Construction Project Risk Assessment Research Articles

Implementation of a Combined Fuzzy Controller Model to Enhance Risk Assessment in Oil and Gas Construction Projects

Implementation of a Combined Fuzzy Controller Model to Enhance Risk Assessment in Oil and Gas Construction Projects

The Nexus Between Construction Contract Risk Assessment and Big Data in China

The construction market in China is currently showing an increasing trend in terms of project size, complexity, and technical difficulty. With large initial investments and long capital payback periods, construction projects are vulnerable to the external environment during development and risk control is particularly important. Contracts are at the heart of project management and every step of project development revolves around the content of the contract signed by the contractor. Signing contracts to protect the rights of both parties has become the most effective way of controlling project risk. And with big data technology being rapidly developed and widely used, and the amount of data created and accumulated by the internet growing exponentially, big data has the potential to be used for analysis, forecasting and decision making in the construction industry. The aim of this study is therefore to develop a risk identification list for construction project contracts in China, to score the risks within the list according to their incidence and importance, and to find practical applications of big data technology in contract risk assessment. To achieve this goal, this study used qualitative research and in-depth interviews with experts within the Chinese construction engineering industry. The results of this study form a list of risks in Chinese construction contracts, indicating that late payment and government intervention are the most important risks in Chinese construction contracts. This study also identifies TianYanCha, a commonly used big data enterprise risk identification platform in China, which provides big data support in three areas: evaluating owner integrity, enterprise risk identification, and owner relationship knowledge. At the practical level, this study helps contractors to assess project risks and improve contractual contents during the preparation phase of construction projects, thus improving the success rate of projects. At the theoretical level, this study fills the gap in contractual risk assessment for construction projects in China and provides insights for subsequent risk assessment of construction projects based on the contractor's perspective.

Risk assessment of high and low budget construction projects

Risk assessment of high and low budget construction projects

Ergonomic Risk Assessment of Construction Workers and Projects Based on Fuzzy Bayesian Network and D-S Evidence Theory

Work-related musculoskeletal disorders (WMSDs) are the main causes of physical diseases of workers in the construction industry. The occurrence of WMSDs can result in project delays, cost overruns, workers’ worsened health status, and even unanticipated safety risks. Ergonomic rules and instrument-based methods have enabled automatic postural ergonomic evaluation and intervention, while a research gap lies in how to consider more comprehensive personalized factors and how to integrate individual risks for project-level risk control. This study developed a two-hierarchy method to assess the ergonomic risk for both individual workers and the entire project. To alleviate the problems of data insufficiency and imprecision in real-life construction projects, experts’ evaluations were incorporated with existing instrument-based methods. A methodology combining fuzzy theory, D-S evidence theory, and Bayesian network was employed to deal with fuzziness, uncertainty, and conflicting judgments, and to provide a probabilistic assessment. To measure the potential impact on projects from the perspectives both of cost and productivity, this study also developed a practical framework for project integration. A real-life case study was conducted to validate the approach and demonstrated its applicability. The results of sensitivity analysis indicate that previous WMSD records, age, working posture, and working intensity are the top critical risk factors that have the most significant impact on individuals’ WMSD risk status. This study provides deeper insights into WMSD risk assessment, which can facilitate personalized instructions and intervention for individual WMSD risk control, and support managerial initiatives and decisions to mitigate the negative effects on construction projects.

Exploring barriers to effective safety risk assessment in Indian construction projects

Risk assessment (RA) is a critical process that can help avoid costly incidents. However, RA is usually undertaken incorrectly due to lack of construction experience. This study aimed to understand the challenges that users face during RA and users’ viewpoints to improve RA quality in the Indian construction sector. A mixed-methods approach was adopted to elicit the perspectives of safety heads (users) participating in Indian construction projects. The results show that the users faced six challenges during RA, including identifying significant hazards and steps involved in each activity and selecting control measures. The users’ requirements were gathered to facilitate future RA processes. As a guide, the results of this study can be used by construction organisations to make an informed RA method.

