IDEAS home Printed from https://ideas.repec.org/a/spr/elcore/v20y2020i3d10.1007_s10660-020-09423-2.html
   My bibliography  Save this article

Examining the role of the marketing activity and eWOM in the movie diffusion: the decomposition perspective

Author

Listed:
  • Hailin Zhang

    (Yonsei University)

  • Xina Yuan

    (Xiamen University)

  • Tae Ho Song

    (Pusan National University)

Abstract

Advertising as a direct marketing activity as well as word-of-mouth (WOM) as an indirect marketing activity are widely accepted as the most influential determinants of new product performance. Although electronic WOM (eWOM), as a type of WOM, has recently been studied extensively in various industries, previous results appear mixed due to their characteristics such as volume and valence. To bridge the gap regarding the roles of advertising and eWOM in the movie diffusion process, they were classified into pre-eWOM/advertising and post-eWOM/advertising based on two stages of the diffusion process. To reflect the heterogeneity of consumption characteristics on a new product, consumers were divided into two groups—innovators and imitators. This study proposed a model to investigate the role of advertising and eWOM in the movie diffusion process. In addition, the proposed model was used to analyze the impact of firm-initiated advertising and user-generated online reviews on movie performance in Korea.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:elcore:v:20:y:2020:i:3:d:10.1007_s10660-020-09423-2
    DOI: 10.1007/s10660-020-09423-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10660-020-09423-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10660-020-09423-2?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. Jordi McKenzie, 2009. "Revealed word-of-mouth demand and adaptive supply: survival of motion pictures at the Australian box office," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 33(4), pages 279-299, November.
    2. Prasad A. Naik & Murali K. Mantrala & Alan G. Sawyer, 1998. "Planning Media Schedules in the Presence of Dynamic Advertising Quality," Marketing Science, INFORMS, vol. 17(3), pages 214-235.
    3. Engelen, Andreas & Brettel, Malte, 2011. "Assessing cross-cultural marketing theory and research," Journal of Business Research, Elsevier, vol. 64(5), pages 516-523, May.
    4. Stephanie Watts Sussman & Wendy Schneier Siegal, 2003. "Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption," Information Systems Research, INFORMS, vol. 14(1), pages 47-65, March.
    5. Francis Lee, 2006. "Cultural Discount and Cross-Culture Predictability: Examining the Box Office Performance of American Movies in Hong Kong," Journal of Media Economics, Taylor & Francis Journals, vol. 19(4), pages 259-278.
    6. V. Srinivasan & Charlotte H. Mason, 1986. "Technical Note—Nonlinear Least Squares Estimation of New Product Diffusion Models," Marketing Science, INFORMS, vol. 5(2), pages 169-178.
    7. Mizerski, Richard W, 1982. "An Attribution Explanation of the Disproportionate Influence of Unfavorable Information," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(3), pages 301-310, December.
    8. 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.
    9. 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.
    10. Meyers-Levy, Joan & Maheswaran, Durairaj, 1991. "Exploring Differences in Males' and Females' Processing Strategies," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(1), pages 63-70, June.
    11. 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.
    12. Pechmann, Cornelia & Stewart, David W, 1990. "The Effects of Comparative Advertising on Attention, Memory, and Purchase Intentions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(2), pages 180-191, September.
    13. Nelson, Philip, 1974. "Advertising as Information," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 729-754, July/Aug..
    14. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    15. Yani Wang & Jun Wang & Tang Yao, 2019. "What makes a helpful online review? A meta-analysis of review characteristics," Electronic Commerce Research, Springer, vol. 19(2), pages 257-284, June.
    16. Moon, Sangkil & Song, Reo, 2015. "The Roles of Cultural Elements in International Retailing of Cultural Products: An Application to the Motion Picture Industry," Journal of Retailing, Elsevier, vol. 91(1), pages 154-170.
    17. 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.
    18. David C. Schmittlein & Vijay Mahajan, 1982. "Maximum Likelihood Estimation for an Innovation Diffusion Model of New Product Acceptance," Marketing Science, INFORMS, vol. 1(1), pages 57-78.
    19. 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.
    20. 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.
    21. 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.
    22. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    23. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    24. Christophe Van den Bulte & Stefan Stremersch, 2004. "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test," Marketing Science, INFORMS, vol. 23(4), pages 530-544, July.
