Decision Making Trial And Evaluation Laboratory Method Research Articles

Application of the DEMATEL method for quantitative analysis of risk factors for railway investments in Poland.

The paper presents the results of research on the influence of risk factors on the implementation of railway investments in Poland (build stage) and deals with a detailed diagnosis of relation between factors. The application of DEcision MAking Trial and Evaluation Laboratory (DEMATEL) method for the analyses allowed to develop a cause-and-effect model of key factors and analyse the importance of the factors. Eleven factors identified in eariel studies as the most important risk factors were examined. It was found that the factors: errors in the preparation of tender documents (10.38%), errors in project documentation (10.02%), improperly estimated time of completion of the investment by the Employer (9.82%), internal regulations of PKP Polskie Koleje Państwowe S.A. (Polish State Railways) not coordinated with the provisions of contracts (9.51%) have the highest degree of importance. Factors: too many external institutions involved in the investment process and internal regulations of PKP Polskie Koleje Państwowe S.A. (Polish State Railways) not coordinated with the provisions of contracts, have the greatest net impact on the other factors. The relations between the factors and factors importance are valuable knowledge for engineers, enabling the project to be implemented according to the planned schedule and investment cost.

Analyzing the drivers of the low-carbon construction supply chain based on an integrated DEMATEL–ANP approach

PurposeCarbon reduction in the construction supply chain can critically affect the construction industry’s transition to an environmentally sustainable one. However, implementing carbon reduction in all parties is restricted because of the poor understanding of the drivers influencing the low-carbon construction supply chain (LCCSC). The purpose of this paper is to systematically identify the drivers of LCCSC, analyze their causality, and prioritize the importance of their management.Design/methodology/approachA decision-making analysis process was developed using an integrated decision-making trial and evaluation laboratory (DEMATEL)–analytical network process (ANP). First, the hierarchical drivers of the LCCSC were identified through a literature review. The DEMATEL method was subsequently applied to analyze the interactions between the drivers, including the direction and strength of impact. Finally, the ANP analysis was used to obtain the drivers’ weights; consequently, their priorities were established.FindingsVarious factors with complex interactions drive LCCSC. With respect to their influence relationships, incentive policy, regulatory policy, consumers’ low-carbon preference, market competition, supply chain performance, and managers’ low-carbon awareness have more significant center degrees and are cause drivers. Their strong correlations and influence on other drivers should be noticed. In terms of weights in the driver system, regulatory policy, consumers’ low-carbon preference, supply chain performance, and incentive policy are the key drivers of LCCSC and require primary attention. Other drivers, such as supply chain collaboration, employee motivation, and public participation, play a minor driving role with less management priority.Originality/valueDespite some contributing studies with localized perspectives, the systematic analysis of LCCSC drivers is limited, especially considering their intricate interactions. This paper establishes the LCCSC driver system, explores the influence relationships among the drivers, and determines the key drivers. Hence, it contributes to the sustainable construction supply chain domain by enabling decision-makers and practitioners to systematically understand the drivers of LCCSC and gain management implications on priority issues with limited resources.

Evolutionary model and risk analysis of ship collision accidents based on complex networks and DEMATEL

To manage and control ship collision risk, this paper aims to develop a quantitative risk analysis approach based on complex networks and Decision-making Trial and Evaluation Laboratory (DEMATEL), to study the evolution of ship collision accidents. Firstly, through the search, selection and analysis of accident investigation reports of ship collisions in the world, 46 Risk Influential Factors (RIFs) were identified, and a network model for the evolution of ship collision was established. Secondly, a risk analysis of the evolution model for ship collision accidents was conducted by utilizing the topology characteristics of the complex network theory. Thirdly, a robustness analysis was used to identify 10 key RIFs involved in ship collisions from a global network perspective, and the grey relation analysis technique was employed to verify the key RIFs. Finally, the DEMATEL method was utilized to identify 11 key RIFs from a perspective of causality, and corresponding risk control measures were proposed to mitigate those key RIFs. The research results provide theoretical support for identifying the key RIFs and controlling the risk transmission of ship collision, and have practical significance for preventing the occurrence of ship collision accidents and ensuring the safe navigation of ships.

