Modelling the mass adoption potentials of fashion-augmented reality among the young consumers: evidence from an emerging economy

Mohima Akther · Mohammad Nurul Hassan Reza · Abdullah Al Mamun · Norzalita Abd Aziz · Marvello Yang

5 citations0/0 files storedJournal of Fashion Marketing and Management

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Technology Adoption and User Behaviour Augmented Reality Applications Consumer Perception and Purchasing Behavior

Abstract

Purpose The increasing demand for fashion-augmented reality (FAR) in online fast fashion shopping has the potential to reduce soil and water pollution. Hence, it is vital to understand the success factors that influence consumers’ intention to use FAR (IAR) and actual usage of FAR (UAR) to enhance its adoption. Design/methodology/approach By incorporating the unified theory of acceptance and use of technology, this study examined the influence of success factors on IAR, the effect of IAR on UAR and the mediating role of IAR in the relationship between success factors and UAR. In total, 803 responses were collected from Indonesia using a cross-sectional approach. Data were examined using partial least squares structural equation modelling. Findings Their findings revealed that perceived enjoyment, perceived service value and facilitating conditions significantly influenced IAR and UAR. However, the impacts of perceived functional benefits, lifestyle compatibility and perceived trust were insignificant. Nevertheless, the IAR has a significant influence on UAR. Finally, the IAR mediates the relationships among perceived enjoyment, perceived service value, facilitating conditions and UAR. Research limitations/implications This study provides valuable insights for practitioners to develop marketing strategies and improve consumer perceptions of FAR, particularly in emerging economies. One limitation of this study is that it exclusively examined young consumers and restricted the examination to specific aspects of consumer behaviour. Originality/value Integrating the unified theory of acceptance and use of technology and partial least squares structural equation modelling provides a comprehensive understanding of the underlying dynamics and sheds light on the success factors that drive consumer IAR into UAR and contribute to Sustainable Development Goal 12 by reducing soil and water pollution.

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References

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