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The purpose of this paper is, first, to review the main conceptual proposals for the study of information and communication technologies (ICT) in tourism companies, and second, to develop and validate a formative scale for measuring the degree of technological advancement in hotels, based on the perceptions of a sample of Spanish hotel guests.

After a literature review on the measurement of technology advancement in tourism, a formative scale for ICT advancement in hotels from the guest perspective is developed and validated through a multiple-indicator, multiple-cause model estimated through partial least squares regression with data from 197 Spanish hotel guests.

Results of the empirical research allow validating the proposed formative scale for measuring technological advancement in hotels, identifying solutions that hotel guests mainly associate with highly technified establishments.

The proposed and validated formative scale for measuring the degree of technological advancement of hotels is expected to enable the proposal of models where the relations between central variables in consumer behaviour research (e.g. value) and their dependent variables (e.g. satisfaction) may be influenced by guests’ perception of hotel technology.

This paper presents an initial attempt to develop a scale for measuring the degree of technological advancement of tourism companies, a topic that has received scant attention in acad`emic research in spite of the importance of technology in this industry.

本论文研究目的, 第一, 审阅关于旅游公司的信息通信技术（ICT）相关理论研究；第二, 以西班牙酒店客户为样本, 编制和验证酒店科技先进度的形成性量度。

本论文首先审阅了旅游产业中科技先进度测量的相关文献, 然后通过MIMIC模型编制了从酒店客户角度出发的测量酒店ICT的形成性量度, 最后通过197份西班牙酒店客户样本和偏最小二乘回归来验证模型。

本论文验证了衡量酒店科技先进度的形成性量度, 并且发现各种解决方案, 其酒店客户用来评价高科技酒店个体的标准。

编制和验证的衡量酒店科技先进度的形成性量度, 表明消费者行为学核心概念（比如, 价值）和消费者满意度之间, 是可以由酒店客户对酒店科技度的感知因素来影响的。

本论文首次编制衡量旅游公司科技先进度的量度。尽管科技在行业中被视为很重要, 但是这个话题在科研界受到较少的关注。

科技先进度、信息通信科技、形成性量度、反应性量度、酒店

研究论文

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.

This study aims to develop and validate a scale for measuring hotel brand experience.

Based on existing hotel and brand experience literature, and seven distinct studies carried out as part of this research, a 17-item five-dimensional hotel brand experience scale was developed.

The scale revealed sound psychometric properties based on the findings from different reliability and validity tests, as well as from successful scale replications across several different samples. The study found a significant influence of hotel brand experience on revisit intention and word-of-mouth, which confirms nomological validity of the scale.

The developed hotel brand experience scale can provide hoteliers a way to examine the experiences evoked through hotel brand-related stimuli.

This study is the first to develop and validate measures of brand experience in context of hotel industry.

The purpose of this study is to identify an appropriate factor structure that may be utilized to effectively measure a hotel’s performance relative to service quality in a mid-scale setting. Customer perceptions of service quality in mid-scale hotels have largely been ignored; the focus of researchers has been the upscale (4-star) and luxury (5-star) segments.

A 27-item questionnaire is utilized to measure service quality with an initial sample size of over 2,500 respondents. Principle component analysis is utilized to determine the factor structure and regression analysis to determine which factors may serve as predictors of a hotel’s ability to meet customers’ expectations and to provide value.

A three-dimensional model emerged from the data, consistent with the theorizing of Rust and Oliver (1994), which includes the service product, service delivery and service environment. The service environment is the strongest predictor of a hotel’s ability to meet guests’ expectations and to provide guests with value within this context, which is inconsistent with findings in upscale and luxury hotels.

The generalizability of this research may be challenged, as the study was conducted within the context of an oceanfront resort destination dominated by leisure travelers; however, the study may be replicated in additional settings to determine if a similar bundling of service quality attributes occurs in other mid-scale settings including business hotels, as well as economy hotels.

A three-factor model may be more appropriate for assessing service quality in a mid-scale (3-star) environment. In this setting, the service environment and service product may be more important measures of service quality than service delivery. This is an important finding, as many mid-scale and select-service, as well as new mid-scale, lifestyle hotel concepts, attempt to drive profitability by deemphasizing service delivery or by utilizing technology to facilitate service delivery. These findings may also assist operators of mid-scale hotels in improving guests’ perceptions of quality, which has been found to increase perceived value and may positively influence purchase or revisit intentions (Kashyap and Bojanic, 2000).

Service quality research has been conducted, almost exclusively, in first-class (4-star) and luxury (5-star) hotels, while the majority of hotels do not fall into these categories. Although guest expectations relative to service quality may be lower in more moderately priced, mid-scale hotels, service quality remains a critical variable that influences a guest’s decision to return or recommend a hotel to others. Many travelers now utilize online reviews to minimize purchase risk by seeking information relative to service quality when selecting a hotel. Consequently, it is more important than ever that service quality is understood in hotels at all service levels. The present research contributes to filling this gap in the literature.

