Evaluating garments in augmented reality when shopping online

Author:

Baytar FatmaORCID,Chung Telin,Shin Eonyou

Abstract

PurposeAugmented Reality (AR) integrates computer-generated images to a physical environment in real-time. Online apparel shopping presents some product-related risks, as consumers can neither physically see and touch the products nor try them on. The present study examined whether AR conveys reliable apparel product information in terms of fit, size, and product performance; and how AR affects attitudes toward apparel and purchase intentions when shopping online.Design/methodology/approachThis research was designed as a within-subject quasi-experimental study using repeated measures in two conditions: virtual try-on using the AR technology vs. physical try-on. A scenario was developed to help participants imagine themselves shopping online for a specific dress.FindingsResults indicated that size and color of dresses were conveyed accurately when utilizing AR as compared to physical try-on. Visual attributes such as style, garment details, and coordination with other items were found to be satisfactorily predicted when AR was employed. Overall, attitudes towards both AR and real dress, and purchase intentions were favorable. Participants with higher telepresence levels were found to have more positive attitudes towards the dress and greater purchase intentions when using AR as compared to the participants with low telepresence levels.Research limitations/implicationsOur findings implied that AR can provide enough information especially for garment sizes and visual characteristics when making purchase decisions. AR technology can be instrumental in introducing a certain style, building positive attitudes towards products, and driving sales, when the consumers perceive a certain level of “being there”. This study was limited to female students in North America. Also, because a single stimulus was used, the results cannot be generalized to other stimuli.Originality/valueOur study findings showed that participants were able to select the right garment size by using AR. The average ratings for visual characteristics such as style and detail were above the neutral level when using AR; indicating that participants can understand visual attributes in AR when shopping online. Moreover, in the AR condition participants with higher telepresence levels had higher attitudes towards the garment and purchase intentions as compared to the participants with low telepresence. AR can be instrumental for online apparel shopping. Retailers need to understand the potentials of these technologies and work with technology developers to enhance consumers' experiences.

Publisher

Emerald

Subject

Marketing,Business and International Management

Reference70 articles.

1. Avametric (2018), available at: https://www.avametric.com/.

2. A survey of augmented reality;Presence-Teleoperators and Virtual Environments,1997

3. Batisa, L. (2013), “New business models enabled by digital technologies: a perspective from the fashion sector”, Study report for the EPSRC RCUK DE research project NEMODE (New Economic Models in the Digital Economy), available at: http://www.nemode.ac.uk/wp-content/uploads/2013/03/BATISTA-case-study-in-the-fashion-sector-FINAL-Report.pdf.

4. I virtually try it … I want it! Virtual fitting room: a tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions;Journal of Retailing and Consumer Services,2018

5. Boyle, A. (2018), “Amazon's blended-reality mirror shows you wearing virtual clothes in virtual locales”, available at: https://www.geekwire.com/2018/amazon-patents-blended-reality-mirror-shows-wearing-virtual-clothes-virtual-locales/ (accessed 15 March 2019).

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