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The creation of intercultural education in the Quechua and Mapuche contexts, in Peru and Chile respectively, marks a milestone in the institutionalisation of equity-oriented state policies that deserves attention given the serious inequalities that still persist in these societies. In this chapter, we analyse ethnographic studies of intercultural knowledge and practices inside and outside the classroom and interpret them as catalysts for equity in education. The findings of the analysis point to the centrality of Indigenous actors as transformative agents inside and outside the classroom and the urgency of restructuring not only education but also society towards equity.

This paper aims to address what it means to brand a city as “smart”. In other words, what ideas, understandings and actions are mobilized by the discourse of smart cities in a particular context.

Taking a brand interpretive approach, this paper uses deconstructive criticism to understand the performativity of smart cities within the Brazilian Charter for Smart Cities and to expose hegemonic power structures and the various colonizations that disenfranchise consumers and citizens of the Global South.

This paper finds that the branding of smart cities within the Brazilian Charter for Smart Cities is largely performative and rhetorical in nature. The authors identify those dimensions of the smart city that are materialized by this branding performance. For example, the authors identify how the Charter calls forth issues around technological solutionism, sustainability and social inclusion. At the same time, the analysis draws attention to the dimensions of smart cities that are disguised by such performances.

The implications of the work suggest that the authors need to understand the designation “smart city” as a branding performance. More research is required in context to determine in exactly what ways smart city projects are being implemented.

Rather than adhering only to the rhetoric of smartness, cities have to work hard to make smartness a reality – a smartness constructed not just on technical solutions but also on human solutions. That is, the complexity of urban issues that are apparently addressed in the move to smartness demand more than a technological fix.

The research offers a novel lens through which to view smart cities.

A review of the literature provides a solid reason to believe that an increase in environmental, social and corporate governance (ESG) activities have a positive impact on banks’ default risk (DR). However, the increasing impact of climate risk on credit, operational and market risks, as well as the reduced availability of funding for banks that underperform in terms of ESG risk, is a concern. Therefore, the purpose of this study is to verify the relevance of the implementation of ESG policies to a bank’s DR, against the background of macroeconomic and bank-specific factors.

Using a data set of 303 commercial banks from 61 countries from 2012 to 2021 and a panel regression methodology, the empirical importance of ESG activities for bank DR is documented. The two-stage generalized method of moments estimator was used to test the research questions.

Comparing different factors, the results highlight the positive impact of ESG activities on the bank’s DR. However, this relationship varies according to the specific pillars of the bank’s sustainability policies and changes into negative ones.

This paper fits the domain of DR management research, investigating whether ESG performance affects bank DR while controlling macroeconomic and market drivers. Prior literature has shown evidence on the relationship between macro and market forces and a bank’s risk profile while a limited one on the non-market drivers. The main contribution is to consider ESG (in total and as separate pillars) as independent drivers of the bank risk profile.

This paper argues that past events of queer resistance – such as the Stonewall Riots in 1969 in New York – need to be critically inquired for their meaningful legacy and future potentiality through remembering and re-experiencing these events affectively. Considering the recent backlash against LGBTQI+ people, the paper underlines the importance of a nuanced understanding and affective remembering of historic events like the Stonewall riots for contemporary queer activism and scholarship.

The study engages with the analysis of a new opera production commissioned by the New York City Opera at the occasion of the 50th anniversary of the Stonewall riots. The focus of this uprise at and around the Stonewall Inn is seen as an emblematic event synonymous with what was then called “gay” liberation and forms a significant moment of collective troublemaking in queer history. Operas like other cultural performances are considered as forms of queer worldmaking, which can be analyzed as an evolving stream of ambivalent affect and minor feelings.

The paper offers an affective analysis of the performance of the opera “Stonewall.” First, the analysis provides a sketch of how individual storylines struggling with the ambivalence between daily humiliation and sexual longing assemble into a collective affective complex that layered the intensity of the uprising. Second, the analysis documents how the Stonewall-opera “re-members” the intersectional composition of these ambivalent affects to counter the tendency to mainstream queer history.

The paper’s writing illustrates how the collective organizing of queer resistance can be advanced through exploring such unusual aesthetic realms like queer opera, as it connects troublemaking politics with affective activism, the reviving of affective moments in queer history. It underlines the potential of queer opera and other cultural, popular productions to feel and live the intensity and energy of reimagining and realizing queer worldmaking.

