Research on Immersion and Satisfaction Game Design Based on Kano Model and Entropy Weight TOPSIS

With the rapid advancement of Virtual Reality (VR) technology, the gaming industry is confronted with unprecedented opportunities and challenges. Immersion, as a fundamental aspect of the VR gaming experience, has a direct impact on player engagement and satisfaction. Consequently, the design of game elements that can enhance immersion has become a critical factor in improving the overall quality of games. This study, based on the Kano model and the Entropy Weight TOPSIS method, examines the relationship between immersion elements and user satisfaction in VR game design. The Kano model categorizes game design elements into Must-be Attributes, One-dimensional Attributes, Attractive Attributes, Indifferent Attributes, Reverse Attributes, and Questionable Attributes, thereby enabling designers to identify and classify different player needs and optimize the design of immersive experiences. Simultaneously, the Entropy Weight TOPSIS method combines the entropy weight approach with the TOPSIS method to objectively calculate the importance and weights of various design elements, evaluating the relative effectiveness of different design alternatives, and ultimately determining the immersion design scheme that best aligns with player preferences. The findings indicate that immersion and user satisfaction do not always exhibit a positive correlation, as factors such as interaction usability, ease of use, comfort, gameplay content, game difficulty, graphics and sound effects, stability, and social interactivity also contribute to overall satisfaction. Based on these insights, this paper constructs a comprehensive immersion element library for VR game mechanics, and applies the Kano model and Entropy Weight TOPSIS method to evaluate and prioritize the design elements. The selected elements are those that most effectively fulfill both immersion and user satisfaction requirements, providing a scientific foundation for VR game design.