Digital Innovations in E-Commerce: Augmented Reality Applications in Online Fashion Retail—A Qualitative Study among Gen Z Consumers
Abstract
:1. Introduction
1.1. Visual Technology Solutions
- Marker-based AR (Image Recognition or Recognition-based AR) that provides more information about an object by recognizing it.
- Marker-less AR (location-based AR) that is widely implemented in smartphones, offering location detection features.
- Projection AR that projects light onto a surface, creating an interactive experience.
- Superimposition-based AR that replaces the entire or partial view of an object with an augmented view.
- Digital Packaging AR that allows users to interact with a physical object, revealing a deeper experience.
- Information Overlay and Virtual Objects that use virtual objects to create reactive images based on the physical surroundings.
1.2. Visual Experience
2. Methodology
3. Results and Discussion
3.1. Consumption Habits and Online Purchases
3.2. The Customer Journey Model of Online Fashion Purchase
- Enhanced product visualization;
- Try-before-you-buy experience;
- Improved engagement;
- Impulse buying facilitation;
- Enjoyable and entertaining shopping;
- Discovery of unique items;
- Customizable filters for better search results;
- Detailed product information;
- Visual context for decision making.
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Stage | Over 75% | 25% to 75% | Under 25% |
---|---|---|---|
Awareness | Facebook Messenger, Instagram Stories, Instagram, Pinterest, YouTube, Instagram Influencers, and Tagged Brands | Brand Instagram, Facebook, and Displays | Blogs, Retailer’s Websites, and Brand’s Website Applications |
Research | Google Manually, Google by Picture, Comments, and Ratings | n.data | n.data |
Selection | Style, Price/Affordability, Color, Fabric, Rating, Comments, and Shipping Price | Items Fit Together | Designer, Origin, and Ethical Brand |
Delivery | Delivery to Home or Workplace | n.data | In Shop |
Follow Up/Evaluation | Coupons, Newsletters, Brand Social Media Site, and Messenger | n.data | n.data |
Motivation | Why Online? | Contextual Factors |
---|---|---|
Fashion involvement; fashion awareness; “changing fashion trends”; emotional needs: “I need to buy some new clothes”; casual wear, suits, dress shirts, and casual slacks; trends unless a major change takes place; and “Check to see what is currently fashionable”. | Wide variety of brands, contain product descriptions to give detailed character to products, presenting new products, introduce new clearances, make it easy to buy the right size, average user-generated content, (customer reviews) helps the decision, read customer reviews, presenting related products, presenting related accessories, size guide, recommended products, accessories, multiple images, and view products in different colors. | Shopping value, store visit intentions, entertaining experiences, utilitarian value, impulsive buying, examining the online search process through visual context, experiential visual solutions, and fantasies |
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Kovács, I.; Keresztes, É.R. Digital Innovations in E-Commerce: Augmented Reality Applications in Online Fashion Retail—A Qualitative Study among Gen Z Consumers. Informatics 2024, 11, 56. https://doi.org/10.3390/informatics11030056
Kovács I, Keresztes ÉR. Digital Innovations in E-Commerce: Augmented Reality Applications in Online Fashion Retail—A Qualitative Study among Gen Z Consumers. Informatics. 2024; 11(3):56. https://doi.org/10.3390/informatics11030056
Chicago/Turabian StyleKovács, Ildikó, and Éva Réka Keresztes. 2024. "Digital Innovations in E-Commerce: Augmented Reality Applications in Online Fashion Retail—A Qualitative Study among Gen Z Consumers" Informatics 11, no. 3: 56. https://doi.org/10.3390/informatics11030056
APA StyleKovács, I., & Keresztes, É. R. (2024). Digital Innovations in E-Commerce: Augmented Reality Applications in Online Fashion Retail—A Qualitative Study among Gen Z Consumers. Informatics, 11(3), 56. https://doi.org/10.3390/informatics11030056