The present study aims to identify the practices employed to bring heirs into family businesses as successors.

We conducted an exploratory, qualitative investigation using a case study approach. Semi-structured face-to-face interviews were conducted with external consultants and with incumbent leaders, next-generation heirs working in the firm (and likely to become successors) and employees from three family firms from different industries and under ownership and control of different generations of their respective families (first, second and third and fourth generations). In addition to surveying their general perceptions of the succession processes in their firms, each informant was asked to rate the degree of importance of 12 succession practices identified in the literature and the extent to which they exist in their respective firms.

Our results showed that heirs typically enter the family business after a development process outside of the family business, which we have termed as coming back to the nest. This process was enacted through practices that we allocated to the following categories: continued development of heirs, developing relationships in the succession process, separation of roles and attitude of the successor heirs. Overall, 8 of the 12 practices derived from the theoretical framework were endorsed as important by representatives of the family businesses and 9 were endorsed by the consultants, 7 of which coincided in both groups. However, only 5 of the practices were identified as present in the firms’ succession processes by the representatives of the family businesses, while the consultants did not identify any of the 12 practices as present.

We present additional important practices, the adoption of which would be beneficial for family business succession, such as adapting external learning to the family business, acquiring leadership skills and experience and developing emotional intelligence. Our study advances the prior literature since we do not merely discuss succession planning but analyze in an applied manner how succession actually takes place in family businesses.

This paper aims to evaluate the measurement properties of the Employee Perception to Assess the Lean Implementation Tool (EPLIT) in the Brazilian hospital context.

A cross-sectional study was conducted in two Brazilian hospitals, adhering to COnsensus-based Standards for the selection of health Measurement Instruments (COSMIN) guidelines. Exploratory factor analysis (EFA) and Cronbach's alpha were used for construct validity and reliability.

The adapted tool comprises 27 items across five domains, explaining 63.3% of the variance. Cronbach's alpha ranged from 0.78 to 0.86, indicating satisfactory reliability.

Limitations include convenience sampling and exclusive use of EFA for validation. Future studies may employ Confirmatory Factor Analysis for further validation.

The tool aids healthcare managers in Brazil to systematically evaluate Lean implementation, contributing to process optimization and quality improvement.

Effective Lean implementation using the validated tool could lead to improved healthcare delivery and patient outcomes.

This is the first study to adapt and validate EPLIT for the Brazilian healthcare sector, offering a robust tool for managers and researchers.

Building an open data ecosystem is a long-term process during which it is necessary to collect feedback so that its development corresponds to the preferences and needs of users. The purpose of this paper is to provide findings and recommendations on how the intentions to use of Open Government Data (OGD) and OGD portals by Czech students evolved over the three years period from 2021 to 2023.

A mixed research approach was used to conduct the research study and to collect input data. A methodology followed the behavioural intention-based analysis using the model developed by Lnenicka et al. (2022) to analyse relationships between respective constructs and test the hypotheses. Each cycle of data collection using structured questionnaires was supplemented with semi-structured interviews to get students’ feedback on the findings.

The findings revealed that intentions to use of OGD and OGD portals by Czech students slightly decrease every year. Although students believe that using OGD is beneficial, can increase their performance and productivity, as well as they are influenced by other people to try to (re)use OGD, they miss concrete support above their daily activities in which they could use OGD. Therefore, we provided recommendations to improve their (re)use such as linking OGD with life events to show their usefulness for concrete life situations and activities.

The study provides insights into how intentions to use of OGD and OGD portals among Czech students evolved over the years and what should be the actions to consider improving the level of use. It provides governments on all administrative levels the recommendations for further improvements and actions to promote and stimulate the (re)use of OGD by students as well as other stakeholders.

Integrated marketing communication (IMC) is a management tool that accompanies market dynamics, business environment and technological transformations and can become a competitive differential for organizations that use it. This study’s aim is to propose that IMC can be a strategic tool in the context of geographical indication (GI).

Exploratory research was conducted with a qualitative approach through an integrated unique case study, including bibliographic, documentary research, direct observation and in-depth semi-structured interviews. The case chosen was the GI of Matas de Rondônia coffee, located in the Amazonia biome, which is the first denomination in the world of the sustainable Coffea canephora species and, to date, Brazil’s only GI to include indigenous lands.

