Developing and Evaluating AR for Food Ordering System based on Technological Acceptance Evaluation Approach: A Case Study of Restaurant's Menu Item Selection
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2022 by IJETT Journal|
|Year of Publication : 2022|
|Authors : Nurul Amera Muhamad Nazmi, Wan Rizhan, Normala Rahim
|DOI : 10.14445/22315381/IJETT-V70I5P204|
MLA Style: Nurul Amera Muhamad Nazmi, et al. "Developing and Evaluating AR for Food Ordering System based on Technological Acceptance Evaluation Approach: A Case Study of Restaurant's Menu Item Selection." International Journal of Engineering Trends and Technology, vol. 70, no. 5, May. 2022, pp. 24-29. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I5P204
APA Style:Nurul Amera Muhamad Nazmi, Wan Rizhan, Normala Rahim. (2022). Developing and Evaluating AR for Food Ordering System based on Technological Acceptance Evaluation Approach: A Case Study of Restaurant's Menu Item Selection. International Journal of Engineering Trends and Technology, 70(5), 24-29. https://doi.org/10.14445/22315381/IJETT-V70I5P204
Nowadays, people are more concerned about how attractive the dining place is in terms of its services regardless pre or post ordering process. There are just a handful of AR apps available for restaurant ordering systems, given the evolution of numerous Augmented Reality (AR) applications in various fields. In this study, the current trend of AR technology for food ordering systems was investigated to develop a food ordering system using AR for restaurant menu item selection (MenAR). Marker-based technique on the conventional menu was used in this MenAR to visualize 3D food models. Pilot research was executed to evaluate users' acceptability of MenAR using the Unified Theory of Acceptance and Use of Technology (UTAUT). Multiple regression analysis was used to analyze all of the data from the questionnaires. The result later advocated that the suggested factors explained 82.4% of users' intention to use MenAR in the future respondents involved. Performance Expectancy (PE) was the strongest determinant. Overall, MenAR can give an engaging and dynamic information experience. Furthermore, further constructions can be explored to understand better differences in various fields covering the food industry.
Technological acceptance evaluation, UTAUT, Augmented reality, Food ordering system.
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