Search Results (134)

The maritime transport of liquefied gases poses significant safety and environmental hazards such as fire, explosion, toxic gas emissions, and air pollution. The main objective of this study was to systematically identify, analyze, and prioritise the potential risks associated with the operation of liquefied gas tankers using a hybrid methodological framework. This framework integrates Fuzzy Delphi, Fuzzy DEMATEL, and Fault Tree Analysis (FTA) techniques to provide a comprehensive risk assessment. Initially, 20 key risk factors were identified through expert consensus using the Fuzzy Delphi method. The causal relationships between these factors were then assessed using Fuzzy DEMATEL to understand their interdependencies. Based on these results, accident probabilities were further analyzed using FTA modelling. The results show that fires, explosions, and large gas leaks are the most serious threats. Equipment failures—often caused by corrosion and operational errors by crew members—are also significant contributors. In contrast, cyber-related risks were found to be of lower criticality. The study highlights the need for improved crew training, rigorous inspection mechanisms, and the implementation of robust preventive risk controls. It also suggests that the prioritisation of these risks may need to be reevaluated as autonomous ship technologies become more widespread. By mapping the interrelated structure of operational hazards, this research contributes to a more integrated and strategic approach to risk management in the LNG/LPG shipping industry. Full article

In competitive organizations and projects, assessing risks related to human capital is essential for improving workplace conditions and ensuring project success. This study evaluates primary, secondary, and residual human capital risks in urban water transfer projects using an innovative hybrid DEMATEL–MARCOS approach. The DEMATEL method was employed to analyze causal relationships and interdependencies among risks, while the MARCOS method ranked their significance. The key findings reveal that “accidents during material transportation” (primary risk), “corrosion” (secondary risk), and “pipeline pressure” (residual risk) are the most critical factors influencing human capital in such projects. The study provides a structured framework for prioritizing risk mitigation strategies, offering actionable insights for policymakers and project managers to enhance safety, efficiency, and workforce well-being. By integrating multi-criteria decision-making techniques, this research bridges a gap in the water industry’s risk management practices and contributes to safer, more sustainable infrastructure development. Full article

This study enhances coastal vulnerability assessment by introducing a Modified Fuzzy DEMATEL technique that incorporates socio-ecological and power dynamic considerations. The novelty of the study lies in integrating causal analysis with a participatory vulnerability framework tailored to coastal management. By analyzing multiple natural and socio-economic parameters, the results identify land use and land cover as the most influential factors, highlighting a shift toward socio-economic prioritization. The model also acknowledges limitations due to reliance on expert judgment and the absence of ground-truth validation. Our findings emphasize the need for location-specific vulnerability models rather than universal frameworks, offering insights for future participatory and evidence-based coastal management strategies. Full article

The construction industry is a major contributor to global carbon emissions, making the decarbonization of its supply chain a critical goal for sustainable development. This study aims to identify key drivers of decarbonization within the construction supply chain and analyze their interrelationships using causal and structural modeling techniques. A bibliometric analysis is conducted to highlight theoretical gaps in the field, followed by the application of the Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) method to identify key decarbonization factors, and the Adversarial Interpretive Structural Modeling (AISM) method to construct a causal model that reveals their interactions. The results identify 17 key factors, categorized into five levels, with low-carbon policy guidance and consumer preferences emerging as the most influential. Based on these findings, a three-tier strategy is proposed to guide decarbonization efforts within the construction supply chain. This research provides theoretical insights into decarbonization and offers actionable recommendations for future industry practices and policy development. Full article

Considering the inherent characteristics of long-term agreements, public–private partnership (PPP) projects are confronted with diverse uncertainties and external challenges. However, existing research has devoted limited attention to the resilience of PPP projects. This study seeks to identify governance factors influencing PPP project resilience and analyze the interconnections among these factors in fostering such resilience. A governance framework for PPP project resilience is proposed, comprising thirteen governance factors across four dimensions: institutional, organizational, contractual, and managerial factors. The interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) techniques are adopted to explore the hierarchical relationships and interactive mechanisms among these governance factors in a systematic view. The findings reveal that strategic alliances, risk allocation and transfer, flexible contracting, and long-term relationship management represent core governance factors critical to enhancing project resilience. Institutional factors are identified as the most foundational determinants within the governance system, while contractual and managerial factors act as mediating elements facilitating the translation of institutional foundations into operational resilience. This study deepened the understanding of the practitioners with regard to the key governance factors and their inter-relationships, which can help systematically enhance the resilience of PPP projects. Full article

