Constructing a digital twin maturity assessment framework for the building construction phase based on an improved matter-element model: A case study of a construction project in Xinyang, China

Digital twin technology has the potential to enhance construction efficiency, reduce costs, and minimize errors. However, its application during the construction phase remains at an early stage, largely constrained by the absence of standardized guidelines and principles. To address this challenge, it is essential to establish a comprehensive and universal maturity assessment framework to facilitate the effective implementation of this technology in the construction phase of building projects. This study focuses on two critical aspects: the development of the maturity assessment framework and its empirical validation. The proposed framework encompasses a maturity assessment indicator system covering five dimensions: acquisition layer, data layer, modeling layer, analysis layer, and application layer. For the first time, an optimized matter-element model based on dynamic thresholds and nonlinear correlation is introduced to improve the accuracy of maturity assessments. Furthermore, a feedback mechanism based on Importance-Performance Analysis (IPA) is utilized to clarify the formulation of optimization strategies. Finally, the framework is applied to the CAZ Innovation Industrial Park construction phase in Xinyang, Henan Province. The assessment results demonstrate that the system precisely measures the project’s maturity level and provides effective improvement recommendations. This study not only offers technological support for assessing and optimizing the digital twin maturity during the construction phase of building projects but also provides methodological insights into global digital twin maturity assessments.