Risk assessment of public road construction projects using analytical hierarchy process (AHP)

Highways or road construction project are one of the public infrastructure project that are important for social economic development. Due to this reason Malaysia government paying much more attention to these projects. Even though appropriate measurement taken, there is still great probability of r...

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Bibliographic Details
Main Author: Putri Aifa Syuhaida, Shabuddin
Format: Undergraduates Project Papers
Language:English
Published: 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/35876/1/Risk%20assessment%20of%20public%20road%20construction%20projects%20using%20analytical%20hierarchy%20process%20%28AHP%29.pdf
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Summary:Highways or road construction project are one of the public infrastructure project that are important for social economic development. Due to this reason Malaysia government paying much more attention to these projects. Even though appropriate measurement taken, there is still great probability of risk to occur which places the road construction project at risk of cost, time overruns and poor quality delivery. The aim of this study was to analyze the risk assessment of public road construction projects. The factors and sub-factors of risk in public road construction project were scrutinized from the literature review. The designate pair-wise questionnaire survey was distributed to the road engineering section of public work department, road contractors and road concessionaires in accordance with the Analytic Hierarchy Process (AHP). This study identified the most prioritized risk factors as follows: economic and financial (0.267), technical (0.165), organizational (0.148), contractual (0.130), natural hazard (0.125), socio and politic (0.086) and resources (0.079). The risk sub-factors were also ranked and the top five sub-factors were determined as follows: flood (0.633), inflation risk (0.561), changes in government law and regulation (0.543), lack coordination between parties (0.467), fund risk (0.439). It is expected that the data presented in this study can be used to strategically select elements for risk monitoring on the prioritization risk.