IDEAS home Printed from https://ideas.repec.org/a/eee/ijrema/v32y2015i4p408-417.html
   My bibliography  Save this article

The impact of pre- and post-launch publicity and advertising on new product sales

Author

Listed:
  • Burmester, Alexa B.
  • Becker, Jan U.
  • van Heerde, Harald J.
  • Clement, Michel

Abstract

When companies launch new products, they need to understand the impact of publicity and advertising on sales. What is their relative effectiveness? Do they strengthen each other (have a positive interaction effect) or weaken each other (have a negative interaction effect)? Further, does the timing of these activities (before or after launch) affect their impact on sales? This paper develops hypotheses regarding the elasticities of pre- and post-launch publicity and advertising on sales. The hypotheses are tested on a large-scale empirical data set that tracks sales, publicity, and advertising for 3336 video games across 52 weeks covering the pre- and post-launch phases. The results demonstrate that pre-launch publicity is more effective than pre-launch advertising but that the reverse is true post-launch. Surprisingly, the analysis reveals a negative interaction effect between pre-launch advertising and publicity, which means that publicity becomes less effective when it is accompanied by higher levels of advertising for the same product. Simulations indicate that companies can gain most sales by focusing on publicity pre-launch, and that there is little benefit from increasing publicity and advertising during the same phase, which is consistent with negative (pre-launch) and zero (post-launch) interaction effects.

Suggested Citation

  • Burmester, Alexa B. & Becker, Jan U. & van Heerde, Harald J. & Clement, Michel, 2015. "The impact of pre- and post-launch publicity and advertising on new product sales," International Journal of Research in Marketing, Elsevier, vol. 32(4), pages 408-417.
    • Handle: RePEc:eee:ijrema:v:32:y:2015:i:4:p:408-417
    DOI: 10.1016/j.ijresmar.2015.05.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016781161500066X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijresmar.2015.05.005?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. 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.
    2. Il-Horn Hann & Kai-Lung Hui & Sang-Yong Tom Lee & Ivan Png, 2005. "Consumer Privacy and Marketing Avoidance," Industrial Organization 0503009, University Library of Munich, Germany.
    3. Harald J. van Heerde & Peter S. H. Leeflang & Dick R. Wittink, 2002. "How Promotions Work: Scan Pro-Based Evolutionary Model Building," Schmalenbach Business Review (sbr), LMU Munich School of Management, vol. 54(3), pages 198-220, July.
    4. Frison, Steffi & Dekimpe, Marnik G. & Croux, Christophe & De Maeyer, Peter, 2014. "Billboard and cinema advertising: Missed opportunity or spoiled arms?," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 425-433.
    5. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    6. Jonathan Beck, 2007. "The sales effect of word of mouth: a model for creative goods and estimates for novels," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 31(1), pages 5-23, March.
    7. Schumann, David W & Petty, Richard E & Clemons, D Scott, 1990. "Predicting the Effectiveness of Different Strategies of Advertising Variation: A Test of the Repetition-Variation Hypotheses," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(2), pages 192-202, September.
    8. Andrew Ainslie & Xavier Drèze & Fred Zufryden, 2005. "Modeling Movie Life Cycles and Market Share," Marketing Science, INFORMS, vol. 24(3), pages 508-517, November.
    9. Sungho Park & Sachin Gupta, 2012. "Handling Endogenous Regressors by Joint Estimation Using Copulas," Marketing Science, INFORMS, vol. 31(4), pages 567-586, July.
    10. Gerard J. Tellis & Stefan Stremersch & Eden Yin, 2003. "The International Takeoff of New Products: The Role of Economics, Culture, and Country Innovativeness," Marketing Science, INFORMS, vol. 22(2), pages 188-208, October.
    11. Lord, Kenneth R. & Putrevu, Sanjay, 1993. "Advertising and publicity: An information processing perspective," Journal of Economic Psychology, Elsevier, vol. 14(1), pages 57-84, March.
    12. Peter S.H. Leeflang & Harald J. van Heerde & Dick Wittink, 2002. "How Promotions Work: SCAN*PRO-Based Evolutionary Model Building," Yale School of Management Working Papers ysm292, Yale School of Management.
    13. Peter Boatwright & Suman Basuroy & Wagner Kamakura, 2007. "Reviewing the reviewers: The impact of individual film critics on box office performance," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 401-425, December.
    14. 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)

    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. 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.
    2. Franses, Philip Hans, 2021. "Modeling box office revenues of motion pictures✰," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    3. Michel Clement & Anke Hille & Bernd Lucke & Christina Schmidt-Stölting & Frank Sambeth, 2008. "Der Einfluss von Rankings auf den Absatz — Eine empirische Analyse der Wirkung von Bestsellerlisten und Rangpositionen auf den Erfolg von Büchern," Schmalenbach Journal of Business Research, Springer, vol. 60(8), pages 746-777, December.
    4. Jason M. T. Roos & Ron Shachar, 2014. "When Kerry Met Sally: Politics and Perceptions in the Demand for Movies," Management Science, INFORMS, vol. 60(7), pages 1617-1631, July.
    5. Sumiko Asai, 2009. "Sales Patterns of Hit Music in Japan," Journal of Media Economics, Taylor & Francis Journals, vol. 22(2), pages 81-101.
    6. 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.
    7. John Hauser & Gerard J. Tellis & Abbie Griffin, 2006. "Research on Innovation: A Review and Agenda for," Marketing Science, INFORMS, vol. 25(6), pages 687-717, 11-12.
    8. Gaenssle Sophia & Budzinski Oliver & Astakhova Daria, 2018. "Conquering the Box Office: Factors Influencing Success of International Movies in Russia," Review of Network Economics, De Gruyter, vol. 17(4), pages 245-266, December.
    9. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Fei Peng & Lili Kang & Sajid Anwar & Xue Li, 2019. "Star power and box office revenues: evidence from China," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(2), pages 247-278, June.
    16. Kim, Taegu & Hong, Jungsik & Kang, Pilsung, 2015. "Box office forecasting using machine learning algorithms based on SNS data," International Journal of Forecasting, Elsevier, vol. 31(2), pages 364-390.
    17. Weber, Anett & Steiner, Winfried J., 2021. "Modeling price response from retail sales: An empirical comparison of models with different representations of heterogeneity," European Journal of Operational Research, Elsevier, vol. 294(3), pages 843-859.
    18. 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.
    19. Delre, S.A. & Jager, W. & Bijmolt, T.H.A. & Janssen, M.A., 2007. "Targeting and timing promotional activities: An agent-based model for the takeoff of new products," Journal of Business Research, Elsevier, vol. 60(8), pages 826-835, August.
    20. Moez Hababou & Nawel Amrouche & Kamel Jedidi, 2016. "Measuring Economic Efficiency in the Motion Picture Industry: a Data Envelopment Analysis Approach," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(3), pages 144-158, December.

    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:ijrema:v:32:y:2015:i:4:p:408-417. 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: https://www.journals.elsevier.com/international-journal-of-research-in-marketing/ .

    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.