# VR Reading Revolution: Decoding User Intentions Through Task-Technology Fit and Emotional Resonance
## 2 Literature Review and Research Hypothesis
### External Influences  
The concept of task-technology fit (TTF) was first introduced by [PERSON] and [PERSON] [24], who identified task, technology, and fit as the three foundational components of the model. In this framework, task refers to the set of actions undertaken by an individual during the transformation of inputs into outputs through the use of an information system, while technology encompasses computer-based systems including hardware, software, data, and associated user support services such as training and documentation. As the model has evolved, scholars have provided varying interpretations of TTF. [PERSON] [25] defined TTF as the degree of alignment between the functional capabilities of an information technology system and the requirements of user tasks. [PERSON] [26] further conceptualized TTF as a diagnostic instrument for assessing whether a given information system adequately meets user demands, positively influencing the effectiveness of systems such as group support systems and management support systems. In the context of digital libraries, typical user tasks include information retrieval, knowledge construction, and interactive learning. Accordingly, a virtual reality system must accommodate these task requirements in its operational mechanisms, presentation logic, and interactive pathways to effectively stimulate user motivation for engagement. The alignment between VR system functionalities and task expectations is therefore critical to driving users' willingness to adopt and continuously use the platform. Concurrently, the Innovation Diffusion Theory (IDT) provides a cognitive perspective that complements TTF by emphasizing the importance of perceived technological attributesin adoption and diffusion processes. According to [PERSON] [27], an individual's decision to adopt an innovation is influenced by their subjective perceptions of five key attributes: relative advantage, compatibility, complexity, trialability, and observability. These attributes are shaped not only by the inherent structural characteristics of the technology, but also by its perceived fit during actual use. In practical terms, when a VR-based digital library system is well-aligned with users' core tasks--such as search, reading, and knowledge management--it enhances users' perceptions of its relative advantage, fosters greater compatibility with prior experience, and reduces both complexity and uncertainty during usage. This dynamic illustrates how TTF can serve to amplify the five dimensions of IDT, thus facilitating the formation of usage intention. Based on TTF's emphasis on task support and IDT's focus on user perception, this study proposes the following hypotheses:  
**H1. **: _External technological and social factors within the virtual community have a positive effect on usage intention._  
**H1a. **: _Technology-task fit has a positive effect on usage intention._  
Based on the previous discussion on the influence of technical factors on users' willingness to use, this paper further introduces a social psychology perspective, focusing on how social norms influence users' adoption of virtual communities through \"peer recommendation\". According to the Theory of Planned Behavior (TPB), an individual's behavioral intention is not only influenced by their own attitudes, but also by the perceived expectations of significant others. In virtual environments, such subjective norms are often manifested in the form of peer recommendations, i.e., suggestions or feedback on usage from family, friends, or members of the social circle. Peer recommendation, as a typical social influence mechanism, plays an important role in enhancing users' trust and reducing the perception of uncertainty. [PERSON] [28] found that compared to expert recommendations, acquaintance recommendations are more likely to inspire users' trust and adoption motivation.