This research targets at gauging the use of yield management in Saudi hotels. Consequently, the focus of this chapter is to argue the results retrieved from research scrutiny in Saudi hotels. The argument will criticize earlier finding of other researchers to establish a firm foundation and reasoning in the current hotel services. In a bid to perform this task, the chapter has been divided into: Section 5.1, location, Section 5.2, occupancy and room rate, Section 5.3, pricing strategy, Section 5.4, price adjustment, Section 5.5, HR, Section 5.6, customer management, Section 5.7 third party websites and Section 5.8, summary of this chapter.
Section 5.1, Location
We cannot afford to discriminate the postulation of Kotler (1999) that location has direct effects on hotel’s premiums. Hotels located within the city center have an advantage of enjoying high prices for their services. This, further, supports the arguments of several researchers that ability to charge highly is dependent on accessibility and central location (Egan and Nield, 2000; Weaver, 1993; Taylor, 1995; Bateman and Ashworth, 1981). Apparently, they have a credible access to customers from various sources. These sources include the government institutions, private sectors, corporations and businesspersons. Since these people usually have their activities running in these places, we expect that they are more fit when staying in the city center. For this reason, there is high occupancy within the center and a contrary low intake away from the center. This finding is consistent with earlier research finding by Shoval (2006) dictating that hotels located centrally receive a higher proportion of clients than those at the periphery. It is a rare incident to have customer preferring to receive accommodation far from the city or their working area unless they cannot afford to live in these hotels. Contrary, the hotels located far from such institutions charge low to attract customers and establish other strategies to cover for these influences. This is a clear and concise indication that there is a direct effect of location in room rates. We can attribute this to those hotel located far from the holy mosque. For instance, hotel charges could reduce by 40% when located 5km away. This affirms that Ching Fu and Rothschild (2010) were right when they stipulated that there exist an inverse relationship between room rates and proximity to the central business district. Room rates for these hotels demand for movements that establish need for other transport costs. Additionally, these hotels do not allow for freedom to visit the room frequently. Agglomeration effect enhances the prior supply and shortens the distance that the customers have to move during daily operations (Yang et. al, 2012).
Hotels have defined strategies of regulating room rates according to demand. This study shows high room rating where demand is high, while there is low room rating in instances of low demand. The demand of rooms is high within the city center and the holy mosque. For this reason, the management has increased the room rating to maximize revenue. At these locations, hotels do not have to put effort on increasing the occupancy because they have ready customers. Increment of room rates when demand is high allows a hotel to maximize its revenue. When demand is low, these hotels lower room rates and concentrate on maximizing occupancy which becomes the only strategy of increasing revenue at that time. In contrast, hotels that are located far from the city center pay more attention about the occupancy than the revenue. They charge low to maximize the room revenues by the number of individuals to book rooms. Additionally, they provide quality services that those hotels located at places of high demand do not offer. This attracts customers to fill the hotels’ rooms and attain the achievable revenue. For these hotels, it does not matter whether demand is high or low because occupancy remains an issue to handle. We can, therefore, conclude that hotels exploited their income depending on demand provided by their location
We can support the argument of Juaneda and Raya (2011) that hotel prices have an inverse relationship with distance from center of high demand. This has challenged hotels far from the city center. When challenges arise, solutions are gathered to prevent loses. Consequently, hotels have defined some distinguished strategies to accommodate the challenge of occupancy. First, they have used the most fundamental aspect of reducing their prices to draw customers into their hotels. The depicted prices reduction allows a space for competition with the hotels located at the points of high demand. Some customers, therefore, decide to book rooms from the hotels that are cheaper and located far from the city center or such place. Customers can choose to lodge in hotels with quality furniture and other additional services than in a place that an individual is not acknowledged and appreciated. Other hotels provide free or cheap transport that controls the factor of distance and addition cost due to travelling. This reduces the effects of distance such as that experienced by businesspersons when travelling each day to the point of activities. Also, the research warrants that these hotels give offers to attract and appreciate customer. It is crucial to note that hospitality harbors a potential effect to customer retention and satisfaction. When customers are handled with integrity, they become potential future customers. In fact, we must note that these hotels request for customers from other hotels. This collaboration could be a tool essential to cater for occupancy. Segmentation was another tool that provided a solution to occupancy. These hotels offered different rooms that had distinct prices. Customer who cannot afford certain prices can choose the affordable room types and prices. These factors create an allowance to attract customer and improve occupancy which in turn increase room revenue. It could, therefore, be stipulated that hotels far from the point of high demand try to initiate strategies that assist in maximizing revenue.
