research on online travel agencies

Can online travel agencies contribute to the recovery of the tourism activity after a health crisis?

Journal of Humanities and Applied Social Sciences

ISSN : 2632-279X

Article publication date: 14 July 2023

Issue publication date: 28 August 2023

Online travel agencies (OTAs) have an important role to play in reactivating tourism activity following a health crisis by providing information about the health conditions of tourist destinations. Once developed, it is necessary to analyze the effectiveness of the information provided and ascertain whether the provision of such information effects the understanding of the value of using OTAs and, in turn, the intention to do so.

Design/methodology/approach

This paper, based on an empirical case study conducted during the COVID-19 pandemic, examines whether following a health crisis, the quality of information provided by OTAs on the health conditions of tourist destinations and the perceived value of their offer generate a greater OTA services reuse intention, and signals, therefore, a return to travel.

The results show the quality of the information positively influences the perceived value, but not the OTA services reuse intention. Rather, the perceived value positively influences the OTA services reuse intention.

Practical implications

Overall, it can be suggested that providing quality health information for a destination is a necessary strategy because it contributes to increasing the perceived value of OTAs. To incentivize the intention for repeated use of OTA services, it is necessary to consider the perceived value that influences the intention to make repeat OTA reservations.

Originality/value

This research offers a novel perspective about the OTAs’ contribution to the recovery of the activity of the tourism industry after a health crisis. This contributes to achieving a more resilient sector in the face of future health crises.

• Health crisis
• Online travel agencies
• Information quality
• Perceived value
• Reservation intention
• Intention to travel

Polo Peña, A.I. , Andrews, H. and Morales Fernández, V. (2023), "Can online travel agencies contribute to the recovery of the tourism activity after a health crisis?", Journal of Humanities and Applied Social Sciences , Vol. 5 No. 4, pp. 271-292. https://doi.org/10.1108/JHASS-12-2022-0171

Emerald Publishing Limited

Copyright © 2023, Ana Isabel Polo Peña, Hazel Andrews and Victor Morales Fernández

Published in Journal of Humanities and Applied Social Sciences . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

The COVID-19 pandemic was a stark reminder of the way in which tourism supply and demand is sensitive to both natural and anthropogenic crises. As future pandemics, which may have similar devastating effects on the tourism industry, cannot be ruled out ( Ivanova et al. , 2021 ; Magno and Cassia, 2022 ), it is important to identify strategies and mechanisms that contribute towards the sector’s recovery ( Sampaio et al. , 2022 ).

Studies that show the evolution of the extensive literature specializing in the study of crises in the tourism and hospitality industry identify a need to understand more about the impacts on consumer behaviour of market mechanisms and strategies (e.g. Berbekova et al. , 2021 ; Li et al. , 2022 ; Wut et al. , 2021 ). Although these works have focused on the perspective of the company (managers or employees), there is a gap in the literature regarding the effect that the adoption of these strategies exerts from the perspective of the market. The study of the effect that response measures to health crises adopted by companies have on consumer behaviour is key to moving forward in the face of potential future health crises. In a crisis context, and from the perspective of the consumer, the psychometric or “revealed preference approach” ( Fischhoff et al. , 1978 ; Slovic, 1987 ) is used to identify and test factors that help to mitigate tourists’ perceived risk and restimulate the desire to travel.

Online travel agencies (OTAs) are the leading tourist intermediary in the distribution of tourist services as an instrument for managing trips and searching for information pre-stay ( Cortés Bello and Vargas Martínez, 2018 ). OTAs have enough potential to generate consumer participation in the purchase choice process and during the search for information ( Harrigan et al. , 2017 ). In addition, consumers appreciate information provided by OTAs. This is because OTAs facilitate the reduction of the perceived risk about if one should travel and to where that occurs as part of the travel decision-making process. This is even more pertinent during periods of crises and the resulting greater uncertainty ( Gössling et al. , 2020 ; Menchero Sánchez, 2020 ).

Considering the capacity and potential of OTAs to offer value to the customer, it is worth analyzing whether offering a higher perceived value contributes to generating a greater intention to book a trip and therefore to travel again following a crisis. Among the different elements that OTAs can face to provide a service with high perceived value is time saved in the search for information about choices available ( Sarmiento Guede, 2017 ), affordable prices ( Rodríguez et al. , 2015 ), ease of usage ( Dwikesumasari and Ervianty, 2017 ) and service quality ( Talwar et al. , 2020 ). In addition, using an OTA at the height of the pandemic, and in its immediate aftermath, negated the need for an in-person visit to high street travel agencies, which afforded a greater sense of safety because it allowed social distancing.

Considering the need for information in accordance with the new trends of responsibility in public health ( De la Puente Pacheco, 2015 ), tourists are concerned about obtaining health information during trip planning. Accordingly, OTAs can adopt communication strategies based on the health information at a destination ( Wang and Lopez, 2020 ). At the same time, there is evidence that providing information about a destination’s sanitary conditions has a positive influence on the behaviour of potential tourists. This is especially during public health crises, when the perception of risk and concern for safety are most pronounced ( Jiang and Wen, 2020 ; Wang and Lopez, 2020 ).

The implications of variables, such as the quality of information in purchasing decisions within the online context, have been studied as an instrument to measure the quality of service and as an antecedent of the repurchase intentions ( Matute Vallejo et al. , 2015 ). The quality of information is also recognized as an important factor in the adoption of information by the electronic user ( Cheung et al. , 2008 ). There is, however, a lack of research that analyzes the influence of the quality of the information provided about the sanitary conditions of a destination during a health crisis and the impact on the perceived value and the intention to make travel reservations.

The lack of understanding about the influence of the quality of information about the sanitary conditions of a destination during a health crisis will be addressed in this paper. The overall aim of this study focuses in a novel way on identifying whether the provision of quality information about the health conditions of tourist destinations and the offer provided by OTAs (collected with the variable of perceived value) constitutes actions capable of prompting potential tourists to make reservations again, and therefore to travel in the context of a health crisis, such as that generated by COVID-19. More specifically, the research objectives are (1) to analyze whether the perceived value provided by OTAs has a positive influence on the OTA services reuse intention in the context of a health crisis, (2) to determine whether providing quality information about the sanitary conditions of the tourist destination has a positive influence on the perceived value of the offer provided by OTAs and (3) to examine whether providing quality information about the health conditions of the tourist destination has a positive influence on the OTA services reuse intention in the context of a health crisis.

Given the aim and objectives of this research it was necessary to conduct the research aims in a country that has been deeply affected by the global health emergency caused by COVID-19. Thus, Spain was selected for study because it was among one of the most badly impacted countries in terms of tourism during the crisis. This was due to the widespread restrictions placed on both domestic and international travel and government-imposed lockdowns around the world ( Gursoy and Chi, 2020 ). In addition, the tourism industry is a major economic driver in Spain ( Garrido-Moreno et al. , 2018 ).

Literature review

Online travel agencies, crisis management and the recovery of tourist activity in health crises situations.

The tourism industry is inherently vulnerable to disaster and external crises, from natural to anthropogenic incidents ( Ritchie, 2004 ). Despite some recent studies of crisis management in tourism, the field lacks research about both the impact of such events on specific organizations and responses to such events ( Faulkner, 2001 ; Ritchie, 2004 ). This section reviews existing literature on crisis management in the tourism industry. It, firstly, defines the main concepts. Secondly, it summarizes relevant studies of crisis management and recovery plans in the tourism industry.

There has been extensive discussion in the literature describing and conceptualizing what a crisis and/or disaster is. This is especially so in the context of the tourism industry ( Faulkner, 2001 ; Lo et al. , 2006 ; Ritchie, 2004 ). Faulkner (2001) conceptualizes disasters as unpredictable, catastrophic changes that originate outside an organization and over which it has very little control. As Kim et al. (2005) highlight, a disaster involves unexpected changes to which one can normally respond only after the event happens, by implementing contingency plans or responding reactively. A crisis is defined as any action or failure to act that interferes with an organization’s ongoing functions, achievement of objectives, viability or survival; or that has a detrimental personal effect on its main stakeholders ( Ritchie, 2004 ). It is argued that crises arise due to a lack of planning and proper management and could thus have been anticipated, whereas one can only respond to a disaster after the fact ( Kim et al. , 2005 ).

The COVID-19 pandemic was unique in nature, scale and complexity, combining a natural disaster with sociopolitical, economic and hospitality demand crises ( Zenker and Kock, 2020 ). To address this complex situation properly, tourism industry research must help managers implement crisis recovery and response strategies, with a view to providing valuable knowledge to inform and foster crisis-enabled transformations in the industry (e.g. Garrido-Moreno et al. , 2021 ; Romao, 2020 ; Sigala, 2020 ).

Development and implementation of crisis guidelines are essential to facilitate tourism’s recovery from negative events ( Kim et al. , 2005 ). The importance of post-crisis recovery in terms of a health issue has been discussed in the academic literature, and in terms of the COVID-19 pandemic, there is a greater emphasis on how to respond to such situations (e.g.  Garrido-Moreno et al. , 2021 ). Table 1 summarizes the main results of studies on health crisis management in major tourism journals (ordered chronologically), and recent studies of crisis management in the COVID-19 scenario.

The contributions collated in Table 1 are focused on the study of strategies and actions from the perspective of companies. What is missing is a consideration of the behaviour of customers. It is essential to consider the perspective of customers about the effect that measures adopted by hotels have in the recovery of tourist activity to understand the degree to which procedures are successful ( Sigala, 2020 ; Polo-Peña et al. , 2023 ). There is little research that consider the client’s point of view during a crisis (e.g. Peco-Torres et al. , 2021 ).

Indeed, Gursoy and Chi (2020) underline the need for research that provides answers to critical questions such as, for example, what are the factors that will influence consumers’ intentions to resume their consumption of tourism services ( Wang et al. , 2020 ). In crises contexts, perceived risk is a key variable affecting the changes in consumer behaviour. Perceived risk “refers to the combined measurement of ‘perceived probability’ and ‘perceived consequences’ of a certain event or activity” ( Bubeck et al. , 2012 , p. 1483). The psychometric or “revealed preference approach” is the most influential paradigm in modelling and forecasting risk perceptions and acceptance ( Fischhoff et al. , 1978 ; Slovic, 1987 ). Following on from Volgger et al. (2021) , the key insights of this risk perception/acceptance framework have been used in this research to identify and test factors that help to mitigate tourists’ perceived risk and encourage them to travel again.

The psychometric model asserts that informed awareness of a risk and how prepared someone is can increase acceptance of the risk. In general, preparedness and awareness are usually associated with increased notions of control over the risk and increased trust in the managers of the risk ( Fischhoff et al. , 1978 ; Slovic, 1992 ). This also applies in the tourism context ( Volgger et al. , 2021 ). One important method of increasing perceived control over risks is the provision of information related to the sanitary conditions of the tourist destinations that they wish to visit.

In relation to the process of tourists searching for information, an essential link in the chain of the tourism sector with the ability to influence the decision-making process of tourists are OTAs ( Ku and Fan, 2009 ). OTAs have visibility in the global market. Their use is part of the information search process that potential tourists usually carry out before travelling. This makes OTAs, therefore, ideal for providing information on the health conditions of tourist destinations that reaches the entire market ( Wang and Lopez, 2020 ). Additionally, after a health crisis, OTAs need tourists to start to reuse their accommodation services again. For this to happen, they require the use of effective strategies to guarantee the safety of potential tourists ( Niewiadomski, 2020 ; Wang and Lopez, 2020 ). In periods of crisis, intermediaries, such as OTAs, must face episodes of greater uncertainty that contribute to potential tourists perceiving a more attractive offer ( Rodríguez et al. , 2015 ) and a reduction in the perceived risk of travelling to affected areas ( Menchero Sánchez, 2020 ).

Despite the fact that much has been written about OTAs, the value they offered and the effect on consumer behaviour in times of health crises (such as COVID-19) have not, however, been previously analyzed. In addition, the role of OTAs and their use in contributing to the recovery of the tourism sector – by offering a higher perceived value and generating a greater intention to return to tourist accommodation services – have also not been assessed.

