Evaluation of revenue management application in Nigerian hotels.
This thesis has provided a structured literature review which gives a broader definitions of the major concepts in revenue management in terms of the applications and the long term relationship with customers. It then explores the extent to which revenue management is been applied in the Nigerian hospitality sector.
The aim of this thesis is to analyze revenue management application in some selected hotels in Nigeria, Nigeria is made up of 36 states including the Federal Capital Territory.
Three hotels will be selected from the 36 states adding up to a total of 108 hotels to which questionnaires will be sent, the result will give how RM is been applied in line with the manipulation techniques involved, above that, from the research, it will conduct a development plan for other hotels under utilising the full strength of RM tools.
The goal of this thesis is to improve the profitability of the room capacity with the tools of revenue management being explored, The theoretical data for this thesis will be collected from the selected hotels, hospitality management literatures, and Internet. In addition, other important information sources will be from the author’s personal experience and a result from the questionnaires rolled out to gain a reliable and comprehensive information of the RM adoption.
This chapter gives an introduction to RM, following literatures by Orkin, (1990), Jones and Val, (1993), Karaesmen and van Ryzin, (2004), Kimes, (2000, 1998), Rothstein (1971, 1975), Bitran and Caldentey, (2003), and Weatherford, (2003). We start with an elaborated explanation of revenue management, the history and its origin (Rothstein (1971, 1975), Bitran and Caldentey, (2003), and Weatherford, (2003)). Afterwards, a conceptual framework for understanding the objectives of revenue management, the business platform on which RM can be adopted (Kimes, 1989), the way the system works and finally, this thesis will conclude by giving an outline of the remaining chapters of the thesis.
We here trace the history of revenue management as practiced in the hospitality industry in an effort to illustrate what Jones and Lockwood, (1998), said about RM, they said that Revenue management is a well researched and explored manipulation technique for maximising revenue. Unfortunately, revenue management practice in Nigeria is little known, for example, it has been a commonplace to sell a room twice a day if the opportunity arise, increasing the revenue generated directly leading to RM application indirectly, this form the bisis of this dissertation and it is a gap this research is seeking to fill by exploring the extent to which RM is practised in Nigerian hotels directly and not been blind folded by an indirect approach of the application of Revenue Management.
RM can be define as a management tool or technique which is currently being utilized by an increasing number of international chain of hotels and independently owned hotels in order to maximize the effective use of their available room capacity and ensure a boost financially, (Salmon, 1990). Furthermore, Jones and Lockwood, (1998), researched and concluded that RM is not entirely a new capacity manipulation tactic in the world, and most hoteliers practice some form of RM, such as the adjusting of room rates to temper fluctuations between peak and off-peak seasons, mid-week, and weekend rates. This Research, therefore, examines the use and application of RM in the hotel industry in Nigeria and aims to demonstrate its application towards effectively maximizing room revenue and profit maximization.
For the sake of this thesis, a comprehensive literature review based on secondary sources in order to explore RM application will be established as a guide to the fieldwork and the areas of interest will be extracted from the literature review. Above others, these areas and issues will be investigated through the method of collecting primary data. Furthermore, all collected documentations will be made available in order to validate the information given during these interviews.
This thesis is a very satisfying and challenging process since it focuses on the gap which has never been researched in the hospitality industry in Nigeria. Nevertheless, it is a valuable learning experience which will be cherished by revenue managers in Nigeria in order to enhance the revenue generated in their respective hotel(s). This thesis seek to give a proper understanding of revenue management tools including; Overbooking, Inventory control, displacement analysis pricing and lastly forecasting method, their impacts on the corporate performance in terms of customer satisfaction and loyalty leading to customer retention will be of secondary concern.
This thesis seeks to explore the extent to which revenue management is being practised in Nigerian hotel in terms of the usage of RM tools which is afore mentioned. This will be achieved by exploring three hotels from each 36 states in Nigeria, some which will be from an international chain of hotels and others an independently owned hotels. Questionnaires will be rolled out to these selected hotels in other to have a generic perception towards the adoption of RM following the literature by Vinod (2004) in that the value of revenue management is assessed in the hotel industry.
