Search Results (283)

This study aims to critically analyze the theoretical and practical contributions of recent literature on the Critical Chain Project Management (CCPM) method in multi-project environments. To this end, a systematic literature review (SLR) was conducted based on 62 studies indexed in the Scopus and Web of Science databases between 2014 and 2025. The articles were analyzed in terms of application domains, employed methods, obtained results, and proposed integrations with other approaches. Most studies used modeling and simulation, focusing on time reduction, risk mitigation, and cost optimization. A growing trend has been identified toward integrating CCPM with methodologies, such as Scrum, BIM, Lean Construction, Fuzzy FMEA, and predictive algorithms, thereby broadening its applicability in high-complexity scenarios. However, a significant gap remains in empirical studies applied to Engineer-to-Order (ETO) systems and service-based organizations, which are characterized by high customization, variability, and interdependence of resources. The research is justified by the need to consolidate accumulated knowledge on CCPM and to guide future investigations toward underexplored sectors. The findings strengthen the theoretical robustness of the method while indicating concrete opportunities for empirical validation in real-world organizational settings. Full article

This study presents a comprehensive review of risk assessment and scheduling techniques in highway construction, addressing the complex interplay between uncertainty, project planning, and decision-making. The research critically reviews key risk assessment methods, including Probability–Impact (P-I), Monte Carlo Simulation (MCS), Fuzzy Set Theory (FST), and the Analytical Hierarchy Process (AHP), alongside traditional scheduling approaches such as the Critical Path Method (CPM) and the Program Evaluation and Review Technique (PERT). The findings reveal that, although traditional methods like CPM and PERT remain widely used, they exhibit limitations in addressing the dynamic and uncertain nature of construction projects. Advanced techniques such as MCS, FST, and AHP enhance decision-making capabilities but require careful adaptation. The review further highlights the growing relevance of hybrid and integrated approaches that combine risk assessment and scheduling. Bayesian Networks (BNs) are identified as highly promising due to their capacity to integrate both qualitative and quantitative data, offering potential for greater reliability in risk-informed scheduling while supporting improvements in cost efficiency, schedule reliability, and adaptability under uncertainty. The study outlines recommendations for the future development of intelligent, risk-based scheduling frameworks suitable for industry adoption. Full article

Today, companies face complexities and uncertainties that make it difficult to manage various risks. One of the important tools for achieving success in water supply projects is the proper implementation of risk management processes and activities throughout the project’s make-span. Risk identification and assessment are two important steps in project risk management. In this research, the Fuzzy DEMATEL and Fuzzy ANP as well as Artificial Neural Network methods are exploited for the analyzing and ranking of environmental risks of water supply projects. Risks are classified and then prioritized by the Fuzzy ANP and Artificial Neural Network methods into four main categories, including technical, organizational, project management, and external risks. The weight of each of the technical, organizational, project management, and external risks using the ANP method was obtained as 0.31, 0.26, 0.25, and 0.18, respectively, and the following weights were obtained using the Artificial Neural Network: 0.42, 0.27, 0.22, and 0.09, respectively. The results show that although the exact weights differed between methods, especially for technical and external risks, the overall prioritization of risk categories followed a broadly consistent pattern. In addition, the risk associated with the suppliers obtained the highest weight among the external risks; the risk associated with the high cost of materials gained the highest weight among the organizational risks; the risk associated with the requirements acquired the highest weight among the technical risks; and finally, the risk associated with communication achieved the highest weight among the project management risks. The method presented in this research helps project managers and decision-makers in the water supply industry to make a better and more realistic risk assessment by considering the mutual effects of project risks. Full article

The EVM method is an essential project management technique that compares the work done to the planned values (PVs) to identify project variances. However, the inherent uncertainties and possibilities in the project introduce uncertainty in the input data. Despite this importance, the input data for this method is often considered deterministic in most research, and several researchers have modeled it under fuzzy information. In this research, we developed a novel approach using a combined model of fuzzy numbers and grey numbers called interval grey triangular fuzzy (IGTF) numbers. This model is designed to manage the project’s fuzzy grey value, addressing the two pillars of fuzzy and grey uncertainty. The findings of the study indicate that by combining the grey degree of confidence with the triangular fuzzy number (TFN), the results are closer to the real world and more lenient. Finally, based on the estimation of the actual final cost of the project, managers are encouraged to use certainty in lowering costs concerning the value obtained by using the Z-number for the phases of the project. This research provides practical insights and a new model for managing sustainable project uncertainties using fuzzy and grey theories, offering a potential solution to this challenge. Full article

