Data Asset Quality Evaluation Model Considering the Requirements of Circulation Scenarios

PurposeIncreased demand for new batteries and strict government protocols have stressed the battery industries to collect and recycle used batteries for economic and environmental benefits. This scenario has forced the battery industries to collect used batteries and establish the formal battery recycling plant (BRP) for effective recycling. The starting of BRP includes several strategic decisions, one of the most critical decisions encountered is to find the best sustainable location for BRP. Hence, this paper aims to address the complexity of the issues faced during the BRP location selection through a hybrid framework.Design/methodology/approachIn this study, the criteria are identified under socio-cultural, technical, environmental, economic and policy and legal (STEEP) dimensions through literature review and experts' opinions. Then, the hybrid methodology integrating fuzzy decision making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and technique for order preference by similarity to an ideal solution (TOPSIS) has been proposed to find the inter-relationship between criteria, the weights of criteria and the best alternative.FindingsThe identified five main criteria and 26 sub-criteria have been analyzed through fuzzy DEMATEL, and found that the policy and legal criteria have more inter-relationship with other criteria. Then from BWM results, it is found that the support from government bodies has attained the maximum weightage. Finally, the second alternative has been identified as a more suitable location for establishing BRP using TOPSIS. Further, it is found from the results that the support from government bodies, the impact of emissions, availability of basic facilities and community health are the essential criteria under STEEP dimensions for establishing BRP.Originality/valueIn addition to the various existing sustainable criteria, this study has also considered a set of policy and legal criteria for the evaluation of locations for BRP. Further, the hybrid MCDM method has been proposed in this study for selecting the best alternative. Thus, this study has yielded more insights to the decision-makers in choosing a sustainable location for BRP.

Rooftop distributed photovoltaic projects have been quickly proposed in China because of policy promotion. Before, the rooftops of the shopping mall had not been occupied, and it was urged to have a decision-making framework to select suitable shopping mall photovoltaic plans. However, a traditional multi-criteria decision-making (MCDM) method failed to solve this issue at the same time, due to the following three defects: the interactions problems between the criteria, the loss of evaluation information in the conversion process, and the compensation problems between diverse criteria. In this paper, an integrated MCDM framework was proposed to address these problems. First of all, the compositive evaluation index was constructed, and the application of decision-making trial and evaluation laboratory (DEMATEL) method helped analyze the internal influence and connection behind each criterion. Then, the interval-valued neutrosophic set was utilized to express the imperfect knowledge of experts group and avoid the information loss. Next, an extended elimination et choice translation reality (ELECTRE) III method was applied, and it succeed in avoiding the compensation problem and obtaining the scientific result. The integrated method used maintained symmetry in the solar photovoltaic (PV) investment. Last but not least, a comparative analysis using Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method and VIKOR method was carried out, and alternative plan X1 ranks first at the same. The outcome certified the correctness and rationality of the results obtained in this study.

Interval neutrosophic fuzzy decision making is an important part of decision making under uncertainty, which is based on preference order. In this study, a new multi-valued interval neutrosophic fuzzy multiple attribute decision making method has been developed by integrating the DEMATEL (decision making trial and evaluation laboratory) method and the TOPSIS (the technique for order preference by similarity to an ideal solution) method. Evaluation values are given in the form of multi-valued interval neutrosophic fuzzy values. By using DEMATEL, dependencies among attributes can be modeled, and attribute weights are determined. The normalized Euclidean distance and the normalized Hamming distance between multi-valued interval neutrosophic fuzzy values are defined. Alternatives are ranked by using the TOPSIS method based on the distance measures. The truck selection problem in the logistics industry is presented to illustrate the feasibility and practical advantages of the proposed method. Some comparisons of the new method with other methods are also made.

Failure mode and effect analysis (FMEA) is a prospective method for medical human reliability analysis that evaluates the risks of potential medical failure modes. To better address the complexities of medical environments characterized by uncertainty and limited information, this study employs an interval-valued intuitionistic fuzzy set (IVIFS) to represent and analyze such environments within the FMEA framework. To tackle the challenges posed by the subjective ambiguity and hesitation in expert decision-making during the risk assessment of medical failure modes, this paper proposes an integrated approach based on the decision-making trial and evaluation laboratory (DEMATEL) methodology and the technique for order preference by similarity to an ideal solution (TOPSIS) within an interval-valued intuitionistic fuzzy framework. To overcome the limitations of traditional FMEA, which neglects expert weight and risk factor weight, this paper introduces an enhanced methodology. First, a dual-goal programming model is developed, incorporating both individual uncertainty and group consensus among experts to determine expert weight. Second, a comprehensive weighting method that combines expert-driven weighting with information-based weighting derived from fuzzy entropy calculations applied to expert data is applied to calculate the weights of risk factors. The proposed FMEA model presented in this study provides a systematic method to identify and evaluate high-risk failure modes in medical systems proactively. By doing so, it seeks to minimize the occurrence of human medical errors and adverse events while enhancing the safety and reliability of medical service delivery processes.

