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This study aims to examine the moderating role of generational identity in the relationship between user-generated content (UGC) and tourist destination image. It seeks to unveil the differential impact of UGC on the cognitive and affective dimensions of tourist destination image across generational cohorts: Generation Z, Millennials and Generation X.

This study has an experimental design. It used online surveys to gather data from 317 participants recruited through social media channels. Participants were presented with both positive and negative UGC, and their responses were measured using cognitive and affective scales.

This study reveals that UGC significantly affects both the cognitive and affective dimensions of the destination image. However, the impact on the cognitive aspect is moderated by generational differences, with distinct variations observed across Generation Z, Millennials and Generation X. No significant generational moderation was found for the affective dimension, indicating a universal influence of UGC on emotional perceptions of destinations.

The findings suggest that marketers should tailor their communication strategies to the generational characteristics of their target audience, especially concerning the cognitive aspects of destination marketing. However, for affective appeals, a uniform strategy could be applied across generations, simplifying the approach for emotional marketing content.

This research contributes to the extant literature by highlighting the importance of generational segmentation in the strategic marketing of tourism destinations. It extends the discourse to generational analysis, providing a more granular understanding of the interactions between tourists and UGC.

This study aims to identify how the sustainability of Brazilian Federal Institutes of Education, Science and Technology is implemented.

The research is descriptive and quantitative, and questionnaires were used to collect data, which were applied to the campuses and deans of the 38 IFs. The sample selection resulted from a sampling calculation for a finite population, which considered the five Brazilian regions, reaching 248 respondents. To analyze the collected data, descriptive statistics were used to demonstrate the mean, standard deviation (σ) and coefficient of variation of each of the seven axes of the questionnaire and also of the axes and regions jointly; and the sustainability indicator was defined.

A majority of the analyzed FIs were considered to be medium or highly sustainable. The classifications achieved by the FIs demonstrate that sustainability practices are reasonably present in a significant number of campi and Principals’ Offices.

This study contributes by creating a data collection instrument to measure the sustainability practice, not only in educational institutions but also in any type of institution; and the sustainability indicators created, which make it possible to classify organs and entities in accordance with sustainable initiatives implemented by them.

This study’s authors can highlight the mapping of sustainability implementation in the Brazilian Federal Institutes analyzed, which, owing to the sample used, allows for the verification of similarities and differences in these practices between the five Brazilian regions, in addition to making comparisons possible.

This study aims to provide an analysis of teaching the “10 Rs” – Refuse, Rethink, Reduce, Reuse, Repair, Remodel, Remanufacture, Reuse, Recycle and Recover energy, in technological-level undergraduate courses offered in Brazil. Technological undergraduate courses are more dynamic and pragmatic than bachelor’s degrees and aim to meet market demand.

The study collected data from 39 educators who know the reality of technological-level undergraduate courses in Brazil. The data were analyzed using the fuzzy technique for order preference by similarity to ideal solution class technique.

The main findings of the research show potential for improvement in teaching all the “Rs” analyzed when considering technological-level undergraduate courses. Refuse, Restore and Recover energy are the most critical when considering how they should be taught in undergraduate technology courses in Brazil.

The paper’s originality lies in a unique empirical analysis of the circular economy – which is increasingly emerging as an intriguing approach to seeking sustainability in production chains – and the new generation of professionals in technological undergraduate courses who need to be educated and aligned with these concepts. The results can improve the curriculum, syllabus, course objectives and learning outcomes, upgrading the courses’ pedagogical projects.

The authors investigate the impact of the US stock market on the economies of the BRICS and major industrialized economies (G7).

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. Global vector autoregressive (GVAR) empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

The authors summarize the results in four points: (1) financial integration variables increase the effect of the US stock market on the BRICS and G7, (2) the US shock produces similar responses in these groups regarding industrial production, stock markets and confidence but different responses regarding domestic currencies: in the BRICS, the authors detect appreciation of the currencies, while in the G7, the authors find depreciation, (3) G7 stock markets and policy rates are more sensitive to the US shock than the BRICS and (4) the estimates point out to heterogeneities such as the importance of industrial production to the transmission shock in Japan and China, the exchange rate to India, Japan and the UK, the interest rates to the Eurozone and the UK and confidence to Brazil, South Africa and Canada.

The results reinforce the importance of taking into account different levels of economic development.

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. GVAR empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

This paper, based on the 2022 Master Class delivered at the 50th National Economic Meeting organized by ANPEC, discusses how post-Keynesian macroeconomics and New Developmentalism complement each other to understand middle-income economies' development in financial globalization. It summarizes my academic reflection about the advance in post-Keynesian thinking to develop macroeconomics for peripheral middle-income economies.

As part of this reflection, I first bring up the idea of a developmental convention and, next, how peripheral financialization impacts the elaboration of this convention. Given the asymmetric configuration of the international financial system and the context of hierarchical currencies, I discuss the challenge of overcoming underdevelopment in peripheral economies. The post-Keynesian macroeconomics and advances in the structuralist debate provide the analytical tools to understand how peripheral economies develop virtuous or vicious growth cycles. At the end of the paper, I present some comments on the stagnation of the Brazilian economy.

The growth strategy with foreign savings does not provide the conditions for middle-income economies to operate with sufficient economic policy autonomy to promote productive transformation. To this end, a developmental convention should replace the neoliberal convention that has dominated since the 1970s.