Serving as critical sustainable transportation infrastructure, inland waterways provide dual socioeconomic and ecological value by (1) facilitating high-efficiency freight logistics through cost-effective bulk cargo transport while stimulating regional economic growth, and (2) delivering essential ecosystem services including flood regulation, water resource preservation, and biodiversity conservation. This study establishes a stakeholder-centered risk assessment framework to enhance decision-making of waterway engineering projects and promote the sustainable development of Inland Waterway Transport. We propose a three-layer approach: (1) identifying key stakeholders in the decision-making stage of waterway engineering projects through multi-dimensional criteria; (2) listing and classifying decision-making risks from the perspectives of managers, users, and other stakeholders; (3) applying the Decision-Making Trial and Evaluation Laboratory (DEMATEL) to prioritize key risks and proposing a risk assessment model based on fuzzy reasoning theory to evaluate decision-making risks under uncertain conditions. This framework was applied to the Yangtze River Trunk Line Wuhan–Anqing Waterway Regulation Project. The results show that the risk ranking is managers, users, and other stakeholders, among which the risk of engineering freight demand is particularly prominent. This suggests that we need to pay attention to optimizing material transportation and operational organization, promote the development of large-scale ships, and realize the diversification of ship types and transportation organizations. This study combines fuzzy reasoning with stakeholder theory, providing a replicable tool for the Waterway Management Authority to address the complex sustainability challenges in global waterway development projects. Full article

To address potential risks during the construction process, improve construction quality and engineering safety, this paper constructs a construction safety risk analysis model for concrete gravity dams in cold regions based on fuzzy VIKOR-LEC. Firstly, an expert team employs linguistic variables to evaluate the likelihood of accidents (L), the frequency of personnel exposure to hazardous environments (E), and the consequences of accidents (C) for various risk factors in the LEC model. Secondly, the fuzzy analytic hierarchy process (FAHP) and maximum deviation method were used to construct a risk factor weight analysis matrix and find subjective and objective weights, respectively, to obtain the comprehensive weights of risk factors. Thirdly, VlseKriterijumska Optimizacija Kompromisno Resenje (VIKOR) is introduced to improve the traditional LEC model and is used to calculate the risk priority number. Finally, in order to further verify the validity of the model, this paper selects the example of Linhai Reservoir dam in Heilongjiang Province to analyze the management of the construction safety risk. The research results may provide a scientific basis for the safety management of gravity dam construction projects in cold areas, and help to improve the level of project management and reduce construction risks. Full article

In the operation period of long-distance water delivery tunnels, safety may be impacted by the risks that arise from different aspects including the complex geological conditions with fault fracture zones and karst caves, the diverse environment affecting structural safety and stability, and the construction defects of tunnels. It is crucial to assess and mitigate potential risks to ensure operation safety. To address this challenge, this study presents a systemic risk assessment for the operation safety of a real project of a water delivery tunnel. The potential risks of this project were first summarized based on the analytical hierarchy process (AHP), and a model that integrates the AHP and fuzzy comprehensive evaluation (FCE) was built to effectively quantify and categorize risks for the project in its operation stage. Results of the assessment indicate that the risk of this tunnel operation can be classified at a moderate grade with a calculted specific risk score of 43.935, with the high-risk factors including segment lining cracking, flow control, and regular maintenance. In response to the high-risk factors, the preventative and control measures are proposed to guide effective risk management. The model presented offers an efficient risk assessment tool for water delivery tunnels, aiding decision makers making more rational management decisions in complex and uncertain environments. Full article

As sponge city construction is gradually promoted globally, it is very important to construct a scientific and reasonable performance evaluation framework. This paper establishes an indicator system with 5 primary indicators and 15 secondary indicators, calculates subjective weights by fuzzy hierarchical analysis, determines objective weights by a projection tracing model, calculates comprehensive weights of indicators by combining game theory, and finally determines the city’s evaluation level based on the interval-counting multi-objective gray target decision-making model. Eleven typical sponge cities were selected for the case study analysis, which verified that the research framework of this paper can effectively deal with complex data and the reliability of the evaluation results, providing new ideas for the evaluation of sponge city construction performance. It also helps city managers to optimize the construction plan and resource allocation in a timely manner, thus enhancing the comprehensive benefits of the city and providing a scientific basis for the long-term development of sponge cities. Full article

