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The main objective of this study is to compare the service quality of two retail chains of hypermarkets, namely, Big Bazaar and Spencer's, using the trapezoidal fuzzy approach.

Customers from Big Bazaar and Spencer's of Andhra Pradesh, India, have been surveyed through a well-designed questionnaire. The study attempts to compare the service quality of two major retail giants (Spencer's and Big Bazaar) in Andhra Pradesh by using the trapezoidal fuzzy approach to prioritize the attributes of service quality of retail outlets.

The result of the study indicates that the expectations of Big Bazar customers are higher as compared to Spencer's. Further, the study reveals – that Spencer's need to improve in the dimension of tangibility while Big Bazar needs to focus more on responsiveness.

As the data taken for the study are primary in nature, chances of bias may arise on the part of respondents, which may affect the validity of results. Further, the study is confined to two retail stores in Andhra Pradesh, India only, which may not reflect the broader picture.

Retailers may provide more importance to two major service quality dimensions, i.e. tangibility and responsiveness while preparing for their service and marketing strategies.

As the study relates to the comparative analysis of service quality of Big Bazar and Spencer's, the findings will be of additional value to these specific retailers. Therefore, it is expected that this study will fill the gap in the literature by prioritizing the expectations and perceptions of customers of Big Bazar and Spencer's.

A digital supply chain (DSC) positively enhances circular economy (CE) practices. However, what factors and conditions lead to the implementation of DSC for transitioning toward CE is not yet clear. Therefore, this study aims at identifying and subsequently analyzing the antecedents of DSC for CE.

The study identifies major antecedents of DSC for CE to achieve sustainability objectives through literature review and expert opinions. In this study, 19 potential antecedents of DSCs for CE are established from the literature and suggestions from industry professionals. A trapezoidal fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is applied quantitatively to investigate the antecedents identified.

Conducted in the context of Indian automobile manufacturing industry, the findings of the study reflect that advanced information sharing arrangement, effective government policies for DSC and CE implementation and digitalizing the supply chains are the top three potential antecedents of DSC for a CE.

In the existing literature, few studies are specific to investigating the DSC and CE paradigm. The present study will help organizations develop a practical and integrated strategic approach that will foster DSC through improved knowledge of CE.

Creating green ports, while observing international and international standards and maritime conventions and regulations and moving toward smart ports, can increase the speed of goods transfer, enable the tracking of ships and goods, increase the transparency of statistics, increase the quality and capacity of ports and reduce costs. Hence, the purpose of this study the development and evaluation of ports play a key role in their commercial success. Development policies can be formulated for these ports by properly evaluating their performance indicators. On the other hand, traditional methods of performance evaluation cannot provide a good multidimensional evaluation of the status of ports.

More than 90% of the world’s heavy transit today is carried out by the sea. With this volume of freight, transit accidents are inevitable for ships passing through oceans, seas, waterways, rivers, ports and mooring at docks. Besides, gases from ships’ fuels at sea, especially in ports, oil spills due to maritime incidents, the negligence of the ship’s crew, the use of port equipment, dirty fuel of diesel power substations, etc., have increased greenhouse gases, polluted the environment and endangered human lives.

A new approach has been introduced in the field of port performance evaluation based on the components of greenness and intelligence. This approach performs evaluations in two stages and a network. In this study, the performance of 11 Iranian ports was evaluated based on the network data envelopment analysis approach in 2 stages of greenness and intelligence during 4 years. The results indicated that only 5% of the ports meet the standards of intelligence and greenness.

On the other hand, as shown in the above studies, the issue of green ports is directly related to the development of animal and plant ecosystems in the seas and the environment around ports. The presence of pollution in the ports has caused the animal and plant habitats around the ports to face a complete pollution crisis or to be completely destroyed. Therefore, the development of green port concepts in third world countries will help prevent environmental pollution of the seas. Therefore, it is necessary for ports to review their strategic maritime transport model and use the development of green port indicators in their implementation processes. Therefore, the strategic development of green ports is created to create and benefit from the components of intelligence, and as mentioned in previous research, intelligence and greenness are in line and the lack of development of one of the concepts causes defects in others. According to reports provided in Iran’s maritime transport systems, most accidents have led to environmental disasters during the absence of intelligent equipment. The use of smart technologies prevents all environmental damage and the development of port services. On the other hand, in evaluating the published articles in the field of development of green and smart ports, so far, the components of intelligence and greenness have not been evaluated and analyzed in a practical and operational way in ports and only the influencing the development of agents on each other has been done (Chen, 2019). Therefore, evaluating the efficiency of ports based on green components and intelligence causes ports to fundamentally review their executive infrastructure and take an active part in the global green development plan.

