Effects of Performance Schedules on Event Ticket Sales

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2009

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Event scheduling is one of many important decisions facing event marketers in the entertainment industry (i.e., how should multiple performances be scheduled across markets, across venues, and over time?). While there is ample research examining the issues of costs and constraints associated with such a decision, virtually no research exists to examine the impact of these decisions on consumer demand. Hence, the objective of this dissertation is to examine how consumers respond to event marketers' scheduling decisions.

First, a scheduling effect may arise from performances within a market. When performances are scheduled closely in distance or time, their similarity in venue locations or performance dates may result in a stronger relationship and influence ticket sales. This relationship may have a positive effect on ticket sales because the similarity could signal the quality of an event and suggest the desirability of these performances. Thus, these performances attract more consumers and sell more tickets. However, the relationship could be negative. When performances are close in distance or time, they become direct substitutes and compete for consumer patronage.

Another effect arises from an event distribution across markets. When an event travels from one market to another and each market has a different performance schedule, the word of mouth of this event may accumulate and carry over to later markets. If so, market sales may be a good proxy of word of mouth. How well (or poorly) an event sells in preceding markets may affect ticket sales in following markets.

This dissertation consists of three essays to examine the abovementioned scheduling effects. We contact a national ticket seller to acquire a dataset containing ticket sales of a family event traveling across 42 markets. The first essay analyzes a performance schedule in one metropolitan market and investigates the scheduling effect on ticket sales. The second essay employs all performance schedules in 42 markets to study heterogeneous market responses and propose explanatory factors. Finally, the third essay incorporates the distribution sequence of this event and examines whether ticket sales in preceding markets have a carryover effect to influence ticket sales in later markets.

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