Search Results (308)

In order to achieve the ‘dual carbon’ goal, based on the DEMATEL-ISM model, 19 main factors affecting the carbon emissions of prefabricated buildings were preliminarily identified from five dimensions, including government decision-making, technical environment, social economy, energy consumption, and market supply and demand. The logical relationship, hierarchical structure, and importance between the factors were clarified, and finally, the four influencing factors were determined. According to the causal feedback relationship between the above four factors in the system flow from 2010 to 2030, eight different control scenarios were proposed, and the impact and change trend of each control scenario on the reduction of carbon emissions of prefabricated buildings were analyzed. The research results show that the key factors for carbon emissions from prefabricated buildings include 14 outcome factors and 5 cause factors, and that the causal factors are key drivers. They are the standard specification system, the incremental cost of prefabricated buildings, investment in scientific and technological innovation, and the level of prefabricated integrated technology. The key factors were structurally stratified from the essential level to the superficial level in four tiers. The first tier of the standard specification system is the surface causal factor affecting carbon emissions from prefabricated buildings. Investment in scientific and technological innovation in the second and third tiers, and the level of prefabricated integrated technology are the causes of the transition. The incremental cost of prefabricated buildings at the fourth level is the essential causal factor. Finally, based on the data related to carbon emissions of prefabricated buildings in Yunnan, China, and verified in eight regulatory scenarios, the results of the study can effectively reveal the carbon emission reduction transmission path of prefabricated buildings, which can provide a reference for the development of prefabricated buildings and carbon emission reduction strategies. Full article

New productive forces are the new impetus for the high-quality development of the marine economy. To accurately measure the development level of marine new productive forces, this study constructs an evaluation index system from four aspects: development impetus, development structure, development mode, and development achievements. This study determines the combination weights of indicators based on relative entropy. Kernel density estimation, spatial Markov chain and Dagum Gini coefficient are used to analyze the spatiotemporal evolution, regional disparities and sources of marine new productive forces in coastal provinces of China. Finally, the decision-making trial and evaluation laboratory together with interpretative structural modeling (DEMATEL-ISM) is used to analyze the key influencing factors of marine new productive forces. Results show that the marine new productive forces have been increasing year by year, but the overall level is relatively low. There is a phenomenon of “club convergence” in the development level of marine new productive forces, and the state transfer occurs between adjacent types. The overall variation in marine new productive forces is showing a downward trend, with disparities arising mainly from inter-regional variation and hypervariable densities. The key influencing factors include investment in marine R&D, the openness of foreign investment, the openness of foreign trade, and investment in pollution control. The study conclusion provides support for designing a development path for marine new productive forces that conforms to regional characteristics. 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

Background: Supply chains operate under the changing influences of multiple external and internal factors. Sustainable supply chain development requires an assessment of these factors, as well as drivers and barriers. Various sustainability assessment criteria, methods, and models based on the consideration of the influence of different factors are used depending on the type and structure of the supply chain. Methods: The combination of DEMATEL and CRADIS multi-criteria methods is applied to rank the efficiency of drivers for achieving sustainable development goals, both for the supply chain as a whole and for each of its structural elements. Results: This study proposes a system of drivers for sustainable supply chain development. The peculiarity of the used supply chain model is the universality of its structure, which ensures the realization by the structural elements of the chain of all known functional areas of logistics. A framework for sustainable supply chain drivers’ multi-criteria assessment based on the use of the original two-level system of drivers’ assessment criteria is developed. Conclusions: The results of the supply chain sustainability drivers’ ranking and the framework developed by the authors are intended to justify decisions on the green logistics methods and instrument selection. Full article

The schedule is a critical factor in the development of prefabricated buildings. This paper establishes the schedule risk influencing factors for prefabricated building projects across five dimensions—design, production, transportation, installation, and others—encompassing a total of 14 factors. By integrating DEMATEL and ISM, it constructs a hierarchical network model using expert knowledge and maps it to Bayesian networks (BN), and the node probabilities were calculated using fuzzy set theory combined with the noisy-OR gate model. This DEMATEL-ISM-BN model not only infers the probability of schedule risk occurrence in prefabricated construction projects through causal reasoning and controls the schedule risk of prefabricated construction projects, but it also deduces the posterior probabilities of other influencing factors when a schedule risk occurs through diagnostic reasoning. This approach identifies the key factors contributing to schedule risk and pinpoints the final influencing factors. Research has shown that the three influencing factors of “tower crane worker lifting level”, “construction worker component installation technology”, and “design changes” significantly affect project progress, providing a new risk assessment tool for prefabricated building project progress, effectively helping enterprises identify potential risks, formulate risk control strategies, improve project success rates, and overall benefits. Full article

