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The main objective of this paper is to justify the implementation of blockchain (BC) over the traditional method deployed in the supply chain (SC) after using the fuzzy–analytic network process (fuzzy-ANP) application. Over the past two decades, the overall product cost is affected by the SC at a global level. Organizations are working on their existing SC for improving their performance. BC technology is a newly emerging technology and magnetizes the attention of researchers and industrialists. This technology is still at the initial stage, and only little investigation is available in the literature and it has not been much investigated by researchers.

Literature and expert opinion interpretation in BC characteristics are further analyzed and modeled using fuzzy–interpretive structural modeling (fuzzy-ISM), fuzzy-MICMAC and fuzzy-ANP. The combined approach of both fuzzy-ISM and fuzzy-MICMAC is applied to identify the common drivers to integrate the BC technology in the light of efficient supply chain management (SCM).

Comparative analysis between traditional and BC-based supply chain (BCSC) using fuzzy-ANP is carried out, considering the common driving characteristics. The proposed integrated (combined) approach of fuzzy-ISM, fuzzy-MICMAC and Fuzzy-ANP found that integration of BC with SCM is better prioritized than traditional supply chain management (TSCM). The findings in the article endorse that the TSCM can be made efficient by integrating the BC technology considering five most driving characteristics, namely, data safety and decentralization, accessibility, documentation, data management and quality.

The current proposed research work identifies 12 characteristics after studying numerous literature reviews and having a discussion with SC experts with knowledge of BC. The integrated approach of fuzzy-ISM and fuzzy-MICMAC is implemented here. After that, fuzzy-ANP is used to give ranking among BCSCM and TSCM. The study carried out in this article motivates industries to implement BC in their SC system. It will reduce the transaction cost, documentation work, save time and eliminate human error at the national and international levels. The common characteristics identified in this proposed work would help in managerial decisions for the adoption of BC to ensure that the system becomes more transparent, easily traceable and finally improve the performance.

The purpose of this paper is to evaluate the impact of lean criteria on leanness as well as prioritize them, taking the relationships between dimensions into consideration for manufacturing enterprises.

This study considers leanness over quality, cost, delivery and innovation (QCDI) performance dimensions. Twenty eight criteria related with these dimensions were determined that are focused on manufacturing organizations and then fuzzy analytic network process (ANP) approach was used to determine the influence value of each criterion on leanness.

The existing literature shows a lack of studies on systematically measuring the impact of lean criteria on leanness. To fill the gap, this paper presents a fuzzy ANP approach. Firstly interactions between the performance dimensions were configured. Then, according to the relationship, weights were obtained while taking the network structure that allows dynamic multidirectional relationships for interdependencies among performance dimensions into consideration. This provides a more accurate approach for determining the impact value on leanness performance in real-life decision-making environments.

The limitation of this study is that only manufacturing enterprises have been considered. Different criteria may need to be developed for service organizations.

This study gives a real insight to lean practitioners in the manufacturing system. Due to the fact it is difficult to achieve all the criteria at the same time for a company, this study is significant for manufacturers, indicating which criteria should primarily be focused on in order to achieve leanness.

Applying fuzzy ANP on interrelated QCDI performance dimensions to evaluate the impact of lean criteria on leanness is the novelty of this study in the related literature. The fuzzy ANP approach is thought to be a more suitable approach to obtain more realistic and accurate results with the power to cope with ambiguity. This study provides a systematic measurement of the influence of lean criteria, also considering interdependencies between performance dimensions. Another contribution of this study is adding innovation to the performance dimensions that are commonly known as quality, cost and delivery to assess leanness in a comprehensive manner.

The aims of this paper is to establish an appropriate physical-change-based renewal (PCBR) projects selection mechanism capable of selecting the combination of the PCBR projects that can make up an integrated urban renewal program in high-density cities.

The research design follows a sequential integrated methodology that combines the calculation algorithms of Fuzzy Analytic Network Process (Fuzzy-ANP) with Zero-One Goal Programming (ZOGP) to support decisions for the selection of PCBR projects. In the first phase, general criteria for assessing the sustainability performance of PCBR projects were collected from relevant literature. In the second phase, the Fuzzy-ANP was used to identify the priority weights of the candidate projects through clarifying the interdependent degree between the criteria and candidate projects. Finally, ZOGP method was selected as a predetermined number of PCBR projects among candidate projects.

The feasibility and effectiveness of this hybrid approach is then verified in a case study of Yuzhong District, Chongqing in China. The results of this study indicate that the integrated method is capable of directing the decision maker toward the best compromising solution of PCBR program that can achieve the maximization of sustainable benefits and allocate limited resources most efficiently.

The novelty of this paper consists in combining the algorithms of the Fuzzy-ANP method with those of the ZOGP model that serves as an effective analysis tool to address practical decision problems. This is the first hybrid algorithms to make PCBR projects selection decision that reach the maximization of the sustainable benefits, both in economic and socio-environmental terms.

The paper aims to build a customized hybrid multi-criteria model to identify the top three utilities of drones at both personal and community levels for two use cases: firefighting in high-rise buildings and logistic support.

