Revenue management is applied widely to predict the behavior of the customer through the optimization of the usage of product and price strategies in order to maximize revenues(Talluri and Van Ryzin, 2006). According to Talluri and Van Ryzin (2006), the significant objective of revenue management is the maximization of the revenue through sales of the right product at the right time and to the right individual. It is imperative in business decision making that involves decision on what, when, how and how much to sell to the customer. The decision-making process is mainly achieved through mining of data, management of customer relationship, usage of operations research and operation management techniques like demand down techniques, LP programming and probability. Revenue management is imperative in playing its role in perishable inventory items like hotel, spas, airlines, online bookings, and restaurants(Chiang, Chen and Xu, 2007). Revenue management in firms is driven by several factors which include marketing and avenues of product distribution, levers and drivers. In this paper, focus is to be given to key techniques such as overbooking, rate fencing, and strategic pricing to help meet the main goal of revenue management. Further, the paper will explain how of each of them meet the concept as allocating the right product to the right customer at the right price and at the right time to optimize revenue(Talluri and Van Ryzin, 2006).

Strategic Pricing

Pricing and price strategies are pivotal aspects of revenue management of a firm which is mainly dictated by market forces of demand and supply, the perception of customer value, competitive strategy and competitive factors(Burger and Fuchs, 2005). In order to establish a successful firm in growth and productivity, effective and efficient pricing tactics and strategies are significant(Anderson and Wilson,2003). The tactful strategies in the area of pricing entails sensitive pricing, discount pricing, markup pricing, market, cost plus, and competitive pricing. In order to properly optimize prices, there is a need to use strategies such as price ratios, inventory control, single or uniform pricing which prove to be effective tools for pricing and revenue management(Chiang, Chen and Xu, 2007). Conditions such as stiff competitions in the early 90s and deregulation of airlines like British Airways in the US necessitated the use of price strategies to manage revenue. The success of the fair pricing in the British Airways would then later make other industries adopt it. In the Hotel industry, for instance, The Marriot Group of Hotels used the discounted strategic pricing to help them gain a competitive edge over its competitors in the market(Bailey, 1998). There was also adoption of dynamic and innovative pricing strategies by The Ford Motor Company of the US. In its adoption, the company made use of differential target pricing system which was mainly based on the different segments of customers thus eliminating any likely emergence of underpricing or overpricing of firm products. The company successfully carried out this through the adoption of efficient, market-driven; value based strategy of setting the appropriate target price for the firm(Anderson and Wilson, 2003).

The concept of price elasticity and demand based pricing can also be applied in crafting the right prices. In instances of inventory-driven pricing strategy, the price is usually set on the basis of marginal or variable cost. In strategic pricing, it is imperative to ensure that prices cover all the costs such as total-fixed as well as variable costs. The minimum sustainable costs must be met, and the prices should not be lower than the costs that customer perceive as unfair or unreasonable. Therefore, prices are the main drivers for revenues and profitability thus they are interrelated. The application of demand management decisions through markdown and LP programming technique enables organizations to maximize revenue.
Rate Fencing

The main reasons for setting up of fences is to enable creative thinking and leveraging of knowledge on the customer behavior and the available number of customers that one can target from their competitors(Manson, 2009). A case in the study of the rate fencing is in the airline industry where in the 70s, airlines were regulated and had no mandate to offer discount rate unless they had sufficient evidence pointing to the generation of new revenues more than the dilution of the current revenues. The American Airlines is known to be the first company to launch the fenced fare called the Super Saver where they would offer a highly discounted rate such as 40 percent off, for round-trip air travel that stayed away from the city of origin over Saturday night. This fare was attractive to the personal traveller but a turnoff to the business traveller(Manson, 2009). There are several types of fences that are set up, and they include geographic fences where a business has to open up to foreign markets in order to expand itself. In this case you establish new markets and offer low rate that is not able to dilute the current revenue stream. Therefore, the new market would not allow for purchases of products from the country of origin or supply.

Time-of-purchase fences

In this case the organization comes up with advance purchase fence than the normal and then further lowers the fares for their products(Talluri and Van Ryzin, 2006). For instance, if an organization is aware that all the current customers book within two weeks of arrival, then they may institute advance purchase fence where fares are lowered only to customers that are willing to purchase 21 days in advance. This type of fence is a little less foolproof, and there is a need to watch for current customers’ behavior in terms of booking(Collins and Thomas, 2013)(Chiang, Chen and Xu, 2007).

