An examination of dynamic ticket pricing and secondary market price determinants in Major League Baseball

2014 ◽  
Vol 17 (2) ◽  
pp. 145-159 ◽  
Author(s):  
Stephen L. Shapiro ◽  
Joris Drayer
2007 ◽  
Vol 21 (3) ◽  
pp. 407-437 ◽  
Author(s):  
Daniel A. Rascher ◽  
Chad D. McEvoy ◽  
Mark S. Nagel ◽  
Matthew T. Brown

Sport teams historically have been reluctant to change ticket prices during the season. Recently, however, numerous sport organizations have implemented variable ticket pricing in an effort to maximize revenues. In Major League Baseball variable pricing results in ticket price increases or decreases depending on factors such as quality of the opponent, day of the week, month of the year, and for special events such as opening day, Memorial Day, and Independence Day. Using censored regression and elasticity analysis, this article demonstrates that variable pricing would have yielded approximately $590,000 per year in additional ticket revenue for each major league team in 1996, ceteris paribus. Accounting for capacity constraints, this amounts to only about a 2.8% increase above what occurs when prices are not varied. For the 1996 season, the largest revenue gain would have been the Cleveland Indians, who would have generated an extra $1.4 million in revenue. The largest percentage revenue gain would have been the San Francisco Giants. The Giants would have seen an estimated 6.7% increase in revenue had they used optimal variable pricing.


2012 ◽  
Vol 26 (6) ◽  
pp. 532-546 ◽  
Author(s):  
Stephen L. Shapiro ◽  
Joris Drayer

In 2010, the San Francisco Giants became the first professional team to implement a comprehensive demand-based ticket pricing strategy called dynamic ticket pricing (DTP). In an effort to understand DTP as a price setting strategy, the current investigation explored Giants’ ticket prices during the 2010 season. First, the relationship between fixed ticket prices, dynamic ticket prices, and secondary market ticket prices for comparable seats were examined. In addition, seat location and price changes over time were examined to identify potential effects on ticket price in the primary and secondary market. Giants’ ticket price data were collected for various games throughout the 2010 season. A purposive selection of 12 games, which included (N= 1,316) ticket price observations, were chosen in an effort to include a multitude of game settings. Two ANOVA models were developed to examine price differences based on pricing structure, market, section, and time. Findings showed significant differences between fixed ticket prices, dynamic ticket prices, and secondary market ticket prices, with fixed ticket prices on the low end and secondary market ticket prices on the high end of the pricing spectrum. Furthermore, time was found to have a significant influence on ticket price; however, the influence of time varied by market and seat location. These findings are discussed and both theoretical and practical implications are considered.


Author(s):  
Daniel A. Rascher ◽  
Andrew D. Schwarz

This article explores the ticket pricing behavior of the clubs to illustrate the theory of price discrimination. An example presented shows how useful it is to be flexible in recognizing that while a box seat to a game is not an identical product to an upper reserved seat at the same game, the two tickets sufficiently share the core product that the price discrimination framework is useful for analyzing pricing, even if the products are clearly not identical on every dimension of quality. It is stated that every single Major League Baseball ticket is sold under some form of price discrimination. As teams grow increasingly sophisticated in their pricing strategies, price discrimination is becoming more precise, more widespread, and more profitable, while at the same time providing more opportunities for more fans to find tickets at a price they are willing to pay.


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