7-Score Function for Assessing the Strength of Association Rules Applied for Construction Risk Quantifying

There are several factors influencing the time of construction project execution. The properties of the planned structure, the details of an order, and macroeconomic factors affect the project completion time. Every construction project is unique, but the data collected from previously completed projects help to plan the new one. The association analysis is a suitable tool for uncovering the rules—showing the influence of some factors appearing simultaneously. The input data to the association analysis must be preprocessed—every feature influencing the duration of the project must be divided into ranges. The number of features and the number of ranges (for each feature) create a very complicated combinatorial problem. The authors applied a metaheuristic tabu search algorithm to find the acceptable thresholds in the association analysis, increasing the strength of the rules found. The increase in the strength of the rules can help clients to avoid unfavorable sets of features, which in the past—with high confidence—significantly delayed projects. The new 7-score method can be used in various industries. This article shows its application to reduce the risk of a road construction contract delay. Importantly, the method is not based on expert opinions, but on historical data.

Moderating role of government Acts, laws and policies between team competency and skills and construction risk management among KSA contractors

Contractors have given importance to risks in the construction process as it causes time and cost overrun, delays, and total desertion in activities and events present in the construction project. The uncertainty in the completion time, cost, and quality during construction relate to construction risks. Project goals are achieved by classifying, investigating, and replying to risks associated with construction projects. To achieve project objectives, team competency and skills are required, which are viewed as attitude, aptitude, versatility, and knowledge. Based on organisation control theory, current research (quantitative in nature) discusses the influence of team competency and skills on construction risk management with the moderation role of government Acts, laws, and policies among 303 large-size contractors working in the Kingdom of Saudi Arabia using PLS-SEM technique. PLS-SEM is a composite-based approach that provides high efficiency parameter estimation with increased statistical power for analyzing complex models. Results depict that government Acts, laws and policies and team competency and skills positively influence construction risk management. In addition, moderation of government Acts, laws, and policies has positive relation among team competency and skills and construction risk management. Organisational management can reduce risk occurrence within a project by building conditions for enhancing team competency and skills.

Integration of Interpretive Structural Modeling with Fuzzy Bayesian Network for Risk Assessment of Tunnel Collapse

Frequent collapse accidents in tunnels are associated with many construction risk factors, and the interrelationship among these risk factors is complex and ambiguous. This study’s aim is to clarify the relationship among risk factors to reduce the tunnel collapse risk. A multicriteria decision-making method is proposed by combining interpretive structural modeling (ISM) and fuzzy Bayesian network (FBN). ISM is used to determine the hierarchical relationships among risk factors. FBN quantitatively analyzes the strength of the interaction among risk factors and conducts risk analysis. The ISM-FBN method contains three steps: (1) drawing the ISM-directed graph; (2) obtaining the probability of the FBN nodes; and (3) using GeNle to implement risk analysis. The proposed method is also used to assess the collapse risk and detect the critical factors in the Canglongxia Tunnel, China. This method’s tunnel collapse risk model can provide managers with clear risk information and better realize project management.

Research on Graded Management of Construction Risk Factors of a Subway Station

Based on a subway station project, this paper puts forward the risk factors in the process of subway construction. The analytic hierarchy process (AHP) is used to establish the risk factor model of metro station. Establishes the risk judgment matrix at all levels by combining the results of expert investigation method. By evaluating the risk factors of the subway station, the weight values of the above risk factors are calculated and sorted. As a result, the risk management system of subway station is put forward.The research results of this method provide a theoretical basis for the project managers to determine the risk factors, and lay a foundation for the smooth progress of the subway station construction project.

Semantic IFC Data Model for Automatic Safety Risk Identification in Deep Excavation Projects

Safety risk identification throughout deep excavation construction is an information-intensive task, involving construction information scattered in project planning documentation and dynamic information obtained from different field sensors. However, inefficient information integration and exchange have been an important obstacle to the development of automatic safety risk identification in actual applications. This research aims to achieve the requirements for information integration and exchange by developing a semantic industry foundation classes (IFC) data model based on a central database of Building Information Modeling (BIM) in dynamic deep excavation process. Construction information required for risk identification in dynamic deep excavation is analyzed. The relationships among construction information are identified based on the semantic IFC data model, involved relationships (i.e., logical relationships and constraints among risk events, risk factors, construction parameters, and construction phases), and BIM elements. Furthermore, an automatic safety risk identification approach is presented based on the semantic data model, and it is tested through a construction risk identification prototype established under the BIM environment. Results illustrate the effectiveness of the BIM-based central database in accelerating automatic safety risk identification by linking BIM elements and required construction information corresponding to the dynamic construction process.

Research on the Dynamic Evolution of Sponge City Construction Risk Based on System Dynamics

Following the research idea of "theoretical analysis -- mechanism analysis -- model simulation", the basic concept and basic theory of sponge city construction risk are firstly defined, and then the risk factors and internal mechanism of sponge city construction are analyzed by the grounded theory method. Finally, the system dynamics model is used for simulation. The dynamic development and key risk factors of each sub-risk system in the whole life cycle are analyzed, and the countermeasures to reduce the risk of sponge city construction are given.