This paper studies the problem of purchasing and allocating copies of movies to multiple stores of a movie rental chain. A unique characteristic of this problem is the return process of rented movies. We formulate this problem for new movies as a newsvendor-like problem with multiple rental opportunities for each copy. We provide demand and return forecasts at the store-day level based on comparable movies. We estimate the parameters of various demand and return models using an iterative maximum-likelihood estimation and Bayesian estimation via Markov chain Monte Carlo simulation. Test results on data from a large movie rental firm reveal systematic underbuying of movies purchased through revenue-sharing contracts and overbuying of movies purchased through standard (nonrevenue-sharing) ones. For the movies considered, our model estimates an increase in the average profit per title for new movies by 15.5% and 2.5% for revenue sharing and standard titles, respectively. We discuss the implications of revenue sharing on the profitability of the rental firm.
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Baron et al. (2010) studied this question.
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