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The Pricing of Meetings and Event Spaces in Hotel Revenue Management

Received: 26 November 2021     Accepted: 15 December 2021     Published: 24 December 2021
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Abstract

In this paper, we discuss the pricing of Meetings and Event Spaces in Hotel Revenue Management. We use a measure called Attendee Density, for a Meeting and Event Space, which is similar to the measure of Occupancy for a hotel room. Based on the method for forecasting Occupancy for a hotel room, we forecast Attendee Density for an Event Space. The Attendee Density is the ratio of Attendees Booked to Capacity. To forecast Attendee Density, we have to forecast how many attendees will book in the future. To forecast how many attendees will book at a specific date in the future, we sum our current Reservations on Hand and a quantity called the Pickup. The Pickup is calculated based on a Booking Curve. The Booking Curve is a graph which plots Reservations on Hand against Time. It shows us how bookings happen leading upto a particular event. Once we calculate Pickup based on the Booking Curve, we can forecast how many attendees will book at a date in the future. We can then calculate Attendee Density. A high Attendee Density for the future results in charging a High Price today. On the other hand, a low future Attendee Density results in charging a Low Price currently. We also discuss how we can go about determining a High Price and a Low Price for a Meeting and Event Space.

Published in American Journal of Operations Management and Information Systems (Volume 6, Issue 4)
DOI 10.11648/j.ajomis.20210604.13
Page(s) 86-91
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Hotel Revenue Management, Meetings and Event Spaces, Pricing, Attendee Density

References
[1] Cornell School of Hotel Administration’s Online Course on ‘Forecasting and Availability Controls’.
[2] http://www.quora.com, accessed in August 2018.
[3] Cullen, K. (2015) The Evolving Dynamics of Revenue Management, HSMAI Foundation and STR, Nashville.
[4] http://www.ideas.com, Webinar, `Smart Space by IDeaS: Extending Revenue Strategy to Meetings and Events’.
[5] Talluri, K. and van Ryzin, G. (2005) The Theory and Practice of Revenue Management, Springer, New York.
[6] Phillips, R. (2005) Pricing and Revenue Optimization, Stanford University Press, Stanford, California.
[7] Ivanov, S. (2014) Hotel revenue management: From theory to practice. Zangador.
[8] Kimes, S. E. (2011) The future of hotel revenue management. Journal of Revenue and Pricing Management, 10 (1), pp. 62-72.
[9] Weatherford, L. R. and Kimes, S. E. (2003) A comparison of forecasting methods for hotel revenue management. International journal of forecasting, 19 (3), pp. 401-415.
[10] Ivanov, S. and Zhechev, V. (2012) Hotel revenue management–a critical literature review. Tourism: an international interdisciplinary journal, 60 (2), pp. 175-197.
[11] Noone, B. M., McGuire, K. A. and Rohlfs, K. V. (2011) Social media meets hotel revenue management: Opportunities, issues and unanswered questions. Journal of Revenue and Pricing Management, 10 (4), pp. 293-305.
[12] Choi, S. and Mattila, A. S. (2004) Hotel revenue management and its impact on customers' perceptions of fairness. Journal of Revenue and pricing Management, 2 (4), pp. 303-314.
[13] Abrate, G. and Viglia, G. (2016) Strategic and tactical price decisions in hotel revenue management. Tourism Management, 55, pp. 123-132.
[14] Choi, S. and Kimes, S. E. (2002) Electronic distribution channels' effect on hotel revenue management. The Cornell hotel and restaurant administration quarterly, 43 (3), pp. 23-31.
[15] Kimes, S. E. (2016) The evolution of hotel revenue management. Journal of Revenue and Pricing Management, 15 (3), pp. 247-251.
Cite This Article
  • APA Style

    Siddharth Mahajan. (2021). The Pricing of Meetings and Event Spaces in Hotel Revenue Management. American Journal of Operations Management and Information Systems, 6(4), 86-91. https://doi.org/10.11648/j.ajomis.20210604.13

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    ACS Style

    Siddharth Mahajan. The Pricing of Meetings and Event Spaces in Hotel Revenue Management. Am. J. Oper. Manag. Inf. Syst. 2021, 6(4), 86-91. doi: 10.11648/j.ajomis.20210604.13

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    AMA Style

    Siddharth Mahajan. The Pricing of Meetings and Event Spaces in Hotel Revenue Management. Am J Oper Manag Inf Syst. 2021;6(4):86-91. doi: 10.11648/j.ajomis.20210604.13

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  • @article{10.11648/j.ajomis.20210604.13,
      author = {Siddharth Mahajan},
      title = {The Pricing of Meetings and Event Spaces in Hotel Revenue Management},
      journal = {American Journal of Operations Management and Information Systems},
      volume = {6},
      number = {4},
      pages = {86-91},
      doi = {10.11648/j.ajomis.20210604.13},
      url = {https://doi.org/10.11648/j.ajomis.20210604.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajomis.20210604.13},
      abstract = {In this paper, we discuss the pricing of Meetings and Event Spaces in Hotel Revenue Management. We use a measure called Attendee Density, for a Meeting and Event Space, which is similar to the measure of Occupancy for a hotel room. Based on the method for forecasting Occupancy for a hotel room, we forecast Attendee Density for an Event Space. The Attendee Density is the ratio of Attendees Booked to Capacity. To forecast Attendee Density, we have to forecast how many attendees will book in the future. To forecast how many attendees will book at a specific date in the future, we sum our current Reservations on Hand and a quantity called the Pickup. The Pickup is calculated based on a Booking Curve. The Booking Curve is a graph which plots Reservations on Hand against Time. It shows us how bookings happen leading upto a particular event. Once we calculate Pickup based on the Booking Curve, we can forecast how many attendees will book at a date in the future. We can then calculate Attendee Density. A high Attendee Density for the future results in charging a High Price today. On the other hand, a low future Attendee Density results in charging a Low Price currently. We also discuss how we can go about determining a High Price and a Low Price for a Meeting and Event Space.},
     year = {2021}
    }
    

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    T2  - American Journal of Operations Management and Information Systems
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    AB  - In this paper, we discuss the pricing of Meetings and Event Spaces in Hotel Revenue Management. We use a measure called Attendee Density, for a Meeting and Event Space, which is similar to the measure of Occupancy for a hotel room. Based on the method for forecasting Occupancy for a hotel room, we forecast Attendee Density for an Event Space. The Attendee Density is the ratio of Attendees Booked to Capacity. To forecast Attendee Density, we have to forecast how many attendees will book in the future. To forecast how many attendees will book at a specific date in the future, we sum our current Reservations on Hand and a quantity called the Pickup. The Pickup is calculated based on a Booking Curve. The Booking Curve is a graph which plots Reservations on Hand against Time. It shows us how bookings happen leading upto a particular event. Once we calculate Pickup based on the Booking Curve, we can forecast how many attendees will book at a date in the future. We can then calculate Attendee Density. A high Attendee Density for the future results in charging a High Price today. On the other hand, a low future Attendee Density results in charging a Low Price currently. We also discuss how we can go about determining a High Price and a Low Price for a Meeting and Event Space.
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Author Information
  • Production and Operations Management Area, Indian Institute of Management, Bangalore, India

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