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

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.

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

Facilities ◽  
2014 ◽  
Vol 32 (11/12) ◽  
pp. 624-646 ◽  
Author(s):  
Daniel W.M. Chan ◽  
Joseph H.L. Chan ◽  
Tony Ma
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Construction Projects ◽  
South Australia ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Content Type ◽  
Risk Levels ◽  
Target Cost ◽  
Fuzzy Risk Assessment

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.

scholarly journals Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism

2019 ◽  
Vol 48 (4) ◽  
pp. 030006051989317
Author(s):  
Xindan Wang ◽  
Jing Huang ◽  
Zhao Bingbing ◽  
Shape Li ◽  
Li Li
Keyword(s):  
Risk Assessment ◽  
Gynecological Cancer ◽  
Area Under The Curve ◽  
Assessment Model ◽  
Receiver Operating Curve ◽  
Risk Level ◽  
Control Group ◽  
Risk Assessment Model ◽  
Vein Thrombosis ◽  
Risk Assessment Models

Objective This study aimed to investigate a suitable risk assessment model to predict deep vein thrombosis (DVT) in patients with gynecological cancer. Methods Data from 212 patients with gynecological cancer in the Affiliated Tumor Hospital of Guangxi Medical University were retrospectively analyzed. Patients were risk-stratified with three different risk assessment models individually, including the Caprini model, Wells DVT model, and Khorana model. Results The difference in risk level evaluated by the Caprini model was not different between the DVT and control groups. However, the DVT group had a significantly higher risk level than the control group with the Wells DVT or Khorana model. The Wells DVT model was more effective for stratifying patients in the DVT group into the higher risk level and for stratifying those in the control group into the lower risk level. Receiver operating curve analysis showed that the area under the curve of the Wells DVT, Khorana, and Caprini models was 0.995 ± 0.002, 0.642 ± 0.038, and 0.567 ± 0.039, respectively. Conclusion The Wells DVT model is the most suitable risk assessment model for predicting DVT. Clinicians could also combine the Caprini and Wells DVT models to effectively identify high-risk patients and eliminate patients without DVT.

AHP-Driven Knowledge Leakage Risk Assessment Model

2016 ◽  
Vol 7 (3) ◽  
pp. 1-18 ◽  
Author(s):  
Haley Wing Chi Tsang ◽  
Wing Bun Lee ◽  
Eric Tsui
Keyword(s):  
Risk Assessment ◽  
Intellectual Capital ◽  
Value Creation ◽  
Value Chain ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Analytic Hierarchy ◽  
Job Knowledge ◽  
Knowledge Leakage ◽  
Hierarchy Process

Intellectual Capital (IC) is becoming more widely understood by the academic and business communities, especially its important role in value creation of an organization. However, few people are aware that IC, if not managed properly, may also pose threats, sometime serious, to an organization. Knowledge leakage from an organization, for example, may come about when an experienced employee leaves for another job. Knowledge leakage is pervasive throughout an organization but is seldom noticed until the consequence is felt. This intellectual capital risk has to be systematically and effectively identified, assessed and controlled in the whole value chain of an organization. An AHP (Analytic Hierarchy Process) based multi-dimensional decision making and assessment model is developed to determine knowledge leakage risk in an organization.

Risk assessment model for information system based on classification of risk events

2009 ◽  
Vol 29 (10) ◽  
pp. 2806-2808 ◽  
Author(s):  
Ting-yuan LI ◽  
Cheng-yu FAN ◽  
Zhi-guang QING ◽  
Xiao-dong LIU
Keyword(s):  
Risk Assessment ◽  
Information System ◽  
Assessment Model ◽  
Risk Assessment Model

scholarly journals Water Quality Pollutants and Health Risk assessment for Four Different Drinking Water Sources

2019 ◽  
Vol 78 ◽  
pp. 03004
Author(s):  
Miaomiao Tian ◽  
Wenzhao Li ◽  
Meijuan Ruan ◽  
Jing Wei ◽  
Weiwei Ma
Keyword(s):  
Water Quality ◽  
Risk Assessment ◽  
Drinking Water ◽  
Health Risk ◽  
Health Risk Assessment ◽  
Rural Areas ◽  
Assessment Model ◽  
Risk Level ◽  
Risk Assessment Model ◽  
Acceptable Risk