This study investigates wellbore leakage accidents associated with Carbon Capture, Utilization, and Storage Enhanced Oil Recovery (CCUS-EOR) to identify causal factors, clarify their degrees of influence, hierarchical structures, and substantive roles, while revealing the causal mechanisms behind these incidents to promote the safe development of CCUS-EOR. A distinctive aspect of this research is its integrated framework, which effectively combines the theory of integrated safety management with advanced methodologies such as the Decision-Making Trial and Evaluation Laboratory (DEMATEL), Interpretive Structural Models (ISM), and Cross-Impact Matrix Multiplication (MICMAC) to systematically analyze the interdependencies among risk factors. This comprehensive approach provides a nuanced understanding of the interactions among the 20 identified influencing factors across four domains, organized into a multilayered, three-stage structure. Furthermore, the study uncovers two critical causal pathways for wellbore leakage, namely F17 (lack of supervision and feedback) → F20 (inadequate safety investment) → F16 (lack of education and training) → F3 (weak safety awareness) → F9 (improper material selection) and F13 (high geological activity) → F11 (poor reservoir properties) → F6 (corrosion and aging failure), offering unique insights into risk dynamics that remain underexplored in the existing literature. This study could be enhanced in future research by taking into account a broader spectrum of causal factors, incorporating scenario simulations to facilitate a more comprehensive analysis, and involving a greater number of experts from diverse fields to enrich the insights derived. Full article

Background/Objectives: The health sector is one of the most important sectors, and occupational accidents and occupational diseases that health workers are exposed to are more important compared to those in other sectors. Especially, the increase in health and safety problems faced by hospital workers necessitates the development of an occupational health and safety (OHS) management system model specific to the health sector. Existing health and safety management systems generally do not sufficiently take sectoral dynamics into account, and the adaptation of these standards to the sectors is left to the individual efforts of the users. This situation leads to management systems that lack a sector-specific approach and do not adopt a common language and methodology. Methods: The aim of this study was to create an OHS management system specific to the health sector. While developing the model, AHP and DEMATEL, which are multi-criteria decision-making methods that help people to make complex decisions, were used. Results: By applying these methods, important criteria for the proposed model were determined. The criteria, including “Improvement of the management system of the health institution”, “Determination of control measures”, “Assessment of risks specific to the health institution”, “Identifying hazards specific to the health institution” and “Determining its context”, have been determined as priority criteria and weighted using the AHP and DEMATEL methods. Conclusions: As a result of the findings of this research, designing a unique occupational health and safety (OHS) management system that takes into account the dynamics of the health sector will contribute to the prevention of occupational accidents and occupational diseases in the health sector. Full article

Blockchain technology holds the potential to significantly enhance efficiency and safety in freeport operations. However, fully realising its benefits necessitates a thorough assessment of the obstacles hindering its applications, which often depends on expert opinions characterised by uncertainty and inconsistency. This issue remains inadequately addressed in the existing literature due to the limitations of currently employed methods. To address this gap, this study aims to develop a novel methodology for assessing blockchain adoption barriers in freeports. It makes methodological contributions by combining the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Bayesian Network (BN) methods to identify and quantify complex interrelationships between barriers and facilitate probabilistic predictions of barrier strength. The model is parameterised using the ranked nodes method to reduce the reliance on expert-assigned probabilities. Primary data on barriers’ causal relationships are collected from experts with interdisciplinary experience in blockchain and freeport operations, grounding the analysis in real-world insights. This study makes practical contributions by analysing the blockchain application within a new context (i.e., freeports) and presenting novel findings. Key managerial insights include identifying high investment costs as the most interactive barrier and lack of trust among stakeholders as the most essential barrier. Additionally, evaluating the overall impact of barriers enables targeted strategies for freeport policymakers. Full article

In order to solve the problem that the key risk factors in the construction of mechanical cross passages are relatively vague, the decision-making test and evaluation test method (DEMATEL) and the interpretation structure model (ISM) are combined to analyze safety risks in the construction of mechanical cross passages scientifically and reasonably. Based on the ‘personnel’, ‘material’, ‘machine’, ‘method’, and ‘environment’ of 4M1E comprehensive management, the construction safety risk index system of mechanical method cross passage, including 18 risk factors, is extracted. DEMATEL was used to divide the risk factors into four factor sets: strong cause, weak cause, strong result, and weak result. Furthermore, ISM is used to construct a hierarchical structure diagram of risk factors, and deep risk factors and risk factors with a high node degree are divided. The results show that the safety awareness of construction personnel, the safety technology level of construction personnel, the establishment and implementation of the safety construction system, the level of construction management, and the degree of geological complexity are strong cause-type risk factors with both high centrality and high causality. Additionally, the effect of reinforcement of the internal support system, the setting of the digging parameter, the effect of grouting, and the effect of assembling the pipe sheet comprise the strong result-type risk factors with high centrality. The risk factors with higher node degree in ISM are consistent with the risk factors with higher centrality in the DEMATEL model, which are key factors that play an important role in risk control. Full article