The effect of perceived value of the offer provided by online tourist intermediaries

The conceptual proposal made by Zeithaml (1988 , p. 14) defines perceived value as “the overall assessment of the utility of a product based on the perceptions of what is received and what is given”. As the perceived value construct reflects customers’ evaluations of the offer, it is considered to be the greatest indicator of key variables of customer behaviour (e.g.  Gallarza and Gil, 2006 ; Polo-Peña et al. , 2012 ).

There are numerous articles that have studied the effects of perceived value on consumer behaviour. In relation to the tourist context, the empirical studies carried out show the effect of perceived value on variables such as satisfaction ( Choe and Kim, 2019 ), trust ( Bonsón et al. , 2015 ), repurchase intention ( Choe and Kim, 2019 ) or consumer loyalty ( Chang and Wang, 2011 ). While in the online context, there is also evidence of the positive effects of perceived value on web user satisfaction ( Chen and Lin, 2019 ; Chang and Wang, 2011 ), trust ( Kim et al. , 2011 ), intention to use ( Li and Shang, 2020 ), the intention to continue using ( Yang et al. , 2018 ), the intention to purchase ( Talwar et al. , 2020 ), or repurchase ( Bonsón et al. , 2015 ; Droguett et al. , 2010 ), or consumer loyalty ( Karjaluoto et al. , 2019 ; Sabiote-Ortiz et al. , 2014 ). In addition, Talwar et al. (2020) found a positive relationship between functional value (perceived value dimension) and the intention to book accommodation through OTAs ( Talwar et al. , 2020 ).

The perceived value of OTAs in a health crisis situation has a positive and significant effect on the intention to reuse their services.

Effects of the quality of information about a destination’s health situation offered by online travel agencies

The new trends in the search for well-being and greater commitment to public health, in addition to the increase in tourists’ knowledge and the information available to them ( De la Puente Pacheco, 2015 ), materialize in the search for health information as a planning action prior to embarking on a trip. In exceptional situations, like a health crisis, tourists consider that it is necessary to spend time searching for security information as an antecedent to the decision of choosing a destination ( Wang and Lopez, 2020 ). This means that tourist intermediary agents must develop communication based on messages that provide effective reassurance to those who are willing to travel ( Liu-Lastres et al. , 2019 ).

In accordance with previous crises faced by the tourism sector in recent years, the development of appropriate messaging is crucial to develop travellers’ positive perceptions about travel and destinations. This, in turn, can influence behaviour during trips, or in the phase prior to the purchase decision. When it comes to public health, the content of the messages promoted is educational in an effort to protect the public from diseases ( Liu-Lastres et al. , 2019 ), and it is well-established that the said information must be of good quality. Cheung et al. (2008) describe the quality of information within the online context. They emphasize its effectiveness as a factor to be taken into account in the adoption of information by the electronic user. In turn, the quality of the information is also part of the advantageous features offered by virtual communities ( Mellinas et al. , 2016 ).

Research that has analyzed how information quality can affect consumer behaviour in the online environment has drawn three main conclusions. Firstly, the quality of the information will facilitate the success of the tourist intermediary ( Matute Vallejo et al. , 2015 ). Secondly, this will serve to evaluate its potential ( Cheung et al. , 2008 ), and, by corollary, thirdly, the information quality would positively affect the value of purchases online, both for the functional and affective components ( Kim et al. , 2012 ).

The quality of the information about the health situation of the destination provided by the OTAs in a health crisis situation has a positive and significant effect on the perceived value.

However, studies by, for example, Matute Vallejo et al. (2015) provide empirical evidence of the effect of the quality of information as an antecedent to intention to repurchase online (through the perceived usefulness of the web), so that when the client perceives quality in the information that the online seller displays on its website, the client would be predisposed to continue acquiring the services of the same seller. This leads to the study of the effect that the quality of the information provided by the OTAs, related to the sanitary conditions of the destination, can have on a consumer’s intention to reuse OTA services during a health crisis.

The quality of information about the health situation of the destination provided by the OTAs in a health crisis situation has a positive and significant effect on the intention to reuse their services.

Figure 1 shows the proposed research model.

Methodology

Research population and sample.

The research was conducted in 2020 in Spain, at a time when there was still a heightened awareness and concern about the risks related to COVID-19. The study of the effect of the quality of the information on COVID-19 provided by OTAs required that a representative OTA of the sector be selected, and, in addition, provide information about the sanitary conditions of the tourist destinations. This led to Booking.com being selected as the OTA of reference for the development of the research. Booking.com has been the leading OTA in the market for several years ( Balagué et al. , 2016 ; Lorenzo Padilla, 2017 ). It has also incorporated, as part of its services, information regarding the sanitary conditions of tourist destinations for its users. As in the cases of Liu et al. (2020) and Sánchez-Cañizares et al. (2021) , a convenience sample was obtained, with data collected for the empirical analysis by means of a self-administered questionnaire. The sample population consists of residents in Spain, who may potentially be travellers in the short/medium term within the environment created by the virus and with previous experience in the use of OTAs. The link to the survey was shared on social networks and travel forums for Spaniards.

A total of 394 responses were received. The distribution of the sample is similar to the structure of the population of domestic tourists in Spain (e.g. Sánchez-Cañizares et al. , 2021 ) in terms of gender (49.6% men and 50.4% women) and age (16% aged 18 and 24 years; 53.6% aged 25 and 39 years, and 30.4% from 40 years).

Questionnaire and measurement scales

The questionnaire consisted of two different parts: the first includes filter questions about information regarding the health situation of the tourist destination given by an OTA ( Booking.com ). The second part included the measurement scales of variables used in the research model and the sociodemographic and psychographic profiles of the respondent.

First, the respondent was consulted about the place within Spain they would like to visit.

Second, the respondent is informed that they are to be provided with information from the OTA referring to the destination that the respondent had indicated that they wished to travel to and that this would be displayed for at least 80 s.

The information provided adopted a format like the one used by Booking.com in Spain. This information included two images with information about the sanitary conditions of the tourist destination to which they wanted to travel.

The second part of the questionnaire included the measurement scales of the variables collected in the research model ( Appendix ). Specifically, the “perceived value of OTAs in a health crisis situation” variable is measured based on the scales proposed in the literature such as, for example, by Choe and Kim (2019) , Lee et al. (2015) , Lin and Huang (2012) , Mohd Suki (2016) and Talwar et al. (2020) . The Quality of the health information of the destination variable is made up of four items adapted from Bailey and Pearson (1983) and Hur et al. (2017) , both are examples of applied research in the field of social networks and online media. The intention to reuse the OTAs’ services variable is made up of three items adapted from Matute Vallejo et al. ’s (2015) , study that analyzes the characteristics of word of mouth in the electronic context and its impact on online repurchase intention.

In addition, the variable previous image of the OTA ( Drolet et al. , 2007 ; Keppel, 1991 ), which although is not part of the research model, is included as a control variable that corrects the possible bias that can be introduced in the assessment of the relationships established between the variables analyzed.

The items of the measurement scales included Likert-type items from 1 to 7 points, with 1 being “totally disagree” and 7 “totally agree”, except for the previous image of the OTA scale that was a semantic differential.

Finally, the sociodemographic and psychographic variables of the respondents were collected.

Analysis strategy

The research model used ( Figure 1 ) shows the relationships included in the hypotheses. It is suggested that destination-related health information influences perceived value and intention to reuse OTA services, and that perceived value influences intention to reuse OTA services. Additionally, the “previous image of the OTA” variable was included as a control variable that acts on the “perceived value of OTAs in a health crisis situation” and the “intention to reuse the OTAs’ services” as a mechanism to correct the possible bias that can be introduced in the assessment of the relationships established between the variables analyzed based on the previous image of Booking.com held by the respondents in the study.

The structural equation modelling (SEM) methodology was deemed the most appropriate, given that the research model includes latent variables that are not directly observable ( Hair et al. , 2018 , pp. 541–591). SEM is a multivariate analysis technique widely used for this type of test, and it brings together methodological techniques that have been perfected over time and developed in various disciplines ( Hair et al. , 2018 , pp. 541–591). SPSS 21 and AMOS 21 data analysis software were therefore used to examine descriptive statistics and the factor structure of the proposed scales, and the hypotheses were tested using SEM. SEM allowed us to perform validation tests on the measurement scales (which requires adequate reliability and validity of the scales) and then test the relationships between the variables of the research model (to provide empirical evidence in relation to the research hypotheses proposed).

First, the psychometric properties of the proposed model were estimated and evaluated. Since the multivariate normality test of the variables included in the proposed model proved significant, the estimation was conducted using the maximum likelihood model combined with the bootstrap methodology ( Yuan and Hayashi, 2003 ). Even applying this technique, the Chi-square value remained significant. The fact that the results of the Chi-square were significant was due to its being sensitive to sample size. In this case, a valid reference was the value of Normed Chi-square, which gave a value of 1.86 – within the limits recommended in the literature. As for the overall fit of the model, the RMSEA value was (0.07). The incremental fit measures of CFI (0.91), IFI (0.92) and TLI (0.91) were also found to be adequate. Thus, the model fit can be said to be acceptable in line with the recommendations of Hair et al. (2018) .

Evaluating scale reliability and validity

The dimensions included in the research variables (“perceived value of OTAs in a health crisis situation”, “quality of the health information of the destination”, “intention to reuse the OTAs’ services” and “previous image of the OTA”) reflect the composition of the scales when their validity and reliability can be confirmed ( Devlin et al. , 1993 ). To achieve this, the standardized charges, the individual reliability coefficient ( R 2 ), the confidence interval and the significance of each one of the items included must be analyzed ( Table 2 ). The reliability indicators show a value greater or close to the minimum acceptable limit which is 0.50 ( Hair et al. , 2018 ). The next step is to verify the internal consistency of each one of the dimensions on the first-order and second-order scales. Consistency can be measured with composite reliability and variance extracted. In both cases, the values obtained are acceptable, as they are close to or above the reference value of 0.70 for composite reliability and 0.50 in the case of variance extracted ( Hair et al. , 2018 ) ( Table 2 ). The results obtained to date lead to the conclusion that the set of first-order dimensions proposed to measure perceived value – quality information, OTA services reuse intention and previous image is valid – given that it allows the existence of adequate validity and reliability to be confirmed.

As regards second-order construct, Table 2 shows the standardized charges, individual reliability, confidence intervals, and the level of significance for each of the first-order dimensions included, as well as for the composite reliability and variance extracted for second-order construct. It can be seen that the scale for perceived value offers individual reliability levels above or close to 0.50. That is, with the exception of the social dimension which show a value lower than the recommended levels are not removed from the model. This is because their removal does not significantly improve the overall fit of the model and can adversely affect the validity of the content ( Hair et al. , 2018 ). Similarly, overall these results contribute to determining that the second-order scale referring to perceived value has a high level of internal consistency.

Finally, the discriminant validity was assessed among the different variables and dimensions included in the research model. For this, the method proposed by Anderson and Gerbing (1988) is used according to which, for there to be adequate discriminant validity, the confidence interval of the estimated correlation coefficient must not include the value “1”. The results achieved in relation to the measurement scales used in the study indicate that the scales are adequate for measuring each of the variables included in the research model ( Table 3 ).

Taken together, the results show that the measurement scales used for the variables of perceived value, quality information, OTA services reuse intention and previous image provide adequate convergent and discriminant validity.

Evaluating the research model

Returning to the proposed research model, it is necessary to consider the effect that the previous image of the OTA exerts as a control variable. The previous image of the OTA does not have a significant effect on the perceived value (since the standardized load is 0.14, with a p -value ≥0.05). It does, however, on the intention to reuse the OTAs’ services with a p -value ≤1% (with a standardized load of 0.29). These results show the adequacy of having considered the previous image of the OTA variable as a control variable, since it has allowed bias correction introduced in the research model.

