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Taiwan’s hotel industry was adversely impacted by the COVID-19 pandemic. This study aims to examine the effect of strategic choices by Taiwanese international tourist hotels before and during the pandemic environments.

A data envelopment analysis (DEA)-based Malmquist methodology is used in this study to provide a mechanism to assess Taiwanese hotel strategy performance. Changes in the productivity and performance of Taiwanese international tourist hotels were analyzed in the periods before and during the pandemic to uncover insights useful should a similar crisis occur in the future. Panel data were obtained from the annual report of international tourist hotels published by the Taiwan Tourism Bureau from 2017–2020. Two groups of hotels were analyzed in this study: city hotels and scenic hotels.

The findings of this study reveal that chain hotels tended to perform better than independent hotels in both city and scenic areas during the global pandemic. Specifically, the crisis caused a substantial decline in productivity and profitability for international tourist hotels in Taipei City during the COVID-19 period. Compared to city hotels, findings also indicate that most international tourist hotels in scenic areas were able to maintain better productivity, including larger-sized scenic hotels.

The DEA-based analysis provides unique and valuable insights for hotel firm leaders on how to better identify and make strategic choices when responding to future crises.

Focusing on two beer festivals held in Nottingham, England, this study aims to evaluate their indirect impact on the performance of city hotels. This study builds on theoretical insights from the revenue management literature to shed empirical light on the potentially beneficial effects of events on the hotels’ performance. This study investigates the impact of the differential support offered by the destination management organisation (DMO) over two years.

Using online prices posted in advance of the events on an online travel agent, the authors assess hotel performance for each day of the events relative to the same day of the week in a week with no event. A similar comparison is made to assess the impact across two different years. In both cases, an ordinary least squares methodology was used.

Both events appear not to have had a strong impact on hotel prices and occupancy in 2016, i.e. when the DMO’s promotional effort was more proactive. Instead, in 2017, one event registered higher hotel prices and occupancy both relative to the year before and to the “business as usual” week.

The study identifies the existence of an indirect positive economic impact of the events on the hospitality sector.

The investigation adopts a more naturalistic experimental design to collect the data, which allows the authors to control for both the impact on prices and occupancy at the level of the single hotel. The evidence is therefore micro-founded. Moreover, results shed light on the role played by the DMO.

Although networked hospitality businesses as Airbnb are a recent phenomenon, a rapid growth has made them a serious competitor for the hospitality industry with important consequences for tourism and for tourist destinations. The purpose of this paper is to analyse the nature of the phenomenon, its potential further development in the next five years and the impact this developments will have on tourism, on hotels and on city destinations.

A literature study, combined with scenario workshops and a Delphi panel, were used to map current trends and uncertainties. With this input, future scenarios were elaborated using the Global Business Network (“scenario cross”) method.

Network platforms as Airbnb are often classified under something called the “Sharing Economy”, a denomination that obscures their true nature. Airbnb is a challenging innovation to which traditional hospitality will have to respond. Its impact has at the same time led to a call for regulatory policies. The definition of these policies and the evolution of tourism are variables that determine future scenarios. Attempts to ban the phenomenon mean a disincentive to innovation and protect oligopolistic markets; more receptive policies may have the desired results if tourism grows moderately but in booming destinations they may lead to a harmful commercialization.

Until now, Airbnb has been described in conceptual studies about the so-called “Sharing economy”, or more recently in empirical studies about isolated effects of holiday rentals. This paper contextualizes the evolution of networked hospitality and seeks to synthesize the sum of its impacts, thus enabling businesses and local governments to define positions and strategies.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

This study aims to examine the influence of service quality, satisfaction, trust, value and commitment on hotel customers’ attitudinal and behavioural loyalty.

The purpose of this study is to examine the influence of key hotel attributes on the room rates of selected hotels in the Greater Gaborone Region, Botswana.

Using hedonic pricing analysis, the effect of eight attributes collected from 80 standard double rooms on Booking.com in the area was analysed using quantile regression.

The estimated results from quantile regression suggested the importance of the 10th quantile as the best predictor of hotel room price distribution. Overall, the presence of a fitness centre and the availability of meeting and conference facilities were positively significant for the lowest- and premium-priced hotels, respectively.

