INTRODUCTION
Service organizations face a challenge in terms of managing demand and capacity. Revenue management (also known as yield management) is a technique designed to address that challenge. Mudie and Pirrie, define revenue management as ‘provision of the right service to the right customer at the right time for the right price’ (164). Therefore, revenue management is a technique used to determine the optimal price of products generated by sale. It involves detailed forecasting of demand behavior and sophisticated mathematical modeling. There exists a strong relation between revenue management and marketing. Since, revenue management is responsible for demand control, including setting rate and availability controls, marketing is responsible for demand generation, campaign strategies, customer relationship management and loyalty programs. This describes techniques to allocate limited resources, such as airplane seats or hotel rooms, among a variety of customers, such as business or leisure travelers while optimizing profits.
There are several definitions of revenue management in literature. An expert in the airline industry, Bob Cross, president of the consulting firm Aeronomics Inc., uses a general definition to express the concept of ‘yield’ management. He says it is “using price incentives and inventory controls to maximize the value of existing processes” (Cross, 69). Cross (1997) states that revenue management focuses the organization on maximizing profitability by forecasting consumer behavior at the micro-level and control inventory availability at each price level. From the hotel industry’s perspective it has been defined as “charging a different rate for the same service to a different individual” and “controlling the tradeoff between average rate and occupancy.”
Revenue management is undoubtedly a significant advance in the service industries. However, certain industry branches are better suited than others, especially in the aviation and tourism industry. Among the existing industries where revenue management is already applied, one can observe that no prototypical model for the application and implementation exists. Rather, as Lieberman states, the root concepts are the same, but the applications and the techniques differ widely (Lieberman, 34). Thus, the decision to apply revenue management techniques depends on the specific circumstances of the company and the industry branch in which it is found. In the end, it comes down to a cost-benefit analysis for each individual company, where management assesses potential benefits versus potential costs and risks associated with the process. Following Talluri and van Ryzin (17), once the technology and methodology mature within a specific industry branch, the majority of companies will benefit from revenue management. However, the term revenue management is misleading, since it encompasses far more than revenue as Pinchuk (283) pointed out. Instead, revenue management is more accurately reflected by the term profit optimization since the objective is to optimize profit over just increasing revenue or lowering cost.
In this research, revenue management is examined with the concepts of marketing. It is clear that there are key areas of overlap in terms of segmentation, the marketing mix, particularly optimal price and the product life cycle. The focus of this research is on the area of Consumer demand, Inventory control, and Price elasticity.
LITERATURE REVIEW
The field of revenue management subsumes approaches of dynamic and simultaneous price and capacity management (Lindenmeier and Tscheulin, 630) and originates from the passenger airline industry. In the literature, especially in early papers on the subject, revenue management is also referred to as yield management. Some authors, though, have argued that the term yield (meaning, as a technical term in the airline industry, the actually obtained price) does not reflect the aspect of controlling price and quantity simultaneously (Weatherford and Bodily, 833) and therefore prefer the term revenue (i.e., price and quantity) management. Today, the two terms are considered synonymous (McGill and van Ryzin, 251). Weatherford and Bodily have proposed the term perishable assets though price segmentation, which is thus explicitly not restricted to the airline industry (835). In this thesis, the term revenue management is used, with the hospitality industry context in mind.
Background
Revenue management origins from the aviation industry of the late 1960s and early 1970s through the research of capacity management decisions (Lieberman, 92). Up to that time, yield management was still rather narrowly and its application concentrated on capacity management and overbooking, and little was done in the area of dynamic pricing. Still, prices for single classes were generally assumed as fixed and the managers had to decide when to open or close a certain class depending on the demand, but they did not yet have the control to set dynamic prices for these tickets. But with the work of Belobaba and the success of American Airlines among others, interest in quantity-based yield management expanded and spread to other industries (183). With the increase of interest beyond the aviation industry, the term’s use changed and the expression ‘revenue management’ was established, since it was more acceptable to executives outside the airline industry.
Today, revenue management techniques are applied in many different industries, such as automobile rental, hospitality and gastronomy, passenger railways, internet service providers and cruising lines (Jerenz, 9). Two industries which incorporate revenue management most heavily are aviation and hospitality. Through the use of specialized software, airlines monitor seat reservations and react accordingly, for example by offering discounts when the seats would otherwise be vacant. Hotels apply revenue management in the same way by calculating rates and sales restrictions to maximize the return for the property.
