원문정보
초록
영어
This research studies NPCs applied by Generative Pre-trained Transformer (GPT) Technology. This study set three independent variables as characteristics of the NPCs applied GPT. User immersion is set as a mediator variable, while user game satisfaction and loyalty are chosen as dependent variables. The Stimulus-Organism-Response (SOR) theory is employed to study user attitude changes, and immersion is examined through the Flow Theory. The study found that interactions between NPCs and users directly and indirectly influence user satisfaction and loyalty. This suggests that NPCs capable of providing users with desired information, rather than merely following predetermined protocols, can enhance the user’s affinity for the game. Furthermore, the intelligence and human-likeness of NPCs were found to indirectly influence satisfaction and loyalty through immersion. These findings underscore the importance of GPT-applied NPCs in the gaming industry, with potential implications for the future development and enhancement of such NPCs within games.
목차
1. Introduction
2. Theoretical Background
2.1 Non-player Characters (NPCs)
2.2 Flow Theory
2.3 Stimulus-Organism-Response (SOR) Theory
3. Research Methodology
3.1 Hypothesis Development
4. Research Results
4.1 Characteristics of the Sample
4.2 Correlations and Means, Standard Deviations
4.3 Exploratory Factor Analysis Result
4.4 Confirmatory Factor and Validity Analysis Results
4.5 Results of Hypothesis Testing
5. Conclusion
References