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The goal of this article is to introduce the notion of a grey relation between grey sets using grey numbers.

This study uses the grey number to create novel ideas of grey sets. We suggest several operations that can be performed on it, including the union, intersection, join, merge, and composition of grey relations. In addition, we present the definitions of reflexive, symmetric, and transitive grey relations and analyze certain characteristics associated with them. Furthermore, we formulate the concept of the grey equivalence relation, apply it to the study of the grey equivalence class over the grey relation, and go over some of its features.

We present new algebraic aspects of grey system theory by defining grey relations and then analyzing their characteristic features.

This paper proposes a new theoretical direction for grey sets according to grey numbers, namely, grey relations. This paper proposes a new theoretical direction for grey sets according to grey numbers, namely, grey relations. As such, it can be applied to create rough approximations as well as congruences in algebras, topologies, and semigroups.

The presented notions are regarded as new algebraic approaches in grey system theory for the first time. Additionally, some fundamental operations on grey relations are also investigated. Consequently, different types of grey relations, such as reflexive, symmetric, and transitive relations, are discussed. Then, the grey equivalence class derived from the grey equivalence relation is demonstrated, and its properties are examined.

Since conducting agile strategies provides sustainable passenger satisfaction and revenue by replacing applied policies with more profitable ones rapidly, the focus of this study is to evaluate agile attributes for managing low-cost carriers (LCCs) operations by means of resources and competences based on dynamic capabilities built on resource-based view (RBV) theory and to achieve sustainable competitive advantage in a volatile and dynamic air transport environment. LCCs in Turkey are also evaluated in this study since the competition among LCCs is high to gain market share and they can adapt quickly to all kinds of circumstances.

Two well-known Multi-Criteria Decision-Making Methods (MCDM) named as the Stepwise Weight Assessment Ratio Analysis (SWARA) and multi-attributive border approximation area comparison (MABAC) methods by employing Picture fuzzy sets (PiFS) are employed to determine weight of agile attributes and superiority of LCCs based on agile attributes in the market, respectively. To check the consistency and robustness of the results for the proposed approach, comparative and sensitivity analysis are performed at the end of the study.

While the ranking orders of agile attributes are Strategic Responsiveness (AG1), Financial Management (AG4), Quality (AG2), Digital integration (AG3) and Reliability (AG5), respectively, LCC2 is selected as the best agile airline company in Turkey with respect to agile attributes. SWARA and MABAC method based on PiFS is appropriate and effective method to evaluate agile attributes that has important reference value for the airline companies in aviation industry.

The findings of this study will support managers in the airline industry to conduct airline operations more flexibly and effectively to take sustainable competitive advantage in unexpected and dynamic environment.

To the author' best knowledge, this study is the first developed to identify the attributes necessary to increase agility in LCCs. Thus, as a systematic tool, a framework is developed for the implementation of agile attributes to achieve sustainable competitive advantage in the airline industry and presented a roadmap for airline managers to deal with crises and challenging situations by satisfying customer and increasing competitiveness.

This study aims to focus on sustainable supplier selection in a construction company considering a new multi-criteria decision-making (MCDM) method based on dominance-based rough set analysis. The inclusion of sustainability concept in industrial supply chains has started gaining momentum due to increased environmental protection awareness and social obligations. The selection of sustainable suppliers marks the first step toward accomplishing this objective. The problem of selecting the right suppliers fulfilling the sustainable requirements is a major MCDM problem since various conflicting factors are underplay in the selection process. The decision-makers are often confronted with inconsistent situations forcing them to make imprecise and vague decisions.

This paper presents a new method based on dominance-based rough sets for the selection of right suppliers based on sustainable performance criteria relying on the triple bottom line approach. The method applied has its distinct advantages by providing more transparency in dealing with the preference information provided by the decision-makers and is thus found to be more intuitive and appealing as a performance measurement tool.

The technique is easy to apply using “jrank” software package and devises results in the form of decision rules and ranking that further assist the decision-makers in making an informed decision that increases credibility in the decision-making process.

The novelty of this study of its kind is that uses the dominance-based rough set approach for a sustainable supplier selection process.

The main goal of this research is to analyze and assess the barriers to Digital Transformation (DT) of the healthcare Supply Chain (SC) in developing countries and evaluate strategies to overcome such barriers. The DT has been related not only to the development of SC performance but also to the expansion of its resilience capabilities in a healthcare setting to overcome the results of unavoidable risk events and return to its previous or new state, which has at least the same or better conditions, after the occurrence of an unpredicted event.

