## 6 Discussion  
Since the budget allocation only has an effect from the sixth year onward due to existing medium-term planning, the trends only diverge from the sixth year onward if the prioritization strategy is the same, but the budget allocation differs (scenario 2). When considering the two scenarios with prioritization according to the effect on the BAQ grade, budget allocation according to prioritization has a positive effect on the BAQ grade. Long-term behavior shows an improvement of about 40%-points compared to the reference scenario. If the budgets are allocated based on existing medium-term planning, the BAQ grade still improves by about 35%-points compared with the reference scenario. However, it is too simplified to only demand a BAQ-optimizing business strategy, and therefore an adjustment of the investment and maintenance regime from the station infrastructure company, to significantly improve the BAQ grade. Prioritizing only based on the BAQ score may neglect factors and constraints that must be considered in business reality. These include, for example, measures in assets with a small effect on the BAQ score or measures that serve to maintain safety. Therefore, it is important to note how the BAQ grade is determined. Here, whether financial resources should be exclusively spent on the basis of this quality indicator must be critically questioned. In the BAQ methodology, which is described in Section 2, different assets are weighted differently. Platforms, which account for 30% (see Table 1) of the BAQ grade, have the highest weighting. In reality, this weight is even higher in many cases, since not all asset classes listed in the BAQ methodology are present at every station, and the weightings are redistributed. In addition to the platforms, platform halls and passenger underpasses have a significant impact on the overall grade. Passenger overpasses, windbreaks, floors and staircases, entrance doors, and walls, on the other hand, only have a weighting of 1% or less to the overall grade. This means that assets of this type have hardly any influence on the overall grade. To significantly improve the BAQ grade, the BAQ-optimized control model prioritizes the maintenance or replacement of assets with those having a high impact on the BAQ grade. Accordingly, a significant part of the available budget is allocated to the asset classes with a high weighting for the BAQ grade. Thus, in scenario 4, up to 80% of the budget of a year is only spent on platforms. Other asset classes, such as passenger overpasses, receive a very small part, or even no budget at all, in this scenario due to their low weighting. Consequently, quality strongly diverges between different asset classes. While asset classes with a high weighting are in very good condition, asset classes with a low weighting are in poor condition. Hence, if the exclusive attempt is to optimize the BAQ grade, not all of the assets will be in a good or serviceable condition. Thus, the exclusive consideration of the BAQ grade methodology sets disincentives for control and planning. The divergence of quality conditions in different asset classes can be countered by budget allocation to asset classes and subsequent prioritization within those asset classes, such as in scenario 3. Here, a fixed budget is assigned to each asset class before prioritization so that a specified budget is available for each asset class. BAQ-optimized measures are then selected in the model within the asset class. In this scenario, the BAQ grade also improves compared to the reference scenario. However, all BAQ-optimizing measures can be detected and executed in the model. In reality, this is not necessarily possible due to restrictions such as possible closures, construction capacities, and the bundling of measures. These restrictions are not given in the model; therefore, an exact implementation of the measures from the model cannot be necessarily conducted in reality. Nevertheless, it should be possible to further improve the BAQ grade with the available budget.