Against the backdrop of global economic changes and rapid technological innovation, the sharing economy model is gradually transforming the operational mechanisms of traditional industries. However, some industries have experienced stagnation and recession during this transition, leading to market development constraints. The necessity of this study lies in filling the gap in the existing literature by conducting an in-depth analysis of the critical factors contributing to industrial stagnation and recession in the sharing economy. This study aims to provide concrete countermeasures for businesses and policymakers. The novelty of this research study lies in integrating multiple key variables affecting industrial development, including green production concepts, the circular economy, large-scale production, high-quality product demand driven by industrial automation, the sharing economy, and smart production. By employing multi-criterion decision-making methods, we quantitatively assess the impact of these factors more accurately. This study employs the Multi-Attribute Decision-Making (MADM) model, integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and the Analytic Network Process (ANP) to form D&ANP for analytical research. Highly automated industries are selected as the research subjects. The DEMATEL technique is used to construct the Influential Network Relationship Map (INRM), while the ANP concept is incorporated to develop the D&ANP model. Through the D&ANP method, influential weights are calculated and combined with industry-specific assessments of the suitability of potential causes (or attributes) contributing to economic stagnation and recession to determine the average performance values for each industry. These values are further compared with benchmark suitability performance values to distinguish ideal and non-ideal conditions across industries facing economic stagnation and recession. The analysis results indicate that different industries are influenced by varying factors, requiring strategic adjustments based on their unique development environments. Accordingly, this study provides industry-specific recommendations to optimize business models and resource allocation, mitigate the risks of economic stagnation and recession, and promote sustainable industrial development and economic recovery. The findings of this study not only contribute to empirical research on the impact of the sharing economy on industrial development but also serve as a decision-making reference for businesses. By offering strategic insights, enterprises can better respond to market dynamics, enhance competitiveness, and ensure long-term stable growth. Full article

Proper management of vehicle structural factors related to public transportation safety is vital to formulate maintenance strategies and to enhance transportation safety. Therefore, this work aims to comprehensively identify potential structural factors, assess their impacts as regards causing public transportation vehicle malfunctions, and understand their cause–effect interrelationships. Maintenance management can be improved based on the analysis outcomes. Multi-Criteria Decision-Making (MCDM) techniques are widely applied to decision-making problems. However, due to the advanced and complex structures of modern vehicles, conventional single-used MCDM techniques encounter limitations in their ability to thoroughly account for all potential failure factors and to systematically manage the causal interrelationships, which makes the analysis results less practically applicable. To overcome these challenges, this article proposes an innovative MCDM framework. Specifically, Failure Tree Analysis (FTA) and the Interval-Valued Pythagorean Fuzzy Analytic Hierarchy Process (IVPF-AHP) are integrated to construct the logical relationships between the failure structural factors from real-world maintenance records. The factors are ranked and selected based on their severity influence and occurrence likelihood influence. Subsequently, the Interval-Valued Pythagorean Fuzzy Decision-Making Trial and Evaluation Laboratory (IVPF-DEMATEL) takes causal diagrams to identify interdependencies between the factors based on the mitigated ambiguity of human assessments. A case study in the public transportation bus domain is conducted to demonstrate the effectiveness of the proposed MCDM framework. The results offer insightful maintenance suggestions for public transportation operators and engineers to save human labor and material resources. Full article

Biodiversity is essential for the health and stability of our planet, contributing to ecosystem services like pollination, nutrient cycling, and climate regulation. However, it faces significant threats from human activities, including habitat destruction and pollution. Transportation infrastructure, if not carefully managed, can fragment habitats and disrupt wildlife migration, exacerbating biodiversity loss. Thus, incorporating environmental and biodiversity considerations into transport planning is crucial for promoting long-term sustainability. Accordingly, the goal of this paper is to define a framework for evaluating and ranking intermodal transport routes based on their impact on the environment and biodiversity. The study employs a Geographic Information System (GIS)-based Multi-Criteria Decision-Making (MCDM) model, combining input from interactive GIS maps and stakeholders with a novel hybrid approach. The MCDM part of the model combines fuzzy Delphi and fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods for obtaining the criteria weights and the Axial Distance-based Aggregated Measurement (ADAM) method for obtaining the final ranking of the routes. This methodology application on several Trans-European Transport Network (TEN-T) routes revealed that the Hamburg/Bremerhaven–Wurzburg–Verona route had the least environmental and biodiversity impact. The study identified the Rotterdam–Milano route as the optimal choice, balancing sustainability, ecological preservation, and transport efficiency. The route minimizes ecological disruption, protects biodiversity, and aligns with European Union strategies to reduce environmental impact in infrastructure projects. The study established a framework for evaluating intermodal transport routes based on environmental and biodiversity impacts, balancing efficiency with ecological responsibility. It makes significant contributions by integrating biodiversity criteria into transport planning and introducing a novel combination of GIS and MCDM techniques for route assessment. Full article