Large-scale group hierarchical DEMATEL method with automatic consensus reaching

Decision-making trial and evaluation laboratory (DEMATEL) is widely used because of its ability to effectively analyze nonlinear relationships between factors in complex systems. With the increasing complexity of decision-making problems, large-scale group decision-making (LSGDM) has become the norm. Most existing DEMATEL methods are only suitable for small-scale groups and simple systems. This study, therefore, proposes a large-scale group hierarchical DEMATEL method that considers consensus reaching. The DEMATEL method for LSGDM faces three challenges: large differences in knowledge structures, difficulty coordinating expert opinions, and slow group-consensus convergence. To address these challenges, first, we use hierarchical decomposition to decompose the complex system into simple systems with different levels to reduce the difficulty of decision-making in complex systems. Second, considering the limitations of expert knowledge and experience, we use the basic probability assignment function to extract the opinions of experts at different levels of subsystems and factors. Third, we divide experts into different clusters using K-means clustering to solve the problem of difficult expert-opinion coordination. Fourth, we design two types of consensuses (intrasubgroup and intersubgroup consensus) and an efficient new type of opinion autocorrection mechanism to solve the problem of the slow convergence of intragroup consensus and improve the efficiency of consensus reaching. Finally, we demonstrate the superiority of the proposed method through data analysis and method comparison.

Design Warehouse Information System to Increase Stock Accuracy

In its development, the warehouse is currently not only used as a room for storage but has been integrated with the information system used in carrying out its warehousing activities. One of the objectives of the warehousing information system is to achieve stock accuracy according to the Company's target. PT Zoomlion Indonesia Heavy Industry (PT. ZIHI) is one of the heavy equipment industry companies engaged in the provision of heavy equipment, construction and plantations that have used the SAP system in managing their inventory but have not reached the stock accuracy target expected by the Company because in SAP there is no warehouse module. The purpose of this study is to find out what causative factors can affect stock inaccuracies in Jakarta warehouses, find out the dominant factors that cause stock inaccuracies and to find out the improvements made in increasing stock accuracy in PT Zoomlion Indonesia's Jakarta warehouse. The methods used are the DEMATEL (Decision Making Trial and Evaluation Laboratory) method, five why analysis, fishbone diagrams, for further design of the bin location system database. The results showed that (1) the factors causing stock accuracy inaccuracies at PT Zoomlion Indonesia Heavy Industry were due to increased receiving, storage, and shipping activities and limited manpower, and were not supported by a system that facilitates the location of parts. Meanwhile, according to fishbone analysis, the factor diagram that causes stock accuracy is not optimal is done through the five whys approach, which consists of human factors, methods, materials and the environment, (2) the dominant factors that cause inaccuracies in stock accuracy occur at risk (E10) There is no SAP support system for registering Bin location, (3)The web database stock location design developed is a form of improvement effort from the manual monitoring system that is not running smoothly. This stock location database will provide information about materials while in the warehouse room. Therefore, the use of a mobile- based web server can make it easier for users to access the system from a smartphone device.

Hybrid multi-criteria decision making approach proposal for evaluating workloads of aircraft maintenance technicians.

Aircraft maintenance technicians (AMTs) have the most difficulty in terms of total workload criteria working in line maintenance. This is a very important problem for the Aircraft Maintenance Organization. A systematic and scientific approach is required for its solution. This study proposes a new Multi-Criteria Decision Making (MCDM) based approach to evaluating the total workloads of AMTs to identify the most challenging AMT tasks in the aircraft maintenance organization. A new hybrid MCDM approach is proposed by integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Technique for Order Preference by Similarity (TOPSIS) methods to compare AMTs on the basis of workloads according to license categories. The hybrid method proposed in this study evaluates the total workload under three main titles: mental, physical, and environmental workload. Focusing on AMTs working in line maintenance of an aircraft maintenance organization, this study revealed that the most important workload criteria determined by the DEMATEL method are lower back strain, upper back strain, time pressure, and air temperature criteria. The results of the TOPSIS method showed that the license categories of AMTs are sorted according to the workloads as follows: A, B2, B1, and B1 + B2. The AMTs holding a "Category A" license have fewer workloads than the other categories. The findings of the study reveal some measures that might allow authorities to minimize the workload of AMTs. In addition, the study contributes to the literature because there are few studies that systematically analyze total workloads by using MCDM methods.

