Topic
Dynamic pricing
About: Dynamic pricing is a research topic. Over the lifetime, 4144 publications have been published within this topic receiving 91390 citations. The topic is also known as: surge pricing & demand pricing.
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TL;DR: It is shown that price skimming arises as the unique pure-strategy Markov perfect equilibrium in the game under a simple condition and that unilateral commitment to static pricing by either firm generally improves profits of both firms.
Abstract: We consider dynamic pricing competition between two firms offering vertically differentiated products to strategic customers who are intertemporal utility maximizers. We show that price skimming arises as the unique pure-strategy Markov perfect equilibrium in the game under a simple condition. Our results highlight the asymmetric effect of strategic customer behavior on quality-differentiated firms. Even though the profit of either firm decreases as customers become more strategic, the low-quality firm suffers substantially more than the high-quality firm. Furthermore, we show that unilateral commitment to static pricing by either firm generally improves profits of both firms. Interestingly, both firms enjoy higher profit lifts when the high-quality firm commits rather than when the low-quality firm commits.
This paper was accepted by Yossi Aviv, operations management.
212 citations
TL;DR: It is shown that the smallest achievable revenue loss in T periods, relative to a clairvoyant who knows the underlying demand model, is of order T in the former case and of order log T inthe latter case.
Abstract: We consider a monopolist who sells a set of products over a time horizon of T periods. The seller initially does not know the parameters of the products' linear demand curve, but can estimate them based on demand observations. We first assume that the seller knows nothing about the parameters of the demand curve, and then consider the case where the seller knows the expected demand under an incumbent price. It is shown that the smallest achievable revenue loss in T periods, relative to a clairvoyant who knows the underlying demand model, is of order T in the former case and of order log T in the latter case. To derive pricing policies that are practically implementable, we take as our point of departure the widely used policy called greedy iterated least squares ILS, which combines sequential estimation and myopic price optimization. It is known that the greedy ILS policy itself suffers from incomplete learning, but we show that certain variants of greedy ILS achieve the minimum asymptotic loss rate. To highlight the essential features of well-performing pricing policies, we derive sufficient conditions for asymptotic optimality.
210 citations
TL;DR: In this article, the authors used the results of a dynamic pricing experiment for households in the District of Columbia to determine whether the reduction in demand associated with an hourly price signal is economically different from the demand reduction associated with the equivalent price signal that is four times longer in duration.
Abstract: This paper uses the results of a dynamic pricing experiment for households in the District of Columbia to determine whether the reduction in demand associated with an hourly price signal is economically different from the demand reduction associated with an equivalent price signal that is four times longer in duration. For both regular and all-electric customers, the percentage demand reduction associated with a given percentage increase in the hourly price is approximately equal to the percentage demand reduction associated with the same percentage price increase of a much longer duration.
210 citations
TL;DR: In this paper, a bi-level optimal dispatching model for a community integrated energy system (CIES) with an EVCS in multi-stakeholder scenarios is established, and an integrated demand response program is designed to promote a balance between energy supply and demand while maintaining a user comprehensive satisfaction within an acceptable range.
Abstract: A community integrated energy system (CIES) with an electric vehicle charging station (EVCS) provides a new way for tackling growing concerns of energy efficiency and environmental pollution, it is a critical task to coordinate flexible demand response and multiple renewable uncertainties. To this end, a novel bi-level optimal dispatching model for the CIES with an EVCS in multi-stakeholder scenarios is established in this paper. In this model, an integrated demand response program is designed to promote a balance between energy supply and demand while maintaining a user comprehensive satisfaction within an acceptable range. To further tap the potential of demand response through flexibly guiding users energy consumption and electric vehicles behaviors (charging, discharging and providing spinning reserves), a dynamic pricing mechanism combining time-of-use and real-time pricing is put forward. In the solution phase, by using sequence operation theory (SOT), the original chance-constrained programming (CCP) model is converted into a readily solvable mixed-integer linear programming (MILP) formulation and finally solved by CPLEX solver. The simulation results on a practical CIES located in North China demonstrate that the presented method manages to balance the interests between CIES and EVCS via the coordination of flexible demand response and uncertain renewables.
209 citations
TL;DR: In this article, the authors collected data on the price of a single room booked in advance (from three months to a single day), from almost 1000 hotels in eight European capital cities, and analyzed pricing strategies by means of descriptive statistics, box plots and econometric panel data techniques.
206 citations