Development of a data mining-based analysis framework for multi-attribute construction project information

Data mining techniques extract repeated and useful patterns from a large data set that in turn are utilized to predict the outcome of future events. The main purpose of the research presented in this paper is to investigate data mining strategies and develop an efficient framework for multi-attribute project information analysis to predict the performance of construction projects. The research team first reviewed existing data mining algorithms, applied them to systematically analyze a large project data set collected by the survey, and finally proposed a data-mining-based decision support framework for project performance prediction. To evaluate the potential of the framework, a case study was conducted using data collected from 139 capital projects and analyzed the relationship between use of information technology and project cost performance. The study results showed that the proposed framework has potential to promote fast, easy to use, interpretable, and accurate project data analysis.

Comparison of key competences of DB clients and contractors in the construction market of the People’s Republic of China

Clients and Design-build (DB) contractors are two key stakeholders in DB projects, and contribute significantly to the successful project performance. This study aims to identify and compare such key competences in the construction market of the PRC. After the survey of available literature and face-to-face interviews, a two-round Delphi questionnaire survey was conducted to identify the key competences of clients and DB contractors in DB projects. Relative importance of these identified competences were ranked and compared. The questionnaire results indicated distinct differences between the key competences of clients and that of contractors. The contractor’s key competences emphasize on DB experience, corporate management capability, building and design expertise, financial capability, enterprise qualification and reputation. While the client’s competences focus on the ability to clearly define the project scope & requirements, financial capacity, contract management ability, adequate staff, effective coordination with DB contractor and similar DB experience. Both clients and DB contractors should clearly understand the competence requirements in DB projects and possess all the necessary competences for the successful outcome of DB projects. The identification of these key competences provides clients and DB contractors with indicators to assess their capabilities before going for the DB option. Furthermore, the comparison of competences for clients and DB contractors will result in better understanding of DB system and improve the communication between these stakeholders.

R&D investment in green building initiatives in Western Australia

This paper reports on a current case study of green building initiatives implemented by the Western Australian government in the past decade. The intent is to provide a qualitative understanding of past R&D investments in the Australian built environment. The case method was selected to illustrate three sector-based investments, one of which is reported on here. The conceptual framework underpinning interview design and data analysis uses dynamic capability, absorptive capacity and open innovation theories to better understand the organisational environment in which these initiatives were implemented. Data has been thematically coded to criteria identified from the literature to illustrate organisational characteristics which may have contributed to dissemination and impact. The results will be combined with two further case studies (construction safety and digital modelling), to inform this research. This industry supported project will conclude by developing policy guidelines for future R&D investment in the built environment.