Ghazal, M M and Hammad, A (2022) Application of knowledge discovery in database (KDD) techniques in cost overrun of construction projects. International Journal of Construction Management, 22(9), pp. 1632-1646. ISSN 1562-3599
Abstract
Currently, cost overrun is a global challenge to completing construction projects successfully. To overcome this problem, earlier studies investigated factors of cost overrun. Knowledge Discovery in Data (KDD) and data mining techniques have been implemented effectively in various research areas to extract novel and valuable knowledge from historical data but have only recently been implemented in the construction industry. The aim of this research is to develop a model that predicts project cost overrun using a suitable data mining technique and cost overrun factors as predictors. A review of the literature identified twelve factors that can be easily measured and analyzed in construction projects. A case study was performed to validate the model with an actual data set of executed projects. The resulting model is simple, interpretable, and relatively accurate (60.87%), and it uses three steps of data mining–clustering, feature selection, and classification. These steps improve model performance.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | construction projects; cost overrun; cost performance; data mining; data warehousing; knowledge discovery; knowledge management |
| Index terms: | data mining, case study, cost overrun, database, construction industry, clustering, overrun, project cost, construction project, cost performance, knowledge management |
| Subjects: | project controls, data management, industry analysis, economics, production management, professional development, data science, financial and cost management, data collection methods |
| Topics: | Information Management, Research Practice, Project Management, Cost Management, Time Control, Digital Applications |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here