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The exponential growth of the construction sector exerts considerable pressure on the environment, and the circular economy (CE) concept has recently gained traction as a means of alleviating such environmental issues. In order to propose solutions to the phenomenon of contractors being hesitant to participate in CE implementation in developing countries, this paper aims to comprehensively explore the enabling factors that motivate contractors to implement CE.

This study is based on the push-pull-mooring (PPM) theory and extends it by introducing information provision (IP) as a trigger on contractors’ intrinsic subjective initiative states on CE implementation. The study considers what and how positive pull, negative push and neutral mooring factors influence the contractors’ CE transition. The framework was validated by questionnaires collected from contractors in China, and the data were analyzed using the structural equation modeling method.

The findings indicate that all factors from the PPM framework exert a positive influence on CE intention, with push factors demonstrating a greater average impact. Furthermore, this study confirms the influence of the IP on contractors’ CE intentions by influencing their intrinsic status. The impact of the IP is most pronounced in terms of contractors’ perceived usefulness and environmental concerns.

This study contributes to the existing body of knowledge in the CE transition studies by extending the PPM theory into the construction industry through the lenses of contractors in developing countries. The results highlight the trigger impacts of the IP on contractors’ psychological status regarding CE transition. Furthermore, it offers insights into government management in the CE transition by providing the government with novel approaches to facilitate the CE transition in the construction sector.

Machine learning (ML) technologies are increasingly being applied in building cost estimation as an advanced method to overcome the challenge of insufficient data and subjective effects of experts. To address the gap of lacking a review of ML applications in building cost estimation, this research aimed to conduct a systematic literature review to provide a robust reference and suggest development pathways for creating novel ML-based building cost prediction models, ultimately enhancing construction project management capabilities.

A systematic literature review according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) was adopted using quantitative bibliographic analysis and qualitative narrative synthesis based on the 70 screened publications from Web of Science (WOS) and Scopus databases. The VOSviewer software was used to prepare the thematic focus from the bibliographic data garnered.

Based on the results of a bibliographic analysis, current research hotspots and future trends in the application of ML to building cost estimation have been identified. Additionally, the mechanisms behind existing ML models and other key points were analyzed using narrative synthesis. Importantly, the weaknesses of current applications were highlighted and recommendations for future development were made. These recommendations included defining the availability of building attributes, increasing the application of emerging ML algorithms and models to various aspects of building cost estimation and addressing the lack of public databases.

The findings are instrumental in aiding project management professionals in grasping current trends in ML for cost estimation and in promoting its adoption in real-world industries. The insights and recommendations can be utilized by researchers to refine ML-based cost estimation models, thereby enhancing construction project management. Additionally, policymakers can leverage the findings to advocate for industry standards, which will elevate technical proficiency and ensure consistency.

Compared to previous research, the findings revealed research hotspots and future trends in the application of ML cost estimation models in only building projects. Additionally, the analysis of the establishment mechanisms of existing ML models and other key points, along with the developed recommendations, were more beneficial for developing improved ML-based cost estimation models, thereby enhancing project management capabilities.

This study aims to investigate the impact of trust in the metaverse on the Islamic banking sector, particularly in facilitating market success. Additionally, it seeks to explore the relationship between metaverse-driven brand image, product features, service quality and overall performance in the market.

Data were collected from 187 participants in Jordan, with the SmartPLS software used to test the hypotheses.

The findings reveal a significant impact of metaverse-enhanced brand image, product features and service quality on Islamic banking market performance. Furthermore, customer trust in the metaverse plays a significant role in shaping the relationship between product features, service quality and Islamic banking market performance.

The study’s practical implications still suggest the need for a more holistic metaverse-driven approach. Investing in service quality initiatives alone may not adequately build and sustain customer trust in the metaverse. Instead, transparent communication on ethical practices in the metaverse is required to reinforce trust and magnify the positive influence of superior service quality in the metaverse.

It is widely accepted that one criterion for determining if a construction project is successful is whether it is completed within the expected budget. There have been advancements in the management of building projects throughout time but cost overruns remain a key concern in the construction sector internationally, particularly in emerging economies such as Ghana. This study aims to answer the question, “What are the critical success factors (CSFs) that can assist reduce cost overruns in public sector infrastructure projects in the Ghanaian construction industry?”

This study used a quantitative survey method. The questionnaire was pre-tested by interviewing 15 contractors to ascertain the validity of the content. Factor analysis and multiple regression were adopted to analyze the data.

This study discovered that the critical factors that can reduce cost overruns in construction projects in Ghana are directly linked to five themes: early contractor involvement in the project planning stage, adequate funding, good project team relations, competent managers/supervisors and project participant incentives/bonuses. This study identifies indestructible, empirically measurable important success criteria for reducing cost overruns in public building projects in Ghana.

When well thought through from the project initiation stage to completion, these critical successes can also be used to deal with damaging economic effects such as allocative inefficiency of scarce resources, further delays, contractual disputes, claims and litigation, project failure and total abandonment.

The uniqueness of this research resides in the fact that it is, to the best of the authors’ knowledge, a first-of-its-kind investigation of the CSFs for reducing cost overruns in public building projects in developing countries.