Influencing factor analysis and enterprise evaluation of lithium-ion battery recycling based on improved DEMATEL method

Spent lithium-ion battery (LIB) recycling can create great pollution to the environment. Understanding the safety, environment, technique, and regulation factors’ impact on the recycling process is crucial. Due to the complexity of the relevant factors, and there is a certain degree of correlation and dependence between the factors, the Decision Making Trial and Evaluation Laboratory (DEMATEL) method is used to analyze the factors’ degree of impact in this study. As the experts are ambiguous about some relations between the factors, it is impossible to conduct integrated evaluation. The improved DEMATEL method is proposed in this study to make up the missing relations. Further, the weights of the factors will be calculated. In the improved DEMATEL method, the numerical scale of a linguistic term set is introduced. Therefore, the numerical scale used by experts can not only be uniform and symmetrical, but can also be non-uniform symmetric, non-uniform asymmetric, etc. Finally, both reusing and recycling companies are included in this study and their factors’ importance weights were analyzed with the fuzzy comprehensive evaluation method.

Exploring the curricular and pedagogical decision criteria for research-based learning design in undergraduate studies

Learning design has a multifaceted nature requiring a range of course- and institutional considerations. Analyzing the decision criteria’s influence on research-based learning design helps understand the causes of the success/failure of the approach in achieving the teaching goals to improve the study programs. This study explores the interrelationship between the curricular and pedagogical criteria for research-based learning design decisions at the undergraduate level. For this purpose, the DEcision-MAking Trial and Evaluation Laboratory (DEMATEL) method is used to systematically analyze the decisive criteria and their causal relationships. Feedback from education professionals and university professors from Scandinavian universities is used to validate the pedagogy decision framework and provides input into the DEMATEL method. The student's role in the course is identified as the central criterion, featuring the highest level of interactions in the network of curricular and pedagogical decision criteria. Results are supportive of the identified institutional and course-specific criteria as prerequisites for the study outcomes.

Analysis of earthquake resilience factors for buildings: the case of Istanbul high-rise buildings

PurposeThe objective of this study is to investigate the concept of “earthquake resistance” in high-rise buildings and assess the current level of structural strength in the areas where these structures are situated. The study aims to identify and implement necessary measures to enhance resilience in these areas. A comprehensive literature review was conducted to develop a conceptual framework focusing on earthquake resistance's meanings, stages and physical elements to achieve these goals.Design/methodology/approachThis study focuses on Istanbul, a city known for its high earthquake risk, specifically targeting the Atasehir district. The research utilizes the DEMATEL (Decision-Making Trial and Evaluation Laboratory) method to evaluate urban resilience parameters. Additionally, the Fuzzy TOPSIS (Preference Ranking Technique by Similarity) method is employed to analyze the location of five buildings in Atasehir, using criterion weights derived from this methodology.FindingsThe findings indicate that resilience varies depending on the distance of the buffers. Moreover, the amount and quality of urban equipment in the study areas have a significant impact on the earthquake resistance level of the surrounding areas where high-rise buildings are situated. Building upon this analysis, the study suggests the implementation of measures aimed at augmenting the quantity and quality of urban facilities in the study areas, consequently enhancing urban resilience.Originality/valueThe originality and value of this study lie in its examination of seismic resilience within the context of high-rise buildings and the identification of necessary measures to increase resilience in areas where these structures are prevalent. By focusing on Istanbul, a city with a high earthquake risk, and specifically selecting the Atasehir district as the study area, this research provides a comprehensive conceptual framework for understanding urban resilience and its physical components. Moreover, the study offers a fresh perspective on urban resilience by highlighting the influence of tall buildings on the surrounding areas. Ultimately, it provides practical recommendations for architects, urban planners and other stakeholders to improve regional earthquake resilience.

