Dynamic pricing with automated purchase-reservation algorithms
- PDF / 1,262,722 Bytes
- 9 Pages / 595.276 x 790.866 pts Page_size
- 40 Downloads / 232 Views
RESEARCH ARTICLE
Dynamic pricing with automated purchase‑reservation algorithms Kimitoshi Sato1 Received: 1 May 2020 / Accepted: 11 August 2020 © Springer Nature Limited 2020
Abstract We consider the problem of a firm that sells a perishable product such as airline tickets or hotel rooms with a dynamic pricing scheme in the presence of Internet bots. The bots automatically check for changes in the selling price every few seconds and hold the price for a short period by making a tentative reservation. Since the bots are not willing to buy the product, the bots’ reservation does not generate revenue for the firm. In addition, such a behavior would temporarily increase the price in conjunction with decreasing the inventory level. In this paper, we formulate a dynamic pricing model that accounts for tentative reservations made by bots, and derive an optimal pricing policy so as to maximize the total expected revenue. We show the monotone properties of the optimal price: (1) the optimal price decreases with inventory at any given timestep; (2) the optimal price decreases over time even if there is a temporary inventory decrease due to bot reservations. We demonstrate numerically that the optimal pricing policy is robust against the presence of bots, and further show that, as bot activity increases, the optimal price tends to decrease in the first portion of the sales interval. Keywords Dynamic pricing · Revenue management · Internet bots · Dynamic programming
Introduction The advent of the Internet of Things (IoT) and the increasing prevalence of digital tools have enabled a variety of new ways to use real-time information for customer analysis. One prominent trend has been a growing reliance on initiatives that combine large customer-behavior databases with methods of dynamic pricing (DP)—in which prices are adjusted in response to changing conditions—for purposes such as equalizing demand, using resources effectively, and increasing corporate revenue. While DP is an effective short-term strategy, in the longer term, it risks tarnishing the image of corporations in the eyes of customers, who may remain unconvinced of the significance of price fluctuations. Thus, it is crucial to earn the trust and understanding of customers by offering accurate explanations of pertinent background and the key factors driving price variations.
* Kimitoshi Sato k‑sato@kanagawa‑u.ac.jp 1
Faculty of Engineering, Kanagawa University, 3‑27‑1 Rokkakubashi, Kanagawa‑ku, Yokohama, Kanagawa 221‑8686, Japan
In this study, we consider firms that implement DP by deploying Internet bots (or simply “bots”), which are programs that automatically execute reservation and purchasing processes, and analyze the impact of these bots on revenue and customer surplus (that is, customer satisfaction). More specifically, we focus on the marketplace for sales of event or travel tickets, a sector that, in recent years, has witnessed the deployment of bots for purposes such as assessing the availability of seats, searching for competitive prices, identify
Data Loading...
