Risk Assessment Model for Optimal Gain–Pain Share Ratio in Target Cost Contract for Construction Projects

Purpose – This paper aims to develop a fuzzy risk assessment model for construction projects procured with target cost contracts and guaranteed maximum price contracts (TCC/GMP) using the fuzzy synthetic evaluation method, based on an empirical questionnaire survey with relevant industrial practitioners in South Australia. Design/methodology/approach – A total of 34 major risk factors inherent with TCC/GMP contracts were identified through an extensive literature review and a series of structured interviews. A questionnaire survey was then launched to solicit the opinions of industrial practitioners on risk assessment of such risk factors. Findings – The most important 14 key risk factors after the computation of normalised values were selected for undertaking fuzzy evaluation analysis. Five key risk groups (KRGs) were then generated in descending order of importance as: physical risks, lack of experience of contracting parties throughout TCC/GMP procurement process, design risks, contractual risks and delayed payment on contracts. These survey findings also revealed that physical risks may be the major hurdle to the success of TCC/GMP projects in South Australia. Practical implications – Although the fuzzy risk assessment model was developed for those new-build construction projects procured by TCC/GMP contracts in this paper, the same research methodology may be applied to other contracts within the wide spectrum of facilities management or building maintenance services under the target cost-based model. Therefore, the contribution from this paper could be extended to the discipline of facilities management as well. Originality/value – An overall risk index associated with TCC/GMP construction projects and the risk indices of individual KRGs can be generated from the model for reference. An objective and a holistic assessment can be achieved. The model has provided a solid platform to measure, evaluate and reduce the risk levels of TCC/GMP projects based on objective evidence instead of subjective judgements. The research methodology could be replicated in other countries or regions to produce similar models for international comparisons, and the assessment of risk levels for different types of TCC/GMP projects (including new-build or maintenance) worldwide.

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Risk assessment model for target cost contracts

Target Cost Contracting Strategy in Construction ◽

10.4324/9781315624532-18 ◽

2016 ◽

pp. 79-95

Keyword(s):

Risk Assessment ◽

Assessment Model ◽

Risk Assessment Model ◽

Target Cost

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DESIGN AND PILOT RUN OF FUZZY SYNTHETIC MODEL (FSM) FOR RISK EVALUATION IN CIVIL ENGINEERING

Journal of Civil Engineering and Management ◽

10.3846/13923730.2012.743926 ◽

2013 ◽

Vol 19 (2) ◽

pp. 217-238 ◽

Cited By ~ 15

Author(s):

Hamzah Abdul-Rahman ◽

Chen Wang ◽

Yee Lin Lee

Keyword(s):

Risk Assessment ◽

Construction Projects ◽

Optimal Allocation ◽

Early Stage ◽

Model Development ◽

Assessment Tools ◽

Assessment Model ◽

Quality Data ◽

Risk Assessment Model ◽

Synthetic Model

Most of the current construction risk assessment tools deliver unsatisfactory results because the prerequisite for their effective applications rely on the availability of high quality data especially during the early stage of a project. Unfortunately, such data are limited, ambiguous or even not exist due to the great uncertainty inherent in construction projects. Based on Fuzzy Synthetic Analysis (FSA), a model development team was formed among construction engineers, IT professionals, and Mathematicians in developing a holistic risk assessment model to estimate the construction risks especially for the situations with incomplete data and vague environments. Through qualitative scales defined by triangular fuzzy numbers used in pairwise comparisons to capture the vagueness in the linguistic variables, a risk assessment model using Analytic Hierarchy Process (AHP) was developed. The Pilot Run revealed the developed Fuzzy Synthetic Model (FSM) could accelerate the decision-making process and provide optimal allocation of project resources to mitigate possible risks detrimental to the success of a project in terms of time, cost, and quality.

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Developing an Ensemble Predictive Safety Risk Assessment Model: Case of Malaysian Construction Projects

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17228395 ◽

2020 ◽

Vol 17 (22) ◽

pp. 8395 ◽

Cited By ~ 1

Author(s):

Haleh Sadeghi ◽

Saeed Reza Mohandes ◽

M. Reza Hosseini ◽

Saeed Banihashemi ◽

Amir Mahdiyar ◽

...

