Abstract

Consumer testing in re-created purchase or consumption contexts may produce results with a higher external validity than laboratory testing and be a valid alternative to consumer testing in real-life contexts. Hence, the present study evaluates the utility of a novel immersive approach in sensory consumer testing. An immersive multisensory room was designed to reproduce consumption conditions close to real life, with large wall screen projections, audio and olfactory stimuli and furniture consistent with the video scenario. Overall liking and perceived freshness of two vegetable products (salad tomato and wild rocket) at different storage time were evaluated by a group of volunteers, regular consumers of the products. Evaluations were performed both in a immersive environment setting - the scenario was the dining room of a holiday farm overlooking a patio and the countryside - and in a traditional sensory lab setting, as a control. The magnitude of liking was higher when evaluations were performed in the immersive environment setting than in the traditional lab setting. However, the discrimination efficacy for freshness and liking of stored and un-stored vegetables was reduced in the immersive environment with respect to the control lab. Additional research, aimed at exploring other products and other consumption or purchase immersive scenarios, will further clarify whether these findings are product-dependent or determined by the contingent immersive situation.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.