-induced EKC in the South Asian region. By filling this gap in the current literature, the study provides valuable insights into major SAE and their environmental challenges.

Coronavirus disease 2019 (COVID-19) pandemic has led to unprecedented mental health repercussions in the lives of every individual including university students. Therefore, study on students’ psychological state and its associated factors during the pandemic are of importance. This study aims to discuss the aforementioned issue.

An online survey was done on a total of 207 university students of Pakistan to collect information on socio-demographic characteristics, concerns or fears amidst COVID-19 and mental distress. Validated tools; Perceived Stress Scale (PSS), Generalized Anxiety Disorder Scale (GAD-7) and Patient Health Questionnaire (PHQ-9)-Depression were used to assess stress, anxiety and depression, respectively.

Around 14% of the university students were experiencing severe stress and anxiety, while 8.2% had severe depression. The authors found that stress among university students was related to psychiatric illness or symptoms (OR = 5.1: 1.1, 22.9) and unpredictability due to the pandemic (OR = 3.7: 1.2, 11.2). The significant determinants of anxiety were psychiatric illness/symptoms (OR = 6.6: 3.4, 12.9), implementation of public health measures (OR = 3.7: 1.1, 11.6), employed mothers (OR = 2.4: 1.1, 5.0) and lack of support from university administration (OR = 2.2: 1.0, 5.0). While the factors associated with depression included psychiatric illness or symptoms (OR = 8.4: 3.3, 21.5), unpredictability due to pandemic (OR = 6.8: 2.2, 20.7), impaired social support system (OR = 3.7: 1.3, 10.4) and studying without a scholarship (OR = 2.1: 1.0, 4.4).

These findings call for an urgent need to develop appropriate interventions and educational programs that could address the psychological needs of students.

The study directs the role of university and faculty in dealing the mental health needs of the student in COVID-19 pandemic time.

Educational programs are important that could address the psychological needs of students in COVID-19 pandemic.

University students reported mental distress during COVID-19 pandemic which shows that younger people are at risk of COVID-19 repercussions. Moreover, several stressors (i.e. impaired social support system and lack of support from universities) were revealed that could be mitigated by implementing appropriate strategies.

The prime objective of this study is to examine the impact of sight cues and corporate social responsibility (CSR) activities of the Islamic banks on loyalty by improving the corporate image (CI) of the Islamic banks. This study also examines the mediating effect of a CI along with moderating impact of religion and collectivism on loyalty.

The data were obtained through the purposive sampling method by distributing questionnaires among the customers of Islamic banks. A total of 550 questionnaires were surveyed from six full-fledged commercial Islamic banks and eight Islamic windows of the commercial bank in Pakistan using variance-based structural equation modelling (partial least squares) to test the hypothesis.

The results of the study reflected that sight cues and CSR activities have a significant impact on CI and keeping the customer’s loyalty. Additionally, religion and collectivism also moderate the relationship between CI and loyalty.

From a managerial perspective, the study finding exhibits the significant effect, both directly and indirectly, of religiosity on the loyalty intention of the customers of Islamic banks. Hence, persuading the client that the bank is in complete compliance with (Shariah) will forestall their clients switching to another bank.

This study is unique in its nature because it revealed the factors that lead to customer loyalty towards Islamic banks. The study found sight cues and CSR are the new indicators used to build CIs of Islamic banks.

This study focuses on work from home (WFH) issues faced by faculty members of higher education institutes in India during the coronavirus infection (COVID-19) pandemic. The study aims to understand the impact of these issues on faculty productivity. The study also analyzes the moderating effect of information technology (IT) training on the relationship between work- from-home issues and faculty productivity.

This study is quantitative. Data were collected from 215 faculty members working in higher education institutes in India. Correlation and hierarchical regression analysis have been used to analyze the data.

The analysis revealed that online teaching, lack of technology acceptance, poor working environment and work–life conflict negatively impacts faculty productivity. Thus, IT training work as a moderator plays an important role in reducing the WFH issues mainly Online Teaching, Lack of Technology acceptance & Poor Working Enviornment by increasing faculty productivity. IT training work does not moderate the relationship between work–life conflict and faculty productivity.

This research is limited to the higher education sector; the research limits the generalization of the higher education sector's finding to other sectors.

The findings would help policymakers and educational institutes to explore the use of digital technology to break boundaries of workplace and education institutes to disseminate knowledge to a global level. The findings also help to understand how the workplace is essential for the smooth functioning of tasks of the institute.

The study will also help management, institute, organization, society and individuals to change their mindset that education can be imparted through online mode in a better way with the help of digital technology.

There is a scarcity of research work examining WFH issues in conducting mandatory online classes due to COVID-19 pandemic and COVID-19's relation to faculty productivity in the higher education sector. This study contributes to the knowledge regarding the impact of COVID-19 on faculty productivity in the education sector.

Despite growing interest in workplace spirituality (WPS) and its impact on employee behaviors, there is a dearth of literature discussing an underlying mechanism of how it affects adaptive performance. Against this backdrop, this study aims to develop and test a comprehensive model that examined the effects of WPS on adaptive performance through serial mediation of job satisfaction and emotional labor strategies.

Using a multi-stage sampling technique, the data is collected from 390 faculty members of the higher education institutions in two-time lags.

The findings indicate that spirituality practices at the workplace help to increase the adaptive performance of employees through serial mediation of job satisfaction and emotional labor strategies.

This study offers important implications to researchers as well as practitioners and highlights the significance of WPS in increasing the adaptive performance of employees.

This research is among the initial attempts to assess the impact of WPS on adaptive performance through serial mediation.

The purpose of this investigation is to identify, evaluate, integrate and summarize relevant and qualified papers through conducting a systematic literature review (SLR) on the application of recommender systems (RSs) to suggest a scholarly publication venue for researcher's paper.

To identify the relevant papers published up to August 11, 2018, an SLR study on four databases (Scopus, Web of Science, IEEE Xplore and ScienceDirect) was conducted. We pursued the guidelines presented by Kitchenham and Charters (2007) for performing SLRs in software engineering. The papers were analyzed based on data sources, RSs classes, techniques/methods/algorithms, datasets, evaluation methodologies and metrics, as well as future directions.

A total of 32 papers were identified. The most data sources exploited in these papers were textual (title/abstract/keywords) and co-authorship data. The RS classes in the selected papers were almost equally used. DBLP was the main dataset utilized. Cosine similarity, social network analysis (SNA) and term frequency–inverse document frequency (TF–IDF) algorithm were frequently used. In terms of evaluation methodologies, 24 papers applied only offline evaluations. Furthermore, precision, accuracy and recall metrics were the popular performance metrics. In the reviewed papers, “use more datasets” and “new algorithms” were frequently mentioned in the future work part as well as conclusions.

Given that a review study has not been conducted in this area, this paper can provide an insight into the current status in this area and may also contribute to future research in this field.