IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v144y2019icp157-168.html
   My bibliography  Save this article

Programmatic Advertising: Forewarning and avoiding hype-cycle failure

Author

Listed:
  • White, Gareth R.T.
  • Samuel, Anthony

Abstract

The emergence of new technologies has often been examined through their transition along the hype-cycle. While this has been a useful approach, recent research indicates that not all new technologies follow the pattern of the hype-cycle as originally envisaged by Gartner.

Suggested Citation

  • White, Gareth R.T. & Samuel, Anthony, 2019. "Programmatic Advertising: Forewarning and avoiding hype-cycle failure," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 157-168.
  • Handle: RePEc:eee:tefoso:v:144:y:2019:i:c:p:157-168
    DOI: 10.1016/j.techfore.2019.03.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162518314902
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2019.03.020?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. Bleier, Alexander & Eisenbeiss, Maik, 2015. "The Importance of Trust for Personalized Online Advertising," Journal of Retailing, Elsevier, vol. 91(3), pages 390-409.
    2. Jürgen Seitz & Steffen Zorn, 2016. "Perspectives of Programmatic Advertising," Management for Professionals, in: Oliver Busch (ed.), Programmatic Advertising, pages 37-51, Springer.
    3. Konrad, Kornelia & Markard, Jochen & Ruef, Annette & Truffer, Bernhard, 2012. "Strategic responses to fuel cell hype and disappointment," Technological Forecasting and Social Change, Elsevier, vol. 79(6), pages 1084-1098.
    4. Benjamin Shiller & Joel Waldfogel & Johnny Ryan, 2018. "The effect of ad blocking on website traffic and quality," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 43-63, March.
    5. Stephann Makri & Ann Blandford & Mel Woods & Sarah Sharples & Deborah Maxwell, 2014. "“Making my own luck”: Serendipity strategies and how to support them in digital information environments," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(11), pages 2179-2194, November.
    6. van Lente, Harro & Spitters, Charlotte & Peine, Alexander, 2013. "Comparing technological hype cycles: Towards a theory," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1615-1628.
    7. Seung-Pyo Jun, 2012. "An empirical study of users’ hype cycle based on search traffic: the case study on hybrid cars," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 81-99, April.
    8. Niko Marcel Waesche & Tilman Rotberg & Florian Renz, 2016. "The Contribution of Measurement in a Cross-Device, Data-Driven, Real-Time Marketing World," Management for Professionals, in: Oliver Busch (ed.), Programmatic Advertising, pages 153-164, Springer.
    9. Rajagopal, 2014. "Organizations and Innovation," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 3, pages 58-86, Palgrave Macmillan.
    10. Nils Hachen & Stefan Bardega, 2016. "Evolution of Digital Campaign Design and Management," Management for Professionals, in: Oliver Busch (ed.), Programmatic Advertising, pages 211-220, Springer.
    11. Aguirre, Elizabeth & Mahr, Dominik & Grewal, Dhruv & de Ruyter, Ko & Wetzels, Martin, 2015. "Unraveling the Personalization Paradox: The Effect of Information Collection and Trust-Building Strategies on Online Advertisement Effectiveness," Journal of Retailing, Elsevier, vol. 91(1), pages 34-49.
    12. Kolja Brosche & Arun Kumar, 2016. "Realtime Data Accelerates Online Marketing," Management for Professionals, in: Oliver Busch (ed.), Programmatic Advertising, pages 221-232, Springer.
    13. Sven Weisbrich & Caroline Owens, 2016. "The Creative Challenge," Management for Professionals, in: Oliver Busch (ed.), Programmatic Advertising, pages 123-130, Springer.
    14. Oliver Gertz & Deirdre McGlashan, 2016. "Consumer-Centric Programmatic Advertising," Management for Professionals, in: Oliver Busch (ed.), Programmatic Advertising, pages 55-73, Springer.
    15. S. Sriram & Puneet Manchanda & Mercedes Bravo & Junhong Chu & Liye Ma & Minjae Song & Scott Shriver & Upender Subramanian, 2015. "Platforms: a multiplicity of research opportunities," Marketing Letters, Springer, vol. 26(2), pages 141-152, June.
    16. Dedehayir, Ozgur & Steinert, Martin, 2016. "The hype cycle model: A review and future directions," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 28-41.
    17. Jun, Seung-Pyo, 2012. "A comparative study of hype cycles among actors within the socio-technical system: With a focus on the case study of hybrid cars," Technological Forecasting and Social Change, Elsevier, vol. 79(8), pages 1413-1430.
    18. Jenny Doorn & Janny Hoekstra, 2013. "Customization of online advertising: The role of intrusiveness," Marketing Letters, Springer, vol. 24(4), pages 339-351, December.
    19. Michael S. McPherson & Lawrence S. Bacow, 2015. "Online Higher Education: Beyond the Hype Cycle," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 135-154, Fall.
    20. Lori McCay-Peet & Elaine G. Toms, 2015. "Investigating serendipity: How it unfolds and what may influence it," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(7), pages 1463-1476, July.
    21. Burkhardt Funk & Nadia Abou Nabout, 2016. "Cross-Channel Real-Time Response Analysis," Management for Professionals, in: Oliver Busch (ed.), Programmatic Advertising, pages 141-151, Springer.