1.2 RESEARCH OBJECTIVES AND QUESTIONS
Every seller is faced with fundamental decisions, juxtaposing this, a BBQ restaurant selling chicken and chips should be able to decide on which period to make her maximum sale, the price to give and when to reduce the price. A cinema ticket or stadium ticket must be sold within a certain period, therefore, the manager must decide when to start selling tickets, what the asking price should be, and when to drop price if necessary. In the Hotel industry, it is similar; hotel managers should know when to drop prices on rooms, when to stop selling rooms, when to increase the prices of rooms. Following these examples, the Nigerian hotels’ operations led us to the objectives of the thesis:
To explore the extent to which revenue management is applied.
To seek the awareness of RM within the Nigerian hotels.
How is revenue managed in Nigerian hotels
To what extent do Nigerian hotels consider Customer loyalty, customer satisfaction and customer retention a priority
For the sake of this thesis, only three hotels will be explored from each of the 36 states in Nigeria, because there are several unregistered hotels and there is no proper list of all the hotels in Nigeria. However, some of the hotels are part of international chain of hotels operating on an international level while some are independently owned. Furthermore, we have limited the research to RM application and from the survey, the sensitive areas as regards to customer loyalty, satisfaction and long term retention will be explored, in other words, the loyalty, retention and satisfaction will be our secondary aim. Nonetheless, there may of course be other operations or practices within these hotels that affect revenue but our research is focused on the five RM tools been employed as afore mentioned. The followings under listed are the possible limitation this thesis might face.
One of the major problems for the research is finance, the financial aspect in terms of travelling to Nigeria to schedule and execute an interview with the managers of the selected hotels and therefore, questionnaires will be sent via the wireless network (internet) using kwicksurvey; an internet based questionnaire software.
Authenticity of information
Secondly, Some of the managers to fill the questionnaires might accept the purpose of the study and fill, but some might be offended by it and feel it is a time wasting process and give a biased information.
Lastly, the risk for the study of not been able to find the information it needs at the allowed time. Finding the information may take more time than the limited time given (time constraints).
Chapter one will set a solid foundation for this thesis, therefore, the research will continue by presenting a comprehensive literature review as far as revenue management is concerned in Chapter Two. A concise description and critical understanding of RM background will be the aim of the literature review (Chapter two). Furthermore, an overview of the literature within the following RM tools including; overbooking, displacement analysis, price control, inventory control (length of stay restriction) and as they lead to customer management will be given in order to set the base and create an understating of how these tools influence revenue generated. Chapter Two concludes with a brief structured analysis of the literature review presented.
Chapter three will seek to explore and examine the aim of the research process and how the fieldwork will be conducted. Research limitations will be presented, the fieldwork and how information will be handled. This chapter describes what happens in all the stages on the fieldwork. (Before, during, and after the fieldwork).
In Chapter Four we present a generic practice within the studied hotels and give a short generic presentation of the hotels participating and describe how RM tools are used in terms of the followings; overbooking, displacement analysis, price control, inventory control (length of stay restriction). Concluding the chapter with a description of how the respondents recognize the external environment followed by their perception on revenue management and their practices of RM techniques.
In Chapter Five, the empirical findings will be evaluated and analysed in a way that it can be linked with the literature overview presented in Chapter Two. This will be done through a critical analysis. These analyses will illustrate the effectiveness of RM application in Nigerian hotels and how it is been adopted, therefore, Chapter Six will be based on the analysis of revenue management tactics.
Chapter Six gives the implication of our main findings and conclusions, as this will be based on the entire research carried out, Furthermore, suggestions of areas which is felt to be further developed after critical evaluation of RM application in Nigeria is made following Choi and Mattila (2004)’s investigation on the impact of revenue management as regards to customers’ perceptions on fairness.
LITERATURE REVIEW ON REVENUEMANAGEMENT
In this chapter, RM literature will be explored, following all the five application tools afore mentioned. In the literature, Burgess and Bryant, (2001) said, many authors are conversant with the use of interchanging the term revenue management (RM) with yield management (YM). Some consider YM only to be related with revenue derived from accommodation whereas RM may encompass all areas of hotel revenue Therefore, it is important to highlight the term YM and clarify its meaning for the purpose of this thesis. Many definitions are available on YM. Jones and Val, (1993) said, yield is calculated by taking revenue realized and dividing it by revenue potential. However, RM is often associated with the following definition by Kimes, (2000, p. 121) “The application of information systems and pricing strategies to allocate the right capacity to the right customer at the right place at the right time.” further assessment conducted by Mitchell (1992) states that revenue management is the process of controlling room availability by opening, closing and restricting different room rates based on forecast demand in order to maximise room revenue.