Monitoring and forecasting the condition of structures in the small river basins in southern Russia

Introduction. The southern regions of Russia need to adapt to higher peak river flows and flash floods. Since 1960, the number of recorded flood events has increased. The intensity and severity of flood events tend to decrease, but their annual frequency is increasing. This illustrates the social component of flooding. Trends in the number of flood events are closely related to the increasing population in river valleys. “Integrated management” of construction sites in river basins is based on three elements: monitoring, forecasting and early warning, vulnerability assessment, mitigation and response. The purpose of this study is to establish means of prediction, risk assessment of operational construction projects in river basins taking into account the current natural and climatic factors.
 
 Materials and methods. The research is based on the factual material collected in the field studies in the river basins of recreational regions of southern Russia. Design, construction and operational documentation of complex structures was analyzed and their structural elements were evaluated.
 
 Results. On the basis of the carried out theoretical, field and numerical researches, the problem of increasing ecological safety of the urban environment was solved by monitoring, assessing, ranging of the technical condition of building structures and forecasting risks in the urbanized areas of river basins. The results of the research should be considered as a basis of practical methods for the complex estimation of ecological safety of natural and technical system of river basins. Further development of the topic can be connected with the scaling studies of urbanized territories, monitoring crisis sites and forecasting of the further condition of construction projects by subjects.
 
 Conclusions. The developed software package has practical importance, the product is implemented in the Republic of Crimea, in the operation of the long-term operated HES complexes of the Partizanskoe reservoir supplying water to the city of federal importance Simferopol and the Alminsky reservoir irrigating Bakhchisaray region of the peninsula and it is also being tested in the Krasnodar Territory, the Republic of Dagestan, the Stavropol Territory and Caucasian Mineral Waters.

Railway construction project risk assessment techniques: systematic literature review

The purpose of this study is to conduct a systematic literature review of risk analysis techniques for railway construction projects. This review includes related papers on construction project risk analysis methods published between January 2000 and March 2020. For this review, the existing project risk analysis methods are classified as probabilistic, fuzzy logic, multi-criteria decision-making (MCDM) and system dynamics approaches. The results of the review showed that fuzzy analytic hierarchy process (FAHP) and fuzzy analytic network process (FANP) are dominant hybrid MCDM approaches for construction project risk assessment. Nonetheless, these approaches have their own limitations to handle dynamic and feedback effects of project risks as well as update new information when available. Hence, for railway construction project risk assessment, hybrid approaches that can deal with uncertainty, causal relationship, feedback, correlated and conflicting criteria are recommended for future research.

Risk Assessment in Construction Projects Using the Grey Theory

Construction projects are of a particular nature and are affected by many factors, which exposes them to risks due to the long implementation period and the multiplicity of phases from the project idea phase through the implementation phase to the final delivery of the project, which leads to increased uncertainty and increased likelihood of these risks. This paper examines the risks in construction projects in Libya, and their impact on project objectives. This research identified risks in construction projects based on previous studies and a number of interviews with experts in construction projects, as well as field visits to project sites. On this basis, a questionnaire was prepared to locate and identify the risks that construction projects may face and was distributed to a number of local companies affiliated to the Libyan state operating in the construction sector. After the compilation of the questionnaire, the risks were analyzed qualitatively and quantitatively to determine the impact of each risk and the probability of its occurrence. The results of the study showed that 28% of the risks are certain and high, and 53% of the risks affect the project implementation time to a high degree. The results also showed a strong correlation between the probability of occurrence of the risks. Grey theory was used to weigh and rank the most important risks, and the most important of these was the insufficient manpower, material and equipment criterion.

Risk identification and analysis for the green redevelopment of industrial brownfields: a social network analysis.