Using a novel conjunctive MCDM approach based on DEMATEL, fuzzy ANP, and TOPSIS as an innovation support system for Taiwanese higher education

As one of the purposes to conduct sustainability assessment of energy systems, providing information on improving system sustainability for decision-makers is crucial. However, the existing literature fails to provide comprehensive information to improve the sustainability from both short-term and long-term perspectives while considering the uncertainties existing in decision-making process. In order to narrow the research gap, the methodological framework for sustainability assessment of energy systems was established by integrating an improved hierarchical fuzzy Best–Worst Method (BWM), fuzzy Decision-making and Trial Evaluation Laboratory (DEMATEL) method and fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. In which, the improved hierarchical fuzzy BWM was used to obtain the weights of the criteria, and further to provide the short-term information of improving the sustainability. While the cause-effect relationships among criteria were captured by using the fuzzy DEMATEL method to provide information for the long-term improvement of the system sustainability. The priorities of energy systems were finally acquired by using the fuzzy TOPSIS method. And the validity of the sustainability assessment framework of energy systems was verified using a case study of five combined cooling, heating, and power systems.

The growth of Internet of Things (IoT) systems is driven by their potential to improve efficiency, enhance decision-making, and create new business opportunities across various domains. In this paper, the main selection problems in IoT-type systems, criteria used in multi-criteria evaluation, and multi-criteria methods used for solving IoT selection problems are identified. Then, a Hybrid Group Multi-Criteria Approach for solving selection problems in IoT-type systems is proposed. The approach contains the Best Worst Method (BWM) weighting method, multi-criteria Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and Complex Proportional Assessment Method (COPRAS), and a method that combines the solutions obtained using the four considered multi-criteria methods to obtain a single solution. The SAW, TOPSIS, VIKOR, and COPRAS methods were analyzed in relation to their advantages, disadvantages, inputs, outputs, measurement scale, type of normalization, aggregation method, parameters, complexity of implementation, and interactivity. An application of the Hybrid Group Multi-Criteria Approach for IoT platform selection and a comparison between the SAW, TOPSIS, VIKOR, and COPRAS solutions and the solution of the proposed approach is realized. A Spearman correlation analysis is presented.

A spatial model for coastal flood susceptibility assessment using the 2D-SPR method with complex network theory: A case study of a reclamation island in Zhoushan, China

<p>Interval neutrosophic fuzzy decision making is an important part of decision making under uncertainty, which is based on preference order. In this study, a new multi-valued interval neutrosophic fuzzy multiple attribute decision making method has been developed by integrating the DEMATEL (decision making trial and evaluation laboratory) method and the TOPSIS (the technique for order preference by similarity to an ideal solution) method.</p>

In most of the machining processes, the complexity arises in the selection of the right process parameters, which influence the machining process and output responses such as machinability and surface roughness. In such situations, it is important to estimate the inter-relationships among the output responses. One such method, Decision-Making Trial and Evaluation Laboratory (DEMATEL) is applied to study the inter-relationships of the output responses. Estimation of proper weights is also crucial where the output responses are conflicting in nature. In the current study, DEMATEL technique is used for estimating the inter-relationships for output responses in machining of EN 24 alloy under dry conditions. CRiteria Importance Through Inter-criteria Correlation (CRITIC) method is used to estimate the weights and finally the optimal selection of machining parameters is carried out using Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. The model developed guides the decision maker in selection of precise weights, estimation of the inter relationships among the responses and selection of optimal process parameters.

PurposeIn this study, an integrated decision-making model consisting of decision-making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and a modified version of evaluation based on distance from average solution (EDAS) methods is proposed for supplier selection problem in a public procurement system considering sustainable development goals.Design/methodology/approachDEMATEL and BWM methods are used to determine weights of the criteria that are defined for the supplier selection problem. Weight aggregation method is applied to combine the weights obtained from these two methods. A modified version of EDAS method is then used in order to rank the alternative suppliers.FindingsThe proposed decision-making model is investigated for a supplier selection problem for a hospital in Spain. The validity of the results is checked using comparison with other decision-making methods and several performance analysis tests.Practical implicationsThe proposed multi-criteria decision-making (MCDM) model contributes to the healthcare supply chain management (SCM) and aims to lead the policy makers in selecting the best supplier.Originality/valueThere is no such study that combines DEMATEL and BWM together for weight generation. The application of the modified EDAS method is also new. In real time situations, the decision experts may confront to the difficulty of using BWM while identifying the best and the worst criteria choices. The idea of using DEMATEL is to aid the experts to make them enable in distinguishing between the best/worst criteria and handle BWM easily.

