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The unique nature of the construction sector makes it fall behind other sectors in terms of productivity. Monitoring construction productivity is crucial for the construction project's success. Current practices for construction productivity monitoring are time-consuming, manned and error prone. Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity.

This study aims to investigate and assess the different techniques used for monitoring productivity in building construction projects. Therefore, a mixed review methodology (bibliometric analysis and systematic review) was adopted. All the related publications were collected from different databases, which were further screened to get the most relevant based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) criteria.

A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. Also, it was observed that current studies did not cover all the complex construction job sites and they were applied based on a small sample of construction workers and machines separately.

This review paper contributes to the literature on construction management by providing insight into different productivity monitoring techniques.

Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.

The purpose of this paper is to assess the sources of Dubai Financial Market Index volatility shocks if they are from its own or previous shocks on the one hand, or if they are out board shocks (FSTE and S&P500) on the other.

A daily time series data were collected over the period 1st January 2014-31st December 2015 and the generalized autoregressive conditional heteroskedasticity (GARCH) methodology was implemented.

Empirically, the authors find that the current volatility of Dubai Financial Market Index is largely dependent on its own shocks and part of the external shock; in particular, S&P500. However, other external volatility (FSTE) cannot contribute to this volatility. Furthermore, our findings indicate that Abu Dhabi stock Exchange (APX) affects Dubai Financial Market Index.

These results conclude that Securities Regulation Department in the federal state of United Arab Emirates had captured the effect of outside shocks from the UK only, but not from USA; this is basically due to the strong ties between the two countries. Accordingly, UAE investors seek capital outside their home country within a climate of increasing overseas’ investment options in the UK. More transparency of transactions via information technology will increase the efficiency of Dubai Financial Market.

To the best of the knowledge, this is the first work that shows the external and internal sources of volatility shocks at once; previous studies have focused almost exclusively on one type of shocks. To investigate DFM volatility shocks, the authors employed GARCH methodology; this method is an advanced econometric method and is often a preferred method to depict actual effects because it provides a more real-world context than other forms when trying to predict volatility shocks of financial instruments.

Given the persistent receptive skills challenges faced by language learners and the numerous merits of using technologically-enhanced learning in the form of mobile-assisted language learning in language teaching, this study decides to incorporate a context-analysis-practice-exploration lesson-planning framework with mobile learning to improve the receptive skills of learners. This step is necessary on the recommendation by scholarly research that while implementing technology, teacher training, digital literacy and expertise, incorporating good teaching practices and lesson planning frameworks may assist in yielding positive results.

This study decides to utilize a mixed-method research design through an experimental approach to elicit information from 90 EFL students concerning the effectiveness of incorporating the context-analysis-practice-exploration framework in a mobile-leaning mode instructional delivery to improve their reading and listening skills.

After collecting and analyzing data, the study found that while the participants perceived enhanced-mobile learning to make lessons enjoyable, integrating this framework and m-learning improved their reading skills. This study used notable findings to make pedagogical conclusions on the objective of this study.

This study contributes through empirical evidence on the effectiveness of incorporating mobile learning and a responsive lesson planning framework towards improving English as a foreign language learners' learning outcome. Besides, this study is the first to probe and unpack the effectiveness of a responsive lesson-planning framework in language education.

This paper aims to investigate the role of nature and nurture in students’ entrepreneurial intention (EIs). In doing so, the study examines the relationship between prenatal testosterone exposure (2D:4D), risk-taking propensity, entrepreneurial self-efficacy and EIs. Moreover, the moderating role of entrepreneurial education between entrepreneurial self-efficacy and EI is also investigated.

In line with previous studies on EI, the authors tested hypotheses based on quantitative data obtained from university students.

Data were analyzed with the help of the structural equation modeling technique, and the results revealed that all the hypothesized relationships were supported.

The field of entrepreneurship has become an attractive area of research for practitioners and academics. One tinted area of research in entrepreneurship is the investigation of EI because it is a good predictor of entrepreneurial behavior. Several antecedents of EIs have been recognized in the literature ranging from personality traits to environmental factors. However, less is known about the role of biology in entrepreneurship. Incorporating biological factors in the field of entrepreneurship appears to be theoretically viable and sound. Thus, this study investigates the effect of biological factors in the presence of psychological factors on EIs, which is a unique contribution to the literature on entrepreneurship.

The purpose of this study is to investigate the adoption of waqf technology (Waqftech) using blockchain smart contracts for corporate waqf crowdfunding. Despite the growing interest in Waqftech, Malaysian enterprises have not fully embraced this emerging technology because of uncertainty regarding the benefits it offers to contributors. The research incorporates two theoretical frameworks: the electronic data interchange (EDI) model for firms’ technology adoption, and the triple bottom line theory (TBL) for corporate social responsibility.

