Construction industry suffers from under-performance, especially in the apartment construction sector. Contractors are the driving force which delivers built assets. Performance measurement within the industry occurs in two aspects: 1) contractors gauging their own level of performance towards continuous improvement and 2) selecting better performing contractors to achieve project success. However, the industry lacks a systematic and purpose driven method to assess performance of contractors using objective metrics. The available methods are complicated and heavily dependent on granular level data.

This research developed a performance model based on metrics that are easily measurable, readily available and within the control of the contractor. It utilises data from contracting organisations and construction projects that are recorded due to administrative and regulatory requirements. A series of Delphi-based expert forums was conducted to shortlist critical measures of performance and to define benchmarks. Fuzzy analytical hierarchy process was used to calculate weights and Monte Carlo Simulation was used to develop the overall performance index.

The developed performance model: Contractors’ Performance Index (CPI) provides a performance score based on seven critical non-price measures (Figure 1). As CPI is based on factors that are within the control of the contractor, it provides a fair and independent assessment of performance which is not influenced by other factors. In an industry significantly driven by price-based decisions, being solely based on non-price measures, CPI shifts the focus towards other aspects such as quality, health and safety, sustainability and productivity when evaluating performance. Contractors can use CPI for self-evaluating their level of project and overall performance. It can also be used as a tool for industry analytics to track performance of contractors and projects across the sector (Figure 2). CPI is presented as a mobile application for ease of use (Figure 3).

This research is supervised by Prof. Srinath Perera, A/Prof. Xiaohua Jin and A/Prof. Mary Hardie. Collaborators of Centre for Smart Modern Construction are acknowledged for their support.