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The pandemic has enhanced the global phenomenon of disinformation. This paper aims to study the false news concerning COVID-19, spread through social media in Spain, by using the LatamChequea database for a duration from 01/22/2020, when the first false information has been detected, up to 03/09/2021.

A quantitative analysis has been conducted with regard to the correlation between fake news stories and the pandemic state, the motive to share them, their dissemination in other countries and the effectiveness of fact checking. This study is complemented by a qualitative method: a focus group conducted with representatives of different groups within the society.

Fake news has been primarily disseminated through several social networks at the same time, with two peaks taking place in over a half of the said false stories. The first took place from March to April of 2020 during complete lockdown, and we were informed of prevention measures, the country’s situation and the origin of the virus, whereas the second was related to news revolving around the coming vaccines, which occurred between October and November. The audience tends to neither cross-check the information received nor report fake news to competent authorities, and fact-checking methods fail to stop their spread. Further awareness and digital literacy campaigns are thus required in addition to more involvement from governments and technological platforms.

The main limitation of the research is the fact that it was only possible to conduct a focus group of five individuals who do not belong to generation Z due to the restrictions imposed by the pandemic, although a clear contribution to the analysis of the impact of fake news on social networks during the COVID-19 pandemic in Spain can be seen from the privileged experiences in each of the fields of work that were identified. In this sense, the results of the study are not generalizable to a larger population. On the other hand, and with a view to future research, it would be advisable to carry out a more specific study of how fake news affects generation Z.

This research is original in nature, and the findings of this study are valuable for business practitioners and scholars, brand marketers, social media platform owners, opinion leaders and policymakers.

This study aims to perform a benefit segmentation and then a classification of visitors that travel to the Rocha Department in Uruguay from the capital city of Montevideo during the summer months.

A convenience sample was obtained with an online survey. A total of 290 cases were usable for subsequent data analysis. The following statistical techniques were used: hierarchical cluster analysis, K-means cluster analysis, machine learning, support vector machines, random forest and logistic regression.

Visitors that travel to the Rocha Department from Montevideo can be classified into four distinct clusters. Clusters are labelled as “entertainment seekers”, “Rocha followers”, “relax and activities seekers” and “active tourists”. The support vector machine model achieved the best classification results.

Implications for destination marketers who cater to young visitors are discussed. Destination marketers should determine an optimal level of resource allocation and destination management activities that compare both present costs and discounted potential future income of the different target markets. Surveying non-residents was not possible. Future work should sample tourists from abroad.

The combination of market segmentation of Rocha Department’s visitors from the city of Montevideo and classification of sampled individuals training various machine learning classifiers would allow Rocha’s destination marketers determine the belonging of an unsampled individual into one of the already obtained four clusters, enhancing marketing promotion for targeted offers.

Gender equality plans (GEPs) are currently the preferred approach to initiate structural change towards gender equality in research organisations. In order to achieve structural change, GEPs have to be more than just a formally adopted institutional policy. Effective GEPs lead to a transformation of gendered practices and thus to structural change. This chapter presents the innovative approach developed for an H2020 structural change project and its theoretical background. We argue that due to the dual logic, which characterises academic organisations, the organisational logic and the academic logic, change is a complex endeavour. To deal with this complexity, one of the main functions of a GEP is to provide space and initiate reflexivity at an individual as well as at an institutional level. A theory of change approach supports reflexivity in all stages of a GEP as it ensures that basic assumptions of the institutional change process are questioned and reflected on by the different stakeholder groups involved in the implementation.

The TARGET approach aims at establishing a reflexive gender equality policy in research performing and research funding organisations. Monitoring has enormous potential to support reflexivity at both the institutional and the individual levels in the gender equality plan (GEP) development and implementation context. To exploit this potential, the monitoring system has to consist of meaningful indicators, which adequately represent the complex construct of gender equality and refer to the concrete objectives and policies of the GEP. To achieve this, we propose an approach to indicator development that refers to a theory of change for the GEP and its policies. Indicator development thus becomes a reflexive endeavour and monitoring a living tool. This requires constant reflection on data gaps, validity of indicators and the further development of indicators. Furthermore, we recommend the creation of space for reflexivity to discuss monitoring results with the community of practice.