Learning by doing: diary study of attitude formation in voice-commerce
Purpose Voice commerce (VC) is gaining momentum as a new channel and consumer touchpoint, with popular e-retailers adding it as an additional interface option on their websites. Its adoption and continuous usage are currently limited to low-involvement purchases. This research explores consumers' buying journey of high-involvement products using VC to understand how it influences actual buying behaviour. Design/methodology/approach A qualitative self-report diary was used to collect data. A total of 23 respondents completed the process with eight different products over 8 weeks. Findings Findings reveal that consumer behaviour in VC for high-involvement purchases is a self-reinforcement loop where consumer attitude and trust, arising from personal experiences, modify intentions and behaviour in VC. Further, this study identified learning-by-doing and immersive shopping experiences as drivers of consumers' preference for VC in high-involvement purchases. Also, individual factors such as regulatory focus and technophilic orientation moderate the behaviour. Originality/value This research contributes by extending the Stimulus-Organism-Behaviour-Consequence framework in explaining consumers buying behaviour in high-involvement products using VC. It identifies a self-reinforcement loop through the learning-by-doing effect and an immersive shopping experience as organismic factors that alter trust, making it a dynamic psychological mechanism that influences consumer behaviour in VC. Further, it uncovers the role of individual factors, such as a technophilic orientation and regulatory focus.
Authors
- Jaydeep Mukherjee (ORCID: https://orcid.org/0000-0002-6276-4415)
- Astha Sanjeev Gupta (ORCID: https://orcid.org/0000-0001-6648-9388)
Institutions
- Management Development Institute (IN)
- International Management Institute (IN)
Publication Details
- Journal
- International Journal of Retail & Distribution Management
- Published
- 2026-10-05
- DOI
- https://doi.org/10.1108/ijrdm-09-2025-0741
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00