RESUMEN
This study examines how certain artificial intelligence (AI) drivers affect the industry's adoption of this technology in the construction industry. The research methods comprised a comprehensive analysis of previous studies to pinpoint the primary factors influencing AI adoption in the construction industry. Data collection was carried out through a well-structured survey involving relevant stakeholders in the building construction sector. The three main constructs of technological devices, advancement, and knowledge were found from the set of drivers with the technique of exploratory factor analysis. The deployment of AI in construction has the potential to improve health and safety and expedite project completion, as this research has evaluated. To figure out how these factors relate to the adoption of AI in the construction industry, partial least squares structural equation modeling was used. The study's conclusions showed that the influence of AI installation in the construction industry is reasonably significant thanks to the technology, advancement, and knowledge, contributing around 15 % of the effects that have been directly witnessed. The practical implications of AI for policy makers, engineers, and construction stakeholders are extensive and provide valuable insights for customized strategies aimed at using AI's potential to improve projects, promote sustainability, and elevate health and safety standards.
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Objective To optimize the quality management of project completion,improve the quality of scientific research outcomes,as well as promote the sustainable development of medical science and technology.Methods Based on the statistical analysis of the completion and postponement of the 2016-2018 provincial basic research projects in a medical school,explored the potential factors of project postponement.Identified possible problems in project execution and management,and furtherly,proposed effective countermeasures and suggestions for improvement.Results The main factors identified causing the postponement of project completion include the technique bottleneck of the experiment,unsatisfied research outcomes,long term of manuscript review,not well organized process management and so on.To deal with those problems,proposals including enhancing the publicity and education,optimizing the incentive system,reinforcing the whole process management,improving the multi-level management and strengthening the construction of scientific research integrity were put forward.Conclusions The quality management of project completion requires an improvement in the delicacy management of scientific research projects and a more comprehensive enhancement in cognition,rules and regulations,management means and scientific research integrity construction.
RESUMEN
In this study, Monte Carlo simulation and Bayesian network methods are combined to present a structure for assessing the aggregated impact of risks on the completion time of a construction project. Construction projects often encounter different risks which affect and prevent their desired completion at the predicted time and budget. The probability of construction project success is increased in the case of controlling influential risks. On the other hand, interactions among risks lead to the increase of aggregated impact of risks. This fact requires paying attention to assessment and management of project aggregated risk before and during the implementation phase. The developed structure of this article considers the interactions among risks to provide an indicator for estimating the effects of risks, so that the shortage of extant models including the lack of attention to estimate the aggregated impact caused by risks and the intensifying impacts can be evaluated. Moreover, the introduced structure is implemented in an industrial case study in order to validate the model, cover the functional aspect of the problem, and explain the procedure of structure implementation in detail.