Multiple-attribute group decision-making method of linguistic q-rung orthopair fuzzy generalized power average operator based on DEMATEL

Linguistic q-rung orthpair fuzzy sets (Lq-ROFSs) can facilitate describing the uncertainty and the vagueness information existing in the real world. Based on the advantages of Lq-ROFSs, this paper innovatively puts forward a new method to solve the multi-attribute group decision-making (MAGDM) problems when the attribute weight is completely unknown, and proves the feasibility and effectiveness of this method through illustrative examples. Firstly, we propose the linguistic q-rung orthopair fuzzy generalized power average (Lq-ROFGPA) operator, which considers not only the importance of the data itself, but also the interaction between the data, and prove its properties. In particular, the linguistic q-rung orthopair fuzzy weighted generalized power average (Lq-ROFWGPA) operator takes into account the weight between data, which can better aggregate evaluation information. Then, we introduce decision making trial and evaluation laboratory (DEMATEL) method of the linguistic q-rung orthpair fuzzy numbers (Lq-ROFNs) to analyze the causal relationship and key elements of complex systems. Based on DEMATEL method, we further develop a weight model to calculate the attribute weights, which can make up for the deficiency which is the influence of the interaction between attributes that the existing weight determination method for Lq-ROFNs does not consider. Finally, we present a new MAGDM method based on the Lq-ROFWGPA operator and DEMATEL method. Further, several practical examples are given to illustrate the effectiveness and superiority of this new method in comparison with other existing MAGDM methods.

Analysis of project complexity factors and their interdependencies in metro rail projects

PurposeThe purpose of this paper is to identify and analyze the interdependence of project complexity factors (PCFs) in metro rail projects using the Decision-Making Trial and Evaluation Laboratory (DEMATEL). The study provides qualitative and quantitative analysis of project complexities factors and their relationships. The results of the study facilitate effective project planning, proactive risk management and informed decision-making by stakeholders.Design/methodology/approach This study employs a case-based method for identifying PCFs and a DEMATEL method for analyzing the interdependence of complexity factors in metro rail projects. Initially, PCFs were identified through an extensive literature review. To validate and refine these factors, semi-structured interviews were conducted with thirty experienced professionals, each having 5–20 years of experience in roles such as project management, engineering, and planning. Further, elevated and underground metro rail projects were purposefully selected as cases, for identifying the similarities and differences in PCFs. A questionnaire survey was conducted with various technical experts in metro rail projects. These experts rated the impact of PCFs on a five-point Likert scale, for the evaluation of the interdependence of PCFs. The DEMATEL technique was used to analyze the interdependencies of the PCFs.Findings Metro rail projects are influenced by project complexity, which significantly impacts their performance. The analysis reveals that “design problems with existing structures,” “change in design or construction” and “land acquisition” are the key factors contributing to project complexity.Originality/value The study of project complexity in metro rail projects is limited because most of the studies have studies on examining complexity in mega projects. The existing literature lacks adequate attention in identifying project complexity and its effects on metro rail project performance. This research aims to bridge this gap by examining project complexity and interdependencies in metro rail projects.

Identification of Key Factors of Digital Transformation of Manufacturing companies Using Hybrid DEMATEL Method

This study constructs the influencing factors system of digital transformation of manufacturing companies and determines the influencing factors of digital transformation of manufacturing companies from the technical level, the ability level, the environmental level in order to promote the process of digital transformation of manufacturing companies, consider the impact of technology, capacity and environment on digital transformation of manufacturing. To identify the most important factors and crucial factors, developed a model for identifying critical factors based on the hybrid DEMATEL (Decision-Making Trial and Evaluation Laboratory) methodology. Combined with the related data, this study carries out empirical analysis to demonstrate and verify the influencing factors system of digital transformation of manufacturing companies with the help of hybrid DEMATEL method. The empirical analysis results indicate that the investment share of digital technology, the benefit level of company of manufacturing industry and government support are the crucial factors, and the construction level of digital platform, the technical level of employees, level of construction of digitized equipment and industrial supporting capacity are the non crucial factors. The feasibility and validity of hybrid DEMATEL method are verified.

