IDEAS home Printed from https://ideas.repec.org/a/eee/joinma/v48y2019icp1-16.html
   My bibliography  Save this article

Drama Goes Viral: Effects of Story Development on Shares and Views of Online Advertising Videos

Author

Listed:
  • Quesenberry, Keith A.
  • Coolsen, Michael K.

Abstract

Viral advertising videos are a prominent form of viral marketing, yet little is known about which factors influence an online video's virality or likelihood to be shared and viewed. A content analysis of 155 viral ad videos found that average shares and views were higher for videos with full story development versus videos with less than full story development as measured via a five-point drama scale based on Freytag's Pyramid. An incremental story development effect on shares and views was also found. Time duration and company size did not significantly influence the results for shares but did have some effect on the results for views. The role of story in viral videos, the relationship between drama theory, narrative theory, story grammar theory and transportation theory, and managerial implications of story development in viral marketing are also discussed.

Suggested Citation

  • Quesenberry, Keith A. & Coolsen, Michael K., 2019. "Drama Goes Viral: Effects of Story Development on Shares and Views of Online Advertising Videos," Journal of Interactive Marketing, Elsevier, vol. 48(C), pages 1-16.
    • Handle: RePEc:eee:joinma:v:48:y:2019:i:c:p:1-16
    DOI: 10.1016/j.intmar.2019.05.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1094996819300714
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intmar.2019.05.001?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. Escalas, Jennifer Edson & Stern, Barbara B, 2003. "Sympathy and Empathy: Emotional Responses to Advertising Dramas," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 29(4), pages 566-578, March.
    2. Shehu, Edlira & Bijmolt, Tammo H.A. & Clement, Michel, 2016. "Effects of Likeability Dynamics on Consumers' Intention to Share Online Video Advertisements," Journal of Interactive Marketing, Elsevier, vol. 35(C), pages 27-43.
    3. Deighton, John & Romer, Daniel & McQueen, Josh, 1989. "Using Drama to Persuade," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(3), pages 335-343, December.
    4. Tian, Shaonan & Yu, Yan & Guo, Hui, 2015. "Variable selection and corporate bankruptcy forecasts," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 89-100.
    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. Hamby, Anne & Kim, Hongmin & Spezzano, Francesca, 2024. "Sensational stories: The role of narrative characteristics in distinguishing real and fake news and predicting their spread," Journal of Business Research, Elsevier, vol. 170(C).
    2. Müller, Lara Marie & Harrs, Sören & Rockenbach, Bettina, 2022. "How Narratives Impact Financial Behavior - Experimental Evidence from the COVID-19 Pandemic," VfS Annual Conference 2022 (Basel): Big Data in Economics 264089, Verein für Socialpolitik / German Economic Association.
    3. Ngai, Eric W.T. & Wu, Yuanyuan, 2022. "Machine learning in marketing: A literature review, conceptual framework, and research agenda," Journal of Business Research, Elsevier, vol. 145(C), pages 35-48.
    4. Schwenzow, Jasper & Hartmann, Jochen & Schikowsky, Amos & Heitmann, Mark, 2021. "Understanding videos at scale: How to extract insights for business research," Journal of Business Research, Elsevier, vol. 123(C), pages 367-379.
    5. Jansen, Nora & Hinz, Oliver & Deusser, Clemens & Strufe, Thorsten, 2021. "Is the Buzz on? – A Buzz Detection System for Viral Posts in Social Media," Journal of Interactive Marketing, Elsevier, vol. 56(C), pages 1-17.
    6. Motoki, Kosuke & Suzuki, Shinsuke & Kawashima, Ryuta & Sugiura, Motoaki, 2020. "A Combination of Self-Reported Data and Social-Related Neural Measures Forecasts Viral Marketing Success on Social Media," Journal of Interactive Marketing, Elsevier, vol. 52(C), pages 99-117.
    7. Mulier, Lana & Slabbinck, Hendrik & Vermeir, Iris, 2021. "This Way Up: The Effectiveness of Mobile Vertical Video Marketing," Journal of Interactive Marketing, Elsevier, vol. 55(C), pages 1-15.
    8. Dharun Kasilingam & Soundararaj Ajitha, 2022. "Storytelling in advertisements: understanding the effect of humor and drama on the attitude toward brands," Journal of Brand Management, Palgrave Macmillan, vol. 29(4), pages 341-362, July.
