Artificial Intelligence-Driven Music Biometrics Influencing Customers’ Retail Buying Behavior
: Rodgers Waymond, Yeung Fannie, Odindo Christopher, Degbey William Y.
Publisher: Elsevier
: 2021
: Journal of Business Research
: 126
: 401
: 414
: 1873-7978
DOI: https://doi.org/10.1016/j.jbusres.2020.12.039
: https://doi.org/10.1016/j.jbusres.2020.12.039
: https://research.utu.fi/converis/portal/detail/Publication/51132887
This study
examines the digital transformation effects of artificial intelligence (AI)-based
facial and music biometrics on customers’ cognitive and emotional states, and
how these effects influence their behavioral responses in terms of value
creation. Using a real-life, major optical retail store in China, 386 customers participated in a five-day experiment with different
types of music (enhanced by music-recognition biometrics). The findings show
that for utilitarian-type customers in a high-involvement AI purchase condition,
music-recognition biometric-induced emotion mediates cognition and behavioral
intentions. Both likability and the tempo of the music affect the impact of
music on cognition. This study contributes to a better understanding of the
relationship between cognition and emotion induced by AI-based facial and music biometric systems in shaping customer behavior and it adds to the atmospheric
literature. This is a significant contribution given the paucity of research in
the context of the Chinese retail environment, which is now a significant
retail market with global importance.