With the dawn of economic globalization and the knowledge economy, intellectual capital has become the most important factor to determine economic growth. However, due to resource endowment, location conditions, policy differences, and other factors, provinces in China show sizeable differences in regional intellectual capital (RIC), which affects the coordinated development of the regional economy. Evaluating RIC is a typical multiple-criteria decision-making (MCDM) problem. Therefore, this study employs a set of MCDM techniques to solve this problem. First, the Delphi method is used to determine the formal decision structure based on a systematic literature review. A novel hybrid method, namely, the Grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP), i.e., GDANP, is employed to obtain the relative weight of each criterion. Finally, based on the data of 31 provinces in China, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to evaluate the RIC. According to the questionnaires filled out by an expert panel, we establish an evaluation index of RIC with 21 criteria. Based on the results of empirical study, the level of RIC in different regions in China is quite different. Furthermore, the RIC ranking is largely consistent with the provincial gross domestic product (GDP) ranking, in line with the current status of development in the regions. Indeed, this paper shows that the proposed hybrid method can effectively measure the level of RIC.

The complexity of assessment is a significant problem in designing renewable energy source (RES) products, especially when one wants to take into account their various aspects, e.g., technical, environmental, or social. Hence, the aim of the research is to develop a model supporting the decision-making process of RES product development based on meeting the criteria of quality, environmental impact, and social responsibility (QES). The model was developed in four main stages, implementing multi-criteria decision support methods such as DEMATEL (decision-making trial and evaluation laboratory) and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), as well as criteria for social responsibility and environmental impact from the ISO 26000 standard. The model was tested and illustrated using the example of photovoltaic panels (PVs): (i) five prototypes were developed, (ii) 30 PV criteria were identified from the qualitative, environmental, and social groups, (iii) the criteria were reduced to 13 key (strongly intercorrelated) criteria according to DEMATEL, (iv) the PV prototypes were assessed taking into account the importance and fulfilment of their key criteria according to TOPSIS, and (v) a PV ranking was created, where the fifth prototype turned out to be the most advantageous (QES = 0.79). The main advantage of the model is its simple form and transparency of application through a systematic analysis and evaluation of many different criteria, after which a ranking of design solutions is obtained. QES ensures precise decision-making in terms of sustainability of new or already available products on the market, also those belonging to RES. Therefore, QES will find application in various companies, especially those looking for low-cost decision-making support techniques at early stages of product development (design and conceptualization).

The selection of marketing strategy is very important for the sustainability of small and medium enterprises (SMEs). Choosing the best marketing strategy is a process involving problem of multiple decision-making criteria, which considers many attributes in various phases of a strategy formulation method. This paper proposes a model of selecting marketing strategy for Batik Madura SMEs. The model selected five criteria including customer networking, innovation capabilities, managerial competency, human capital, and company reputation based on literature reviews and focus group decision-making discussion. Analytic network process (ANP), decision-making trial and evaluation laboratory (DEMATEL) and technique for order preference by similarity to an ideal solution (TOPSIS) methods were applied to obtain an impact relation map from each criteria and to determine the priority of marketing strategy. The implementation of the model shows that Batik Madura SMEs should maintain their focus on segmentation marketing as the most appropriate marketing strategy.

In Industry 4.0 environment, supply chains have become prone to various risks due to rapid globalization and process digitalization. The uncertainties and unplanned and unnatural events that are internal to supply chain networks and external to the environment of a firm pertaining to global supply chains are regarded as supply chain risks. The objective of this study is to identify and analyze the various emerging supply chain risks for strategy formulation in Industry 4.0 environment. Based on a systematic literature review and experts’ opinion, different supply chain risks in the present business environment have been analyzed. Major identified risks are operational and manufacturing process risk, behavioural risk, demand risk, governmental and organisational risk, system risk, financial risk, product recovery risk, social and environmental risk, supply risk, disruption risk, cyber security, and safety risk. For developing risk mitigation strategies, risk prioritization is very important. Sufficient research has not been done on ranking and categorization of these risks in the Industry 4.0 environment. Therefore, this study has tried to rank these emerging supply chain risks by the Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) approach. These risks are further categorized as cause and effect using a Decision Making Trial and Evaluation Laboratory (DEMATEL). This classification of risks will facilitate top management of the organization in formulating strategies for risk mitigations in the Industry 4.0 environment. The findings of the study imply that supply chain managers should focus on disruption risk; cyber security and safety risk in the current Industry 4.0 environment. As supply chain risk management is an emerging research area in Industry 4.0 environment, the findings of this study will be very useful for industry professionals and researchers for further studies.