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This paper aims to identify the impacts of wire and arc additive manufacturing (WAAM) technology on the green supply chain management (GSCM) performance. Also, it intends to identify the most essential WAAM capabilities.

An exploratory case study related to a metallurgical company using WAAM technology to repair metallic components was developed. A research framework to identify WAAM production capabilities and the different GSCM performance criteria was proposed based on the current state of the art. Primary qualitative data provided evidence for developing seven propositions relating WAAM capabilities to GSCM performance.

The paper provides empirical evidence relating to how WAAM production capabilities impact the different performance criteria of the GSCM performance. The results show that “relative advantage” and “supply-side benefits” are critical capabilities developed through WAAM. Furthermore, most of the capabilities regarding “relative advantage” and “supply-side benefits” promote a higher GSCM performance.

This research was carried out using a single case study research design and using qualitative data. Thus, future works are encouraged to test the propositions empirically using quantitative methodologies.

The case study findings support that most WAAM production capabilities promote a higher GSCM performance. Managers could use this research to understand the capabilities developed by this fusion-based additive manufacturing (AM), become aware of the implications of new technology adoption on the supply chain environmental externalities, and develop new business models based on the WAAM capabilities.

This research contributes to expanding the state-of-the art related to WAAM technology by evidencing the relationship between adopting this fusion-based AM technology and green supply chain practices. Also, it provides a set of seven propositions that could be used to theorise the impacts of WAAM adoption on the GSCM performance.

The purpose of this study was to develop a scale that can be used to assess inequality at work based on gender, age and ethnicity that is grounded in Acker’s (2006) inequality regimes.

The authors used three representative samples (total N = 1,806) of Swedish teachers, nurses and social workers to develop and validate the scale. The validation process included the assessment of content validity, confirmatory factor analysis for factorial validity, internal consistency and associations with theoretically warranted outcomes and related constructs to assess criterion-related validity and convergent validity.

The authors found evidence supporting the content, factorial, criterion-related and convergent validity of the InEquality in organisations Scale (InE-S). Furthermore, the scale demonstrated high internal consistency.

The newly developed scale InE-S may be used to further the understanding of how inequality at work influences employees. This study makes a contribution to the current literature by providing a scale that, for the first time, can test Acker’s hypotheses using quantitative methods to demonstrate the consequences of inequality at work.

This research analyses and evaluates the trends and perspectives of climate change in Colombia. This study aims to understand the main ideas and concepts of climate change in five regions of the country by analysing attitudes and values, information habits, institutionalism and the social appropriation of science and technology.

The research study involved a focus group technique. Ten focus groups in five regions of the country, including rural regions, were administered. The selection of cities and municipalities in this study took into account vulnerability scenarios based on the two criteria of temperature and precipitation for the 2011-2040 period.

The participants of the focus groups believe that climate change began 10 years ago and that human activities have caused climate change. The main effects of climate change are believed to be droughts and floods that have appeared in the past several years and have negatively impacted agricultural activities and the quality of life of the population. Moreover, the participants believe that it is important to design and apply adequate measures to adapt to and mitigate climate change.

This study makes an important contribution to the extant climate change literature by identifying and categorising the main ideas and knowledge on this issue from the perspective of the population in Colombia. In developing countries with high climate change vulnerability, it is especially important to analyse this issue to determine relevant official policy instruments that could promote adequate actions and instruments to prevent, adapt to and mitigate climate change.

Olanzapine-induced neutropenia is a rare adverse effect that is currently poorly described in literature. Although neutropenia is a known adverse effect of clozapine, it has been associated with the use of other antipsychotic medications like olanzapine. This case report describes and reviews a case of olanza-pine-induced neutropenia in a schizophrenic patient. Although the mechanism of antipsychotic-induced neutropenia is still debated, this report attempts to discuss current theories as well as supply evidence in literature of this rare but potentially dangerous adverse effect.

This paper aims to analyse residents’ perceptions of tourism growth in Porto prior to the COVID-19 pandemic, aiming to determine the most appropriate strategies to mitigate negative tourism impacts. Studies on resident perceptions of tourism impacts are still scarce, particularly the ones addressing the topic in the context of Portuguese urban tourism areas.