    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. James, Steffan & Liu, Zheng & White, Gareth R.T. & Samuel, Anthony, 2023. "Introducing ethical theory to the triple helix model: Supererogatory acts in crisis innovation," Technovation, Elsevier, vol. 126(C).
    2. Xiaoli Wang & Yun Liu & Lingdi Chen & Yifan Zhang, 2022. "Correlation Monitoring Method and model of Science-Technology-Industry in the AI Field: A Case of the Neural Network," SAGE Open, , vol. 12(4), pages 21582440221, December.
    3. Jessica Mancilla-de-la-Cruz & Marisela Rodriguez-Salvador & Laura Ruiz-Cantu, 2020. "The Next Pharmaceutical Path: Determining Technology Evolution in Drug Delivery Products Fabricated with Additive Manufacturing," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 14(3), pages 55-70.
    4. Richet, Jean-Loup, 2022. "How cybercriminal communities grow and change: An investigation of ad-fraud communities," Technological Forecasting and Social Change, Elsevier, vol. 174(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. Shi, Yuwei & Herniman, John, 2023. "The role of expectation in innovation evolution: Exploring hype cycles," Technovation, Elsevier, vol. 119(C).
    2. Kriechbaum, Michael & López Prol, Javier & Posch, Alfred, 2018. "Looking back at the future: Dynamics of collective expectations about photovoltaic technology in Germany & Spain," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 76-87.
    3. Dedehayir, Ozgur & Steinert, Martin, 2016. "The hype cycle model: A review and future directions," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 28-41.
    4. Jun, Seung-Pyo & Yoo, Hyoung Sun & Choi, San, 2018. "Ten years of research change using Google Trends: From the perspective of big data utilizations and applications," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 69-87.
    5. Kriechbaum, Michael & Posch, Alfred & Hauswiesner, Angelika, 2021. "Hype cycles during socio-technical transitions: The dynamics of collective expectations about renewable energy in Germany," Research Policy, Elsevier, vol. 50(9).
    6. Bleier, Alexander & Goldfarb, Avi & Tucker, Catherine, 2020. "Consumer privacy and the future of data-based innovation and marketing," International Journal of Research in Marketing, Elsevier, vol. 37(3), pages 466-480.
    7. Jun, Seung-Pyo & Sung, Tae-Eung & Park, Hyun-Woo, 2017. "Forecasting by analogy using the web search traffic," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 37-51.
    8. Kirkels, Arjan, 2016. "Biomass boom or bubble? A longitudinal study on expectation dynamics," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 83-96.
    9. Hashemi, Fariba & Gallay, Olivier & Hongler, Max-Olivier, 2021. "Opinion formation dynamics — Swift collective disillusionment triggered by unmet expectations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    10. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    11. Sabinne Lee & Kwangho Jung, 2018. "The Role of Community-led Governance in Innovation Diffusion: The Case of RFID Waste Pricing System in the Republic of Korea," Sustainability, MDPI, vol. 10(9), pages 1-23, September.
    12. Schreiner, Timo & Rese, Alexandra & Baier, Daniel, 2019. "Multichannel personalization: Identifying consumer preferences for product recommendations in advertisements across different media channels," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 87-99.
    13. Mejía, Cristian & Kajikawa, Yuya, 2019. "Technology news and their linkage to production of knowledge in robotics research," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 114-124.
    14. Cheng, Junjun & Chen, Bo & Huang, Zihang, 2023. "Collective-based ad transparency in targeted hotel advertising: Consumers’ regulatory focus underlying the crowd safety effect," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    15. Cremonini, Marco, 2016. "Introducing serendipity in a social network model of knowledge diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 64-71.
    16. Lena Steinhoff & Denni Arli & Scott Weaven & Irina V. Kozlenkova, 2019. "Online relationship marketing," Journal of the Academy of Marketing Science, Springer, vol. 47(3), pages 369-393, May.
    17. Yap, Xiao-Shan & Truffer, Bernhard, 2019. "Shaping selection environments for industrial catch-up and sustainability transitions: A systemic perspective on endogenizing windows of opportunity," Research Policy, Elsevier, vol. 48(4), pages 1030-1047.
    18. Mpinganjira, Mercy & Maduku, Daniel K., 2019. "Ethics of mobile behavioral advertising: Antecedents and outcomes of perceived ethical value of advertised brands," Journal of Business Research, Elsevier, vol. 95(C), pages 464-478.
    19. Grigorios, Lamprinakos & Magrizos, Solon & Kostopoulos, Ioannis & Drossos, Dimitrios & Santos, David, 2022. "Overt and covert customer data collection in online personalized advertising: The role of user emotions," Journal of Business Research, Elsevier, vol. 141(C), pages 308-320.
    20. Pallant, Jason I. & Pallant, Jessica L. & Sands, Sean J. & Ferraro, Carla R. & Afifi, Eslam, 2022. "When and how consumers are willing to exchange data with retailers: An exploratory segmentation," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).

    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:tefoso:v:144:y:2019:i:c:p:157-168. 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.sciencedirect.com/science/journal/00401625 .

    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.