With innovative technologies, various types of immersive digital experiences (IDEs) have gained significant attention in the past few years. Despite their popularity, little research has been conducted on the factors that examine visitors’ experiences and behavioral intentions. This study applies experience economy within the framework of the SOR (Stimulus-Organism-Response) theory, indicating the dimensions of IDE function as stimulus (S), mental imagery and attitude as the organism (O), and behavioral intentions as the response (R). This study aims to identify the antecedents and consequences of mental imagery to explain and understand the mechanism behind visitors’ evaluations for future decisions.
A total of 268 samples were collected for data analysis through an online survey on Qualtrics. Exploratory Factor Analysis (EFA) was conducted to determine the final measure items. A series of multiple regression analyses were employed to test the impacts of the dimensions of IDE on mental imagery and the differences between prior knowledge (low PK vs. high PK) groups on those relationships. Simple regression analyses were also conducted to test the relationship between mental imagery, attitude, and behavioral intentions. An independent t-test was conducted to confirm whether there were significant differences between PK groups.
This study found that immersive educational experience has the most significant impact on mental imagery among the dimensions of IDEs. Moreover, the results indicate that the impact of IDEs on mental imagery varies depending on visitors’ level of prior knowledge. This study provides practical guidance on identifying which experience elements should be considered to maximize visitors' experiences and enhance their behavioral intentions.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1427 |
| Date | 01 January 2024 |
| Creators | Kim, yeonjae |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Thesis and Dissertation 2023-2024 |
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