Simulation Modeling and Analysis
Simulation Modeling and Analysis
Marketing Science
Flow Management to Optimize Retail Profits at Theme Parks
Operations Research
Managing customers as investments the strategic value of customers in the long run
Managing customers as investments the strategic value of customers in the long run
Handbook of Marketing Decision Models
Handbook of Marketing Decision Models
Functional Data Analysis with R and MATLAB
Functional Data Analysis with R and MATLAB
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Despite the economic significance of the theme park industry and the huge investments needed to set up new attractions, no marketing models exist to guide these investment decisions. This study addresses this gap in the literature by estimating a response model for theme park attendance. The model not only determines the contribution of each attraction to attendance, but also how this contribution is distributed within and across years. The model accommodates saturation effects, which imply that the impact of a new attraction is smaller if similar attractions are already present. It also captures reinforcement effects, meaning that a new attraction may reinforce the drawing power of similar extant attractions, especially when these were introduced recently. The model is calibrated on 25 years of weekly attendance data from the Efteling, a leading European theme park. Our return on investment calculations show that it is more profitable to invest in multiple smaller attractions than in one big one. This finding is in remarkable contrast with the current “arms race” in the industry. Furthermore, even though thrill rides tend to be more effective than theme rides, there are conditions under which one should consider to switch to the latter.