Section 5.2, Occupancy and Room Rate
According to the investigations conducted by Harewood (2006), no concise correlation exists between average daily room rate and occupancy. Although, it cannot be stated flatly that occupancy percentage is not an essential factor when setting room rates, this research approves that occupancy and room rates have greater effects from other factor such as location. Occupancy and room rates might possess some relationships that are controlled by demand within a hotel. For instance, when occupancy is high, managers choose to increase on room rates. On the other side, managers reduce room rates when occupancy is low. However, this strategy does not apply to hotels located away from the market centers such as airport and city centers. Therefore, we can applaud that hotels do not shift room prices majorly due to occupancy. O’Neill & Mattila (2006) identified room rate and occupancy to be vital elements of signaling the revenue awaited by a hotel. For instance, high occupancy would signify high income from other facilities within the hotel.
It is identifiable that there exists a strong correlation between the rack rate and ADR (Harewood, 2006). It was recorded under research results that almost all rack rates were higher than the ADR by a figure between 40 SAR and 600 SAR. What leads to these differences? Some customers have the willingness to pay for any amount as far as they get a room. This could, also, be attributed to better services being offered in those rooms sold at rack rates than the rest. Probably, there are quality furniture, space, and attendance among others. Customers in need of such services, therefore, choose to pay for rack rates. This allows revenue manager to maximize revenue by capturing as many customers as possible. For instance, the managers decide to regulate the price in a way that can accommodate customer who can only afford lower rates. On the other hand, they differentiate and discriminate among prices to exempt room competition. It would be expected that when room rates are similar, the customers will pay attention on a single type of rooms. Those who are not willing to waste time or who are in dire need of quality services avoid the competition. We can, therefore, applaud that differentiating ADR and rack rates is a vital factor of discrimination which facilitates the establishment of two distinct booking systems.
How do we perceive the issue relating to past and present finding? Do we really think that hotels that existed 20 years ago are similar to the ones running currently? The rise of information technology (IT) has established systems that facilitate faster and efficient communication than in the past. What establishment have IT achieved in hotel management? The stipulation of Ellerbrock, Hitet, & Wellst (1984) applauded the use of magazines in causing prior effects on occupancy rates. However, technology has made magazines inferior. Information can travel thousands of miles within a second. In contrast, magazines had to be printed and transported for days or months before reaching the target. Tourists have the access to transact with hotels throughout the globe. In fact, Gazzoli, Kim & Palakurthi (2008) marked the use of internet to be the strategy of advertisement that reaches a wider group of people. Ideally, since Hayes & Ninemeier (2006) recognized that there must be strategies to increase occupancy rates, IT has defined strategies that tie the globe together through media, internet, and websites among others. For these reasons, current hotels in Saudi Arabia have different and efficient strategies of advertisement.
The use of closed to arrivals (CTA) and minimum length of stay (MLOS) is a vital factor in all hotels especially when demand is high. According to Talluri and Ryzin (2005), these strategies play a fundamental role in revenue maximization. This research identified that there exists a critical situation where arrivals must book earlier. In case the customers are not able to book earlier, they pay higher prices than to those who book earlier. These finding were consistent with the findings of Hayes & Ninemeier (2006) that revealed the need of earlier booking. They had evaluated a case in Veema Hotel that depicted the need to book rooms one day before arrival. In compliance to their findings, this research revealed that hotel management tries to encourage customer to book rooms before arriving. Gurbuz (2011) had noted that length of stay was a crucial factor in revenues maximization. Additionally, Noone and Colleagues supported the same stipulation by stating that a combination of CTA and MLOS maximizes revenues attainable for a single transaction. This research depicts replica ideas on the issue. Many hotels were determined to use CTA and MLOS to increase their revenue and restrict some customer when the demand is high. However, this research does not disapprove the findings of Shoemaker (2003) who stated that customer attain a negative attitude towards hotels using CTA and MLOS. Some hotels could identify the negative attitude that arises from CTA and MLOS. In fact, these are the strategies that Schuessler (2010) acknowledged to cause loss of customers.
