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Platform-based enterprises, as micro-entities in the platform economy, have the potential to effectively promote the low-carbon development of both supply and demand sides in the supply chain. Therefore, this paper aims to provide a multi-criteria decision-making method in a probabilistic hesitant fuzzy environment to assist platform-type companies in selecting cooperative suppliers for carbon reduction in green supply chains.

This paper combines the advantages of probabilistic hesitant fuzzy sets (PHFS) to address uncertainty issues and proposes an improved multi-criteria decision-making method called PHFS-DNMEREC-MABAC for aiding platform-based enterprises in selecting carbon emission reduction collaboration suppliers in green supply chains. Within this decision-making method, we enhance the standardization process of both the DNMEREC and MABAC methods by directly standardizing probabilistic hesitant fuzzy elements. Additionally, a probability splitting algorithm is introduced to handle probabilistic hesitant fuzzy elements of varying lengths, mitigating information bias that traditional approaches tend to introduce when adding values based on risk preferences.

In this paper, we apply the proposed method to a case study involving the selection of carbon emission reduction collaboration suppliers for Tmall Mart and compare it with the latest existing decision-making methods. The results demonstrate the applicability of the proposed method and the effectiveness of the introduced probability splitting algorithm in avoiding information bias.

Firstly, this paper proposes a new multi-criteria decision making method for aiding platform-based enterprises in selecting carbon emission reduction collaboration suppliers in green supply chains. Secondly, in this method, we provided a new standard method to process probability hesitant fuzzy decision making information. Finally, the probability splitting algorithm was introduced to avoid information bias in the process of dealing with inconsistent lengths of probabilistic hesitant fuzzy elements.

The textile industry harms the environment at every stage of production, from the acquisition of raw materials to the disposal of finished products. It is very important for the textile industry to adapt to the basic policies on environmental sensitivity and sustainability to keep up with the transformation in production processes and the rapid changes occurring around the world in order to exist in global competition. Within the scope of sustainable development goals, it is of great importance to measure and evaluate indicators of all processes of the sector. This paper aims to present application of multi-criteria decision making (MCDM) methods for the assessment of sustainable development in textile industry.

The data of a multinational clothing company’s four-year sustainability performance between 2018 and 2021 were evaluated under 22 sustainability parameters determined using two new MCDM techniques, namely the combined consensus solution method and multi-attribute ideal real comparative analysis. In determining the criteria, priority key indicators were determined by taking into account the sector’s relationship with the environment, raw material consumption and social adequacy.

According to the application results of both methods, the year 2021 shows the best performance. It has been seen that the sustainability performance of the Inditex group has increased over the years and the results of the applied models support each other. It can be suggested that the proposed approach be applied to evaluate the progress in the textile sector with the relevant data on a particular company or on a macro scale.

This study makes an important contribution to the field in terms of the fact that the methods used are recent and have no application in the field of textiles. It allows the evaluation of different sustainability criteria together using a single method. It is very important to share data on sustainability indicators with customers, employees, suppliers, investors, partner organizations and society and evaluate performance. Analyzing sustainability performance on the basis of annual reports is important in terms of identifying good practices, sharing them with the community and setting an example. In addition, using scientific methods in the evaluation of the sustainability report data published by companies regularly provides significant feedback for policymakers and academics.

This study aims to evaluate sustainable investment policies for housing in Qatar.

This paper proposes a new model for analyzing sustainable investment policies for housing demand in Qatar via a hybrid quantum fuzzy decision-making model. The study processed the criteria with the facial expression-based Quantum Spherical fuzzy DEMATEL and ranked the alternatives with the facial expressions-based quantum spherical fuzzy TOPSIS. Four factors were determined due to a comprehensive literature review (Environment, Housing Design, Building Design, and Surrounding the building), with five sustainable investment policy alternatives (Electricity production with renewable energies, Recycling systems and materials in construction, Transport with less carbon emission, Biodiversity for residents, and Resilience to natural disasters).

The analysis indicates that the design of the building is the most important factor (0.254), while the environment is the most influencing factor (0.253) regarding housing demand in Qatar. Transport with less carbon emission and electricity production with renewable energies are the most critical alternative investment policies.

This study provides useful insights for regulators, policymakers, and stakeholders in Qatar’s sustainable investment policies for housing demand. The main motivation of this study is that there is a need for a novel model to evaluate the sustainable investment policies for housing demand. The main reason is that existing models in the literature are criticized due to some issues. In most of these models, emotions of the experts are not taken into consideration. However, this situation has a negative impact on the appropriateness of the findings. Because of this situation, in this proposed model, facial expressions of the experts are considered. With the help of this issue, uncertainties in the decision-making process can be handled more effectively.