A quantitative method using a cross-sectional survey design with a five-point Likert scale questionnaire was used. Data was collected from 210 decision-makers representing small and medium-sized enterprises and analyzed using partial least squares-structural equation modeling.

The findings from this research suggest that Malaysian enterprises are influenced by both corporate and social predictive benefits when using blockchain crowdfunding, but not by environmental benefits. The adoption of blockchain smart contracts does not correlate with predictive environmental benefits because of misconceptions about the disruptive technology’s impact on biological and digital environmental preservation.

This research focuses on organizational behavior rather than individual users of waqf crowdfunding, and it is limited, primarily focusing within Malaysia and regions with similar waqf structures.

The Waqftech framework allows innovative mechanisms for executing corporate waqf investment returns to the intended beneficiaries through the smart contracts’ platform. In addition, this study supports relevant corporate social responsibility and creating shared value technology adoption theories, including EDI and TBL. Aside from this, the study provides empirical implications for waqf management using fintech platforms.

This groundbreaking study focuses on creating a Waqftech model for corporate waqf crowdfunding. The results of this study are important for the development of government policies that support the use of Waqftech in charitable fundraising. More research on biological and digital environmental perspectives is proposed to foster investors’ confidence in the visibility of digital tracking and lead to swift investments in future metaverse fundraising platforms.

This study explores the enablers of students “entrepreneurial intentions by identifying the factors that raise students” interest in embracing an entrepreneurial career.

Entrepreneurship education is increasingly attracting attention as a means of fostering entrepreneurial activity and creating a culture of innovation. Developing students' entrepreneurial intentions is critical to promote entrepreneurship. This research is built on a mixed method approach of partial least squares structural equation modelling and fuzzy-set qualitative comparative analysis.

The factors that influence students ‘entrepreneurial intentions are identified: business incubation programmes, non-reimbursable grants for entrepreneurial students, networking events to promote entrepreneurship, mentoring services, innovation labs for business idea validation and entrepreneurship courses. This knowledge can help develop effective entrepreneurship education programmes. The study also provides actionable insights for educational institutions and policymakers. It underscores the need for innovative educational platforms such as entrepreneurial bootcamps. It also highlights the value of advanced learning environments such as decision theatres to foster a culture of entrepreneurship and innovation.

The study contributes to the body of knowledge on entrepreneurship education. It highlights the need for a multidisciplinary approach to understand the factors that shape students’ entrepreneurial intentions.

This study aims to examine the potential determinants of entrepreneurial intentions (EIs) among business students. To that end, the study investigates the role of entrepreneurship education (EE) and entrepreneurial passion (EP) (inventing and founding), as well as the mediating role of attitude towards entrepreneurship (ATE) and the moderating role of university support.

A close-ended questionnaire measured on a seven-point Likert scale was used to collect data from business students at nine universities in Punjab, Pakistan. The sample size comprises 377 participants who were selected using a stratified random sampling technique. Partial least square structural equation modeling (PLS-SEM) was then applied to assess the study’s model and the postulated hypothesis.

The findings indicated that (a) every independent variable (IV) directly impacts EI [dependent variable (DV)] except EP for founding (EPF), (b) ATE significantly mediates the relationship between IV and DV (c) perceived university support positively moderates the relationship between ATE and EI.

As an implication to policy, the Government must ensure that students are exposed to business environments and find university support through different paths. Specifically, Pakistan’s Minister of Education and the Higher Education Commission (HEC) may consider designing university programs that lead to more influential EE. The empirical findings may help policymakers develop effective policies for promoting entrepreneurship.

The purpose of this paper is to examine the antecedents of entrepreneurial intentions amongst open and distance learning students during employment crisis. To achieve the purpose of this study, Ajzen’s theory of planned behaviour (TPB) was applied and empirically tested on the sample population.

Data were taken from a sample of university students pursuing business-related courses in Open and Distance Learning mode. Self-reported questionnaires were handed to a total of 500 students to complete and return. Returned and usable questionnaires numbered 245 in total, giving a return rate of 49 per cent. Descriptive statistics and regression analyses were utilised to analyse data. Structural equation modelling incorporated into SPSS was used to assess the structural model.

The key finding reveal that Ajzen’s TPB can partially be applied in determining entrepreneurial intentions in the developing economy. The study results also revealed that perceived behavioural control, personal attitude and subjective norm (SN) explained 62.5 per cent of variations in entrepreneurial intention, which surpasses many other studies conducted previously.

Present study relied on cross-sectional data using quantitative design, therefore limiting the full understanding of the causal relationship between variables.

The study developed a conceptual framework based on literature that was empirically tested, which adds to existing ones, thereby extending the literature in the field. Moreover, the study managed to incorporate SN as an intervening variable, which has rarely been done.