The study advanced the literature in hedonic pricing models by confirming the applicability of hotel room rate attribute research in unexplored environments.

Hotel managers should be aware of the influence of key attributes, such as meeting and conference space availability and locational factors, on the pricing decisions of room rates in the Greater Gaborone Region. The study also presented opportunities for business-to-business marketing between hotel and tour operators in the region.

The study is one of the few that uses quantile regression in the hedonic pricing analysis of hotel room rates.

The purpose of this paper is to investigate specific marketing mix activities and influencing factors in hotels coping with falling room demand derived from drug cartel-related risk and insecurity.

A case study research was carried out using semistructured interviews with key informants (hotel managers) in two neighboring destinations at the US–Mexico border, an area where criminal organizations' drug trafficking-related violence has impacted the hospitality industry.

The research identifies factors that are internal (market segment diversification, type of ownership, magnitude of investments) and external (tourism promotion organizations, media coverage, tourist flow volume) to the firms as they affect their marketing mix implementation.

The research developed a framework to better understand the use of marketing mix practices and influencing factors in criminal insecurity contexts, which could be further studied in other risk and conflict scenarios.

The pricing and communication tactics are employed more intensively, while product-service and distribution channel actions are used to a lesser extent. Greater emphasis should be placed on product-service, distribution and market segment diversification.

Considering the positive impacts that tourism and hospitality businesses have on local communities, it is recommended that the hotel sector works together with government and industry associations to improve the safety and security at tourism destinations.

The research extends the extant knowledge in hospitality crisis management by investigating the full marketing mix tactics in hotels at destinations stricken by cartel-related organized crime, an understudied context in the literature.

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.

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.

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.

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.

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.

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

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。

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。

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。

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。

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.

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.

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.

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.

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.

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.

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.

The purpose of this paper is understand these perceptions and identify main problems associated to climate change in order to design effective mitigation and adaptation strategies to guarantee the sustainability of tourism and natural resources. The Mediterranean basin is a leading international tourist destination and one that is particularly vulnerable to the effects of climate change. Although these effects are largely known, in-depth studies of how they and the associated risks are perceived by key tourism stakeholders have not been performed.

Interviews were held with 31 hotels, campsites and rural lodgings in the Muga River basin in north-east Catalonia, in which both owners and managers were asked about their perceptions of climate change, effects and countermeasures.

Perceptions of climate change and its effects varied according to the type of establishment and location (coast, cities or inland). Significant differences were observed for perceptions of how responsibilities for implementing mitigation and adaptation measures to counter the effects of climate change, including water shortages, should be shared out between the main agents with an interest in guaranteeing the sustainability of tourism, namely, government bodies, tourist establishments and clients. The predominant opinion, however, was that the bulk of the responsibility should lie with government bodies.

Only when those responsible for running tourist establishments are aware of the risks of climate change, it will be possible to design and implement effective short-, medium- and long-term strategies aimed at strengthening the resilience of the tourist industry.

The originality of this study lies in its novel methodology and approach, which involved analyzing perceptions of climate change, including water shortages and its effects among owners and managers of different types of tourist accommodation establishments in distinct parts of the same area.

This research aims to grasp hotel guests' motives and potential benefits sought when interacting with other guests, service personnel and residents and examines how these benefits can contribute to the total guest experience.

Mixed methods are adopted for the purpose of this study comprising individual interviews and a questionnaire survey.

Five groups of advantages emerge from individual interviews, including friendliness in interaction, social benefits, information acquisition, curiosity gratification and hospitality services. In the survey, which gathers 326 questionnaires, this study reveals that the five types of benefits derived from hotel guests' interactions could be further categorized into two dimensions: civility (e.g. friendliness and social) and utility (e.g. information, curiosity and service). The study confirms that four out of five potential or expected benefits from this personal interaction is significantly associated with the total hotel experience.

Respondents of this study are culturally homogenous; as a result, multi-cultural settings should be considered for future research.

Tourism and hospitality literature on people's interaction is mostly center around social aspects of interaction. The current study comprehensively explores all expected utilities of interaction, occurring in all sorts of interactions (e.g. customer-to-resident and customer-to-service personnel). Specifically, the findings of this study uncover the underlying factors which prompt the tourists to interact with other people in a lodging setting and examine the relative importance of those underlying factors to the total lodging experiences.