Assessment of the barriers and determination of the importance or effectiveness of proposed strategies to handle these barriers are conducted through a hybrid Multi-Criteria-Decision-Making method consisting of an Analytical Hierarchy Process and multi-attributive border approximation area comparison (MABAC) under picture fuzzy (PiF) environment.

Based on the outcomes of the research, the most important barriers for DT in healthcare SC functions were the organizational and technological issues, including Low support from top managers (O1), Lack of digital culture (O2), and Info/data safety and privacy (T4). To handle these barriers, the prior strategy was selected as “Making breakthroughs and incentives of top managers for the DT in the industry (ST3)”.

The study may be extended to include developed countries and or experts from developed countries. Through this, the study will be generalized to a global level. The most common qualitative criteria, which include subjectivity, are considered. The research may be enhanced by including quantitative criteria in the decision-making process. The barriers related to DT for healthcare SC were considered. Thus, the study may be detailed by looking at the problem in terms of operational failure and determining the digital technology that can overcome such operational failures. The precedence or importance of any barrier may fluctuate with the upgradation of technological tools and improvements.

In terms of practical contribution, this research provides real-world suggestions to facilitate digital transformation in their SCs. Specifically, this study increases the awareness of healthcare and other industries' managers about obstacles that prevents digital transformation in SC and provides managerial path to relieve the effects of barriers.

To the authors' best knowledge, this is the first study to examine barriers of DT required for the promotion of resilient healthcare SCs in this concept. In addition, no previous research applied PiFSs-based AHP and MABAC integration to assess barriers and develop strategies for the DT of healthcare SC. The findings may be references for governmental institutions, policymakers, decision-makers, and stakeholders to develop proper strategies for a successful DT in healthcare SC resilience and the healthcare industry.

To overcome the limitations of traditional multi-attribute decision making (MADM) methods, which only provide deterministic rankings of decision objects, this paper proposes a novel multi-attribute 3WD model. This model presents three-parameter interval grey number decision-theoretic rough sets (TPIGNDTRSs), aiming to offer a reasoned interpretation of loss functions in grey environments and ensure objective assessment of conditional probabilities.

Firstly, the traditional equivalence relation is replaced with the probabilistic dominance relation (PDR), categorizing decision objects into two state sets in DTRS for more objective conditional probabilities. Secondly, as the three-parameter interval grey number (TPIGN) introduces the most probable value on the basis of the traditional two-parameter interval grey number, it provides a more comprehensive method for describing grey information. Consequently, integrating TPIGN into DTRS refines the interpretations of loss functions in grey environments. Finally, by utilizing two main sorting techniques, relative kernel and degree of accuracy ranking and possibility ranking, two types of 3WD rules with TPIGNDTRSs, are constructed.

This study has successfully developed and validated a new multi-attribute 3WD model. The model was tested in two distinct domains: evaluating innovation efficiency in high-tech enterprises and recommending movies in a practical case. The findings reveal that the model can effectively integrate relevant information of high-tech enterprises, provide the government with enterprise-level assessments, and gather consumer preferences to recommend the most suitable movies.

This study treats the loss function as grey information in the 3WD model but overlooks the grey nature of evaluation values, limiting its applicability. Additionally, the model’s reliance on subjective expert judgments and historical data to establish the loss function may affect its objectivity. The implications of this research are that the novel model overcomes traditional MADM limitations, enhancing decision-making quality and efficiency in complex and grey scenarios. The model’s successful application in evaluating high-tech enterprises and recommending movies illustrates its dual value in both theory and practice.

Initially, the model proposed in this study is of significant importance for the development of the 3WD field, as it successfully addresses the challenges of uncertain loss functions and unknown conditional probabilities in grey information environments. Moreover, by integrating the 3WD model with MADM problems, it has broken through the bottlenecks of traditional MADM methods, offering new perspectives and strategies for solving MADM issues. Therefore, this research not only advances theoretical research but also provides powerful tools for practical applications.

The study looks into the idea of Circular Economy through the lens of stock market performance. More specifically the authors examine if a company's association with the innovative and environment friendly disposal practices has an implication on its stock market performance.

The study adopts a quantitative approach to derive conclusions. The market efficiency and excess volatility are estimated using OHLC measures for more accuracy. For robustness checks VRatio, bootstrapping and simulation are used as detailed in section 3.2 of the study.

The study estimates show a clear sign of excess volatility in the majority of the stocks under consideration. That confirms that the market is highly fragmented for Circular Economy–focused stocks. These types of stocks are often cyclical in nature and can offer a variety investment opportunity in the short to medium term. In addition to it the study estimates confirm that Circular Economy–focused stocks show limited signs of market efficiency. Thus, unlike ESG investment the concept of Circular Economy investment is a bit more ambiguous to the global investors.