Jauncey et al. concluded through an analysis of literatures, came up with the term “best fit” definition for RM, which is “An integrated, continuous and systematic approach to maximizing room revenue through the manipulation of room rates in response to forecasted patterns of demand.” Jauncey et al., (1995, p. 25) and a description of RM, according to Jones and Val (1993), is to apply basic economic principles to pricing and to control the supply of rooms for the purpose of maximizing room revenue. Which means that in order to have an effective RM technique in place one would need to understand the basic economics of supply and demand so that the right price could be set in order to increase room revenue for the company, following what kimes (1998a) said about selling the right product to the right customer at the right time and the right place. Nevertheless, some conditions for the application of revenue management must predominate according to kimes (2000). These conditions include;
Capacity must be relatively fixed, RM tactics is primarily designed for a capacity constrained firms but firms not having this capacity constraints can make use of inventory as a buffer dealing with fluctuations in demand.
Service should be perishable, service ends when ends.
Service could be sold well in advance of cunsumption, to maximize room revenue, some sort of reservation system which allows inventory bookings to be received well in advance should be put in place.
The cost of a sale should be relatively low, this simply means the cost of putting a guest in another unoccupied room is relatively lower than building another room.
Demand should flunctuate substancially, peak and off peak seasons, festive periods are all examples of demand fluctuations.
Market could be segmented e.g Leisure travellers and business travellers.
When looking at the literature from a historical perspective, it was the airline industry that has been credited with the development and refinement of RM following the deregulation of the U.S. airline industry in the 1970s, Kimes, (1989a), and McMahon-Beattie et al., (1999). This deregulation resulted in a heavy competition within the airline industry and led to a price cutting war. Nevertheless, from the literatures of Rothstein (1971, 1975), Bitran and Caldentey, (2003), and Weatherford, (2003), managing inventory became an important part of running a successful business in the early 1970s. As a result of this competitive circumstances, McMahon-Beattie et al., (1999) said, the adoption of RM began in the hotel industry in the middle of the 1980s as the industry was faced with excess capacity, severe short-term liquidity problem and increasing business failure rates.
Purpose of Yield Management
Jones and Hamilton (1992) among others said, RM in the hotel industry tries to maximize the available guest room rates when room demand exceeds available room and to maximize occupancy when available room exceeds room demands, even at the expense of the average room rate. Nevertheless, some authors like Jauncey et al., (1995), McMahon-Beattie et al.,(1999), Siguaw et al., (2001) all agree that the purpose of RM is the maximization of room revenue through the manipulation of room rates in a structured fashion, so as to take into account forecasted patterns of demand. It is a technique that attempts to maximize profits by using information about buying behaviour and sales to create pricing and inventory controls, Lee-Ross and Johns, (1997).
Donaghy et. al., (1995), and Kimes, (1989b) just to mention a few, has examined RM applications and studied its definition, researchers like Donaghy and McMahon, (1995), Fitzsimmons and Fitzsimmons, (1998), Hiemstra, (1999), Kimes, (1989a, b, 1997), Yeoman and Watson, (1997), looked at the critical factors that are likely to influence the application and implementation of RM and finally, the ethical issues in terms of customer satisfaction, retention and loyalty over a long period of time can be seen in the following literatures, Cross, (1992, 1997), Jauncey et al., (1995), Kimes, (1994), and Lieberman, (1993).
Cross, (1997) added that within one year of the adoption of RM, Delta airline generated $300 million increment, $500 million annually was recorded annually by American airline, over $100 million is annually generated by Marriott jr Hotels and $2 million gained in the first two weeks, following the adoption of RM techniques at the Canadian Broadcasting Corporation.
