Dynamic Pricing with Demand Learning and Reference Effects

Dynamic Pricing with Demand Learning and Reference Effects

Author: Arnoud den Boer

Publisher:

Published: 2020

Total Pages: 75

ISBN-13:

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We consider a seller's dynamic pricing problem with demand learning and reference effects. We first study the case where customers are loss-averse: they have a reference price that can vary over time, and the demand reduction when the selling price exceeds the reference price dominates the demand increase when the selling price falls behind the reference price by the same amount. Thus, the expected demand as a function of price has a time-varying "kink" and is not differentiable everywhere. The seller neither knows the underlying demand function nor observes the time-varying reference prices. In this setting, we design and analyze a policy that (i) changes the selling price very slowly to control the evolution of the reference price, and (ii) gradually accumulates sales data to balance the tradeoff between learning and earning. We prove that, under a variety of reference-price updating mechanisms, our policy is asymptotically optimal; i.e., its T-period revenue loss relative to a clairvoyant who knows the demand function and the reference-price updating mechanism grows at the smallest possible rate in T. We also extend our analysis to the case of a fixed reference price, and show how reference effects increase the complexity of dynamic pricing with demand learning in this case. Moreover, we study the case where customers are gain-seeking and design asymptotically optimal policies for this case. Finally, we design and analyze an asymptotically optimal statistical test for detecting whether customers are loss-averse or gain-seeking.


Behavioral Consequences of Dynamic Pricing

Behavioral Consequences of Dynamic Pricing

Author: David Prakash

Publisher: BoD – Books on Demand

Published: 2022-07-28

Total Pages: 156

ISBN-13: 3754359932

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Digital technologies are driving the application of dynamic pricing. Today, this pricing strategy is used not only for perishable products such as flights or hotel rooms, but for almost any product or service category. With dynamic pricing, retailers frequently adjust their prices over time to respond to factors such as demand, their supply and that of competitors, or the time of sale. Additionally, dynamic pricing allows retailers to take advantage of a large share of consumers' willingness to pay while avoiding losses from unsold products. Ultimately, this can lead to an increase in revenue and profit. However, the application of dynamic pricing comes with great challenges. In addition to the technological implementation, companies have to take into account that dynamic pricing can cause complex and unintended behavioral consequences on the consumer side. The key objective of this dissertation is to provide a deeper understanding of the impact of dynamic pricing on consumer behavior. To this end, this dissertation presents insights from four perspectives. First, how reference prices as a critical component in purchase decisions are operationalized. Second, how customers search for products priced dynamically, differentiated by business and private customers, as well as by different devices used for the search. Third, whether and how dynamic pricing influences the impact of internal reference prices on purchase decisions. Finally, this dissertation demonstrates that consumers perceive price changes as personalized in different purchase contexts, leading to reduced perceptions of fairness and undesirable behavioral consequences.


Consumer-Driven Demand and Operations Management Models

Consumer-Driven Demand and Operations Management Models

Author: Serguei Netessine

Publisher: Springer Science & Business Media

Published: 2009-06-02

Total Pages: 488

ISBN-13: 0387980261

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This important book is by top scholars in supply chain management, revenue management, and e-commerce, all of which are grounded in information technologies and consumer demand research. The book looks at new selling techniques designed to reach the consumer.


Online Learning and Pricing for Multiple Products with Reference Price Effects

Online Learning and Pricing for Multiple Products with Reference Price Effects

Author: Sheng Ji

Publisher:

Published: 2023

Total Pages: 0

ISBN-13:

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We consider the dynamic pricing problem of a monopolist seller who sells a set of mutually substitutable products over a finite time horizon. Customer demand is sensitive to the price of each individual product and the reference price which is formed from a comparison among the prices of all products. To maximize the total expected profit, the seller needs to determine the selling price of each product and also selects a reference product (to be displayed) that affects the consumer's reference price. However, the seller initially knows neither the demand function nor the customer's reference price, but can learn them from past observations on the fly. As such, the seller faces the classical trade-off between exploration (learning the demand function and reference price) and exploitation (using what has been learned thus far to maximize revenue). We propose a dynamic learning-and-pricing algorithm that integrates iterative least squares estimation and bandit control techniques in a seamless fashion. We show that the cumulative regret, i.e., the expected revenue loss caused by not using the optimal policy over $T$ periods, is upper bounded by $O((n^2+n) sqrt{T} log T)$, which is optimal up to a logarithmic factor in terms of the time horizon $T$ and polynomially scaling with the number of products $n$. We also establish the regret lower bound (for any learning policies) to be $ Omega(n^{1.5} sqrt{T})$. We then generalize our analysis to a more general demand model. Finally, our algorithm performs consistently well numerically, outperforming an exploration-exploitation benchmark. We also identify an interesting ``loss-leader'' phenomenon in our computational study.


