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.

Demand Management and Inventory Control for Substitutable Products

Abstract: This paper studies dynamic inventory and pricing decisions for a set of substitutable products over a flnite planning horizon. We present a general stochastic, price-dependent demand model that unifles many commonly used demand models in the literature. Unsatisfled demands are backlogged. There are linear purchasing, inventory-holding, and backordering costs. The objective is to maximize the total expected discounted proflt. The original formulation is not jointly concave in the decision variables and is therefore intractable. One key observation here is that the problem becomes jointly concave if we work with the inverse of the price vector { the market share vector. We characterize the optimal policy and develop algorithms to compute it. We establish conditions under which the optimal policy demonstrates certain monotonicity property, which, in turn, can greatly enhance computation. We also analyze the myopic policy and its optimality, and present a numerical study to illustrate the interplay of the pricing and inventory decisions.

Modeling and optimization of multimodal urban network with limitedparking and dynamic pricing

Abstract: Cruising-for-parking is a critical mobility issue in urban cities. The cost and accessibility of parking significantly influence people’s travel behavior (such as mode choice) and facility choice (on-street or garage parking). Furthermore, parking affects traffic performance for all users of a city. Car-users may have to cruise for on-street parking space before reaching destinations and cause delays eventually to everyone, even users with destinations outside limited parking areas. It is therefore crucial to understand the impact of parking on mobility and identify traffic management policies to avoid the negative externalities. Most existing studies of parking either fall short in reproducing the dynamic spatiotemporal features of traffic congestion in general and the cruising-for-parking phenomenon, or require data that are expensive and difficult to collect. In this paper, the authors propose an aggregated dynamic model for multimodal mobility with the consideration of parking, and utilize the model to evaluate management policies, such as parking pricing. The proposed approach is based on the recent development of the low-scattered Macroscopic Fundamental Diagram (MFD), which demonstrated decent representation of the complex dynamics of transport system at network-level for single-mode and bi-modal (car and bus) urban networks. The MFD-based bi-modal modeling framework is extended with a parking module where cruising delay and change of behavior (e.g. mode choice and parking facility choice) caused by parking are taken into account. Pricing strategies of parking are then developed to reduce congestion and travel cost. Result of a case study shows that traffic performance under various types of parking policies can be investigated and close-to-optimum pricing schemes can be obtained. Furthermore, parking market competition can be simulated and studied with the proposed modeling approach.

Dynamic Pricing and the Direct-to-Customer Model in the Automotive Industry

Abstract: The Internet is changing the automotive industry as the traditional manufacturer and dealer structure faces increased threats from third party e-tailers. Dynamic pricing together with the Direct-to-Customer business model can be used by manufacturers to respond to these challenges. Indeed, by coordinating production and inventory decisions with dynamic pricing, the automotive industry can increase profits and improve supply chain performance. To illustrate these benefits, we discuss a strategy that incorporates pricing, production scheduling, and inventory control under production capacity limits in a multi-period horizon. We show that under concave revenue curves, a greedy algorithm provides the optimal solution, and we describe extensions to the model such as multiple products sharing production capacity. Using computational analysis, we quantify the profit potential and sales variability due to dynamic pricing, and we suggest that it is possible to achieve significant benefit with few price changes.

Integrating Home Energy Simulation and Dynamic Electricity Price for Demand Response Study

Abstract: This paper studies how to develop and evaluate demand response strategies from the consumer's perspective through a computational experiment approach. The proposed approach includes a home energy consumption simulator, a demand response mechanism obtained through optimization, particle swam or heuristic method, and an integrative computing platform that combines the home energy simulator and MATLAB together for demand response development and evaluation. Several demand response strategies are developed and evaluated through the computational experiment technique. The paper investigates and compares characteristics of different demand response strategies and how they are affected by dynamic pricing tariffs, seasons, and weather. Case studies are conducted by considering home energy consumption, dynamic electricity pricing schemes, and demand response methods.