Evaluation of the extended TAM for digital signage augmented roadshow (DiSAR) using PLS-SEM

Introduction With the advancement in digital signage technology, it is now possible to carry out a roadshow operation with digital signage as the main medium of the roadshow, leading to the development of the Digital Signage Augmented Roadshow (DiSAR) framework. To foster confidence in advertisers in considering DiSAR, understanding user acceptance through a theoretical model is crucial. Therefore, this study proposes an extended Technology Acceptance Model incorporating System Quality, Perceived Interactivity and Perceived Enjoyment as antecedents and empirically analyzes its performance in modelling the user acceptance of the participants in a DiSAR. Methods The Technology Acceptance Model was added with constructs that best reflect the unique characteristics of the DiSAR. The additional constructs are System Quality, Perceived Interactivity and Perceived Enjoyment. To investigate the relationship between the additional constructs and the original constructs, Partial Least Squares Structural Equation Modelling was used on a sample of 203 DiSAR participants. The aim is to understand the relationship of the additional constructs towards the user acceptance of DiSAR. The explanatory and predictive power of the model was also examined to provide a more holistic view of the model’s capability to accurately predict user acceptance and identify key factors influencing the user acceptance of DiSAR. Results The statistical analysis revealed that System Quality and Perceived Interactivity have a significant relationship with the Perceived Ease of Use of DiSAR, while Perceived Enjoyment has a significant relationship with the Perceived Usefulness of DiSAR. Structural model analysis also showed that the Technology Acceptance Model has good explanatory power but attenuated predictive power. Discussion These findings contributes to understanding the overall performance of the Technology Acceptance Model in modelling the user acceptance of DiSAR participants. The findings also contribute to understanding how the unique characteristics of DiSAR influences user acceptance, which can further drive development to improve the roadshow framework itself.