Opaque Channel Fences

In this type, the customer is not privy to the identity of the hotel until after they make a purchase, and they also do not know the rate(Chiang, Chen and Xu, 2007). This fencing is advantageous given that all the current loyal customers will be willing to make it. Going forward, there are few customers who are likely to be loyal to your brands. When using this strategy, it is recommended to have a full program to ensure that the customers’ details are in the database, and they are enrolled for loyalty programs of the organization(Alreckand Settle, 2007). In some instances, the customers could be provided with incentives for joining the programs or redeeming their points within a specified period. It is, therefore, deemed that good fences will make good neighbors even in today’s hotel and airline marketplace.

 

Overbooking

Overbooking is a significant revenue management tool that enables effective operation and profitability in the airlines and hotel industry (Alderighi, NicoliniandPiga, 2012). In order to maximize their revenues, hotels increasingly have to implement revenue management practices. Given the positivity of the system, many companies in the service sector like the hotels usually overbook capacity in order to maximize revenue at one particular point in time. Improper implementation of overbooking easily result in loss of room revenue, loss of hotel reputation reduced customer loyalty and eventually decreased profitability in hotels(Alderighi, Nicolini and Piga, 2012). Overbooking can then be defined as confirming more reservations that the available physical capacity to provide the service. The goal of overbooking is to increase the expected profit and instead of selling each room once, profit can be increased by selling it several times. In the hospitality industry, the profitability of hotels largely depends on their ability to utilize the available capacity. Additionally, the room demands and extensions of stay for individuals are very unstable and hard to predict. Therefore, the hoteliers find themselves in a situation where they are challenged by how much to determine the occupation of rooms for customers who are financially unequal and at the same time maintain a stable rate of demand given that the surrounding circumstances are hard to predict. Thus, with the adoption of all these mechanisms, it is all possible to utilize overbooking which enables proper allocation of resources and sales optimization(Alderighi, Nicolini and Piga, 2012). In realizing the optimal revenue, it is quite challenging to deal with the unpredictable nature of the hotel customers by the hotel operation management given that not all booked rooms will turn into service consumption. Through proper implementation, overbooking enables other bookers to be compensated if they cannot receive the value package they agreed on and paid for(Talluri and Van Ryzin, 2006). Hotels usually adopt overbooking to protect against losses with no-shows and to offset the effect of cancellations that might arise as well as shortened stays.

References

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Deleted:Alderighi, M., Nicolini, M. and Piga, C., 2012. Combined effects of load factors and booking time on fares: Insights from the yield management of a low-cost airline (No. 171). University of Pavia, department of economics and quantitative methods. Retrieved from <http://econpapers.repec.org/paper/pavwpaper/171.htm> Alreck, P. L. and Settle, R. B., 2007. Consumer reactions to online behavioural tracking and targeting. Journal of Database Marketing & Customer Strategy Management, 15(1), 11-23. doi:10.1057/palgrave.dbm.3250069 Anderson, C. K. and Wilson, J. G., 2003. Wait or buy? The strategic consumer: Pricing and profit implications. Journal of the Operational Research Society, 54(3), 299-306. doi:10.1057/palgrave.jors.2601497 Bailey, J. P., 1998. Internet price discrimination: Self-regulation, public policy, and global electronic commerce. Proceedings of the Twenty-Sixth Annual Telecommunications Policy Research Conference, Washington, DC. Retrieved from <www.gunadarma.ac.id> on 20th August, 2014. Burger, B., and Fuchs, M., 2005. Dynamic pricing—A future airline business model. Journal of Revenue and Pricing Management, 4(1), 39-53. Chiang, W. C., Chen, J. C., and Xu, X., 2007. An overview of research on revenue management: current issues and future research. International Journal of Revenue Management, 1(1), 97-128. Collins, A., and Thomas, L., 2013. Learning competitive dynamic airline pricing under different customer models. Journal of Revenue & Pricing Management,12(5), 416-430. Fuchs, M., Höpken, W., Eybl, A., and Ulrich, J., 2008. Selling Accommodation Packages in Online Auctions—The Case of eBay. Information and Communication Technologies in Tourism 2008, 291-302. Manson, E., 2009. To discount or not to discount?. Caterer & Hotelkeeper,198(4559), 44. Talluri, K. T., and Van Ryzin, G. J., 2006. The theory and practice of revenue management (Vol. 68). springer.