Abstract
Drawing on action identification and complexity theories, this study explores lifestyle congruency and chatbot identification as drivers of engagement, leading to chatbot advocacy. Data collected from 304 individuals were assessed symmetrically through PLS-SEM. Moreover, configuration causal paths were assessed through fsQCA. Findings reveal the role of chatbot identification in the relationship between lifestyle congruency and customer chatbot engagement. Lifestyle congruency and chatbot identification significantly influence all the dimensions of chatbot engagement. Nevertheless, only customer referrals and customer influence lead to chatbot advocacy. Findings from fsQCA reveal six and seven different paths, leading to high and low levels of chatbot advocacy, respectively. This is one of the first studies to apply both symmetrical and asymmetrical analysis to examine different casual paths to chatbot advocacy.
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No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Sandra Maria Correia Loureiro
Sandra Maria Correia Loureiro is in the ranking of top 2% of the best scientists in the world in Marketing and Sport, Leisure & Tourism by Stanford University. Her research interests include relationship marketing, tourism marketing issues, and the implications of technologies. She is well-published in top-tier peer-reviewed journals.
Faizan Ali
Faizan Ali is listed in the Top 2% of the best scientists in the world in Sport, Leisure & Tourism by Stanford University. His research interests include technology adoption and the digital well-being of consumers. He is well-published in top-tier peer-reviewed journals.
Murad Ali
Murad Ali is Assistant Professor at Newcastle Business School, Northumbria University, UK. His research interests include advancing research methods to understand knowledge management and innovation. He has published articles in several top-tier journals and also serves on editorial boards of journals.