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Assessing air quality with multiple parameters is crucial and demands meticulous analysis due to its profound impact on human health and the environment. Traditional air quality techniques might overlook uncertainties in pollutant data. The fuzzy logic approach adeptly handles such uncertainties. This study thoroughly analyses two approaches: Fuzzy Multi-Attribute Decision Making (MADM) methods and the Fuzzy Inference System (FIS). Fuzzy MADM methods, including the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), are employed with a combined weighting approach involving Analytical Hierarchy Process (AHP) and Entropy. The FIS approach utilizes the Mamdani method built using MATLAB 2021b’s fuzzy logic toolbox. The air quality is assessed for the Diwali festival for the year 2022 in the various regions of Tamil Nadu, India. Spearman’s rank correlation is utilized to determine the result accuracy of fuzzy MADM and FIS. The fuzzy MADM methods attained a higher correlation of 0.88 compared to the Mamdani FIS of 0.84. Fuzzy MADM proves most effective in air quality assessment.

This work presents a fuzzy TOPSIS model under group decisions for solving the facility location selection problem, where the ratings of various alternative locations under different subjective attributes and the importance weights of all attributes are assessed in linguistic values represented by fuzzy numbers. The objective attributed are transformed into dimensionless indices to ensure compatibility with the linguistic ratings of the subjective attributes. Furthermore, the membership function of the aggregation of the ratings and weights for each alternative location versus each attribute can be developed by interval arithmetic and α-cuts of fuzzy numbers. The ranking method of the mean of the integral values is applied to help derive the ideal and negative-ideal fuzzy solutions to complete the proposed fuzzy TOPSIS model. Finally, a numerical example demonstrates the computational process of the proposed model.

This paper presents a framework of website quality evaluation for measuring the performance of government websites. Multiple criteria decision-making (MCDM) is a widely used tool for evaluating and ranking problems containing multiple, usually conflicting criteria. In line with the multi-dimensional characteristics of website quality, MCDM provides an effective framework for an inter-websites comparison involving the evaluation of multiple attributes. It thus ranks different websites compared in terms of their overall performance. This paper models the inter-website comparison problem as an MCDM problem, and presents a practical and selective approach to deal with it. In addition, fuzzy logic is applied to the subjectivity and vagueness in the assessment process. The proposed framework is effectively illustrated to rate Turkish government websites.

Enterprise resource planning (ERP) projects are prone to risk from the strategic, operational, technical and organizational perspective. The assessment of project risks is a challenging task for project managers and is considered in a class of a multi-criteria decision making (MCDM) problem. In this work, an MCDM approach has been presented for risk assessment in ERP project by COPRAS under fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by triangular fuzzy number. Fuzzy COPRAS (COPRAS-F) has been used to determine the weight of risk criteria and then prioritize the risk factor based on the calculated weight of criteria. The prioritized risk factors have been classified in scale from almost certain to rare risks. The proposed approach is illustrated with a real case studying fertilizer plant and the associated results have been compared with fuzzy TOPSIS technique. The result of this study demonstrates that excessive customization, ineffective consulting services experiences, complex architecture and high number of modules, poor project team skills, inadequate change management, inadequate ERP selection, ineffective strategic thinking and planning, poor leadership, lack of business process re-engineering and low-key user involvement are top ten risks that need to be mitigated to avoid failure of ERP project.

In recent years several previous scholars made attempts to develop, extend, propose and apply Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for solving problems in decision making issues. Indeed, there are questions, how TOPSIS can help for solving these problems? Or does TOPSIS solved decision making problems in the real world? Therefore, this study shows the recent developments of TOPSIS approach which are presented by previous scholars. To achieve this objective, there are 105 reviewed papers which developed, extended, proposed and presented TOPSIS approach for solving DM problems. The results of the study indicated that 49 scholars have extended or developed TOPSIS technique and 56 scholars have proposed or presented new modifications for problems solution related to TOPSIS technique from 2000 to 2015. In addition, results of this study indicated that, previous studies have modifications related to this technique in 2011 more than other years.

This paper proposes and validates an e-service quality (eSQ) evaluation model for B2C websites in the textile-and-fashion (TF) sector in Spain. The research allows to represent the positioning of the main websites of this sector according to different utilitarian and hedonic quality dimensions and to establish the global ranking of these websites by using the F-TOPSIS methodology. After a thorough bibliographic review of the most common attributes used to evaluate eSQ of B2C websites, an expert panel has assisted in both, their precise wording and grouping them into the factors and latent dimensions of the proposed model. Later, model validation was carried out through the psychometric analysis of a survey conducted over a sample of 405 users searching/buying on TF industry online sales platforms. The paper already shows the perceptual maps for the eSQ dimensions analyzed for different TF B2C websites. Finally, in order to be able to process the intrinsic uncertainty inherent to the valuations given by the users, the F-TOPSIS method was used to sort the main TF websites. The study has demonstrated the validity of the proposed model, making it replicable in other countries and allowing to obtain the positioning and ranking of the six main websites analyzed in Spain, where Asos and Zara were the leaders.

