Search results

In the era of new technological revolution, seeking to survive and guarantee business sustainability in their digital internationalization, enterprises choose to become environmentally oriented. The need for new green business models has become evident in recent years, and enterprises offer green services in creative and eco-friendly ways. However, does the display of a green label on hotels' websites really promote the eco-conscious tourists' online booking intention? This study aims to examine the impact of the perceived label on the online sustainable hotel booking intention of the eco-conscious tourists, using the foundations of signal theory.

This study adopted a structural equation model to integrate several constructs with a sample of 349 validated responses.

The empirical results highlight, the importance of the green label perception on the eco-conscious tourists' booking intention of online sustainable hotel and the role that green trust and green perceived risk play as a mediating variable between the perception of the exposed label and the booking intention. Indeed, when booking a sustainable hotel online, the tourists may be sensitive to the exposure of a green label. Therefore, this signal decreases the perceived risk of unsustainability and ultimately increases the trust in hotel's sustainability.

The first limitation is related to the sample employed in this study. Given that most of the participants were residents of France, the results of this study may not be generalized to the entire population. Secondly, a range of other factors can affect the eco-conscious tourists' intentions to book online a hotel with green label, such as their attitude, social media influence, tourists' satisfaction, etc. Indeed, other variables and/or signals could be adopted to study online booking intention in the pandemic era.

In light of these results, theoretical and managerial implications are discussed. The findings make an important contribution to SMEs sustainability and internationalization by exploring new ties. This study considers how SMEs and specifically hotels start following green practices (e.g. adoption of an eco-label) relevant to their international environment where they operate and in response to global pressures. SMEs can survive better in the highly competitive global environment where they need to employ more green practices, however, managers should consider how green trust and green perceived risk can affect customer behavior. It also adds to the existing literature by dealing with customer perceptions about the green label of sustainable hotels and its subsequent effect on booking intention.

This study had shown the importance of the display of green label on the eco-conscious tourist's online booking intention.

The primary purpose of this study was to examine the underlying consumer values that drive hotel booking mobile app users to engage more with the app and use the app continuously for hotel booking purposes.

By conducting confirmatory factor analysis (CFA) and structural equation modeling (SEM) on the data collected through the Qualtrics online survey platform from 506 respondents in the United States, the proposed measurements and structural models were tested.

The findings for both Generation Xers and Millennials revealed that hedonic and social values influenced mobile app engagement, which strongly influenced mobile app loyalty. Thus, to enhance customer engagement and indirectly influence mobile app loyalty, the app value delivery should appeal to social and hedonic values. Although the utilitarian values for using apps had a potential direct impact on mobile app loyalty, the mediation analysis showed that mobile app engagement, when connecting consumption values to mobile app loyalty, served as a full mediator for Generation Xers and a partial mediator for Millennials.

This study provides insights into how hotels and online travel agent (OTA) marketing managers may consider augmenting user engagement with hotel booking mobile apps. This study suggests that hoteliers and OTAs should further develop their user experience efforts to enhance the utilitarian features of their mobile app to increase revenue from repeat purchases. Additionally, this study provides implications for enhancing the hedonic and social features of hotel booking mobile apps to appeal to Millennials and Gen Xers.

This study developed and assessed an integrated model to investigate the relationships between consumption values, engagement and loyalty in hotel booking mobile apps. Furthermore, it examined generational cohorts' role in the relationships between these constructs.

This study aims to assess if the benefits outweigh the costs of participation in online travel agencies (OTAs) such as Booking.com.

A two-step system generalised method of moments estimation of a regression model of firm-level return on assets (ROA) is used on a dummy variable indicating whether a lodging facility participates in Booking.com. The assessment contained various control variables, including size, age, leverage, liquidity and lagged ROA. The moderating effect of firm age and size was studied by including interaction variables between the Booking.com dummy and age and size, respectively. The model was estimated using participation and financial data of 775 Belgian firms over a 20-year period (1999–2018).

The findings indicate that participation in Booking.com is associated with higher profitability, with this effect more economically important and pronounced for smaller hotel properties.

The study provides a broadly applicable empirical model to assess the impact of platform participation on the financial performance of tourism, hospitality or retail businesses.

The study provides empirical evidence that, from a transaction cost perspective, the benefits of participation in OTAs outweigh the costs, resulting in substantially higher profitability. The evidence can be used to justify the use of OTAs as distribution channels.