Next, the relationships between information quality, perceived value of OTAs and OTA services reuse intention with the current health crisis conditions were analyzed ( Figure 2 ):

Hypothesis 1 proposed that perceived value of OTAs in a health crisis situation has a positive and significant effect on OTA services reuse intention with the conditions of the health crisis. The results showed a statistically significant relationship between the two variables ( p -value≤ 0.01). The direct effect was 0.60, with a confidence interval of between 0.39 and 0.77. Thus, there is empirical support for this hypothesis.

Hypothesis 2 proposes that quality of the health information of the destination has a positive and significant influence on perceived value of OTAs in a health crisis situation. The results showed a statistically significant relationship ( p -value≤ 0.01), with a direct effect of 0.51 and a confidence interval of between 0.33 and 0.65. Therefore, this hypothesis also finds empirical support.

Hypothesis 3 proposed that quality of the health information of the destination has a positive and significant effect on the OTA services reuse intention with the conditions of the health crisis. The results showed a non-statistically significant relationship between the two variables ( p -value = 0.37). The standardized coefficient was 0.09, with a confidence interval of between −0.07 and 0.26. Thus, there is no empirical support for this hypothesis.

Discussion, conclusions and implications

The COVID-19 global pandemic had profound impacts on the travel and tourism industry. Similarly, future scenarios cannot be discounted ( Ivanova et al. , 2021 ; Li et al. , 2022 ; Magno and Cassia, 2022 ). Further, the COVID-19 pandemic generated conditions that allowed the sector to identify actions and strategies that can contribute to achieving greater resilience ( Kumar et al. , 2022 ; Li et al. , 2022 ).

In this paper, we have considered the development of the study of crisis management before and during the pandemic. The systematic review made it possible to identify an interest in obtaining greater knowledge about the use of market mechanisms and strategies, and their effects on consumer behaviour (e.g. Berbekova et al. , 2021 ; Li et al. , 2022 ; Wut et al. , 2021 ). Chen et al. (2022) found that although previous epidemic research has foregrounded consumers’ perceptions of risk and associated changes to their travel behaviour, potential strategies for ameliorating such behavioural changes while maintaining safety and security have mainly been ignored. Such strategies should not simply be applied, but preferably carefully measured by researchers for their impacts on consumers’ behaviour. This paper addresses this concern by offering original insights into whether providing quality information about the sanitary conditions of the destination influences the perceived value offered by OTAs and the reuse intention. It provides empirical evidence indicating that (1) providing quality information on the sanitary conditions of the destination influences the perceived value of the OTAs, but not the reuse intention; although, (2) the perceived value offered by the OTAs positively influences the OTA services reuse intention.

In accordance with emerging trends, such as a greater commitment to public health and a search for well-being ( De la Puente Pacheco, 2015 ), in times of crises and situations of uncertainty, tourists are increasingly searching for quality information that guarantees their safety during a trip ( Félix Mendoza et al. , 2020 ). The quality of the information must be present in the context of social networks and, even more so, in the offer of OTAs ( Mellinas et al. , 2016 ). In the research for this paper, a strategy based on risk communication and guidelines has been proposed as prevention and protection instruments for tourists that can be implemented by tourist intermediaries. For this study, this information was explicitly included through the information quality variable ( Cheung et al. , 2008 ).

More knowledge is needed regarding the effect that the adoption of this type of action generates from the market perspective in key variables of consumer behaviour (e.g. Volgger et al. , 2021 ). From the “revealed preference approach” ( Fischhoff et al. , 1978 ; Slovic, 1987 ), this research gives empirical evidence about the effect of factors that affect the risk perception and the perceived control tourists exert on perceived value and the intention to resume using OTA services.

The findings of this research make several contributions to knowledge. Firstly, specialized literature on crisis management in the tourism and hospitality industry shows interest in knowing more about the use of market-oriented actions and their impacts on consumer behaviour (e.g. Wut et al. , 2021 ; Li et al. , 2022 ). Also, Chen et al. (2022) recognize that it is necessary to develop a greater knowledge about consumers’ perceptions of risk and associated changes to their travel behaviour and how taking action can contribute to ameliorating the reuse and value of services when travelling while maintaining safety and security.

Specifically, the findings make several contributions to knowledge. There is previous literature examining the quality of health information about a destination and the subsequent effects on the perceived value in the online tourism context. For example, Cheung et al. (2008) test the influence of the quality of the information on the perceived usefulness of the user in the electronic field and Kim et al. (2012) show how information quality would positively affect the value of online purchases, on utilitarian and hedonic dimensions. The first contribution to knowledge is that the results achieved in this work mainly concur with the findings of previous research, showing that the quality of the health information of the destination has a positive influence on the perceived value of the OTA. This corroborates that when the tourist receives quality information about the situation of a health crisis at tourist destinations this, in turn, attributes a greater value to the offer proposed by the OTA.

Previous studies have identified the influence of information quality as an antecedent of the intention to repurchase online, through the influence of the perceived usefulness of the website (e.g. Matute Vallejo et al. , 2015 ), but the direct relationship between the quality of the health information of the destination and the intention to repurchase from the same OTA has not been analyzed. In this work, this relationship has been tested empirically, reaching a result according to which there is no direct significant relationship between the quality of the information related to the health situation of the destination and the OTA services reuse intention. It can be deduced from this that an improvement in the quality of information perceived by tourists would not directly influence their desire to book through the OTA’s platform. The second contribution to knowledge is that these results indicate that in situations of high uncertainty, such as a health crisis, providing quality information about the health conditions of the tourist destination is not enough to encourage potential tourists to book again through OTAs.

Lastly, it has been found that perceived value of OTAs in a health crisis situation positively and significantly influences the OTA services reuse intention in the context of a health crisis. This result is consistent with the empirical evidence of previous research, and shows that an improvement in the value perceived by the tourist of the OTAs offer would have a positive and significant impact on a tourist’s desire to travel, even in the context of a health crisis.

Considering all the results about the relationships established between the variables of quality of the health information of the destination, perceived value of OTAs in a health crisis situation and OTA services reuse intention, it can be suggested that providing quality health information about the destination is a necessary strategy because it contributes to the higher value potential tourists attribute to the offer provided by OTAs. This is not enough, however, to arouse the OTA services reuse intention (and consequently to travel). In order to incentivize the OTA services reuse intention, it is necessary to consider quality health information together with the perceived value of its offer, which does influence the intention to make repeat reservations with the OTAs.

Implications for practitioners

Some of the results of this research have practical and professional applications for tourist and hospitality intermediaries that operate online.

Recommendations can be made about the application of strategic measures appropriate to the development of the offer presented by OTAs and other tourist intermediaries. As an appropriate measure that OTAs can take advantage of to deal with tourism crises, the development and implementation of a risk and crisis communication strategy aimed at potential tourists stand out with the conviction that the perceived risk of travelling will be reduced and the security perceived by the individual in the tourist destination will be increased. At the same time, this measure must be based on quality information. In other words, it is suggested that providing quality information regarding the health situation of the tourist destination is essential information that should be incorporated into the portals of OTAs and other tourist intermediaries. To this end, in the preparation of the said information, OTAs should consult specialized organizations dedicated to studying the health crisis situation, and government institutions to provide reliable and consistent information.

The results from the research model support the idea that the actions of OTAs could contribute to awakening the desire to travel. In view of the fact that intermediary agents have the opportunity to play a relevant role in the recovery of tourist activity, these intermediaries, in addition to providing their own information and that of official government guidelines, also provide official and verified information on their web portals.

However, it has been shown that without an increase in the value of the OTAs’ offer to their users, the strategy based on the provision of quality information on the health situation of the destination is not enough to encourage the intention of the reuse of the OTAs’ services and make reservations for accommodation. In this sense, the results identify that transmitting offer of high perceived value – in which a convenience, social, emotional and epistemic value is contemplated – is key to encouraging the intention to make reservations again through the OTAs.

Taken together, the results show that the adoption of an adequate strategy by OTAs can influence the reuse intention and book accommodation, and therefore, return to travel in a pandemic context. For this, the incorporation of quality information on the sanitary conditions of the destination and transmitting offer of high perceived value is relevant.

Limitations and future research directions

Like all empirical research, this work has limitations that must be considered and, in turn, contribute to recommendations for future research. The first limitation relates to the study context. The study was carried out in the immediate aftermath of the COVID-19 pandemic in the Spanish domestic market. In this respect, it can only act as a “snapshot”, small case study about the unfolding situation. Thus, the first recommendation for further research is to replicate this study in other geographical contexts, and the second is to extend the sample to the international market.

A second limitation is the choice of variables. Although variables relevant to consumer behaviour were selected, there are other relevant variables in contexts of high uncertainty and market strategies. Future research should consider other relevant variables for consumer behaviour, such as risk or perceived safety or the value of user-generated content provided by OTAs. It is also interesting that for future research, more complex research models are tested in which a greater number of variables typical of consumer behaviour and the relationships between them are included. Despite these limitations, if, as predicted, the world faces health emergencies in the future, any knowledge about how the market can respond to support the tourism sector’s recovery is of value.

Another potential line of scholarly inquiry would be to include in the research model other characteristics, or qualities, about the individual respondents that may influence their perceived risk, such as self-efficacy, in addition to considering alternative business strategies that may influence the consumer to perceive a lower risk and decide to return to using an OTA’s services.

Research model proposed

Outline of results from the proposed research model

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Source(s): Own elaboration from literature review

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Acknowledgements

This work was supported by the por la Consejería de Universidad, Investigación e Innovación de la Junta de Andalucía y por FEDER, Una manera de Hacer Europa (Research Project A-SEJ-462-UGR20).

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Online Travel Booking Trends During the Pandemic

Executive summary, overall booking trends, online booking site share shifts, u.s. online travel share in airlines and hotels, u.s. traveler planning habits, related reports.

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Report Overview

This report looks at how online travel booking habits changed during the pandemic and how these behaviors will continue to evolve. Since February 2020, Skift has been regularly surveying 1,000+ Americans about their travel behaviors first on a monthly, and then a bi-monthly basis. The topline results of these surveys are published as our U.S. Travel Tracker . However, we ask more granular travel questions that have not been published previously.

This report teases out specific insights around which channels Americans use to book their hotels and flights. With this data we can see how direct bookings changed during the pandemic and whether it has reverted to pre-crisis trends. We can also look at specific booking site market share shifts and investigate whether the trip planning process shifted.

What You'll Learn From This Report

• How did the pandemic impact direct bookings and are these trends still in place?
• How has online travel agency market share shifted since 2020 in the U.S.?
• Did the pandemic change Americans’ trip planning process?

Using new data from our survey of American travelers we find that online travel booking trends are in flux. The early pandemic drove a wave of direct bookings, likely spurred by safety fears, customer service concerns around cancellations, and a lack of trust that third-parties could provide up-to-the minute in-destination information. 

However, we see mounting evidence that these first-party gains may not be durable. As financial concerns loom larger over trust and safety, our surveys show more shoppers reverting to third-party bookings, likely as they seek out discounts and comparison shopping to find the best value. 

Our survey data also hints at changes in the U.S. online travel agency landscape. Expedia Group’s multi-brand strategy makes it the largest family of booking sites in the U.S. by a wide margin. But their dominance is being challenged by aggressive investment from Booking.com and new challenger brands like Hopper.com and HotelTonight. 

Despite the many shifts happening in online travel bookings, we see little evidence that the online travel planning toolset changed much. Online search and word of mouth recommendations remain the most important sources of travel planning (but not inspiration!) by far. This has been the case for the last three years since 2020 and throughout the pandemic.

Let’s start with the big picture. Skift Research asked U.S. travelers which channels they used to book their hotels and flights. We tagged all channels as either direct or third-party and then aggregated activity across both hotel and flight bookings. 

This gives us our broadest look into how travel direct booking has been trending. We find it is on the decline after a peak early on in the pandemic, although more than half of all transactions still come direct. 

