Casinos Get Strategic: Revenue Management for Table Games

Michael Chen of the Ontario Lottery & Gaming Corporation, Henry Tsai of The Hong Kong Polytechnic University, and Shiang-Lih Chen McCain of Widener University published “A Revenue Management Model for Casino Table Games” on February 28, 2012 in Cornell Hospitality Quarterly. To view other OnlineFirst articles, please click here. Dr. Tsai kindly provided the following responses to the article.

Who Is The Target Audience For This Article?

The target audience is casino managers, management consultants, operations analysts, casino management system developers, researcher / academia in casino management field.

What Inspired You To Be Interested In This Topic?

The application of yield management theory on hotel industry has been well researched. As a matter of fact, many hotel operators have put yield management theory into practice to improve profitability. On the other hand, very little research literature is available on how to apply yield management theory on table games operations.

Essentially, hotel operations and table game operations are very similar. Both sell rights to use the facility for a given period of time – hotel operators sell rights to use the hotel room whereas table game operators sell rights to occupy a table game seat. Both have a perishable inventory –the value of a hotel room for today is gone forever if it cannot be sold by today while the value of a table game seat for this hour is gone forever if it isn’t occupied by a table games player by this hour.

The difficulty of applying yield management theory on table game operations is the pricing, a critical component of the yield management theory. One subtle difference between hotel operations and table game operations is how they price their products. Most hotel clients, other than those who purchase through priceline.com, know the exact price before their purchasing decision. On the other hand, neither the table game operators nor the table game players know the exact price of playing table games before the consumption is over. It could be $5,000 an hour – the table game player lost $5,000 to the casino after one hour of play. It could also be $50 an hour. Sometimes it could even be a negative price – the table game player wins from the casino after one hour of play. Though casino operators don’t know for sure how much revenue they can get by selling table games seats for any given hour, casino operators do know, in the long run, the expected value of price for selling table games seats. The measurement used by casino operator to gauge the expected value of table game price is called theoretical win.

All three authors, two professors in hotel management field and one practitioner in the casino industry, have a thorough understanding of hotel yield management theory as well as table games pricing , thanks to the casino management courses they took when studying at UNLV. Knowing few researches have been done on this field, few table games operators have actually applied yield management on daily operations, and the potential profitability improvement yield management approach can bring to the casino industry, the authors decided to conduct a research on this topic to develop a pragmatic approach that can be easily adopted by table game operators.

Were There Findings That Were Surprising To You?

Yes and no. While we expected that, generally speaking, the application of our revenue management model would yield better results for table game operations, we thought that our approach might be less effective during the off-peak hours – measured by the percentage of incremental theoretical win (revenue). The results show otherwise. This approach is effective both during the peak hours and during the off-peak hours.

How Do You See This Study Influencing Future Research And/Or Practice?

One obstacle prevents casino operators from applying analytics to improve profit margin of table game operations is the table games data accuracy. Most data used in this study, such as average wager, spots (seats) occupied, was based on table games supervisors’ observations, which is subject to human errors. However, the advancement in technology, such as RFID-enabled casino chips, or sensors embedded in casino tables to track cards movement, may enable casino operators to capture all the required data electronically in a more reliable way. Just like slots analytics are widely applied to improve the profit margin of slots operations, once casino operators are assured that they are getting reliable table game data, they are more likely to apply table game analytics to improve the profit margin of table game operations. The results of this research may support practitioners to justify why adopting new table games technology is necessary for the casinos when writing capital budget business cases.

Once casino operators can acquire reliable table games data efficiently, we may see more casino operators apply revenue management on their table game operations. Some table games management system may even have a built-in revenue management module. On the other hand, as more researchers are interested in this topic, we may see future researches that focus on increasing forecasting accuracy to increase the revenue management effectiveness.

How Does This Study Fit Into Your Body Of Work/Line Of Research?

This study represents our first joint effort in looking into table game revenue enhancement, which could lead to future research in revenue management in other game types or in conjunction with hotel revenue management for casino hotels.

How Did Your Paper Change During The Review Process?

We appreciated the constructive comments given by the three reviewers, which helped us better the quality of our paper. We revised majority of the paper including introduction, literature review, results and discussions and the conclusion. Especially, we focused our literature review on the applications of revenue management in the casino industry. We also expanded the test period — from one hour to 24 consecutive hours – to test the effectiveness of the proposed yield management approach.

What, If Anything, Would You Do Differently If You Could Go Back And Do This Study Again?

While our proposed model could be applied to other table games, we could collect more data on more types of games and compare the results to further validate our model.

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