While prior studies have described and conceptually analysed the evolution and role of OTAs in the hotel sector, and speculated on the net effect of OTA participation, to the best of the authors’ knowledge, this is the first study to empirically assess whether OTA participation creates value for hotel owners and investors.

本文采用了两步系统GMM的估计方法, 用一个虚拟变量指示住宿设施是否参与了Booking.com, 以确定企业级别的资产回报率（ROA）的回归模型。评估涵盖了多种控制变量, 包括公司规模, 年限, 杠杆, 流动性和滞后资产回报率。企业年龄和规模的调节作用是通过加入Booking.com虚拟变量与年龄和规模之间的交互变量实现的。该模型是使用20年（1999–2018年）间775家比利时公司的参与和财务数据估算得出的。

本文目的是评估收益是否超过了参与Booking.com等在线旅行社（OTA）的成本。

研究结果表明, 参与Booking.com与更高的获利能力相关联。这种影响在经济上更加重要, 并且对于较小的酒店物业而言更为明显。

该研究提供了广泛适用的经验模型, 以评估平台参与对旅游业, 酒店业或零售业的财务绩效的影响。

该研究提供了重要的实证依据。从交易成本的角度来看, 参与OTA的收益大于成本, 从而大大提高了盈利能力。该实例证明了使用OTA作为分销渠道是合理的。

尽管先前的研究已经描述并从概念上分析了OTA在酒店领域的演变和作用, 并推测了OTA参与的净效应, 但据我们所知, 这是第一个凭经验评估OTA参与是否为酒店所有者和投资者创造价值的研究。

Una estimación GMM en dos pasos de un modelo de regresión del rendimiento de los activos (ROA) a nivel de empresa sobre una variable ficticia que indica si un establecimiento de alojamiento participa en Booking.com. La evaluación contenía diversas variables de control, como el tamaño, la edad, el apalancamiento, la liquidez y el ROA retardado. El efecto moderador de la edad y el tamaño de la empresa se estudió incluyendo variables de interacción entre la variable ficticia de Booking.com y la edad y el tamaño, respectivamente. El modelo se estimó utilizando datos de participación y financieros de 775 empresas belgas durante un periodo de 20 años (1999–2018).

Evaluar si los beneficios superan los costes de la participación en agencias de viajes online (OTAs) como Booking.com.

Los resultados indican que la participación en Booking.com está asociada a una mayor rentabilidad, siendo este efecto más importante y pronunciado desde el punto de vista económico para las propiedades hoteleras más pequeñas.

El estudio proporciona un modelo empírico ampliamente aplicable para evaluar el impacto de la participación en la plataforma en los resultados financieros de las empresas turísticas, hoteleras o minoristas.

El estudio proporciona pruebas empíricas de que, desde la perspectiva de los costes de transacción, los beneficios de la participación en las OTAs superan los costes, lo que se traduce en una rentabilidad sustancialmente mayor. Las pruebas pueden utilizarse para justificar el uso de las OTAs como canales de distribución.

Aunque estudios anteriores han descrito y analizado conceptualmente la evolución y el papel de las OTAs en el sector hotelero, y han especulado sobre el efecto neto de la participación en las OTAs, hasta donde sabemos, éste es el primero que evalúa empíricamente si la participación en las OTAs crea valor para los propietarios e inversores de hoteles.

This paper aims to examine the influences of the number of hotel management responses and especially the textual similarity in hotel management responses to online reviews on hotel online booking.

This study used the data from 437 hotels in New York City on Expedia. The data specifically include online reviews, management responses and real-time number of online hotel bookings, which were merged to create one dataset for this study. To calculate the management response similarity, three widely recognized text mining functions of calculating textual similarity were adopted in this model. Fixed-effect panel data model was then used to examine the influence of management response to consumer online reviews on online hotel booking volume.

The empirical results demonstrate that the number of management responses to consumer online reviews does not significantly affect hotel booking; compared to none or only one management response, or management responses with low similarity, management responses with high similarity can significantly reduce the hotel booking on Expedia.

This study suggests that the similarity of management responses influences customers’ hotel booking, and hotel managers should avoid providing too similar management responses.

First, this study, for the first time, proposes the concept of management response similarity and its measurement methods. Second, this study takes an initial attempt to empirically test the influence of response similarity on hotel booking by using secondary data online.

This study aims to investigate the effect of deepfake video advertisements on hotel booking intention by applying the media richness theory (MRT) and information manipulation theory (IMT).