In order to solve the problem of the lack of an index system of influencing factors and an unclear evolution path of prefabricated housing development in Hainan Province, a method of identifying key influencing factors and analyzing the evolution path based on a back propagation neural network (BPNN) and decision experiment and evaluation laboratory (DEMATEL) was proposed. Firstly, the index system of influencing factors was constructed based on grounded theory; then, the key influencing factors were revealed through an expert survey and a BPNN-optimized DEMATEL model; finally, the evolution path of key influencing factors was explored. The research results show that factors F₁ (imperfect standards and specifications), F₂ (imperfect incentives), F₉ (lack of motivation for corporate strategic transformation), F₁₄ (insufficient market demand), and F₁₇ (ununified design product standards) are the top five key influencing factors. Among the three basic paths and three composite paths, the weight of the composite path is higher than that of the basic path, and the degree of influence gradually increases with the complexity of direct and indirect effects between key influencing factors. In addition to coupling the basic path with key influencing factors, the composite path can also be obtained through the interaction evolution of the basic path. Full article

A new safety risk assessment model for battery pack production processes was developed using the DEMATEL-ANP method to analyze the impact and complex relationships of risk-influencing factors. Initially, five major risk-influencing factors were identified, leading to the construction of a 15-factor indicator system. Through the DEMATEL method, these factors were categorized into cause and result factors. Subsequently, by combining the DEMATEL and ANP methods, key risk-influencing factors were identified by comparing ANP weights with hybrid weights adjusted through the DEMATEL-ANP method. Finally, integrating the DEMATEL-ANP method with the fuzzy comprehensive evaluation method allowed us to assess the overall fire safety risk level. Our findings highlighted “hazards in the test process” and “fire hazards” as critical risk factors needing control and elimination in the highly hazardous battery pack production process. This method offers dynamic evaluation and valuable insights for safety management in battery pack production. Full article

In recent years, the increasing complexity of natural disasters has highlighted the limitations of existing emergency material assistance systems. To address these challenges, this study proposes a collaborative adaptation mechanism for “peacetime and emergency integration” and develops a supplier evaluation framework. The framework incorporates multi-dimensional indicators such as profit, business credit, regional advantages, and emergency capability. Using a DEMATEL-ANP-based model, supplier L2 is identified as the optimal choice with a weight of 0.285. A fuzzy comprehensive assessment approach is applied to classify emergency materials based on demand urgency, identifying drinking water, rescue tools, medical supplies, and other critical items as priority resources. The evaluation vectors for these materials range from 0.1540 to 0.9909. This study enhances emergency material management through improved information systems, a better control of critical processes, and a unified assurance strategy. It provides theoretical support and practical guidance for more scientific and standardized disaster management practices. 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

Global value chains (GVCs) play a pivotal role in advancing export structure optimization in East Asia. As GVCs restructure and digital technology rapidly progresses, effectively leveraging these chains for export competitiveness has become essential. However, research has rarely examined the key factors in GVC restructuring or explored how innovation, policy frameworks, and market access contribute to export optimization. To address these research gaps, this study systematically identifies key success factors for promoting export optimization in East Asian countries under GVC restructuring, based on global value chain theory, resource-based theory, and innovation diffusion theory. Through a literature review and expert interviews, 14 pivotal factors were analyzed using DEMATEL (Decision Making Trial and Evaluation Laboratory), ISM (Interpretive Structural Modeling), and MICMAC (Cross-Impact Matrix Multiplication Applied to Classification) methods. Findings show that strengthening innovation capabilities, facilitating technology spillovers, investing in cross-border e-commerce, and improving market access policies are crucial drivers of export optimization. Policies that enhance market access, promote international standards, and support investments in digital platforms demonstrate strong influence within the GVC system. Collectively, these factors elevate East Asia’s position and competitiveness within GVCs. This study contributes to the theoretical framework on GVC restructuring and export optimization, offering insights into resource-based and innovation diffusion strategies and practical guidance for export policy development. Full article

Resource-based cities are vulnerable to the depletion of natural resources and urgently need to undergo a green transformation to avoid the so-called “resource curse” and achieve sustainable development. At present, there is a lack of a scientific and reasonable indicator system and theoretical model to guide the evaluation of the effectiveness of green transformation of resource-based cities. To undertake a comprehensive analysis of the causality of indicators, this study employs the DPSIR (Driving Force–Pressure–State–Impact–Response) model to construct an evaluation index system for the effectiveness of green transformation of resource-based cities. The DEMATEL (Decision-Making Trial and Evaluation Laboratory) method is employed to explore the level of importance of the evaluation indicators and the causal relationships between the evaluation indicators. The VIKOR (‘VlseKriterijumska Optimizacija I Kompromisno Resenje’ in Serbian) method is introduced to evaluate the effectiveness of green transformation of resource-based cities. This study selects Shandong Province, a strategically important energy resource region in China, as an example. The results of the study show that the effectiveness of green transformation of resource-based cities in Shandong Province as a whole was on an upward trend from 2013 to 2021. This study categorizes the phases into rapid start-up period, adjustment and optimization period, and recovery and acceleration period. Currently, the green transformation shows remarkable effectiveness. The effectiveness of green transformation within each dimension of the DPSIR model reveals a ranking of response > pressure > driving force > state > impact. By incorporating regional characteristics, this study explores and proposes recommendations to enhance the green transformation of resource-based cities. It can not only furnish policy references for green transformation of similar resource-based cities, but also offer case study practices for different types of resource-based cities to achieve sustainable development. Full article