First and foremost, RM tools are intertwined, one tool depends on the other to function effectively. Pricing strategies used to be a decision by the overall managers before, but in recent years, that schedule has been given to a revenue manager but the principle of differential pricing is said not to be attributed to the immergence of RM by Donaghy, et al (1995). Hotel managers have long been using various pricing strategies to maximize their profits by bringing the seasonal demand for rooms and capacity limitations into a balance (Choi and Cho, 2000), even before the deregulation in the airline industry that gave birth to RM in the 1970’s. Differential pricing strategies including; price discrimination, off peak pricing and demand based pricing may change the reference price and reference transaction which could cause customers to feel the current transaction is unfair and the customer could even perceive such differential pricing as price gorging. (Whirtz et al (2003; pg 220)), A stochastic or probabilistic demand seemed justified on the basis that consumers ‘arrive’ at random times before consumption. From the pricing perspective, though, a theoretical structure was needed to explain how demand is shaped or why it would follow a particular pattern across time. Otherwise, there was no assurance that the past is able to predict the future [Bernstein, 1996; Ng, 2004]. Accordingly, despite tremendous computing power available today, pricing based on demand forecasts faces the same old problem in conventional probability theory, where, according to Bernstein [1996: 334], ‘the raw material of the model is the data of the past’. Some research studies have attempted to shed some light on the behaviour of the advance buyer. The literature is scant, dominated by marketing, and not commonly brought into revenue management research. For example, Desiraju and Shugan  evaluated strategic pricing in advance selling and found that yield management strategies such as discounting, overbooking and limiting early sales work best when price-insensitive customers buy later than price-sensitive customers. Shugan and Xie  showed that due to the state dependency of service utility, buyers are uncertain in advance and become certain at consumption time while sellers remain uncertain of buyer states at consumption time because of information asymmetry. They suggest that advance selling overcomes the informational disadvantage of sellers and it is therefore a strategy to increase profit. Xie and Shugan  studied when advance selling improves profits and how advance prices should be set. They have also investigated the optimality of advance selling, investigating selling in a variety of situations, buyer risk aversion, second period arrivals, limited capacity, yield management and other advance selling issues. Png , on the other hand, showed that costless reservations in advance is a profitable pricing strategy as it induces truth revelation on the type of valuation that the consumer has for the service (which is private information). If the consumer has a high valuation i.e. ability to consume, s/he will use the reservation and pay a higher price. If not, the consumer will not use it. In another paper, Png  compared the strategies of charging consumers a lower price for advance sales and attaching a price premium at the date of consumption versus charging them a premium and promising a refund should consumption prices be lower than what was purchased. Despite these models that aim to capture primitive advance demand behaviour, there has not been much effort to integrate them into a unified framework, nor have there been any attempts to bridge the behavioural aspects of demand with revenue management research. Models of the former capture individual consumer behaviour (or homogeneous consumer segments) and it was difficult to see how that could be aggregated and applied to revenue management that mostly dealt
Overbooking, cancellations and no-shows
Overbooking, is simply defined as a concept of accepting more reservations than the physical available capacity with the knowledge that some bookings will end up as a no-show, or cancellations furthermore, this serve as a hedge against early check outs, this is said in the literature that overbooking is one of the oldest form of RM tactics Karaesmen and van Ryzin, (2004). Overbooking is actually not a bad concept, but if not managed well, it could lead to overselling. Overselling happens when the number of arrivals exceeds the available room capacity. Authors have examined how hotels could secure themselves in other to avoid no-shows or cancellations by guests, through appropriate reservation policies,
(Alstrup et al., (1986), Belobaba, (1989), Hersh and Ladany, (1978), Lieberman and Yechiali, (1978), Rothstein, (1971, 1974, 1985), Thompson, (1961), and Toh, (1985)) ———airlines.
Under this strategy, the seller deliberately oversells capacity if high-paying consumers show up, even when capacity is already fully booked. The seller then cancels the sale to some low-paying customers while providing them with appropriate compensation. We derive a new rule to optimally allocate capacity to consumers when overselling is used, and show that overselling helps limit the potential yield and spoilage losses. Yield loss is reduced because the seller can capture more high-paying customers by compensating low-paying customers who give up their right to the product.
Displacement analysis has been a very challenging exercise for function room analysis. It is challenging to determine what to negotiate when considering booking a group with a significant lead time, because when compression does hit it is possible that more money could have been made by waiting and taking the last-minute groups that are willing to pay higher prices. But that requires hotels taking significant risks and gambles
The concept of displacement is defined by Abbort and Lewry, (1991) is said to be “those prospective customers who are unable to obtain a higher rate because the rooms have already been booked by customers paying lower rate.” Furthermore, Biyalogorsky, (1999) added that displacement concept is “selling at a low price, and losing a better price later”.