    9. Wen, Xiaohan (Hannah) & Kim, Shinhye & Bowen, Melanie, 2023. "Doing good by sharing messages: An investigation of “You Share, We Donate” campaigns and how they can attain viral success," Journal of Business Research, Elsevier, vol. 156(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. Dessart, Laurence & Pitardi, Valentina, 2019. "How stories generate consumer engagement: An exploratory study," Journal of Business Research, Elsevier, vol. 104(C), pages 183-195.
    2. Dharun Kasilingam & Soundararaj Ajitha, 2022. "Storytelling in advertisements: understanding the effect of humor and drama on the attitude toward brands," Journal of Brand Management, Palgrave Macmillan, vol. 29(4), pages 341-362, July.
    3. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    4. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2018. "Asset allocation strategies based on penalized quantile regression," Computational Management Science, Springer, vol. 15(1), pages 1-32, January.
    5. Modina, Michele & Pietrovito, Filomena & Gallucci, Carmen & Formisano, Vincenzo, 2023. "Predicting SMEs’ default risk: Evidence from bank-firm relationship data," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 254-268.
    6. Croux, Christophe & Jagtiani, Julapa & Korivi, Tarunsai & Vulanovic, Milos, 2020. "Important factors determining Fintech loan default: Evidence from a lendingclub consumer platform," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 270-296.
    7. Serrano-Cinca, Carlos & Gutiérrez-Nieto, Begoña & Bernate-Valbuena, Martha, 2019. "The use of accounting anomalies indicators to predict business failure," European Management Journal, Elsevier, vol. 37(3), pages 353-375.
    8. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
    9. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
    10. Cao, Xinyue & Qu, Zhirui & Liu, Yan & Hu, JiaJing, 2021. "How the destination short video affects the customers' attitude: The role of narrative transportation," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    11. Kai Dominik Renchen, 2020. "Influencer Impact on Brand Awareness: A Mixed Method Survey in the German Fashion Segment," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 6(2), pages 138-153.
    12. Azizpour, S & Giesecke, K. & Schwenkler, G., 2018. "Exploring the sources of default clustering," Journal of Financial Economics, Elsevier, vol. 129(1), pages 154-183.
    13. Ángel Beade & Manuel Rodríguez & José Santos, 2024. "Multiperiod Bankruptcy Prediction Models with Interpretable Single Models," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1357-1390, September.
    14. O’Sullivan, Conall & Papavassiliou, Vassilios G. & Wafula, Ronald Wekesa & Boubaker, Sabri, 2024. "New insights into liquidity resiliency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    15. Sigrist, Fabio & Leuenberger, Nicola, 2023. "Machine learning for corporate default risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1390-1406.
    16. Xie, Jifei & Wu, Haoyu & Liu, Kexi & Cui, Yunce & Zhang, Xiaofei, 2024. "Is virtual streamer useful? Effect of streamer type on consumer brand forgiveness when streamers make inappropriate remarks," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    17. La Torre, Matteo & Dumay, John & Rea, Michele Antonio & Abhayawansa, Subhash, 2020. "A journey towards a safe harbour: The rhetorical process of the International Integrated Reporting Council," The British Accounting Review, Elsevier, vol. 52(2).
    18. Paul J. H. Schoemaker, 2023. "Exploring scenario planning through controlled experimentation: Commentary on Derbyshire et al. (2022)," Futures & Foresight Science, John Wiley & Sons, vol. 5(2), June.
    19. Campos-Vazquez, Raymundo M. & Cuilty, Emilio, 2014. "The role of emotions on risk aversion: A Prospect Theory experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 50(C), pages 1-9.
    20. Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2023. "Revisiting SME default predictors: The Omega Score," Journal of Small Business Management, Taylor & Francis Journals, vol. 61(6), pages 2383-2417, November.

    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:joinma:v:48:y:2019:i:c:p:1-16. 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/journal-of-interactive-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.