Data was collected through an online survey, focusing on three categories of impacts: (i) economic, (ii) sociocultural (iii) and spatial-environmental, and the respective mitigation strategies, analysed from the perspective of Porto’s residents. Descriptive and bivariate statistics – T-test and Eta correlation – were used to analyse the collected data.

Respondents who live in the city centre experience specific tourism impacts more negatively, when compared to those living outside the inner-city area. Furthermore, no strong correlation is found between the said impacts and the respective mitigation strategies. However, creating awareness among tourists about acceptable behaviour in shared spaces is the strategy that stands out, as it has a medium correlation with all three impact categories. Most impact-strategy associations are weak, meaning that the defined strategies are not the most case-appropriate, which is something that policymakers should address.

To the best of the author’s/authors’ knowledge, this is the first study to adopt this approach in tackling the negative impacts of rapid tourism growth in Porto.

Climate hazards in the form of cyclones are projected to become more intense under the pressures of future climate change. These changes represent a growing hazard to low lying coastal cities like Beira, Mozambique. In 2019, Beira experienced the devastating impact of Cyclone Idai. One of the many impacts resulting from this Cyclone was disrupted drinking water access. This investigation explores the distribution of Cyclone Idai’s impact on drinking water access via an environmental justice lens, exploring how preexisting water access characteristics may have predisposed households to the impacts of Cyclone Idai in Beria.

Relying on household survey data collected in Beira, the investigation applied a decision tree algorithm to investigate how drinking water disruption was distributed across the household survey sample using these preexisting vulnerabilities.

The investigation found that households that mainly relied upon piped water sources and experienced inconsistent access to water in the year prior to Cyclone Idai were more likely to experience disrupted drinking water access immediately after Cyclone Idai. The results indicate that residents in formal areas of Beira, largely reliant upon piped water supply, experienced higher rates of disrupted drinking water access following Cyclone Idai.

These findings question a commonly held assumption that informal areas are more vulnerable to climate hazards, like cyclones, than formal areas of a city. The findings support the inclusion of informal settlements in the design of climate change adaptation strategies.

This paper aims to analyse Barcelona City Council's tourism policy documents to detect how, through the influence of research, different pathways are produced to achieve social impact.

Using the case study approach, a qualitative content analysis is applied to review 31 tourism policy documents of Barcelona City Council.

The results show that the influence of tourism research on Barcelona City Council's policy documents occurs through the following pathways that drive potential social impact: the development of shared research programmes, joint projects, the creation of information exchange platforms, support for academia, the creation of debates, the founding of institutes, the referencing of scientific articles and studies commissioned directly by the City Council from higher education bodies for implementation in the city.

The originality of this paper is to highlight the social relevance of research and to contribute to raising awareness among researchers. The social impact of research is an under-explored topic in the field of tourism. Moreover, there is little research that conducts this analysis through policy documents.

Online education enables location-independent learning, potentially providing university students with more flexible study programs and reducing traffic-related CO₂ emissions. This paper aims to examine whether online education can contribute to university-related sustainable everyday mobility, with particular consideration given to aspects of social sustainability and potential rebound effects. Specifically, it explores sustainability dilemmas that arise from conflicting social and ecological effects.

Drawing on qualitative data from mobility diaries and extensive semistructured interviews (n = 26) collected at Osnabrück University of Applied Sciences in Germany, this study deploys thematic analysis and a typification approach to analyze and classify students’ daily practices related to studying, mobility and dwelling, which may be impacted by online education.

The study identifies six distinct student types with diverse practices in studying, mobility and dwelling. Comparisons between student types reveal stark differences regarding professional and social goals that students associate with their studies, influencing university-related mobility and residential choices. This leads to varying assessments of online education, with some students expecting benefits and others anticipating severe drawbacks.

The typology developed in this paper can assist Higher Education Institutions (HEIs) in comparable contexts in understanding the distinct needs and motivations of students, thereby proactively identifying sustainability dilemmas associated with online education. By leveraging these findings, HEIs can effectively balance diverse interests and contribute meaningfully to sustainability.