Displacement analysis is divided in to two parts, including; Primary displacement and Secondary displacement. Primary displacement is also known as the direct displacement, and these are those prospective guest who are willing to increase the room rate themselves just to get booked for a particular date of arrival but could not be booked due to the fact that the available rooms are already been booked by guests with lower rates. Secondly, the secondary displacement which is also known as indirect displacement and are said to be those subsequent rooms lost due to primary displacement. Example of this displacement analysis can be seen in appendix 1.
1 The Mechanics of Inventory Control
Distribution and Central Reservation Systems
Traditional revenue management is intimately related with distribution and central reservation systems. Distribution and central reservation systems represent a broad and fascinating topic in their own right. An excellent high-level account of airline planning, marketing, and distribution activities and their relation to operations research can be found in Smith et al. (2001). Here we provide only sufficient background information to facilitate discussion of the main topic of this paper, revenue management.
Forecasting is an important strategy of RM in any organisation adopting its techniques; but it is particularly critical in hotel revenue management because of the direct influence forecasts have on the available room booking limits that determine hotel profits. Not surprisingly, forecasting is concurrent with the literature on overbooking because overbooking calculations depend on predictions of ultimate demand, cancellations, and no-shows.
Jauncey et al., (1995), Pak and Piersma, (2002), Kime, (1999), 2003), all agreed that forecasting is one of the key principles of revenue management. Jauncey et al., (1995), Donaghy et al., (1995, 1997), juxtaposed the effectiveness of a good RM system by adding that it should be able to predict demand conditions and fluctuations by analyzing reservation patterns, arrival, departures and a score of other demand characteristics. Recently, the following literatures by Anderson and Blair, (2004), Desiraju and Shugan, (1999) suggested that revenue management systems with forecasting algorithms are expensive to implement in real terms. Lahoti, (2002) added by saying that, a typical RM system costs between $1 million to $3 million and takes more than two years to implement. Moreover, research has proven and showed that these complex and sophisticated revenue management systems are not liable to mislead, deceive, or disappoint. In fact, Ng et al., (1999) added that, using the data of the past and sales department using present day information, conflicts often occur, and many revenue management tactics should employ some level of human intervention, in other words, making use of RM as a guide but human intervention is still relevant.
Forecasting has four limitations, following the literatures by c.f. Chase, 1999; Lieberman, 1993; Relihan, 1989; Boyd, 2004; Desiraju and Shugan, 1999. Firstly, A proposition upon which forecasting is based or from which a forecasting conclusion is drawn, should be based on fundamental concepts of consumer behaviour, (Chase, 1999; Lieberman, 1993, Relihan, 1989). It will be of great importance to bring to revenue managers attention according to Carry, (2004) revenue manipulation and maximisation using forecast method. Consequently, this may not be a good indicator of the subsequent or present bookings, and cannot be determined by using only RM system by studying historical pattern of demand, because the reason why consumers act or react the way they do is just as important as how they are behaving. Secondly, forecasting tactic at its best when adopted is still a combination segments that could, if possible, be desegregated for higher revenue. Thirdly, demand records are subject to many factors, including the pricing strategies of the existing competitors at that time. We can only assume and predict based on the historical data. Finally, demand can be influenced, not merely be known. As early as 1951, Schumpeter, (1951), Liebhafsky, (1968) said that wants cannot be taken as independent and consumers could be taught by producers to want new things.
predictableQuadrant 1MoviesStadiums and arenasConvention centres
Quadrant 2HotelsAirlinesRental cars
unpredictableQuadrant 3RestaurantsGolf CoursesInternet service
(Kimes. 2000. p.127)
The industries found in quadrant 2, such as airlines and hotels, are generally those associated with RM, Weatherford et al., (2001). That is because these industries tend to use variable pricing for services with a specified or predictable duration. Nevertheless, Donaghy and McMahon (1995) state that a successful application of RM techniques results in fluctuating room prices. RM therefore, consists of not two, but three separate, interrelated parts; inventory management, duration control, and pricing.
Abbott, P. and Lewry, S. (1991) Front Office Procedures, Social Skills and Management. Oxford: Butterworth-Heinemann.