A Study of the Factors Influencing the Construction Risk of Steel Truss Bridges Based on the Improved DEMATEL–ISM

To enhance the safety management of steel-truss-bridge construction, an evaluation method based on the improved DEMATEL–ISM was proposed to analyze the risk factors involved in such construction. Decision Making Trial and Evaluation Laboratory (DEMATEL) is a method for systematic factor analysis that utilizes graph-theory and -matrix tools, allowing for the assessment of the existence and strength of relationships between elements by analyzing the logical and direct impact relationships among various elements in a system. The distinctive feature of Interpretative Structural Modeling (ISM) is the decomposing of complex systems into several subsystems (elements) and constructing the system into a multi-level hierarchical structural model through algebraic operations. Specifically, triangular fuzzy numbers are introduced initially to improve the direct influence matrix in the DEMATEL method, thereby reducing the subjectivity of expert evaluations. The degree of influence, influenced degree, centrality degree, and causality degree of each influencing factor are determined and ranked based on the above analysis. In response to the characteristics of top-push construction, 20 key factors were selected from four aspects: “human, material, environment, and management”. The top five identified influencing factors are displacement during pushing (X10), safety-management qualification (X18), local buckling (X14), overturning of steel beams (X13), and collision with bridge piers during guide beam installation (X7). Subsequently, corresponding solutions were proposed for different influencing factors. The results of the study offer targeted measures to enhance the safety management of steel truss bridge construction and provide a reference for accident prevention.

Large-scale group-hierarchical DEMATEL method for complex systems.

Existing Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods are mostly suitable for simple systems with fewer factors, and lack effective integration of expert knowledge and experience from large-scale group populations, resulting in a potential compromise of the quality of the initial direct relation (IDR) matrix. To make DEMATEL better suited for the identification of critical factors in complex systems, this paper proposes a hierarchical DEMATEL method for large-scale group decision-making. Considering the limitations of expert knowledge and experience, a method based on expert consistency network for constructing the expert weight matrix is designed. The expert consistency network is constructed for different elements, and the weights of experts in different elements are determined using the clustering coefficient. Following the principles of the classic DEMATEL method, the steps for identifying key elements in complex systems using the large-scale group-hierarchical DEMATEL method are summarized. To objectively test the effectiveness and superiority of the decision algorithm, the robustness of the algorithm is analyzed in an interference environment. Finally, the superiority of the proposed method and algorithm is verified through a case study, which demonstrating that the proposed decision-making method is suitable for group decision-making in complex systems, with high algorithm stability and low algorithm deviation.

Comparing Power Supply Technologies for Public Transport Buses through the AHP and the Fuzzy DEMATEL Method

The selection of power supply technology for buses is a critical task given the increasing attention paid to environmental sustainability in the public transport sector. Indeed, the compliance of vehicle operational requirements with service characteristics is essential to provide users with an efficient offer. To this end, this study investigates the factors affecting such choices by performing two evaluation procedures, with the integration of different techniques and the engagement of an expert panel. The Analytic Hierarchy Process (AHP) method was used to identify the best power supply technology among a few solutions in both procedures, which differed in the number of analyzed criteria. A literature review suggested a wide set of criteria considered in the first assessment, which were then limited to the most influential criteria using the fuzzy DEcision-MAking Trial and Evaluation Laboratory (DEMATEL) method. Notably, the latter enabled the reduction in the number of the criteria owing to the revealing of cause–effect relationships among them. The methodology was applied to a case study in the city of Trieste, Italy, comparing rankings obtained from the two appraisal procedures, which showed the predominance of internal combustion engine buses over hybrid and electric buses in terms of operational and financial aspects, despite their environmental impact.

