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Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/36704

Title: Superstars power, mining the paths to stars’ persuasion
Author(s): Suárez Vázquez, Ana
Montañés Roces, Elena
Keywords: Movie industry
Star power
Machine learning
Issue date: Dec-2015
Publisher: Springer
Publisher version: http://dx.doi.org/10.1007/s10614-015-9540-5
Citation: Computational Economics, p. 1-15 (2015); doi:10.1007/s10614-015-9540-5
Format extent: p. 1-15
Abstract: This paper analyzes the influence of star power on the cinema market. The study adopts two gauges of star power, one based on the industry’s opinion and one based on the market’s interest. The article merges contributions in the persuasion and cinema market literatures to examine the influence of star power over spectators. This study use machine learning methods based on support vector ordinal regression to analyze the paths to superstars’ persuasion. The present research shows differences in the persuasion effect of star power based on the industry and star power based on the market. Similarly, there are differences in the influence of star power among men and women. The results of this study help to explain the mixed findings of previous research on superstars’ power
URI: http://hdl.handle.net/10651/36704
ISSN: 0927-7099
Sponsored: The paper was finished during the first author’s stay as visiting scholar at the Marketing Department of the University of Maryland. Financial support from the Cátedra Extraordinaria de Distribución Comercial de la Fundación Ramón Areces is gratefully acknowledged
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