IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v130y2021icp603-609.html
   My bibliography  Save this article

Impact of online information on the diffusion of movies: Focusing on cultural differences

Author

Listed:
  • Lee, Youseok
  • Kim, Sang-Hoon
  • Cha, Kyoung Cheon

Abstract

To ensure a movie's success, managers must understand why consumers buy tickets. Some are induced by trailers or movie posters while others are triggered by their friends' recommendations. Using Bass's (1969) terms, we may classify the former as innovators, who are influenced by external factors including advertisements and media reports, and the latter as imitators, who are affected by internal factors such as word-of-mouth. Regardless of their motivation, in the digital era, consumers easily obtain movie-related information through websites or social networking services. Therefore, marketers should focus on how online information influences product diffusion. Additionally, each country's unique cultural background results in different consumer behavior. The current study applies the Bass diffusion model to explore key differences in the diffusion patterns of movies between culturally distinctive markets. Further, this study aims to identify the factors that result in innovation and imitation effects in the markets.

Suggested Citation

  • Lee, Youseok & Kim, Sang-Hoon & Cha, Kyoung Cheon, 2021. "Impact of online information on the diffusion of movies: Focusing on cultural differences," Journal of Business Research, Elsevier, vol. 130(C), pages 603-609.
    • Handle: RePEc:eee:jbrese:v:130:y:2021:i:c:p:603-609
    DOI: 10.1016/j.jbusres.2019.08.044
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296319305144
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2019.08.044?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    2. 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.
    3. Karniouchina, Ekaterina V., 2011. "Impact of star and movie buzz on motion picture distribution and box office revenue," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 62-74.
    4. Turk, Tomaž & Trkman, Peter, 2012. "Bass model estimates for broadband diffusion in European countries," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 85-96.
    5. Marshall, Pablo & Dockendorff, Monika & Ibáñez, Soledad, 2013. "A forecasting system for movie attendance," Journal of Business Research, Elsevier, vol. 66(10), pages 1800-1806.
    6. Amit M. Joshi & Dominique M. Hanssens, 2009. "Movie Advertising and the Stock Market Valuation of Studios: A Case of “Great Expectations?”," Marketing Science, INFORMS, vol. 28(2), pages 239-250, 03-04.
    7. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    8. Holbrook, Morris B, 1999. "Popular Appeal versus Expert Judgments of Motion Pictures," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 26(2), pages 144-155, September.
    9. Seulgi Lee & Eunju Ko & Heeju Chae & Chieko Minami, 2017. "A study of the authenticity of traditional cultural products: focus on Korean, Chinese, and Japanese consumers," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 27(2), pages 93-110, April.
    10. Don M. Chance & Eric Hillebrand & Jimmy E. Hilliard, 2008. "Pricing an Option on Revenue from an Innovation: An Application to Movie Box Office Revenue," Management Science, INFORMS, vol. 54(5), pages 1015-1028, May.
    11. Anita Elberse & Jehoshua Eliashberg, 2003. "Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures," Marketing Science, INFORMS, vol. 22(3), pages 329-354.
    12. Ravid, S Abraham, 1999. "Information, Blockbusters, and Stars: A Study of the Film Industry," The Journal of Business, University of Chicago Press, vol. 72(4), pages 463-492, October.
    13. Wooyang Kim & C. Anthony Di Benedetto & James M. Hunt, 2017. "Consumer innovativeness and international consumer behavior: Comments and extensions," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 27(3), pages 184-194, July.
    14. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    15. Seol, Hyeonju & Park, Gwangman & Lee, Hakyeon & Yoon, Byungun, 2012. "Demand forecasting for new media services with consideration of competitive relationships using the competitive Bass model and the theory of the niche," Technological Forecasting and Social Change, Elsevier, vol. 79(7), pages 1217-1228.
    16. Duan, Wenjing & Gu, Bin & Whinston, Andrew B., 2008. "The dynamics of online word-of-mouth and product sales—An empirical investigation of the movie industry," Journal of Retailing, Elsevier, vol. 84(2), pages 233-242.
    17. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    18. Caroline Elliott & Rob Simmons, 2008. "Determinants of UK Box Office Success: The Impact of Quality Signals," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 33(2), pages 93-111, September.
    19. Ana Maria Soares, 2018. "Revisiting cultures’ consequences in international marketing studies," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 28(2), pages 214-220, April.
    20. Guo, Xuezhen, 2014. "A novel Bass-type model for product life cycle quantification using aggregate market data," International Journal of Production Economics, Elsevier, vol. 158(C), pages 208-216.
    21. Julianne Treme, 2010. "Effects of Celebrity Media Exposure on Box-Office Performance," Journal of Media Economics, Taylor & Francis Journals, vol. 23(1), pages 5-16.
    22. Kim, Ho & Hanssens, Dominique M., 2017. "Advertising and Word-of-Mouth Effects on Pre-launch Consumer Interest and Initial Sales of Experience Products," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 57-74.
    23. Barnes, Belinda & Southwell, Darren & Bruce, Sarah & Woodhams, Felicity, 2014. "Additionality, common practice and incentive schemes for the uptake of innovations," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 43-61.