Determination and maximization of daily revenue rely partially on revenue and occupancy. Gurbuz (2011) found it hard to identify whether it is occupancy or revenue that plays a fundamental role in profit increment. Similarly, the results of this research identified that managers did not manage to choose one. Instead, hotels valued both occupancy and revenue in accordance to the seasons of demand. However, the results depict that hotels located far from the central business district had a prevalent attention on occupancy. As we mentioned previously, these hotels relies on occupancy to increase revenue earned from other facilitations such as foods and drinks (Jones and Lockwood, 1989; Brotherton & Mooney, 1992). The researchers, further, pointed that some managers prefer low occupancy and high room rates that reduce the service cost. This could explain why some hotels decided to charge highly even when the occupancy was low. However, this was not founded significantly in this research. Most hotels emphasized on regulating the prices according to demand and the price makers. For instance, hotels that were located far from the city center had the fervency of regulating prices in a direct proportion with the hotels in the city center.
Wirtz et al. (2001) stipulated that overbooking is a critical tool to handle cancellation and avoid penalty. In this research, the managers used overbooking to cover cancellations. If cancellations are not covered, the hotels are due to make losses and/or dissatisfy the customer due to penalty. Therefore, the allegation made by Humair (2001) that overbooking warrants maximum utilization of the high seasons is true and based. This is because all rooms would be filled and lead to high hotel revenues. However, hotels cannot afford to exempt the employment of penalty to cancellation. Most hotels assigned penalties to all cancellations that were not enacted at a close instance such as 24 hours. Ross (1995) managed to point out that overbooking cautions hotels about unforeseen cancellations. However, some hotels do not apply this strategy because it has negative impacts on the customers. Harewood (2006) stated that overbooking may inconvenience customer due to ineffective booking that does not deliver the services it promises. The allegation is true and based because this research identified that managers have fear on the outcomes of overbooking. For instance, what if we took an incident where a customer books a room and does not get a room after arrival due to space. What do we expect this customer to do? First the customer will no longer trust the hotel in keeping promises. Secondly, it is likely that the customer will no longer have the desires to book a room with the hotel. Lastly, this customer will have to cancel or alter his/her schedule to get time for booking. In other cases, s/he will have to pay extra payment if s/he gets a room without booking. This will, therefore, humiliate the customer and create a stigma that the customer might develop and populate to friends.
Badinelli (2000) postulated that overbooking assists the hotels to incur minimal losses as a result of cancellation. Most hotel managers argued that there are losses associated to cancellation that a hotel must establish strategies to cover. Surely, cancellations leave empty rooms if the strategy of overbooking is not applied. During the high seasons, hotels receive accommodations that are higher than what they can satisfy. Their expectation is to utilize the season maximally. Consequently, these hotels can estimate the number of probable cancellations from the previous year to reduce risks associated with overbooking. Let’s evaluate what would happen if a hotel that relies ultimately on Ramadan does not receive the highest possible profits. The next season will occur after one year. Occupancy of the periods following Ramadan will reduce quantitatively. Probably, the hotel will make losses that will not allow maintenance the hotel. Therefore, it is vital to consider all factors that surround a hotel before deciding whether to use overbooking or not. However, when overbooking results into inadequate space, the hotels undergoes cost to cater for; cost of looking for alternative hotel for the customer, the cost of booking a room in another hotel, the cost of attending courses relating to handling issues of the overbooking ( Enhagen and Healy, 1996).
Jauncey et al. (1995) noticed that there were variations of cancellation across market segments and seasons. The result of this research show clearly that cancellation is prevalent when the room occupancy is 100%. At this instance, there are no rooms to accommodate more people. Additionally, the cancellation implies that one room will become empty in this case. In other cases, cancellation implies that one room has been vacated from the many that were available. The hotel could, therefore, assume that the customer had not booked the room, or the room had been empty just like the rest. After all, they did not deny any customer a chance to stay due to lack of space. However, advance notice is vital during cancellation. It would assist a hotel to predict the rate of cancellation. For this reason, hotels apply fines for cancellation enacted after 24 hours of booking. Selmi and Dornier (2011) suggested that the use of mathematical model to estimate cancellations would be a practical strategy to enhance profit maximization. Hotels evaluated in this research used software to determine the number of possible cancellation in a season. Ideally, many hotels could be using integrated mathematics to determine the cancellations due in a season. Managers alleged to have estimated the cancellation. How did they estimate? They must have used some mathematical calculations to determine the place most probable number of cancellations. Finally, we can argue that cancellation and overbooking have relations in solving problems. However, proper establishment of yield management have to be employed to allow successful ending.