Production of waste has been increased exponentially due to world industrialization and urban and machine life expansion. On the other hand, the outbreak of the COVID-19 coronavirus quickly became a global crisis. This crisis has added a large amount of waste to urban waste. The purpose of this study is to create cooperation between municipal waste collector contractors.

Thus, a mathematical model is proposed under uncertain conditions, which includes the volume of municipal waste and infectious waste including personal protective equipment and used equipment for patients. To reduce total costs, the results are evaluated with four cooperative game theory methods such as Shapley value, t value, core center and least core. Ultimately, the saved cost by cooperation in each coalition is allocated fairly among the contractors. Finally, a comparison was made between the solution methods based on the value of the objective function and the solution time.

The results indicate that the proposed cooperative method increases cost savings and reduces the fine of residual waste. Therefore, it can be mentioned that this kind of cooperation would finally result in more incentives for contractors to form larger coalitions. Genetic algorithms were used to solve the large-scale model.

The proposed model boosts the current understanding of waste management in the COVID-19 pandemic. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

The purpose of this paper is to develop a multi-attribute group decision-making (MAGDM) method under the q-rung orthopair trapezoidal fuzzy environment, which calculates the interaction between the criteria depending on the proposed q-rung orthopair trapezoidal fuzzy aggregation Choquet integral (q-ROTrFACI) and employ TODIM (an acronym in Portuguese of Interactive and Multi-criteria Decision Making) to consider the risk psychology of decision-makers, to determine the optimal ranking of alternatives.

In MAGDM, q-rung orthopair trapezoidal fuzzy numbers (q-ROTrFNs) are efficient to indicate the quantitative vagueness of decision-makers. The q-ROTrFACI operator is defined and some properties are proved. Then, a novel similarity measure is developed by fusing the area and coordinates of the q-rung orthopair trapezoidal fuzzy function. Based on the above, a Choquet integral-based TODIM (CI-TODIM) method to consider the risk psychology of decision-makers is proposed and two cases are provided to prove superiority of the method.

The paper investigates q-ROTrFACI operator to productively solve problems with interdependent criteria. Then, an approach is proposed to determine the center point of q--ROTrFNs and a q-rung orthopair trapezoidal fuzzy similarity is constructed. Furthermore, CI-TODIM method is devised based on the proposed q-ROTrFACI operator and similarity in q-rung orthopair trapezoidal fuzzy context. The illustration example of business models' solutions and hypertension health management are given to demonstrate the effectiveness and superiority of proposed method.

The paper develops a novel CI-TODIM method that effectively solves the MAGDM problems under the premise of fully considering the priority of criteria and the risk preference of decision-makers, which provides guiding advantages for practical decision-making and enriches the application of decision-making theory.

As the functions of environmental regulations cannot be quantified while assessing their environmental efficiency, there has been no comprehensive evaluation of environmental efficiency. The purpose of this paper is to evaluate environmental regulations based on triangular and trapezoidal fuzzy numbers.

This paper uses L-R fuzzy numbers to transform the evaluation language into triangular fuzzy numbers, and adopts an α-level flexible slacks-based measurement model to evaluate the performance of these regulations. Trapezoidal fuzzy numbers are combined with a data envelopment analysis model, and an α-slack-based measurement (SBM) model is used to evaluate the environmental efficiency. The α-SBM model is confirmed to be stable and sustainable.

Relevant index data from 16,375 enterprises were collected to test the proposed model, and models corresponding to triangular fuzzy numbers and trapezoidal fuzzy numbers were used to evaluate their environmental efficiency. Comparative results showed that the proposed model is feasible and stable.

The main contributions of this study are twofold. First, this paper provides a valuable evaluation method for environmental regulation. Second, our research improves the practical performance of trapezoidal fuzzy data envelopment analysis and enhances its feasibility and stability.

Robot appraisement under various dimensions and directions is a crucial issue in real-time manufacturing scenario. Logistic robots are programable-independent movable devices capable of transporting stuffs in a logistic cycle. The purpose of this paper is to opt for the most economical robot under chains of criteria, which is always considered as a sizzling issue in an industrial domain.

