Dynamic Pricing for the Open Online Ticket System: A Surrogate Modeling Approach

IF 7 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

Smart Cities Pub Date : 2023-05-09 DOI:10.3390/smartcities6030063

Elizaveta Stavinova, Ilyas Varshavskiy, P. Chunaev, Ivan Derevitskii, A. Boukhanovsky

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引用次数: 0

Abstract

Dynamic pricing is frequently used in online marketplaces, ticket sales, and booking systems. The commercial principles of dynamic pricing systems are often kept secret; however, their application causes complex changes in human behavior. Thus, a scientific tool is needed to evaluate and predict the impact of dynamic pricing strategies. Publications in the field lack a common quality evaluation methodology, public data, and source code, making them difficult to reproduce. In this paper, a data-driven method, DPRank, for evaluating dynamic pricing systems is proposed. DPRank first builds a surrogate price elasticity of demand model using public data generated by a hidden dynamic pricing model, and then applies the surrogate model to build an exposed dynamic pricing model. The hidden and exposed dynamic pricing models were then systematically compared in terms of quality using a Monte Carlo simulation in terms of a company’s revenue. The effectiveness of the proposed method was tested on the dataset collected from the website of a Russian railway passenger carrier company. Depending on the train type, the quality difference between the hidden and exposed models can vary by several dozen percent on average, indicating the potential for improving the existing (hidden) company’s dynamic pricing model.

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开放在线票务系统的动态定价:代理模型方法

动态定价经常用于在线市场、售票和预订系统。动态定价系统的商业原则往往是保密的；然而，它们的应用会导致人类行为的复杂变化。因此，需要一种科学的工具来评估和预测动态定价策略的影响。该领域的出版物缺乏通用的质量评估方法、公共数据和源代码，难以复制。本文提出了一种数据驱动的动态定价系统评估方法DPRank。DPRank首先利用隐藏动态定价模型生成的公共数据建立需求的替代价格弹性模型，然后应用该替代模型建立暴露动态定价模型。然后，根据公司收入的蒙特卡洛模拟，系统地比较了隐藏和暴露的动态定价模型的质量。在从俄罗斯铁路客运公司网站收集的数据集上测试了所提出方法的有效性。根据列车类型的不同，隐藏和暴露模型之间的质量差异平均可能相差几十个百分点，这表明改进现有（隐藏）公司动态定价模型的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Smart Cities Multiple-

CiteScore

11.20

自引率

6.20%

发文量

审稿时长

11 weeks

期刊介绍： Smart Cities (ISSN 2624-6511) provides an advanced forum for the dissemination of information on the science and technology of smart cities, publishing reviews, regular research papers (articles) and communications in all areas of research concerning smart cities. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible, with no restriction on the maximum length of the papers published so that all experimental results can be reproduced.