The study aims to propose a decision-support system to determine the location of a regional disaster logistics warehouse. Emphasizing the importance of disaster logistics, it considers the criteria to be evaluated for warehouse location selection. It is aimed to determine a warehouse location that will serve the disaster victims most efficiently in case of a disaster by making an application for the province of Izmir, where a massive earthquake hit in 2020.

The paper proposes a fuzzy best–worst method to evaluate the alternative locations for the warehouse. The method considers the linguistic evaluations of the decision-makers and provides an advantage in terms of comparison consistency. The alternatives were identified through interviews and discussions with a group of experts in the fields of humanitarian aid and disaster relief operations. The group consists of academics and a vice-governor, who had worked in Izmir. The results of a previously conducted questionnaire were also used in determining these locations.

It is shown how the method will be applied to this problem, and the most effective location for the disaster logistics warehouse in Izmir has been determined.

This study contributes to disaster preparedness and brings a solution to the organization of the logistics services in Izmir.

The purpose of this paper is to prevent the destruction of other parts of a wind energy conversion system because of faults, the diagnosis of insulated-gate bipolar transistor (IGBT) faults has become an essential topic of study. Demand for sustainable energy sources has been prompted by rising environmental pollution and energy requirements. Renewable energy has been identified as a viable substitute for conventional fossil fuel energy generation. Because of its rapid installation time and adaptable expenditure for construction scale, wind energy has emerged as a great energy resource. Power converter failure is particularly significant for the reliable operation of wind power conversion systems because it not only has a high yearly fault rate but also a prolonged downtime. The power converters will continue to operate even after the failure, especially the open-circuit fault, endangering their other parts and impairing their functionality.

The most widely used signal processing methods for locating open-switch faults in power devices are the short-time Fourier transform and wavelet transform (WT) – based on time–frequency analysis. To increase their effectiveness, these methods necessitate the intensive use of computational resources. This study suggests a fault detection technique using empirical mode decomposition (EMD) that examines the phase currents from a power inverter. Furthermore, the intrinsic mode function’s relative energy entropy (REE) and simple logical operations are used to locate IGBT open switch failures.

The presented scheme successfully locates and detects 21 various classes of IGBT faults that could arise in a two-level three-phase voltage source inverter (VSI). To verify the efficacy of the proposed fault diagnosis (FD) scheme, the test is performed under various operating conditions of the power converter and induction motor load. The proposed method outperforms existing FD schemes in the literature in terms of fault coverage and robustness.

This study introduces an EMD–IMF–REE-based FD method for VSIs in wind turbine systems, which enhances the effectiveness and robustness of the FD method.

In the digital era, the competitiveness of an enterprise is highly dependent on the success of its digital transformation. The effectiveness of such transformation, in turn, relies heavily on the organization's strategic vision and resource fitness. Accordingly, the authors aim to explore the impact of strategic vision on digitalization (SVD) on the digital transformation of small- and medium-sized enterprises (SMEs), drawing on the perspective of resource orchestration theory.

Based on first-hand interview data from 347 Chinese SMEs, the research model was tested empirically by both Structural Equation Modeling and Fuzzy Set Qualitative Comparative Analysis (fsQCA).

The study results supported that the positive effect of SVD on digital transformation, and the mediating effect of resource orchestration (resource structuring, resource bundling and resource leveraging) accounts for the relationship between SVD and digital transformation. Further, the fsQCA showed that neither SVD nor resource orchestration alone constitutes a necessary condition for high digital transformation in SMEs, and that SVD and resource orchestration elements constitute three configuration paths that drive SMEs to achieve high-level digital transformation.

To the authors knowledge, this is the first study of its kind to theorize and empirically examine how SVD affects SMEs digital transformation. In addition, the authors have highlighted the importance of resource orchestration in forging a link between SVD and digital transformation. The research contributes to the resource orchestration theory and digitalization literature and provides guidelines on how SMEs can realize digital transformation.

In a world teeming with concurrent processes and associated chaos, organizational working procedures have adapted to new trends; employees must keep up with everything while maintaining their mental health. Spirituality lends a person's life significance. Spirituality in the workplace can both physically and psychologically engage employees. Spirituality in the workplace is reflected in the organizational culture, which is founded on fundamental values such as trust, honesty, appreciation, innovation, care, respect, and loyalty. Workplace spirituality encompasses the pursuit of one's ultimate purpose in life, the development of a solid connection to colleagues and other people associated with work, and the consistency or alignment between one's fundamental beliefs and the organization's values. To have a competitive advantage and attract the best personnel, an organization's working environment must be based on strong ethical and spiritual values such as compassion, integrity, respect, harmony, trust, teamwork, and forgiveness, among others.

