The advent of computer technologies has had a huge impact on the hotel industry, mainly due to the emergence of online customers. As described by Demirciftci (2007), online consumers are more concerned about wasting time rather than saving money (Koch and Cebula 2002). Murphy, Schegg and Qiu, (2006) elaborated that in June 2005 Google indexed eight billion pages that complicated the online searching process. However, Metasearch engines or shop bots can help overcome this obstacle facing online consumers. Kung, Monroe and Cox (2002) outline that shop bots make available product prices and information from leading suppliers to online consumers. This lowers the searching costs for consumers (Brynjolfsson and Smith, 2000). In addition, they help elevate misleading information between both parties (Kung et al., 2002). Kayak.com is an example of a search engine that enables searching through numerous sites simultaneously thus saving time (Murphy et al., 2006).
In essence, saving is a significant aspect that influences online buying especially among travelers. PhoCusWright Inc. (2006) studies have proved that competitive prices are the main booster for online customers. Moreover, O’Connor, (2002) argued that 64 percent of non-online consumers claimed that the money factor would influence them to indulge in online buying. A survey by Brewer, Feinstein and Bai (2006) indicated that a majority of business and leisure-oriented travelers valued online buying as it facilitated better evaluation of travel and accommodation rates amongst others. Furthermore, Brewer et al., (2006) acknowledged that travelers yearned for the decrease in prices for direct electronic distribution channels, as opposed to indirect distribution channels. The move would attract many online customers to embrace direct distribution channels. Apart from ensuring lower prices on direct channels of distribution, hoteliers should also embrace consistency in order to win customers’ confidence. In addition, hotels should impose higher rates on indirect channels to push away customers. By 2001, a report by Forester Research showed that two-thirds of online travelers enjoyed the offer posed on online products on that very year (O’ Connor, 2002).
Demirciftci (2007) further evaluated the consequences of the merchant model using Smith Travel survey regarding the financial outcomes of hotels in the US. From the study, it was found that online buying cost US hotels $676 million dollars in loss in 2003 (Smith Travel Research, 2009). The following year, the loss reached $30 billion mark. This was attributed to overwhelming credit card frauds affecting online commerce. This subjected hoteliers to a bigger problem, which was further worsened by customers’ decline (Watkins, 2004). In addition, Watkins (2004) demonstrated that online suppliers increased prices for their products by a margin between 20 and 30 percent.
In terms of demand, O’ Connor and Murphy (2004) suggested that a countermeasure had to be applied to counteract the changes in demand. Relative to the rising demand, third-party intermediaries should be eliminated to give room for first parties. On the other hand, when the demand goes down intermediate channels should be employed in order to maximize the sales, regardless of the cost. In simple terms, fewer parties should be involved when demand is rising whereas when demand is lower, more intermediate channels should be employed (O’ Connor and Murphy, 2004).
As proposed by Demirciftci (2007) concerning rate disparities, distribution of prices is more concentrated in online markets as opposed to their counterparts. This is attributed to two factors. The first factor is the variation in product prices due to the net benefits associated with data mining. Secondly, reduced expenses in updating the product prices are also an important factor. For example, the varying cost of online books, and fluctuation of airline tickets by a certain percentage (Demirciftci, 2007). This has resulted in fairness in pricing becoming problematic. As discussed by Yelkur and Delcosta (2001), pricing between different online suppliers can trigger uncertainties regarding prices fairness amongst the consumers. Therefore, more information emphasizing the pricing strategies should be availed to prevent such an occurrence (Yelkur and Delcosta, 2001).
According to Toh, Dekay and Raven (2011), rate parity is a significant aspect to consider especially in all online suppliers, as the travel agencies, since consumers hugely rely on the prices comparison from several suppliers. Although the consumers make a comparison from several channels, their search is limited by the searching cost which is the time factor (Toh et al., 2011). For instance, if a consumer identifies a similar product with a differing rate in one of the suppliers, dissension arises forcing the consumer to make a comparison with other suppliers. As stipulated by O’Connor (2003), this is attributed to lack of patience that is triggered by misleading information particularly if differentiation of the products is not enough. On the contrary, consumers are patient with changes attributed to the demand instead of similarity based on different suppliers/channels. From a hotel perspective, rate parity is emphasized in all the suppliers. According to the investigations made by O’Connor (2003), rate parity varies more or less equally amongst many channels.
