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This study is among the first to integrate the technology acceptance model (TAM) and value-based adoption model (VAM) in the context of augmented reality (AR) shopping. It assesses how consumers' rational (TAM) and emotional (VAM) factors influence their intention to use AR in online shopping via perceived value and consumer engagement.

This study uses a quantitative research approach and employs a standardized survey questionnaire distributed on social media platforms to recruit Gen Z members who are potential buyers or users of AR technology. SmartPLS 4.0 was used to test the responses of 204 respondents.

The results indicate that consumers who perceive a higher value of AR in shopping are inclined to use AR in their future shopping when AR shopping is easy to use, useful, personalized, innovative and provides a highly engaging experience. Interestingly, perceived sacrifice did not influence perceived value. This study confirms that integrating TAM and VAM is instrumental in capturing value, which in turn influences engagement and the intention to use AR in online shopping.

This study further extends the conceptualization of AR perceived value by combining rational components derived from TAM and VAM, thus leading to a sturdy and theoretically grounded framework. In addition, this study contributes to the literature on extended reality, namely AR shopping, and helps brand managers manage highly evolving AR experience for Gen Z.

The urgency to address climate change and its devastating consequences has never been more pressing. As societies become increasingly aware of the detrimental impact of traditional housing on the planet, there is a growing demand for eco-friendly housing solutions that prioritize energy efficiency, resource conservation and reduced carbon emissions. Therefore, this study aims to investigate the factors that influence customers’ priority toward eco-friendly house purchasing intention.

This study collected 386 data using a quantitative research strategy and purposive sampling method. This study uses a hybrid analysis technique using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approaches to identify the influencing factors.

The PLS-SEM analysis found that attitude toward the eco-friendly house, subjective norms, performance expectancy, environmental knowledge and environmental sensitivity have a positive influence on eco-friendly house purchasing intention. However, perceived behavioral control and willingness to pay were found to have insignificant effect on customers’ intention to purchase eco-friendly houses. The fsQCA results further revealed complex causal relationships between the influencing factors.

This research will not only contribute to academic knowledge but also provide practical guidance to real estate developers, policymakers and individuals looking to make environmentally responsible choices. By understanding the factors that influence consumers’ intentions to purchase eco-friendly houses, we can pave the way for a more sustainable and resilient future.

This study has used a hybrid analysis technique, combining PLS-SEM and fsQCA, to enhance the predictive accuracy of eco-friendly house purchase intentions among individuals residing in densely populated and highly polluted developing countries, such as Bangladesh.