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Evaluating Building Information Modeling (BIM) for Residential Project Management: A Case Study of the Panorama Twin Towers | ||
| Civil Engineering and Applied Solutions | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 28 اردیبهشت 1405 | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22080/ceas.2026.30968.1070 | ||
| نویسندگان | ||
| Masoud Ahmadvand1؛ Hossein Eghbali* 2 | ||
| 1Department of Civil Engineering, University of Eyvanekey, Eyvanekey ,Iran | ||
| 2Department of Industrial Engineering, Faculty of Industrial Engineering, University of Eyvanekey, Eyvanekey, Iran | ||
| تاریخ دریافت: 10 دی 1404، تاریخ بازنگری: 22 بهمن 1404، تاریخ پذیرش: 22 اردیبهشت 1405 | ||
| چکیده | ||
| In recent years, Building Information Modeling (BIM) has emerged as an innovative technology in the construction industry, playing a crucial role in enhancing project management processes. This study aims to evaluate and assess the impact of BIM on improving residential project management, with a case study of the Panorama Twin Towers in Pasdaran. The research examines the extent to which BIM influences key project management indicators, including cost reduction, schedule control, resource optimization, improved coordination among project stakeholders, and delay mitigation. To analyze the data, linear regression analysis has been employed. Linear regression is a widely used statistical method for examining the relationships between independent and dependent variables, which in this study is utilized to assess the impact of BIM on project management indicators. Data related to project execution were collected, preprocessed, and analyzed using a regression model. The coefficients of this statistical model determined the magnitude and direction of the influence of various variables, revealing with high precision the relationship between BIM implementation and project management enhancement. The modeling results indicate that the adoption of BIM has a significant and positive impact on improving project management processes. According to regression analysis, BIM contributes to project delay reduction, optimization of execution costs, increased scheduling accuracy, minimization of rework, improved coordination among project teams, and overall productivity enhancement. Furthermore, statistical analysis of the regression model suggests that BIM can accurately predict management trends and enhance strategic decision-making. These findings can assist project managers, consulting engineers, and other stakeholders in the construction industry in making more efficient and effective decisions, fostering the broader adoption of BIM in future projects. | ||
| کلیدواژهها | ||
| Building Information Modeling (BIM)؛ Project Management؛ Linear Regression؛ Data Analysis؛ Cost and Time Optimization | ||
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آمار تعداد مشاهده مقاله: 11 |
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