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Optimal Room Charge and Expected Sales under Discrete Choice Models with Limited Capacity (Forthcoming in "International Journal of Hospitality Management")

Author

Listed:
  • Taiga Saito

    (Financial Research Center at Financial Services Agency, Government of Japan)

  • Akihiko Takahashi

    (Graduate School of Economics, The University of Tokyo.)

  • Hiroshi Tsuda

    (Department of Mathematical Sciences, Doshisha University, Visiting Professor at the Institute of Statistical Mathematics)

Abstract

In this paper, we introduce a model that incorporates features of the fully transparent hotel booking systems and enables estimates of hotel choice probabilities in a group based on the room charges. Firstly, we extract necessary information for the estimation from big data of online booking for major four hotels near Kyoto station. Then, we consider a nested logit model as well as a multinomial logit model for the choice behavior of the customers, where the number of rooms available for booking for each hotel are possibly limited. In addition, we apply the model to an optimal room charge problem for a hotel that aims to maximize its expected sales of a certain room type in the transparent online booking systems. We show numerical examples of the maximization problem using the data of the four hotels of November 2012 which is a high season in Kyoto city. This model is useful in that hotel managers as well as hotel investors, such as hotel REITs and hotel funds, are able to predict the potential sales increase of hotels from online booking data and make use of the result as a tool for investment decisions.

Suggested Citation

  • Taiga Saito & Akihiko Takahashi & Hiroshi Tsuda, 2016. "Optimal Room Charge and Expected Sales under Discrete Choice Models with Limited Capacity (Forthcoming in "International Journal of Hospitality Management")," CARF F-Series CARF-F-380, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    • Handle: RePEc:cfi:fseres:cf380
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    Cited by:

    1. Guizzardi, Andrea & Pons, Flavio Maria Emanuele & Angelini, Giovanni & Ranieri, Ercolino, 2021. "Big data from dynamic pricing: A smart approach to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1049-1060.
    2. Taiga Saito & Akihiko Takahashi & Noriaki Koide & Yu Ichifuji, 2017. "Optimal Overbooking Strategy in Online Hotel Booking Systems," CIRJE F-Series CIRJE-F-1065, CIRJE, Faculty of Economics, University of Tokyo.
    3. Taiga Saito & Shivam Gupta, 2022. "Big data applications with theoretical models and social media in financial management," CARF F-Series CARF-F-550, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    4. Judita Peterlin & Maja Meško & Vlado Dimovski & Vasja Roblek, 2021. "Automated content analysis: The review of the big data systemic discourse in tourism and hospitality," Systems Research and Behavioral Science, Wiley Blackwell, vol. 38(3), pages 377-385, May.
    5. Taiga Saito & Shivam Gupta, 2022. "Big Data Applications with Theoretical Models and Social Media in Financial Management," CIRJE F-Series CIRJE-F-1205, CIRJE, Faculty of Economics, University of Tokyo.
    6. Fatemeh Binesh & Amanda Belarmino & Carola Raab, 2021. "A meta-analysis of hotel revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(5), pages 546-558, October.
    7. Taiga Saito & Akihiko Takahashi & Noriaki Koide & Yu Ichifuji, 2017. "Optimal overbooking strategy in online hotel booking systems¡ÊRevised as "Application of Online Booking Data to Hotel Revenue Management" in F-448¡Ë," CARF F-Series CARF-F-421, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

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