    25. Brown, Jacqueline Johnson & Reingen, Peter H, 1987. "Social Ties and Word-of-Mouth Referral Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(3), pages 350-362, December.
    26. Andrew Ainslie & Xavier Drèze & Fred Zufryden, 2005. "Modeling Movie Life Cycles and Market Share," Marketing Science, INFORMS, vol. 24(3), pages 508-517, November.
    27. Dongpu Fu & Yili Hong & Kanliang Wang & Weiguo Fan, 2018. "Effects of membership tier on user content generation behaviors: evidence from online reviews," Electronic Commerce Research, Springer, vol. 18(3), pages 457-483, September.
    28. Schmalen, Helmut, 1982. "Optimal price and advertising policy for new products," Journal of Business Research, Elsevier, vol. 10(1), pages 17-30, March.
    29. Sanjay Sood & Xavier Drze, 2006. "Brand Extensions of Experiential Goods: Movie Sequel Evaluations," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 33(3), pages 352-360, October.
    30. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    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. 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.
    2. Hoon S. Choi & Michele Maasberg, 2022. "An empirical analysis of experienced reviewers in online communities: what, how, and why to review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1293-1310, September.
    3. Yanwu Yang & Baozhu Feng & Joni Salminen & Bernard J. Jansen, 2022. "Optimal advertising for a generalized Vidale–Wolfe response model," Electronic Commerce Research, Springer, vol. 22(4), pages 1275-1305, December.
    4. 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).
    5. Kuang, Di & Ma, Baolong & Wang, Hong, 2022. "The relative impact of advertising and referral reward programs on the post-consumption evaluations in the context of service failure," Journal of Retailing and Consumer Services, Elsevier, vol. 65(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. 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.
    2. 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.
    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. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    5. Marchand, André & Hennig-Thurau, Thorsten & Wiertz, Caroline, 2017. "Not all digital word of mouth is created equal: Understanding the respective impact of consumer reviews and microblogs on new product success," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 336-354.
    6. Park, Sang-June & Lee, Yeong-Ran & Borle, Sharad, 2018. "The shape of Word-of-Mouth response function," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 304-309.
    7. 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.
    8. Olivier Toubia & Jacob Goldenberg & Rosanna Garcia, 2014. "Improving Penetration Forecasts Using Social Interactions Data," Management Science, INFORMS, vol. 60(12), pages 3049-3066, December.
    9. Shyam Gopinath & Jacquelyn S. Thomas & Lakshman Krishnamurthi, 2014. "Investigating the Relationship Between the Content of Online Word of Mouth, Advertising, and Brand Performance," Marketing Science, INFORMS, vol. 33(2), pages 241-258, March.
    10. Gazley, Aaron & Clark, Gemma & Sinha, Ashish, 2011. "Understanding preferences for motion pictures," Journal of Business Research, Elsevier, vol. 64(8), pages 854-861, August.
    11. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    12. Huang Dongling & Strijnev Andrei & Ratchford Brian, 2015. "Role of Advertising and Consumer Interest in the Motion Picture Industry," Review of Marketing Science, De Gruyter, vol. 13(1), pages 1-40, November.
    13. Akbari, Morteza & Foroudi, Pantea & Zaman Fashami, Rahime & Mahavarpour, Nasrin & Khodayari, Maryam, 2022. "Let us talk about something: The evolution of e-WOM from the past to the future," Journal of Business Research, Elsevier, vol. 149(C), pages 663-689.
    14. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    15. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    16. Wang, Feng & Liu, Xuefeng & Fang, Eric (Er), 2015. "User Reviews Variance, Critic Reviews Variance, and Product Sales: An Exploration of Customer Breadth and Depth Effects," Journal of Retailing, Elsevier, vol. 91(3), pages 372-389.
    17. Thaís L. D. Souza & Marislei Nishijima & Ana C. P. Fava, 2019. "Do consumer and expert reviews affect the length of time a film is kept on screens in the USA?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(1), pages 145-171, March.
    18. Darren Filson & James H. Havlicek, 2018. "The performance of global film franchises: installment effects and extension decisions," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 42(3), pages 447-467, August.
    19. Haris Krijestorac & Rajiv Garg & Vijay Mahajan, 2020. "Cross-Platform Spillover Effects in Consumption of Viral Content: A Quasi-Experimental Analysis Using Synthetic Controls," Information Systems Research, INFORMS, vol. 31(2), pages 449-472, June.
    20. Cheng Zhao & Chong Alex Wang, 2023. "A cross-site comparison of online review manipulation using Benford’s law," Electronic Commerce Research, Springer, vol. 23(1), pages 365-406, March.

    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:spr:elcore:v:20:y:2020:i:3:d:10.1007_s10660-020-09423-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.