The authors proposed a cluster approach, i.e. ratio analysis, reference point analysis and full mutification form, embedded type-2 fuzzy sets with weighted geometric aggregation operator (WGAO) to tackle the elected problem of industrial robot. The motive to use WGAO coupled with type-2 fuzzy sets is to effectively undertake the uncertainty associated with comprehensive information of professionals against defined dimensions. Furthermore, the cluster approach is used to carry out the comparative analysis for evaluating robust scores against candidate robot’s manufacturing firms, considering 59 crucial beneficial and non-beneficial dimensions. A case research study is carried out to demonstrate the validity of the proposed approach.

The most challenging task in real-time manufacturing scenario is robot selection for a particular industrial application. This problem has become more complex in recent years because of advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. In the past decade, robots have been selected in accordance with cost criteria excluding other beneficial criteria, which results in declined product quality, customer’s expectation, ill productivity, higher deliver time, etc. The proposed research incorporates the aforesaid issues and provides the various important attributes needed to be considered for the optimum evaluation and selection of industrial robots.

The need for changes in the technological dimensions (speed, productivity, navigation, upgraded product demands, etc.) of robot was encountered as a hardship work for managers to take wise decision dealing with a wide range of availability of robot types and models with distinct features in the manufacturing firms. The presented work aids the managers in taking their decisions effectively while dealing with the aforesaid circumstances.

The proposed work suggests chains of dimensions (59 crucial beneficial and non-beneficial dimensions) that can be used by managers to measure the economic worth of robot to carry out logistic activities in updated manufacturing environment. The proposed work evolves as an effective cluster approach-embedded type-2 fuzzy sets with WGAO to assess manufacturing firms under availability of low information.

This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.

Based on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.

The results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.

This study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.

This paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

Construction is a highly dynamic environment with numerous interacting factors that affect construction processes and decisions. Uncertainty is inherent in most aspects of construction engineering and management, and traditionally, it has been treated as a random phenomenon. However, there are many types of uncertainty that are not naturally modelled by probability theory, such as subjectivity, ambiguity and vagueness. Fuzzy logic provides an approach for handling such uncertainties. However, fuzzy logic alone has some limitations, including its inability to learn from data and its extensive reliance on expert knowledge. To address these limitations, fuzzy logic has been combined with other techniques to create fuzzy hybrid techniques, which have helped solve complex problems in construction. In this chapter, a background on fuzzy logic in the context of construction engineering and management applications is presented. The chapter provides an introduction to uncertainty in construction and illustrates how fuzzy logic can improve construction modelling and decision-making. The role of fuzzy logic in representing uncertainty is contrasted with that of probability theory. Introductory material is presented on key definitions, properties and methods of fuzzy logic, including the definition and representation of fuzzy sets and membership functions, basic operations on fuzzy sets, fuzzy relations and compositions, defuzzification methods, entropy for fuzzy sets, fuzzy numbers, methods for the specification of membership functions and fuzzy rule-based systems. Finally, a discussion on the need for fuzzy hybrid modelling in construction applications is presented, and future research directions are proposed.

For a nation to become a superpower, it's scientific and technological advancement is essential. Each country is exploring how to improve themselves in terms of science and technology. The authors analyzed the innovation capabilities of 35 OECD countries that have not recently joined Lithuania.

In recent years, a lot of research work has been done on trapezoidal interval type-2 fuzzy sets (TIT-2 FS), and many research works have been published. The trapezoidal interval type-2 fuzzy set helps effectively to represent the uncertainty comparatively than the type-1 fuzzy set. Taking advantage of this effectiveness, the authors extend the best multi-criteria decision making method (MCDM) for trapezoidal interval type-2 fuzzy sets. Here, ELimination and Choice Expressing REality III (ELECTRE III) method in the trapezoidal interval type-2 fuzzy set environment is proposed.

This analysis helps to the OECD countries to develop their level of innovation in the criteria. The authors are making this evaluation for the year 2018 based on the 31 criteria. Application of the proposed method expressed by evaluation of the national innovation capability problem. Based on the obtained results, the top five countries are United States, Switzerland, Canada, Germany and Japan.

The authors collected required data from different available data sources like OECD, IMD, USPTO, ITU and surveyed data reported by KISTEP. After collecting all the data from different sources, the authors calculated the standard values as KISTEP. After converting the standard values into trapezoidal interval type-2 fuzzy values, the authors construct a decision matrix based on these values. Then, the authors determined the possibility mean values and preference. Then, they calculated the concordance and discordance credibility degree values. Finally, they ranked OECD countries by the net credibility degree. The results are computed by using the MATLAB software.