If You're Happy, I'm Happy

2022 ◽  
pp. 122-140
Author(s):  
Ondrej Mitas ◽  
Marcel Bastiaansen ◽  
Wilco Boode

An increasing body of research has addressed what a tourism experience is and how it should best be measured and managed. One conclusion has been to recommend observational methods such as facial expression analysis. The chapter uses facial expression analysis to determine whether the emotions of employees in the tourism industry affect the emotions of their customers, following a pattern of emotional contagion. The findings show that emotional valence and arousal are both contagious. Furthermore, the findings show that arousal is less contagious at a higher likelihood to recommend, likely due to higher employee arousal during approximately the middle third of their conversation. Furthermore, findings demonstrate that emotion measurement is now possible at reasonable convenience for the tourism industry and gives a unique insight into tourists' actual experiences that is more precise and valid than self-report alone, though with certain costs and stringent methodological limitations.

2020 ◽  
pp. 106591292091284
Author(s):  
Kim Fridkin ◽  
Patrick J. Kenney ◽  
Bartia Cooper ◽  
Ryan Deutsch ◽  
Manuel Gutierrez ◽  
...  

We compare two alternative measures for assessing people’s emotional reactions to political stimuli: the traditional self-report measure and facial expression analysis. We recruited participants to take part in a study examining reactions to a set of negative political commercials aired during the 2018 elections. We compare people’s self-reporting of their emotional reactions to negative political advertisements with their expressed emotion, according to the facial expression analysis. We find the discriminant validity of the facial expression analysis is higher than the self-report measure. Second, the self-report and facial expression measures of emotion have little convergent validity: we fail to find a consistent and strong positive correlation between the self-report and facial software measures of the same emotion and the same political advertisement. Third, the facial software measure has better predictive validity than the self-report measure, generating better predictions for the three dependent variables examined: changes in political interest, changes in people’s confidence in elected officials, and people’s assessment of the tone of the senate campaign.


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