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This paper aims to determine whether policy uncertainty caused by institutional decay in countries with populist rulers influences the internationalization decision of emerging market firms (EMFs).

The study used binary logit analysis on firms from Latin American countries undertaking cross-border greenfield investment projects.

The results suggest that internationalization decision is demotivated by policy uncertainty generated by populist chief executives and promoted by that of political parties.

This study uses populist rhetoric to describe policy uncertainty due to chief executives and ruling parties, which influences internationalization decision by increasing anticipated transaction costs. This inquiry identifies populism as a variable that influences EMFs to internationalize, while empirically testing the claim of theoretical scholarship that populism reconfigured the sociopolitical and institutional forces that shape the world’s business. This study further advances institutional theory by offering a fresh perspective on the influence of home instead of host-country institutions on the internationalization motivation of firms due to institutional decay caused by populist regimes.

The objective of this research is to propose a framework which is apt to assess how a nation branding campaign could promote cultural identity by ultimately curbing political polarization.

By relying on a multidisciplinary approach that blends theoretical constructs from different fields the methodology is based on a mixed-method approach whereby the qualitative data stemming from a set of interviews with key-informants is coupled by a survey of Colombian citizens in order to gain in-depth insights over the impact of nation branding on political polarization.

From the findings, it emerges that a campaign based on nation branding and targeting domestic citizens could curb political polarization within Colombia, by also fostering cultural identity.

The study considers only Colombia. To fully assess the robustness of the framework it would be useful to extend the analysis to a broader range of countries and to a wider set of domestic issues.

The research not only provides in-depth insights on how nation branding can be used effectively in order to curb political polarization but also practical guidance on how a nation branding campaign can be effectively designed. The findings are relevant to policy-makers that have the opportunity to implement informed and educated nation branding campaigns not just overseas, but also to strategically address important domestic issues by engaging the domestic stakeholders.

While country branding has been extensively investigated within the context of international business, we have a relatively limited understanding of its domestic impact. In contrast to traditional country branding literature, this paper aims to theoretically advance our understanding of nation branding and its effect on political polarization, as well as gauging its impact on cultural identity.

This study aims to provide a new perspective on the factors determining a country’s tourism performance, understand the interrelationships among these factors and explore their implications for the future of tourism in high-income countries.

The study employs a fuzzy-set qualitative comparative analysis (fsQCA) using five variables from the World Economic Forum’s Travel and Tourism Development Index (TTDI). The focus is on identifying seven configurations of antecedents of Travel and Tourism Industry Gross Domestic Product (T&T Industry GDP).

The study identifies seven configurations of antecedents influencing T&T Industry GDP, revealing how these factors operate in different scenarios, specifically in countries with high and low T&T GDP. These configurations offer insights into potential future pathways for tourism development.

The study implies that tourism is a complex phenomenon influenced by multiple interacting factors. It provides a framework for understanding how different combinations of factors can lead to high or low tourism performance, offering valuable insights for anticipating and shaping the future of tourism.

This study adds value by providing a more nuanced understanding of the tourism industry, challenging the notion of singular effects of variables and highlighting the importance of analyzing multiple, interacting factors in understanding and predicting tourism performance. It contributes to the field of futures studies by offering a tool for anticipating potential future scenarios and their impact on the tourism industry.

This paper studies the interactive valuation discourses of an online user community (transfermarkt.de) that seeks to determine market values for soccer players. Despite their seemingly casual nature, these values have featured in newspapers, transfer negotiations, academic research, and capital market communication – and have thus become reified.

The paper employs netnographic research methodology to collect and thematically analyze a wide range of user entries on the platform. These entries are studied using theoretical insights from the sociology of quantification and valuation.

The analysis reveals how values are constructed in constant interaction between value-proposing users and value-justifying “experts.” This dynamic form of relational valuation positions players relative to one another as well as to actual transactions on the transfer market. In the absence of authoritative guidelines, it is this possibility and affordance for interaction that enacts a coherent valuation regime. The paper further reveals the platform's response to a disruptive event, which risked bringing the user-expert dynamics to a halt, requiring intervention from the platform to repair its valuation frame.

The paper responds to increased scholarly interests in the valuation of professional athletes. It contributes to the extant literature on valuation, first, by analyzing the dynamic valuation work that feeds into the social construction of values and, second, by studying platform participation and user interaction in a socially engineered online space.