A quantitative survey was conducted using a structured questionnaire to understand the effect of deepfake hotel video advertisements on booking intention. A large cross-section of 1,240 tourists was surveyed and data were analyzed with partial least squares structural equation modeling (PLS-SEM).

The outcome of this research provides the factors affecting the booking intention due to deepfake hotel video advertisements. These factors are media richness (MR), information manipulation (IM) tactics, perceived value (PV) and perceived trust (PT). Cognitive load and perceived deception (DC) negatively influence the hotel booking intention.

The distinctive model that emerged is insightful for senior executives and managers in the hospitality sector to understand the influence of deepfake video advertisements. This research provides the factors of hotel booking intention due to deepfake video advertisements, which are helpful for designers, developers, marketing managers and other stakeholders in the hotel industry.

MR and IMT are integrated with variables such as PT and PV to explore the tourists' hotel booking intention after watching deepfake video advertisements. It is the first step toward deepfake video advertisements and hotel booking intentions for tourists. It provides an empirically tested and validated robust theoretical model to understand the effect of deepfake video advertisements on hotel booking intention.

The importance of online reviews on online hotel booking has been widely acknowledged. However, not all online reviews affect consumers equally. Compared with common online reviews, key online reviews (KORs) have a greater influence on consumers' decisions and online hotel booking. This study takes the first step to investigate the factors affecting the identification of KORs and the role of KORs in online hotel booking.

To test the research hypotheses, this study develops a crawler to obtain 551,600 online reviews of 650 hotels in ten representative large cities in China. This study first uses a binary logistic regression to identify KORs by combining review content quality and reviewer characteristics and then uses a log-regression model to investigate the role of KORs in online hotel booking.

This study mined the factors affecting the identification of KORs by analyzing review contents and reviewer characteristics. Our results revealed that KORs play a mediating role in the effects of review content and reviewer characteristics on online hotel booking.

This study focuses on KORs, which have received limited attention in research but are important to practitioners. Specifically, this study investigates the antecedents and consequences of KORs. Our results enable hotel managers to manage online reviews effectively, particularly KORs.

The purpose of this study is to provide new insights into the factors that influence cancellation behaviour with respect to hotel bookings. The data are based on individual bookings drawn from a hotel reservation system database comprising nine hotels.

The determinants of cancellation probability are estimated using a probit model with cluster adjusted standard errors at the hotel level. Separate estimates are provided for rooms booked offline, through online travel agencies and through traditional travel agencies.

Evidence based on 233,000 bookings shows that the overall cancellation rate is 8 per cent. Cancellation rates are highest for online bookings (17 per cent), followed by offline bookings (12 per cent) and travel agency bookings (4 per cent). Probit estimations show that the probability of cancelling a booking is significantly higher for early bookings, large groups that book offline, offline bookings during high seasons, bookings not involving children and bookings made by guests from specific countries (e.g. China and Russia). Among the factors, booking lead time and country of residence play the largest role, particularly for online bookings.

The analysis is based on individual-level booking data from one hotel chain in Finland, and therefore cannot be generalised for the total population of hotels in the country under observation.

The main contribution of this paper is a thorough investigation of the factors that influence cancellation behaviour at both the theoretical and empirical levels. Detailed and unique data from a hotel reservation system allow for new empirical insights into this behaviour.

This study examined how marketer- and user-generated photographs jointly influence consumers' online hotel booking.

Viewing photographs as stimuli that influence consumers' online hotel booking, this study proposes a research model and validates that using one quasi-experiment.

The findings of this study provide some empirical insights. Marketers can release room- and scene-related photographs. Users can release product- and social-related photographs. The interaction between room-related photographs by marketers and product-related photographs by users can promote energetic arousal and dominance and then promote online booking intention. The interaction between scene-related photographs by marketers and social-related photographs by users can promote energetic arousal and dominance and then promote online booking intention. Pleasure, energetic arousal and dominance can positively influence the attitude toward photographs. Pleasure and energetic arousal can positively influence the attitude toward photographs and then positively influence booking intention. Dominance can positively influence booking intention.

The findings of this study reveal significant interaction effects between marketer- and user-generated photographs on consumers' online booking. The findings will help researchers and marketers better understand the impact of photographs on consumers' online hotel booking.

