Purpose -Building Information Modeling (BIM) technologies and Virtual Design and Construction (VDC) processes are becoming a driving force for advancing the design, construction and operation of buildings that may have the potential to reduce claims, disputes and litigation throughout the construction process. However, evidence shows that BIM isn't universally successful. To this end, this research aims to identify the most common BIM contractual risks (BCR).Design/Methodology/approach -This research intends to go further into about 22 BIM Contractual Risks that have been identified from the literature review. A questionnaire survey was made to identify the risks occurrence rate, involved parties and solutions for highest faced risks based on number of participants and their years of experience. Result analysis was based on experience years for each participant's vs each risk's parameters.Findings -The presented process mitigates the construction project participant's ability to complete the construction project under BIM collaborative environment and contracts isolation nature through the following: (1) identification and examination of about 22 BIM contractual risks, level of occurrence and solutions; (2) provide a BIM contractual framework that allows for defining each party's responsibility in BIM workflow.Research Limitations -Due to diversity in construction project, BIM based projects require an additional drafting method to the contract and provide an understanding of each party's responsibility by analyzing legal implication of BIM adoption. In addition, local legislation can provide the support needed for BIM implementations.Practical implications -Findings' implication suggests providing a legal understanding of BIM work flow through the investigation of BIM risks among
Many real estate owners change the building in terms of the type of usage in response to changes in economic conditions and the requirements of the surrounding environment to get the best potential financial return. To investigate the possibilities of changing the real estate's usage, the owners of these existing structures turned to feasibility study experts for assistance in making the optimum alternatives. So, they need an integrated model between VE and BIM, especially applicable to an existing structure, to determine the optimum usage type for the existing structure. Value Engineering (VE) and Building Information Modeling (BIM) must be connected to profit from both outputs simultaneously. Previous studies only investigated the VE alternatives during the design phase; when they decided to reduce project costs by using construction materials alternatives, they ignored existing structure alternatives significantly when changing the usage type. This study attempts to provide an integrated model between VE and BIM that can be applied to the existing structure to assist in determining the best alternative in terms of the type of usage for such existing structures by conducting BIM methodology such as a feasibility study, including BIM software such as Revit and Primavera. A feasibility study that contains the bank rate of interest. As a result, the maximum financial return is obtained based on predetermined criteria and in compliance with decision-making requirements. Doi: 10.28991/CEJ-2022-08-08-06 Full Text: PDF
This study aims to model construction projects cost and time overruns, with the specific objectives of identifying the causes and effects of cost and schedule overruns in construction projects. This is because the concept of construction projects cost and schedule overruns has attracted much attention in recent years and that researchers and research bodies, be it corporate or government that try to formulate remedies to projects cost and schedule overruns should begin with an understanding of the causes of these overruns and their effects to the construction industry as a whole. Since, time and cost performance are the fundamental criteria for success of any project. The project management technique for tracking the most critical factors that affect the project's overruns of planned schedule and planned budget using tools and developed software are helpful in comparing the project with stipulated time and cost.This research investigates ranking factors from two questionnaires to compute the severity index among various construction projects and ranked each factor according to the percentages of each factor occurrence. Two models constructed using Linear regression (LR) and machine learning (Support Vector Machine) is one of the artificial intelligence systems to fit the given data for all construction projects. First model is developed for time overrun prediction with high accuracy and second model is developed for cost overrun for various construction projects. Check the performance and accuracy of the predicting model by some certain projects of time and cost projects data and check the variation of the results between the actual results and predicted results.
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