It was possible to confirm all propositions, and obtain theoretical, practical and public management contributions.

This research brings unpublished theoretical contributions, when presenting IMC as a strategic tool for GI, fills gaps and increases the literature in the areas of marketing, communication, food marketing and GI.

This paper proposes a multicriteria model for risk management to identify and assess risks associated with an integrated management system (IMS). The main benefit of the proposed model is its systemic and logical visualization, which may facilitate the understanding of this proposal’s practical application.

The research design consists of four stages: (1) conduct a literature review to establish risk management models in IMS; (2) collect data concerning risk management models in IMS from a large multinational automotive company; (3) propose a multicriteria model to define and assess risks as well as prioritize mitigation actions and (4) apply the proposed multicriteria model to the data collected in case-based research to evaluate the practical viability of the model to contribute to methods traditionally used.

The results showed that the proposed risk management model contributes to more reliable decision-making in an IMS. The application of the proposed model identified 85 risks in the total processes of the IMS, 31 of which were classified as high risk; thus, priority actions to be taken were defined. The risk classification and prioritization facilitated the implementation of measures to mitigate or eliminate risks, as pointed out by the company managers.

One of the limitations is the fact that specific knowledge is required to maintain and update the multicriteria decision-making tool used in this study. Another one implies the approach to managing risks under the different ISO standards and sector-specific requirements, since this may require updates and customization of the proposed risk management model.

The implementation of IMS in contemporary business environments can be supported by a robust risk management approach. In addition, it provides the leadership with a holistic view of multiple aspects related to a company and fosters continuous improvement.

The social implications of this study are assessed indirectly. This study contributes to the improvement of company management models.

Traditionally, the methods used for risk management in IMS are usually applied independently of techniques such as failure mode and effect analysis. The model developed in this work enables to manage risks continuously to achieve a systemic view of organizational issues and greater transparency of the processes.

Social media platforms that disseminate scientific information to the public during the COVID-19 pandemic highlighted the importance of the topic of scientific communication. Content creators in the field, as well as researchers who study the impact of scientific information online, are interested in how people react to these information resources and how they judge them. This study aims to devise a framework for extracting large social media datasets and find specific feedback to content delivery, enabling scientific content creators to gain insights into how the public perceives scientific information.

To collect public reactions to scientific information, the study focused on Twitter users who are doctors, researchers, science communicators or representatives of research institutes, and processed their replies for two years from the start of the pandemic. The study aimed in developing a solution powered by topic modeling enhanced by manual validation and other machine learning techniques, such as word embeddings, that is capable of filtering massive social media datasets in search of documents related to reactions to scientific communication. The architecture developed in this paper can be replicated for finding any documents related to niche topics in social media data. As a final step of our framework, we also fine-tuned a large language model to be able to perform the classification task with even more accuracy, forgoing the need of more human validation after the first step.

We provided a framework capable of receiving a large document dataset, and, with the help of with a small degree of human validation at different stages, is able to filter out documents within the corpus that are relevant to a very underrepresented niche theme inside the database, with much higher precision than traditional state-of-the-art machine learning algorithms. Performance was improved even further by the fine-tuning of a large language model based on BERT, which would allow for the use of such model to classify even larger unseen datasets in search of reactions to scientific communication without the need for further manual validation or topic modeling.

The challenges of scientific communication are even higher with the rampant increase of misinformation in social media, and the difficulty of competing in a saturated attention economy of the social media landscape. Our study aimed at creating a solution that could be used by scientific content creators to better locate and understand constructive feedback toward their content and how it is received, which can be hidden as a minor subject between hundreds of thousands of comments. By leveraging an ensemble of techniques ranging from heuristics to state-of-the-art machine learning algorithms, we created a framework that is able to detect texts related to very niche subjects in very large datasets, with just a small amount of examples of texts related to the subject being given as input.

With this tool, scientific content creators can sift through their social media following and quickly understand how to adapt their content to their current user’s needs and standards of content consumption.

This study aimed to find reactions to scientific communication in social media. We applied three methods with human intervention and compared their performance. This study shows for the first time, the topics of interest which were discussed in Brazil during the COVID-19 pandemic.