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The aim of this study is to investigate subject independent emotion recognition capabilities of EEG and peripheral physiological signals namely: electroocoulogram (EOG), electromyography (EMG), electrodermal activity (EDA), temperature, plethysmograph and respiration. The experiments are conducted on both modalities independently and in combination. This study arranges the physiological signals in order based on the prediction accuracy obtained on test data using time and frequency domain features.

DEAP dataset is used in this experiment. Time and frequency domain features of EEG and physiological signals are extracted, followed by correlation-based feature selection. Classifiers namely – Naïve Bayes, logistic regression, linear discriminant analysis, quadratic discriminant analysis, logit boost and stacking are trained on the selected features. Based on the performance of the classifiers on the test set, the best modality for each dimension of emotion is identified.

 The experimental results with EEG as one modality and all physiological signals as another modality indicate that EEG signals are better at arousal prediction compared to physiological signals by 7.18%, while physiological signals are better at valence prediction compared to EEG signals by 3.51%. The valence prediction accuracy of EOG is superior to zygomaticus electromyography (zEMG) and EDA by 1.75% at the cost of higher number of electrodes. This paper concludes that valence can be measured from the eyes (EOG) while arousal can be measured from the changes in blood volume (plethysmograph). The sorted order of physiological signals based on arousal prediction accuracy is plethysmograph, EOG (hEOG + vEOG), vEOG, hEOG, zEMG, tEMG, temperature, EMG (tEMG + zEMG), respiration, EDA, while based on valence prediction accuracy the sorted order is EOG (hEOG + vEOG), EDA, zEMG, hEOG, respiration, tEMG, vEOG, EMG (tEMG + zEMG), temperature and plethysmograph.

Many of the emotion recognition studies in literature are subject dependent and the limited subject independent emotion recognition studies in the literature report an average of leave one subject out (LOSO) validation result as accuracy. The work reported in this paper sets the baseline for subject independent emotion recognition using DEAP dataset by clearly specifying the subjects used in training and test set. In addition, this work specifies the cut-off score used to classify the scale as low or high in arousal and valence dimensions. Generally, statistical features are used for emotion recognition using physiological signals as a modality, whereas in this work, time and frequency domain features of physiological signals and EEG are used. This paper concludes that valence can be identified from EOG while arousal can be predicted from plethysmograph.

Applying the value-attitude-behavior (VAB) model, this study investigated how perceived utilitarian and hedonic values (i.e. novelty and emotion) affect individuals' attitudes toward medical hotels and how these attitudes, in turn, influence their intentions to stay at medical hotels. The current study also explored the moderating impact of overall health status on the relationships between perceived utilitarian, novelty and emotional values and attitudes toward medical hotels.

The data collected from 351 individuals who spent a night in a hospital to undergo medical treatment was used in conducting structural equation modeling to evaluate the research model and test the study hypotheses.

The study results revealed that perceived utilitarian, novelty and emotional values exerted a positive influence on individuals’ attitudes toward medical hotels, consequently enhancing their intention to stay. Additionally, significant moderating impacts of overall health status on the associations between perceived utilitarian, novelty and emotional values and attitudes toward medical hotels were observed.

The study findings provide useful guidance for professionals, such as operators, marketers and managers in medical hotels. These insights can improve operational and marketing strategies, benefiting both the industry and healthcare accommodation seekers.

This study is among the first to empirically assess a theoretical model that explored the influence of individuals' value perceptions within the realm of medical hotel establishments.

The objective of the present study was to investigate the impacts of familiarity with and awareness of Florida as a snowbird destination, and satisfaction with the snowbird experience on Florida's image and on snowbirds' permanent relocation intention to Florida. Additionally, the influence of Florida's image on snowbirds' behavioral intention to move to Florida permanently was investigated.

Data gathered from 304 snowbirds were utilized in employing structural equation modeling to assess the research model.

The study results showed that awareness of and familiarity with Florida as a snowbird destination, and satisfaction with the snowbird experience significantly influenced participants' image perceptions of Florida. In addition, awareness of and familiarity with Florida as a snowbird destination, and participants' image of Florida had a significant influence on snowbirds' intentions to move to Florida permanently.

The findings of the study provide significant insights for destination marketing and management organizations and local policymakers in formulating and enacting policies in snowbird destinations to efficiently address migration trends.

This study is one of the first papers to empirically investigate and successfully construct a comprehensive model that explicate the determinants of snowbird tourists' permanent relocation intention.

This study aims to diagnose the perception, knowledge, awareness and position of the bioeconomy in university education and research.

This study is based on a questionnaire survey conducted at universities in Poland, the Czech Republic, Spain and Portugal (n = 464). The questionnaire consisted of open-ended, dichotomous and Likert-type questions. Variable frequency distribution methods and the non-parametric chi-square test were used to test the independence of the characteristics. The Cramer’s V contingency coefficient was used to determine the degree of dependence between the variables.

The researched academic community is dominated by a traditional approach to the bioeconomy, which relates to agriculture and ecological aspects. Respondents believe in the positive environmental impacts of the bioeconomy, while less often being aware of its importance from a socio-economic perspective. Insufficient teaching and research in the field of the bioeconomy can be widely observed. The presumed link between the existence of a bioeconomy strategy at national level and awareness of the bioeconomy was not confirmed.

The limited sample, the narrow geographical scope of the study does not allow for a comprehensive analysis of the topic. Another limitation is the lack of representativeness of the results in relation to all university representatives in the countries studied and the uneven composition of the samples.

This study fills the knowledge gap about the status of the bioeconomy in European academic communities by analysing its perception among both teachers and students of social, natural and applied sciences.