\subsection{Case Study Dataset}
\label{data}

The studied dataset consists of a meal delivery platform's entire
    transactional data covering the French market from launch in February of
    2016 to January of 2017.
The platform operated in five cities throughout this period and received a
    total of 686,385 orders.
The forecasting models were developed based on the data from Lyon and Paris in
    the period from August through December; this ensures comparability across
    cities and avoids irregularities in demand assumed for a new service
    within the first operating weeks.
The data exhibit a steady-state as the UDP's service area remained
    unchanged, and the numbers of orders and of couriers grew in lock-step and
    organically.
This does not mean that no new restaurants were openend: If that happened, the
    new restaurant did not attract new customers, but demand was shifted from
    other member restaurants.
Results are similar in both cities, and we only report them for Paris for
    greater conciseness.
Lastly, the platform recorded all incoming orders, and lost demand does not
    exist.
See \ref{dataset} for details on the raw data.