Due to Gazzoli, Kim and Palakurthi (2003), evaluation of rate disparities in a different hotel channel had shown that rate disparities influenced consumer’s perception triggering the use of several search engines and shop bots to find fair prices. Earlier research recommended that hotel online suppliers stick to a consistent price strategy (Gazzoli et al., 2003). Rate parity involves the formulation of similar price structure by all the suppliers. The revenue management sector is held responsible for enhancing rate parity that signifies prevalence of integrity. This is instrumental in ensuring that consumers become loyal to a particular online supplier brand. Moreover, maintaining consistency in pricing across all suppliers in order to win customers’ loyalty. Apart from ensuring fair rates, rate parity is also crucial as a controlling factor. It facilitates rate control as well as brand erosion for all distribution channels. Pricing inconsistency is a theoretical aspect resulting from perceived fairness (Kimes, 2002). Kahneman, Knetsch and Thaler (1986) used transaction and price reference concepts to evaluate fairness practices in online pricing. The reference transaction concept relates to the customer’s influence on setting sale of commodities, such as hotel rooms, while reference prices target cost of product or service. Reference pricing is influenced by posted prices, market prices and past experiences. For instance, considering a certain case in one of New York’s hotels (market price) based on the earlier standard charges (past experience) and the current price, let say $150, the posted price becomes the reference price. Consequently, if the reference price is varied in other online suppliers, this will trigger the notion about the unfairness in consumers causing a breach of customer’s dual entitlement (Kimes, 2002).
In accordance with Kahneman et al., (1986), dual entitlement is directly related to fairness. Supposedly, firms are motivated by the profits gained or to be gained whereas customers are driven by the idea of reference transaction. There are two hypotheses under which the dual entitlement is based. First, pikes increases should be directly proportional to the production cost. Customers tend to agree with this relationship. The next hypothesis pertains to the indirect proportionality of the two factors, commodity prices and production cost. For instance, price increases whereas the production are constant. Customers are strongly opposed to this hypothesis (Kahneman et al., 1986). Based on the hotel industry, the rates of accommodation rooms may rise as a result of their setup cost increases. In addition, the increment in rates should be consistent in all the hotels. This is acceptable to the customers. However, inconsistency in either the proportionality between prices to cost increase as well as with other similar websites offering the same is termed unfair. Offering varying prices and charges for similar products, service and accommodation compared with others impact negative perception on the consumers. The concept of fairness has been much investigated where it is collectively agreed that it is a contemporary and most significant aspect determining loyalty and satisfaction of consumers and companies profitability, as well (Kimes, 2002).
Over the years, rate parity has evolved as an average measure in the hospitality industry despite being viewed as the fair rate surety. To date, hotels have not been able to unlock the stalemate involved with rate disparities. Nevertheless, online pricing stills remains a big problem for hoteliers prompting further research into this area from a global perspective. Hotels in the United States offer the lowest price rates through their own websites worldwide. More specifically, hoteliers in the US perform better when compared with their international counterparts in respect to rate parity, price rates and accommodation availability across their websites. Nevertheless, rate parity remains a big challenge facing most the US brands. This is due to coexistence of the indirect channels of distribution. Despite a majority of US hotels adapting to direct channels of distribution, indirect channels still represent a larger portion of the entire online reservation process. To overcome this margin by indirect channels, hotels must come up with strict rate parity measures in their direct channels to ensure best rates are guaranteed. This can promote efficacy due to the direct business-to-consumer (B2C) relationship. B2C relationship increases bonding and thus enhances consumer loyalty. In addition, B2C helps in reducing overreliance on third parties hence attracting more profits to hotels with the help of their own websites (Wolff, 2004).
In regard to online pricing benefits, hotels are attracted to online pricing rather than ordinary travel agencies. This is attributed to the fact that travel agencies’ charges are extremely expensive leaving little or no profits to the hotels. With the introduction of online commerce, many firms have benefitted not only hospitality industry. Online commerce ensures high internet traffic, that is, majority of consumers can be reached. In addition, it enables easy and fast distribution. For example, Best Western International employed telephone technology in making reservations, which contributed to over half of its business (Wolff, 2004). However, the situation changed drastically when with the help of the Best Western Web-Site telephone reservation fell to 28 percent. As a result, the firm’s revenue elevated to over $1million on a regular basis. In respect to Marriott’s, a lodging firm using online commerce, aimed at achieving the most influential site, www.marriott.com.
