Analysis of Design Change Mechanism in Apartment Housing Projects Using Association Rule Mining (ARM) Model

Abstract

Apartment housing occupies the highest proportion of the domestic construction market and significantly influences the flow of the real estate market. Frequent design changes and reconstruction in new apartment housing projects lead to an increase in construction cost and schedule, and a decline in design and construction quality, which is an important issue affecting the quality of use for occupants. The causal relationship of design changes and error in new apartment building projects has not been previously identified. Accordingly, design changes management activities in the construction phase using reactive manner are a critical risk that causes the productivity of the project to deteriorate. In this study, a complex and non-linear causal relationship between the design change factors was investigated using the association rule mining technique (ARM), a type of data mining technique. In particular, the associated relationship between design change factors that can be changed according to conditions that significantly affect the productivity and performance of projects, such as a contractor’s ranking in the field, contract price which means the project size, and contractor selection methods, was identified. The association rule between the design changes at the construction phase derived in this research can be used as a guide to identify and minimize the risk of design changes in advance.

Keywords

• design changes
• association rule mining (ARM)
• apartment housing project
• data mining
• construction stages