According to our survey results, 64% of U.S. flight and hotel bookings came direct in 2020.. This fell to 61% in 2021 and to 57% in 2022. 

We can rechart this to examine how the trend evolved over time. We exclude 2020 data here as it was too volatile at the monthly level with such limited travel activity taking place. What we see in the time series is that direct bookings peaked in early 2021 and quickly fell off into summer and fall 2021. 

We suspect that it is no coincidence that this quick fall-off in direct bookings coincides with the rapid return of mass travel in the U.S. as vaccines became widely available and international locations began to re-open. 

Let’s split this aggregate data into its two component travel products: Airlines and Hotels. Individually the broad direction of the trend is the same and since the summer of 2022, both hotels and airlines have been operating at parity in terms of direct booking share. However, Airlines fell farther, coming from a high of 70%+ direct bookings down to 57%, today.

Our best guess for this divergence is flight vouchers issued in the wake of mass cancellations in 2020. Online booking sites struggled to handle these future flight credits and we suspect most consumers rebooked directly. This would explain why Airline direct bookings remained elevated throughout all of 2021 even as Hotels fell. It would also neatly fit with the rapid decline of airline direct bookings in Summer 2022 as that is around the same time we began anecdotally hearing that consumers had used up many of their outstanding travel credits. 

After a mostly stable 2022, in both hotels and airlines, we see a small dip in the most recent reading from December 2022. It is still too early to tell if this is the start of another, larger, leg down or just a blip. But overall, what we see is a strong decline in direct bookings as we get further out from the heart of the pandemic.

This is consistent with our ongoing thesis around online travel built on the core that the pandemic was a crisis of trust and not of finances. We believe that consumers have higher confidence in both the travel product and the customer experience they will receive when they book direct. This is even more so in the case of booking branded travel experiences. But staying within a brand ecosystem limits the consumers’ ability to shop around for deals. Comparison shopping is the strong suit of the online booking platforms while their ability to control the end product experience and to resolve customer service issues is limited by their nature as third parties.

Skift Research believes that online travel booking sites stumbled in the early phases of the recovery because consumers didn’t trust that these brands could deliver on the very specific and safety-conscious experiences they were seeking. Consumers were also skeptical of third parties’ ability to provide real-time updates as to what amenities and activities were available in both properties and destinations. Plus, consumers were flush with savings from the pandemic and held branded travel vouchers. 

All of this drove a strong direct booking push that benefited travel supplier brands. To wit, in 2020, just 9% of American travelers told Skift that they had booked a trip because of discounts being offered. Trust and safety far outweighed financial concerns. That share of travelers remained mostly unchanged in 2021, rising to 11% of travelers incentivized by discounts. 

However, our last two surveys, conducted in October and December of 2022, mark a potentially significant shift in this trend. Most recently, 18% of respondents told us that discounts proved effective in driving their travel booking decision in December 2022, a six point share shift versus December 2021. 

When paired with the broad lifting of COVID restrictions, rising prices due to inflation, and growing recessionary fears, we think the stage is set for a change in sentiment among the U.S. traveling public. We may be moving from a regime where trust and safety are the top priority to one where price is king. If not yet broad based, we suspect this change is rapidly taking place in certain demographics, especially in the more midscale and economy chain scales. 

Let’s focus in on inflation which we think is rapidly supplanting COVID-19 as the top concern impacting travel for the American public. The below chart shows how lodging and airfare prices have increased relative to 2019. While this is not the traditional way an economist would display inflation, we think that benchmarking the numbers against 2019 helps visualize the gut reactions that many consumers feel when looking to book travel today and comparing it in their minds eye against their last pre-COVID trip.

As of January 2023, lodging prices were up 15% relative to the same period in 2019. Air fares were 6% higher, though note the summer spike when tickets were briefly 27% pricier than the same time in 2019. Broad U.S. inflation along the same methodology was actually 16% above 2019 levels. This means that in inflation adjusted terms, both hotels and airlines are still cheaper relative to 2019. But consumers struggle to think in real (inflation adjusted) price terms and instead see nominal price changes. Plus, broad inflation hurts the wallet just as well. When groceries and fuel prices go up, consumers have less to spend on travel, even if they can recognize that hotel price increases have lagged broader price changes. 

Our travel tracker survey says that inflation is already impacting traveler decisions. A majority of respondents told us that they had altered their travel plans due to rising prices. The most common decisions made were to take an alternative form of transport rather than flying and to pick a less expensive destination. We also saw nearly a third of respondents indicated that they had shopped around to pick a less expensive flight or hotel. 

This ties directly into our thesis on brand value growing in importance relative to brand trust. We see evidence that discounts are becoming more effective and we suspect hotels and airlines alike will increasingly need to compete on price. This would undermine the current situation where brands have held the line on pricing power and much revenue growth is being driven by rising yields. It would also play straight into the hands of the online travel agencies which excel at comparison shopping and are strongly associated with value pricing. 

Even if an individual brand is not discounting, online travel agencies help consumers find properties within a market that are offering below market rates or else help them discover well-reviewed ‘trade-downs’ into lower price scales in the same market.

This narrative is consistent with the direct booking data that we are receiving from our travel tracking survey. If correct, it suggests that the high direct booking rates may have been a pandemic-only event and that we are on track to return to a more competitive mix of channel booking shares. Ultimately, we see this as a positive tailwind for online travel agencies. 

With the trend shifting in favor of third-party bookings, let’s examine what specific booking sites American travelers told Skift they used. 

We asked travelers to tell us if they booked either their flights or hotels via one of 16 specific online travel sites. Of these, three brands were owned by Booking Holdings (Booking.com, Priceline, and Agoda) while six were owned by Expedia Group (Expedia.com, Hotels.com, Orbitz, Hotwire, Travelocity, and Cheaptickets.com). Alternative accommodations were not included in these survey questions and so Airbnb and Vrbo.com are excluded from our data. Bear in mind that, as sample sizes in our survey get smaller at this granular level, these results likely don’t represent true market shares. But we believe this is still useful data to help us understand the order of magnitude of differences across brands and how trends in their relative positions are changing.

What we find is that Expedia Group is overwhelmingly the most popular family of booking sites used in the United States. In 2022, our survey suggested that 49% of airline or hotel bookings made on OTAs were done via one of the Expedia Groups’ brands. That is nearly double the share of its rival competitor, Booking Holdings. 

But it is not all smooth sailing for Expedia Group. Although it remains the largest family of brands in the U.S., our data suggests a worrying trend that these sites are ceding market share. In our data, Expedia Group websites saw a ten point share decline, falling from 59% of OTA bookings in 2020 to 49% in 2022. 

Looking at individual websites and brands rather than at the parent company level gives us a bit more insight into the puts and takes of what is happening here. However, we again caution that as sample sizes get thin here, this data can be helpful in drawing an informed thesis about what is happening in the market, but it is not a conclusive market share.

We asked respondents to tell us what site they used when booking a flight or hotel. This data was then aggregated by year, and each site was ranked. This lets us come to a more nuanced conclusion about how consumer usage of OTA brands is evolving.  

Right off the bat, the most shocking result is that, in our survey data, Booking.com surpassed Expedia.com as the most used booking site in the U.S. in 2022. Expedia.com had been number one in 2020 and 2021 with Booking.com in second place. 

We should note here that this finding does not tie out with web traffic data from SimilarWeb that ranks Expedia.com above Booking.com. But then again, SimilarWeb only measures web traffic and not actual bookings. It is possible that Booking.com has a better conversion rate of lookers to bookers as compared to  Expedia.com.

Nonetheless, we think it is unlikely that Booking.com truly overtook Expedia.com in 2022 in the U.S. But we do think that this data captures a very real surge in momentum that Booking.com experienced in North America because of its increased strategic focus on this region. Also, it seems that Booking.com’s U.S. push cannibalized bookings from Priceline. Priceline fell from a fourth place ranking in 2021 to sixth in 2022. This explains why market share at the parent company level for Booking Holdings didn’t budge last year.

It also emphasizes the importance of Expedia Groups multi-brand strategy. Expedia.com goes toe-to-toe with booking.com and both have similar usage amongst our survey respondents. But Booking Holdings has a weaker bench, and traction for Priceline and Agoda is slim. Expedia Group, on the other hand, owned four out of the five top brands in the U.S. in our survey. This is how the parent company has such greater U.S. share in aggregate than its European rival. 

This also explains why Expedia Group has been so reluctant to abandon its multi-brand strategy . It has good reason to fear that it could lose market share  by shutting down its smaller brands. But despite these valid concerns, a multi-brand strategy may face challenges in a future where Google continues to grow at the expense of other metasearch sites and where travel supplier brands consolidate and push direct loyalty. 

If Booking Holdings kept its overall share the same, then who stole Expedia Group’s market share since 2020? Our survey suggests a number of emerging competitors that are growing in the U.S. Each is small individually but add up to a notable market share shift in aggregate. Independent Lastminute.com and Airbnb-owned HotelTonight both have climbed our rankings since 2020. But the most dramatic was Hopper.com.

Hopper has rapidly risen as a new and formidable competitor in the online travel space. We only began including Hopper.com as a specific booking site in May 2022 (before that respondents would’ve included it in the “other” category) but it immediately shot up our ranking to become the seventh most popular OTA in our survey. 

Hopper proves that it is still possible to grow as a challenger brand in the U.S. online travel market, which many have long assumed to be fully saturated. Hopper has employed unique tactics like the development use of new fintech products and a heavy dose of user gamification a la Chinese social media apps. 

We can slice the booking site data for our survey by product type. The decline in Expedia Group market share and the rise of new OTA competitors is most pronounced in the market for hotels. In the market for flights, Expedia Groups’ share has remained consistently higher, unsurprising since booking.com sells few flights. 

Skift Research asked respondents to tell us what tools and sources they used when planning a trip. We provided 13 different options. The most popular choices were online search, recommendations from friends and family, and travel review websites like Tripadvisor. 

We wanted to test a theory that the pandemic pushed Americans to do more of their travel planning online. To do this, we categorized each of our options into either an online or offline source and aggregated them. 

Did these travel planning patterns change much because of the pandemic? Short answer: no. 

Note that percentages add to greater than 100% as most respondents use multiple travel planning sources. Online travel planning source usage has remained mostly consistent since 2020 and the same is true for offline sources. 

In fact, when we dig into the numbers, we saw few major changes in travel planning source usage. There were some small changes. The sources that saw higher usage in 2022 over 2020 were online travel publications, online metasearch sites, travel books, and traditional travel. This was offset by a moderate decline in recommendations from friends and families and online search.

Note however, that because respondents can select multiple answers here, the percentages don’t add up to 100% and the percent shifts don’t net out to zero. With the gains in sources outweighing declines, it seems that Americans simply added more research sources into their travel planning process rather than swap out one source for another. This makes sense in the context of a more complicated travel landscape during and after the pandemic. 

Let’s wrap up this report by returning to our three original core questions and try to answer them. 

How did the pandemic impact direct bookings and are these trends still in place? The pandemic drove a large bump in direct bookings traffic to hotel and airline suppliers. The pandemic created a trust, safety, and customer service crisis that online booking third-parties struggled to overcome. As we increasingly put the pandemic in the rearview mirror and instead financial concerns take center stage, third-party bookings are returning. However, more than half of all bookings in our survey still come direct to suppliers. 

How has online booking site market share shifted since 2020 in the U.S.? Expedia Group was, and remains the largest family of online booking sites in the United States. But it seems to have lost some market share during the pandemic. Booking.com grew as it heavily invested in a U.S. presence but our data suggests that Priceline declined for an overall neutral impact on Booking Holdings corporate. Instead most of the market shares during the pandemic flowed to OTA challenger brands, most notably Hopper, but also HotelTonight and Lastminute.com.

Did the pandemic change Americans’ trip planning process? Not really. Our survey data suggests that travel planning habits remained mostly static during the pandemic. Americans are turning to more information sources than in the past, but these new sources are incremental and not replacing previous modes of planning. There was little shift in preference for online vs. offline travel planning sources.

