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The objective of the study is to develop a parsimonious model to predict the box office success of a Bollywood movie before its release. A movie is considered successful if the revenue generated is greater than its budget, in other words, a Revenue to Budget Ratio (RBR) greater than 1. An original data set of 1698 Hindi movies released across a period of 13 years is used to identify the success factors of a movie in the Indian context. Predictive models are developed using traditional methodologies like multiple regression and logistic regression, as well as, contemporary approaches like regression trees and classification trees. The results highlight a unique mix of elements that a producer should consider to ensure the success of a movie in the highly competitive Indian movie market.