## 2 Theoretical Background
### Parametric Method  
Some previous scholars have addressed construction cost estimation using cost-modeling techniques [15; 16] or case-based actual construction costs [10; 17; 18]. However, their study has been limited to research on the error ranges of estimates simply to verify the accuracy of construction cost estimation methods. These methods are difficult to apply to actual architectural planning work; furthermore, discussions of the application of cost prediction models in this stage have also been lacking. In addition, although comparative analysis of statistical techniques and artificial intelligence methods has been conducted to test and verify the accuracy of construction cost estimation models, the absolute number of case-based actual construction cost data is insufficient, and the usage of these cases is limited. Furthermore, in the current situation in which BIM design is required, these methods have difficulties in terms of implementing the BIM design. Therefore, in architectural planning, further in-depth research is required to identify the parameters influencing the accuracy of the estimates, develop datasets with ensured objectivity, and propose a method that can utilize the parameters and dataset in BIM. In this context, we adopted a parametric regression analysis-based method. This approach is known to be easy [6], utilizing a dataset with parameters that is straightforward to apply when the relevant information is insufficient for a given project scope and data. In this manner, we developed a construction cost estimation model that reflects not only the highly correlated factors dealt with in previous studies as influencing factors, but also the information generated in the planning stage, and explores the possibility of connection with BIM design. The parametric method has been reported to utilize datasets with parameters and is suitable for application when there is insufficient available information for the scope of a given project and data [19]. The parametric method performs cost estimation by extracting parameters reflecting the characteristics of the subject that requires cost prediction. The method is used for cost estimation in the early design phase of a construction project; it is advantageous in that it can support cost planning according to various design changes [16]. In particular, it has been reported that the \"parametric cost estimation model is a highly useful method when there is insufficient information available for a given project scope and data\" [19]. For example, in the pre-design stage, uncertain information such as scale analysis results, regulations, and standards for the construction project is available, but it is difficult to predict more detailed information such as material quantities, the details of the processes required, and the predicted time to completion. In addition, because this stage occurs before the schematic design phase of the construction project, it can be considered as a time of insufficient information in relation to the plan design. From a general perspective, there are items for which quantity take-off is not possible, owing to a lack of information, and because detailed design has not been implemented yet, direct calculation using equations is not possible at this timepoint. Instead, predictions need to be made through statistical estimation using existing case-based actual construction data or according to the experience of experts in this field. Considering this complex situation, a conceptual cost estimation model based on the parametric method developed by identifying parameters influencing the cost estimation, using the construction cost dataset developed in this study, can be utilized when there is insufficient information in the schematic design and design development phases of a construction project [20]. A parameter in a parametric method is defined as an element that effectively reflects the characteristics of the project [21].