## 5 Discussion  
### Key Findings and Some Unsupported Hypotheses  
This study aimed to deepen the understanding of the attributes of physical and virtual SSTs that influence both online and offline behavioral processes simultaneously and the transitional effects from offline to online regarding the usage of SST. The applied model exhibited satisfactory model fit indices and a high percentage of explanatory power, and seven of the ten hypotheses were supported. The key findings and some unsupported hypotheses are discussed. First, we identified two critical attributes of physical SST, namely system service quality and perceived convenience, which have also been analyzed in related studies [14; 18]. Consistent with previous studies, these two factors considerably influence consumers' satisfaction [39; 51; 55], which in turn affects their subsequent usage. Moreover, all the hypothetical paths in the online environment were also supported. Two key attributes of virtual SST, namely system service quality and perceived ubiquity, were also identified. This finding is consistent with previous research [18; 51; 56]. Based on the results, we confirmed that system service quality and perceived ubiquity positively affect consumers' attitudes toward virtual SST, affecting their intention to download and use the ibon app. Second, in terms of the transition effect from offline to online, only one hypothesis was supported (i.e., the impact of perceived physical system service quality on attitude toward virtual SST), which echoes the research of [PERSON] et al. [47]. This result indicates that consumers' positive evaluation of the service quality of SST enhances their favorable attitude toward virtual SST. Specifically, it was observed that consumers' positive assessment of the service quality of SST enhances their favorable attitude toward virtual SST. Based on the literature [51], this outcome implies that companies that prioritize enhancing service quality and functionality of in-store (offline) SST are more likely to enhance consumer satisfaction and foster loyalty among their customers, providing contributions to the SST literature. Third, further discussion of the weak effect (H4b) and three hypotheses that were not supported from offline to online (H6b, H2b, and H1) are provided. Regarding H4b, the results support that the perceived system quality of the ibon SST influenced the attitude towards the ibon app. However, the relatively weak effect (\(t=2.33\)) suggests that system quality may play a less substantial role in attitude formation compared to other factors in the proposed model. While system quality contributes to attitude formation, other variables are likely to have stronger influences on users' attitudes toward the ibon app. Figure 3: Result of the structural model, with offline features marked in blue and online features marked in green. (* \(p<0.05;\)** \(p<0.01;\)** \(p<0.001\)). Future research should investigate whether factors such as perceived usefulness have a more direct impact on attitude formation, as users may prioritize functional benefits over technical system performance. In addition, intuitive interfaces and ease of use may be more immediately apparent to users than back-end system quality in influencing user attitudes toward the ibon app. Next, we found that consumers' perceived convenience of physical SST locations failed to enhance their attitude toward online SST (H6b). Some possible explanations are provided, including user familiarity, digital resistance, and different interaction expectations between physical and digital SSTs. User familiarity with physical SSTs may create a comfort zone. Consumers who are used to interacting with ibon kiosks may evaluate the ibon app independently. Digital resistance also plays a role from another perspective, as consumers who prefer tangible interactions may maintain barriers to mobile alternatives regardless of the convenience of virtual SSTs.