Analyzing the factors influencing the wind energy adoption in Bangladesh: A pathway to sustainability for emerging economies

The future of energy security has become a prominent concern for emerging economies due to the inevitable depletion of fossil fuels and the ongoing disruptions in their supply. The crippling effect of complete dependence on expensive fossil fuel imports is magnified by the ineffective policy response to the enduring energy crisis, impeding progress across various sectors and thwarting efforts to meet the demands of population growth and industrialization amid acute electricity shortages. Amidst the economic growth of a prominent emerging economy, Bangladesh, wind energy emerges as a transformative solution to effectively tackle the mounting challenges of electricity demand, environmental pollution, greenhouse gas emissions, and the depleting reserves of fossil fuels. Therefore, this study utilizes an integrated multi-criteria decision-making (MCDM) approach combining the inter-valued type 2 intuitionistic fuzzy (IVT2IF) theory with the decision-making trial and evaluation laboratory (DEMATEL) method aiming to identify, prioritize, and investigate the relationships among the factors that impact the sustainable adoption and growth of wind energy in an emerging economy like Bangladesh. Initially, the factors were derived from reviewing existing literature. After subsequent expert validation, sixteen factors were selected for analysis using the IVT2IF DEMATEL method. The findings of the study indicate that "Fossil fuel supply disruption," "Stable financial investment and resource mobilization," and "Geographical region" are the most significant factors influencing the adoption of wind energy for national grid support with prominence value 4.415, 4.406 and 4.339 respectively. Moreover, "Fossil fuel supply disruption" is also the most significant causal factor with a causal weight of 1.274, which is followed by "Stable financial investment and resource mobilization" and "Geographical region" with a causal weight of 1.029 and 0.794. The study's findings have the potential to aid decision-makers and policymakers in formulating long-term strategies and investment decisions to improve the sustainability of the national grid and achieve carbon neutrality.

Decision-theoretic rough set model and spatial analysis-based waste-to-energy incineration plant site selection: a case study in first-tier cities of China.

Selecting a sustainable waste-to-energy (WTE) incineration plant site is important for handling huge challenges created by on-going municipal solid waste. However, many studies with WTE incineration plant site problems fail to determine alternative evaluation criteria and cities beforehand, which may increase decision costs and evaluation risks. This paper proposes a novel methodology based on decision-theoretic rough set model and suitable analysis for selecting the optimal WTE incineration plant site. Firstly, from the features of cities, alternative evaluation criteria are determined by three-phase method. Considering different geographical features, a geographical index system is established. Secondly, subjective and objective criteria weights are determined by an improved DEMATEL (Decision Making Trial and Evaluation Laboratory) method and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method-based linear programming model under the hesitant fuzzy linguistic context, respectively. Subjective and objective criteria weights are combined to form the final criteria weights by building an optimization model. Thirdly, the decision-theoretic rough set model is utilized to select alternative WTE incineration plant sites. We utilize spatial analysis adopting Geographic Information System technology to rank all alternative cities to build facilities. Finally, a numerical case is performed to illustrate the feasibility of the proposed methodology. The sensitivity analysis with the parameter [Formula: see text] ranking from 0 to 1 is performed, the result confirms that the proposed methodology has better robustness. Compared with the multi-criteria decision-making methods, the effectiveness and superiority of the proposed methodology are demonstrated.

A New Model for Determining Factors Affecting Human Errors in Manual Assembly Processes Using Fuzzy Delphi and DEMATEL Methods

