A general multiple distributed lag framework for estimating the dynamic effects of promotions

Eelco Kappe, Ashley Stadler Blank, Wayne S. Desarbo

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


Game attendance resulting from ticket sales is the single largest revenue stream for Major League Baseball (MLB) teams. We propose a general multiple distributed lag framework following the Koyck family of models for estimating MLB attendance drivers and focus specifically on the differential direct and carryover effects of in-game promotions. By setting various model constraints, the proposed framework incorporates different forms of serial correlation and promotion-specific dynamic effects. Using information model-selection heuristics, we select an optimal model of attendance drivers for the Pittsburgh Pirates' 2010-2012 MLB seasons. We demonstrate that our newly proposed model with an unrestricted serial correlation structure performs best. We find that although kids promotions have the highest direct effect on attendance, giveaway and entertainment promotions have substantial carryover effects and the largest total effects. We use our results to optimize the Pirates' promotional schedule and find that a reallocation of resources across promotional categories can increase profits between 39% and 88%.

Original languageEnglish (US)
Pages (from-to)1489-1510
Number of pages22
JournalManagement Science
Issue number6
StatePublished - Jun 2014

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research


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