DOI: https://doi.org/10.18601/01207555.n27.08
Turismo, gestión y hospitalidad
ANALYSIS OF OTA IMPACT ON HOTEL RESERVATIONS. CASE STUDY: BOGOTÁ1
ANÁLISIS DEL IMPACTO DE LAS OTA EN LAS RESERVAS DE LOS HOTELES. CASO DE ESTUDIO: BOGOTÁ
Joaquim Majó Fernández
Doctor en Turismo por la Universidad Politécnica de Cataluña
Decano de la Facultad de Turismo de la Universidad de Girona, España
[Joaquim.majo@udg.edu]
Laura Vall-Llosera
Doctora en Economía por la Universidad de Girona (UdG)
Vinculada al Departamento de Economía en el Área de Métodos Cuantitativos para la Economía y la Empresa de la Universidad de Girona (UdG)
Vicerrectora de Estudiantes e Inserción Laboral de la Universidad de Girona (UdG), España
[laura.vall_llosera@udg.edu]
Daissy H. Moya
Doctora en Turismo por la Universidad de Girona y la Universidad de las Islas Baleares
Docente en la Facultad de Administración de Empresas Turísticas y Hoteleras de la Universidad Externado de Colombia, Colombia
[daissy.moya@uexternado.edu.co]
1 Para citar el artículo: Majó, J., Vall-Llosera, L. y Moya, D. (2020). Analysis of the OTA's impact in hotel reservations: Case study: Bogotá. Turismo y Sociedad, XXVII, pp. 145-159.
Fecha de recepción: 27 de junio de 2019
Fecha de modificación: 18 de julio de 2019
Fecha de aceptación: 27 de agosto de 2019
Abstract
The purpose is to analyze the impact of online travel agencies (OTA) reservations on the probability of making reservations on the hotel website. For this purpose, from January 26 to February 26, 2016, the reservations made at 10 hotels located in Bogota (Colombia) of the GHL Hotel Chain were analyzed through the official website of the hotel and OTA. It was found that 6,8% of reservations are made through the hotel websites, while OTA groups make up 93,2% of the bookings. Booking.com was the OTA where the biggest number of reservations were made, with 55,3%, followed by Expedia.com, with 29,1%. The present research is the first in Latin America to analyze the reservations made through OTA's and to compare them with those received by the hotel website. Likewise, it analyzes, the percentage and number of reservations by different OTA's, allowing to gain insight into the interests of the guests at the time of booking.
Keywords: Online travel agency, tourism, hotel, revenue management, website.
Resumen
El objetivo del presente trabajo fue analizar el impacto de las OTA en la probabilidad de realización de reservas en la página web de un hotel. Con este fin, del 26 de enero al 26 de febrero de 2016 se observaron las reservas realizadas en 10 hoteles de la Cadena Hotelera GHL de Bogotá (Colombia) por medio de la página web y OTA. Se encontró que el 6,8% de las reservaciones fueron hechas mediante la página web del hotel, mientras que el 93,2% se hicieron por intermedio de OTA. La OTA que registró el mayor número de reservas fue Booking.com, con el 55,3%, seguida por Expedia.com, con un 29,1%. La presente investigación es la primera en América Latina en llevar a cabo un análisis de las reservas mediante OTA y compararlas con la página web de un hotel. También analiza el porcentaje y número de reservaciones por las diferentes OTA.
Palabras clave: Agencia de viajes en línea, turismo, hotel, revenue management, página web.
1. Introduction
Nowadays, hoteliers have noticed that most of their bookings are being made through electronic systems, especially through OTA (Online Travel Agencies) which charge a certain fee for each reservation, thus reducing the hotel's utility. This circumstance has led to conduct research about the amount of people who make their bookings using an online platform. Toh, DeKay y Raven (2011), in their study of 249 people in 4 hotels in Seattle, wa, USA, proved that 80% of potential guests used the internet while looking for the hotel in which they would stay at. When considering the entire group, 67% of the people made their reservation using either the hotel's website or an OTA (Toh, DeKay, & Raven, 2011). Furthermore, research has been conducted to analyze the effect that the ranking of a hotel in the OTA has over its reservations, showing that hotels positioned on the top are the first ones that potential guests see and analyze. There is the case when, if the list is too long, guests are going to focus their attention towards the hotels that best fit their budget. Once there is a group of selected hotels, the images next to the descriptive text give the hotel a hedonic touch that affects the decision making process for a reservation; which in turn complements the explanation given by the hotel (in the descriptive text) where the services offered may not appear as very appealing (Pan, Zhang, & Law, 2013). This situation has led to the analysis of the aspects that truly affect the decision-making process of making a hotel reservation or not.
