## 3 Review Results
### Gaps in Current Empirical Studies  
The impact of demographic factors such as age, gender, education, and income on the intention to adopt ChatGPT has shown inconsistent results across empirical studies. While some research has suggested that these demographic characteristics play a significant role, other studies have found them to be insignificant, indicating that individual attitudes, intrinsic motivations, and external factors may exert a stronger influence on adoption behavior than demographic attributes. This suggests that demographic variables may not be consistent predictors of adoption, highlighting the need for more targeted research to better understand when and how they impact ChatGPT use. Trust in ChatGPT also presents mixed findings. While some studies suggest that trust strongly correlates with perceived usefulness and behavioral intention, others show no significant relationship. This inconsistency points to a gap in understanding how trust interacts with other adoption factors, such as perceived ease of use, user satisfaction, and system reliability. Further research is needed to explore trust's nuanced role, particularly in contexts involving high-stakes academic decisions. Similarly, privacy and security concerns, although important, did not consistently influence perceived usefulness or ease of use. This suggests that, while users acknowledge the importance of privacy and security, they may prioritize the functional benefits of ChatGPT over these concerns. This gap indicates a need for future research to investigate how institutions can address privacy and security concerns without compromising the user experience or discouraging adoption. Extrinsic motivation, including external rewards or institutional mandates, has been found to have a limited impact on ChatGPT adoption. Instead, intrinsic factors like perceived usefulness, personal enjoyment, and engagement with the tool seem to play more critical roles in driving adoption. This highlights a gap in understanding how extrinsic motivations can be effectively integrated into adoption strategies. More research is needed to explore the balance between extrinsic incentives and intrinsic motivations in educational settings. Inconsistent findings also arise regarding effort expectancy and facilitating conditions. While some studies found these factors to be strong predictors of adoption, others did not. This variability suggests that contextual factors, such as the specific academic environment or the availability of technical support, may significantly influence how effort expectancy and facilitating conditions impact user behavior. To clarify this, the future research should focus on contextualized studies across different educational settings. Cost and financial considerations similarly showed inconsistent effects on adoption intentions. While financial concerns may play a role in some cases, many users prioritize the educational benefits of ChatGPT over financial constraints, indicating that perceived value and utility can outweigh cost concerns. This underscores the need for further research to understand the conditions under which cost becomes a barrier to adoption and how financial considerations interact with perceived benefits. Additionally, the limited significance of external motivations, such as institutional mandates, underscores a gap in understanding how to leverage these motivations to enhance the adoption rates effectively. The current research suggests that personal attitudes and intrinsic motivations are more decisive factors. The future research should explore ways to align external incentives with intrinsic motivations to encourage broader adoption. Another important gap in the literature concerns the variation in sample sizes and methodological approaches. The studies range from small pilot studies to large-scale surveys, making it difficult to generalize the findings. The predominance of cross-sectional research designs and quantitative surveys also limits the depth of analysis.