Guided by paradox theory, the study aims to significantly advance Sustainability in Higher Education Institutions (SHEI) scholarship and inform change agents’ (CAs) practices by uncovering the tensions underlying the challenges CAs face in embedding sustainability in their universities and learning about potential strategies to manage these tensions.

The authors conducted a multi-step, mix-methods study including interviews (n = 15), an online survey (n = 36) and focus groups (n = 29) with CAs from 17 of Austria’s 22 public universities. Participating CAs consisted of faculty, staff and administrators with leading roles in their Higher Education Institutions’ sustainability change processes.

Austrian SHEI CAs’ responses revealed 15 tensions at and between the individual, organizational and system level addressing academic, organizational and external stakeholder engagement aspects. Six tensions were selected for more in-depth exploration including elaboration of management strategies, building on CAs’ experiences. Results revealed examples of acceptance, separation and synthesis strategies.

Based on the exploratory nature of our study, the authors do not claim to have identified a comprehensive list of tensions underlying the challenges faced by SHEI CAs, nor of all potential management strategies.

Although this study focused exclusively on Austrian SHEI CAs, the challenges they shared were consistent with those in the literature and, thus, insights should also support the CAs’ efforts in other countries.

This study offers novel perspectives on how to manage the challenges to SHEI. To the best of the authors’ knowledge, it is the first to describe paradox theory-informed management strategies recommended by a heterogenous group of SHEI CAs to address the barriers they face in transforming their universities toward sustainability.

The emotion regulation research has drawn considerable attention from academicians and scholars in the contemporary world. As a result, the publications that are specifically dedicated to emotion regulation research are rapidly escalating. Therefore, this study aims to conduct a bibliometric analysis of research articles that have been published in the field of “emotion regulation.” The study primarily examines the growth and development of scholarly publications, seminal studies, influential authors, productive journals, research production and collaboration among countries, emerging research themes, research hotspots and thematic evolution of emotion regulation research.

The Web of Science Core Collection database was used to gather the study’s data, which was then analysed using VOSviewer and Bibliometrix, Biblioshiney open-source package of the R language environment.

The study’s results reveal that the research on emotion regulation has grown significantly over the last three decades. Notably, Emotion and Frontiers in Psychology are the most dominant and productive journals in the field of emotion regulation research. The most prominent author in the area of emotion regulation is identified as James Gross, followed by Gratz, Wang and Tull. The USA is at the forefront of research on emotion regulation and has collaborated with most of the developed countries like Germany, England and Canada. The keyword analysis revealed that the most potential research areas in the field of emotion regulation are functional magnetic resonance imaging, amygdala, post-traumatic stress disorder, borderline personality disorder, alexithymia, emotion dysregulation, depression, anxiety, functional connectivity, neuroimaging, mindfulness, self-regulation, resilience and coping. The thematic evolution reflects that the research on emotion regulation has recently focused on issues including Covid-19, non-suicidal self-injury, psychological distress, intimate partner violence and mental health.

The results of this study highlighted the current knowledge gaps in emotion regulation research and suggested areas for further investigation. The present study could be useful for researchers, academicians, planners, publishers and universities engaged in emotion regulation research.

Primary teachers play a vital role in fostering pupils' successful futures. Therefore, gaining knowledge of primary teacher students' learning processes, including the achievement of information-seeking skills, is crucial. The aim of this paper is to understand better the interplay between cognitive appraisals and emotions in the constructivist process of learning and achieving information-seeking skills.

In-depth semi-structured interviews were conducted with six Swedish primary teacher students. The analysis of qualitative data was deductive and theory-driven, guided by Kuhlthau's information search process model, Scherer's semantic space of emotions and Pekrun's control-value theory of achievement emotions.

Anger/frustration, enjoyment and boredom were identified as activity emotions and anxiety, hopelessness and hope as prospective outcome emotions. The retrospective outcome emotions found were pride, joy, gratitude, surprise and relief. The appraisals eliciting the achievement emotions were the control appraisals uncertainty/certainty (activity and prospective outcome) and oneself/other (retrospective), and value appraisals negative/positive intrinsic motivation (activity) and failure/success (prospective and retrospective). The interplay between appraisals and emotions was complex and dynamic. The processes were individually unique, non-linear and iterative, and the appraisals did not always elicit emotions.

The study has theoretical and methodological implications for information behaviour research in its application of appraisal theories and the Geneva affect label coder. In addition, it has practical implications for academic librarians teaching information-seeking skills.