The following investigation analyzes the behavior of the bookings made in 10 hotels of the hotel chain GHL in Bogotá from January 26 to February 26 of 2016; with the conclusion that most of the reservations are made through an OTA and that as the amount of reservations made on this platform increases, so does the amount of reservations made on the hotel's website. The hospitality sector nowadays needs to adopt innovative means that will catch the customer's attention and that will improve the competitiveness in a world that is constantly changing. The objective of this article is to analyze the impact that reservations made on an OTA have over the probability of making reservations on the hotel's website. In order to do this the hypothesis established is based on the idea that when hotel bookings made on OTAS increases, the reservations made on hotel websites also increases. The investigation ends by presenting some suggestions for having a good website that will allow to increase the percentage of reservations made on the hotel's official site, thus increasing income, and reducing the percentage of the OTA that take part in the hotel's sales.
2. Literature review
2.1 History and evolution of hotel reservations
In the early 70s, the big hotel chains began to use computerized reservations systems or CRS in order to manage their inventory of vacant rooms (Martínez, Majó, & Casadesús, 2006). Currently, the majority of hotel reservations are made by electronic means that facilitate marketing strategies and sales opportunities (Schegg, Stangl, Fux, & Inversini, 2013). Nowadays, guests are more informed about their destination due to the fact that they search for information online and therefore they create a previous image that will allow them to manage the reservations (Li, Pan, Zhang, & Smith, 2009). New technologies affect knowledge, attitudes and behavior of tourists due to the level of transparency in prices as well as products that in turn increase the power of travelers, who are more sensitive to prices each day, less loyal to a certain brand, and more sophisticated (Dabas & Manaktola, 2007). Hotel managers have discovered that one way to increase reservations is by improving the management and the use of social networks which provide the hotel with a communication channel with tourists by asking them to register their good experiences online (Gretzel & Yoo, 2008). Several clients, depending on their culture, start to make their reservations with anticipation and they take advantage of online discounts in order to get better fees (Beldona & Kwansa, 2008). Clients are leaving behind the participation of so called travel agencies that are face to face and they prefer an OTA (Grenflaten, 2009).
2.2 Online travel agencies (OTA)
Now, hotels have several sale channels, one of them are the Online Travel Agencies (Kang, Brewer, & Baloglu, 2007). Said agencies facilitate sales by getting the service providers in touch with potential clients (Kracht & Wang, 2010), doing the job that could formerly only be done by travel agencies (Law, Leung, Lo, Leung, & Fong, 2015). Some of this OTA offer their clients packages with special fees for the purchase of accommodation and transport that make the clients fall in love, and therefore they end up preferring to make their purchases through this channel instead of the hotel's official website (Kim, Bojanic, & Warnick, 2009).
OTA offer their services and receive a fee that reduces the hotel's utility (Toh, Raven, & DeKay, 2011). Their successful marketing is based on providing the potential guest the lowest fee in the market, which in turn pressures the hotels to maintain fee parity (Gazzoli, Gon Kim, & Palakurthi, 2008), and then a level of concern emerges in the hoteliers for the way in which they should organize the price structure, room inventory, and on how they could maintain brand loyalty of guests (Carvell & Quan, 2008). It is important to clarify that the rank in which a hotel appears in each one of the OTA depends on ratings received by guests that have used the services; on the room availability provided by the hotel; on sales conversion, which refers to the amount of effective sales of a hotel in one period; and finally, on the participation, in special deals to appear in the top positions. The space provided for each hotel in the OTA is intended to be used for images, a presentation of the hotel's services, prices, and location (Pan et al., 2013).
