2015 DynamicPricingandLearningHistor
- (Boer, 2015) ⇒ Arnoud V. den Boer. (2015). “Dynamic Pricing and Learning: Historical Origins, Current Research, and New Directions.” In: Surveys in operations research and management science, 20(1). doi:10.1016/j.sorms.2015.03.001
Subject Headings: Dynamic Pricing, Pricing with Learning.
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Highlights
- The historical origins of research on pricing and demand estimation are sketched.
- An in-depth survey of literature on dynamic pricing and learning is given.
- Relations with methodologically related research areas are highlighted.
- Important directions for future research are identified.
Abstract
The topic of dynamic pricing and learning has received a considerable amount of attention in recent years, from different scientific communities. We survey these literature streams: we provide a brief introduction to the historical origins of quantitative research on pricing and demand estimation, point to different subfields in the area of dynamic pricing, and provide an in-depth overview of the available literature on dynamic pricing and learning. Our focus is on the operations research and management science literature, but we also discuss relevant contributions from marketing, economics, econometrics, and computer science. We discuss relations with methodologically related research areas, and identify directions for future research.
1 Introduction
Dynamic pricing is the study of determining optimal selling prices of products or services, in a setting where prices can easily and frequently be adjusted. This applies to vendors selling their products via Internet, or to brick-and-mortar stores that make use of digital price tags. In both cases, digital technology has made it possible to continuously adjust prices to changing circumstances, without any costs or efforts. Dynamic pricing techniques are nowadays widely used in various businesses, and in some cases considered to be an indispensable part of pricing policies. Digital sales environments generally provide firms with an abundance of sales data. This data may contain important insights on consumer behavior, in particular on how consumers respond to different selling prices. Exploiting the knowledge contained in the data and applying this to dynamic pricing policies may provide key competitive advantages, and knowledge how this should be done is of highly practical relevance and theoretical interest. This consideration is a main driver of research on dynamic pricing and learning: the study of optimal dynamic pricing in an uncertain environment where characteristics of consumer behavior can be learned from accumulating sales data.
The literature on dynamic pricing and learning has grown fast in recent years, with contributions from different scientific communities: operations research and management science (OR/MS), marketing, computer science, and economics / econometrics. This survey aims at bringing together the literature from these different fields, and at highlighting some of the older (and sometimes forgotten) literature where many important results and ideas already can be found.
A few literature reviews on dynamic pricing and learning do already exist. Araman and Caldentey (2011) and Aviv and Vulcano (2012, Section 4) review in detail a number of recent studies, mostly from the OR/MS community, and Christ (2011, Section 3.2.1) contains an elaborate discussion of a selection of demand learning studies. Our survey complements these publications by aiming at a larger scope, and, although our main focus is on the OR/MS literature, we also address relevant contributions from computer science, marketing, economics and econometrics.
This survey reviews the literature on dynamic pricing with demand uncertainty. We discuss how this is embedded in the literature on dynamic pricing in general, but do not review all relevant research topics associated with dynamic pricing; for this we refer to Bitran and Caldentey (2003), Elmaghraby and Keskinocak (2003), Talluri and van Ryzin (2004), Phillips (2005), Heching and Leung (2005), G¨onsch et al. (2009), Rao (2009), Chenavaz et al. (2011), Deksnyte and Lydeka (2012) and ¨Ozer and Phillips (2012). We focus on studies where selling price is a control variable; we only scarcely discuss learning in capacity-based revenue management (Talluri and van Ryzin, 2004) or learning in news-vendor / inventory control problems. Neither do we consider mechanism design (Harris and Raviv, 1981, Maskin and Riley, 1984) or auction theory with incomplete information (see e.g. Segal (2003), Babaioff et al. (2011) and the references therein), although there are some similarities with dynamic pricing and learning. Most of the studies that we discuss are written from an (online) retailer perspective. We do not dive into specific details associated with particular application area such as pricing in queueing or telecommunication environments (Mutlu et al., 2012), road pricing (de Palma et al., 2006, Tsekeris and Voß, 2009, Lou, 2013), or electricity pricing (Garcia et al., 2005, Roozbehani et al., 2010), to name a few. Finally, this survey focuses on studies where the seller learns about the demand function, and not on studies where buyers are learning (Bergemann and V¨alim¨aki, 1997, Ottaviani, 1999, Caminal and Vives, 1999, Schlee, 2001, Bose et al., 2006, Bhalla, 2012, Ifrach et al., 2012).
This survey is organized as follows. We review in Section 2 some of the pioneering historical work on pricing and demand estimation, and discuss how this work initially was difficult to apply in practice. In Section 3 we sketch important references and developments for dynamic pricing in general, and in Section 4 we focus on the literature that specifically deals with dynamic pricing and learning. Connections between dynamic pricing and related research areas are addressed in Section 5, and related new research directions are discussed in Section 6.
2 Historical Origins of Pricing and Demand Estimation
Dynamic pricing with learning can be regarded as the combined application of two research fields: (1) statistical learning, specifically applied to the problem of estimating demand functions, and (2) price optimization. Both these fields are already quite old, dating back more than a century.
In this section we briefly describe the historical fundaments out of which dynamic pricing and learning has emerged, by pointing to some key references on static pricing and estimating demand functions that have been important in the progress of the field.
2.1 Demand functions in pricing problems
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References
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2015 DynamicPricingandLearningHistor | Arnoud V. den Boer | Dynamic Pricing and Learning: Historical Origins, Current Research, and New Directions |