Conditions for the Application of Revenue Management
Harris and Pinder (1995) and Weatherford and Bodily (1992) have identified several common characteristics of businesses and situations in which revenue management is effectively applied:
a) Relative fixed capacity – e.g. once a hotel has rented out all its rooms further demand cannot be met without substantial capital investment.
b) Perishable inventory – a major constraint for services is time or more specifically time during which a unit of capacity is available. If hotel room (unit of capacity) is not sold for a particular date the revenue that would have been gained is lost.
c) Segmented markets – where the market for a service can be segmented according to certain criteria, e.g. price sensitivity
d) Fluctuating demand – where the adoption of various pricing approaches enables the reduction of peaks and valleys in variable demand. Success in this regard results in more effective utilization capacity
e) Services that can be sold in advance through reservation systems – allows for better use of capacity
f) Low variable to fixed cost ratio – in service pricing some contribution must be made towards fixed cost. The low level of variable cost, e.g. cleaning a hotel room, is invariably greater than if it was not sold. That is why yield management is usually regarded as a profit-enhancing strategy.
COMPONENTS OF REVENUE MANAGEMENT SYSTEMS
Revenue management systems serve the simultaneous control of price and capacity. However, in a revenue management process, the control problem is usually divided in multiple sub-problems and solved sequentially (Stuhlmann, 243). Figure 1 below gives an overview of the generic structure of an integrated revenue management system. The process can be divided into three parts: data input, forecasting, and optimization. The optimization part comprises price and capacity control, the latter being achieved by the application of models for inventory control and overbooking.
The contributions to the revenue management literature introduced in the following focus on overbooking, inventory control, pricing and forecasting.
Overbooking
Intentionally setting booking levels higher than capacity that is, selling more capacity than one actually has, is called overbooking. Starting in the 1960s, airlines have countered cancellations and no-shows by overbooking, i.e., by accepting higher number of reservations than seats available. Smith, Leimkuhler and Darrow state that, “on average, about half of all reservations made for a flight are canceled or become no-shows” (11).
Overbooking is an essential revenue management technique in optimizing room revenue. Through overbooking hotels risk being unable to accommodate all those guests who have reservations, and this could result in customer dissatisfaction. Within an effective revenue management system, overbooking levels are not calculated by mere chance but are set after a thorough and detailed analysis of historical data and projected trends. Predictions of cancellations, no-shows and even early guest departures also form elements of a complex calculation, which facilitates the establishment of capacity levels. Surprisingly, in 82 per cent of the sample hotels staff in the UK still referred to management on a daily basis for instructions on the number of rooms to be overbooked. Twenty-one hotels (17 of which were classified as understanding revenue management) had a computer software which suggested a level of overbooking for each day. As such, while most hotels were seen to overbook rooms, the effective application of revenue management requires more formalized approach than those used by the sample hotels in order to establish precise overbooking levels (Ingold, Yeoman and McMahon-Beattie, 247).
Inventory control
The application of revenue management has been most effective when applied to operations that have a perishable inventory. Thus, inventory control focuses on allocating capacity to fare classes, determining the optimal availability or non-availability policy for fare classes, and thus on whether or not to accept or denying booking request. The problem is one of matching a probabilistic and sometimes unknown demand to a set of finite resources in a manner which will optimize profits or utilization.
In the sphere of hospitality, this is a difficult optimization problem. The duration of the service offered by a restaurant is unpredictable and prices are usually fixed, making inventory control, i.e., pacing and prediction of customer arrivals and length of stay, the predominant lever of revenue management. In some ways yield management is the reverse of the inventory control problem, in that the decision is not how much to stock, but rather, given a fixed capacity, how demand should be managed to ensure optimal usage and revenue maximization.
Pricing
The tariff structure in a revenue management system is based on the principle of price discrimination or segmented pricing (Talluri and van Rtzin, 352). This is the practice by which the seller charges different prices to buyers for the same product or slightly different versions of the same product. Ideally, the seller first segments the market into groups of customers by their respective price sensitivity and creates restrictions between the segments that prevent dilution. Then the seller establishes a price for each class of customers based on forecasted demand and allocates the fixed capacity among the classes.