The accomplishment of the dream triggered much increment in reservation and revenue by 38 percent and 48 percent respectively. The revenue achieved was twice higher when compared to the industry’s average. In terms of gross revenue, $2.7 billion were yielded from the online commerce plus others emanating from online call center services (Wolff, 2004). Wolff (2004) noted that high revenues and low running costs influenced firms to adopt online commerce. Relative to Hilton Hotels, their online site achieved 530,000 reservations in February 2004, which was a 34 percent increment compared relatively to the figures in the previous year. Likewise for Fairmont hotel, whereby, reservation increased by 35 percent in 2002 using its direct internet site, Fairmont.com. In addition, its inventory control became more effective. As of 2004, one-fifth of its online commerce was facilitated by the indirect (third party) intermediaries (Wolff, 2004).
According to Carroll and Siguaw (2003), hotels opted to use electronic distribution in order to forego the cost of selling through indirect intermediaries and coming up with their online sites. Because of this, hotels are able to eliminate commissions from travel agencies and Global Distribution System (GDS) fees. The commission ranges from 5 to 10 percent whereas the fees are from $3 to $5 per transaction respectively. The most significant and effective channel of distribution is the direct channel. This is due to the fact that it is the cheapest marketing strategy. In reality, making a reservation through GDS costs $24 and from $8 to $12 while using a call center. On the contrary, hotels were charged between $3 and $3.5 for reservations achieved through their own websites. PhoCusWright Inc. (2006) carried out a research about the fees charged in making reservations in Hyatt Hotels. Through the use of call centers, $3 would be charged while $3 for direct online reservations through the website. Likewise, the charges are similar for other hotels such as Marriott and Six Continents. Direct channel of distribution is of much importance as it eliminates overreliance on indirect channels like intermediaries and discounters.
Finally, Toh et al., (2011) portrayed the online sales breakdown using the 2009 Travel CLICK statistics featuring about 30 international hotels in 2008. The statistics showed that 75 percent of online sales came from hotel websites, 16 percent came from travel agencies while opaque sites catered for the remaining percentage. From the statistics, it was found that hoteliers embraced the significance of applying appealing strategies to woo many customers to their online sites (Toh et al., 2011).
To attract potential customers, hotels came up with several strategies to market their online sites. Most often, data mining was the strategy most employed by hotels. This strategy involves merging up the entire customer’s information obtained from previous visits. Thereafter, follow-ups are made to those customers by sending them invitational mails. These invitation emails contain attractive offers and bonuses to lure customers. Additionally, hotels can also employ the best rate guarantee to attract customers. The best rate guarantee assures customers get reduced prices as recommended by the online travel agencies (OTAs) (Schultz, 2008). Schultz (2008) reported that a particular hotel had guaranteed to offer free accommodation twice plus a gift worth $100 to their customers who returned to counteract any lower rate from their competitors. He further noted that harmonization of better rates on different distributions channels could be achieved using the best rate guarantee.
To enhance the searching stability of their websites, the majority of hoteliers employ Google, “pay by click” internet sites amongst other search engines such as OTAs websites. More often, large hotels and their affiliates find themselves at the top of the searching list on the OTAs websites. This is because large hotels can negotiate for low commissions rates as opposed to the smaller ones. Although OTAs provide broad alternatives ensuring effective searches based on prices, location and other criteria, it poses a great challenge to hotels aiming to attract customers to their own websites. Therefore, hotels must properly evaluate the online search they are using and the effect it has on their website. Moreover, another approach that can be employed to lure customers is call centers and onsite toll-free telephone. These calls are meant to lure customers using their free offers like parking, movies, breakfast and Wi-Fi among others. Hotels are going to an extent of training their customer services personnel on tricks to attract more customers. These tricks are aimed at directing their customers to their hotel’s websites as well as using them. To win customers’ loyalty to their websites, hoteliers upgrade their sites more frequently to adjust their rates. This is because customers concentrate more on rates. To achieve this, however, the hotel needs more creativity in the provision of free service offers such as free parking and free internet (Schultz, 2008).
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