The threats like increasing pollution level and scarcity of natural resources are showing that Sustainable Consumption and Production (SCP) is one of the key solutions and the main contributor driver of Sustainable Development Goals (SDGs). Eventually, a mysterious disease named as COVID-19 started spreading very fast around the globe and it was declared a pandemic. To protect citizens from this pandemic, the government announced complete lockdown in the country. This lockdown due to COVID-19 has put its impact on every aspect of life. In this research study, the efforts have been made to identify various impacts of COVID-19 on SCP practices and propose various solutions to overcome these impacts of COVID-19. In the Indian perspective, a total fifteen impacts of COVID-19 under five different heads along with eighteen solutions to overcome these impacts have been identified with the help of literature, various reports and experts’ inputs. All these impacts and solutions were analyzed using a hybrid framework. Results revealed that COVID-19 majorly put its impact on nation, business and behavior followed by the impact on society and environment. All these impacts can be overcome by adopting solutions like strong and clear policies formation and its implementation, financial packages to industries to boost up the economy, firm determination of top management, safety of the workforce and tax reduction on sustainable products. The final results will be very helpful for all the actors focused on SCP.

The aim of study is to prioritize resilient capabilities required for an Industry 4.0 manufacturing business. These capabilities are prioritized considering the barriers faced by their supply chains in becoming resilient. After the review of literature and discussion with experts from the case company and other supply chain professionals, the barriers and resilient capabilities were shortlisted. The study utilized a hybrid of AHP-fuzzy TOPSIS technique to provide weights to the criteria variables (here barriers) and rank the alternatives (here resilient capabilities). Five criteria of barriers were identified for the purpose of the study, namely, strategic barriers, technological barriers, cultural barriers, individual barriers, and organizational barriers. Twenty-three subcriteria were identified for these barriers. Six capabilities were decided upon to be prioritized out of which planning capabilities were obtained to be the most important followed by collaborative, agile, supply chain design modification capability, interoperability, and supply flexibility. The study attempts to fill the gap identified in the literature regarding the lack of studies on supply chain resilience barriers. It therefore provides a realistic framework to prioritize the resilience capabilities required for mitigating such barriers.

Nowadays most of the organizations tend to outsource their projects. In these cases, two major problems arise: project selection and contractor selection. There are many papers which have argued separately about project and contractor selections. In this paper, we propose a decision support system for selecting projects and related contractors. The proposed approach contains three phases including contractors' prequalification (Phase 1), computing success coefficient of each contractor in projects using fuzzy TOPSIS method (Phase 2), and selecting projects and assigning each project to the most appropriate contractor using a linear programming model (Phase 3). Finally, a numerical example is illustrated to show the application of the proposed method.

Continuous and effective communication with suppliers can play a very important role in the strength and balance of the supply chain and create competitive advantages for manufacturers. Choosing the right supplier is crucial while choosing the wrong suppliers can affect the financial and operational activities of an organization negatively. In this study, an attempt is made to tackle a fuzzy multi-criteria supplier selection problem of a detergent factory as a case study. Moreover, the objective of the investigation is to put forth a model within a fully ambiguous setting, as this allows for the model’s practicality in addressing real-world issues and achieving more precise outcomes. This problem is modeled as ranking 5 suppliers according to 15 criteria selected from the literature. For this aim, a stepwise solution methodology consisting of fuzzy DEMATEL, fuzzy QFD, fuzzy TOPSIS, and fuzzy VIKOR approaches is developed for the first time in order to cover all aspects of the problem e.g., the fuzzy DEMATEL is used to select the effective criteria and eliminate the unnecessary ones, the fuzzy QFD is used to determine importance weight of each selected criterion, and the fuzzy TOPSIS and VIKOR approaches are used to rank the suppliers separately. According to the computations made on the data of the case study, the ranking of the suppliers is obtained by both of the methods while some similarities of the obtained rankings are discovered. Consequently, this study introduces a hybrid model that combines highly favorable decision-making methodologies specifically designed for a fully ambiguous environment.

In today’s highly turbulent and competitive environment, the success of the organization depends on the performance of its suppliers. However, supplier selection problems are complex as they involve a large number of criteria and, frequently, some of the criteria cannot be evaluated precisely. Moreover, fluctuations of supplier performances and unknown information always exist in real-world decision-making. It is a complex multiple-criteria decision-making (MCDM) problem as it involves a trade-off among various criteria with vagueness and imprecision and also involves a group of experts with diverse opinion. Therefore, to make more practical decisions, this paper is intended to propose an integrated technique for order preference by similarity to ideal solution (TOPSIS) in fuzzy environment with multi-choice goal programming (MCGP) to handle the supplier assessment and order allocation for a battery manufacturing organization. Using linguistic variables, the decision-makers assess the rating of suppliers as well as the importance of various factors. Linguistic variables are expressed in trapezoidal fuzzy numbers (TrFN). Fuzzy-TOPSIS method is proposed to obtain the rank of suppliers and MCGP method is used to allocate suitable orders to the selected suppliers. A case study is implemented to find the applicability and validity of the proposed model. Finally, sensitivity analysis is performed to observe the effect of weights of criteria on supplier evaluation problem.

The use of fuzzy numbers (FNs) for uncertainty treatment within Multi-Criteria Decision Analysis (MCDA) is a claiming approach for examination of multicriteria problems in fuzzy environment. For proper use of a fuzzy extension for the MCDA method (FMCDA), the fulfilment of corresponding axioms/requirements, associated with this method, should be analyzed. For empirical MCDA methods (e.g., TOPSIS, AHP, PROMETHEE) the basic axiom concerns the properties of generalized criterion for this method. The goal of this contribution is exploring violation of basic axioms for FMCDA methods for Fuzzy TOPSIS (FTOPSIS) as an example. The ways of adjustment of fuzzy MCDA methods to correct use is briefly discussed.