The green redevelopment of industrial brownfields (GRIB) is an important means to solve the shortage of urban land resources and realize sustainable urban renewal and green development. The identification and analysis of risk factors in GRIB projects are of immense significance for completing construction tasks and ensuring the planned benefits. In this study, work and risk breakdown structures and expert interviews are used to construct the risk network model of a GRIB project, based on three dimensions: process, subject, and system sources. The software package UCINET is used to conduct social network analysis and determine the key risk factors and relationships. The results of this study suggest that the four risk factors with the most brokerage roles and the highest node betweenness centralities are located at the core of the network; the six risk relationships with the highest line betweenness centralities are those with the strongest transmission capacities; the key risk factors are mostly response and stress risks; the main source is the design unit; and the key risk relationships are the influence of the decision-making stage on the design stage and of the design stage on the construction stage. Surpassing the limitations of traditional linear research, this study explains the internal relationship among the risk factors of GRIB projects and identifies the risk factors that play a brokerage role and the risk relationship that plays a conductive role, providing a theoretical basis for introducing social network analysis tools into the risk assessment of such complex construction projects.

Multi-Information Fusion Based on BIM and Intuitionistic Fuzzy D-S Evidence Theory for Safety Risk Assessment of Undersea Tunnel Construction Projects

Safety risk assessment is essential in ensuring the smooth construction of undersea tunnels. Obtaining reasonable safety risk assessment results requires multi-source information that enjoys static and dynamic attributes. However, acquiring and utilizing such uncertain information creates difficulties in the decision-making process. Therefore, this paper proposes a safety risk assessment approach based on building information modeling (BIM), intuitionistic fuzzy set (IFS) theory, and Dempster–Shafer (D-S) evidence theory. Firstly, an undersea tunnel construction collapse risk evaluation index system is established to clarify the information requirements of the pre-construction and construction stages. The semantic information of the BIM geometric model is then enriched through industry foundation classes (IFC) extension to match the multi-criteria decision-making (MCDM) process, with BIM technology used to assist in information acquisition and risk visualization. Finally, based on the intuitionistic fuzzy D-S evidence theory, multi-information fusion is performed to dynamically determine safety risk levels. Specifically, IFS theory is utilized for basic probability assignments (BPAs) determination before applying D-S evidence theory. The conflicting evidence is dealt with by reliability calculation based on the normalized Hamming distance between pairs of IFSs, while safety risk levels are accomplished with score functions of intuitionistic fuzzy values (IFVs). The proposed method is applied to collapse risk assessment in the karst developed area of a shield tunnel construction project in Dalian, China, and the feasibility and effectiveness are verified. The novelty of the proposed method lies in: (1) information collaboration between the BIM model and the dynamic safety risk assessment process being realized through IFC-based semantic enrichment and Dynamo programming to enhance the decision-making process and (2) the introduction of IFS theory to improve the applicability of D-S evidence theory in expressing fuzziness and hesitation during multi-information fusion. With the proposed method, dynamic safety risk assessment of undersea tunnel construction projects can be performed under uncertainty, fuzziness, and a conflicting environment, while the safety risk perception can be enhanced through visualization.

Cost Overrun Risk Assessment and Prediction in Construction Projects: A Bayesian Network Classifier Approach

Cost overrun risks are declared to be dynamic and interdependent. Ignoring the relationship between cost overrun risks during the risk assessment process is one of the primary reasons construction projects go over budget. Conversely, recent studies have failed to account for potential interrelationships between risk factors in their machine learning (ML) models. Additionally, the presented ML models are not interpretable. Thus, this study contributes to the entire ML process using a Bayesian network (BN) classifier model by considering the possible interactions between predictors, which are cost overrun risks, to predict cost overrun and assess cost overrun risks. Furthermore, this study compared the BN classifier model’s performance accuracy to that of the Naive Bayes (NB) and decision tree (DT) models to determine the effect of considering possible correlations between cost overrun risks on prediction accuracy. Moreover, the most critical risks and their relationships are identified by interpreting the learned BN model. The results indicated that the 18 BN models demonstrated an average prediction accuracy of 78.86%, significantly higher than the NB and DT. The present study identified the most significant risks as an increase in the cost of materials, lack of knowledge and experience among human resources, and inflation.

