Excel F1 Night City Race
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Vol. 11, No. 1, September 2010, pp. 35–42 issn 1532-0545 10 1101 0035
informs
®
doi 10.1287/ited.1100.0053
© 2010 INFORMS
INFORMS
Transactions on Education
Teaching Note
Spreadsheet Modeling to Determine the Optimum
Hotel Room Rate for a Short High-Demand Period
Thin-Yin Leong, Wee-Leong Lee
School of Information Systems, Singapore Management University, Singapore 178902, Republic of Singapore,
{tyleong@smu.edu.sg, wllee@smu.edu.sg}
I
n this article, we describe a business modeling exercise that helps students understand the complex relationship between demand and price. The exercise seeks to determine the optimum pricing, in view of anticipated occupancy response that maximises profit for a hotel. Through the exercise, students are introduced to advanced
Excel operations such as Goal Seek and Solver. This exercise goes through a systematic series of basic modeling steps, starting from identifying input variables and performance measures, and building from a basic model to a final model with sufficient complexity to represent reality. A problem commonly encountered when modeling real-world problems is the lack of complete information; often, information has to be inferred from what little is available from the past. This is demonstrated in developing the hotel occupancy and rate relationship. To ensure the model is robust, we show how trade-off and sensitivity analyses can be conducted.
Key words : spreadsheet modeling; demand management
History : Received: January 2010; accepted: June 2010.
1.
The F1 Night City Race
deciding on the final room pricing. Some managers were considering throwing in extras, such as wine, cheese, fruits, and possibly tickets to popular tourist attractions, to make the steep increase in room rates more palatable.
The objective of this classroom
Vol. 11, No. 1, September 2010, pp. 35–42 issn 1532-0545 10 1101 0035
informs
®
doi 10.1287/ited.1100.0053
© 2010 INFORMS
INFORMS
Transactions on Education
Teaching Note
Spreadsheet Modeling to Determine the Optimum
Hotel Room Rate for a Short High-Demand Period
Thin-Yin Leong, Wee-Leong Lee
School of Information Systems, Singapore Management University, Singapore 178902, Republic of Singapore,
{tyleong@smu.edu.sg, wllee@smu.edu.sg}
I
n this article, we describe a business modeling exercise that helps students understand the complex relationship between demand and price. The exercise seeks to determine the optimum pricing, in view of anticipated occupancy response that maximises profit for a hotel. Through the exercise, students are introduced to advanced
Excel operations such as Goal Seek and Solver. This exercise goes through a systematic series of basic modeling steps, starting from identifying input variables and performance measures, and building from a basic model to a final model with sufficient complexity to represent reality. A problem commonly encountered when modeling real-world problems is the lack of complete information; often, information has to be inferred from what little is available from the past. This is demonstrated in developing the hotel occupancy and rate relationship. To ensure the model is robust, we show how trade-off and sensitivity analyses can be conducted.
Key words : spreadsheet modeling; demand management
History : Received: January 2010; accepted: June 2010.
1.
The F1 Night City Race
deciding on the final room pricing. Some managers were considering throwing in extras, such as wine, cheese, fruits, and possibly tickets to popular tourist attractions, to make the steep increase in room rates more palatable.
The objective of this classroom
References: Canina, L., C. A. Enz. 2008. Pricing for revenue enhancement in Asian and Pacific region hotels: A study of relative pricing strategies. Cornell University Center for Hospitality Res. Report 8(3). http://www.hotelschool.cornell.edu/research/chr/pubs/ reports/abstract-14684.html. Enz, C. A., L. Canina, M. Lomanno. 2009. Competitive pricing decisions in uncertain times. Cornell Hospitality Quart. 50(3) 325–341.