OTA have evolved in a way that they provide more and better services each day, as much as the internet allows (Buhalis & Law, 2008). One of the services they provide is showing the reviews made by guests who have used the services, which then affect the fee that can be established for a room (Duverger, 2013). Some hoteliers have taken advantage of technology to improve their brand and market position, however, some others, who are less receptive, are having significant losses because of not knowing how to confront change (Runfola, Rosati, & Guercini, 2013). Beritelli and Scheef (2016) affirm that the hotels that use more online marketing channels are those that are currently receiving the most reservations. The study conducted by Anderson (2009) proves that when hotels start to work with OTA their reservations have increased between 7,5% and 26%. Meanwhile, Thakran and Verma (2013) state that online presence should not be limited to marketing channels, but should also consider Social Media, opinion websites, and the hotel should be highly ranked on the main search engines. In the meantime, Baloglu et al. (2010) emphasize on the importance of "price comparing" websites, which are also used by clients before making their online reservation.
2.3 Hotel price comparison
Among all the price comparison sites, one of the most important ones is Trivago, which compares daily hotel offers of approximately 1,3 million hotels around the world, in 33 languages with 55 local websites (Trivago, 2018). Another price comparison company is Kayak, which processes around 15.000 million requests each year, in 20 languages (Kayak, 2018). Skyscanner is also a relevant price comparison company, it was established in 2003, provides jobs for more than 800 people and has offices in Barcelona, Peking, Budapest, Edinburgh, Glasgow, London, Miami, Shenzhen, Singapore, and Sofia. Skyscanner is part of the Ctrip group and is available in over 30 languages and 70 currencies (Skyscanner, 2018). It is important to point out TripAdvisor as well, which has approximately 390 million visitors each month, 435 million reviews and has over 6,8 million comments on hotels, restaurants, and attractions (TripAdvisor, 2018). Even though Google is not considered under the price comparison category, as a search engine it has the option of comparing hotel prices by typing in the search box: "Hotels in". Once you type the destination a map of the city appears showing different hotels, therefore allowing the client to filter their search by price, location, value, and hotel category (Google, 2018).
In the meantime, hotels are also taking advantage of technology in order to design their marketing strategies due to the fact that internet improves accessibility, comfort, speed, novelty, global coverage, quality/richness of information, flexibility, and a reduced cost that allows guests to get to know the services from anywhere in the world and on any device (Cañero, Orgaz, & Moral, 2015). Having an appropriate internet presence does not just mean having a website of the hotel or commercializing services through an OTA. The emergence of web 2.0, which includes social networks, travelers' reviews, and online reputation among other things, makes it necessary for hoteliers to adapt to this new reality (Martínez, Bernal, & Mellinas, 2012). People who use hotels consult the opinions of guests who have already used the services increasingly each day, and those opinions allow them to make decisions. The study conducted by Vermeulen & Seegers (2009) shows that hotels with the lowest brand recognition are the ones that are more analyzed, while the experience of people who register their opinions does not affect as much in the decision-making process of those who are making the reservations.
2.4 Revenue management
Revenue management (RM) is usually defined as the art and science of projecting the demand while simultaneously adjusting the price and the availability of products in order to properly achieve the expected demand (Erdem & Jiang, 2016; Queenan, Ferguson, & Stratman, 2011). The RM started to be used approximately 70 years ago in the aeronautic industry and then began to extend to the entire sector of hospitality (Anderson & Xie, 2010). The first published article about RM concepts was written by Eric Orkin in 1988 and was published by Cornell Quarterly (Orkin, 1988). Nowadays, with the technological support, the RM is integrating with all aspects of hotel commercialization, operation strategies, and goes beyond the management of room inventory. Due to the fact that prices are essentially transparent, hotels have to keep in mind the price elasticity to the client and not just focus on having the same prices as the competition, with the objective of optimizing prices (Cross, Higbie, & Cross, 2009). It is important to have revenue management and ota participation strategies that are properly defined, as well as a good design of the hotel's website.
2.5 Tips for having a good website
Since the space given to hotels on an OTA is limited to showing their services, they should take advantage of their website because they can offer more content on the information provided so that they can possibly turn a visit into a sale.
Some authors recommend that, in order to improve reservations made directly on the hotel's official website, it (the website) should include eye catching photographs, provide links to other sites of the main web-page, use sober colors, be organized, and be careful with appearance (Phelan, Christodoulidou, Countryman, & Kistner, 2011). Some others suggest that the best possible fee should be published, thus optimizing the site so that it can be easily found by online clients. Also, they suggest that they should collect guest information so that there can be a more personalized service offered, maintain the best rooms for online sale on the official website, offer discounts and other special deals to clients that register online, provide incentives for a client's future stay if they make the reservation on the official website, and improve the website by providing the best information (Toh et al., 2011).