Intertemporal Price Discrimination Via Reference Price Effects

Intertemporal Price Discrimination Via Reference Price Effects

Author: Zizhuo Wang

Publisher:

Published: 2015

Total Pages: 21

ISBN-13:

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We consider the dynamic pricing problem a monopolistic seller faces when customers arrive in heterogeneous time periods and their purchase decisions are affected by reference prices formed from their past purchase experiences. We illustrate that a new form of price discrimination opportunity exists in such situations, where the seller's optimal pricing strategy is a cyclic one, even when the customers are loss-neutral and their demand functions are identical. This result differs from those in prior studies where the optimal price paths are shown to be asymptotically constant when customer arrival times are homogeneous or when there are no reference price effects, thus is unique due to the interaction between the heterogeneous arrivals and the reference price effects. We also provide the length of the cycle when the demand function is linear. In this era where customer information becomes easier accessible, our results suggest the seller consider this new dimension of price discrimination in conjunction with the old ones, in order to take advantage of the full power of customer data.


Multi-Product Dynamic Pricing with Reference Effects Under Logit Demand

Multi-Product Dynamic Pricing with Reference Effects Under Logit Demand

Author: Mengzi Amy Guo

Publisher:

Published: 2022

Total Pages: 0

ISBN-13:

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We consider an infinite-horizon multi-product dynamic pricing problem with reference effects in a monopolistic setting, where the reference price is an exponentially weighted average of historical prices. In each period, the demand follows the multinomial logit (MNL) model, where the utility depends on both the current price and the reference price, and consumers can have product-differentiated sensitivities to the price and the reference price. We conduct thorough analyses of the myopic pricing policy, including its solution, long-run convergence behavior, and performance guarantee compared to the long-term discounted revenue of the optimal pricing policy. Furthermore, we establish the structural properties of the optimal pricing policy. When consumers are loss-neutral towards all products, we explicitly characterize the optimal pricing policy if it converges to a steady state, and based on our characterization we show that the steady state price can be computed efficiently by a binary search. Interestingly, we find that such a convergence behavior of the optimal pricing policy heavily relies on the upper bound of the admissible price range, and a low price upper bound facilitates the policy to converge. In contrast, when consumers are gain-seeking towards all products, we prove that the optimal pricing policy admits no steady state regardless of the price range. Nevertheless, if consumers are only gain-seeking towards certain but not all products, the optimal pricing policy can potentially be convergent. In addition, our numerical experiments show that loss-aversion over all products does not rule out price fluctuations. This finding is at odds with the classic belief on loss-averse consumers and hence, highlights the significance of accounting for cross-product effects through the MNL demand.


Supermodularity and Complementarity

Supermodularity and Complementarity

Author: Donald M. Topkis

Publisher: Princeton University Press

Published: 2011-02-11

Total Pages: 285

ISBN-13: 140082253X

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The economics literature is replete with examples of monotone comparative statics; that is, scenarios where optimal decisions or equilibria in a parameterized collection of models vary monotonically with the parameter. Most of these examples are manifestations of complementarity, with a common explicit or implicit theoretical basis in properties of a super-modular function on a lattice. Supermodular functions yield a characterization for complementarity and extend the notion of complementarity to a general setting that is a natural mathematical context for studying complementarity and monotone comparative statics. Concepts and results related to supermodularity and monotone comparative statics constitute a new and important formal step in the long line of economics literature on complementarity. This monograph links complementarity to powerful concepts and results involving supermodular functions on lattices and focuses on analyses and issues related to monotone comparative statics. Don Topkis, who is known for his seminal contributions to this area, here presents a self-contained and up-to-date view of this field, including many new results, to scholars interested in economic theory and its applications as well as to those in related disciplines. The emphasis is on methodology. The book systematically develops a comprehensive, integrated theory pertaining to supermodularity, complementarity, and monotone comparative statics. It then applies that theory in the analysis of many diverse economic models formulated as decision problems, noncooperative games, and cooperative games.