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Highlights
| • | We examined market factors that influence ticket price. | ||||
| • | Pricing determinants were focused on dynamic ticket pricing and secondary market prices. | ||||
| • | Four regression models were developed to examine demand-based price determinants. | ||||
| • | A variety of factors significantly influenced dynamic ticket price and secondary market price. Determinants ranged from 10 to 13 variables in each model. | ||||
| • | Significant variables included an emphasis on team and individual performance factors, ticket-related factors, and time-related factors. | ||||
Abstract
Over the past several years, professional sport organizations have started to shift from cost-based ticket pricing strategies to a demand-based focus, where price considerations are driven, in part, by market demand. Dynamic ticket pricing (DTP), where prices fluctuate daily based on market factors, evolved from this transition. The motivation for DTP stems from the significant growth of the secondary ticket market, where ticket prices are almost completely demand driven. One issue with this strategy is the limited understanding of specific factors that influence dynamically priced tickets and secondary market tickets. The current study examined price determinants in the primary market where DTP has been implemented and comparable tickets in the secondary market. Four regression models were developed for this purpose. The first two models examined factors influencing dynamic ticket price. Both DTP models were found to be significant, explaining 91.4% and 70.8% of the variance in dynamic price, respectively. The second two models examined factors influencing secondary market ticket price. Both secondary market models were found to be significant, explaining 82.7% and 79.7% of the variance in secondary market price, respectively. There were many consistencies between models, including an emphasis on team and individual performance factors, ticket-related factors, and time-related factors. However, there were a number of unique aspects to each model, which may help sport managers develop pricing strategies that better reflect market demand for sport