Since the appearance of mechanized rail transport systems in England in the 1820s, the railway has developed to a great extent and has become the primary mode of longdistance land transportation for people as well as for bulk material across the world. What began with steam locomotives, gradually made way for diesel and then to electric engines. Over the past couple of centuries, with the increase in importance of the railway to economy, the complexity of railway networks and consequently the decision-making involved with railway organizations have also increased significantly. With a great deal of decision-making involved in managing different aspects of the railway, every decision made by the management of railway organizations has a profound impact on profitability.
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.
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