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.

Agents, system and method for dynamic pricing in a reputation-brokered, agent-mediated marketplace

Abstract: Agent-mediated commerce method and system, and agents for use therein. Seller agents may offer services at prices that vary over time, based on past experiences. Buyer agents may be configured by their users according to time and constraints, budget and the importance of a specific task. Buyer agents try, probabilistically, to maximize their owners' utilities (in part, by estimating the expected performance of each seller based on the reputation of that seller in the relevant marketplace. Buying agents may reveal only their time constraints and descriptions of the tasks (services) desired to the sellers. Seller agents bid for the offered tasks and base their bids at least partly on their owners' reputations, their time availability, the difficulty of the task and the current demand on the marketplace. Seller reputations are updated in a collaborative fashion based on seller performance. Seller agents employ dynamic pricing mechanisms, including specifically profit maximizing reputation followers.

Dynamic Pricing Through Discounts for Optimizing Multiple-Class Demand Fulfillment

Abstract: In a multiple-customer-class model of demand fulfillment for a single item, we consider the use of dynamic price discounts to encourage backlogging of demand for customer classes denied immediate service. Customers are assumed to arrive over several stages in a period, and customer classes are distinguished by their contractual price and sensitivity to discounts. Through dynamic programming we determine the optimal discounts to offer, assuming a linear model for the sensitivity of customers to such inducements. We show that customers are served in class order, and allocation of inventory to demand is determined by considering the current number of customers backlogged, as well as the current inventory position. Through comparison to a naive supplier allocating inventory first come/first served with no discounting, we show that profits are primarily influenced by the allocation of capacity, and the use of price discounts primarily benefits the second-class customers overall fill rate. Heuristics for implementation of the solution in real-time settings are given.

Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes

Abstract: Modernization of electricity networks is currently being carried out using the concept of the smart grid; hence, the active participation of end-user consumers and distributed generators will be allowed in order to increase system efficiency and renewable power accommodation. In this context, this paper proposes a comprehensive methodology to optimally control lead-acid batteries operating under dynamic pricing schemes in both independent and aggregated ways, taking into account the effects of the charge controller operation, the variable efficiency of the power converter, and the maximum capacity of the electricity network. A genetic algorithm is used to solve the optimization problem in which the daily net cost is minimized. The effectiveness and computational efficiency of the proposed methodology is illustrated using real data from the Spanish electricity market during 2014 and 2015 in order to evaluate the effects of forecasting error of energy prices, observing an important reduction in the estimated benefit as a result of both factors: 1) forecasting error and 2) power system limitations.

Dynamic pricing in the presence of reference price effect and consumer strategic behaviour

Abstract: This paper presents a model for designing two-stage dynamic pricing strategies when the seller faces strategic consumers in the presence of a reference price effect. The consumers form the utilitie...