Landside operations in the air cargo industry are subject to strongly fluctuating demand with daily peak- and off-peak hours, which result in delays, unreliability and high costs for the entire chain. The purpose of this study is to develop and evaluate (unassisted) off-peak hour pickup and delivery (OHP&D) schemes that are supported by decision-makers and improve the performance. The methodology combines value-focused thinking (VFT) and the Bayesian Best-Worst Method (BWM). VFT ensures that the actor-specific objectives of decision-makers are central throughout the entire decision process. BWM determines the objective weights based on actor-specific sets and evaluations. We find that the risk level is an important evaluation criterion for all actors in this industry and that weights vary significantly across actors. Nine possible OHP&D schemes were generated with the value-based approach. When aggregating the utilities of the individual DMs, the results show that an unassisted OHP&D scheme with dedicated transport, information sharing, a priority lane and Carriage paid to liability agreements is the preferred concept. This concept has the potential to decrease costs up to 65%, driven by a reduction in truck waiting hours of 63%.