ARAM: A Technology Acceptance Model to Ascertain the Behavioural Intention to Use Augmented Reality

Abstract

The expansion of augmented reality across society, its availability in mobile platforms and the novelty character it embodies by appearing in a growing number of areas, have raised new questions related to people’s predisposition to use this technology in their daily life. Acceptance models, which have been updated following technological breakthroughs and society changes, are known to be great tools for predicting the intention to use a new technological system. This paper proposes a new acceptance model aiming to ascertain the intention to use augmented reality technology in heritage sites—the Augmented Reality Acceptance Model (ARAM). ARAM relies on the use of the Unified Theory of Acceptance and Use of Technology model (UTAUT) model’s constructs, namely performance expectancy, effort expectancy, social influence, and facilitating conditions, to which the new and adapted constructs of trust expectancy, technological innovation, computer anxiety and hedonic motivation are added. This model was validated with data gathered from 528 participants. Results confirm ARAM as a reliable tool to determine the acceptance of augmented reality technology for usage in cultural heritage sites. The direct impact of performance expectancy, facilitating conditions and hedonic motivation is validated as having a positive influence on behavioural intention. Trust expectancy and technological innovation are demonstrated to have a positive influence on performance expectancy whereas hedonic motivation is negatively influenced by effort expectancy and by computer anxiety. The research, thus, supports ARAM as a suitable model to ascertain the behavioural intention to use augmented reality in new areas of activity.

Acceptance of augmented reality for laboratory safety training: methodology and an evaluation study

“…This was reflected in the qualitative data through the category "Potential of the solution for training". As indicated in the results section and consistent with prior research Marto et al (2023) Alqahtani and Kavakli (2017), earlier studies have shown that both Performance Expectancy and Hedonic Motivation play a significant role in influencing Behavioral Intention (BI) to accept an AR system.…”

“…As far as we know, there are no studies on AR acceptance models that specifically address Emotional Reaction, Realism, and Attention. However, Performance Expectancy and Hedonic Motivation, in line with the previous research of Marto et al (2023) and Alqahtani and Kavakli (2017), have been shown to influence Behavioral Intention (BI). This confirms that a stronger Performance Expectancy and participants' hedonic motivation, emphasizing pleasure and fun in using the system, lead to a stronger behavioral intention to use the system.…”

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“…facilitating condition yang lebih tinggi atau memadai akan megarahkan pada niat penggunaan yang lebih tinggi untuk menggunakan JakOne Mobile. Semakin baik facilitating condition maka akan semakin kuat behavioral intention (Marto et al, 2021). Dalam hal ini penggunaan jakone mobile sangat terikat dengan sumber daya seperti smartphone dan koneksi internet (Tarhini et al, 2017).…”

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