— Skift Senior Research Analyst Varsha Arora contributed to this report.

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The Pros and Cons of Booking Through Online Travel Agencies

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You’re likely already familiar with online travel agencies, even if you don’t travel often. These companies — such as Priceline , Expedia and Orbitz — act as intermediaries between you and a travel provider.

Booking your travel through an OTA can be a good idea in some circumstances, but you’ll want to be wary of its pitfalls. Let’s take a look at the pros and cons of online travel agencies, so you’ll know what to use to book your next vacation.

Pros of booking through online travel agencies

There are certainly advantages booking through online travel agencies, though you’ll find different experiences whether you’re using public OTAs — such as Kayak — or private ones like those offered by your card issuer, such as the Chase's travel portal .

✅ It may be cheaper

When searching for flights online, you may see different prices for the same routes that vary across websites. Although it may be a result of fare type — for example, some search results may not clarify that a fare is basic economy rather than main cabin or economy — other times, the difference comes down to competition for your business.

Online travel services will often offer slightly lower prices on flights in an effort to entice you as a customer. This is true for both hotels and airlines.

» Learn more: Best credit cards for online travel-booking websites

✅ It can earn you more rewards

Have you ever heard of shopping portals ? By logging into a shopping portal, you can earn rewards for purchases made with many online merchants. Some hotel chains, such as Hilton , Marriott and IHG , can be accessed through shopping portals while still booking directly on the hotel website. In this way, you can earn rewards with the hotel directly as well as with the shopping portal.

The same isn’t true for shopping portals and most airline sites. However, many public online travel agencies are accessible through shopping portals, which can then earn you rewards for airfare bookings. By opting to book in this way, you’ll be able to earn points or cash-back rewards through the shopping portal that you’d otherwise miss.

Some card issuers will also reward you heavily when using their online travel services. Clear examples of this can be seen with Capital One and Chase. With the Capital One Venture X Rewards Credit Card , for example, you’ll get 10 miles per dollar spent on hotels and rental cars booked through Capital One Travel .

The Chase Sapphire Reserve® is similar. With this card, you can get 10 Ultimate Rewards® points per dollar spent on hotels and rental cars booked through Chase's portal.

While these numbers are high, it’s important to remember that there are trade-offs when booking through an OTA rather than directly with a hotel or airline. We’ll get into that a little later.

Online travel agencies offered by your card issuer may not feature the same prices as booking directly; you’ll want to compare these before committing to a purchase.

Some card issuers will go so far as to give your points more value when redeeming through their online travel agencies.

This is true with the Chase Sapphire Preferred® Card . When redeeming points on Chase's travel portal, you’ll get 1.25 cents in value per point rather than 1 cent elsewhere.

» Learn more: How much are your airline miles and hotel points worth this year?

Cons of booking through online travel agencies

There are several downsides when it comes to using online travel services for booking travel. It mainly comes down to the fact that travel providers prefer that you book directly with them — and offer more perks to woo your business.

❌ It can be harder to change a booking

Ever needed to change a flight after it's booked? No matter the reason, attempting to alter or otherwise cancel a flight can be a hassle — especially if you’ve booked through a third party.

Generally speaking, rather than offering you direct assistance, both hotels and airlines will recommend you contact the online travel agency you’ve booked with in order to make any changes.

While you may be able to make changes or get refunds with the travel agency, airlines and hotels can — and will — offer much more flexibility when you’ve booked with them directly. You may also be subject to additional fees charged by the online travel agency, which can erase any savings you’ve received.

❌ You may not receive elite benefits

This is the real kicker for anyone wanting elite status. Although airlines will almost always recognize your elite status and allow you to earn miles even for bookings made through an online travel agency, hotels and rental car companies will not.

This is especially important for hotel chains. Earning elite status with hotels generally relies on elite night credits. Although these can be earned in a variety of ways — including having complimentary status by holding certain credit cards — the main method of acquiring elite night credits is by spending nights in hotels. Rooms booked through an online travel agency do not count toward elite status as elite night credits.

Additionally, you will not receive any of the benefits of your existing elite status if your booking is through a third party. This can mean the loss of perks such as room upgrades, complimentary breakfast and even free Wi-Fi.

» Learn more: The best airline and hotel rewards loyalty programs this year

❌ It may be more expensive

Did you know that many hotel chains have best price guarantees? Hyatt, Hilton, Marriott and IHG all have a guarantee that’ll give you either points or a discount if you find a better rate elsewhere.

These guarantees are generous; Hilton, for example, will match the rate and then discount it by a further 25%.

Although you’ll need to file claims for these guarantees and they face limitations — such as a 24-hour window from when you made the booking — you can save a lot of money on your stay if your request is approved.

Online travel agencies can be hit or miss

There are two sides to every coin and this is no different, as there are several benefits and limitations of online travel services. Depending on your needs and loyalty program status, you’ll want to choose whether to book directly with a travel provider or rely on OTAs to do the job for you.

Booking travel through credit card portals from issuers like Chase and Capital One can earn you big rewards. But if you anticipate altering your travel plans or aim to earn elite status instead, booking directly is the way to go.

How to maximize your rewards

You want a travel credit card that prioritizes what’s important to you. Here are our picks for the best travel credit cards of 2024 , including those best for:

Flexibility, point transfers and a large bonus: Chase Sapphire Preferred® Card

No annual fee: Bank of America® Travel Rewards credit card

Flat-rate travel rewards: Capital One Venture Rewards Credit Card

Bonus travel rewards and high-end perks: Chase Sapphire Reserve®

Luxury perks: The Platinum Card® from American Express

Business travelers: Ink Business Preferred® Credit Card

on Chase's website

1x-5x 5x on travel purchased through Chase Travel℠, 3x on dining, select streaming services and online groceries, 2x on all other travel purchases, 1x on all other purchases.

60,000 Earn 60,000 bonus points after you spend $4,000 on purchases in the first 3 months from account opening. That's $750 when you redeem through Chase Travel℠.

1.5%-6.5% Enjoy 6.5% cash back on travel purchased through Chase Travel; 4.5% cash back on drugstore purchases and dining at restaurants, including takeout and eligible delivery service, and 3% on all other purchases (on up to $20,000 spent in the first year). After your first year or $20,000 spent, enjoy 5% cash back on travel purchased through Chase Travel, 3% cash back on drugstore purchases and dining at restaurants, including takeout and eligible delivery service, and unlimited 1.5% cash back on all other purchases.

$300 Earn an additional 1.5% cash back on everything you buy (on up to $20,000 spent in the first year) - worth up to $300 cash back!

on Capital One's website

2x-5x Earn unlimited 2X miles on every purchase, every day. Earn 5X miles on hotels and rental cars booked through Capital One Travel, where you'll get Capital One's best prices on thousands of trip options.

75,000 Enjoy a one-time bonus of 75,000 miles once you spend $4,000 on purchases within 3 months from account opening, equal to $750 in travel.

The Complete Guide to Booking Travel Online

What is an online travel agency, and what are the best sites and apps to use to search for hotels and flights we break it all down for you..

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There’s a lot to navigate when researching and booking travel online.

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My first travel adventure was to Venezuela. I booked the ticket with a travel agent over a pay phone. The agent searched a dozen flight itineraries over a few days, all so I could save $15.

Times have changed. Today, flight searches start online , often on your mobile device. Passengers book either directly with the airline or hotel or with online travel agencies. Rarely do we get on the phone. In fact, American Airlines and United Airlines charge $25 to make a domestic flight booking by phone. And pay phones hardly exist anymore.

So, what is the best way to book online? Here is our complete guide to online travel agencies, search tools, and the variety of booking options available on both mobile devices and desktops.

What is an OTA?

An online travel agency, or OTA, is a website or mobile app that allows users to search for and book travel services such as flights, hotels, car rentals, cruises, and activities. The booking is made directly with the online travel agency but confirmed by the service provider, such as an airline or a hotel. As a customer, your relationship is with the OTA.

What are the main OTAs?

Many online travel agencies nowadays are owned by two main companies: Expedia and Priceline. The Expedia Group is the largest online travel agency in the United States with 70 percent market share, according to travel data firm Phocuswright. Expedia Group operates Expedia.com , Orbitz, Hotels.com , Trivago, CheapTickets , Hotwire , Vrbo , and Travelocity .

Priceline is a major competitor to Expedia, with global revenues larger than the Expedia Group. The company owns Priceline.com, Booking.com, Cheapflights, Momondo, and Kayak—the latter two being metasearch engines (more on that below).

There are also independent newcomers such as Hopper (a mobile-only booking tool) and Kiwi.com (which allows you to book flights on air carriers that don’t normally have a commercial relationship).

Are OTA fares lower than booking directly?

Generally, no. The fares that are displayed by an OTA will be similar if not slightly more expensive when compared to an airline’s website. They’re usually only a few dollars higher or lower. The OTAs charge a booking fee to the airlines, and often that fee is passed directly to consumers. For example, Lufthansa tacks on an additional $18 to any booking made through an OTA for Lufthansa flights. The same flights are exactly $18 cheaper on the airline’s website.

Where you can score a good travel deal through an OTA is when booking a last-minute hotel and flight package. Many OTAs have cut agreements with airlines allowing last-minute travelers to access lower rates than are typically available when passengers book a flight alone.

Are all airlines available to be booked through OTAs?

No. Many OTAs do not display flights from some of the low-fare leaders. For example, Southwest and Allegiant flights are not available through OTAs; the same goes for Ryanair in Europe. And, earlier this year United Airlines threatened to pull out of Expedia altogether, only recently signing a multi-year agreement to stay in. The airlines would rather not lose any margin to online travel agencies in an already low-margin industry and would rather maintain a direct relationship with the customer.

Are smaller OTAs safe to use?

Expedia and Priceline are the two largest players in the online booking space, but there are dozens of independent OTAs, such as CheapOAir, OneTravel, JustFly, and SmartFares. Confusingly, you might actually stumble on ads for these OTAs while using Expedia or Priceline sites. That’s because the larger OTAs earn revenue through advertising, sending passengers to smaller OTAs and charging those OTAs for the favor.

Buyer beware: some of these lesser-known OTAs are masters at hidden fees. For example, a flight search on JetBlue allows for free seat selection in many instances. If you perform the same search on FlightNetwork, an independent OTA, and select a seat, you will be charged an additional $25—despite the fact that JetBlue doesn’t charge a seat selection fee if you book directly.

What if you need to change your itinerary?

Itinerary changes are often a pain. If your plans change, it won’t matter whether you’ve booked directly with an airline or with an OTA—you’re going to pay fees for the privilege, if you can even change your ticket at all.

For example, CheapTickets.com, which is part of the Expedia Group, charges $25 to change or cancel a ticket if that change is requested after 24 hours of making the booking—it is free if you do so within 24 hours of booking. However, the fees go up from there. JustFly, an independent OTA, charges a $75 fee for changes to domestic flights in addition to airline change fees, plus the difference in fare, for tickets that can be changed. For an international trip, the fee rises to $200. That means to change an international flight with Delta (which charges a $100 change fee) booked through JustFly, you’ll be assessed $300 in fees, plus the difference in fare. At that rate, you may as well book a new flight. FlightNetwork indicates in its terms of service that changes may incur a change fee but doesn’t specify what those fees are. That hardly makes the few dollars you saved by booking with the OTA in the first place worth it.

What is an OTA price match policy?

To assure travelers that they are getting the lowest fare possible, many OTAs have a price match policy. The rules vary and so do the benefits.

For example, if you book with Orbitz and find a less expensive flight, car rental, or activity on any U.S.-based website within 24 hours of your booking, Orbitz will refund you the difference you paid. And it works: I have personally found a flight in the same class, on the same airline, for the same origin and destination cities, and requested Orbitz to refund the difference of around $35. Within a few weeks, I received a check in the mail. A similar program applies for CheapOAir, but there’s a catch—the price difference must be found on a major OTA such as Expedia or Travelocity.