The main objective of the hotel's website should be appearing at the top positions on Google when a client types in the key word. To do so, that key word should be placed on the photographs, on the website's headings and other places of the website so that Google can index all these pages (Bodenlos, Bogert, Gordon, Hearne, & Anderson, 2010). The hotel can also purchase AdWords so that it improves its ranking on the search results. One should ensure that the hotel appears on the local tourism authorities' websites.
The hotel's website should be kept up to date permanently, it should be in several languages, provide complete information about reservations, which includes reservation policies, contact information (phone number, address, email, fax, a space for frequently asked questions, contact through the website and an option of making a direct reservation online). It should also have a booking motor that can allow transactions to be made directly on the hotel's website, the motor should let frequent clients make reservations allowing them to access a certain code that gives them special fees (Avcikurt, Giritlioglu, & Sahin, 2011). Furthermore, it is suggested that there should be information about special services for children, transportation services near the hotel, distance to the airport, general information of the city and nearby tourist attractions, as well as the weather. Additionally, the website's managers should be aware of the software that allows them to know where the visits came from so that marketing strategies can be refocused. It is very important to show the number of stars the hotel has from the home page, because the guests know what type of accommodation they are looking for and from the home page they can have an idea of whether the hotel fulfills their expectations or not. It is also relevant to highlight the importance of having a map of the website and of having links that lead to it other pages (Rong, Li, & Law, 2009).
As a final recommendation, it would be useful to take advantage of the information registered by guests on the website, so that they can have a more personalized visit and improve their experience during their stay. However, it is important to be careful with the use of confidential information, because the wrong management of personal information could lead to legal problems (O'Connor, 2007).
Information and communication technologies have had an unprecedented impact in the hotel industry, thus revolutionizing the way in which hotel managers deal with the everyday tasks (Law, 2009). The growing popularity of internet applications has increased the number of people that use technology when searching for information and making online purchases (Lawton & Weaver, 2009). As a result of the huge potential market that exists through electronic and mobile marketing, the majority of touristic service suppliers have established websites and/or smartphone apps in order to distribute and make their products and/or services known to consumers (Law et al., 2015; Liu & Law, 2013). Internet and mobile technologies allow consumers to acquire information, connect directly with touristic service suppliers, and purchase products related to their trips using their electronic devices (Morosan, 2014).
Hoteliers that manage their distribution channels and prices efficiently end up improving the positioning of their brand, make more of their guests loyal, and reduce the risk of losing potential clients among intermediaries (O'Connor & Murphy, 2008).
3. Methodological design, objectives, and hypothesis
For the following study, a general objective and hypothesis are defined in such way that they contrast methodologically with a regression model of a dichotomous dependent variable (logit).
The main objective of this article is to analyze the impact of bookings made on OTA have over the probability of making reservations on the hotel's website. As a consequence of this, the need to have a good website that maintains the client curious about having opportunities of added value to their reservation is manifested.
In order to do so, we propose the following hypothesis:
H1. When hotel reservations made on OTA increase, so do the reservations made on the hotels' websites.
To prove this hypothesis, a sample of hotels in Bogotá was taken. Since one of the highest season in Bogotá (Colombia) is during the annual tourism fair, called Vitrina Turística de ANATO (which took place from February 24-26 in 2016), we requested the collaboration of the GHL hotel chain with the investigation, so that they would approve the observation of the behavior of their reservations during one month in all their hotels in Bogotá. Once they were selected, they were organized by location in Bogotá (table 1).
With the purpose of determining the influence of bookings made on OTA have over reservations made on the hotel's website, information about the behavior of reservations made on three OTA (table 2) during the same period and for the exact same 10 hotels of the GHL chain was gathered. The search criteria that was considered were the date of the reservation (February 26), the number of people (1 person), and the reason of the trip (business).
3.1 Variables
Information for these 10 hotels of the GHL chain in Bogotá was gathered daily during the period defined between January 26 and February 26 of 2016. The information gathered referred to the reservations made on the hotel's website and regarding the ones made through any of the OTA mentioned before (table 3).