Drinking water quality has become a great concern to the whole society, especially in heavily polluted rural areas. This paper analyzes the water quality of 100 water supping the US Environmental Protection Agency's (USEPA) recommended health risk assessment model. The results showed that the microbial indicators exceeded the standard in the whole year, and some of the water supply units which lead, nitrated and dissolved solids exceeding the standard. The model recommended by EPA is applied to establish risk assessment model for health risk assessment of adults in wet and dry seasons, respectively. Results of HRA indicated that carcinogenic risk of chromium was 7.61E-05a-1 and the risk value of arsenic was 9.92E-06a-1 which exceed the maximum acceptable risk level recommended by USEPA 5.0×10-5 closely to the ICPR recommendation 1.0×10-6. Meanwhile we conduct health risk assessment (HRA) on relevant non-carcinogenic indicators: nitrate is 2.95E-09a-1, the risk value of fluoride (F) is 2.49E-09a-1, the risk value of lead is 2.39E-09a-1 and copper (Cu) 9.00E-10a-1 exceeds the maximum acceptable risk level risk value recommended by USEPA 1.0×10-9. The above indicators require priority control and management of pollutants that are prioritized and managed.

scholarly journals Fuzzy Model for Risk Assessment of Machinery Failures

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 525 ◽  
Author(s):  
Dejan V. Petrović ◽  
Miloš Tanasijević ◽  
Saša Stojadinović ◽  
Jelena Ivaz ◽  
Pavle Stojković
Keyword(s):  
Risk Assessment ◽  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Fuzzy Inference ◽  
Mining Industry ◽  
Fuzzy Model ◽  
Assessment Model ◽  
Risk Level ◽  
Engineering System ◽  
Risk Assessment Model

The main goal of this research was the development of an algorithm for the implementation of negative risk parameters in a synthesis model for a risk level assessment for a specific machine used in the mining industry. Fuzzy sets and fuzzy logic theory, in combination with statistical methods, were applied to analyze the time picture state of the observed machine. Fuzzy logic is presented through fuzzy proposition and a fuzzy composition module. Using these tools, the symmetric position of the fuzzy sets with regard to class was used, and the symmetric fuzzy inference approach was used in an outcome calculation. The main benefit of the proposed model is being able to use numerical and linguistic data in a risk assessment model. The proposed risk assessment model, using fuzzy logic conclusions and min–max composition, was used on a mobile crushing machine. The results indicated that the risk level of the mobile crushing machine was in the “high” category, which means that it is necessary to introduce maintenance policies based on this high risk. The proposed risk assessment model is useful for any engineering system.

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

2013 ◽  
Vol 19 (2) ◽  
pp. 217-238 ◽  
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.

scholarly journals Risk Assessment of Nautical Navigational Environment Based on Grey Fixed Weight Cluster

2017 ◽  
Vol 29 (3) ◽  
pp. 331-342 ◽  
Author(s):  
Yanfei Tian ◽  
Xuecheng Sun ◽  
Lijia Chen ◽  
Liwen Huang
Keyword(s):  
Risk Assessment ◽  
Risk Evaluation ◽  
Assessment Model ◽  
Risk Level ◽  
Weight Functions ◽  
Risk Assessment Model ◽  
Membership Degree ◽  
Fixed Weight ◽  
Qiongzhou Strait ◽  
Set Up

In order to set up a mathematical model suitable for nautical navigational environment risk evaluation and systematically master the navigational environment risk characteristics of the Qiongzhou Strait in a quantitative way, a risk assessment model with approach steps is set up based on the grey fixed weight cluster (GFWC). The evaluation index system is structured scientifically through both literature review and expert investigation. The relative weight of each index is designed to be obtained via fuzzy analytic hierarchy process (FAHP); Index membership degree of every grey class is proposed to be achieved by fuzzy statistics (FS) to avoid the difficulty of building whiten weight functions. By using the model, nautical navigational environment risk of the Qiongzhou Strait is determined at a “moderate” level according to the principle of maximum membership degree. The comprehensive risk evaluation of the Qiongzhou Strait nautical navigational environment can provide theoretical reference for implementing targeted risk control measures. It shows that the constructed GFWC risk assessment model as well as the presented steps are workable in case of incomplete information. The proposed strategy can excavate the collected experts’ knowledge mathematically, quantify the weight of each index and risk level, and finally lead to a comprehensive risk evaluation result. Besides, the adoptions of probability and statistic theory, fuzzy theory, aiming at solving the bottlenecks in case of uncertainty, will give the model a better adaptability and executability.

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