The dynamics of peripheral, middle-income economies, often influenced by international liquidity flows, are a crucial area of study. This research underscores the importance of understanding these dynamics, as it forms the basis for economic policy recommendations. The paper also highlights the inadequacy of the growth strategy with foreign savings in the current configuration of the international financial system, emphasizing the need for middle-income economies to operate with greater economic policy autonomy to foster productive transformation.

Digital sustainable maturity (DSM) is an important factor for gaining a competitive advantage. However, the literature on this topic is scarce. This study was designed to understand and formalize the concept of DSM and investigate models for measuring it in the context of supply chains.

To this end, a systematic literature review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) tool, whose steps and evaluation criteria resulted in a portfolio of 87 articles. These were analyzed based on pre-established criteria from the literature on scope, design and application.

The results revealed an emerging field, but with the domain of DSM still underexplored. No formal concept of DSM was found in the literature. Thus, this paper presents the first definition in the field, which can be understood as the organization’s dynamic capability to leverage its digital assets to promote sustainable performance in economic, environmental and social dimensions. Regarding the analyzed models, 72 maturity models were identified considering both domains. However, only nine of them provided a model for evaluating DSM. Overall, the models presented varied architectures, which made it impossible to determine a consistent approach for measuring maturity in this domain.

This study is original as it systematically integrated digital and sustainable constructs to measure maturity. Furthermore, it formalizes the concept of DSM, which was not found in the existing literature.

This study analysed students’ perceptions of teachers’ behaviours, teachers’ management practices and the use of inputs by teachers and whether these are associated with primary school progression and completion.

School-level fixed effect analysis is conducted using cross-sectional data collected from 4,000 randomly selected primary school-aged students and their schools.

Our findings reveal that students’ perceptions of teachers’ behaviours are associated with the probability of grade progression during primary school, and whether students complete primary school. Particularly important are positive behaviours, like students perceiving their teachers to be engaged and being praised by their teachers while in primary schools. It increased the likelihood of school progression by at least 15%. The use of inputs such as worksheets/written handouts and reading stories/books in the language of instruction were also found to have a statistically significant positive effect on students’ primary school performance. These are important results which hold after accounting for school management, household and child-level factors and regional differences.

Our findings provide a deeper understanding of the teaching practices which pupils perceive as beneficial to retention. While we are unable to conclude that learning is taking place, our contention is that greater time in school could increase the opportunity to learn. In this respect, beyond its policy relevance in improving educational outcomes, the paper contributes to the limited literature on the student–teacher classroom relationships particularly when looking from the perspective of students’ perception of their teachers’ teaching behaviours in developing countries.

This study aims to promote the preservation of endangered traditional knowledge and practices in the Andes of Peru by documenting, publishing and disseminating them.

Based on a literature review of coca and coca divination, the author will describe these types of divination practices. Subsequently, the author will address the context and characteristics of a coca reading conducted in October 2022. Afterwards, the threats and prejudices faced by this type of indigenous knowledge and practice are discussed.

Coca divination in the Andean region of Ancash differs from the most common form of divination with coca leaves performed in northern Argentina, Bolivia, northern Chile, Colombia and southern Peru. The results of the coca reading conducted in October 2022 align with Andean worldviews. These practices and the associated episteme face various threats from academic, social and political actors and their discourses.

Scientific and academic researchers should be aware that their work can foster and maintain epistemic colonialism in Latin American territories. Archaeological excavations and interpretations should respect ancestral and traditional worldviews and practices.

This study advances the understanding of coca divination in the Andes of Ancash, Peru, by providing nuanced insights into this cultural practice in relation to a landslide event that occurred near a 3,000-year-old temple. The implications extend beyond academic discourse, offering valuable perspectives for conducting archaeological excavation activities that respect ancestral and traditional local beliefs. Future research should build on these findings to deepen comprehension of threats to traditional beliefs and practices.

Artificial intelligence (AI) has been touted as one of the viable solutions to address urban mobility issues. Despite a growing body of research on AI across various sectors, its use in the mobility sector remains underexplored. This study addresses this limitation by investigating AI applications and identifying the AI material properties and use cases that offer mobility-specific affordances.

Although AI applications in mobility are growing, academic research on the subject has yet to catch up. Therefore, we follow a systematic review and analysis of practitioner literature. We conducted a comprehensive search for relevant documents through Advanced Google and OECD databases and identified 173 sources. We selected 40 sources published between 2015 and 2022 and analysed the corpus of evidence through abductive qualitative analysis technique.

The analysis reveals that mobility organisations are implementing various AI technologies and systems such as cameras, sensors, IoT, computer vision, natural language processing, robotic process automation, machine learning, deep learning and neural networks. These technologies offer material properties for sensing mobility objects and events, comprehending mobility data, automating mobility activities and learning from mobility data. By exploiting these material properties, mobility organisations are integrating urban mobility management, personalising and automating urban mobility, enabling the smartification of infrastructure and asset management, developing better urban transport planning and management, and enabling automatic driving.

The study contributes a mid-range theory of the affordances of AI for mobility (AI4M) at the infrastructure, operation and service levels. This contribution extends the existing understanding of AI and offers an interconnected perspective of AI affordances for further research. For practitioners, the study provides insights on how to explore AI in alignment with organisational goals to collectively transform urban mobility to be affordable, efficient and sustainable.