| Title |
Forecasting Economic Impacts of Construction R&D Investment: A Quantitative System Dynamics Forecast Model Using Qualitative Data |
| Authors |
Hwang, Sungjoo ; Park, Moonseo ; Lee, Hyun-Soo ; Jang, Youjin ; Moon, Myung-Gi ; Moon, Yeji |
| DOI |
http://dx.doi.org/10.6106/KJCEM.2013.14.2.131 |
| Keywords |
R&D programs ; System Dynamics ; Qualitative Data ; Forecast Model |
| Abstract |
Econometric forecast models based on past time-series data have been applied to a wide variety of applications due to their advantages in short-term point estimating. These models are particularly used in predicting the impact of governmental research and development (R&D) programs because program managers should assert their feasibility due to R&D program’s huge amount of budget. The construction governmental R&D programs, however, separately make an investment by dividing total budget into five sub-business area. It make R&D program managers difficult to understand how R&D programs affect the whole system including economy because they are restricted with regard to many dependent and dynamic variables. In this regard, system dynamics (SD) model provides an analytic solution for complex, nonlinear, and dynamic systems such as the impacts of R&D programs by focusing on interactions among variables and understanding their structures. This research, therefore, developed SD model to capture the different impacts of five construction R&D sub-business by considering different characteristics of sub-business area. To overcome the SD’s disadvantages in point estimating, this research also proposed the method for constructing quantitative forecasting model using qualitative data. Understanding the different characteristics of each construction R&D sub-business can support R&D program managers to demonstrate their feasibility of capital investment. |