Unrealistic cash flow forecasts negatively affect project stakeholders and are a common issue for construction practitioners. This study proposes a new method for predicting the probabilistic cash flow of a project that can automate the calculation process while considering the impact of risks and their inter-related structure. This research integrates a Bayesian Belief Network (BBN) and 5D-BIM to provide a new probabilistic cash flow analysis approach. Here, 5D-BIM is used to facilitate cash flow calculations and automate the process. The BBN has also been implemented to assess the impact of risk factors on project cash flow, considering their complex inter-related structure. In addition, a hybrid approach combining fuzzy set theory, decision-making trial and evaluation laboratory (DEMATEL), and interpretive structural modeling (ISM) is used to form the BBN. The proposed method provides a robust tool for calculating the probabilistic cash flow of the project. The results showed that the project’s cash flow in the last month was IRR 14.4 billion without considering the impact of risks. The probabilistic cash flow of the project indicates that due to the impact of the risks, the project cash flow will be in the range of IRR −142.2 billion and IRR 1.11 billion at the end of the project. This shows the possibility of experiencing between 11 and 130% deviation in the project cash flow due to existing risks. In conclusion, project cash flow is unreliable without considering the impact of risks. This framework supports better financial decisions and allows for the evaluation of cash flow risk management scenarios. Full article

Prefabricated construction is an effective method for reducing project time and waste and improving quality and safety compared to traditional construction. However, its widespread adoption faces risks and challenges, having detrimental impacts on project performance. This research aims to assess prefabricated construction risks in Iraq using fuzzy synthetic evaluation (FSE). After determining the mean importance score for the likelihood and impact of risks extracted from comprehensive theoretical reviews, significant risks were selected using normalization, followed by FSE. The theoretical review results yielded 79 risks across 11 categories. After normalization, 34 significant risks across 10 categories were identified. The results showed that all risk categories had a medium probability and impact, except for investment and political risks, while experience risks had a high probability and high impact, respectively. FSE results showed that the highest risk importance index was for experience (12.075), followed by political (11.753), capital investment (11.362), safety (11.242), and design risks (10.902). Through its detailed and integrated methodology, the study contributes to formulating an accurate roadmap for FSE of prefabricated construction risks and provides accurate results that add a deeper understanding of risks, helping project managers identify significant risks and formulate the necessary policies to mitigate and control them. Full article

This study seeks to advance group decision-making in project management by introducing a hybrid intuitionistic fuzzy brainstorming (IFBS) method tailored for identifying and assessing earthquake risks in worn-out urban fabrics in Iran. By integrating the collaborative ideation of brainstorming with intuitionistic fuzzy sets (IFSs), the IFBS method effectively addresses uncertainties inherent in expert judgments, providing a robust and systematic framework for risk prioritization. Expert opinions, captured as linguistic variables, were transformed into triangular intuitionistic fuzzy numbers using a 5-point Likert scale measurement, enabling precise numerical analysis of 11 identified earthquake risks. Compared to the PMBOK-based qualitative analysis, the IFBS method demonstrates superior accuracy and granularity in risk assessment, as evidenced by its ability to model complex uncertainties and prioritize risks effectively. This study contributes a novel, scalable decision-making tool that enhances precision in urban risk management, offering practical implications for project managers and researchers tackling natural disaster risks. Its primary novelty lies in the innovative combination of IFSs with brainstorming, creating a scientific guide for managing earthquake vulnerabilities in worn-out urban fabrics. This approach not only improves decision-making outcomes but also sets a foundation for future research in hybrid fuzzy methodologies for disaster resilience. Full article