The purpose of this paper is to know which hotels mostly rely on Booking.com, investigating the level of presence on Booking.com around the world by country, hotel size, hotel category and managerial form. Neither the company nor the hotels provide this information, so the authors use the number of reviews as an indicator of estimated sales.

Data from 33,996 hotels worldwide are downloaded from Booking.com using a Web browser automatically controlled, developed in Python, that simulated a user navigation (clicks and selections). The comparison between independent hotels and hotels belonging to a chain is performed by a Student’s t distribution test and the comparison of hotel categories and hotel size is analyzed by a one-way ANOVA test.

The results show that three factors clearly influence the usage level of Booking.com: independent vs chain hotels, small vs large hotels and low vs high category hotels worldwide. The authors also observe that hotels from Europe are the ones that rely more on Booking.com.

The originality of this research is to identify the factors that make hotels to have a greater (lesser) dependence on Booking.com within each destination and geographical area. Moreover, the use of big data from hotels worldwide allows the authors to know the level of use of Booking.com in dozens of countries, especially those with the highest tourist activity. This work expands the capabilities of big data in the hospitality industry research, and with a simple ratio, this study counteracts the lack of public data on hotel sales through Booking.com. This new approach could be extended to the analysis of other online travel agencies (OTAs), which use similar review systems.

Studies show that internet has become a major force propelling growth in tourism sector in many countries. An appropriate diffusion of the information and communication technology (ICT) services can facilitate visibility of hotels and lodges on search sites and third-party booking websites and thus influence demand. It also helps leverage the use of social media for promotion and customer acquisition purposes. Recently, Myanmar, with impressive historical world heritage sites, is witnessing a tourist boom; more hotels are opening up and achieving competitive advantage by offering free internet connectivity to guests and locating their premises in the vicinity of an ICT infrastructure. The purpose of this paper is to investigate ICT readiness to support the lodging industry in Myanmar by focusing on one sub-index of the Network Readiness Index (NRI, a term heavily used by World Economic Forum). The paper focuses on the “Network Use” component of NRI, pertaining to the effect of the “quality of the Internet connection” available to lodges, and its association with the following dimensions: customer service: the availability of ICT services to guests, such as internet connectivity and availability of ATM in the vicinity; digital marketing: the use of social media, keeping records of guests and analyzing aggregate data to extract business insights; and business-to-business online booking: the use of online booking via major third-party intermediary websites like Expedia, Booking.com and Agoda.com.

Surveys were conducted in three major touristic cities in Myanmar: Bagan, Mandalay and the capital city, Nay Pyi Taw. A total of 101 valid questionnaires were used. Survey questions were centered around the following themes: internet connection problems, digital marketing activities, and online booking directly or via third party digital intermediary. The data are presented and interpreted by descriptive statistics and regression analysis.

Though, Myanmar is new to internet and commercial use of ICT, the awareness of the importance of leveraging social media and online booking for business development is surprisingly high in the lodging sector. On average, about 80 percent of surveyed hotels are present on the WWW through a dedicated hotel website. However, most websites lack an online booking capability. As a result, and due to a global trend, online booking through third-party intermediaries has become the dominant option for hotel booking arrangements in Myanmar. Agoda, founded in Bangkok in 2002, was found to be the number one choice for online booking intermediary in Myanmar, followed by Booking.com. Analysis of the logistic regression revealed that it was highly likely that areas around ATMs have better internet connectivity. As expected, it was also found that it is very unlikely that hotels reporting a problem in internet connectivity will be able to provide internet service to their guests. Despite the presence of problems in internet connectivity in Mandalay and Bagan cities, located away from the capital; most hotels in these cities resort to leveraging social media for promotion and customer/guest development. The analysis also revealed that cities located away from the capital are more aggressive in leverage online third-booking intermediaries.

While researchers were hoping for a higher participation rate in the survey, especially in the city of Mandalay, data collection was challenging, a number of hotels/lodges denied participation. This may have some implications on the generalization of results. However, over 70 and 45 percent of hotels/lodges in the capital city and the ancient city of Bagan, respectively, had participated in the survey.

Tourism has a great potential for growth in Myanmar. This research recommends ways to achieve and sustain competitive advantage for the lodging sector, which is vital for tourism.

Though a considerable research exists on tourism and the recent advances of the ICT sector in Myanmar, the country’s readiness for the actual usage of the internet for the development of tourism has not been specifically addressed. This paper explores this with compelling research findings useful for policy makers as well as players in the tourism sector.