Cost performance of building refurbishment works: the case of Malaysia

• Main Authors: Ali, Azlan Shah, Azmi, Nur Farhana, Baaki, Timothy Kurannen
• Format: Article
• Published: Emerald 2018
• Subjects: TH Building construction
• Online Access: http://eprints.um.edu.my/22564/; https://doi.org/10.1108/IJBPA-02-2017-0010

Purpose: Refurbishment is inherently more sustainable than building new. However, planned and actual costs of refurbishment projects are bound to vary due to the complex nature of most such projects. This can affect the performance of refurbishment work. The purpose of this paper is to examine factors responsible for elemental cost variations between the actual and planned costs of refurbishment projects. The study also examines factors that contribute to differences in actual and planned cost between refurbishment and new build projects. Design/methodology/approach: A quantitative approach was adopted for this study. A literature review identified factors responsible for elemental cost variations in refurbishment projects, as well as factors responsible for differences in actual and planned cost of new build and refurbishment projects. This was followed by a questionnaire survey of refurbishment projects across Malaysia. A total of 55 respondents provided input through a questionnaire survey to identify these factors. Findings: This study demonstrates that procurement strategy (PS), inappropriate contractors (IC), poor project management (PPM), availability of funding, materials and equipment, and force majeure (FM) significantly affect refurbishment cost performance. Electrical installations, firefighting equipment, and painting were the building elements most affected by cost variations. A regression model for refurbishment cost prediction indicates that PS, IC, PPM, availability of funding, materials and equipment, and FM were significant predictors of building refurbishment cost performance. Originality/value: This paper provides insight into the major factors affecting elemental cost variation of refurbishment works, as well as building elements most affected by cost variations and provides a model for predicting refurbishment cost performance.