Keyword(s):

Risk Assessment ◽

Developing Countries ◽

Construction Projects ◽

Well Being ◽

Working Environment ◽

Assessment Model ◽

Machine Learning Techniques ◽

Risk Assessment Model ◽

Safety Risk ◽

Safety Risks

Occupational Health and Safety (OHS)-related injuries are vexing problems for construction projects in developing countries, mostly due to poor managerial-, governmental-, and technical safety-related issues. Though some studies have been conducted on OHS-associated issues in developing countries, research on this topic remains scarce. A review of the literature shows that presenting a predictive assessment framework through machine learning techniques can add much to the field. As for Malaysia, despite the ongoing growth of the construction sector, there has not been any study focused on OHS assessment of workers involved in construction activities. To fill these gaps, an Ensemble Predictive Safety Risk Assessment Model (EPSRAM) is developed in this paper as an effective tool to assess the OHS risks related to workers on construction sites. The developed EPSRAM is based on the integration of neural networks with fuzzy inference systems. To show the effectiveness of the EPSRAM developed, it is applied to several Malaysian construction case projects. This paper contributes to the field in several ways, through: (1) identifying major potential safety risks, (2) determining crucial factors that affect the safety assessment for construction workers, (3) predicting the magnitude of identified safety risks accurately, and (4) predicting the evaluation strategies applicable to the identified risks. It is demonstrated how EPSRAM can provide safety professionals and inspectors concerned with well-being of workers with valuable information, leading to improving the working environment of construction crew members.

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The risk assessment model for construction projects including value creation and protection aspects

17th International Colloquium „Sustainable decisions in built environment ◽

10.3846/colloquium.2019.006 ◽

2019 ◽

Author(s):

Jolanta Tamošaitienė ◽

Miglė Lapeikytė

Keyword(s):

Risk Assessment ◽

Construction Industry ◽

Value Creation ◽

Construction Projects ◽

Assessment Model ◽

Risk Level ◽

Risk Assessment Model ◽

Construction Sector

The article focuses on the identification and classification of key risk management criteria that represent the value creation and protection aspects for the construction industry. Nowadays, the assessment of the risk level of a construction project is especially important for the quality of construction projects as well as the growth of enterprises and the sector. To establish the most important criteria for the successful growth of the construction sector including value creation and protection aspects are developed.

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DEVELOPING A COMPREHENSIVE RISK ASSESSMENT MODEL BASED ON FUZZY BAYESIAN BELIEF NETWORK (FBBN)

Journal of Civil Engineering and Management ◽

10.3846/jcem.2020.12322 ◽

2020 ◽

Vol 26 (7) ◽

pp. 614-634

Author(s):

Li Guan ◽

Qiang Liu ◽

Alireza Abbasi ◽

Michael J. Ryan

Keyword(s):

Risk Factors ◽

Risk Assessment ◽

Risk Management ◽

Construction Projects ◽

Bayesian Belief Network ◽

Assessment Model ◽

Risk Assessment Model ◽

Causal Relationships ◽

Belief Network ◽

International Construction

Reliable and efficient risk assessments are essential to deal effectively with potential risks in international construction projects. However, most conventional risk modeling methods are based on the hypothesis that risk factors are independent, which does not account adequately for the causal relationships among risk factors. In this study, a risk assessment model for international construction projects was developed to improve the efficacy of risk management by integrating fault tree analysis and fuzzy set theory with a Bayesian belief network. The risk rating of each risk factor, expressed as the product of risk occurrence probability and impact, was incorporated into the risk assessment model to evaluate degrees of risk. Therefore, risk factors were categorized into different risk levels taking into account their inherent causal relationships, which allowed the identification of critical risk factors. The applicability of the fuzzy Bayesian belief network-based risk assessment model was verified using a case study through a comparative analysis with the results from a fuzzy synthetic evaluation method. The comparison shows that the proposed risk assessment model is able to provide guidelines for an effective risk management process and ultimately to increase project performance in a complex environment such as international construction projects.