Bitran, G. and Caldentey, R. (2003). “An Overview of Pricing Models for Revenue Management”. Manufacturing and Service Operations Management, Vol. 5, No. 3, pp. 203-229
Chang, Y.N and Chanpo-Flores, F.C (1980). Business policy and strategy: text and cases. Goodyear pub. Co: Santa Monica, Calif
Chase Jr., C.W. (1999) “Revenue management: A review’, Journal of Business Forecasting Methods and Systems, Vol. 18, pp.2 & 28.
Choi, T.Y., Cho, V., 2000. Toward a knowledge discovery framework for yield management in the Hong Kong hotel industry. International Journal of Hospitality Management 19 (1), 17–31.
Choi, S., Mattila, A.S., 2004. Hotel revenue management and its impact on customers’ perception of fairness. Journal of Revenue and Pricing Management 2 (4), 303–314.
Cross, R.G., (1992). The ethics of yield management. In: Davis, D.T., Harless, M. (Eds.), Ethics in
Hospitality Management. Educational Institute Of American Hotel & Motel Association, Michigan,
Cross, R. G (1997). Revenue Management: Hard-Core Tactics for profit making and Market domination. Broadway books: New York, NY
Donaghy Kevin , Una McMahon and McDowell David (1995). “Yield Management: An overview”: Intenational Journal of Hospitality Management. 14. 139-150
Donaghy, K., McMahon, U. and McDowell, D. (1997) Implementing Yield Management : Lesson from the Hotel Sector, International Journal of Contemporary Hospitality Management., 9 (2), pp. 50-54.
Donaghy, K and McMahon, U, (1995).”Managing Yield: A Marketing Perspective”, Journal of Vacation Marketing, Vol. 2, No. 1, pp 55 – 62
Fitzsimmons, J.A., Fitzsimmons, M.J., 1998. Service Management. McGraw-Hill, Singapore.
Griffin,R.K (1995). ‘A categorization scheme for critical success factor for lodging yield management systems’. International Journal of Hospitality management. 4, 325-338
Hiemstra, S.J., 1999. Economic pricing strategies for hotels. In: Thomas, B., Ram, M. (Eds.), Economic and Management Methods for Tourism and Hospitality Research. Wiley, West Sussex, pp. 215–231.
Jarvis, N, Lindh, A and Jones, P(1998). ‘An investigation of the key criteria affecting the adoption of yield management in UK hotels’. Progress in Tourism and Hospitality Research 4, 207-216
Jauncey, S., I. Mitchell, and Slamet, P. (1995) The Meaning and Management of Yield in Hotels, International Journal of Contemporary Hospitality Management, 7 (4), pp. 23-26.
Jones, P and Lockwood, A (1989). The management of hotel operations. Casell Education Ltd: London.
Jones, P. and Hamilton, D, (1992).” Yield Management: Putting People in Big Picture”, Cornell Hotel and Restaurant Administration Quarterly, February, pp 89-96.
Karaesmen, I., and van Ryzin, G. (2004) Overbooking with Substitutable Inventory Classes, Operations Research, Columbia University, New York, NY, 52 (1), pp. 83-104.
Kimes,S.E, (1989), ‘Yield Management a tool for capacity constrained service firms’. Journals of Operations Management8.(4), 348-63.
Kimes S.E. (1997), Yield Management: An Overview, in I. Yeoman. and A. Ingold (eds.), Yield Management: ‘Strategies for the Service Industries’. Cassell:London
Kimes S.E, 1997. ‘Yield Management: An overview’ in Yeoman, I and Ingold, A (eds), Yield management: Strategies for service industries. Cassel Education Ltd: London. 3-11.
Kimes, S, (1989a). “The Basic of Yield Management”, Cornell Hotel and Restaurant Administration Quarterly, November, pp 14 – 19.
Kimes, S.E., 1989b. The basics of yield management. The Cornell H.R.A. Quarterly 30 (3), 14–19.
Kimes, S.E., 1989c. Yield management: a tool for capacity-constrained service firms. Journal of
Operations Management, 8 (4), 348–363; In: Lovelock, C. (Ed.), 1992. Managing Services. Prentice
Hall, New Jersey, pp. 188–201.
Kimes, S, (1994). “ Perceived Fairness of Yield Management”, Cornell Hotel and Restaurant Administration Quarterly, February, pp 22 – 29.
