Emotional attributes of digital assistants driving engagement, purchase intentions and well-being
Purpose Grounded in the stimulus–organism–response (SOR) model and the spillover concept, the study examines how digital assistants’ (DAs) affective attributes shape customer engagement, which then spills over into emotional values, purchase intentions and well-being. Design/methodology/approach A two-wave longitudinal survey was conducted, yielding 440 responses at Time 1 and 315 at Time 2. Partial least squares structural equation modeling (PLS-SEM) by SmartPLS 4.0 was used to verify the reliability and validity of the measurement model and test the hypothesised relationships. Findings The findings reveal that DAs’ aesthetics, friendliness and playfulness significantly increase customer engagement, with effect sizes for these emotional stimuli varying from low to high. Customers’ active engagement also subsequently influences their emotional values: perceived happiness and relaxation. Together, these emotional values have a positive and significant effect on purchase intentions. The results also show that customer well-being is significantly spilled through purchase intentions. Moreover, customer engagement, emotional values and purchase intention yield substantial serial mediation effects in the relationships between attributional stimuli and well-being. Originality/value The originality of this study lies in extending the SOR model to a psychological outcome (well-being) and quantitatively verifying the interrelationships in retail settings. It investigates the serial mediation of emotional attributional stimuli, presenting their activeness continuum from low to high. Besides, it offers key managerial insights into effectively utilising DA attributes to engage and evoke customers’ emotional values, thereby driving purchase intentions and, subsequently, extending the experience to well-being in technology-mediated services.
Authors
- Md. Shahinur Rahman (ORCID: https://orcid.org/0000-0001-9129-1234)
- Md. Abdul Kaium (ORCID: https://orcid.org/0000-0003-2036-8825)
- Md. Mahiuddin Sabbir (ORCID: https://orcid.org/0000-0001-5804-3343)
- Md Mehedi Hassan (ORCID: https://orcid.org/0000-0003-2398-9213)
Institutions
- University of Barishal (BD)
Publication Details
- Journal
- International Journal of Retail & Distribution Management
- Published
- 2026-11-11
- DOI
- https://doi.org/10.1108/ijrdm-10-2025-0808
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00