The present study is first of its kind that looks into the idea of Circular Economy through the lens of stock market performance.

Cost overrun in infrastructure projects is a constant concern, with a need for a proper solution. The current estimation practice needs improvement to reduce cost overruns. This study aimed to find possible statistical modelling techniques that could be used to develop cost models to produce more reliable cost estimates.

A bibliographic literature review was conducted using a two-stage selection method to compile the relevant publications from Scopus. Then, Visualisation of Similarities (VOS)-Viewer was used to develop the visualisation maps for co-occurrence keyword analysis and yearly trends in research topics.

The study found seven primary techniques used as cost models in construction projects: regression analysis (RA), artificial neural network (ANN), case-based reasoning (CBR), fuzzy logic, Monte-Carlo simulation (MCS), support vector machine (SVM) and reference class forecasting (RCF). RA, ANN and CBR were the most researched techniques. Furthermore, it was observed that the model's performance could be improved by combining two or more techniques into one model.

The research was limited to the findings from the bibliometric literature review.

The findings provided an assessment of statistical techniques that the industry can adopt to improve the traditional estimation practice of infrastructure projects.

This study mapped the research carried out on cost-modelling techniques and analysed the trends. It also reviewed the performance of the models developed for infrastructure projects. The findings could be used to further research to develop more reliable cost models using statistical modelling techniques with better performance.

The purpose of this paper is the identification of the magnetic characteristics of the induction load by means of the B–H curve proposed by Fröhlich.

An electromagnetic description of the inductor system is performed to substitute the effects of the induction load, for a mathematical condition, the so-called impedance boundary condition (IBC).

A significant reduction in the computational cost of electromagnetic simulation has been achieved through the use of the IBC, resulting in a computation time approximately 400 times faster than time domain simulation. Moreover, an alternative method has been developed to experimentally identify the parameters that determine the magnetic behavior of the induction load. Finally, further research has been conducted to understand the relationship between the equivalent impedance of an induction load and the excitation current level.

This work is performed to achieve a better understanding of the fundamentals involved in the electromagnetic modeling of an induction heating system.

This paper introduces the dependence on the excitation level based on a first harmonic approximation and extends the IBC to nonlinear magnetic materials which allows the identification of the magnetic characteristics of the induction load.

Through Bourdieusian sociology, this study aims to interpret a globalized symbolic environment ward by the States and dominated by organizations through the States’ Nobilities enticing and the Euro-American influences disseminated by the cultural circuit of capitalism in the inculcation and incorporation of a class habitus conniving with this logic of domination.

This study has developed a theoretical essay based on the contributions of Bourdieusian sociology to discuss and understand the following concepts and their respective relationships: symbolic environment, globalization, organizations, State, State Nobility, Euro-American influences, cultural circuit of capitalism and class habitus.

The arguments built throughout this theoretical essay recognized how class habitus on environment contributes to organizations establishing themselves as a space that consolidates and replicates the domination logic. As indicated, the State Nobility is an intermediary element between dominant organizations and the State, as dominated.

This theoretical essay signals that less harmful alliances between organizations, the State Nobility and the State could culminate in social, environmental and economic scenarios provided with more inclusion, diversity and preservation.

This study presents an in-depth conceptual analysis to hold power structures responsible as direct and indirect drivers of environmental problems, with their different proportions and severity levels, affecting the planet.

This study proposes an alternative lens to debate and question how much the results presented by the contemporary world order compensate (if in any way) the damage that invades and deteriorate environmental assets.

This study aims to analyse the positioning of young people in the face of the challenges posed by the Sustainable Development Goals (SDGs). It focuses on the case of Erasmus+ students at a Spanish university and tries to evaluate the importance of each of the SDGs for them.

Based on primary data obtained through a survey of more than 300 young people, factor analysis was applied to evaluate the importance assigned to each SDG and quantify the degree of concern assigned to each of them.

Results show a high degree of concern for all the SDGs among Erasmus students, although they have done so with different levels of intensity. College students especially value education. Women are more concerned about socioeconomic problems. Furthermore, surprising results have been found in terms of gender equality, which indicates the need to deepen this analysis.

This work contributes to the academic literature, still limited but growing, on how Erasmus students perceive the SDGs and to what level they feel committed to these objectives. Furthermore, it can be helpful for public policy managers regarding a specific group of young university students and a hot topic such as sustainability.