The primary concern of research in the area of fraud risk relevant to sustainability reporting lies in understanding the potential for fraudulent or misleading reporting practices and developing strategies and tools to identify and prevent such behaviors. Taking into consideration that significant research has yet to be conducted on fraud risk models associated with sustainability reporting, this study represents an innovative contribution. It uses a mixed-methods approach to design a fraud risk model based on sustainability reporting. Given its type and approach, this research does not posit any hypotheses involving thematic analysis and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. This study is exploratory and applied, aiming to design a model through a mixed-methods methodology. Therefore, the research is hypothesis-free and instead utilizes a qualitative sample of experts and academics in the field of accounting from Iran and Denmark. The DEMATEL technique identifies key external and internal factors that significantly impact sustainability reporting, including comprehensive internal controls, strong governance and oversight, training and awareness, the utilization of technology, and data analytics. The influence of stakeholders, third-party audits, and the credibility of sustainability reports emerges as particularly significant in this context, exceeding the impact of other factors. These findings underscore that stakeholders, third-party audits, and report credibility to play a more prominent role in shaping sustainability performance compared to other considerations. This would imply that such variables remain key drivers in the perceptiveness and effectiveness of sustainability performance. Full article

In the evolving landscape of cybersecurity, traditional information technology (IT) infrastructures often struggle to meet the demands of modern risk management frameworks, which require enhanced security, scalability, and analytical capabilities. This paper proposes a novel artificial intelligence (AI)–driven IT infrastructure backed by blockchain technology, specifically designed to optimize risk management processes in diverse organizational environments. By leveraging artificial intelligence for predictive analytics, anomaly detection, and data-driven decision-making, combined with blockchain’s secure and immutable ledger for data integrity and transparency, the proposed infrastructure offers a robust solution to existing challenges in risk management. The infrastructure is adaptable and scalable to support a variety of risk management methodologies, providing a more secure, efficient, and intelligent system. The findings highlight significant improvements in the accuracy, speed, and reliability of risk management, underscoring the infrastructure’s capability to proactively address emerging cyber threats. To ensure the proposed model effectively addresses the most critical issues, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique will be used to analyze and evaluate the interrelationships among the existing critical factors. This approach evaluates the interrelationships and impacts of these factors, verifying the model’s comprehensiveness in managing organizational risk. This study lays the foundation for future research aimed at refining AI-driven infrastructures and exploring their broader applications in enhancing organizational cybersecurity. Full article

Industry 5.0 (I5.0) builds upon Industry 4.0 by emphasizing the role of workers in production processes and prioritizing socio-economic-environmental sustainability. It has been shown that I5.0 can enhance sustainability within supply chains (SCs). However, companies in emerging economies, especially small and medium-sized manufacturing enterprises (SMEs), which are crucial to developing economies, face challenges in implementing these concepts. These SMEs are in the early stages of adopting I5.0 to foster sustainability in their SCs and require urgent identification of key I5.0 enablers. Unfortunately, the current literature lacks research on this topic specifically within the context of SMEs in emerging economies. To bridge this gap, this study identifies the enablers of I5.0 that promote sustainability diffusion in SCs, using China’s SME manufacturing sector as a case study. The integrated framework for applying multiple criteria decision-making (MCDM) techniques in this study aims to assist decision-makers in evaluating different options and making optimal choices in a systematic and structured manner when faced with complex situations. The study employs the fuzzy Delphi method (FDM) to identify 15 key I5.0 enablers and categorize them into three clusters. Grey-DEMATEL is subsequently utilized to determine the causal relationships, rank the importance of the enablers, and construct an interrelationship diagram. This study found that ‘availability and functionality of resources’; ‘top management support, active participation, and effective governance’; ‘support from government, regulators, and financial resources’; and ‘introduction of safer and more efficient robotic systems for human–robot interaction and collaboration’ serve as the primary means of resolving issues. Overall, this study helps managers, practitioners, and policymakers interested in I5.0 applications to promote sustainability in the supply chain. Full article

