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Using sentiment analysis (SA), this study aims to examine the impact of COVID-19 on mental health and virtual learning experiences among 1,125 students at a public Argentinean faculty.

A study was conducted during the COVID-19 pandemic, surveying 1,125 students to gather their opinions. The survey data was analysed using text mining tools and SA. SA was used to extract the students’ emotions, views and feelings computationally and identify co-occurrences and patterns in related words. The study also examines educational policies implemented after the pandemic.

The prevalent emotions expressed in the comments were trust, sadness, anticipation and fear. A combination of trust and fear resulted in submission. Negative comments often included the words “virtual”, “virtual classroom”, “virtual classes” and “professor”. Two significant issues were identified: teachers’ inexperience with virtual classes and inadequate server infrastructure, leading to frequent crashes. The most effective educational policies addressed vital issues related to the “virtual classroom”.

Text mining and SA are valuable tools for decision-making during uncertain times, such as the COVID-19 pandemic. They can also provide insights to recover quality assurance processes at universities impacted by health concerns or external shocks.

The paper makes two main contributions: it conducts a SA to gain insights from comments and analyses the relationship between emotions and sentiments to identify optimal educational policies. The study pioneers exploring the link between emotions, policies and the pandemic at a public university in Argentina. This area of research still needs to be explored.

The authors extend research suggesting that external funders reduce their contributions to not-for-profit (NFP) organizations in response to media-reported CEO compensation levels.

Employing a maximum archival sample of 44,807 observations from US Form 990s, the authors comprehensively assess the extent that high relative NFP CEO compensation is associated with decreases in future contributions.

The authors find that donors and grantors react negatively to high relative CEO compensation but do not react adversely to high absolute executive compensation. Contributors seem to take issue with CEO compensation when they perceive it absorbs a relatively large portion of the organizations’ total expenses, which may hinder the NFP’s mission. Additional findings suggest that excess cash held by the NFP significantly exacerbates the negative baseline relationship between future contributions and high relative CEO compensation. Finally, both individual donors and professional grantors are sensitive to cash NFP CEO compensation levels, but grantors are more sensitive to CEO noncash compensation.

The authors’ data are focused on larger NFP organizations, so this limits the generalizability of the study. Furthermore, survivorship bias potentially influences their time-series investigations because a current year large-scale decrease in funding due to high relative CEO compensation may cause some NFP firms to drop out of the sample the following year due to significant funding reductions.

The study makes three noteworthy contributions to the literature. First, the study documents that the negative association between high relative CEO compensation levels and future donor and grantor contributions is much more widespread than previous literature suggested. Second, the authors document that high relative CEO compensation levels that trigger reductions in future contributions are significantly exacerbated by excess cash held by the NFP. Finally, the authors find that more sophisticated grantors are more sensitive to noncash CEO compensation levels as compared with donors.

The main purpose of this paper is to analyse the impact of the intellectual capital (IC) on the competitiveness in the manufacturing small- and medium-sized enterprises (SMEs) in Mexico.

The approach of this investigation is developing a theoretical construct to determine the correlation between IC and competitiveness and find the most relevant factors that impact it, where IC is independent variable and the competitiveness is dependant variable. Using the Likert scale to determine the degree of agreement or disagreement, the survey was applied to 420 SMEs. The results were analysed using confirmatory factor analysis, Cronbach’s alpha and subsequently structural equation models.

The results show that the IC dimensions – the information obtained, IC developed and learning and feedback – have an effect on the competitiveness of SMEs. The paper presents the theoretical validation of the factors that impact on IC and competitiveness and hence they are the key elements that impact mostly on each analysed variable.

The results obtained measure the level of correlation between the variables in the study, helping to design strategies for the key factors needed to integrate the IC and to develop competitive synergies in the manufacturing SMEs.

This study shows the effects of the IC that are directly impacting the competitiveness of SMEs so that each factor of the dependent and independent variables should be analysed separately to propose improvements in implementing IC to seek higher level of competitiveness.

The purpose of this paper is to develop an approach to optimize the cycles‐to‐failure of a peened component with respect to laser peening (LP) variables: pressure magnitude, mid‐span, and spot size when the component is subject to a variable amplitude loading.

To optimally design an LP process, an experimentally validated 3D finite element simulation of the LP process, a cycles‐to‐failure estimation capability incorporating residual stress, and a particle swarm optimization strategy were developed and employed to maximize the cycles‐to‐failure of a component of a titanium turbine disk.

The most critical finding of this research is that a minor difference in the residual stress profile can lead to a large difference in the cycles‐to‐failure. This finding implies that selecting the optimization objective to be the cycles‐to‐failure is a better option as compared to the residual stress profile.