To the best of the authors’ knowledge, this study is among the first to systematically investigate conflicts and rebound effects of online education in the context of sustainable mobility within HEIs.

This paper aims to explore the perspectives of university students on the learning management system (LMS) and determine factors that influence user experience and the outcomes of e-learning.

This paper employs a mixed-method approach. For qualitative data, 20 semi-structure interviews were conducted. Moreover, for quantitative data, a short survey was developed and distributed among the potential respondents.

The results showed that students, particularly in programs where courses are mainly offered online, are dependent on such learning platforms. Moreover, the use of modular object-oriented dynamic learning environment (Moodle) as an application of LMS was rated positively, and e-learning was considered as an effective sustainable learning solution in current conditions.

The authors have illustrated empirically how the notion of UX of the LMS provides a means of exploring both students' participation in e-learning and their intention towards using such learning platforms.

In the context of the journey toward digital transformation and the realization of a fully connected factory, concepts such as data science, artificial intelligence (AI), machine learning (ML) and even predictive models emerge as indispensable pillars. Given the relevance of these topics, the present study focused on the analysis of customer complaint data, employing ML techniques to anticipate complaint accountability. The primary objective was to enhance data accessibility, harnessing the potential of ML models to optimize the complaint handling process and thereby positively contribute to data-driven decision-making. This approach aimed not only to reduce the number of units to be analyzed and customer response time but also to underscore the pressing need for a paradigm shift in quality management. The application of AI techniques sought to enhance not only the efficiency of the complaint handling process and data accessibility but also to demonstrate how the integration of these innovative approaches could profoundly transform the way quality is conceived and managed within organizations.

To conduct this study, real customer complaint data from an automotive company was utilized. Our main objective was to highlight the importance of artificial intelligence (AI) techniques in the context of quality. To achieve this, we adopted a methodology consisting of 10 distinct phases: business analysis and understanding; project plan definition; sample definition; data exploration; data processing and pre-processing; feature selection; acquisition of predictive models; evaluation of the models; presentation of the results; and implementation. This methodology was adapted from data mining methodologies referenced in the literature, taking into account the specific reality of the company under study. This ensured that the obtained results were applicable and replicable across different fields, thereby strengthening the relevance and generalizability of our research findings.

The achieved results not only demonstrated the ability of ML models to predict complaint accountability with an accuracy of 64%, but also underscored the significance of the adopted approach within the context of Quality 4.0 (Q4.0). This study served as a proof of concept in complaint analysis, enabling process automation and the development of a guide applicable across various areas of the company. The successful integration of AI techniques and Q4.0 principles highlighted the pressing need to apply concepts of digitization and artificial intelligence in quality management. Furthermore, it emphasized the critical importance of data, its organization, analysis and availability in driving digital transformation and enhancing operational efficiency across all company domains. In summary, this work not only showcased the advancements achieved through ML application but also emphasized the pivotal role of data and digitization in the ongoing evolution of Quality 4.0.

This study presents a significant contribution by exploring complaint data within the organization, an area lacking investigation in real-world contexts, particularly focusing on practical applications. The development of standardized processes for data handling and the application of predictions for classification models not only demonstrated the viability of this approach but also provided a valuable proof of concept for the company. Most importantly, this work was designed to be replicable in other areas of the factory, serving as a fundamental basis for the company’s data scientists. Until then, limited data access and lack of automation in its treatment and analysis represented significant challenges. In the context of Quality 4.0, this study highlights not only the immediate advantages for decision-making and predicting complaint outcomes but also the long-term benefits, including clearer and standardized processes, data-driven decision-making and improved analysis time. Thus, this study not only underscores the importance of data and the application of AI techniques in the era of quality but also fills a knowledge gap by providing an innovative and replicable approach to complaint analysis within the organization. In terms of originality, this article stands out for addressing an underexplored area and providing a tangible and applicable solution for the company, highlighting the intrinsic value of aligning quality with AI and digitization.