Panels (a)-(c) : Routes in the Dutch railways of (a) the train service 3028 from Nijmegen to Alkmaar via Amsterdam, (b) a rolling stock unit used in part of this service and (c) a crew member (partly) executing this service. The schedules for 3 December 2017 are used, a day selected randomly from the dataset. Dark brown lines mark the route they share between Nijmegen and Alkmaar, after which they go their separate ways—marked in light brown lines and yellow arrows. While the service continues along its service route in panel (a) towards Den Helder, the rolling stock unit is coupled in Alkmaar onto another service to the south-east (leaving the service with only part of its original rolling stock)—via Schiphol Airport back to Nijmegen shown in panel (b). Panel (c) shows that the crew member transfers towards another service to the south-west—via Amsterdam to Leiden and The Hague, proceeding via Utrecht to Leiden and eventually ending in Utrecht. If service 3028 would have an initial delay d init > 0, so does the rolling stock and crew executing the service; meaning that if scheduled buffer times for the resource transfers in Alkmaar would be exceeded by the delay (and no replacement resource would be available), then the subsequent services of these resources would become delayed as well. In other words, service 3028’s delay will potentially be transmitted to other services, and subsequently carried to other geographical regions. Panel (d) shows the d init - γ plot: γ remains zero for d init < 23 minutes as the entire delay is absorbed by scheduled buffer times for resource transfers. However, with d init = 23 minutes, a first resource delay overcomes the transfer buffer and adds delay to another service: namely the rolling stock unit in Alkmaar, going towards Nijmegen. As d init grows, more and more transfer buffers are overcome and delay is added to many service lines throughout the country. Panel (e) contains the same information as in panel (d), for for a log-linear plot, revealing the near-exponential ...