The LP‐induced residual stresses are assumed static and do not change as number of load cycles increase.

The paper develops a framework that relates the LP variables and the cycles‐to‐failure of a peened component. A modified particle swarm optimization approach is developed to optimize the fatigue life of a turbine disk.

Students of tourism have long recognized the Caribbean area as a popular tourist objective. The visitors have come primarily from North America; as Burkart and Medlik ob‐served, “…the principal tourist reception areas in the world lie up to about 1,000 miles or so from the generating source or, to put it another way, at about two hours flying time”. The Caribbean's large and expanding tourist trade may be attributed to, in addition to this obviously significant factor of proximity, the physical geographic factors of tropical climate, sandy beaches and varied topography. The Caribbean's cultural geographic assets include its diversity of colonial heritage and its variety of racial and ethnic populations. The unique economic and social situation of this region of the world, together with the continuing role of the U. S. as a prime generating source, will probably result in continued encouragement of and catering to this impressive tourist trade. Of particular note to students of tourism is the rising volume of cruiseship traffic within the Caribbean. This aspect of tourist trade illustrates some significant interrelationships of transport and tourism. This study's objectives are the analysis and interpretation of contemporary cruise‐ship traffic patterns, specifically in terms of studying the relationships which are apparent among various ports of origin and their related ports of call.

The aim of the study is to conduct a thematic review of assessment tools and types of activities in the application of robotics to autistic students during the period 1996–2021 using Web of Science and Scopus. The sample consisted of 119 documents.

Nowadays, emerging technologies have become increasingly prevalent across various fields of knowledge. In this regard, robotics is being increasingly applied in the educational environment. The characteristics of this tool are the ones that best suit the needs of autistic students.

Results reveal that 16.80% of the studies used automatic measurement systems, whilst 15.96% of the studies used user observation and recording techniques. As for the tasks, 37.80% were focussed on imitation tasks. Amongst the practical implications is the need to include tasks that could be developed collaboratively in the regular classroom.

With this research, it is intended to disseminate in the scientific community what are the characteristics that should have the interaction activities between a robot and autistic students. In addition, the type of tool needed to evaluate the improvements in the interaction is proposed.

The main purpose of this research was to develop a universal model to evaluate the perceived value of tourism services and satisfaction with, and loyalty to, destinations from the consumers’ perspective and demonstrated the model’s applicability in this context.

Using the structural equation model, cause and effect relationships were identified between the proposed model’s constructs, and indices of quality, satisfaction and loyalty among tourists were estimated. This system was applied to a large set of data collected with a structured questionnaire distributed to tourists visiting the city of Seville through a non-probabilistic sampling by intentional quotas method. In total, 922 valid surveys were obtained.

The indices show that tourists who visit Seville report a high level of loyalty to, and satisfaction with, this place because of the perceived quality of a variety of services. It is observed that the perceived quality index is much higher (17.95 per cent) than the expected quality index, so the quality of the service received by the tourist during his/her visit to Seville is described as excellent.

Regarding this study’s limitations, other variables could have been included that influence tourist satisfaction, such as the climate, the effect of advertising medium, the prices and the emotional components. In addition, surveying tourists’ expectations before their visit is virtually impossible, as is surveying the same tourists again about their perceived value and satisfaction after their visit. Future lines of research could focus on the intersection of information between tourism offer and demand, providing information about an appropriate balance in specific markets. The proposed model can also be applied to other tourism places that are similar to Seville’s tourism offer, allowing useful comparisons and identification of critical points and ways to improve customer satisfaction continuously.

By establishing indices of expected and perceived quality and satisfaction and loyalty among tourists, tourism authorities and different economic agents involved in this sector can receive objective information about the results and quality of tourism services. Tourism managers, thus, can set objectives for improvements and competitiveness, as well as building and maintaining customer loyalty. At the same time, these indices allow comparisons with other organisations and places. By facilitating greater transparency in the measurement of quality and satisfaction, service providers connected to tourism can create a platform on which to articulate clearly their contributions to interested parties and local communities.

These results constitute strategies and findings that any tourism place has to consider in the planning and development of its products. Therefore the model can help to encourage a long-term market perspective among tourism sector regulators, investors and agencies. With the information obtained with this model, areas needing improvement can be identified and the appropriate procedures can be put into practice to improve the tourism offer, adjusting it to meet travellers’ needs according to their motivations to travel to the destination. Residents also can benefit from these measures, as their quality of life will improve through upgrades of the city’s tourism facilities.

The unique contribution of the present study lies in how the indices or indicators of quality of, satisfaction with and loyalty to destinations among tourists are easily measured by applying structural equation modelling. A new approach to measure satisfaction, loyalty and quality is used based on a scale from 0 to 100, and the index results are very useful for comparing different tourist places.

