When AR meets food: A structural overview of the research space on multi-facets of food

Wei, Jun; Zhao, Shengdong; Nakatsu, Ryohei; Duh, Henry Been-Lirn

doi:10.1109/ismar-amh.2012.6483999

Cited by 3 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…But still, slightly some research about Augmented Reality in food and beverage. However, this technology has many opportunities in the food and beverage industries [28]. A prior study explored the usage of AR to enhance customers' experience [13].…”

Section: B Augmented Reality In Foodmentioning

confidence: 99%

Intention to Adopt Online Food Delivery Using Augmented Reality Mobile Apps: A Perspective of SOR Framework

Khosasih¹,

Lisana²

2023

Int. J. Adv. Sci. Eng. Inf. Technol.

View full text Add to dashboard Cite

Globally, the COVID-19 pandemic has affected all sectors, including the food and beverage industry. The pandemic has changed customers' behavior from dine-in services to online food ordering systems. Technology advancements make ordering food easier with Online Food Delivery (OFD) service. However, before buying food online, consumers require a physical assessment to decide to buy the food or beverage. Augmented Reality (AR) is a popular technology to show 3D virtual elements. Meanwhile, the stimulusorganism-response (SOR) framework can be used to analyze consumers' behavior. More specifically, the SOR model has been used to evaluate the user's behavior intention to accept online shopping apps. However, in the OFD context, there is a lack of research investigating the customer's intention to use the AR app based on the SOR perspective. This study aims to assess the factors influencing consumers' intention to adopt augmented reality apps. 52 AR OFD app customers participate in this study. Partial Least Square-Structural Equation Modeling (PLS-SEM) and SMARTPLS 3 was used to analyze the research model. This study evaluated from measurement and structural model. The measurement model using factor loading, Composite Reliability (CR), Average Variance Extracted (AVE), and heterotrait-monotrait (HTMT) ratio. The structural model assessed the variance inflation factor (VIF), R2, path coefficient (β), f2, and p-value. The results showed the significance of food image on hedonic, utilitarianism, and perceived informativeness. Furthermore, hedonism was the only determinant that positively influenced the customers' intention to use the AR OFD apps.

show abstract

Section: B Augmented Reality In Foodmentioning

confidence: 99%