Studying the impact of social media integration into online augmented reality-enabled services on consumer purchase intentions

This research extends the current body of knowledge on the application of augmented reality (AR) technology within the marketing field. The study investigates the impact of the augmented reality-enabled service on consumer behaviour, such as engagement levels, enjoyment, perceived trust, willingness to recommend to others, and decision to purchase. Addressing a critical gap in the existing literature, the thesis probes into the intricate interplay of social content embedded in AR layers—ranging from consumers' virtual mirror feed to their social media presence and product reviews. It scrutinises how these elements impact customer trust, decision comfort, and purchase intentions. The theory of social presence is central to understanding these effects. Furthermore, the study provides insights into the crucial elements of AR technology that facilitate its effective integration in the marketing field, such as heightened colour vividness, realistic graphics, and comprehensive product information. Methodologically, the study employs a quantitative data analysis approach, after a successful pilot study, the main survey was conducted with 924 participants. The findings suggest that the characteristics of AR technology, such as content informativeness, graphic vividness, amount of perceived control, and interactivity, have a significant positive impact on the feeling of perceived social presence. Subsequently, a heightened feeling of Social Presence is positively associated with increased levels of consumer engagement and trust, resulting in increased enjoyment and a more efficient decision-making process, ultimately leading to increased purchase intentions. The theoretical model depicts a sequence of interdependent variables, where changes in one variable can affect another variable. This knowledge can fuel valuable theoretical and managerial contributions and directions for further research.

Level dc:type.qualificationlevel

PhD thesis

Grantor dc:publisher.institution

Middlesex University

Year dc:date.issued

2023

Author dc:creator

• Cheremisina, K.

Identifier

oai:repository.mdx.ac.uk:116z36

OAI identifier oai:identifier

oai:repository.mdx.ac.uk:116z36