IDEAS home Printed from https://ideas.repec.org/a/spr/elmark/v32y2022i3d10.1007_s12525-022-00546-y.html
   My bibliography  Save this article

The effects of advertisement disclosure on heavy and light Instagram users

Author

Listed:
  • Zofia Saternus

    (Goethe University Frankfurt)

  • Patrick Weber

    (Goethe University Frankfurt)

  • Oliver Hinz

    (Goethe University Frankfurt)

Abstract

The present study investigates the moderating effect of usage intensity of the social networking site (SNS) Instagram (IG) on the influence of advertisement disclosure types on advertising performance. A national sample (N = 566) participated in a randomized online experiment including a real influencer and followers in order to investigate how different advertisement disclosure types affect advertising performance and how usage intensity moderates this effect. We find that disclosing an influencer’s postings with “#ad” increases the trustworthiness of the influencer and the general credibility of the posting for heavy users, but not for light users. Followership of a user has been found to strongly improve all researched variables (attitude toward product placement, trustworthiness of the spokesperson and general credibility of the posting). This study adds to literature the first distinction on heavy and light usage intensity, and on followership of an IG user when regarding the effects of advertisement disclosure types on advertising performance. To conclude, we present a number of recommendations regarding how advertisers, influencers, and SNS providers should develop strategies for monitoring, understanding, and responding to different social media users, e.g., to closely monitor an influencer’s audience to identify heavy users and optimally target them.

Suggested Citation

  • Zofia Saternus & Patrick Weber & Oliver Hinz, 2022. "The effects of advertisement disclosure on heavy and light Instagram users," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1351-1372, September.
  • Handle: RePEc:spr:elmark:v:32:y:2022:i:3:d:10.1007_s12525-022-00546-y
    DOI: 10.1007/s12525-022-00546-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12525-022-00546-y
    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/s12525-022-00546-y?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. Patti Williams & Aimee Drolet, 2005. "Age-Related Differences in Responses to Emotional Advertisements," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(3), pages 343-354, December.
    2. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    3. Uzunoğlu, Ebru & Misci Kip, Sema, 2014. "Brand communication through digital influencers: Leveraging blogger engagement," International Journal of Information Management, Elsevier, vol. 34(5), pages 592-602.
    4. Kim, Do Yuon & Kim, Hye-Young, 2021. "Influencer advertising on social media: The multiple inference model on influencer-product congruence and sponsorship disclosure," Journal of Business Research, Elsevier, vol. 130(C), pages 405-415.
    5. Friestad, Marian & Wright, Peter, 1994. "The Persuasion Knowledge Model: How People Cope with Persuasion Attempts," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(1), pages 1-31, June.
    6. Ricardo Buettner, 2017. "Predicting user behavior in electronic markets based on personality-mining in large online social networks," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 247-265, August.
    7. Othman Boujena & Isabelle Ulrich & Aikaterini Manthiou & Bruno Godey, 2021. "Customer engagement and performance in social media: a managerial perspective," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(4), pages 965-987, December.
    8. Jani Merikivi & Antti Salovaara & Matti Mäntymäki & Lilong Zhang, 2018. "On the way to understanding binge watching behavior: the over-estimated role of involvement," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(1), pages 111-122, February.
    9. Campbell, Colin & Farrell, Justine Rapp, 2020. "More than meets the eye: The functional components underlying influencer marketing," Business Horizons, Elsevier, vol. 63(4), pages 469-479.
    10. Russell, Cristel Antonia, 2002. "Investigating the Effectiveness of Product Placements in Television Shows: The Role of Modality and Plot Connection Congruence on Brand Memory and Attitude," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 29(3), pages 306-318, December.
    11. Alice Audrezet & Gwarlann de Kerviler & Julie Guidry Moulard, 2018. "Authenticity under threat: When social media influencers need to go beyond self-presentation," Post-Print hal-01914732, HAL.
    12. Manfred Bruhn & Verena Schoenmueller & Daniela B. Schäfer, 2012. "Are social media replacing traditional media in terms of brand equity creation?," Management Research Review, Emerald Group Publishing Limited, vol. 35(9), pages 770-790, August.
    13. Calder, Bobby J. & Malthouse, Edward C. & Schaedel, Ute, 2009. "An Experimental Study of the Relationship between Online Engagement and Advertising Effectiveness," Journal of Interactive Marketing, Elsevier, vol. 23(4), pages 321-331.
    14. Kietzmann, Jan H. & Hermkens, Kristopher & McCarthy, Ian P. & Silvestre, Bruno S., 2011. "Social media? Get serious! Understanding the functional building blocks of social media," Business Horizons, Elsevier, vol. 54(3), pages 241-251, May.
    15. Yi-Ting Huang & Sheng-Fang Su, 2018. "Motives for Instagram Use and Topics of Interest among Young Adults," Future Internet, MDPI, vol. 10(8), pages 1-12, August.
    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. Rainer Alt, 2022. "Electronic Markets on platform culture," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1019-1031, September.

