## 5 Discussion  
### Key Features and Predictions of Turn-Taking Coordination Failures  
Using logistic regression analysis, we addressed RQI, identifying which interaction dynamics significantly influence participants' success in acquiring speaking turns in VR environments. We also explored the potential of these factors for predicting coordination failures. The analysis identified five variables across three dimensions with significant impacts on turn-taking success. Below, we provide an in-depth discussion of these variables to uncover the underlying mechanisms driving their effects. Firstly, the individual status significantly affects their success in acquiring a turn. The negative logarithm of the speaking interval reflects this, with participants expressing intentions shortly after their last turn being more likely to succeed. This phenomenon can be attributed to several underlying mechanisms. This phenomenon can be attributed to several underlying mechanisms. Previous studies have identified the \"short-term gain effect\" in communication, where participants who have just spoken are more likely to speak again within a short period [74]. The regularity in such speaking sequences increases the predictability of the next speaker for group members [75]. Consequently, participants who have just spoken are better able to sustain and capture others' attention, making their social signals of speaking intention more easily perceived and responded to. Interaction proactivity features, such as speaking duration ratio, utterance count, and speaking intention count, strongly influence turn-taking coordination. An increase in speaking turns, speaking time, and participants expressing speaking intentions heightens the risk of turn-taking failures. The successful implementation of rapid turn exchanges relies on a clear signaling system to effectively manage the turn-taking process. However, existing literature highlights that the interpretation of signals often depends on specific contextual factors and is not always unambiguous, further complicating rapid turn exchanges [76]. In high-intensity interaction scenarios, participants are required to not only process others' spoken content quickly but also dynamically interpret and adapt to evolving social signals, which significantly increases the complexity of interactions. Moreover, technical limitations in VR environments, such as delays or inaccuracies in the transmission of non-verbal signals, may exacerbate these challenges. Taken together, these factors make interaction proactivity a critical contributor to speech overlaps and turn-taking failures. Interestingly, the communication quality dimension's speaking overlap ratio yielded counterintuitive results: increased overlap was associated with a higher likelihood of successfully acquiring speaking turns. This phenomenon may indicate that during overlapping speech, participants tend to actively coordinate to reach a conversational consensus. According to the \"one speaker at a time\" principle [16], extended periods of overlap may prompt participants to adjust their speaking rhythms to clarify a single active speaker. Through this coordination, participants become more attuned to others' speaking intentions, creating conditions for smoother turn acquisition. Thus, in specific contexts, overlapping speech may serve as a mechanism for achieving smoother turn transitions rather than as a barrier. As for the max speaker duration ratio, no significant effect was observed. Initially, we hypothesized that more balanced speaking distributions would create a more open conversational atmosphere, facilitating turn acquisition. However, this assumption was not supported. This suggests that the relationship between openness in turn-taking and participation balance may be more complex than initially anticipated. Finally, spatial relationships, measured by the group area feature, showed no significant effect on turn-taking coordination.