# The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
## 4 Discussion
### Mobility  
In analyzing the SHAP plots in Figure 4 of our ML model for predicting housing prices, we can derive insights about the relative importance of mobility features (Bus, Subway, and Train), their specific impact on predictions, and their implications in real estate market analysis context. The SHAP beeswarm plot, which visualizes the distribution of each feature's impact on the model output, shows that proximity to subway stations (Subway) is a significant predictor of real estate prices, as indicated by the broader spread and higher positioning of its SHAP values. This effect suggests that properties closer to subway stations are generally valued higher, likely due to the convenience and efficiency of subway transport in urban settings. The higher mean absolute SHAP value for this feature suggests that properties near subway stations are often at a premium. This pattern reflects a broader market trend where homebuyers value the convenience of rapid transportation, which can be particularly appealing in dense urban areas where traffic congestion is a concern. The positive correlation with property prices might also indicate areas subject to gentrification or urban development. Proximity to subway stations often spurs investment and can catalyze neighborhood revitalization, increasing property values. Our results on the influence of subway transportation on real estate values parallel the findings of [PERSON] et al. (2023) [55]. Their study reveals how transport infrastructure significantly impacts real estate values, showing a 5.2% to 10.5% increase in flat prices within a 1-1.5 km radius of future subway stations, affirming the premium placed on subway accessibility in urban property markets. These insights are particularly relevant to our study, demonstrating the tangible value added by proximity to main transport links, a factor crucial in shaping real estate trends and urban development strategies. On the other hand, nearby bus stops (Bus) seem to have a negligible effect on pricing. The SHAP values for Bus are tightly clustered around zero, indicating that this feature does not substantially sway the model's predictions. This pattern could be attributed to the widespread availability of bus stops, making them less of a differentiating factor for property prices. The lower impact of Bus on property prices relative to Subway and Train may suggest that while bus routes are essential for basic accessibility, they do not add as much premium value to properties as access to faster and more reliable modes of transportation does. Given the lower SHAP values, there might be more flexibility in the valuation of properties based on bus access, which could benefit more location-sensitive market segments. This finding aligns interestingly with [PERSON] et al. 's (2018) [102] study, where the Jiangbei submarket, on the city's outskirts, showed significant influence from bus stops. This pattern suggests a nuanced landscape within the city, where bus stops' impact on real estate values might be more pronounced in less central areas like Jiangbei. Such variations highlight the importance of considering specific urban contexts when assessing the influence of transportation infrastructure on property valuation. The proximity to train stations (Train) also positively influences property values, albeit somewhat less than subway stations. The SHAP values for the Train feature are spread out but less so than for Subway, reflecting a moderately positive effect on price. This finding validates previous research by [PERSON] and [PERSON] (2023) [44] and implies that while train station accessibility to regional or national rail networks is a valued asset, it may not be as critical for daily commuting within the city as subway access is. The SHAP beeswarm plot also shows positive and negative impacts, and it could reflect the dual nature of train stations as hubs for opportunity and potential nuisances. While they offer connectivity, they can also bring noise, which some buyers might find undesirable.