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This study examines why long-term relationships between expert users and smart voice assistants (SVAs) develop. It postulates that the five dimensions of experience (i.e. sensory, affective, intellectual, behavioural and relational) generate feelings of love for SVAs. The formation of love is examined considering three components: passion, intimacy and commitment. These feelings encourage users to continue employing and to generate long-term relationships with SVAs.

Data from a survey of 403 USA expert users of SVAs provide the input for structural equation modelling.

The results show that three dimensions of experience influence users’ passion towards SVAs: affective, intellectual and behavioural. Moreover, passion can convert the effect of users’ experiences into intimacy and commitment. Finally, intimacy and commitment increase users’ intentions to continue using SVAs.

The findings obtained make three original contributions. First, this study is the first to analyse expert users of SVAs and the post-technology adoption stage. Therefore, it introduces a new case of relational marketing in smart technologies. Second, this study contributes by applying a new theoretical perspective that evaluates the importance of users’ experiences with SVAs. Third, it takes an interpersonal approach to explore user-SVA interactions, revealing that users can develop human-like love feelings for SVAs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2022-0570

This study aims to examine users’ affective relationships with smart voice assistants (SVAs) and aims to analyze how these relationships explain user engagement behaviors toward the brands of SVAs. Drawing on relational cohesion theory, it proposes that cohesion between users and SVAs influences brand engagement behaviors, that is, continuing purchasing other products of the brand, providing knowledge to the brand and referring the brand.

Data from a survey of 717 US regular SVA users confirm the validity of the measurement scales and provide the input for the covariance-based structural equation modeling.

The results demonstrate that frequent user-SVA interactions evoke positive emotions, which encourage cohesive relationships. Pleasured-satisfaction and interest emerge as strong emotions. Moreover, relational cohesion between users and SVAs promotes engagement with the brand of the assistant.

This paper applies an interpersonal approach in a context that, to date, has been examined from a predominantly technological perspective. It shows that users develop positive emotions toward smart technologies through their interactions, and establishes the importance of building affective relationships. To the best of the authors’ knowledge, this is the first study to analyze cohesion between users and smart technologies and to examine the effect of this cohesion on user engagement with the brand.

The purpose of this paper is to understand the nomological network of associations between collective mindfulness and big data analytics in fostering resilient humanitarian relief supply chains.

The authors conceptualize a research model grounded in literature and test the hypotheses using survey data collected from informants at humanitarian aid organizations in Africa and Europe.

The findings demonstrate that organizational mindfulness is key to enabling resilient humanitarian relief supply chains, as opposed to just big data analytics.

This is the first study to examine organizational mindfulness and big data analytics in the context of humanitarian relief supply chains.