Risk Assessment for Off-Shore Petroleum and Gas Construction Projects in Egypt

Risk Assessment for Off-Shore Petroleum and Gas Construction Projects in Egypt

An intuitionistic fuzzy multi-class approach for risk assessment in sustainable BOT highway construction projects: A case study

An intuitionistic fuzzy multi-class approach for risk assessment in sustainable BOT highway construction projects: A case study

A decision-support tool for risk and complexity assessment and visualization in construction projects

Risk assessment in projects requires the integration of various information on project characteristics as well as external and internal sources of uncertainty and is based on assumptions about future and project vulnerability. Complexity is a major source of uncertainty that decreases the predictability of project outputs. In this research, the aim was to develop a decision-support tool that can estimate the level of risk and required contingency in a project by assessment of complexity factors as well as contextual information such as contract conditions and mitigation strategies. A process model and a tool were developed using the data of 11 mega construction projects. The tool was tested on a real project, and promising results were obtained about its usability. The tool has the potential to support decision-making during bidding in construction projects with its visualization and prediction features. On the other hand, as a limited number of cases and experts were involved in this study, findings on its performance cannot be generalized. The identified complexity and risk factors, proposed process model, and visual representations may help the development of similar decision-support tools according to different company needs.

Preliminary Studies and Performance of Construction Projects in Rwanda: A Case of Gatuna One Stop Border Post

In spite of the vibrant significance of preliminary studies in assisting choices related to government spending on construction programs, there are no efforts to appraise such studies once construction of facilities. Hence, this study seeks to investigate the contribution of preliminary study on performance of construction projects with specific reference to Gatuna one stop border post.  The study was guided by three specific objectives namely: to determine contribution of economic feasibility on performance of construction projects in Gatuna one stop border post; to assess contribution of technical requirements on performance of construction projects in Gatuna one stop border post as well as to determine how risk assessment contributes to the performance of construction projects in One Stop Border Post. The study will be important to Gatuna One Stop Border Post, citizen and traders in Rwanda. This study used descriptive research design .The target population of the study will be 150 Gatuna one stop border post staffs and a sample size of 109 beneficiaries, which was selected over, stratified random sampling technique. Questionnaires and guided interview were as data collection instruments where descriptive statistics was used for quantitative data analysis through the software of statistical package for the social sciences (SPSS) version 21,qualitative data were analyzed by using thematic method ; Karl  Pearson  product moment correlation coefficient was used to establish relationship between variables while regression analysis was used to check the influence of preliminary studies and performance of construction projects  at 32.1 percent of R -square. Cronbach's alpha coefficient of 73.1 percent showed that the instruments were reliable while the validity was established by peer discussion with experts. This study will be significant to site engineers, site supervisors and beneficiaries as well as ministry of infrastructure. The findings on the first objective showed that IRR, NPV, PBP and PI are considered as economic feasibility as it was confirmed by 83.1 percent of beneficiaries agreed that Internal Rate of Return is used to determine stages and timelines for test performance. The findings on the second objective showed that 85.4 percent of the beneficiaries agreed that they beneficiaries agreed that Appraisal of information infrastructure fulfils the sustainability of the project. The findings on the third objective showed that risk assessment influences construction project performance, it was also shown that there is significant low degree of positive correlation of 0.026 between risk assessment and performance of construction projects. It was concluded that effective implementation of preliminary study leads to positive performance of construction project. The study recommends that national budget planners and intervening people should provide financial facilities and make effective set up that should enhance performance of construction project. Keywords: Preliminary Studies, Performance of Construction Projects, Rwanda

Design risk modeling and analysis for railway construction projects

A systematic and comprehensive risk assessment is essential for the success of railway construction projects. Even though numerous studies have been conducted on railway construction project risk assessment, few attempts have been made to evaluate the overall dynamics, interrelationships, uncertainty, and impact of risks on project objectives. To address these limitations, this study developed a risk analysis model to evaluate the impact of design-related risks on delays and cost overruns of the Addis-Djibouti railway construction project. The model was developed using fuzzy synthetic evaluation (FSE) and system dynamics (SD) approaches. The results of the study revealed that scope change and design changes were the predominant design risks that have a higher impact on delays and cost overruns. The proposed model can be used as a project risk analysis tool for other construction projects to help managers identify significant risks and analyze dynamic effects on project objectives.