The purpose of this paper is to examine the politics involved in local struggles against forestry extractivism. The forestry sector is dependent on vast areas of land for tree plantations. This creates deep-rooted conflicts between global corporations that seek access to natural resources and locals whose way of life requires the use of the same land.

This study draws on a political ontology frame of reference and storytelling methodology to build on testimonies of three small-scale farmers who actively seek to resist forestry plantations next to their land in rural Uruguay. The stories reveal the impossibilities they face when raising claims in the public political sphere and how they lack the means to organise strong collective resistance.

One of the testimonies reveals how the farmers engage in a form of “politics of place” (Escobar, 2001, 2008) to counter the power of the proponents of forestry and the further expansion of plantations. This form of politics strengthens and politicises the ontological difference between extractive and non-extractive worlds. The farmers seek to build new imaginations of rural living and sustainable futures without the presence of extractive corporations. They fulfil this aim by designing community projects that aim to revitalise ancient indigenous legends, set up agro-ecological farms, and teach schoolchildren about the environment.

The struggles of the farmers indicate the territorial transformations involved in (un)making (non)extractive places and the need to expand the analysis of the politics involved in struggles against extractivism beyond social struggles.

Students pursuing different professional courses at the higher education level during 2021–2022 saw the first-time occurrence of a pandemic in the form of coronavirus disease 2019 (COVID-19), and their mental health was affected. Many works are available in the literature to assess mental health severity. However, it is necessary to identify the affected students early for effective treatment.

Predictive analytics, a part of machine learning (ML), helps with early identification based on mental health severity levels to aid clinical psychologists. As a case study, engineering and medical course students were comparatively analysed in this work as they have rich course content and a stricter evaluation process than other streams. The methodology includes an online survey that obtains demographic details, academic qualifications, family details, etc. and anxiety and depression questions using the Hospital Anxiety and Depression Scale (HADS). The responses acquired through social media networks are analysed using ML algorithms – support vector machines (SVMs) (robust handling of health information) and J48 decision tree (DT) (interpretability/comprehensibility). Also, random forest is used to identify the predictors for anxiety and depression.

The results show that the support vector classifier produces outperforming results with classification accuracy of 100%, 1.0 precision and 1.0 recall, followed by the J48 DT classifier with 96%. It was found that medical students are affected by anxiety and depression marginally more when compared with engineering students.

The entire work is dependent on the social media-displayed online questionnaire, and the participants were not met in person. This indicates that the response rate could not be evaluated appropriately. Due to the medical restrictions imposed by COVID-19, which remain in effect in 2022, this is the only method found to collect primary data from college students. Additionally, students self-selected themselves to participate in this survey, which raises the possibility of selection bias.

The responses acquired through social media networks are analysed using ML algorithms. This will be a big support for understanding the mental issues of the students due to COVID-19 and can taking appropriate actions to rectify them. This will improve the quality of the learning process in higher education in Oman.

Furthermore, this study aims to provide recommendations for mental health screening as a regular practice in educational institutions to identify undetected students.

Comparing the mental health issues of two professional course students is the novelty of this work. This is needed because both studies require practical learning, long hours of work, etc.

The goal was to improve the quality of the hospitalization process and the management of patients, allowing the reduction of costs and the minimization of the preoperative Length of Hospital Stay (LOS).

The methodology used to improve the quality of the hospitalization process and patient management was Lean Thinking. Therefore, the Lean tools (Value stream map and Ishikawa diagram) were used to identify waste and inefficiencies, improving the process with the implementation of corrective actions. The data was collected through personal observations, patient interviews, brainstorming and from printed medical records of 151 patients undergoing oral cancer surgery in the period from 2006 to 2018.

The authors identified, through Value Stream Map, waste and inefficiencies during preoperative activities, consequently influencing preoperative LOS, considered the best performance indicator. The main causes were identified through the Ishikawa diagram, allowing reflection on possible solutions. The main corrective action was the introduction of the pre-hospitalization service. A comparative statistical analysis showed the significance of the solutions implemented. The average preoperative LOS decreased from 4.90 to 3.80 days (−22.40%) with a p-value of 0.001.

The methodology allowed to highlight the improvement of the patient hospitalization process with the introduction of the pre-hospitalization service. Therefore, by adopting the culture of continuous improvement, the flow of hospitalization was redrawn. The benefits of the solutions implemented are addressed to the patient in terms of lower LOS and greater service satisfaction and to the hospital for lower patient management costs and improved process quality. This article will be useful for those who need examples on how to apply Lean tools in healthcare.