    24. Sung-Joon Yoon, 2018. "Social-cultural-psychological perspectives on future word-of-mouth research," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 28(2), pages 166-174, April.
    25. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    26. Paul J. Costanzo & Cynthia P. Costanzo, 2019. "Gender differences in marketer and non-marketer-dominated sources of sustainable health and wellness information," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 29(1), pages 42-50, January.
    27. Wu, Feng-Shang & Chu, Wen-Lin, 2010. "Diffusion models of mobile telephony," Journal of Business Research, Elsevier, vol. 63(5), pages 497-501, May.
    28. Dina Mayzlin, 2006. "Promotional Chat on the Internet," Marketing Science, INFORMS, vol. 25(2), pages 155-163, 03-04.
    29. Praveen K. Kopalle & Donald R. Lehmann, 2006. "Setting Quality Expectations When Entering a Market: What Should the Promise Be?," Marketing Science, INFORMS, vol. 25(1), pages 8-24, 01-02.
    30. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tian Liang & Bin Yang & Chenning Deng & Ping Du & Tuqiang Wang & Hongxing Zhou & Panpan Wang & Jingjing Yu & Aizhong Ding & Fujun Ma & Qingbao Gu & Fasheng Li, 2022. "Diffusion of Cement Kiln Co-Processing of Contaminated Soil in Selected Provinces of China: Engineering Practices, Modeling, and Driving Factors," Sustainability, MDPI, vol. 14(22), pages 1-13, November.
    2. Chaab, Jafar & Salhab, Rabih & Zaccour, Georges, 2022. "Dynamic pricing and advertising in the presence of strategic consumers and social contagion: A mean-field game approach," Omega, Elsevier, vol. 109(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fan, Zhi-Ping & Che, Yu-Jie & Chen, Zhen-Yu, 2017. "Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis," Journal of Business Research, Elsevier, vol. 74(C), pages 90-100.
    2. Hofmann, Julian & Clement, Michel & Völckner, Franziska & Hennig-Thurau, Thorsten, 2017. "Empirical generalizations on the impact of stars on the economic success of movies," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 442-461.
    3. Bae, Giwoong & Kim, Hye-jin, 2019. "The impact of movie titles on box office success," Journal of Business Research, Elsevier, vol. 103(C), pages 100-109.
    4. Jordi McKenzie, 2023. "The economics of movies (revisited): A survey of recent literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 480-525, April.
    5. Delre, Sebastiano A. & Panico, Claudio & Wierenga, Berend, 2017. "Competitive strategies in the motion picture industry: An ABM to study investment decisions," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 69-99.
    6. Marchand, André, 2016. "The power of an installed base to combat lifecycle decline: The case of video games," International Journal of Research in Marketing, Elsevier, vol. 33(1), pages 140-154.
    7. Belvaux, Bertrand & Mencarelli, Rémi, 2021. "Prevision model and empirical test of box office results for sequels," Journal of Business Research, Elsevier, vol. 130(C), pages 38-48.
    8. Clement, Michel & Wu, Steven & Fischer, Marc, 2014. "Empirical generalizations of demand and supply dynamics for movies," International Journal of Research in Marketing, Elsevier, vol. 31(2), pages 207-223.
    9. Youseok Lee & Sang-Hoon Kim & Kyoung Cheon Cha, 2023. "The diffusion pattern of new products: evidence from the Korean movie industry," Asian Business & Management, Palgrave Macmillan, vol. 22(5), pages 1830-1847, November.
    10. Divakaran, Pradeep Kumar Ponnamma & Palmer, Adrian & Søndergaard, Helle Alsted & Matkovskyy, Roman, 2017. "Pre-launch Prediction of Market Performance for Short Lifecycle Products Using Online Community Data," Journal of Interactive Marketing, Elsevier, vol. 38(C), pages 12-28.
    11. Hailin Zhang & Xina Yuan & Tae Ho Song, 2020. "Examining the role of the marketing activity and eWOM in the movie diffusion: the decomposition perspective," Electronic Commerce Research, Springer, vol. 20(3), pages 589-608, September.
    12. Thorsten Hennig-Thurau & André Marchand & Barbara Hiller, 2012. "The relationship between reviewer judgments and motion picture success: re-analysis and extension," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(3), pages 249-283, August.
    13. Daekook Kang, 2021. "Box-office forecasting in Korea using search trend data: a modified generalized Bass diffusion model," Electronic Commerce Research, Springer, vol. 21(1), pages 41-72, March.
    14. Chakravarty, Anindita & Liu, Yong & Mazumdar, Tridib, 2010. "The Differential Effects of Online Word-of-Mouth and Critics' Reviews on Pre-release Movie Evaluation," Journal of Interactive Marketing, Elsevier, vol. 24(3), pages 185-197.
    15. Angela (Xia) Liu & Tridib Mazumdar & Bo Li, 2015. "Counterfactual Decomposition of Movie Star Effects with Star Selection," Management Science, INFORMS, vol. 61(7), pages 1704-1721, July.
    16. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    17. Kim, Ho & Hanssens, Dominique M., 2017. "Advertising and Word-of-Mouth Effects on Pre-launch Consumer Interest and Initial Sales of Experience Products," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 57-74.
    18. Delre, Sebastiano A. & Luffarelli, Jonathan, 2023. "Consumer reviews and product life cycle: On the temporal dynamics of electronic word of mouth on movie box office," Journal of Business Research, Elsevier, vol. 156(C).
    19. Leenders, Mark A.A.M. & Eliashberg, Jehoshua, 2011. "The antecedents and consequences of restrictive age-based ratings in the global motion picture industry," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 367-377.
    20. Natalia Gmerek, 2015. "The determinants of Polish movies’ box office performance in Poland," Journal of Marketing and Consumer Behaviour in Emerging Markets, University of Warsaw, Faculty of Management, vol. 1(1), pages 15-35.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:130:y:2021:i:c:p:603-609. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.