Project Risk Distribution during the Construction Phase of Small Building Projects

Perrenoud, Anthony; Smithwick, Jake; Hurtado, Kristen; Sullivan, Kenneth

doi:10.1061/(asce)me.1943-5479.0000417

Cited by 25 publications

(9 citation statements)

References 17 publications

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“…Construction projects have always been exposed to various unforeseeable risks, particularly during the construction phase of office projects. The following table summarizes ten critical quality risk factors of the Biconsi Tower project in Vietnam based on a survey of research publications and in-depth expert interviews (Arumsari et al, 2018;Dehdasht et al, 2017;Do et al, 2017;El-Sayegh & Mansour, 2015;Eybpoosh et al, 2011;Gan et al, 2017;Hussain et al, 2019;Kassem et al, 2020;Likhitruangsilp & Ioannou, 2009Likhitruangsilp et al, 2016;Liu et al, 2017;Naderpour et al, 2019;Nguyen & Nguyen, 2020;Nguyen et al, 2021;Perrenoud et al, 2016;Rustom & Amer, 2006;Siraj & Fayek, 2019;Subramanyan et al, 2012;Tadayon et al, 2012;Tamošaitienė et al, 2021;Viswanathan et al, 2020;Xu et al, 2010;Zavadskas et al, 2010;Zeng et al, 2007;Zou & Zhang, 2009)…”

Section: Research Backgroundmentioning

confidence: 99%

Assessment Quality Risk Factors During the Construction Phase of the Biconsi Tower Project

Nguyen

2022

Jour Proc Manag New Tech

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Project performance is assessed by various criteria. One of the typical triangle criteria used to assess the performance of any office building project is quality. However, office projects in Vietnam have faced numerous quality risks, particularly during their construction periods. This can cause the building projects behind schedule and over budget. As a result, identifying quality risk factors throughout the construction phase of office projects is essential. Therefore, this paper has applied the Analytical Hierarchy Process (AHP) method to prioritize critical risk factors affecting project quality during the construction phase of the Biconsi Tower project in Vietnam. The research results showed that the five top risk factors affecting the quality of the Biconsi Tower project with decreasing impact levels are as follows: (1) Inspection and acceptance work are not in accordance with regulations and procedures, (2) Lack of coordination between project stakeholders; (3) Poor quality design documents and drawings; (4) Poor construction methods; and (5) Poor quality input materials.

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Section: Research Backgroundmentioning

confidence: 99%

Assessment Quality Risk Factors During the Construction Phase of the Biconsi Tower Project

Nguyen

2022

Jour Proc Manag New Tech

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“…As the beginning of the risk management, risk identification is a process through which a series of potential risks are identified according to their frequency of occurrence and possible influence, either positively or negatively, on principal project objectives (Perrenoud et al, 2015). Many efforts have been made to identify risks or causes for the construction delay in infrastructures (Table 1).…”

Section: Construction Schedule Risks Of Infrastructure Projectmentioning

confidence: 99%

Bayesian Monte Carlo Simulation–Driven Approach for Construction Schedule Risk Inference

Chen

et al. 2021

J. Manage. Eng.

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As the construction of infrastructures becomes increasingly complex, it has been often challenged by construction delay with enormous losses. The delivery of complex infrastructures provides rich source of data for new opportunities to understand and address schedule issues. Based on these data, many efforts have been made to identify key construction schedule risks and predict the probability of risk occurrence. Bayesian network is one of the most useful tools for risk inference. However, there are still two obstacles preventing the Bayesian network from being adopted popularly in construction schedule risk management: (1) the development of directed acyclic graph (DAG) and associated conditional probability tables (CPTs); (2) the lack of observation data to trigger risk inference as evidence at the planning stage. This research aims to develop a novel Bayesian Monte Carlo simulation driven approach for construction schedule risk inference of infrastructures, where the Bayesian network model can be developed in a more convenient way and be used without observation data required. It firstly constructs the key risk network with key risks and links through network theory-based analysis. Then the DAG structure of Bayesian network is developed based on the topological structure of key risk network using deep-first search (DFS) and adapted maximum-weight spanning tree (A-MWST) algorithms. The CPTs are further developed using the leaky-MAX model. Finally, the Bayesian Monte Carlo simulation driven risk inference method is developed for predicting and quantifying the probability of construction schedule risk occurrence. A real infrastructure project is selected as case study to verify this developed approach. The results show that the developed approach is more appropriate to deal with risk inference of infrastructures considering its reliability, convenience, and flexibility. This research contributes a new way to construction schedule risk management and provides a novel approach for quantifying and predicting risk occurrence probability.

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“…The study noted the importance of distributing such information to all parties involved with the project. Perrenoud et al (2016) recommended that construction teams document the timing with which issues are “encountered” within the project schedule. Kotb and Ghattas (2018) noted issue logs as a primary project document that can provide important information for identifying threats to project performance in the context of construction projects.…”

Section: Literature Reviewmentioning

confidence: 99%

Using issue logs to improve construction project performance

Shalwani

Lines

2021

ECAM

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PurposeThe Project Management Body of Knowledge recommends the use of issue logs as a best practice to minimize the potential project cost and schedule growth. Although the broader topic of project control has been widely studied in the construction literature, the specific application of issue logs has remained relatively understudied. This study aims to analyze the extent and consistency with which construction teams utilize issue logs and the corresponding project performance outcomes.Design/methodology/approachA dataset of 5,635 individual issues was gathered from the final issue logs of 881 small building projects delivered via the design–bid–build method. Differences between groups were determined using the Kruskal–Wallis H test with post hoc testing via the Mann–Whitney U test with pairwise comparison.FindingsThe results showed that, on average, project teams who used issue logs to a greater extent achieved a 3.1 to 4.3% reduction in cost growth and a 5.3 to 12.3% reduction in schedule growth. This result shows that issue logs can be used to improve construction project performance in the areas of cost and schedule.Originality/valueThis result provides a contribution to practitioners, wherein project teams should be encouraged to establish their issue management practices early in the project schedule to encourage greater issue log usage for the remainder of the project.

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Project Risk Distribution during the Construction Phase of Small Building Projects

Cited by 25 publications

References 17 publications

Assessment Quality Risk Factors During the Construction Phase of the Biconsi Tower Project

Assessment Quality Risk Factors During the Construction Phase of the Biconsi Tower Project

Bayesian Monte Carlo Simulation–Driven Approach for Construction Schedule Risk Inference

Using issue logs to improve construction project performance

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