Expedia has a particularly good price match policy, but you have to pay extra for it at the time of booking. Expedia offers the price match option as an add-on that costs between $5 and $30 when you book. With the price match applied, if the airfare on Expedia drops between 120 days of the flight and up to six hours before the flight, Expedia will automatically refund you the difference in fare. Unfortunately, fares generally do not drop substantially as the travel date approaches, so while this might give you peace of mind, it’s probably not worth the expense.

How do Google Flights and other travel metasearch engines work?

Frequent fliers are likely familiar with websites such as Google Flights, Kayak, Momondo, or Skyscanner. On these websites, passengers search on the site but are redirected to the service provider to complete the booking, such as an airline, rental car company, or hotel.

Metasearch started with a product called ITA Matrix, which is a tool for searching airfares online but not for actually booking online. ITA Matrix allows for multi-city searching, such as setting two different departure or arrival airports, and for offering a calendar view of fares for easier comparison. That company was acquired by Google in 2011, and savvy travelers swear by it to help find the least expensive fares online. Most consumers are more familiar with Google Flights, which has gained traction more recently not least because it has the benefit of being displayed first in search results on Google.

Metasearch engines receive distribution fees from the airlines for sending traffic to the supplier websites. There are no additional hidden fees for using a metasearch engine because you’re booking directly with the airline or hotel.

A major benefit of the metasearch engines is their price tracking tool, which lets users know whether the displayed fares are low, average, or high for the flight, allowing travelers to make a more informed decision on whether to book a flight or not . Google Flights and Kayak, for instance, both have price tracking tools.

Why not just book directly?

The airlines would definitely much rather you book directly with them. Over the past five years, they have gotten much better at marketing and selling their product directly to consumers online and through mobile sites and apps. But in the past, they weren’t so good at it. In fact, Delta, Northwest, United, American, and Continental got together to invest $145 million to launch Orbitz in 1999 to counter the threat from Expedia. Now Orbitz is owned by Expedia.

The airlines also try to encourage customers to book directly so that they can maintain a closer relationship with them. It allows carriers to connect bookings with loyalty programs and create special offers and discounts catered to individual passengers.

There is another benefit to booking directly. The U.S. Department of Transportation requires carriers to hold a reservation at the quoted fare for 24 hours without payment or allow a reservation to be cancelled within 24 hours without penalty, so long as the booking is made at least seven days before travel. The law applies, however, only to U.S. and foreign air carriers that have websites marketed to U.S. consumers. This means that, in theory, an online travel agency does not have to offer such a policy, although most OTAs do.

What are the options for booking on your mobile device?

Airlines and the major OTAs all have apps to help you book and manage your trip on your mobile device, but their functionality is lacking compared to these websites’ desktop editions. For example, Expedia’s app doesn’t allow you to view flights on a month-view calendar. Kayak has an app with more bells and whistles and a better user interface, including a month-view calendar with color-coded pricing. It also has a handy “augmented reality” function to help you see if your carry-on bag will fit in the overhead bin (a feature originally developed by KLM). Point your phone’s camera at the luggage, and it’ll give you the dimensions.

While apps are improving and gaining in popularity, you still might find it easier to locate the best deals on flights and hotels by using your desktop, where you can have multiple tabs open and have all the available search tools at your disposal. Apps are fine for booking directly with an airline once you know which flights you want to book.

If you’re determined to use your mobile device, you may want to look into Hopper. Hopper is a mobile-first flight booking tool that has a solid price prediction tool. You can research travel options and book directly on the app. Another benefit of Hopper: Of its team of 300 employees, nearly half are dedicated to customer support and are based in Canada versus some OTAs and airlines that outsource much of their customer service further afield.

The bottom line?

Like many travelers, I enjoy a flight deal as much as the next person, but I also don’t like any added hassle. I typically start my travel searches using the ITA Matrix or Google Flights to get a general sense of the fares. It helps to know what is a good deal and what is expensive for a particular route. I do my research, typically on a desktop computer. When I’m ready to book, I’ll book directly with the airline. I’ve found that customer service is better when booking directly with the service provider. But I’ve also saved money by using OTAs and have booked with them, too. Whichever way you choose to book, you can be safe in the knowledge that finding and purchasing travel online is a lot easier today than searching for a deal with a travel agent on a pay phone.

>> Next: How to Get the Best Last-Minute Travel Deals

Pricing mechanism of variable opaque products for dual-channel online travel agencies

• S.I. : Information- Transparent Supply Chains
• Published: 14 July 2021
• Volume 329 , pages 901–930, ( 2023 )

Cite this article

• Zhaofang Mao 1 ,
• Ting Liu 1 &
• Xiaomei Li   ORCID: orcid.org/0000-0001-6981-0448 1  

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With the rapid development of e-commerce, an increasing number of online travel agencies (OTA) have combined traditional channels with opaque channels to maximise revenue, by implementing a price-discrimination strategy. Based on posted-price (PP) mechanism, this study reviews variable opaque products (VOPs) that allow travellers to change the opacity of an opaque channel to avoid unsatisfactory hotels. The purpose of the study is to determine how to optimise OTA revenue. Using a variation of the Hotelling model, this study examines the behaviour of travellers whose reservation values are relatively low. Additionally, we determine the optimal pricing strategy, which changes with the opacity of the opaque channel. The study shows that when the proportion of high-value travellers is low, OTA should decrease the price of transparent hotels; however, when the proportion is high, OTA should set a high price in the traditional channel, so that high-value travellers buy in the traditional channel, while low-value travellers buy in the opaque channel. And when the valuations differ greatly, OTA tend to increase the price of transparent hotels. Finally, when the number of travellers is constant, revenue increases when hotels increase, though there is an upper limit, and revenue decreases when the market expands. The results provide significant implications.

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Acknowledgements

The authors gratefully acknowledge editors and reviewers for their constructive comments. This paper is supported in part by research grants from National Natural Science Foundation of China (Project No.71872125).

The research is supported by the National Natural Science Foundation of China (Project No. 71872125).

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Appendix A: Proofs of the piecewise function when N is large

If there are N hotels, and N is even.

For one leisure-traveller who is located at x , \(0\le x\le \frac{\pi *D}{2N}\) , we obtain the following if no hotels are removed:

If the leisure-traveller removes one disliked hotel:

If the leisure-traveller removes two disliked hotels:

If the leisure-traveller removes three disliked hotels:

If the leisure-traveller removes four disliked hotels:

If the leisure-traveller removes five disliked hotels:

If the leisure-traveller removes six disliked hotels:

In conclusion, the general formula is given by

The calculation for an odd number of hotels is similar to when there is an even number of hotels; therefore, it is omitted here. The general formulas are symmetrical, whether the number of hotels is even or odd.□

Appendix B: Proofs of Proposition 1

Through Appendix A, we can find that the leisure-travellers’ valuation for the VOP with two hotels is \({\bar{V}}_{2}={V}_{L}-\frac{\pi {*}D}{2N}t\) \((0\le x\le \frac{\pi {*}D}{2N})\) , which would not be impacted by the position of leisure-travellers in the circle city; the valuation of the VOP with three hotels is \({\bar{V}}_{3}={V}_{L}-\frac{1}{3}xt-\frac{2\pi {*}D}{3N}t\) \((0\le x\le \frac{\pi {*}D}{2N})\) , which is decreasing in x. When \(x=0\) , \({\bar{V}}_{3}^{max}={V}_{L}-\frac{2\pi {*}D}{3N}t<{V}_{L}-\frac{\pi {*}D}{2N}t={\bar{V}}_{2}\) . The derivation process for the valuation of other VOPs is similar, i.e., \({\bar{V}}_{2}>{\bar{V}}_{n}^{max}\) , \(n\ge 3\) , that is, the leisure-travellers’ valuation of the VOP with two hotels is higher than any other type of VOPs. In order to maximize the revenue, the OTA will set the price for the VOP with two hotels as \({\bar{V}}_{2}\) , and set the price of each other type of VOPs higher than the corresponding highest valuation, in order to make the leisure-travellers give up buying other types of VOPs and only buy the two hotels left on OTA. Therefore, \({p}_{2}^{{*}}={V}_{L}-\frac{\pi {*}D}{2N}t\) , \({p}_{3}^{{*}}={V}_{L}-\frac{2\pi {*}D}{3N}t\) , \({p}_{4}^{{*}}>{V}_{L}-\frac{\pi {*}D}{N}t\) , \({p}_{5}^{{*}}={V}_{L}-\frac{6\pi {*}D}{5N}t\) , \({p}_{6}^{{*}}>{V}_{L}-\frac{3\pi {*}D}{2N}t\) , \({p}_{7}^{{*}}={V}_{L}-\frac{12\pi {*}D}{7N}t\) , \({p}_{8}^{{*}}>{V}_{L}-\frac{2\pi {*}D}{N}t\) , and so on.□

Appendix C: Proofs of Proposition 2

When \({p}_{1}\in \left[{V}_{L},{V}_{H}\right]\) , the optimal revenue is given by

When \({p}_{1}\in \left[{V}_{L}-\frac{\pi *D}{2N}t,{V}_{L}\right]\) , the revenue is derived by

The first order is as follows:

The second order is as follows:

Since \(\frac{{\partial }^{2}{{\Pi }}_{2}}{\partial {p}_{T}^{2}}<0\) , maximum revenue can be obtained when

Because \(0\le x\le \frac{\pi *D}{2N}\) , we can get that \( V_{L} - \frac{{\pi *D}}{{2N}}t \le p_{1} \le V_{L} ,{\text{~}}0 \le \rho \le \frac{1}{2} \) .

We obtain the optimal revenue

Then, \({\Delta }{\Pi }={{\Pi }}_{2}^{*}-{{\Pi }}_{1}^{*}\)

Taking the derivative of \({\Delta }{\Pi }\) with respect of \(\rho \)

We can conclude that \(\Delta {\Pi }\) is a decreasing function of \(\rho \) , when \(\rho =0,{\Delta }{\Pi }=\frac{\pi *{D}^{2}*t}{8N}>0\) . When \(\rho =\frac{1}{2},{\Delta }{\Pi }=\frac{D \left({V}_{L}-{V}_{H}\right)}{2}<0\) .

Therefore, there must be \(\bar{\rho }\in \left[0,\frac{1}{2}\right]\) ; when \(\rho {\epsilon }\left[0,\bar{\rho }\right]\) , \({\Delta }{\Pi }\ge 0\) , when \(\rho {\epsilon }\left[\bar{\rho },1\right]\) , \({\Delta }{\Pi }\le 0\) .□

Appendix D: Proofs of Corollary 4

From Case I and Case II, we can get that \({{\Pi }}_{1}^{D}={{\Pi }}_{1}^{*}={D*\rho *V}_{H}+D*\left(1-\rho \right)*\left({V}_{L}-\frac{\pi *D}{2N}t\right)\) , \({{\Pi }}_{2}^{D}={{\Pi }}_{2}^{*}=D*\rho *\left({V}_{L}-\frac{\pi *D}{4N}\left(\frac{1-2\rho }{1-\rho }\right)t\right)+\frac{2N*D*(1-\rho )}{\pi *D}\left(\left({V}_{L}-\frac{\pi *D}{4N}\left(\frac{1-2\rho }{1-\rho }\right)t\right)*\left(\frac{\pi *D}{4N}\left(\frac{1-2\rho }{1-\rho }\right)\right)+\left({V}_{L}-\frac{\pi *D}{2N}t\right)\left(\frac{\pi *D}{2N}-\left(\frac{\pi *D}{4N}\left(\frac{1-2\rho }{1-\rho }\right)\right)\right)\right)\) .

When the OTA only adopts the traditional channel, we can get the following piecewise revenue function

For \({{\Pi }}_{1}^{D}\) and \({{\Pi }}_{1}^{S}\) , as long as \({V}_{L}-\frac{\pi *D}{2N}t\ge 0\) is satisfied, the dual channel is always better than the single channel, and the closer \(\rho \) is to 1, the closer \({{\Pi }}_{1}^{S}\) is to \({{\Pi }}_{1}^{D}\) .

