Problem definition: We investigate surge pricing in ride-hailing platforms from a temporal perspective, highlighting strategic behavior by riders and drivers and that drivers respond to surge pricing much more slowly than riders do. Academic/practical relevance: Surge pricing in ride-hailing platforms is a pivotal and controversial subject. Despite abundant anecdotal evidence, strategic behavior by riders and drivers has not been formally studied in the literature. Methodology: We adopt and analyze a classic two-period, game-theoretical model as in the strategic consumer literature. Results: We identify two types of equilibrium pricing strategies. The first consists of a short-lived, sharp price surge followed by a lower price, which we refer to as skimming surge pricing (SSP). The second consists of a low initial price followed by a higher price, which we refer to as penetration surge pricing (PSP). We find that PSP equilibria are generally superior to SSP equilibria when both exist but require platforms to share demand–supply information with drivers. Managerial implications: The SSP equilibrium rationalizes the controversial sharp surge-pricing practice: the short-lived sharp price surge causes many high-value riders to voluntarily wait out the initial surge period, which attracts additional drivers to the region to serve riders at a much lower price than the initial surge price. The theoretically superior PSP equilibrium suggests that a vastly different approach may improve surge pricing and highlights the potential value and importance for platforms to share demand–supply information with drivers.

This study examines the design of appointment scheduling policies with considerations of not only the conventional factors, for example, the random consultation time and multiple patient types, but also of a new factor, particularly, patient unpunctuality, that is, one patient may arrive earlier or later than the appointment time. Patient unpunctuality negatively affects the appointment scheduling system, for example, such behaviour, reduces provider productivity and clinical efficiency, increases health care costs, and limits the ability of a clinic to serve its patients population by reducing the clinic’s effective capacity. In this study, while considering patient unpunctuality, we first introduce an analytical model and show the optimality of a fixed-interval policy for a simplified two-patient model. Motivated by the result, we propose an easy-to-implement heuristic policy with a simple structure using a simulation framework to improve the performance of the appointment scheduling system. The simulation result shows that our policy is overwhelmingly preponderant in current practice. We also measure the effect of patient unpunctuality and other factors. Actual data are used to add realism to the input parameters, and practical guidelines are developed for appointment scheduling.