3.2 Analysis methodology
With the purpose of determining the probability of making a reservation on the hotel's website based on the number of reservations made on one of the OTA analyzed, the following regression model with a dichotomous dependent variable (binary logistic regression model) was specified as shown in equation (1):
where p is the probability that the event studied will occur, which in our case is that a reservation is made through the hotel's website; and refers to the ODDS-Ratio of the number of reservations made on each of the OTA of the study. The coefficients were estimated using the maximum likelihood method (Agresti, 2002; Hosmer Jr., Lemeshow, & Sturdivant, 2013; Jiménez & Aldás, 2005).
The data were analyzed with the specific software of statistical analysis, RStudio (version 0.99.903) (Yau, 2013).
4. Results
The results of the univariate descriptive analysis show that OTA are the ones that make a greater number of reservations, and therefore they are the ones with a larger volume of turnover (table 4). Particularly speaking, for these 10 hotels during the period of the study, it is evident that only 6,8% of the reservations are made through the hotel's website (which represents 3,1% of the turnover volume), whereas 93,1% of the reservations are attributed to the group of OTA (which represents 96,9% of the turnover volume). On the other hand, it can be said that Booking.com is the OTA in which the greatest number of reservations are made and where the largest volume of turnover is made (55,3% and 59,5%, respectively). In the meantime, Despegar.com is the OTA with the lowest number of reservations and the smallest value of turnover (8,4% and 8,3%, respectively).
Regarding the scores and ranks of these 10 hotels in the different OTA (table 5), it is evident that Despegar.com is the one with the best average score and the best rank, while Expedia.com has the worst average score, and Booking.com has the lowest rank.
Considering the results of the Logistic Regression Model (table 6), we can observe that, in every case, when the number of reservations on an OTA increase, the probability of making a reservation through the hotel's website increases as well.
In this sense, when the number of reservations made on Booking, Despegar, or Expedia increases in one unit, the probability that the hotel will receive a reservation through its website increases in 11,6%, 47,3%, and 22%, respectively.
This information makes it clear that OTA end up leading clients to the hotel's own website or its chain's website, and that if security and added value elements are included in the reservation, a lot of the reservations of the OTA can be transferred to the hotel's very own reservation agent, thus allowing to reduce commissions.
5. Conclusions and managerial implications
The results found from the 10 hotels that were analyzed show how, nowadays, OTA are the ones that make the greatest number of reservations and the largest volume of turnover. This is not news even though the evidence of the volume of turnover could be a reason to reflect upon. On the one hand, one could define a complete study of costs to find out up to what point would having a "personal" reservation system be profitable, if there are not going to be any changes made to improve those percentages. This situation itself cannot be seen as positive for the hotels, because they would stop receiving income for the purchases made on the OTA. Therefore, one of the possible options is improving the hotel's website and taking advantage of the synergies that OTA offer to invite the guest to make the reservation directly. In this analysis, a direct and positive relationship is revealed between the number of reservations made on OTA and the probability of making a reservation through the hotel's website. The hotel manager should seize the visits of possible clients with a website that solves the process of their reservations in a direct, safe, and trustful way, a website that provides some degree of added value that cannot be offered through the OTA: the personalization of these reservations.
5.1 Theoretical implications
This investigation broadens previous work that has been carried out in the field of OTA and contributes to knowledge in the touristic field.
Our results scientifically prove that, when reservations on an OTA increase, direct sales on the GHL hotel chain's website increase significantly.
These results are related to previous studies, such as the one carried out by Franke & Hader (2014), who emphasize the importance of offering clients a variety of options, like tools of selection that let them choose the product they wish to buy. In our case, the OTA offer tools such as filter by price, location, and scores, that allow the client to choose the hotel that best suits his/her budget and needs.
Few researches have been conducted in which the behavior of hotel reservations made using OTA is analyzed; this study offers a perspective on the behavior of guests in their process of making an online reservation.