Product Lifecycle Management (PLM) provides a paradigmatic model that enables companies to operate more effectively in the face of shorter product lifecycles, global networking, and increasing complexity. However, despite strengthening the PLM initiative, companies still struggle to implement this concept. The limited results of current PLM implementations often stem from a lack of unique indicators or consistent methodologies that help companies prioritize their implementation efforts. This article proposes an approach to set a PLM strategy, focusing on enhancing company innovation potential by introducing a structured methodology capable of (i) capturing latent needs based on the normative-contingent New Product Development (NPD) evaluation model and (ii) quantifying the influence of various PLM functional aspects on NPD capability. The proposed methodology is based on the Quality Function Deployment (QFD) method, modified to overcome the limitations of the conventional approach, employing the Analytic Hierarchy Process (AHP) for prioritizing request attributes and the Evaluation based on Distance from Average Solution (EDAS) method for quality attribute importance ranking. Motivated by the arbitrary and vague nature of the decision-making environment in the PLM implementation projects, which introduces uncertainties that could be effectively managed by fuzzy logic, the study introduces Interval Type-2 Fuzzy Sets (IT2FSs) to minimize ambiguity and inconsistency in expressing and modeling preferences. The main study contribution pertains to generating quantitative and objective guidelines for adequately grounding a PLM strategy from the perspective of enhancing the company’s innovation potential. The findings of this study ultimately contribute to establishing an optimal model of the PLM concept implementation process, tailored to specific company requirements. Finally, an empirical case study demonstrates the effectiveness and practicality of the proposed approach. Full article

The jacking renovation construction of aging bridges faces significant safety risks due to the complexity and uncertainty of their structures. Addressing the limitations of traditional risk assessment methods in handling dynamic changes and data scarcity, this study proposes a safety risk assessment approach based on dynamic Bayesian networks (DBN) and fuzzy set theory (FST). By using DBN to model the temporal evolution of risks, combined with the Leaky Noisy-OR Gate extension model and FST to quantify expert knowledge, this method overcomes the constraints of insufficient data. Taking an elevated bridge jacking renovation project in Qingdao, China, as a case study, a risk indicator system was established, incorporating factors such as personnel, equipment, and the environment. The results show that risks are higher in the early stages of construction and stabilize later on, with poor foundation conditions, instability of the substructure, and improper operations identified as key risk sources requiring focused control. Through forward reasoning, the study predicts risk trends, while backward reasoning identifies sensitive factors, providing a scientific basis for construction safety management. Full article

To improve the accuracy and scientific of science and technology project management, a fuzzy decision support system was developed in this study. We designed the overall deployment architecture of the system, which consists of the system access layer, system core layer, system service layer, and basic platform layer. A Web server was used to reduce the response time of the system. The indices of science and technology projects were sorted by using the fuzzy decision support process and the expert’s weight matrix. To improve evaluation accuracy, a program and the storage process of the results were established at each stage of the evaluation. The developed system spent less time querying evaluation results. The query error rate was low, indicating improved efficiency of science and technology project management. Full article

Building Information Modeling (BIM) has recently gained popularity in the public building industry, and BIM is widely implemented in the construction industry in many developed countries around the world. In this paper, in order to evaluate the application level of BIM technology in assembly buildings in China, five maturity levels of BIM application in assembly buildings are established based on the commonly used maturity model, including the initial level, the starting level, the management level, the integration level, and the continuous optimization level. In order to construct a maturity evaluation index system for BIM application in prefabricated buildings, the literature review method was chosen to identify the indexes initially, the indexes were optimized by combining the questionnaire survey method, and using the balanced scorecard model, the maturity evaluation index system for BlM application in prefabricated buildings consisting of one target level, five guidance levels, thirteen graded element levels and thirty-one secondary index levels were identified. Based on this framework, the study establishes a maturity assessment model for BIM application in prefabricated buildings through three methodological integrations. First, the hierarchical analysis method Analytic Hierarchy Process (AHP) was employed to assign weights to indexes within the evaluation system. Subsequently, the Entropy Weight Method (EWM) was utilized to systematically construct the index system. This quantitative foundation was then combined with fuzzy comprehensive evaluation principles to develop the integrated assessment model. The practical application of this model was demonstrated through a case study of a prefabricated building project in China. The assessment results revealed that the project’s BIM application maturity level falls within the transitional phase “between the management level and integrated level”, indicating progressive but not yet fully optimized implementation. The result verifies the validity of the assessment model and proposes corresponding optimization suggestions based on the assessment results. Full article