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Developing a fuzzy risk assessment model for guaranteed maximum price and target cost contracts in construction

Journal of Facilities Management ◽

10.1108/14725961111105709 ◽

2011 ◽

Vol 9 (1) ◽

pp. 34-51 ◽

Cited By ~ 7

Author(s):

Joseph H.L. Chan ◽

Daniel W.M. Chan ◽

Albert P.C. Chan ◽

Patrick T.I. Lam ◽

John F.Y. Yeung

Keyword(s):

Risk Assessment ◽

Assessment Model ◽

Risk Assessment Model ◽

Target Cost ◽

Maximum Price ◽

Fuzzy Risk Assessment

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Risk assessment model for venous thromboembolism in hospitalized surgical and non-surgical patients in the 4th Hungarian Antithrombotic Guidelines entitled “Diminution and Treatment of Venous Thromboembolism”

Orvosi Hetilap ◽

10.1556/oh.2010.28944 ◽

2010 ◽

Vol 151 (34) ◽

pp. 1365-1374 ◽

Cited By ~ 1

Author(s):

Marianna Dávid ◽

Hajna Losonczy ◽

Miklós Udvardy ◽

Zoltán Boda ◽

György Blaskó ◽

...

Keyword(s):

Risk Assessment ◽

Venous Thromboembolism ◽

Assessment Model ◽

Surgical Patients ◽

Risk Assessment Model

A kórházban kezelt sebészeti és belgyógyászati betegekben jelentős a vénásthromboembolia-rizikó. Profilaxis nélkül, a műtét típusától függően, a sebészeti beavatkozások kapcsán a betegek 15–60%-ában alakul ki mélyvénás trombózis vagy tüdőembólia, és az utóbbi ma is vezető kórházi halálok. Bár a vénás thromboemboliát leggyakrabban a közelmúltban végzett műtéttel vagy traumával hozzák kapcsolatba, a szimptómás thromboemboliás események 50–70%-a és a fatális tüdőembóliák 70–80%-a nem a sebészeti betegekben alakul ki. Nemzetközi és hazai felmérések alapján a nagy kockázattal rendelkező sebészeti betegek többsége megkapja a szükséges trombózisprofilaxist. Azonban profilaxis nélkül marad a rizikóval rendelkező belgyógyászati betegek jelentős része, a konszenzuson alapuló nemzetközi és hazai irányelvi ajánlások ellenére. A belgyógyászati betegek körében növelni kell a profilaxisban részesülők arányát és el kell érni, hogy trombózisrizikó esetén a betegek megkapják a hatásos megelőzést. A beteg trombóziskockázatának felmérése fontos eszköze a vénás thromboembolia által veszélyeztetett betegek felderítésének, megkönnyíti a döntést a profilaxis elrendeléséről és javítja az irányelvi ajánlások betartását. A trombózisveszély megállapításakor, ha nem ellenjavallt, profilaxist kell alkalmazni. „A thromboemboliák kockázatának csökkentése és kezelése” című, 4. magyar antithromboticus irányelv felhívja a figyelmet a vénástrombózis-rizikó felmérésének szükségességére, és elsőként tartalmazza a kórházban fekvő belgyógyászati és sebészeti betegek kockázati kérdőívét. Ismertetjük a kockázatbecslő kérdőíveket és áttekintjük a kérdőívekben szereplő rizikófaktorokra vonatkozó bizonyítékokon alapuló adatokat.

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Signature Analysis: Statistical Models and Their Application to FA

ISTFA 1996: Conference Proceedings from the 22nd International Symposium for Testing and Failure Analysis ◽

10.31399/asm.cp.istfa1996p0183 ◽

1996 ◽

Author(s):

C.K. Lakshminarayan ◽

S. Pabbisetty ◽

O. Adams ◽

F. Pires ◽

M. Thomas ◽

...

Keyword(s):

Risk Assessment ◽

Failure Analysis ◽

Statistical Models ◽

Essential Elements ◽

Assessment Model ◽

Signature Analysis ◽

Risk Assessment Model ◽

Sample Sizes ◽

Reliability Engineering ◽

Semiconductor Chips

Abstract This paper deals with the basic concepts of Signature Analysis and the application of statistical models for its implementation. It develops a scheme for computing sample sizes when the failures are random. It also introduces statistical models that comprehend correlations among failures that fail due to the same failure mechanism. The idea of correlation is important because semiconductor chips are processed in batches. Also any risk assessment model should comprehend correlations over time. The statistical models developed will provide the required sample sizes for the Failure Analysis lab to state "We are A% confident that B% of future parts will fail due to the same signature." The paper provides tables and graphs for the evaluation of such a risk assessment. The implementation of Signature Analysis will achieve the dual objective of improved customer satisfaction and reduced cycle time. This paper will also highlight it's applicability as well as the essential elements that need to be in place for it to be effective. Different examples have been illustrated of how the concept is being used by Failure Analysis Operations (FA) and Customer Quality and Reliability Engineering groups.

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