Despite being one of the largest industry sectors in the world, construction continues to suffer from underperformance. Contractors are the driving force behind built assets, and selecting high-performing contractors is crucial to the success of construction projects. However, the industry lacks a systematic and purpose-driven method of assessing contractors' performance using objective metrics. Furthermore, contractors do not have a systematic way to gauge their own performance in the pursuit of continuous improvement. Although there are numerous approaches to the measurement of contractors' performance, the literature suggests that most are complicated and highly dependent on data that are difficult to attain. The research presented in this thesis addresses this knowledge gap by creating a model for predicting construction contractors' performance based on directly attributable measures that are quantitatively measurable and easily accessible. The findings of this research make a number of contributions to theory and practice. The developed performance model-the Contractors' Performance Index (CPIx) provides a performance score based on seven non-price CMoPs. As the CPIx is based on factors that are within the control of the contractor, it provides a fair and independent assessment of performance that is not influenced by other factors. In an industry significantly driven by pricebased decisions that are solely based on non-price measures, the CPIx shifts the focus towards other aspects such as quality, health and safety, sustainability and productivity when evaluating performance, leaving price based measures for commercial considerations. Contractors can use the CPIx to self-evaluate their levels of project and organisational performance. If implemented as a sector-based performance evaluator, it can then be used to develop industry benchmarks for different categories of construction. The CPIx is presented as a prototype mobile application that can be conveniently used by various stakeholders to track performance within the construction industry.
Date of Award | 2021 |
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Original language | English |
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- construction industry
- contractors
- benchmarking (management)
- performance
- measurement
Methodology to predict construction contractors' performance using non-price measures
Thalagala Achchi Maddumage, K. G. (Author). 2021
Western Sydney University thesis: Doctoral thesis