Tourist destinations increasingly sustain their consolidation, promotion, and development from gastronomy. This research aims to contribute to the scientific literature analyzing the relationship between tourism and gastronomy for the specific case of the Costa del Sol (Spain) from tourists’ experiences of different nationalities who have visited the area. The methodology has been based on questionnaires applied to foreign travellers, after the gastronomic tasting of lunch or dinner in typical beach restaurants, called “chiringuitos”. Results show the existence of different segments of tourists based on their attitude towards local cuisine. Three groups have been identified, with different gastronomic predispositions and knowledge, and it is concluded that there are different levels of satisfaction and motivations in tourists, as they are identified in one segment or the other.

The present work aims to analyze the properties of the working conditions recorded in the Sixth European Working Conditions Survey (EWCS); with it, it has being built seven independent indexes about different aspects of work’ quality in the health sector, and these constructs are used to evaluate their effects on work engagement (WE). In this sense, the originality of incorporating teamwork as a modulating variable is included. To analyze the effects of the job quality index (JQI) on the WE, a logistic regression model is proposed for a total of 3044 workers within the health sector, differentiating between those who work or not in a team; in a first stage and these estimates are compared with those obtained using an artificial neural network model, and both are used for the consideration of the research hypotheses about several causal factor. An important contributions of the study, it is related to how work commitment is mainly influenced by prospects, social environment, intensity and earnings, all of them related to job performance. Therefore, knowledge of the determinants of work commitment and the ability to modulate its effects in teamwork environments is necessary for the development of truly sustainable Human Resources policies.

The cultural and historical heritage of a city is a major resource for attracting tourists. Therefore, determining how to perceive and identify the characteristics of persons visiting a locality attracted by its heritage is relevant for the purpose of better meeting their expectations and needs. This research focuses on understanding the perceptions, motivations, and satisfaction of women visiting Cordoba (Spain). Thus, on the basis of a questionnaire completed by women visiting Cordoba between the months of June and November 2019, statistical analysis was conducted. Using various multivalent case-grouping techniques, segments of tourists holding similar perceptions of cultural heritage were detected. Moreover, non-parametric statistical techniques highlighted significant differences between the valuations obtained in the various segments. This analysis exposed a segment of women who, known as absorptive tourists, are characterized by a high cultural motivation to visit the city of Cordoba linked to the heritage sites they have visited. The conclusions obtained herein should be useful for adjusting the city’s provision of tourism services to satisfy the demand of female tourists visiting the city.

Tritordeum is a new cereal resistant to drought and high temperatures, and it is a very healthy crop. The aim of this study was to compare two different diets (tritordeum meadow vs. oat meadow) for grazing pregnant ewes to determine if there was any effect on the objective physiological indicators of animal welfare. A total of 150 pregnant Merino ewes (3–5 years) were randomly divided into two groups (n = 75 each) to be fed with two different meadows, being evaluated during the spring season. Red blood cells count, haemoglobin, packed cell volume, white blood cell count, neutrophiles/lymphocytes ratio, lactate dehydrogenase, creatinine phosphokinase, aspartate aminotransferase, glucose, cortisol, total plasma proteins, albumin, globulins, albumin/globulins ratio, alkaline phosphatase, glutamate dehydrogenase, IgA, and IgG were determined. Overall, the results of this study indicate that the welfare of pregnant ewes fed with tritordeum meadow was better than that of pregnant ewes fed with oat meadow. Tritordeum meadow had a positive influence on the physiological parameters of animal welfare studied in pregnant Merino ewes. Therefore, tritordeum meadow can be considered a functional feed, as it has a beneficial effect on health beyond its basic nutritional value. Farmers are recommended to feed a cereal such as tritordeum grassland to their sheep, as it not only ensures that the animals benefit from all the nutrients, but also prevents diseases and improves their quality of life. In addition, the cereal’s resistance to fungal diseases makes it suitable for use in sustainable production systems with a reduced environmental footprint.

Long-term ratings of companies are obtained from public data plus some additional nondisclosed information. A model based on data from firms’ public accounts is proposed to directly obtain these ratings, showing fairly close similitude with published results from Credit Rating Agencies. The rating models used to assess the creditworthiness of a firm may involve some possible conflicts of interest, as companies pay for most of the rating process and are, thus, clients of the rating firms. Such loss of faith among investors and criticism toward the rating agencies were especially severe during the financial crisis in 2008. To overcome this issue, several alternatives are addressed; in particular, the focus is on elaborating a rating model for Moody’s long-term companies’ ratings for industrial and retailing firms that could be useful as an external check of published rates. Statistical and artificial intelligence methods are used to obtain direct prediction of awarded rates in these sectors, without aggregating adjacent classes, which is usual in previous literature. This approach achieves an easy-to-replicate methodology for real rating forecasts based only on public available data, without incurring the costs associated with the rating process, while achieving a higher accuracy. With additional sampling information, these models can be extended to other sectors.