5.2 Managerial implications
Even though it is important to commercialize hotels through OTA, it is also important to improve and have a strong hotel website to motivate the guest to make his/her reservation directly. In order to do so, we present the following recommendations, that have been summarized from the previously cited documents:
5.3 Limitations and suggestions for future research
This study is limited to the hotels in Bogotá that belong to the GHL hotel chain. The results of this study provide hotel managers in Bogotá and Colombia with information that allows them to improve the design of their hotel's website and the marketing strategies through intermediation of OTA. For future research, it is recommended that the area of study be extended to a greater number of hotels in different cities and countries, and to include the intermediate role of a greater number of OTA.
References
Agresti, A. (2002). Wiley Series in Probability and Statistics. In Analysis of ordinal categorical data (2nd ed.) (pp. 397-405). New Jersey: John Wiley & Sons, Inc. DOI: 10.1002/9780470594001.scard
Anderson, C. K. (2009). The billboard effect: Online travel agent impact on non-OTA reservation volume. Cornell Hospitality Report, 9(16), 5-6.
Anderson, C. K., & Xie, X. (2010). Improving hospitality industry sales twenty-five years of revenue management. Cornell Hospitality Quarterly, 51(1), 53-67. DOI: 10.1177/1938965509354697
Avcikurt, C., Giritlioglu, I., & Sahin, S. (2011). An evaluation of thermal hotel websites and the use/non-use of the Internet as a marketing tool by thermal hotels in Turkey. African Journal of Business Management, 5(7), 2.817-2.827. DOI: 10.5897/AJBM10.1187
Baloglu, S., Erdem, M., Brewer, P., Mayer, K., Christodoulidou, N., Connolly, D. J., & Brewer, P. (2010). An examination of the transactional relationship between online travel agencies, travel meta sites, and suppliers. International Journal of Contemporary Hospitality Management, 22(7), 1.048-1.062. DOI: 10.1108/09596111011066671
Beldona, S., & Kwansa, F. (2008). The impact of cultural orientation on perceived fairness over demand-based pricing. International Journal of Hospitality Management, 27(4), 594-603. DOI: 10.1016/j.ijhm.2007.07.024
Beritelli, P., & Schegg, R. (2016). Maximizing online bookings through a multi-channel-strategy-effects of interdependencies and networks. International Journal of Contemporary Hospitality Management, 28(1), 68-88. DOI: 10.1108/IJCHM-07-2014-0326
Bodenlos, G., Bogert, V., Gordon, D., Hearne, C., & Anderson Ph D., C. (2010). Best practices in search engine marketing and optimization: The case of the St. James Hotel. Cornell Hospitality Report, 10(16), 6-15.
Booking.com. (2017). Booking.com. Retrieved from http://www.booking.com/content/about.es.html?label=gen173nr-1FCAEoggJCAlhYSDNi-BW5vcmVmaEaiAQGYAQrCAQNhYm7IAQZYAQHOAQH4AQuoAgQ;sid=5c1933db682adb7ed67960a22148d80e;dcid=4
Buhalis, D., & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10 years after the Internet-The state of eTourism research. Tourism Management, 29(4), 609-623. DOI: 10.1016/j.tourman.2008.01.005
Cañero, P. M., Orgaz, F., & Moral, S. (2015). Análisis de las variables que influyen en la reputación online de las empresas turísticas. El caso de los hoteles de Córdoba y Granada. Gran Tour, Revista de Investigaciones Turísticas, 11, 103-120. Retrieved from https://dialnet.unirioja.es/servlet/articulo?codigo=5156011
Carvell, S. A., & Quan, D. C. (2008). Exotic reservations-Low-price guarantees. International Journal of Hospitality Management, 27(2), 162-169. DOI: 10.1016/j.ijhm.2007.07.016
Cross, R. G., Higbie, J. A., & Cross, D. Q. (2009). Revenue management's renaissance: A rebirth of the art and science of profitable revenue generation. Cornell Hospitality Quarterly, 50(1), 56-81. DOI: 10.1177/1938965508328716
Dabas, S., & Manaktola, K. (2007). Managing reservations through online distribution channels: An insight into mid-segment hotels in India. International Journal of Contemporary Hospitality Management, 19(5), 388-396. DOI: 10.1108/09596110710757552
Duverger, P. (2013). Curvilinear effects of user-generated content on hotels' market share: A dynamic panel-data analysis. Journal of Travel Research, 52(4), 465-478. DOI: 10.1177/0047287513478498
Erdem, M., & Jiang, L. (2016). An overview of hotel revenue management research and emerging key patterns in the third millennium. Journal of Hospitality and Tourism Technology, 7(3), 300312. DOI: 10.1108/JHTT-10-2014-0058
Expedia. (2017). History of the online travel industry pionner. Retrieved from http://www.expediainc.com/about/history/
Fernández-Pérez, M. F. (2015). Marketing de una marca reciente en el mercado (Doctoral dissertation). Universidad Nacional de Cuyo, Mendoza, Argentina.
