[Forecasting and Revenue Management in Hotel: Case Study of a Hotel]

by

Acknowledgement

I would take this opportunity to thank my research supervisor, family and friends for their support and guidance without which this research would not have been possible.

Declaration

I, [type your full first names and surname here], declare that the contents of this dissertation/thesis represent my own unaided work, and that the dissertation/thesis has not previously been submitted for academic examination towards any qualification. Furthermore, it represents my own opinions and not necessarily those of the University.

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Abstract

In this study we try to explore the concept of forecasting and revenue management in hotel in a holistic context. The main focus of the research is on forecasting and revenue management and its relation with hotel industry. The research also analyzes many aspects of forecasting and revenue management hospitality business and tries to gauge its effect on forecasting and revenue management on hotel. Finally the research describes various factors which are responsible for forecasting and revenue management and tries to describe the overall effect of forecasting and revenue management on hospitality business.

Table of Contents

ACKNOWLEDGEMENT2

DECLARATION3

ABSTRACT4

LIST OF TABLES8

CHAPTER 1: INTRODUCTION10

Background of the study10

Research Aims and Objectives12

Revenue Management12

CHAPTER 2: LITERATURE REVIEW14

History of Revenue Management14

Defining Revenue Management14

Importance of revenue management14

Conditions of Revenue Management15

Revenue Management Formulae and Measurement15

Measurements15

Internal Measurements16

Revenue16

Occupancy Percentage16

Average Daily Rate17

RevPAR- Revenue per Available Room17

Contribution Margin (Net Revenue)17

Identical Net Revenue18

GOPPAR- Gross Operating Profit per Available room18

Overbooking and Cancellations19

External Measurements19

Price Management20

Pricing Strategies23

Price Discrimination23

Pricing Grid25

Rate Optimization32

Price Sensitivity, or Elasticity of Demand32

Price Elasticity of Demand33

Price Elasticity of Revenue34

Practical Elasticity Analysis37

Traditional CVP Analysis38

Distribution Channel Management50

UK Human Resource Management52

HRM research in hotels54

HRM and commitment55

CHAPTER 3: METHODOLOGY57

Research Metho57

Stage 1: Choice hotels157

Results58

FIGURE 20. HOTEL 1 FORECAST ERROR (MAE).59

TABLE 7. BEST NUMBER OF WEEKS FOR EACH FORECASTING METHOD60

Stage 2: Marriott hotels data60

Unconstraining method66

Number of periods to include in forecast67

Which data to use68

Outliers68

Reporting forecast accuracy69

Revenue impact of forecast accuracy70

Level of aggregation71

CHAPTER 4: RESULTS AND DISCUSSION72

Results72

Historical models78

Advanced booking models79

Additive models79

Multiplicative and time-series methods80

Combined forecast methods80

Method comparison82

Forecasting methods used in this paper82

Other forecasting issues83

What to forecast84

CHAPTER 5: CONCLUSION85

REFERENCES91

List of figures

FIGURE 1. REVENUE MANAGEMENT AS A BUSINESS PROCESS (GABOR FORGACS, 2010, P.4)13

FIGURE 2. THE CHALLENGE: HOW TO MANAGE COMPLEXITY?15

FIG 3. HOTEL PRICING STRATEGY25

FIGURE 4. PRICE DISCRIMINATION25

FIGURE 5. PRICE AND DEMAND26

FIGURE 6. PRICING GRID27

FIGURE 7. RATE GRID28

FIGURE 8. BARS 129

FIGURE 9. BARS 229

FIGURE 10. DEMAND LEVEL30

FIGURE 11. DEMAND LEVEL PRICE ELASTICITY OF DEMAND WILL ALWAYS HAVE A NEGATIVE VALUE IN THIS CONTEXT.36

FIGURE 12. EQUATION37

FIGURE 13. REVENUE37

FIGURE 14. REVENUE & ELASTICITY OF REVENUE40

FIGURE 15. Z-VALUE OF 1.5 SHOWN DIAGRAMMATICALLY46

FIGURE 16. OBSERVATIONS TO BE FOUND UNDER THE NORMAL DISTRIBUTION CURVE47

FIGURE 17. BREAK-EVEN CHART OF MARRIOTT HOTEL50

FIGURE 18. NORMAL DISTRIBUTION FOR MARRIOTT HOTEL ROOMS SOLD52

FIGURE 19. PROFIT-VOLUME CHART OF THE MARRIOTT HOTEL55

FIGURE 20. HOTEL 1 FORECAST ERROR (MAE).88

FIG. 21. SAMPLE DATA SET, PROPERTY 1, RATE CATEGORY 1, LENGTH OF STAY 1.90

FIG. 22. BREAKOUT OF LENGTH OF STAY FOR A TYPICAL RATE CATEGORY.90

FIG.23. BREAKOUT OF RATE CATEGORY FOR A TYPICAL LENGTH OF STAY.90

FIG. 24. FORECAST ACCURACY (MAE) FOR PROPERTY 1 (# OF ROOMS=1234), RATE CATEGORY 3 (SUMMARIZED ACROSS ALL SEVEN LOS, AVERAGED ACROSS ALL READING ...