Kimes, S, (2000). “Revenue Management on the Links: Applying Yield Management to the Golf-Course Industry”, Cornell Hotel and Restaurant Administration Quarterly, Vol. 41, No. 1, pp 120 – 127.
Kimes, S. (2002). “A Retrospective Commentary on Discounting in the Hotel Industry: A New Approach”. Cornell Hotel and Restaurant Administration Quarterly, August, pp. 92-93.
Lee-Ross, D. and Johns, N, (1997). ”Yield Management in Hospitality SMEs”, International Journal of Contemporary Hospitality Management, pp. 66-69.
Lieberman, W.H, (1993). Debunking the myth of yield management. The Cornell HRA quarterly 34(1). 34-41
Lieberman, V., and Yechiali, U. (1978) On the Hotel Overbooking Problem: An Inventory Problem with Stochastic Cancellations, Management Science, 24, pp. 1117-1126.
Liberman V. and Yechiali U., (1977). “Hotel Overbooking Problem—Inventory System with Stochastic Cancellations,” Adv. Appl. Probab. 9, 220 –230
Lieberman, W.H. (1993) ‘Debunking the myths of yield management’, Cornell Hotel and Restaurant Administration Quarterly, Vol. 34, pp.34-41.
Liebhafsky, H. H. (1968) The Nature of Price Theory (Revised Edition). The Dorsey Press, Inc., Homewood.
Lockwood, A. and Jones, P. (1990). “Applying value engineering to rooms management”. International Journal of Contemporary Hospitality Management,Vol.2, pp. 27-32.
McMahon-Beattie, U., Donaghy, K and Yeoman, I. (1999). “Yield Management in Hotels”. In Constantinos, S. and Wood, R.C. (Eds.). Accommodation Management Perspectives from the International Hotel Industry. UK: International Thomson Business Press.
Orkin, E.B, (1990). “Strategies for managing transient rate”. The Cornell HRA quarterly. 30, 34-39.
Relihan III, W.J, (1989). “The yield management approach to hotel room pricing”. The Cornell HRA quarterly. 30 (1). 40-45
Rothstein, M. (1971). “An Airline Overbooking Model”, Transportation Science, Vol. 5. Issue 2, pp. 180- 192.
Rothstein, M. (1975). “Airline Overbooking: Fresh Approaches Are Needed”, Transportation Science, Vol. 9. Issue 2, pp. 169-173.
Rothestein, M. (1974). “Hotel Overbooking as a Markovian Sequential Decision Process,” Decision Sci. 5, 389 – 404
Salomon .A.(1990). yield management. Leaders shed light on the “dark science” Hotel and motel management part 205, 85 and 88
Schumpeter, J. A. (1951) Economic Theory and Entrepreneurial History. In R. V. Clemence (eds), Essays on Economic Topics of Joseph Schumpeter, Port Washington, NY: Kennikat Press.
Siguaw, J., Kimes, S, and Gassenheimer, J. (2001). “B2B Sales Force Productivity: Applications of Revenue Management Strategies to Sales Management”. Industrial Marketing Management, No. 32. pp. 539- 551.
Subramanian, J., Lautenbacher, C. J. and Stidham, S. J. (1999). “Yield Management with Overbooking, Cancellations and No Shows,” Transp. Sci. 33, 147–167
Vinod, B. (2004). “Unlocking the Value of Revenue Management in the Hotel Industry”. Journal of Revenue and Pricing Management, Vol. 3, No. 2, pp. 178-190.
Wang, X.L., Mitchell, I. (2001), ‘Yield management: not only yield from capacity, but also your customers’, 10th Council for Hospitality Management Education conference proceeding, Southbank University: London
Weatherford, L. (2003). “Disappeared Fares Within a Fare Class: How Can the Reality be Harnessed?” Journal of Pricing and Revenue Management, Vol. 3. No. 1, pp. 26-40.
Weatherford, L. R., and Bodily, S. E. (1992) A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management, Overbooking, and Pricing, Operations Research, 40, pp. 831–844.
Wirtz, J., Kimes, S., Ho, J. and Patterson, P. (2003), “Revenue management: resolving potential customer conflicts”, Journal of Revenue and Pricing Management, Vol. 2 No. 3, pp. 216-26.Yeoman, I., Watson, S., 1997. Yield management: a human activity system. International Journal of Contemporary Hospitality Management 9 (2), 80–83.