Franke, N., & Hader, C. (2014). Mass or only "niche customization"? Why we should interpret configuration toolkits as learning instruments. Journal of Product Innovation Management, 51(6), 1.214-1.234. DOI: 10.1111/jpim.12137
Gazzoli, G., Gon Kim, W., & Palakurthi, R. (2008). Online distribution strategies and competition: Are the global hotel companies getting it right? International Journal of Contemporary Hospitality Management, 20(4), 375-387. DOI: 10.1108/09596110810873499
Google. (2018). Comparador de tarifas de hoteles en Google. Retrieved from https://support.google.com/websearch/answer/6276008
Gretzel, U., & Yoo, K. H. (2008). Use and impact of online travel reviews. In P. O'Connor, W. Höpken & U. Gretzel (eds.), Information and communication technologies in tourism 2008 (pp. 35-46). Vienne: Springer. DOI: 10.1007/978-3-211-77280-5_4
Grønflaten, Ø. (2009). Predicting travelers' choice of information sources and information channels. Journal of Travel Research, 48(2), 230-244. DOI: 10.1177/0047287509332333
Hosmer Jr., D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression (3th ed.). New Jersey: John Wiley & Sons.
Jiménez, U., & Aldás, J. (2005). Análisis multivariante aplicado: aplicaciones al marketing, investigación de mercados, economía, dirección de empresas y turismo. Stamford: Thomson.
Kang, B., Brewer, K. P., & Baloglu, S. (2007). Profitability and survivability of hotel distribution channels: An industry perspective. Journal of Travel & Tourism Marketing, 22(1), 37-50. DOI: 10.1300/J073v22n01_03
Kayak. (2018). Acerca de Kayak - Kayak. Retrieved from https://www.kayak.es/about
Kim, J., Bojanic, D. C., & Warnick, R. B. (2009). Price bundling and travel product pricing practices used by online channels of distribution. Journal of Travel Research, 47(4), 403-412. DOI: 10.1177/0047287508328658
Kracht, J., & Wang, Y. (2010). Examining the tourism distribution channel: Evolution and transformation. International Journal of Contemporary Hospitality Management, 22(5), 736-757. DOI: 10.1108/09596111011053837
Law, R. (2009). Disintermediation of hotel reservations: The perception of different groups of online buyers in Hong Kong. International Journal of Contemporary Hospitality Management, 21 (6), 766-772. DOI: 10.1108/09596110910976007
Law, R., Leung, R., Lo, A., Leung, D., & Fong, L. H. N. (2015). Distribution channel in hospitality and tourism: Revisiting disintermediation from the perspectives of hotels and travel agencies. International Journal of Contemporary Hospitality Management, 27(3), 431-452. DOI: 10.1108/IJCHM-11-2013-0498
Lawton, L. J., & Weaver, D. B. (2009). Travel agency threats and opportunities: The perspective of successful owners. International Journal of Hospitality & Tourism Administration, 10(1), 68-92. DOI: 10.1080/15256480802557283
Li, X. R., Pan, B., Zhang, L. G., & Smith, W. W. (2009). The effect of online information search on image development: Insights from a mixed-methods study. Journal of TravelResearch, 48(1), 45-57. DOI: 10.1177/0047287508328659
Liu, Y., & Law, R. (2013). The adoption of smartphone applications by Airlines. In L. Cantoni, & Z. P. Xiang (eds.), Information and communication technologies in tourism 2013 (pp. 47-57). Vienne: Springer.