Similarly, those managers who view pricing as essentially a marketing-related task make the case for the utilization of a variety of pricing approaches depending upon the goals of management. These approaches include skim pricing, penetration pricing, neutral pricing and cost-oriented pricing. However, experienced revenue managers understand that differential pricing is a more powerful pricing approach than fixed pricing. This is true, in part, because price differentiation also provides the rationale to practice inventory management; one of the most critical tasks that can be undertaken by effective hoteliers.
To better understand the power of segmented pricing, assuming that the market for a particular good follows the simple straight line price/demand relationship, a single fixed price of $50 and there is enough demand to sell 50 units of inventory. This results in $2500 in revenues. However, the same price/demand relationship yields $4000 if consumers are presented with multiple prices.
Currently, the hospitality industry is faced with a situation that sees some hotels employing poor and potentially risky pricing strategies. Such strategies have the potential to not just negatively impact the revenue of an individual business, but also damage an entire market.
Today, most hoteliers still understand cost-based rooms pricing best, but many have gained a much better understanding of the logic related to yield management. In fact, it is that improved understanding of yield management that has today began to move very experienced hoteliers away from an unwieldy approach to yield management and toward price management practices designed to optimize revenues in a customer-centre manner.
Forecasting
One of the key principles of revenue management lies in the firm’s ability to forecast demand. Revenue management systems must be able to advice on demand conditions by analyzing reservation patters, arrivals, departures and score of other demand characteristics. Recent literature has suggested that revenue management systems with demand forecasting algorithms are increasingly expensive to implement, both in real terms and in lost opportunities.
Moreover, research has suggested that these complex sophisticated revenue management systems are not infallible. In fact, with demand forecasts using the data of the past, and sales departments using present day information, conflicts then occur, and many revenue management systems operate with some level of human intervention, often using these systems as merely a guide (Ng, 122).
Demand-Price Relationship
Most hospitality and tourism businesses serve a wide variety of clientele groups. It is feasible that every operation could have a different mix of consumers, even those operating under the same company or brand name. Of the same accord, it is important to acknowledge that the same consumer can fall into different target market categories. The corporate business traveler during the week becomes a leisure traveler when on holiday or at weekends. Different occasions find the same consumer having different expectations and needs. Such a concept is termed elasticity of demand. Elasticity of demand has three commonly adopted measures – price elasticity, income elasticity and cross elasticity – representing the relationship between the elasticity measure and quantity demanded.
Price elasticity represents the relationship between a change in price and a change in quantity demanded. Income elasticity represents the relationship between a change in consumer income and quantity demanded. Cross elasticity represents the relationship between the change in the price of product x and the quantity of product y demanded. However, the most relevant elasticity measure for the purposes of yield management is price elasticity of demand. The formula provides a result of <1, >1 or 1. A result of <1 indicates a market that is highly elastic, i.e. a change in price will have little effect on quantity demanded, the lower the result, the less price sensitive the market. A result of >1 indicates an elastic market, meaning a more price-sensitive market, while a result of 1 indicates unitary elasticity, i.e. a direct relationship between the change in price and the quantity demanded.
Considering an operation that has a mixture of business and leisure markets all with varying degrees of elasticity, the pricing decision becomes critical to ensure that price-insensitive consumers (those who are highly inelastic) pay full tariff and do not trade down, and that a price is reached where less of the price-sensitive markets are attracted. Combine this with the nature of environments and the problems of seasonal markets and it becomes highly evident that an understanding of the nature of hospitality and tourism units is essential in implementing yield management strategies. Therefore, demand-price relationship is useful in determining the revenue generating potential of an organization.
IMPLEMENTATION AND IMPACT
This focuses on implementation issues and the impact of revenue management both on the seller’s financial performance and the buyer’s perception. Lahoti (2002) focuses on the implementation of revenue management systems and stresses the necessity of management commitment for a successful implementation. From the airline industry perspective, Smith, Leimkuhler and Darrow (2001) describe the prospects of airline marketing and the opportunities for revenue management resulting from using internet platforms in business-to-business and business-to-consumer platforms. Going one step further, Toh and Raven (2003) propose an integrated internet marketing strategy that puts the airline’s revenue management activities at the centre while embracing all marketing and customer relationship management activities in order to archive revenue management goals in consistency with consumer needs.
