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Large-scale disaster response is a global issue. Planners must make effective logistics plans to deliver vital first-aid resources (e.g., medicine, food, clothing, machinery) to affected areas from all over the world. Furthermore, planners must consider surging demand and uncertain transportation situations. To explain the efficiency of distribution plans, this study addresses the resource allocation effectiveness losses, which are the losses caused by the mismatch between supply and demand in affected areas, and the emergency logistics time losses, which are the time losses caused by logistics processes under emergency conditions. A two-stage scheduling method is then proposed that considers random demand and travel time. In consideration of the incompleteness or lack of information in real situations, the scheduling method with Bayesian information updates is proposed by assuming that demand and transportation uncertainty are represented by population transfer rate (PTR) and road affected level (RAL), respectively. Next, a simulation study on Wenchuan earthquake response is conducted to illustrate the proposed method. Finally, the insights derived from the study are provided in the conclusion.