Dynamic Pricing Decisions and Seller-Buyer Interactions under Capacity Constraints

Abstract

Focusing on sellers' pricing decisions and the ensuing seller-buyer interactions, we report an experiment on dynamic pricing with scarcity in the form of capacity constraints. Rational expectations equilibrium solutions are constructed and then tested experimentally with subjects assigned the roles of sellers and buyers. We investigate behavior in two between-subject conditions with high and moderate levels of capacity. Our laboratory market exhibits strategic sophistication: the price offers of sellers and the buyers' aggregate responses largely approximate equilibrium predictions. We also observe systematic deviations from equilibrium benchmarks on both sides of the market. Specifically, in our experiment the sellers are boundedly strategic: their prices often exhibit strategic adjustments to profit from buyers with limited strategic sophistication, but they are also often biased towards equilibrium pricing even when that would not be ex-post optimal.

Factors Influencing Consumer Behavior and Prospective Purchase Decisions in a Dynamic Pricing Environment—An Exploratory Factor Analysis Approach

“…The most modern technology, which uses cookies and clickstream data, etc., allows sellers to make real-time price changes at minimum cost by analyzing the customer traffic, customer demographics, and preference data, etc. (Elmaghraby and Keskinocak 2003;Mak et al 2018).…”

Dynamic Pricing in the Presence of Myopic and Strategic Consumers: Theory and Experiment

“…While this is, technically speaking, different from the continuum of consumers that our model assumes, the discretization is fine enough to represent a continuum well (Mago and Dechenaux 2009). Note that this implementation eliminates any uncertainty about the valuation distribution, which is consistent with our model premises; it facilitates learning, and is similar to the "no-replacement" procedure used in Mak et al (2015) to assign (human) buyers valuations from a fixed set of uniformly distributed values. As discussed in the literature review section, the decision to automate consumers represents a strategic choice in our experimental designit allows us to isolate the impact of strategic consumer behavior, as well as to capture a realistic retail-like setting where there are many more buyers than sellers.…”

“… and Mak et al. for an exception), such that each individual buyer's (possibly irrational) behavior plays a major role in the pricing outcome – if each single buyer is indeed 2‐3 times more likely to myopically buy early (as in Mak et al. ), sellers may benefit from overpricing relative to rational equilibrium predictions.…”

“…Neither of these studies, however, consider strategic consumers. Mak et al (2015) consider retailers' pricing with strategic consumers in a unique setting where both strategic buyers and sellers are played by human subjects. Our work (in which buyers are automated, but a mixture is considered) complements their study.…”

Believing in Analytics: Managers’ Adherence to Price Recommendations from a DSS

“…Managers' behavioral biases in revenue management have been studied mostly in theoretical or laboratory papers; see Özer and Zheng (2012) for a review. Some of the topics these experimental papers study are adjustment to inventory levels (Bearden et al 2008); framing effects (Kocabıyıkoglu et al 2018); managers' physiological conditions (Bendoly 2011(Bendoly , 2013; and how pricing interacts with other considerations, such as inventory (Kocabıyıkoglu et al 2015), production quantity (Ramachandran et al 2018), or buyer/seller role (Mak et al 2018).…”