The purpose of this paper is to estimate the impact of one productive development program (PROPYME) in a developing nation like Costa Rica. This program seeks to increase the capacity of small and medium-sized firms (SMEs) to innovate.

Impacts have been estimated assuming that beneficiary firms are trying to maximize their profits and that PROPYME aims to increase these firms productivity. The impacts were measured in terms of three result variables real average wages employment demand and the probability of exporting. A combination of fixed effects and propensity score matching techniques was used in estimations to correct for any selection bias. The authors worked with panel data companies treated and untreated for the period 2001-2011.

PROPYME’s beneficiaries performed better than other firms in terms of labor demand and their probability of exporting. In addition, the dose and the duration of the effects of the treatment (timing effects) are important.

The authors study the impact in ways that go beyond the average treatment effects on the treated (ATT) usually estimated in the existing literature. Specifically, the research focusses on the identification of the timing or dynamic effects (i.e. how long should we wait to see results?) and treatment intensity (dosage effects).

Se estima el impacto de un programa de desarrollo productivo (Propyme) en un país en vías de desarrollo como Costa Rica. El Propyme busca incrementar la capacidad innovadora de las pequeñas y medidas empresas (pymes) costarricenses.

el impacto se ha estimado y evaluado asumiendo que las pymes beneficiaras buscan maximizar sus beneficios y que Propyme se enfoca en incrementar la productividad de esas empresas. El impacto se valoró en función de tres variables: salarios reales medios, empleo demandado y la probabilidad de exportar. Se utilizó una combinación de técnicas de efectos fijos y emparejamiento en las estimaciones con el fin de prevenir sesgos de selección. Se trabajó con un panel de datos, incluyendo empresas tratadas (beneficiarias de Propyme) así como no tratadas para el periodo 2001-2011.

los beneficiarios de Propyme tuvieron mejor desempeño que las restantes empresas en términos de empleo demandado y su posibilidad de exportar. Adicionalmente los efectos dinámicos (dosis y duración) de los tratamientos son importantes.

este artículo evalúa el impacto de una forma que va más allá de lo usual en la literatura por medio de los efectos promedios de los tratamientos sobre los beneficiarios. Esto por cuanto se enfoca en efectos dinámicos como la duración así como la intensidad.

The purpose of this study was to estimate the capacity of the predominant activity of the Hotel and Restaurant (H&R) sector to create female employment in European Union (EU) countries.

The methodology used was conducted in two stages. First, a branch employment multiplier was calculated using the Leontief input-output tables (IOTs), which show the direct and indirect capacity of the activity to generate female employment. Second, a regression model was estimated to explain the determinants of the female employment multiplier in the H&R sector. It should be noted that the reliability and simplicity of the proposed model allows countries without IOTs, but with gender-disaggregated labor statistics, to easily estimate their own female employment multiplier.

The results show that the job-creation capacity of the H&R sector significantly varies across the EU countries, especially in relation to the female employment multiplier. Although international differences in gender wage gaps help to explain such multipliers, institutional factors and feminization rate also play a key role.

The results may contribute to improving the actions of member states to stimulate the sustainable development of the tourism sector.

Based on previous literature, the finding that higher tourism expenditure may result in increases in tourism employment gives rise to another set of interesting questions. The most fundamental of these may concern the nature of the economic underpinnings of the growth of female employment. This paper contributes to this issue by conducting a specific analysis across EU countries using a homogenous and comparable methodology.

This paper aims to increase the understanding of luxury brands’ branded content strategies concerning follower's engagement generated or not by happiness and well-being feelings spread in their branded content.

This study sample was composed of three of the most relevant luxury brands nowadays: Manolo Blahnik, Loewe, y Balenciaga. To address this research, an exploratory-correlational quantitative methodology was chosen; hypotheses were contrasted using ANOVA analysis with the SPSS software. Although the study can be considered quantitative, the first step of qualitative analysis was applied for content analysis with NVivo QSR software, categorizing all posts (N = 192) into three categories.

The dissemination of branded content and corporate social responsibility, despite being different in each case, show in general an interaction and affective commitment with their stakeholders. In the specific case of Manolo Blahnik and Loewe, they have prioritized their content, in the context of the pandemic, in posts related to social welfare, happiness, mental and physical health care. There are significant differences in the interaction with their audience, which respond very favorably to both “Happiness” and “Health and safety” content.

This study reveals how corporate social responsibility can be achieved using efficient communications in social networks. In this way, the perception of the image of the sector and the reputation can be improved – both sectoral and organizational – which unquestionably translates into economic gains for the brands.