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An Artificial Neural Network technique for on-line hotel booking

Listed author(s):
  • Renato Bettin


    (SG Application & Consulting)

  • Francesco Mason


    (Department of Management, Università Ca' Foscari Venezia)

  • Marco Corazza


    (Department of Economics, Università Ca' Foscari Venezia)

  • Giovanni Fasano


    (Department of Management, Università Ca' Foscari Venezia)

In this paper the use of Artificial Neural Networks (ANNs) in on-line booking for hotel industry is investigated. The paper details the description, the modeling and the resolution technique of on-line booking. The latter problem is modeled using the paradigms of machine learning, in place of standard `If-Then-Else' chains of conditional rules. In particular, a supervised three layers MLP neural network is adopted, which is trained using information from previous customers' reservations. Performance of our ANN is analyzed: it behaves in a quite satisfactory way in managing the (simulated) booking service in a hotel. The customer requires single or double rooms, while the system gives as a reply the confirmation of the required services, if available. Moreover, we highlight that using our approach the system proposes alternative accommodations (from two days in advance to two days later with respect to the requested day), in case rooms or services are not available. Numerical results are given, where the effectiveness of the proposed approach is critically analyzed. Finally, we outline guidelines for future research.

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File Function: First version, 2011
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Paper provided by Department of Management, Università Ca' Foscari Venezia in its series Working Papers with number 10.

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Length: 18 pages
Date of creation: Oct 2011
Handle: RePEc:vnm:wpdman:10
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