IDEAS home Printed from
   My bibliography  Save this article

Marketing Recommender Systems: A New Approach in Digital Economy


  • Loredana MOCEAN


  • Ciprian Marcel POP



Marketing information systems are those systems which make the gathering, processing, selection, storage, transmission and display of coordinated and continuous internal and external information. Includes systematic and formal methods used for managing all of an organization's information market. Recommendation systems are those systems that are widely used in online systems to suggest items that users might find interesting. These recommendations are generated using in particular two techniques: content-based and collaborative filtering. This paper aims to define a new system, namely Marketing Recommender System, a system that serves marketing and uses techniques and methods of the digital economy.

Suggested Citation

  • Loredana MOCEAN & Ciprian Marcel POP, 2012. "Marketing Recommender Systems: A New Approach in Digital Economy," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 16(4), pages 142-149.
  • Handle: RePEc:aes:infoec:v:16:y:2012:i:4:p:142-149

    Download full text from publisher

    File URL:,%20Pop.pdf
    Download Restriction: no

    References listed on IDEAS

    1. Zan Huang & Daniel D. Zeng & Hsinchun Chen, 2007. "Analyzing Consumer-Product Graphs: Empirical Findings and Applications in Recommender Systems," Management Science, INFORMS, vol. 53(7), pages 1146-1164, July.
    Full references (including those not matched with items on IDEAS)


    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:aes:infoec:v:16:y:2012:i:4:p:142-149. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Paul Pocatilu). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.