Martínez, J., Majó, J., & Casadesús, M. (2006). El uso de las tecnologías de la información en el sector hotelero. In A. Aguayo, J. L. Caro, & I. Gómez (coords.), VI Congreso Nacional Turismo y Tecnologías de la Información y las Comunicaciones TURITEC 2006 (pp. 47-58). Málaga: University of Málaga. Retrieved from http://turitec.com/wp-content/uploads/2016/04/TURITEC_2006.pdf
Martínez, M., Bernal, J. J., & Mellinas, J. P. (2012). Los hoteles de la región de Murcia ante las redes sociales y la reputación online. Revista de Análisis Turístico, 13, 1-10. DOI: https://doi.org/10.1234/RAT2011n11
Morosan, C. (2014). Toward an integrated model of adoption of mobile phones for purchasing ancillary services in air travel. International Journal of Contemporary Hospitality Management, 26(2), 246-271. DOI: 10.1108/IJCHM-11-2012-0221
O'Connor, P. (2007). Online consumer privacy: An analysis of hotel company behavior. Cornell Hotel and Restaurant Administration Quarterly, 48(2), 183-200. DOI: 10.1177/0010880407299541
O'Connor, P., & Murphy, J. (2008). Hotel yield management practices across multiple electronic distribution channels. Information Technology & Tourism, 10(2), 161-172. DOI: 10.3727/109830508784913103
Orkin, E. B. (1988). Boosting your bottom line with yield management. Cornell Hotel and RestaurantAdministration Quarterly, 28(4), 52-56. DOI: 10.1177/001088048802800416
Pan, B., Zhang, L., & Law, R. (2013). The complex matter of online hotel choice. Cornell Hospitality Quarterly, 54(1), 74-83. DOI: 10.1177/1938965512463264
Phelan, K. V., Christodoulidou, N., Countryman, C. C., & Kistner, L. J. (2011). To book or not to book: The role of hotel web site heuristics. Journal of Services Marketing, 25(2), 134-148. DOI: 10.1108/08876041111119859
Queenan, C. C., Ferguson, M. E., & Stratman, J. K. (2011). Revenue management performance drivers: An exploratory analysis within the hotel industry. Journal of Revenue and Pricing Management, 10(2), 172-188. DOI: 10.1057/rpm.2009.31
Rong, J., Li, G., & Law, R. (2009). A contrast analysis of online hotel web service purchasers and browsers. International Journal of Hospitality Management, 28(3), 466-478. DOI: 10.1016/j.ijhm.2009.02.002
Runfola, A., Rosati, M., & Guercini, S. (2013). New business models in online hotel distribution: Emerging private sales versus leading ids. Service Business, 7(2), 183-205. DOI: 10.1007/s11628-012-0150-1
Schegg, R., Stangl, B., Fux, M., & Inversini, A. (2013). Distribution channels and management in the Swiss hotel sector. In L. Cantoni & Z. P. Xiang (eds.), Information and communication technologies in tourism 2013 (pp. 554-565). Vienne: Springer.
Skyscanner. (2018). Sobre nosotros. Retrieved from https://www.skyscanner.es/sobre-nosotros
Thakran, K., & Verma, R. (2013). The emergence of hybrid online distribution channels in travel, tourism and hospitality. Cornell Hospitality Quarterly, 54(3), 240-247. DOI: 10.1177/1938965513492107
Toh, R. S., DeKay, C. F., & Raven, P. (2011). Travel planning: Searching for and booking hotels on the Internet. Cornell Hospitality Quarterly, 52(4), 388-398. DOI: 10.1177/1938965511418779
Toh, R. S., Raven, P., & DeKay, F. (2011). Selling rooms: Hotels vs. third-party websites. Cornell Hospitality Quarterly, 52(2), 181-189. DOI: 10.1177/1938965511400409
Tripadvisor. (2013). TripBarometer. Retrieved from https://www.tripadvisor.es/TripAdvisorInsights/tripbarometer
TripAdvisor. (2018). Acerca de TripAdvisor. Retrieved from https://www.tripadvisor.co/pages/about_us.html
Trivago. (2018). About Trivago. Retrieved from https://company.trivago.com/
Vermeulen, I. E., & Seegers, D. (2009). Tried and tested: The impact of online hotel reviews on consumer consideration. Tourism Management, 30(1), 123-127. DOI: 10.1016/j.tourman.2008.04.008
Yau, C. (2013). R tutorial with Bayesian statistics using OpenBUGS. Amazon Digital Services Inc., 554.