    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. Conde, Rita & Casais, Beatriz, 2023. "Micro, macro and mega-influencers on instagram: The power of persuasion via the parasocial relationship," Journal of Business Research, Elsevier, vol. 158(C).
    2. van Reijmersdal, Eva A. & Rozendaal, Esther & Buijzen, Moniek, 2012. "Effects of Prominence, Involvement, and Persuasion Knowledge on Children's Cognitive and Affective Responses to Advergames," Journal of Interactive Marketing, Elsevier, vol. 26(1), pages 33-42.
    3. (Chloe) Ki, Chung-Wha & Park, Sangsoo & Kim, Youn-Kyung, 2022. "Investigating the mechanism through which consumers are “inspired by” social media influencers and “inspired to” adopt influencers’ exemplars as social defaults," Journal of Business Research, Elsevier, vol. 144(C), pages 264-277.
    4. Li Chen & Yajie Yan & Andrew N. Smith, 2023. "What drives digital engagement with sponsored videos? An investigation of video influencers’ authenticity management strategies," Journal of the Academy of Marketing Science, Springer, vol. 51(1), pages 198-221, January.
    5. Tafesse, Wondwesen & Wood, Bronwyn P., 2021. "Followers' engagement with instagram influencers: The role of influencers’ content and engagement strategy," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    6. Thomas, Sunil & Kohli, Chiranjeev S., 2011. "Can brand image move upwards after Sideways? A strategic approach to brand placements," Business Horizons, Elsevier, vol. 54(1), pages 41-49.
    7. 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.
    8. Anand Jhawar & Sanjeev Varshney & Prashant Kumar, 2024. "Sponsorship Disclosure on social media: literature review and future research agenda," Management Review Quarterly, Springer, vol. 74(3), pages 1589-1617, September.
    9. Avramova, Yana R. & Dens, Nathalie & De Pelsmacker, Patrick, 2021. "Brand placement across media: The interaction of placement modality and frequency in film versus text," Journal of Business Research, Elsevier, vol. 128(C), pages 20-30.
    10. J?rg Tropp & Corinna Beuthner, 2018. "Customers¡¯ Understanding of Engagement Advertising," Studies in Media and Communication, Redfame publishing, vol. 6(2), pages 57-76, December.
    11. Dima Sawaftah & Ahmad Aljarah & Eva Lahuerta-Otero, 2021. "Power Brand Defense Up, My Friend! Stimulating Brand Defense through Digital Content Marketing," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    12. Yann Verhellen & Caroline Oates & Patrick Pelsmacker & Nathalie Dens, 2014. "Children’s Responses to Traditional Versus Hybrid Advertising Formats: The Moderating Role of Persuasion Knowledge," Journal of Consumer Policy, Springer, vol. 37(2), pages 235-255, June.
    13. Hu, Han-fen & Krishen, Anjala S. & Barnes, Jesse, 2023. "Through narratives we learn: Exploring knowledge-building as a marketing strategy for prosocial water reuse," Journal of Business Research, Elsevier, vol. 158(C).
    14. Onishi Hiroshi, 2018. "Consumers’ Social Learning About Videogame Consoles Through Multiple Website Browsing," Journal of Systems Science and Information, De Gruyter, vol. 6(6), pages 495-511, December.
    15. Algharabat, Raed & Rana, Nripendra P. & Alalwan, Ali Abdallah & Baabdullah, Abdullah & Gupta, Ashish, 2020. "Investigating the antecedents of customer brand engagement and consumer-based brand equity in social media," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
    16. Wahab, Hamza Kaka Abdul & Tao, Meng & Tandon, Anushree & Ashfaq, Muhammad & Dhir, Amandeep, 2022. "Social media celebrities and new world order. What drives purchasing behavior among social media followers?," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    17. Yana R. Avramova & Patrick De Pelsmacker & Nathalie Dens, 2018. "How reading in a foreign versus native language moderates the impact of repetition-induced brand placement prominence on placement responses," Journal of Brand Management, Palgrave Macmillan, vol. 25(6), pages 500-518, November.
    18. Razzaq, Ali & Shao, Wei & Quach, Sara, 2024. "Meme marketing effectiveness: A moderated-mediation model," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    19. Yasir Rashid, Muhammad Zeeshan, 2018. "Customer Attitude towards Online Ads of Smartphone Brands: A Netnographic Analysis of User Generated Comments on YouTube," Journal of Management Sciences, Geist Science, Iqra University, Faculty of Business Administration, vol. 5(2), pages 40-64, October.
    20. Cheung, Man Lai & Leung, Wilson K.S. & Aw, Eugene Cheng-Xi & Koay, Kian Yeik, 2022. "“I follow what you post!†: The role of social media influencers’ content characteristics in consumers' online brand-related activities (COBRAs)," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).

    More about this item

    Keywords

    Advertisement disclosure; Heavy and light users; Usage intensity; Social networking site; Influencer marketing; Advertising performance;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D18 - Microeconomics - - Household Behavior - - - Consumer Protection
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • K21 - Law and Economics - - Regulation and Business Law - - - Antitrust Law
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising
    • Z18 - Other Special Topics - - Cultural Economics - - - Public Policy

    Statistics

    Access and download statistics

    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:elmark:v:32:y:2022:i:3:d:10.1007_s12525-022-00546-y. 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.