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Augmented reality (AR) provides consumers with added value by allowing them to experience products via mobile devices. An increasing number of brands have adopted AR apps, but little is known about how consumers respond to AR app attributes or what motivates them to use luxury brand AR apps. To fill this gap, this study aims to use the stimulus-organism-response (S-O-R) model to examine how AR app attributes (i.e. interactivity and virtuality) and customer-based brand equity (CBBE) (i.e. brand awareness and brand image) of luxury brands affect consumers’ behavioral intention to share about the app and use it for future purchases.

Participants were recruited using a quantitative online survey (n = 214) and asked to use the Gucci mobile AR app before completing the survey. Partial least squares structural equation modelling (PLS-SEM) was used to analyze the data. All measures were adapted from existing literature.

Findings indicate that AR app attributes lead to positive consumer experience, in turn, creating behavioral intention, while CBBE partially leads to positive consumer perceptions. Post hoc analysis confirms that consumers’ perceived values mediate the relationship between AR app attributes and consumers’ attitudes toward a luxury brand AR app.

Theoretically, this study expands the application of the S-O-R model along with brand equity to AR adoption and luxury retail by demonstrating the intricate mechanism of how AR app attributes and CBBE promote consumers’ behavioral intentions toward luxury brand AR apps. Practitioners may create more interactive and immersive virtual product demonstrations and focus on establishing the overall brand image.

This study aims to explore the impact of decentralized long-term rental apartments on the value of in-community housing from two perspectives of housing price and rent.

This study uses the hedonic model to identify the factors affecting the housing value, and the influence of distributed long-rented apartments on the housing value in the community is analyzed from two aspects of housing price and rent by using the ordinary least square method and propensity score matching method.

The primary finding indicates that decentralized long-term rental apartments increase housing prices while decreasing general rental housing rents in the community, with the average degree of increase ranging from 0.93% to 2.59% and the average degree of decrease ranging from 2.23% to 4.34%. According to additional research, the prices of houses within communities rise by 0.042% for every 1% increase in the share of decentralized long-term rentals, while the rents for other types of rental property fall by 0.162%.

The government can regulate the housing market by regulating the access and layout of distributed long-rent apartments.

The findings of this study indicate that the existence and share of distributed long-rent apartments have a heterogeneous impact on the housing price and rent in the community, respectively.