Enhancing Early-Stage Construction Cost Estimation: A BIM-Driven Framework for Accurate Quantity Take-Off and Decision Support

Abstract

Background: Early-stage cost estimation and quantity take-off (QTO) are critical determinants of project feasibility, budgetary control, and lifecycle outcomes in the built environment. Traditional estimating methods frequently suffer from fragmentation, human error, delayed feedback, and limited interoperability with design and construction workflows (Matipa et al., 2008; Sattineni & Bradford, 2011). Building Information Modeling (BIM) offers parametric, semantic, and interoperable mechanisms that can transform how quantities and costs are produced, validated, and iterated during design (Eastman et al., 2011; Lee et al., 2006).

Objectives: This research article develops a theoretically grounded and practice-oriented framework for integrating BIM-enabled quantity take-off, IFC standard extensions, Virtual Design and Construction (VDC), and lean project delivery principles to optimize cost estimation accuracy, traceability, and decision-support at the design stage. The framework addresses interoperability, parametric object behavior, data quality, and multi-criteria decision-making in quantity estimation.

Methods: A mixed-methods synthesis was undertaken, drawing on canonical BIM literature, empirical studies on IFC-based estimating in China, surveys of industry adoption, and contemporary integrations of VDC and lean delivery. The methods section articulates a descriptive computational pipeline—without code—highlighting object modeling, mapping to cost libraries, rule-based quantity extraction, uncertainty propagation, and AHP-based decision modules for alternative selection (Zhiliang et al., 2011; Choi et al., 2015; Darko et al., 2019).

Results: The framework demonstrates how parametric object behavior and IFC extensions enable early, automated QTO with traceable change logs, enabling rapid generation of scenario-based cost envelopes. Integration with VDC and lean practices reduces rework risk and supports continuous value alignment between design intent and constructability (Aslam et al., 2021; Fosse et al., 2017). The paper elaborates on limitations—data quality, skill gaps, and organizational inertia—and prescribes mitigations.

Conclusions: When applied as an integrated socio-technical system, BIM-based QTO coupled with VDC and lean delivery materially improves early-stage cost management, transparency, and adaptive decision-making. Future research should empirically validate the framework in multi-region pilots and elaborate automated uncertainty quantification techniques.