NBA Primary Market Ticket Consumers: Ex Ante Expectations and Consumer Market Origination

We add to the recent ticket market literature by using a unique, disaggregated, and proprietary data set of primary market ticket sales transactions from a National Basketball Association team that includes previously unavailable information on date of purchase, customer location, and other consumer demographics. We find that local and out-of-market fans differ in their total purchase amounts, with out-of-market fans spending more than local consumers, on average, and differential spending effects based on the home team win probability. In particular, this differential behavior has important implications for Rottenberg’s uncertainty of outcome hypothesis. We find evidence that interest in visiting team quality dominates interest in perceived contest uncertainty, fitting the reference-dependent preference model in the context of low local team quality. Further, these findings also have important implications related to market segmentation and dynamic ticket pricing in professional sport.

A New Age of Demand-Based Pricing: An Examination of Dynamic Ticket Pricing and Secondary Market Prices in Major League Baseball

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.