IDEAS home Printed from https://ideas.repec.org/a/igg/jisss0/v9y2017i2p27-45.html
   My bibliography  Save this article

Framework for a Hospitality Big Data Warehouse: The Implementation of an Efficient Hospitality Business Intelligence System

Author

Listed:
  • Célia M.Q. Ramos

    (CEFAGE & ESGHT, University of the Algarve, Faro, Portugal)

  • Daniel Jorge Martins

    (LARSyS & ISE, University of the Algarve, Faro, Portugal)

  • Francisco Serra

    (ESGHT, University of the Algarve, Faro, Portugal)

  • Roberto Lam

    (LARSyS & ISE, University of Algarve, Faro, Portugal)

  • Pedro J.S. Cardoso

    (LARSyS & ISE, University of the Algarve, Faro, Portugal)

  • Marisol B. Correia

    (CEG-IST & ESGHT, University of the Algarve, Faro, Portugal)

  • João M.F. Rodrigues

    (LARSyS & ISE, University of the Algarve, Faro, Portugal)

Abstract

In order to increase the hotel's competitiveness, to maximize its revenue, to meliorate its online reputation and improve customer relationship, the information about the hotel's business has to be managed by adequate information systems (IS). Those IS should be capable of returning knowledge from a necessarily large quantity of information, anticipating and influencing the consumer's behaviour. One way to manage the information is to develop a Big Data Warehouse (BDW), which includes information from internal sources (e.g., Data Warehouse) and external sources (e.g., competitive set and customers' opinions). This paper presents a framework for a Hospitality Big Data Warehouse (HBDW). The framework includes a (1) Web crawler that periodically accesses targeted websites to automatically extract information from them, and a (2) data model to organize and consolidate the collected data into a HBDW. Additionally, the usefulness of this HBDW to the development of the business analytical tools is discussed, keeping in mind the implementation of the business intelligence (BI) concepts.

Suggested Citation

  • Célia M.Q. Ramos & Daniel Jorge Martins & Francisco Serra & Roberto Lam & Pedro J.S. Cardoso & Marisol B. Correia & João M.F. Rodrigues, 2017. "Framework for a Hospitality Big Data Warehouse: The Implementation of an Efficient Hospitality Business Intelligence System," International Journal of Information Systems in the Service Sector (IJISSS), IGI Global, vol. 9(2), pages 27-45, April.
  • Handle: RePEc:igg:jisss0:v:9:y:2017:i:2:p:27-45
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJISSS.2017040102
    Download Restriction: no
    ---><---

    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:igg:jisss0:v:9:y:2017:i:2:p:27-45. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.