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Article
Publication date: 13 July 2018

Eva Martin-Fuentes and Juan Pedro Mellinas

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…

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Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Tourism Review, vol. 73 no. 4
Type: Research Article
ISSN: 1660-5373

Keywords

Open Access
Article
Publication date: 31 March 2020

Eva Martin-Fuentes, Juan Pedro Mellinas and Eduardo Parra-Lopez

The purpose of this paper is to determine whether different scales and ways to collect reviews and ratings found on online travel agencies (OTAs) can affect hotels, and whether…

6785

Abstract

Purpose

The purpose of this paper is to determine whether different scales and ways to collect reviews and ratings found on online travel agencies (OTAs) can affect hotels, and whether hotels obtain the same or different evaluations.

Design/methodology/approach

Hotel ratings from five OTAs in four European markets were collected and compared in pairs. An initial comparison was made with the hotel scores of each OTA to show what a typical user would see. Then, a rescaled score (0-10) was used to compare all the OTA scales appropriately and to distinguish between what customers observe and what the reality is.

Findings

The results reveal that Booking.com that uses a scale (2.5-10) and Agoda with a scale (2-10) seem to give higher rating scores than Atrapalo (1-10), Travel Republic (0-10) and hotel reservation service (1-10). However, when the scores are rescaled (0-10), the worst ratings are found on Booking.com followed by Agoda.

Practical implications

OTAs should include, next to the scores, the scale used to rate hotels so as to provide users with better and clearer information. Moreover, rating questionnaires should match the verbal denominations with their numerical values to avoid biased ratings.

Social implications

OTAs and hotel managers are losing information provided by customers because customers are not aware of the scale when rating hotels. Moreover, hotel ratings are used by potential customers to obtain a clearer image of an establishment. However, if some hotels are being overrated by some scales, customers might have higher expectations, which may not be met.

Originality/value

The unique rating scales of Booking.com and Agoda provide additional insights into their hotel evaluations, which seem to be apparently higher when in fact they are not.

在线旅行评论评分量表及其对酒店得分和竞争力的影响

摘要

目的

这项研究旨在研究在线旅行社(OTA)上评论和评级的不同量表和方式是否会影响酒店获得的评估。

设计/方法/方法

本研究收集并比较了来自四个欧洲市场中五个OTA的酒店等级数据。研究首先对每个OTA的酒店得分进行了比较, 以显示一般用户会看到的内容。然后研究使用重新缩放的得分(0-10)来恰当地比较所有OTA的酒店等级, 并区分顾客观察到的内容和现实。

结果

结果显示, Booking.com使用的量表(2.5-10)和Agoda的量表(2-10), 似乎高于Atrapalo(1-10), Travel Republic(0-10)和 hotel reservation service (1-10)的评分。但是, 当分数重新调整为(0-10)时, 最差的评分是在Booking.com上, 其次是Agoda。

实际含义

OTA应在评分旁边注明用于对酒店进行评分的量表, 以便为用户提供更好, 更清晰的信息。此外, 评级问卷应使评价描述与其数值相匹配, 以避免评级出现偏差。

社会影响

OTA和酒店经理正在丢失客户所提供的信息, 因为客户在对酒店进行评级时并不了解其使用的量表。此外, 潜在客户使用酒店评级来获得更清晰的企业形象。但是, 如果某些酒店被某些网站的评级量表高估, 那么客户可能会有偏高的期望, 而这些期望可能无法被满足。

创意/价值

Booking.com和Agoda的独特评分等级标准为酒店提供了更多见解, 而实际上酒店的情况可能并非如此。

Las escalas de calificación de las opiniones de los viajes online y sus efectos en la valoración y competitividad de los hoteles.

Propósito

El objetivo de esta investigación es determinar si las diferentes escalas y formas de recopilar opiniones y valoraciones de las Agencias de Viajes Online (OTAs), pueden afectar a si los hoteles tienen las mismas o distintas calificaciones.

Diseño/metodología/enfoque

Las calificaciones de hoteles de cinco OTAs en cuatro mercados europeos, se recopilaron y compararon por pares. Se realizó una comparación inicial con las puntuaciones de los hoteles de cada OTA, para mostrar lo que vería un usuario típico. Luego, se utilizó una puntuación de reescalado (0-10), para comparar todas las escalas de las OTAs de manera apropiada y así poder diferenciar entre lo que los clientes observan y lo que es en realidad.

Resultados

Los resultados revelan que Booking.com, que utiliza una escala (2.5-10) y Agoda con una escala (2-10), parecen puntuar con calificaciones más altas que Atrapalo (1-10), Travel Republic (0-10) y hotel reservation service (1-10). Sin embargo, cuando se vuelven a escalar las puntuaciones (0-10), las peores calificaciones se encuentran en Booking.com, seguida de Agoda.

Implicaciones prácticas

Las OTAs deben incluir, junto a las puntuaciones, la escala utilizada para calificar los hoteles a fin de proporcionar a los usuarios una información mayor y más clara. Además, los cuestionarios de calificación deben hacer coincidir las denominaciones verbales con sus valores numéricos para evitar calificaciones sesgadas.

