Abstract
ABSTRACTThe strategy of overbooking capacity is commonly practiced in business that accepts reservations and subsequently runs the risk of cancellations and no-shows. Traditional overbooking models are mainly based on the assumption that decision-makers are rationally loss-neutral. This paper seeks the optimal overbooking policies for managers with a loss-averse preference towards the loss of compensations when excessive customers actually show up. This study presents overbooking models in both single-period and multiperiod settings in which the loss-averse preference is described with a ¡°kinked¡± piecewise-linear utility function. The analysis demonstrates the optimal policy exhibiting a booking limit structure in both settings. The manager accepts reservation requests up to a booking limit if the number of initial reservations is less than that booking limit, and otherwise declines reservation requests. This study finds that loss-averse managers are cautious and prefer lower booking limits compared to loss-neutral managers. From numerical studies, we investigate the biases between predictions of loss-neutral and loss-averse models. This study also investigates how the optimal policy changes based on certain parameters, including the decision-maker's degree of loss-aversion.
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