Risk Management Practice Adopted in Road Construction Project

Purpose: Zero risk construction is only a dream not reality as there is nothing certainity in the real world and scientists are only capable of coverting the same into risk with high level data science. The practice of risk management is an attempt to highlight risk elements with a case of urban road construction in Sindhupalchowk district, Province 3, Nepal. Design/Methodology/Approach: The 5-point Likert scale questionnaire survey was done to collect the primary data. Risk Management Practice is documented based on survey response in percentage through charts and graphs. Field visit were done for visual assessment of the construction procedure along with key informant interview and Secondary data of Detail Project Reports, Design and Drawings were effectively analyzed. Cronbach’s alpha was used to measure the reliability and triangulations were done for validity. Findings/Result: The results from this research indicates that contractor’s organization are averagely aware with a mean score of 3.30 about Risk Management Practice and averagely practicing risk management formally with mean score of 2.83. They are averagely analyzing risk management techniques with mean score of 3.07. Mean score is slightly higher based on client’s perspective with score for awareness being 3.93 and score for risk management being practiced formally is 3.13. Risk analysis score based on client’s management is 3.40. Mostly adopted technique of risk identification is monitoring and evaluation report of similar past projects and direct judgment is widely used technique for risk assessment of road construction projects at Sindhupalchowk district based on both client’s and contractor’s perspective. Risk response strategy based on contractor’s perspective is monitoring the risk and preparing contingency plan whereas that for client is transfer of risk. Originality/Value: It is action research which is significant for professional to understand the practices of risk management being adopted by Nepalese Contractors in hilly region of Nepal. Paper Type: Ex-Post Facto Research

Assessment of Risk and Uncertainty Factors Inherent in Nigerian Highway Project Using Analytical Hierarchical Process

The study presents a framework through which risk and uncertainties in Nigeria highway projects can be appraised using the analytical hierarchical process model. Pairwise comparison matrix was performed on eleven (11) risk and uncertainty factors that affect highway project performance through a questionnaire survey conducted among two hundred and four (204) respondents, which involved various stakeholders in the highway construction industry using Saaty’s AHP rating scale. The relative weights (significance/impact level) of each of the highway risk factors were estimated during the AHP model development. The results in descending order of risk factors priorities are Standard & Regulations (S&R), Construction (C), Project Staff (PS), Project Sponsor (PSp), Design (D), Project Finance (PF), Economic (E), Equipment (EQ), Environmental & Geotechnical (En&G), Site Location (SL) and Subcontractor (S) with impact levels of 16.6%, 14.2%, 13.9%, 13%, 12.7%, 12.2%, 10.8%, 9.8%, 6.2%, 4.2%, and 3.8% respectively. The model was validated using the statistical consistency test, with the model showing a consistency ratio equal to 0.1. The model was then applied to five (5) highway construction projects which had been constructed to predict the ones with the most and least risks. The result was in tandem with that which was given by the project managers from experiences on the project. This study showed that the Analytical Hierarchical Process (AHP) decision support model can effectively be used for risk assessment and prioritization of highway construction projects for efficient resource utilization in Nigeria.

Comprehensive Methodology of Risk Assessment of Construction Projects in Current Circumstances

Comprehensive Methodology of Risk Assessment of Construction Projects in Current Circumstances

Scoring model of risk assessment of construction projects

The article substantiates the possibility of using a scoring model to assess the risks of construction projects and real estate agencies. The problems of determining the weights of risk categories, individual risks and their factors are analyzed. Examples of using the model to solve practical problems are shown.