# The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
## 4 Discussion
### Governance  
From the SHAP plots in Figure 4, we can analyze the impact of governance-related features such as construction permits (ConstrPermits), Safety, and Security on real estate prices, gain valuable insights into their significance within the model-based perspective and, by extension, their potential implications in the real estate market. The SHAP analysis reveals that governance features like construction permits, safety, and security are significant but not predominant factors in the model's predictions. Their impact on the real estate market can be multifaceted. The SHAP values for construction permits (ConstrPermits) show a central concentration with a moderate spread, indicating that this feature has a variable impact on price predictions. This effect suggests that construction permits moderate influence on price predictions in some instances, while they may have a limited effect in others. This fact is corroborated by the study of [PERSON] et al. (2023) [99] that establishes bidirectional causal relationships between the number of building permits and the housing value index, indicating that this index responds negatively to an increase in building permits in the short term of 4-7 months but positively to an increase in building permits with a lag of 10-12 months. Also, in the work of [PERSON] et al. (2023) [39], the number of new permits is not regarded as a significant factor in their global model results, but its SHAP values in the high-income neighborhoods sub-model reflect it as a top factor in predicting housing values. A higher number of construction permits is typically associated with growth, potentially leading to higher property values. Nevertheless, this could also signal an oversupply that may drive prices down. This dual implication suggests that stakeholders must analyze these metrics within broader economic and development contexts, ensuring an accurate valuation of their investment's potential value, as construction permits reflect market dynamism and can guide strategic development. The safety-related SHAP values are clustered near the lower mid-range of the impact spectrum, suggesting a more uniform but lesser influence on the model's predictions. Whileit is not a dominant factor, its consistent presence indicates it is a feature that the model reliably considers. These insights are aligned with the study by [PERSON] et al. (2018) ([PERSON] et al. (2018), where the authors discuss the relative importance of \"district safety\", ranked as one of the top ten factors in their ANN model, highlighting the importance of safety in the district as a determinant of property value. Security displays a broader range of SHAP values, indicating a more inconsistent but occasionally significant influence on property price predictions. This pattern indicates that for specific-located properties, the presence of security services is a mid-range price determinant, as the proximity to security services might be a proxy for a low-crime environment, adding to an area's appeal. In the 2023 study by [PERSON] ([PERSON], 2017), \"security\" is defined as a variable in the context of points of interest (POIs) linked to public safety comprising elements such as camera surveillance, fire stations, police stations, and prisons. This study contributes to our understanding of the security feature by providing statistical data and assigning a relative importance score to this variable. However, its \(p\)-value of 0.678 indicates that \"security\" does not have a statistically significant impact on housing prices in the model used. The lack of a strong correlation between the security factor and housing prices in this research may be attributed to the complexity of combining various distinct elements into a single POI category. Our SHAP analysis shows that safety and security values can differ significantly based on market type and location. Although our model may not prioritize these features, their impact on property prices could be substantial, especially in markets with more pronounced concerns.