Purpose This paper aims to explore the relationships between website quality – through consumer-generated media stimuli-, emotions and consumer-brand engagement in online environments. Design/methodology/approach Two independent studies are conducted to examine these relationships. Study 1, based on a sample of 366 respondents, uses a structural equation modelling approach to test the research hypotheses. Study 2, based on 1,454 online consumer reviews, uses text-mining technique to examine further the relationship between emotions and consumer-brand engagement. Findings The findings show that all the consumer-generated media stimuli are positively related to the dimensions of emotions. However, only pleasure and arousal are positively related to the three variables of consumer-brand engagement. The findings also show cognitive processing as the strongest dimension of consumer-brand engagement providing positive sentiments towards brands. Practical implications The findings provide marketers with an understanding of how valid, useful and relevant content (i.e. information/content) creates a greater emotional connection and drive consumer-brand engagement. Marketers should be aware that consumer-generated media stimuli influence consumers’ emotions and their reaction. Originality/value This study is one of the firsts to adapt and apply the S-O-R framework in explaining online consumer-brand engagement. This study also adds to the brand engagement literature as the first study that combines PLS-SEM approach with text-mining analysis to provide a better understanding of these relationships.

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Purpose This paper aims to explore tourist perceived value and attachment to intelligent voice assistants (IVAs) as antecedents of the quality of the human–IVA relationship in the hospitality domain. This research also examines the moderating role of psychological factors (self-esteem) and knowledge factors (past experience and technology expertise) in the relationships between antecedents and relationship quality. Design/methodology/approach The researchers conducted two quantitative studies, collecting data via online surveys in Mechanical Turk (n1 = 124 and n2 = 281). The proposed model was tested using partial least squares structural equation modeling. Findings The first study uncovers that tourist perceived value is the main influence on the quality of the relationship between tourists and IVAs. The second study confirms the direct relationships of the first and shows that self-esteem and technology expertise act as moderators. Practical implications This study advances the understanding of the tourism and hospitality stakeholders in using modern technologies (e.g. IVAs). Through comprehending the relationship building between individuals and IVAs, the stakeholders will be able to craft better strategies. Originality/value The study extends the attachment and social exchange theories to the tourist–IVA relationship context. Specifically, this research demonstrates the impact of tourist perceived value on the quality of the relationship with the IVA. It also points out that tourists’ self-esteem and technology expertise can weaken the tourist–IVA relationship.