Understanding preferences for motion pictures
AbstractOf interest in the consumer behavior field are the drivers of experiential and aesthetic consumption. This paper considers these questions in the context of the motion picture industry. Most motion picture industry studies use secondary data to elucidate a relationship between movie attributes (genre, star power, critical reviews, distribution strategy, etc.) and box-office revenues. The study gathers primary data from 225 survey respondents in New Zealand to further understand the factors influencing the purchase decision-making process of movie-going consumers. The study uses a factor-analytic approach to map the different genres in attribute space, and to understand the drivers of choice. Overall, the results show genre, movies based on true stories, critical reviews, word-of-mouth, country of origin, pricing strategy as well as star and director power significantly impact consumers' movie choices.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Business Research.
Volume (Year): 64 (2011)
Issue (Month): 8 (August)
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Web page: http://www.elsevier.com/locate/jbusres
Factor-analytic Conjoint analysis Motion picture Aesthetics;
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- Vag, Andras, 2007. "Simulating changing consumer preferences: A dynamic conjoint model," Journal of Business Research, Elsevier, vol. 60(8), pages 904-911, August.
- Sethuraman, Raj & Kerin, Roger A. & Cron, William L., 2005. "A field study comparing online and offline data collection methods for identifying product attribute preferences using conjoint analysis," Journal of Business Research, Elsevier, vol. 58(5), pages 602-610, May.
- Elrod, Terry & Keane, Michael, 1995. "A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data," MPRA Paper 52434, University Library of Munich, Germany.
- Arthur De Vany & W. Walls, 1999. "Uncertainty in the Movie Industry: Does Star Power Reduce the Terror of the Box Office?," Journal of Cultural Economics, Springer, vol. 23(4), pages 285-318, November.
- Skilton, Paul F., 2009. "Knowledge based resources, property based resources and supplier bargaining power in Hollywood motion picture projects," Journal of Business Research, Elsevier, vol. 62(8), pages 834-840, August.
- Ramya Neelamegham & Pradeep Chintagunta, 1999. "A Bayesian Model to Forecast New Product Performance in Domestic and International Markets," Marketing Science, INFORMS, vol. 18(2), pages 115-136.
- Andrew Ainslie & Xavier Drèze & Fred Zufryden, 2005. "Modeling Movie Life Cycles and Market Share," Marketing Science, INFORMS, vol. 24(3), pages 508-517, November.
- Yie-Fang Kao & Li-Shia Huang & Ming-Hsien Yang, 2007. "Effects of experiential elements on experiential satisfaction and loyalty intentions: a case study of the super basketball league in Taiwan," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 1(1), pages 79-96.
- Elberse, Anita & Anand, Bharat, 2007. "The effectiveness of pre-release advertising for motion pictures: An empirical investigation using a simulated market," Information Economics and Policy, Elsevier, vol. 19(3-4), pages 319-343, October.
- Jehoshua Eliashberg & Jedid-Jah Jonker & Mohanbir S. Sawhney & Berend Wierenga, 2000. "MOVIEMOD: An Implementable Decision-Support System for Prerelease Market Evaluation of Motion Pictures," Marketing Science, INFORMS, vol. 19(3), pages 226-243, January.
- Jehoshua Eliashberg & Anita Elberse & Mark A.A.M. Leenders, 2006. "The Motion Picture Industry: Critical Issues in Practice, Current Research, and New Research Directions," Marketing Science, INFORMS, vol. 25(6), pages 638-661, 11-12.
- Vijay Mahajan & Eitan Muller & Roger A. Kerin, 1984. "Introduction Strategy for New Products with Positive and Negative Word-of-Mouth," Management Science, INFORMS, vol. 30(12), pages 1389-1404, December.
- Charles C. Moul, 2007. "Measuring Word of Mouth's Impact on Theatrical Movie Admissions," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 16(4), pages 859-892, December.
- Byeng-Hee Chang & Eyun-Jung Ki, 2005. "Devising a Practical Model for Predicting Theatrical Movie Success: Focusing on the Experience Good Property," Journal of Media Economics, Taylor & Francis Journals, vol. 18(4), pages 247-269.
- Jehoshua Eliashberg & Mohanbir S. Sawhney, 1994. "Modeling Goes to Hollywood: Predicting Individual Differences in Movie Enjoyment," Management Science, INFORMS, vol. 40(9), pages 1151-1173, September.
- M. Bagella & L. Becchetti, 1999. "The Determinants of Motion Picture Box Office Performance: Evidence from Movies Produced in Italy," Journal of Cultural Economics, Springer, vol. 23(4), pages 237-256, November.
- Berend Wierenga, 2006. "—Motion Pictures: Consumers, Channels, and Intuition," Marketing Science, INFORMS, vol. 25(6), pages 674-677, 11-12.
- Mohanbir S. Sawhney & Jehoshua Eliashberg, 1996. "A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures," Marketing Science, INFORMS, vol. 15(2), pages 113-131.
- Tülin Erdem, 1996. "A Dynamic Analysis of Market Structure Based on Panel Data," Marketing Science, INFORMS, vol. 15(4), pages 359-378.
- Thorsten Hennig-Thurau & Mark Houston & Shrihari Sridhar, 2006. "Can good marketing carry a bad product? Evidence from the motion picture industry," Marketing Letters, Springer, vol. 17(3), pages 205-219, July.
- Hong, Sung-Tai & Wyer, Robert S, Jr, 1989. " Effects of Country-of-Origin and Product-Attribute Information on Product Evaluation: An Information Processing Perspective," Journal of Consumer Research, University of Chicago Press, vol. 16(2), pages 175-87, September.
- Manuel Cuadrado & Marta Frasquet, 1999. "Segmentation of Cinema Audiences: An Exploratory Study Applied to Young Consumers," Journal of Cultural Economics, Springer, vol. 23(4), pages 257-267, November.
- Andrew A. Goett & Kathleen Hudson & Kenneth E. Train, 2000. "Customers' Choice Among Retail Energy Suppliers: The Willingness-to-Pay for Service Attributes," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-28.
- Gerda Gemser & Martine Oostrum & Mark Leenders, 2007. "The impact of film reviews on the box office performance of art house versus mainstream motion pictures," Journal of Cultural Economics, Springer, vol. 31(1), pages 43-63, March.
- Holbrook, Morris B, 1999. " Popular Appeal versus Expert Judgments of Motion Pictures," Journal of Consumer Research, University of Chicago Press, vol. 26(2), pages 144-55, September.
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