Modelling a Decision Maker's Preferences,Part 2: A Tool for Pricing Decisions in the Hospitality Industry

Abstract

Pricing decisions in the hospitality industry are subject to a number of different and competing considerations, including economic (profit), marketing (what price will guarantee a sale), yield, wear and tear on the facility, the owner's preferences, and the manager's preferences. Since a manager balances all these conflicting considerations in determining his or her own preferences, the manager's preferences should be used as the starting point for generating a pricing policy. Specifically, the manager's preferences for the two substitutable attributes – the number of rooms sold and the average room rate – are modelled using the Constrained Choice Table (CCT) to collect the specific preferences and the Linear-Fractional model to fit linear indifference curves with non-constant rates of substitution (unequal slopes) to the CCT data. This model combined with the marginal cost per room is used as a starting point to develop and evaluate different pricing policies. The consequences of using an average room rate, same value room rate pricing policy for two different types of managers, one occupancy level sensitive and the other average room rate sensitive, are evaluated.

Keywords

decision making preferences hospitality yield service

Get full access to this article

View all access options for this article.

References

Ackoff

R. L.

(1981), ‘The art and science of mass management’, Interfaces, Vol 11, No 1.

Brown

J.R.

Israeli

A.A.

Mehrez

(2002), ‘Modelling a decision maker's preferences with different assumptions about the preference structure: Theory development and initial applications for tourism and hospitality management’, Tourism Economics, Vol 8, No 1, pp 39–57.

Chatfield

(1985), ‘The initial examination of data’, Journal of the Royal Statistical Society, Series A, No 5, pp 31–38.

Israeli

A.A.

(2002), ‘Disabled tourists’ accessibility needs in tourist sites', Journal of Travel Research, Vol 41, August, pp 101–104.

Israeli

A.A.

Uriely

(2000), ‘The impact of star ratings and corporate affiliation on hotel room prices’, Tourism and Hospitality Research, Vol 2, No 1, pp 27–36.

Kimes

S. E.

(1989), ‘Yield management: A tool for capacity constrained service firms’, Journal of Operations Management, Vol 8, No 4, pp 348–363.

Lewis

R.C.

Chambers

R.E.

(1989), Marketing Leadership in Hospitality – Foundations and Practices, Van Nostrand Reinhold, New York.

Manocha

D.N.

(1986), Empirical Testing of the Decision Utility Model, unpublished dissertation, Kent State University.

Olsen

M.D.

Tse

E.C.

West

J.J.

(1992), Strategic Management in the Hospitality Industry, Van Nostrand Reinhold, New York.

10.

Orkin

E.B.

(1988), ‘Boosting your bottom line with yield management’, The Cornell Hotel and Restaurant Administration Quarterly, Vol 29, No 1, pp 52–56.

11.

Raeside

(1999), ‘Quantitative methods’, in Yeoman

Ingold

eds, Yield Management: Strategies for the Service Industries, Cassel, London, pp 42–64.

12.

Russell

K. A.

(1999), ‘Expert systems’, in Yeoman

Ingold

eds, Yield Management: Strategies for the Service Industries, Cassel, London, pp 128–140.

13.

Simon

H. A.

(1955), ‘Rational choice and structure of environment’, Psychological Review, Vol 63, pp 129–138.

14.

Yeoman

Ingold

, eds (1999), Yield Management: Strategies for the Service Industries, Cassel, London.

15.

Yoon

P.K.

Hwang

(1995), Multiple Attribute Decision Making, Sage, Thousand Oaks, CA.