Human errors (HEs) are common problems in manual assembly processes, impacting product quality and resulting in additional costs. Based on expert judgments, this study aims to identify the most significant factors affecting HEs in manual assembly processes and explore the cause-and-effect relationships among those factors. In order to achieve this objective, a proposed model is constructed using two types of Multi-Criteria Decision-Making (MCDM) techniques. Firstly, using two rounds of the fuzzy Delphi method (FDM), twenty-seven factors with an influence score of 0.7 or higher were found to have a major impact on HEs during manual assembly processes, with at least a 75% consensus among experts. After that, the twenty-seven factors affecting HEs were given to experts in a third round to analyze the cause-and-effect relationships among those factors using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method. In MCDM techniques, symmetry refers to an important property that can be used to find relationships between variables. It is based on the principle that the relative importance or preference between two variables should remain the same regardless of their positions or roles. Therefore, symmetry is a factor that MCDM approaches take into account to ensure that the relationships between variables are accurately represented, leading to more reliable decision-making outcomes. The reliability and normality of the surveying data were examined using the SPSS 22.0 software program. The study results revealed that training level, poor workplace layout, a lack of necessary tools, and experience were the major factors affecting HEs as root causes. Moreover, a failure to address the error-causing problem, unintentional unsafe acts, fatigue, and poor error visual perception were found to be effect (dependent) factors. The findings of this study can help organizations make better-informed decisions on how to reduce worker errors and interest in the factors that contribute to assembly errors and provide a good basis for reaching the quality of final assembled parts.

Assessing ESG Factors and Policies of Green Finance Investment Decisions for Sustainable Development in China Using the Fuzzy AHP and Fuzzy DEMATEL

China has become more aware of the negative environmental impact caused by its economic expansion and fast-paced development. Therefore, the country mainly focuses on sustainable development and green finance. To evaluate the environmental, social, and governance (ESG) factors and policy options for green finance investment decisions in China, the fuzzy analytical hierarchy process (AHP) and fuzzy decision-making trial and evaluation laboratory (DEMATEL) techniques are employed. The fuzzy AHP method identifies and analyzes the most significant ESG factors and sub-sub-factors to comprehensively understand sustainable investment in China. Furthermore, this study uses the fuzzy DEMATEL method to prioritize the main policy options for advancing sustainable development and green finance investment decisions in China. The fuzzy AHP method shows that the environmental factor (ESG1) is the most significant factor for green finance investment decisions in China, followed by the governance (ESG3) and social factors (ESG2). The fuzzy DEMATEL method results revealed that supporting green finance innovation and development (P1) is the highest priority, followed by encouraging social responsibility and community engagement (P4) and developing and enforcing environmental regulations (P2). The study’s findings will significantly benefit investors and decision-makers who wish to promote sustainable development and make decisions regarding green financing. The study recommends that investors and policy makers concentrate their resources and efforts on the most crucial ESG factors and policies to build sustainability and resilience in the country.

The factors obstructing the blockchain adoption in supply chain finance: a hybrid fuzzy DELPHI-AHP-DEMATEL approach

PurposeSupply chain finance (SCF) is an advanced financing solution for medium and small organizations. However, due to its nascent stage, SCF is still struggling with its application in the supply chain. The blockchain application in SCF can bring lots of opportunities and smart techniques to deal with financing to organizations. However, some factors restrict the proper adoption of blockchain in SCF. Therefore, this study aims to identify and analyze the factors obstructing blockchain adoption in SCF.Design/methodology/approachThe present study applied a hybrid fuzzy DELPHI-AHP-DEMATEL to validate and analyze the factors. The fuzzy Delphi techniques were adopted to validate the identified factors. Thereafter, the analytic hierarchy process (AHP) has been used to prioritize the validated factors. Further, the decision-making trial and evaluation laboratory (DEMATEL) method has opted to classify the factors into cause-and-effect groups.FindingsThe result of the study revealed that lack of technological competence and confidentiality leaking are the most prioritized factors and act as the prime factors for the obstacles in the blockchain application in the SCF. The application of the DEMATEL method revealed that the highest causing factor is authenticity, and the highest effecting factor is high cost.Practical implicationsThe current study enhances the knowledge and information of managers and policymakers about the challenges associated with the blockchain application in SCF as well as provides better insight to deal with various factors obstructing blockchain adoption in SCF.Originality/valueThe current study is the first of its kind, where factors obstructing blockchain adoption in SCF are identified and validated with the help of experts and practitioners by incorporating the fuzzy Delphi method. Thereafter, the validated factors are prioritized by using fuzzy AHP and fuzzy DEMATEL techniques helps to identify the cause-and-effect group, which opens the door for future research work.