The purpose of this paper is twofold: first, to examine the extent to which hotel investments create jobs and, second, to compare whether investment in a particular hotel segment generates more or less jobs in the overall economy and in the tourism, leisure and hospitality industries.

The panel autoregressive distributed lag regression model was used to examine the effect of total hotel investments and hotel investments in economy-scale, midscale, luxury-scale and independent hotels on total employment and employment in the tourism, leisure and hospitality industries in the USA.

Hotel investments increase employment in both the overall economy and the tourism, leisure and hospitality industries. Midscale hotels make the highest contribution to employment in the overall economy. Economy-scale hotels make the highest contribution to employment in the overall tourism, leisure and hospitality industries.

The results support the postulations of growth pole theory. As hotel investment increases, not only does the hotel industry see gains in employment but also does related economic sectors see an increase. Midscale hotels have the greatest positive impact on local labor markets, which is consistent with the assertions of middle-out economics.

Community leaders should encourage the type of investment that benefits the broader area as much as possible by incentivizing the type of growth that is related to employment growth.

This study investigates the relations between hotel investment and employment from a theoretical and empirical perspective by providing objective claims inferred from statistical inferences.

This paper aims to measure customer-based brand equity in the context of hotels, and to develop and empirically validate a new scale, named guest-based hotel equity (GBHE), by incorporating the customer perceived value of hotels as a multidimensional construct in addition to its traditional dimensions (i.e. brand awareness and brand image).

A structured and self-administered survey was used, targeting 348 hotel guests who were surveyed about their experience with the last hotel they had stayed in during the previous year. Exploratory and confirmatory factor analyses were used to assess the research constructs dimensions, unidimensionality, convergent and discriminant validity and composite reliability.

The empirical findings indicate that GBHE is a multidimensional construct with nine dimensions, namely, hotel awareness, hotel overall image and seven dimensions of customer perceived value (i.e. the values of price, quality, self-gratification, aesthetics, prestige, transaction and hedonism). The new scale is found to have excellent psychometric properties; it has demonstrated its predictive power on behavioral intentions.

Although the authors believe that the sample size was reasonable and adequate for conducting CFA analysis, a bigger sample would be better and might increase the robustness of the proposed scale. In addition, to avoid the retrieval failure problem, hotel guests should be surveyed just after their stay in the hotel or not long afterwards. Further, the hotel classification or hotel star rating was not considered in developing and validating the GBHE scale.

The findings of this study provide hotel managers with a new tool to use in assessing the experiential value of the hotel brand equity, other than conventional hotel awareness and brand image. Further, using the multidimensional construct of perceived value provides hotel managers with more insights into what aspects of hotel brand equity they should focus on to influence the behavioral intentions of their guests.

The originality of this research is highlighted in several points. First, it develops and empirically validates a new scale to measure customer-based brand equity in the hotel context, that is, GBHE. Second, it incorporates the customer perceived value of hotels not as a unidimensional construct that is concerned only with cost, but as a multi-dimensional construct which includes in the GBHE scale dimensions that are both cognitive (i.e. of price and quality) and affective (i.e. of self-gratification, aesthetics, prestige, transaction and hedonism) in addition to its traditional dimensions (i.e. brand awareness and brand image). Third, it assesses the predictive power and relative importance of the GBHE dimensions for behavioral intentions (i.e. loyalty to hotels). Finally, no research has been done so far on the brand equity of hotels in the United Arab Emirates (UAE), although it is considered a fertile soil for tourism in the Arabian region.

The main purpose of this study is to identify the dimensions of hotel employees’ job risk perceptions and develop a measurement scale for this construct.

Four studies using a mixed-method design were conducted to develop and validate the scale of hotel employees’ perceived job risk (HEPJR). Study 1 identified the dimensions and initial items of HEPJR through a literature review and in-depth interviews. In Study 2, an explanatory factor analysis was perform to refine the preliminary items. Study 3 further refined the HEPJR scale through a confirmatory factor analysis. Study 4 confirmed that HEPJR is a 19-item scale through a cross-validation analysis.

A reliable and valid scale was developed to measure the following five dimensions of HEPJR: perceived human, equipment, internal environment, external environment and management risks. HEPJR and its dimensions significantly predict negative safety consequences and negative job satisfaction.

Employees in medium- and high-star-rated hotels in China were surveyed. Future research should test the HEPJR scale in other types of lodging formats (e.g. budget hotels, homestays and cruise ships) and different countries or regions.