Safety climates are a crucial factor in determining the safety performance of organizations. One of the most influential factors that affect safety climates is safety management, which consists of several aspects. None of the previous research has investigated the relationship between these managerial aspects. Consequently, the main goal of the current research is to apply the DEMATEL technique in order to determine the interrelationships among the managerial aspects that affect safety climates. This study highlights the critical role of management expertise, including technical knowledge and effective leadership, in driving safety cultures. Adherence to safety rules and a strong commitment to these rules across an organization are equally important. Additionally, responding to safety concerns by taking prompt action toward correcting a situation is essential for ensuring the safety of a workplace. When these factors are applied effectively, they play a significant role in preventing injuries, accidents, and risks in the workplace. Recognizing the most important causal factors of the study’s findings, it presents useful information to both policymakers and industrial leaders in ranking their priorities toward improving safety. Full article

The study examines the effects of semiconductor scarcity on the electric vehicle (EV) supply chain caused by an increase in electronics demand after the 2020 automobile industry downturn due to the COVID-19 pandemic. The rising demand for semiconductor chips in the automotive industry, especially in EVs, necessitates strategic measures for original equipment manufacturers and suppliers to strengthen supply chain resilience. This study uses a consequence-based decision-making framework that uses a hybrid Decision-Making Trial and Evaluation Laboratory (DEMATEL) method with Interpretive Structure Modeling (ISM). By leveraging this innovative approach, the research unveils complex causal relationships among supply chain strategies, providing quantifiable insights for prioritizing resilience in the face of multifaceted risks such as trade wars, regulatory changes, and raw material shortages. In addition, the study enhances our comprehension of supply chain resilience within the electric vehicle sector by illuminating aspects that have not been thoroughly examined by the Multi-Criteria Decision Analysis (MCDA) technique employed in this research. The analysis includes the adoption of multisourcing, fostering ecosystem partnerships, and improving supply chain visibility. Through these novel insights, this analysis aims to empower stakeholders and small- to medium-sized enterprises to navigate future automotive market dynamics, with a focus on evolving manufacturer–supplier relationships in the midst of technological advancements. Full article

This study is based on an investigation of shared mobility in Chinese cities, which identifies the factors affecting the sustainable development of shared mobility based on the theoretical framework of TDM (travel demand management). Through a literature review and expert interviews, the FUZZY-DEMATEL-ISM-MICMAC integration model was used to screen 21 influencing factors from aspects that fit the research theme. Triangular fuzzy numbers are used to quantify the subjective scores of nine expert groups and weaken the subjective influence of expert scores. The logical relationships among DEMATEL technology-building factors and ISM technology-based factors are divided into levels. The MICMAC technique is used to divide the types of factors according to the driving power and dependency. The results show that (1) the influence factors of the “soft strategy” and “hard strategy” in the framework of TDM are determined. In the soft strategy, we should focus on “shared mobility education” (shared mobility education, shared mobility publicity and shared mobility “environment” information) and “community organization” (community organization and advocacy and organizational interaction). In the hard strategy, we should focus on “traffic planning and measures”, “dedicated lanes”, “parking facilities”, and “financial subsidies”. (2) The ISM recursive structure model is divided into five layers. Among them, shared mobility education, shared mobility operating technology, and organizational interaction are at the deep root level, which can continuously influence other factors in the long run. (3) In MICMAC, the number of related factors is large. When making decisions on these factors, managers should comprehensively consider the correlation of factors and adjust the use of factors from an overall perspective. This study can help managers identify the key factors affecting the sustainability of shared mobility and make targeted recommendations. Full article

The objective of this study is to enhance the resilience of the coal-to-liquids (CTL) industrial chain and supply chain to withstand increasing shock pressures. There is an urgent need to improve the resilience of the industrial chain and supply chain. This paper identifies 21 resilience-influencing factors from 4 perspectives: absorption capacity, adaptability, recovery capacity, and self-learning capacity; it then constructs an evaluation indicator system. The Interval Type 2 Fuzzy-Decision-Making Trial and Evaluation Laboratory-Analytic Network Process (IT2F-DEMATEL-ANP) method is adopted to determine the weights of the indicator system, and a resilience evaluation is performed based on the Interval Type 2 Fuzzy-Prospect Theory-Technique for Order Preference by Similarity to an Ideal Solution (IT2F-PT-TOPSIS) method. Furthermore, in the case of the CTL industrial chain and supply chain of China Shenhua Energy Group Ningxia Coal Industry Co., Ltd. (CENC) (Ningxia, China), this study ranks the resilience level from 2018 to 2022 to identify the factors that have contributed to a reduction in resilience and to implement measures to enhance the resilience of the CTL industrial chain and supply chain. The results show that the level of the CTL industrial chain and supply chain resilience was lowest in 2020, while it was highest in 2021. Factors such as the degree of domestication of key technologies, the rationality of the CTL industry layout, and the stability of supply and demand chains are identified as significant determinants of resilience levels. This points the way to enhancing the resilience of the CTL industry and supply chain. Full article