IDEAS home Printed from https://ideas.repec.org/a/taf/tjbaxx/v3y2020i2p138-157.html
   My bibliography  Save this article

Determining rank in the market using a neutrosophic decision support system

Author

Listed:
  • Anuradha Banerjee
  • Basav Roychoudhury
  • Bidyut Jyoti Gogoi

Abstract

A company’s rank vis-à-vis that of its competitors is an important metric in understanding its position in the market. For a company, being ranked below its competitors indicates that customers are dissatisfied with its products, signalling the need for a review of its strategies. Existing state-of-the-art methods for ascertaining a company’s rank do not utilise the valuable data available on social media or most smart technologies such as the Internet of Things (IoT) and artificial intelligence. This study develops a new method to estimate a company’s rank using company-deployed intelligent software agents and social IoT(SIoT) objects. The company objects collect real-time feedback about one or more of the company products from social networks for storage and analysis. These company objects are equipped with questionnaires with important metrics such as the Customer Happiness Index, opinion on features of competitive products, expectations in upcoming models of the product. Then neutrosophic numbers have been used to determine truthiness, falsity and indeterminacy of each opinion and based on such opinions, rank of a company is determined.

Suggested Citation

  • Anuradha Banerjee & Basav Roychoudhury & Bidyut Jyoti Gogoi, 2020. "Determining rank in the market using a neutrosophic decision support system," Journal of Business Analytics, Taylor & Francis Journals, vol. 3(2), pages 138-157, July.
    • Handle: RePEc:taf:tjbaxx:v:3:y:2020:i:2:p:138-157
    DOI: 10.1080/2573234X.2020.1834883
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/2573234X.2020.1834883
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/2573234X.2020.1834883?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.

    More about this item

    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:taf:tjbaxx:v:3:y:2020:i:2:p:138-157. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjba .

    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.