IDEAS home Printed from https://ideas.repec.org/a/spr/trosos/v14y2020i1d10.1007_s12626-019-00057-x.html
   My bibliography  Save this article

Highly Secure Transaction Mechanism for Video Affiliate Services

Author

Listed:
  • M. IWASHITA

    (Chiba Institute of Technology)

  • S. TANIMOTO

    (Chiba Institute of Technology)

  • K. TSUCHIYA

    (Chiba Institute of Technology)

Abstract

Consumer-generated media (CGM) such as YouTube have dramatically changed modern lifestyles and have made it possible for individuals to obtain and share information easily. Enterprises efficiently promote web advertising using CGM as affiliate services. An increase in the affiliate marketing may induce numerous transactions between the players, including consumers, enterprises, affiliates, and providers, and may cause billing issues, such as falsification. First, this paper proposes a new video advertising model toward near future to satisfy the trend of increasing affiliate services. Affiliates have possibilities to earn by both providers and enterprises, while enterprises can control the initial amount for affiliates in this model. Then, three highly secure transaction methods are constructed for the model as an authentication check method which introduces notary organisation and two self-check methods based on the digital sign mechanism. Finally, the features of these methods are qualitatively evaluated and the condition for applying each method is discussed from the practical point of view.

Suggested Citation

  • M. Iwashita & S. Tanimoto & K. Tsuchiya, 2020. "Highly Secure Transaction Mechanism for Video Affiliate Services," The Review of Socionetwork Strategies, Springer, vol. 14(1), pages 77-91, April.
  • Handle: RePEc:spr:trosos:v:14:y:2020:i:1:d:10.1007_s12626-019-00057-x
    DOI: 10.1007/s12626-019-00057-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12626-019-00057-x
    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/s12626-019-00057-x?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. Onishi, Hiroshi & Manchanda, Puneet, 2012. "Marketing activity, blogging and sales," International Journal of Research in Marketing, Elsevier, vol. 29(3), pages 221-234.
    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. Shijie Lu & Xin (Shane) Wang & Neil Bendle, 2020. "Does Piracy Create Online Word of Mouth? An Empirical Analysis in the Movie Industry," Management Science, INFORMS, vol. 66(5), pages 2140-2162, May.
    2. Tingting Song & Jinghua Huang & Yong Tan & Yifan Yu, 2019. "Using User- and Marketer-Generated Content for Box Office Revenue Prediction: Differences Between Microblogging and Third-Party Platforms," Service Science, INFORMS, vol. 30(1), pages 191-203, March.
    3. Chen, Xuqi & Gao, Zhifeng & House, Lisa, 2016. "Own and Cross-effect of Social Media on Demand for Fresh Produce: A Case of Consumer Preference for California versus Florida Strawberry," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230137, Southern Agricultural Economics Association.
    4. Carlson, Keith & Kopalle, Praveen K. & Riddell, Allen & Rockmore, Daniel & Vana, Prasad, 2023. "Complementing human effort in online reviews: A deep learning approach to automatic content generation and review synthesis," International Journal of Research in Marketing, Elsevier, vol. 40(1), pages 54-74.
    5. Pauwels, Koen & Aksehirli, Zeynep & Lackman, Andrew, 2016. "Like the ad or the brand? Marketing stimulates different electronic word-of-mouth content to drive online and offline performance," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 639-655.
    6. Liu, Yizao & Lopez, Rigoberto A., 2013. "The Impact of Social Media on Consumer Demand: The Case of Carbonated Soft Drink Market," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 148913, Agricultural and Applied Economics Association.
    7. Oliver Schaer & Nikolaos Kourentzes & Robert Fildes, 2022. "Predictive competitive intelligence with prerelease online search traffic," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3823-3839, October.
    8. Vasu Unnava & Ashwin Aravindakshan, 2021. "How does consumer engagement evolve when brands post across multiple social media?," Journal of the Academy of Marketing Science, Springer, vol. 49(5), pages 864-881, September.
    9. van Ewijk, Bernadette J. & Stubbe, Astrid & Gijsbrechts, Els & Dekimpe, Marnik G., 2021. "Online display advertising for CPG brands: (When) does it work?," International Journal of Research in Marketing, Elsevier, vol. 38(2), pages 271-289.
    10. Xiao Liu & Param Vir Singh & Kannan Srinivasan, 2016. "A Structured Analysis of Unstructured Big Data by Leveraging Cloud Computing," Marketing Science, INFORMS, vol. 35(3), pages 363-388, May.
    11. Lu, Qiang Steven & Miller, Rohan, 2019. "How Social Media Communications Combine with Customer Loyalty Management to Boost Green Retail Sales," Journal of Interactive Marketing, Elsevier, vol. 46(C), pages 87-100.
    12. Ishita Chakraborty & Minkyung Kim & K. Sudhir, 2019. "Attribute Sentiment Scoring With Online Text Reviews : Accounting for Language Structure and Attribute Self-Selection," Cowles Foundation Discussion Papers 2176R, Cowles Foundation for Research in Economics, Yale University, revised Sep 2020.
    13. Lisa A. House & Yuan Jiang & Matthew Salois, 2015. "Measures of Online Advertising Effectiveness for Market Penetration: The Case of Orange Juice Consumers," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 63(4), pages 435-448, December.
    14. Jinah Yang & Daiki Min & Jeenyoung Kim, 2020. "The Use of Big Data and Its Effects in a Diffusion Forecasting Model for Korean Reverse Mortgage Subscribers," Sustainability, MDPI, vol. 12(3), pages 1-17, January.
    15. House, Lisa A. & Jiang, Yuan & Salois, Matthew, 2014. "Measures of Online Advertising Effectiveness: The Case of Orange Juice," 2014 AAEA/EAAE/CAES Joint Symposium: Social Networks, Social Media and the Economics of Food, May 29-30, 2014, Montreal, Canada 169776, Agricultural and Applied Economics Association.
    16. Valter Afonso Vieira & Marcos Inácio Severo Almeida & Raj Agnihotri & Nôga Simões De Arruda Corrêa Silva & S. Arunachalam, 2019. "In pursuit of an effective B2B digital marketing strategy in an emerging market," Journal of the Academy of Marketing Science, Springer, vol. 47(6), pages 1085-1108, November.
    17. Ho Kim & Juncai Jiang & Norris I. Bruce, 2021. "Discovering heterogeneous consumer journeys in online platforms: implications for networking investment," Journal of the Academy of Marketing Science, Springer, vol. 49(2), pages 374-396, March.
    18. Yao, Becatien H. & Shanoyan, Aleksan & Peterson, Hikaru Hanawa, 2017. "The Use of New Media Marketing in the Green Industry: Analysis of Social Media Adoption and its Impact on Sales," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258292, Agricultural and Applied Economics Association.
    19. Shuba Srinivasan & Oliver J. Rutz & Koen Pauwels, 2016. "Paths to and off purchase: quantifying the impact of traditional marketing and online consumer activity," Journal of the Academy of Marketing Science, Springer, vol. 44(4), pages 440-453, July.
    20. Sood, Ashish & Kappe, Eelco & Stremersch, Stefan, 2014. "The commercial contribution of clinical studies for pharmaceutical drugs," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 65-77.

    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:trosos:v:14:y:2020:i:1:d:10.1007_s12626-019-00057-x. 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.