A hybrid multi-criterion model that integrates fuzzy analytical hierarchy process (AHP), Best Worst, fuzzy analytical network process (ANP), fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) is used to compute the criteria weights. The weights are validated by a novel ensemble ranking technique further whetted by experts at the community and personal levels to two use cases.

Drones' fire handling and disaster recovery utilities are the most important to fight fire in high-rise buildings at both personal and community levels. Similarly, drones' urban planning, municipal works and infrastructure inspection utilities are the most important for providing logistics support at personal and community levels.

The paper presents a novel multi-criteria approach, i.e. ensemble ranking, by combining the criteria ranking of individual methods – fuzzy AHP, Best-Worst, fuzzy ANP and fuzzy DEMATEL – in the ratio of optimal weights to each technique to generate the consolidated ranking. Domain experts also validate this ranking for robustness. This paper demonstrates a viable methodology to quantify the utilities of drones and their capabilities. The proposed model can be recalibrated for different use case scenarios of drones.

The purpose of this paper is to develop a spatial intelligent decision support system (SIDSS) for increasing productivity in the rubber agroindustry by green productivity (GP) approach. The SIDSS was used to measure the productivity of rubber plantation and rubber agroindustry by GP approach, and select the best strategies for increasing the productivity of rubber agroindustry.

This system was developed by combining spatial analysis, GP, and fuzzy analytic network process (ANP) with the model-based management system, which is able to provide comprehensive and meaningful decision alternatives for the development of natural rubber agroindustry. Rubber plantation productivity measurement model was used to find the productivity level of rubber plantation with fuzzy logic, and also to provide information and decision alternatives to all stakeholders regarding spatial condition of rubber agroindustry, production process flow, and analysis of the seven green wastes at each production process flow using the geographic information system. GP measurement model was used to determine the productivity performance of the rubber agroindustry with the green productivity index (GPI). The best strategy for increasing the productivity was determined with fuzzy ANP.

Rubber plantation measurement model showed that the average of plantation productivity was 6.25 kg/ha/day. GP measurement model showed that the GPI value of ribbed smoked sheet (RSS) was 0.730, whereas of crumb rubber (CR) was 0.126. The best strategy for increasing the productivity of rubber agroindustry was raw material characteristics control. Based on the best strategy, the GPI value of RSS was 1.340, whereas of CR was 0.228.

This decision support system is still limited as it is based on static data; it needs further development so that it can be more dynamically based on developments in the rubber agroindustry related levels of productivity and environmental impact. In addition, details regarding the decision to increase the productivity of the rubber section by benchmarking efforts should be studied further, both among plantation as well as among countries such as Thailand so that the productivity of rubber plantation and agroindustry can be integrated.

This research can help the planters to select superior clones for rubber trees, to improve the technique of tapping latex, and to use a better coagulant. The good quality and quantity of raw material is a key factor in increasing the productivity of rubber agroindustry; if the quality of latex is good then the resulting product will also have a good quality and production cost can be reduced. In addition, the application of GP through the calculation of GPI value using improvement scenarios can be used as a reference and comparison for evaluating the performance of rubber agroindustry to reduce the waste generated by the activities of rubber processing plant.

Reduction of waste generated by production activities can improve the quality of life of the workforce and the environment. The calculation of GPI value can also be used as a basis to use raw materials, water, and electricity more efficiently.

This system was developed by combining spatial analysis, GP, and fuzzy ANP with the model-based management system, which is able to provide comprehensive and meaningful decision alternatives for the development of natural rubber agroindustry.

The purpose of this paper is to overcome the drawbacks of analytic hierarchy process in solving complex decision-making problems, especially for the evaluation of enterprise technology innovation ability (ETIA). Because interval type-2 fuzzy sets (IT2 FSs) can handle uncertainty linguistic variables in a more flexible and precise way than type-1 fuzzy sets with their second fuzzy membership functions, a fuzzy ANP method with IT2 FSs is proposed to evaluate the ETIA.

The criteria of evaluation on ETIA are identified and an evaluation model for ETIA is constructed on the basis of the application analysis of ETIA and theoretical design of ANP. In addition, two different ranking methods of IT2 FSs are applied in processing the relationships between influence factors of ETIA.

By using the proposed interval type-2 fuzzy ANP (IT2 FANP) method, the efficiencies of the whole evaluation of ETIA can be measured and the important factors in the ETIA can also be determined. Compared with the type-1 FANP through the ranking results, the proposed IT2 FANP is more reasonable and robust for the evaluation of ETIA.

The proposed IT2 FANP method is applied on the evaluation of ETIA. With respect to the application, the proposed method can be used to evaluate many more complex problems that contain feedback and circular relationships.

The proposed IT2 FANP approach can solve the complexities and uncertainties at the same time. Considering the subjective initiative of decision-makers and the feedback between influence factors, the proposed method is more efficient than the existing type-1 approaches in the literature.