Implicaciones sociales

Por un lado las OTAs y los gerentes de hoteles, están perdiendo información proporcionada por los clientes, porque los clientes no son conscientes del tipo de escala utilizada cuando califican los hoteles. Por otro lado, los clientes potenciales utilizan las calificaciones de los hoteles para obtener una imagen más clara de un establecimiento. Por lo que en muchos casos, los clientes pueden tener expectativas más altas, que pueden no cumplirse, si los hoteles están siendo sobrevalorados por algunas escalas.

Originalidad/valor

Las escalas de calificación únicas de Booking.com y Agoda, brindan información adicional sobre las evaluaciones de sus hoteles que parecen ser aparentemente más altas cuando en realidad no lo son.

Article
Publication date: 15 September 2023

Juan Pedro Mellinas, Eva Martin-Fuentes and Berta Ferrer-Rosell

This research explores why tourists are dissatisfied in places considered “wonders of the world”. The authors ask if the place does not match visitors' expectations or if other…

Abstract

Purpose

This research explores why tourists are dissatisfied in places considered “wonders of the world”. The authors ask if the place does not match visitors' expectations or if other factors spoil the experience.

Design/methodology/approach

The authors analysed the lowest-rated reviews of these wonders on TripAdvisor. The authors identified the main causes of complaints and the problems tourists faced. The authors grouped the complaints into categories and used CoDa.

Findings

The results indicate that dissatisfaction does not stem from unmet expectations regarding the monument itself, but rather from other factors related to the quality of the tourist service.

Practical implications

The findings of this research can be implemented in those tourist spots that, despite their global popularity, have considerable proportions of unhappy visitors, not due to the attraction itself, but to shortcomings in its administration.

Originality/value

This study provides a deeper insight into the causes of complaints about some of the most renowned monuments, regarded as extraordinary places, where high satisfaction levels would be anticipated. It also contributes theoretically to the literature on customer complaints in tourist places.

Details

Journal of Hospitality and Tourism Insights, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9792

Keywords

Book part
Publication date: 4 November 2022

Juan Pedro Mellinas and Eva Martin-Fuentes

Millions of ratings and reviews about products are available on the Internet for free, and they are used by academic researchers in the tourism sector. Data from websites like…

Abstract

Millions of ratings and reviews about products are available on the Internet for free, and they are used by academic researchers in the tourism sector. Data from websites like TripAdvisor are replacing or complementing traditional questionnaires and interviews. The authors are proposing a methodology to estimate the percentage accounted for by the sample of self-interviewed individuals over the total study population, in order to calculate the reliability of the results obtained. Average percentages obtained for hotels cannot be easily generalized due to the high dispersion in participation rates among hotels, even in the same city. Participation levels for tourist attractions are substantially lower than those for hotels and are likely biased, due to the fact that some tourists evaluate places without actually visiting them, merely after viewing them from the outside.

Details

Advanced Research Methods in Hospitality and Tourism
Type: Book
ISBN: 978-1-80117-550-0

Keywords

Book part
Publication date: 8 November 2019

Eva Martin-Fuentes, Estela Marine-Roig, Eduard Cristobal-Fransi and Berta Ferrer-Rosell

This chapter analyzes the pricing policy of hybrid P2P lodgings versus traditional hotels in relation to seasonality. A quantitative comparative analysis of room prices in Airbnb…

Abstract

This chapter analyzes the pricing policy of hybrid P2P lodgings versus traditional hotels in relation to seasonality. A quantitative comparative analysis of room prices in Airbnb and hotel lodgings in the city of Barcelona was conducted across four different pairs or dates (peak versus low season) in one year. Overall, the study shows that Airbnb prices are significantly lower than those of hotels and that the former’s prices fluctuate very little, whereas hotels use yield or revenue management techniques to adjust prices in high and low seasons. This implies that relevant purchase behavioral changes may occur in terms of customers waiting until the last minute to book.

Details

Delivering Tourism Intelligence
Type: Book
ISBN: 978-1-78769-810-9

Keywords

Book part
Publication date: 8 November 2019

Philip L. Pearce and Hera Oktadiana

In this chapter, the analysis-action nexus will be addressed by reviewing studies from across the chapters. The broad themes covered have included governance and sustainability…

Abstract

In this chapter, the analysis-action nexus will be addressed by reviewing studies from across the chapters. The broad themes covered have included governance and sustainability, consumer benefits and experiences, and networking among entrepreneurs and associated opportunities. It is argued that addition to tourism intelligence often lies in improving communication, building trusted connections, and affirming local networks. A focus on the need for trust, the use of tools for insights, the value of identifying new trends, and understanding target markets, together with the usefulness of training and an appreciation of time, help smooth the journey along the long and winding road from analysis to action.

Details

Delivering Tourism Intelligence
Type: Book
ISBN: 978-1-78769-810-9

Keywords

Book part
Publication date: 8 November 2019

Abstract

Details

Delivering Tourism Intelligence
Type: Book
ISBN: 978-1-78769-810-9

Abstract

Details

Advanced Research Methods in Hospitality and Tourism
Type: Book
ISBN: 978-1-80117-550-0

Abstract

Details

Advanced Research Methods in Hospitality and Tourism
Type: Book
ISBN: 978-1-80117-550-0

Content available
Book part
Publication date: 4 November 2022

Abstract

Details

Advanced Research Methods in Hospitality and Tourism
Type: Book
ISBN: 978-1-80117-550-0

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