Given the increasingly serious job risks faced by hotel employees, the HEPJR scale can become a benchmark for job risk identification, accident prevention and safety management.

This scale provides a clear conceptualization and an appropriate measurement tool of HEPJR from a risk-source perspective.

Extending the technology acceptance model (TAM) to a new context, the purpose of this paper is to propose an integrative model of the brand of artificial intelligence-enabled voice assistants (AI-EVA) and customers’ perceptions and behavioral intentions of using AI-EVA in hotels. Moderating effects of construal levels and hotel scales were examined.

This paper adopted a mixed method approach. A qualitative and phenomenological methodology was adopted in Study 1 to explore hotel customers’ experience with AI-EVA. Study 2 applied experimental design to investigate the effects of the brand of AI-EVA and construal level on customers’ perceptions and behavioral intentions of using AI-EVA. Based on Studies 1 and 2 results, Study 3 examined how the brand of AI-EVA and hotel scale affect customers’ perceptions and behavioral intentions of using AI-EVA during hotel stays.

This research found that customers perceive a higher level of perceived usefulness, perceived ease of use and anthropomorphism when AI-EVA is branded (vs off-brand). Perceived usefulness positively affects customers’ intention to use and to spread positive word-of-mouth. Anxiety of using AI-enabled devices and privacy concerns inhibit customers’ intention to use AI-EVA. Anthropomorphism increases customers’ willingness to spread positive word-of-mouth. Construal level moderates the effect of the brand of AI-EVAs on perceived ease of use and anthropomorphism. Hotel scale moderates the effect of brand on perceived usefulness.

This paper is one of the first attempts to uncover and integrate different factors underlying customers’ perceptions of using AI-EVA in an extended TAM in hotel settings. This paper provides an integrative model extending the TAM to a new context by deploying a mixed-method approach across three studies.

This paper aims to describe the detailed process of development of a reliable scale to measure customer perceptions of the upscale hotel servicescape that could then be used as a basis for intra- and inter-hotel comparisons and to examine relationships with other variables, such as emotions, satisfaction and loyalty.

A review of the existing service and hospitality literature provided a range of dimensions and attributes of the hotel servicescape, which were used as the basis for a Q-sort technique to determine the content adequacy of newly developed and existing items. Testing the emergent items was carried out through a questionnaire that was distributed at five luxury upscale hotels in London providing 612 fully valid responses, which, using a split sample, were subjected to both exploratory and confirmatory factor analyses to explore the dimensionality and reliability of the instrument.

Although the Q-sort suggested four key dimensions, the outcome of the factor analyses revealed five dimensions with high reliability – aesthetic quality, functionality, atmosphere, spaciousness and physiological conditions. “Aesthetic quality” appeared to be the most important factor, followed by “functionality”, “atmosphere”, “spaciousness” and “physiological conditions”.

As this study was conducted with customers of upscale luxury hotels in London, the resulting scales need to be further tested in other hotel segments and in other locations.

This study provides upscale hotel managers with an effective measurement tool, which will enable them to benchmark their operation and make improvements that could lead to a better impression and evaluation of their hotel. The scale has a variety of potential applications and can serve as a framework for further research in the hotel industry.

In spite of the wide interest in and importance of the servicescape in hotels, there are only a few studies dealing with this subject in the hotel context. This study provides a new tool for measuring customers’ perceptions.

Valid measurement scales for predicting the adoption of hoteliers’ customer‐centric orientation are in short supply. The present research develops and validates a new scale for a specific variable, i.e. Management Attitudes Towards Customer‐Centric Orientation (MATCCO). Furthermore, this research attempts to identify some broad determinants for a successful CRM system implementation and propose a research model depicting possible relationships among MATCCO, broad determinants and profit.

A structured questionnaire has been developed in order to accomplish the research objectives. Data were collected from 86 Greek luxury hotels. Accepted methodology was used to construct the measure, factor analysis to determine the CRM key success factors (KSFs) and Pearson correlation, ANOVA and discriminant analysis to test the proposed model. Additionally, qualitative research was conducted in two Greek luxury hotels.

A reliable and valid measure of MATCCO was constructed. Four CRM KSFs were identified. The research model was verified and proposed confirming relationships among MATCCO, CRM KSFs and company profit. Cases analysis showed that effective customer communication strategy, IT infrastructure and suitable organizational strategy are the KSFs of CRM implementation provided that hoteliers are positive toward customer‐centric orientation.

The results of this study are applicable to luxury hotels.

There is a necessity of checking the level of MATCCO before undertaking a CRM implementation project. Further, the results of this study highlight some crucial factors that influence successful CRM implementation in the hotel lodgings.

The main contribution of the paper is the construction of the multi‐item measure of hoteliers’ customer‐centric orientation.