For \({{\Pi }}_{2}^{D}\) and \({{\Pi }}_{2}^{S}\) , \(\frac{\partial {{\Pi }}_{2}^{S}}{\partial {p}_{1}^{S}}=D*\rho +\frac{2N\left(1-\rho \right)}{\pi *t}\left({V}_{L}-2{p}_{1}^{S}\right)=0,{p}_{1}^{S}=\frac{1}{2}{V}_{L}+\frac{D*\rho *\pi *t}{4N*(1-\rho )}\) , \(\frac{{\partial }^{2}{{\Pi }}_{2}^{S}}{\partial {\left({p}_{1}^{S}\right)}^{2}}<0\) .

There are some leisure-travellers who will buy in the traditional channel, so \({p}_{1}^{S}<{V}_{L}\) , \({p}_{1}^{D}<{V}_{L}\) , \(\rho <\frac{1}{2}.\) In order to introduce the opaque channel, we must ensure that \({{V}}_{{L}}-\frac{\pi *D}{2N}{t}\ge 0\) . \({p}_{1}^{D}-{p}_{1}^{S}={V}_{L}-\frac{\pi *D}{4N}\left(\frac{1-2\rho }{1-\rho }\right)t-\left(\frac{1}{2}{V}_{L}+\frac{D*\rho *\pi *t}{4N*\left(1-\rho \right)}\right)=\frac{1}{2}{V}_{L}-\frac{\pi *D}{4N}t>0\) , so we can get \({p}_{T}^{S}<{p}_{T}^{D}<{V}_{L}\) . Because \(x\le \frac{\pi *D}{2N}\) , \(\frac{{V}_{L}-{p}_{1}^{S}}{t}\le \frac{\pi *D}{2N}\to \frac{1}{2}{V}_{L}+\frac{D*\rho *\pi *t}{4N*\left(1-\rho \right)}\ge {V}_{L}-\frac{\pi *D}{2N}t\) , so \(\rho \ge 1-\frac{\pi *D*t}{2{V}_{L}*N-\pi *D*t},\) \(1-\frac{\pi *D*t}{2{V}_{L}*N-\pi *D*t}<\frac{1}{2}\to {V}_{L}<\frac{3*\pi *D}{2N}t\) . When \({V}_{L}<\frac{3*\pi *D}{2N}t\) , the above proof results exist.□

\(\Delta {\Pi }={{\Pi }}_{2}^{D}-{{\Pi }}_{2}^{S}=D*\rho *{p}_{1}^{D}+\frac{2N*D*\left(1-\rho \right)}{\pi *D}\left({p}_{1}^{D}*\frac{{V}_{L}-{p}_{1}^{D}}{t}+\left({V}_{L}-\frac{\pi *D}{2N}t\right)\left(\frac{\pi *D}{2N}-\frac{{V}_{L}-{p}_{1}^{D}}{t}\right)\right)-\left(D*\rho {*p}_{1}^{S}+\frac{2N*D*\left(1-\rho \right)}{\pi *D}\frac{{V}_{L}-{p}_{1}^{S}}{t}{p}_{1}^{S}\right)=D*\rho *\left({p}_{1}^{D}-{p}_{1}^{S}\right)+\frac{2N*D*\left(1-\rho \right)}{\pi *D}\left(\frac{{V}_{L}}{t}\left({p}_{1}^{D}-{p}_{1}^{S}\right)-\frac{\left({p}_{1}^{D}-{p}_{1}^{S}\right)\left({p}_{1}^{D}+{p}_{1}^{S}\right)}{t}+\left({V}_{L}-\frac{\pi *D}{2N}t\right)\left(\frac{\pi *D}{2N}-\frac{{V}_{L}-{p}_{1}^{D}}{t}\right)\right)\) , \({p}_{1}^{D}-{p}_{1}^{S}=\frac{1}{2}{V}_{L}-\frac{\pi *D}{4N}t\) , \(\Delta {\Pi }=\left({V}_{L}-\frac{\pi *D*t}{2N}\right)\left(\frac{\pi *D*t*\left(3+2\rho \right)-3\rho *t+2N*{V}_{L}*\left(\rho -1\right)}{4\pi *t}\right)\) . We know that \({V}_{L}<\frac{3*\pi *D}{2N}t\) and \({V}_{L}-\frac{\pi *D}{2N}t>0\) from the above analysis, then we can derive that \(\rho >\frac{2N*{V}_{L}-3\pi *D*t}{2N*{V}_{L}+2\pi *D*t-3t}\) , so \(\Delta {\Pi }>0\) .□

Appendix E: Proofs of Proposition 3

From Appendix B we can get that \({\Delta }{\Pi }={{\Pi }}_{2}^{*}-{{\Pi }}_{1}^{*}\)

Then making \({\Delta }{\Pi }=0\) , it can be derived that \(\frac{1-2\bar{\rho }}{\bar{\rho }}\left(\frac{1-2\bar{\rho }}{1-\bar{\rho }}+\frac{2\bar{\rho }}{1-\bar{\rho }}-2\right)=\frac{8N*\left({V}_{L}-{V}_{H}\right)}{\pi *D*t}\) , \({\left(\bar{\rho }-\frac{1}{2}\right)}^{2}=\frac{2N\left({V}_{H}-{V}_{L}\right)}{8N\left({V}_{H}-{V}_{L}\right)+4\pi *D*t}\) , for \(\bar{\rho }\in \left[0,\frac{1}{2}\right]\) , so \(\frac{1}{2}-\bar{\rho }=\sqrt{\frac{2N\left({V}_{H}-{V}_{L}\right)}{8N\left({V}_{H}-{V}_{L}\right)+4\pi *D*t}}\) , \(\bar{\rho }=\frac{1}{2}-\sqrt{\frac{N\left({V}_{H}-{V}_{L}\right)}{4N\left({V}_{H}-{V}_{L}\right)+2\pi *D*t}}\) .□

Appendix F: Proofs of Proposition 5

We know that \({{\Pi }}_{1}^{*}={D*\rho *V}_{H}+D*\left(1-\rho \right)*\left({V}_{L}-\frac{\pi *D}{2N}t\right)\) in Sect. 4, \(\frac{\partial {{\Pi }}_{1}^{*}}{\partial D}=\rho *{V}_{H}+\left(1-\rho \right)*\left(1-\frac{\pi *D*t}{N}\right)\) , when \(D\le \frac{N}{\pi *t}*\left(1+\frac{\rho }{1-\rho }*{V}_{H}\right)\) , \(\frac{\partial {{\Pi }}_{1}^{*}}{\partial D}\ge 0\) , \({{\Pi }}_{1}^{*}\) increases in D ; while \(D>\frac{N}{\pi *t}*\left(1+\frac{\rho }{1-\rho }*{V}_{H}\right)\) , \(\frac{\partial {{\Pi }}_{1}^{*}}{\partial D}<0\) , \({{\Pi }}_{1}^{*}\) decreases in D , we know that the price in the opaque channel decreases in D , in order to get a positive price, we make \({p}_{2}^{*}={V}_{L}-\frac{\pi *D}{2N}t\ge 0, D\le \frac{2N*{V}_{L}}{\pi *t}.\) \({{\Pi }}_{2}^{*}=D*\rho *\left({V}_{L}-\frac{\pi *D}{4N}\left(\frac{1-2\rho }{1-\rho }\right)t\right)+\frac{2N*D*\left(1-\rho \right)}{\pi *D}\left(\left({V}_{L}-\frac{\pi *D}{4N}\left(\frac{1-2\rho }{1-\rho }\right)t\right)*\frac{\pi *D}{4N}\left(\frac{1-2\rho }{1-\rho }\right)+\left({V}_{L}-\frac{\pi *D}{2N}t\right)\left(\frac{\pi *D}{2N}-\frac{\pi *D}{4N}\left(\frac{1-2\rho }{1-\rho }\right)\right)\right)=D*\rho *\left({V}_{L}-\frac{\pi *D}{4N}\left(\frac{1-2\rho }{1-\rho }\right)t\right)+\left(\frac{D*\left(1-2\rho \right)}{2}*\left({V}_{L}-\frac{\pi *D*t*\left(1-2\rho \right)}{4N*\left(1-\rho \right)}\right)+\frac{D}{2}*\left({V}_{L}-\frac{\pi *D*t}{2N}\right)\right)=\frac{D}{2}*\left(2{V}_{L}-\frac{\pi *D*t*\left(2-3\rho \right)}{4N*\left(1-\rho \right)}\right)\) , \(\frac{\partial {{\Pi }}_{2}^{*}}{\partial D}={V}_{L}-\frac{\pi *D*t*\left(2-3\rho \right)}{4N\left(1-\rho \right)}\) , when \(D\le \frac{4N*{V}_{L}*\left(10\rho \right)}{\pi *t*\left(2-3\rho \right)}\) , \(\frac{\partial {{\Pi }}_{2}^{*}}{\partial D}\ge 0\) , \({{\Pi }}_{2}^{*}\) increases in D ; while \(D>\frac{4N*{V}_{L}*\left(10\rho \right)}{\pi *t*\left(2-3\rho \right)}\) , \(\frac{\partial {{\Pi }}_{2}^{*}}{\partial D}<0\) , \({{\Pi }}_{*}^{2}\) decreases in D . For positive price from both the traditional and opaque channel, we make \({p}_{1}^{*}\ge 0\) and \({p}_{2}^{*}\ge 0\) , \(D\le min\left(\frac{1-\rho }{1-2\rho }\frac{4N*{V}_{L}}{\pi *t}, \frac{2N*{V}_{L}}{\pi *t}\right)=\frac{2N*{V}_{L}}{\pi *t}.\) □

Appendix G: Proofs of Corollary 5

As the city circle expands, the number of travellers also increases proportionally, namely, the distribution density of leisure-travellers remains unchanged. Here, only the circular arc length is calculated, which is equivalent to the increase in the number of travellers. The superscript “+” represents the situation after the city circle expansion. \(\Delta {T}={\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{x}}^{+}-\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{x}=\frac{{V}_{L}-{p}_{1}^{+}}{t}-\frac{{V}_{L}-{p}_{1}}{t}=\frac{{V}_{L}-\frac{\pi *D*t*\left(1-2\rho \right)}{4N*\left(1-\rho \right)}-{V}_{L}+\frac{\pi *{D}^{+}*t*\left(1-2\rho \right)}{4N*\left(1-\rho \right)}}{t}=\frac{\pi *\left({D}^{+}-D\right)*\left(1-2\rho \right)}{4N*\left(1-\rho \right)}\) , and \(\Delta {O}=\frac{\pi *{D}^{+}}{2N}-\frac{\pi *D}{2N}-\left({\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{x}}^{+}-\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{x}\right)=\frac{\pi *\left({D}^{+}-D\right)}{4N}*\left(2-\frac{1-2\rho }{1-\rho }\right)=\frac{\pi *\left({D}^{+}-D\right)}{4N}*\left(\frac{1}{1-\rho }\right)\) , then \(\Delta {T}-\Delta {O}=\frac{\pi *\left({D}^{+}-D\right)}{4N}*\left(\frac{-2\rho }{1-\rho }\right)<0\) , therefore \(\Delta {T}<\Delta {O}\) , and \(\frac{\Delta {T}}{\Delta {O}}=1-2{\rho }\) .□

Appendix H: Proofs of Proposition 6

From the above analysis, \({{\Pi }}_{2}^{*}=\frac{{D}_{T}}{2}*\left(2{V}_{L}-\frac{\pi *D*t*\left(2-3\rho \right)}{4N*\left(1-\rho \right)}\right)\) , \(\frac{\partial {{\Pi }}_{2}^{*}}{\partial D}=-\frac{\pi *{D}_{T}*t*\left(2-3\rho \right)}{8N*\left(1-\rho \right)}<0\) , so \({{\Pi }}_{2}^{*}\) decreases in D .□

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Mao, Z., Liu, T. & Li, X. Pricing mechanism of variable opaque products for dual-channel online travel agencies. Ann Oper Res 329 , 901–930 (2023). https://doi.org/10.1007/s10479-021-04163-4

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DOI : https://doi.org/10.1007/s10479-021-04163-4

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Ads on the sidebar can be distracting

Find deals on airfare, hotels, and car rentals with an aggregator site like Skyscanner , which uses a metasearch engine to compare prices from all online travel agencies and the airline, hotel, or car rental company in question. Run searches with fixed dates, opt to compare airfare prices month to month, or click “Cheapest Month.” Searches also include options for nearby airports or non-stop flights only. With hotel searches, you can choose to select only from properties with free cancellation, a cleanliness rating of 4.5/5 or higher, or 3- or 4-starred hotels only. Car rental searches include an option to select “return car to different location.”