This paper aims to evaluate the market concentration and competition in the European Banking Sector using an integrated multi-criteria decision-making approach under the fuzzy environment.

The hybrid model combining fuzzy decision-making trial and evaluation laboratory (DEMATEL), fuzzy analytic network process (ANP) and fuzzy VIKOR methods is applied to measure the market competition and concentration in the European Banking Sector. For this purpose, two academicians and one expert from banking sector with at least five-year experiences are selected to evaluate the dimensions, criteria and alternatives. The academicians are also appointed to define the decision-making problem and determine the dimensions and the criteria on the basis of related literature. The implementation of the model has been constructed in three main phases. The first phase consists of the fuzzy DEMATEL technique for understanding the impact-relation map among the dimensions. The second phase includes the fuzzy ANP method for measuring the relative importance of the criteria. The last phase comprises the fuzzy VIKOR approach to rank the alternatives with the values of the Herfindahl–Hirschman Index (HHI).

Turkey, France, England and Germany are placed in the competitive market structure of the European Banking Sector respectively. Additionally, the comparative results of the study confirm the market shares and the competitive policies of the European and Turkish Banking Sector.

The novelty of the paper is to construct a hybrid multi-criteria decision-making model with the proposed HHI scales under the fuzzy environment and defined competition dimensions and criteria based on the literature for the European Banking Industry.

Delivering vaccines to the children who need them requires a supply chain that is efficient and effective. In most of the developing countries, however, the unknown and unresolved supply chain issues are causing inefficiencies in distributing vaccines. There is, therefore, a great need in such countries to recognize the issues that cause delays in vaccine delivery. With this purpose, the present study aims to identify and analyze the key issues in the supply chain of basic vaccines required to immunize children in developing countries.

Based on a field survey of three states of India, in-depth review of relevant literature and experts’ opinions, 25 key issues were recognized as factors of the vaccine supply chain (VSC) and categorized into five main domains. Using integrated interpretive structural modeling and fuzzy analytic network process approaches, the issues have been prioritized to determine their relative importance in the VSC. In addition, a sensitivity analysis has been performed to investigate the priority stability of the issues.

The results of the analysis show that among the five domains of VSC issues, the economic domain with a weight of 0.4262 is the most important domain, followed by the management (0.2672), operational (0.2222), environmental (0.0532) and social (0.0312).

This study focuses on the prioritization of VSC issues; therefore, the results of the present study can provide direction to the decision-makers of immunization programs of developing countries in driving their efforts and resources on eliminating the most important obstacles to design successful vaccination programs.

To the authors’ knowledge, this paper is first to provide a direction to the decision-makers in identifying and managing important issues through the use of an analytical approach.

The purpose of this study is to evaluate maintenance strategies based on fuzzy decision-making trial evaluation and laboratory (DEMATEL) and fuzzy analytic network process (ANP) in the petrochemical industry.

This study proposes a hybrid-structured multi-criteria decision-making (MCDM) method based on fuzzy Delphi, fuzzy DEMATEL and fuzzy ANP as a structured methodology to assist decision makers in strategic maintenance. The fuzzy Delphi method (FDM) is applied to refine the effective criteria, fuzzy DEMATEL is applied for defining the direction and relationships between criteria and Fuzzy ANP is used for the selection of optimized maintenance strategy.

The results identify “strategic management complexity” as the top criterion. The predictive maintenance (PdM) with the highest priority is the best strategy. It is followed by reliability-centered (RCM), condition-based (CBM), total productive (TPM), predictive (PM) and corrective maintenance (CM).

Today, companies act in an atmosphere that is known with the features of uncertainty. In this atmosphere, only those companies can survive that have a strategy based on presenting the quality services and products to their customers. Similarly, maintenance as a system plays a vital role in availability and the quality of products, which creates value for customers. The selection of maintenance strategy is a kind of MCDM problem, which includes consideration of different factors. This article considers a broad category of alternates, including CM, PM, TPM, CBM, RCM and PdM.

This paper aims to provide a quantitative basis to analytically determine the ranking of the brand personality of Adidas, Asics, Nike, Puma and Saucony brands among Iranian customers via a conventional multi-criteria decision-making (MCDM) method.

Data for determining the importance of evaluation criteria and ranking of brands are gathered by means of distributing questionnaires among a group of Iranian customers of sport shoes, as well as some industrial experts. The fuzzy analytic network process (FANP) was used to rank the brands with regard to dependencies between criteria and alternatives.

The results indicate that FANP is a capable method which provides invaluable insights for strategic marketing decisions in the sport product industry. Results show Adidas has the best performance in the sports shoe market compared to the other four brands. In this study, it was found that expertise sophistication was the most important criterion among Aaker’s five main criteria.

The value of this paper is applying FANP decision-making method for ranking sport shoe brands. This method has not been commonly used in the area of marketing, hence it is added to the pool of techniques used in ranking brands. In addition, evaluation and ranking of brands can be very useful for both academic research and practice. Researchers can benchmark the competences of each brand through evaluating them, and industrialists can extract the competitive advantages of the selected brands.