Areas of Application
Because revenue management originated from the passenger airline industry, the majority of publications have developed in this field. However, other areas, which revenue management has successfully implemented include: restaurants, contract manufacturing, broadcasting, internet service providers, non-profit companies, golf courses, passenger railways, and cruise liners.
CONCLUSION
As discussed, revenue management is a technique to determine the optimal price of products and services, with the objective to maximize associated expected profits generated by sale. In sum, revenue management has experienced tremendous growth since its introduction in the aviation industry, and its techniques and methods applied to an increasing set of business areas. However, service providers face a particular problem when it comes to demand management and capacity utilization. Unlike manufacturing, service organizations cannot stock-pile their ‘output’ in a warehouse and wait for demand to materialize. Moreover, demand for services can fluctuate in such an unpredictable way that capacity is either unable to cope, or grossly under-utilized. Achieving a match between demand and capacity can be adjusted. A number of options are available for making capacity more flexible, two of which are gathering interest, namely using customers as productive resources, and outsourcing. Demand represents more of a challenge. Among the options here, variable pricing remains attractive. Yield or Revenue management proves to be an attractive technique as discussed in the literature review. However, no matter how successful yield management is, there still remains the residual matter of customers having to wait and queue. This is simply a feature of service for which there appears to be no available solution. Nevertheless, attending to the behavioral principles governing queuing and waiting should focus on making this phenomenon as comfortable and fair as possible for customers.
Works Cited
Belobaba, P.P. 'Airline Yield Management: An overview of Seat Inventory Control'. Transport Science, Vol. 21, No. 2, 1989.
Cross, R. Revenue management: hard-core tactics for market domination, New York: Broadway Books, 1997.
---. 'Yield Management: new horizons for a dark science.' paper presented to paper presented at Yield Management Multi-industry Conference, NC: Charlotte, 1989.
Harris, Frederick, and Jonathan Pinder. A revenue management approach to demand management and order booking in assemble-to-order manufacturing. Journal of Operations Management. Vol. 13, 2001: No.4.
Ingold, Anthony, Ian Yeoman and Una McMahon-Beattie. Yield management: strategies for the service industries. 2nd ed. London: Thomas learning, 2007.
Jerenz, André. Revenue Management and Survival Analysis in the Automobile Industry. Frankfurt: Springer, 2008.
Kalyan, Talluri, and Garrett van Ryzin. The theory and practice of revenue management. New York: Springer, 2004.
Lahoti, A. Why CEOs Should Care About Revenue Management. OR/MS. February 2002, http://www.lionhrtpub.com/orms-2-02/rm.html
Lieberman, W.H. 'Implementing Yield Management', paper presented to ORSA/TIMS National meeting presentation. San Fransisco. 1992.
Lindenmeier, J., & Tscheulin, D. K. The effects of inventory control and denied boarding on customer satisfaction: The case of capacity-based airline revenue management. 2007.
McGill, J.I. and van Ryzin, G. ‘Revenue management: research overview and prospects’, Transportation Science, Vol. 33, 1999.
Mudie, Peter, and Angela Pirrie. Services Marketing Management. 3rd ed. Oxford: Elsevier, 2006.
Ng, Irene. The pricing and revenue management of services: a strategic approach. New York: Routledge, 2008
Pinchuk, Steve. Revenue management’s ability to control marketing, pricing and product development, Journal of revenue and pricing management, Vol. 1, No. 1. 2002.
Simon, W. A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield management, overbooking and pricing. 1992. Operations Research 40 (5)
Smith, BC, Leimkuhler, JF & Darrow, RM., 'Yield management at American Airlines', Interfaces, Vol. 22, No. 1, 1992: 8-31..
Toh, R.S. and Raven, P. ‘Perishable asset revenue management: Integrated Internet marketing strategies for the airlines’, Transportation Journal, Vol. 42, 2003: 30–43.
Weatherford L. R., and Bodily S. E. A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management, Overbooking, and Pricing. Operation Research, 1992