Once you’ve found the best rate, click on the link to be redirected to the third-party site to make your booking. Feeling spontaneous? The Search Everywhere button on the homepage offers a list of the cheapest flight deals for destinations both locally and across the world—just plug in your departure airport first.

Best Price Predictor : Hopper

The company claims a 95 percent accuracy rate at predicting when flights and hotel rates will be cheapest.

Color-coded system makes it easy to determine cheapest days to buy

App is easy to use

Option to track flights and receive alerts when the best time to buy arises

Some have mentioned the app functions better as a research tool than a booking tool

Unclear whether Hopper will price match if you find a cheaper flight elsewhere

Hopper is a travel app available on iOS and Android that aims to help travelers save on airfare by usng historical data and their own algorithm to predict when flights will be cheapest. Just type in where and when you’d like to fly and Hopper will present you with a color-coded pricing calendar indicating how much tickets are likely to cost. (Green is the least expensive, then yellow, orange, and red for most expensive.) Hopper will also recommend you either buy now or wait, or you can choose to watch a trip and receive notifications on the best time to buy. In addition, the app has expanded to offer hotel and car rental price predictions, too.

Some newer features since the app’s inception in 2009 include an option to freeze a price for a limited time—for an extra fee—as well as exclusive app-only discounts. Hopper is free to download, and you can choose to book directly through the app, though some users mentioned they use Hopper as more of a research tool before booking directly with the airline or hotel. The company claims a 95 percent accuracy rate at predicting flight rates up to a year ahead.

Most Innovative : Kiwi.com

This metasearch engine scours the web to piece together the ideal itinerary using planes, trains, buses, and more.

Creative itineraries get you where you need to go, especially if you’ve got a multi-stop trip

Kiwi Guarantee offers rebooking or cancellation protections

Nomad option appeals to travelers with a lot of flexibility

Creative itineraries mean you may not fly out of the same airport you flew into

Kiwi Guarantee has an additional fee

Charges all-in-one fee for booking flights, trains, buses (though you can always purchase a la carte)

Travelers planning multi-city destinations and seeking a bargain, as well as those looking to take planes, trains, and automobiles to get there, might consider Kiwi . Kiwi is a metasearch engine that scours and pieces together itineraries from various airlines (even if they don’t have a codeshare agreement), considers multiple airports (even if your arrival airport is different from departure), and offers booking options, whether you’re looking at very specific dates or more general ones (up to 60 nights).

Some will find the ability to make multiple bookings for a particular trip more convenient than going at it manually several different times, though note that you must opt into the Kiwi Guarantee program to access rebooking and refund protections should your reservation change or be canceled. Kiwi’s Nomad option allows you to plug in a bunch of destinations you’d like to visit and the length of your intended stay, and the website will churn out the most affordable itineraries for review.

Best for Eco-Conscious : Kind Traveler

A give-and-get business model means booking accommodations with exclusive perks, a donation to environmental organizations, and more.

All participating hotels include a local give-back component

Exclusive savings and perks

Participating hotels are located in some of the most beautiful places in the world

Inventory is much smaller compared to other booking platforms

Some of the amenities mentioned are based on availability only

In 2022, Kind Traveler (an online trave agency focused on hotel bookings) announced an increase in environmentally and socially conscious hotels, charity donations, voluntourism opportunities, and additional perks like waived resort fees or a welcome amenity.

Unlock exclusive hotel rates and perks from participating Kind Traveler hotels with a minimum $10/night minimum donation to a local charity. For example, stay at the Six Senses Laamu in the Maldives and receive up to $33 off the nightly rate and perks such as a food and beverage credit and an Earth Lab or Alchemy Bar workshop when you make a donation to Manta Trust. The organization funds coastal research to protect the island nation’s large yet fragile population of reef mantas.

Select from more than 140 participating hotels from the Hawaiian Islands to Bozeman, Montana, and the Maldives. Charities include wildlife, human rights, arts, education, and environmental preservation organizations.

Best for Social Impact : I Like Local

Choose from a host of travel experiences with the peace of mind that 100 percent of the cost goes directly to local partners.

Social impact mission woven into organization’s business model

Immersive experiences led by local guides

Range of experiences offered

May not be best fit for those seeking upscale, luxury experiences and stays

Can’t sort experiences by a list of countries (though an interactive map is available)

No experiences outside of Africa and Asia

For an online travel agency with a booking platform designed to route dollars spent directly to the communities travelers intend to visit, consider I Like Local . Visit the website to browse a host of travel experiences in countries including Indonesia, Kenya, and Cambodia. Experiences include homestays and farmstays as well as wellness and culturally oriented experiences—from cooking and cycling tours to weaving classes.

To search for an experience, select from drop-down items like travel dates and experience categories, or view a global map and click on a country to view experiences that way.

The platform got its start in 2014 and has grown to 4,000 local hosts across nearly 20 countries. As a social impact organization, 100 percent of each booking fee goes to local hosts. To date, 16,000 travelers have booked with I Like Local.

Best for Design-Forward Homestays : Plum Guide

Browse and book seriously vetted, design-forward vacation homes.

Highly curated inventory of vacation rentals across the world

Design-forward

Thorough vetting process

Does not publish guest reviews

Other platforms have homes available across more destinations

When it comes to booking a vacation home, serviced apartment, or condo, travelers are spoiled for choice. Plum Guide is an online travel agency that specializes in accommodations—though not just any home makes its directory. The company claims that each potential home listed on its site must jump through 150 hoops to be included, from internet speed and mattress and pillow quality to the showers’ water pressure and the home’s proximity to dining, shopping, and attractions.

Search by a featured collection on the website such as “ pet-friendly homes ” or “one-of-a-kind homes in Palm Springs.” Scroll to the bottom of its homepage to view its top destinations, as well as a list of all destinations where Plum Guide homes are available, including Barbados, Mexico, Portugal, Switzerland, the U.S., and Turkey. Note: From the top right-hand corner of the site, use the dropdown menu to select currency of choice.

As long as you know what you value most out of your travel experience—such as affordability, social impact, or luxe accommodations—there’s an online travel agency to help plan your next trip. Be sure to read the fine print, as some agencies are third-party websites and not direct vendors. If you're not sure where to start, Booking.com is your best bet for a smooth user experience and hard-to-beat offers on flights, hotels, and other travel arrangements.

What Is the Biggest Travel Agency?

Our choice for best overall, Booking.com, is known as an industry leader with listings for all major hotels, airlines, car rental companies, and more. It boasts more choices for accommodations per destination than any other site, and we found its interface to be user-friendly.

Are Online Travel Agencies Worth It?

This depends on your needs and priorities. The best online travel agencies certainly can save time by booking everything all at once. However, if you're someone who is good at haggling and enjoys the details of planning a trip, you might be able to find better deals by reaching out to hotels or other destinations and speaking to someone personally.

Is It Cheaper to Book Online Than With a Travel Agent?

Not always. A travel agent you know and trust should have the experience and connections to find deals that can match or surpass what you'll find online. Additionally, if something goes wrong, travel agents provide you with an actual person you can use as an advocate to correct the problem . But if you don't have access to a good travel agent, online sites still provide plenty of ways to streamline planning and save money .

We considered dozens of online travel agencies and narrowed down the options based on user experience, volume and quality of inventory, unique offerings and specials, and customer reviews. We also assessed travel companies’ environmentally and socially conscious policies.

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Press Release

ARPA-E Announces Innovation Agreement Outlining Vision for the Future of Electrified Airports at Technology Expo Hosted in San Antonio

Today, the U.S. Department of Energy (DOE) Advanced Research Projects Agency-Energy (ARPA-E), the City of San Antonio Aviation Department and City Public Service Board (CPS Energy), and the University of Texas at San Antonio (UTSA) signed a Memorandum of Understanding (MOU) outlining collective efforts to develop and promote technologies that include, but are not limited to, sustainable aviation, battery technologies and innovative battery storage solutions, enhanced electric vehicle (EV) charging, and power demand management technologies. This agreement marks the first time an international airport will work together with ARPA-E—DOE’s innovation arm—to accelerate the development and deployment of new energy technologies to decarbonize the aviation sector. ARPA-E Director Evelyn Wang, San Antonio Mayor Ron Nirenberg, UTSA President Dr. Taylor Eighmy, and CPS Energy Vice President of Customer Value Karma Nilsson were all present for the signing hosted at Stinson Municipal Airport in San Antonio. “We are excited at this opportunity to collaborate and showcase innovative energy technologies that could transform the future of aviation,” said ARPA-E Director Evelyn N. Wang. “Today’s MOU signing is a step in the right direction to ensuring that these innovative technologies are developed, built, and integrated in America. Our hope is that this partnership will lay the groundwork to enable future electrified airports.” “We are proud to be a part of this innovative initiative that will ultimately benefit the San Antonio community,” said Rudy D. Garza, President and CEO of CPS Energy. “CPS Energy continues to look for ways to participate in electrification projects, especially for critical public infrastructure like the San Antonio International Airport. Projects like these furthers our commitment to finding new and sustainable technologies to enable our growing community and we are excited about the opportunity to work with our community partners to do so.” “This is an important agreement with the potential to shape the aviation industry of the future,” said San Antonio Mayor Ron Nirenberg.  “Researching the decarbonization of aviation and finding new sustainable energy models is important work, and I am proud San Antonio will be playing a leading role in this cutting-edge research.” “This is a unique partnership designed to promote transformative energy technologies and it propels the City of San Antonio’s Aviation Department to the center of innovation,” said Jesus Saenz, Director of Airports, City of San Antonio Aviation Department. “This is an exciting time to be part of the Aviation Team and planning for the future of aviation and our airports.” “This collaborative effort is an incredible opportunity for UTSA to partner with strategic industry leaders in evaluating electric aircraft, advanced energy storage and micro-grid systems to advance the adoption of sustainable multi-modal transportation technologies,” said UTSA President Taylor Eighmy. “Together, this collective will accelerate discoveries that will positively impact the local and regional economies while advancing technologies that change the world.”

To mark this historic milestone, the following ARPA-E-funded project teams were also present to showcase their technologies and share how their innovations could be integrated into future electrified airports:

• Ampaire , who is setting new standards for sustainable air travel and eco-friendly transportation solutions, flew its cutting-edge hybrid electric EEL aircraft and  watch video of the aircraft here ;
• Imagen Energy showcased ultrafast, compact electric vehicle chargers delivering efficient and cost-effective power solutions;
• Natron Energy featured sodium-ion batteries that can safely store energy and efficiently deliver power on demand;
• AutoGrid discussed a distributed energy resource management system that can help grid operators manage energy supply and demand fluctuations; 
• Quidnet Energy brought a wellhead to illustrate a modular geomechanical pumped storage systems that can utilize existing natural resources to store renewable energy over long durations; and
• Texas A&M University Research Team  presented 3D-printed models of a motor and shared concepts for advancing efficiency in electric transportation. 

UTSA and CPS Energy also presented research to leverage a city-scale grid digital twin to evaluate operational efficacy, ensure seamless interoperability, fortify cybersecurity protocols, and assess performance metrics of electric/hybrid aircrafts.

The MOU signed today will enable collaboration to identify research, development, demonstration, and deployment opportunities that will promote sustainable aviation technologies.

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