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Voice assistants (VAs) empower human–computer interactions by recognising human speech and implementing commands pronounced by users. This paper aims to investigate VA-enabled interactions between hotels and guests in the hospitality context. The research positions VAs within the artificial intelligence (AI)-enabled Internet of Things (IoT) context, disrupting old practices and processes. Smart hospitality uses VAs to support effortless value cocreation for guests cost-effectively. The research examines consumer perceptions and expectations of hospitality VAs and explores VA capabilities through expert technology providers.

This empirical paper investigates the current use and future implications of VAs for hotel environments. It uses qualitative, semi-structured in-depth interviews with 7 expert hospitality VA technology providers and 21 hotel guests who have VA experience. The research adopts a demand and supply approach, addressing the VAs in hospitality holistically.

The findings illustrate the requirements from both end-users’ sides, hotels and guests, exploring VA advantages and challenges. The analysis demonstrates that VAs increasingly become digital assistants. VA technology helps hotels to improve customer service, expand operational capability and reduce costs. Although in its infancy, VA technology has made progress towards optimising hotel operations and upgrading customer service. The study proposes a speech-enabled interactions model.

This research stimulates the transformation of hospitality services by using VAs and the development of smart hospitality and tourism ecosystems. The study can benefit from further research with hotel managers, to reflect hoteliers’ points of view and investigate their perception of VAs. Further research can also explore different aspects of consumer–VA interaction in different contexts.

The paper makes a significant contribution to hospitality management and human–computer interaction best practices. It supports technology providers to reconsider how to develop suitable technology solutions towards improving their strategic competitiveness. It also explains how to use VAs cost-effectively and profitably while adding value to travellers’ experience.

VA studies are often focussed on the technology in private households, rather than in commercial or hotel spaces. This paper contributes to the emerging literature on AI and IoT in smart hospitality and explores the acceptance and operationalisation of VAs. The research contributes to the conceptualisation of VA-enabled hotel services and explores positive and negative features, as well as future prospects.

语音（数码, 虚拟或者人工智能）(VAs) 助理能够识别真人声音和系统指令声音从而为人机互动提供助力。 本研究基于酒店业已有的案例探索了酒店和客人语言支持的互动的本质。本研究探索了关于客房服务的表现和实用性的顾客认知和顾客期望。

本研究借用了定性半结构化深入访谈来收集一手数据, 调查了酒店环境中的语音助理目前的运用情况和未来影响。本研究访谈了7位酒店科技服务提供者和21位有使用个人智能扬声器经验的酒店客人。本研究以供需模型来全方位解决此项问题。

研究结论强调了从双方使用者（酒店和客人）角度考量, 并且考虑到语音仪器带来的所有的优势和挑战的重要性。基于顾客之前对这些仪器的使用经验, 本论文深入阐述了对公共空间这些语音助理的使用功能。本分析证明了由AI技术支持下, VAs 可以灵活的识别语音。VAs理解词汇内容并且也懂得词汇作为数据助手来支持智能家庭的自动化以及履行商业职责背后的意义来。酒店从业人员可以尝试运用此科技来提高用户体验, 扩展运营空间和减少成本。从访谈的数据可以证明, 尽管还在初级阶段, VAs 科技已经对酒店运营优化和晋级客户服务做出了显著的贡献和成就。本研究提出了一项介于酒店和客人之间的VA 语言支持的互动模型。

之前的研究主要针对私人使用, 而不是商业或者酒店空间。考虑到敌对环境和客人和酒店的文化差异, 旅游和酒店成为了尤其有挑战性的领域。本研究通过语音识别革新了酒店服务。本研究针对VAs接受程度和运用进行详细研究从而为酒店领域的AI和IoT提供了专业文献。本文为酒店服务中的VAs使用做出了开拓性的调查并且探讨了正面以及负面的特征和未来展望。

本研究为酒店和旅游管理补充了文献, 尤其是在酒店业人机互动领域。本研究通过语音识别技术对酒店服务的转型革新做出贡献。此项研究可以受益于以酒店管理者为视角的进一步研究。相比于收集科技设备供应方的见解, 对酒店管理者进行访谈可以提供更直接的信息来了解酒店员工对数码语音助理和对语音科技的总体接受程度。

酒店经常寻求途径来提高和客户的互动。本论文对酒店管理和人机互动领域提供了应用典例。本研究提供了酒店客人针对语音设备功能性的总体评价作为有价值的信息, 进而帮助科技提供者来重新审视针对顾客需要从而量身定制服务的策略和方式。最终, 本研究在提高行业战略竞争力层面分享了关于发展和采用此项强大有力科技的见解。

Using a video revealing unhygienic practices in Chinese five-star hotels as the case study, this study aims to understand the impact of service failure online exposure on hotel revenue performance in terms of seriousness, magnitude and duration, as well as to identify the hotel-characteristics and hotel-responsiveness factors that influence revenue recovery.

This study uses the actual Revenue per Available Room data of ten hotels involved in the incident and five different market segments during 2016–2019. Event study method is used to investigate the effect of online exposure on hotel revenue performance.

This study confirms the significant negative effect of online exposure and that hotels take nearly nine months to fully recover. The results indicate that hotel size, hotel age and response strategy play an important role in reducing negative impacts. Moreover, this study reveals the dynamic spillover effects of online exposure on different hotel market segments. These effects change from a competitive to a contagious effect with a decrease in class ratings.

Low-class hotel managers should take effective actions to avoid possible negative spillovers from others’ service failure incidents. Hotel managers could consider the synergy of different strategies rather than a single response strategy to minimize losses.

This study theoretically broadens knowledge about the negative impact of online exposure on Chinese hotel revenue. Additionally, the findings examine the dynamic spillover effects on hotels in different segments. Furthermore, they extend the existing findings on the negative impact of online public opinion crises.

本研究以一段揭示中国五星级酒店不卫生行为的视频为案例, 旨在了解网上曝光的服务失败事件在严重程度、规模和持续时间方面对酒店收入绩效的影响, 并确定影响收入恢复的酒店特征和酒店回应因素。

本研究使用了2016–2019年期间10家涉及酒店和5个不同的细分市场的实际每间可用房收入（RevPARs）数据。采用事件研究法（ESM）来研究网上曝光对酒店收入绩效的影响。

本研究证实了网上曝光的显著负面效应, 酒店需要近9个月的时间才能完全恢复。结果表明, 酒店规模、酒店年龄和回应策略在减少负面影响方面发挥了重要作用。此外, 本研究还揭示了在线曝光对不同酒店细分市场的动态溢出效应。这些效应随着酒店星级的下降而从竞争效应变为传染效应。

低星级酒店管理者应采取有效行动, 避免其他酒店的服务失败事件可能带来的负面溢出效应。酒店管理者可以考虑不同策略的协同作用, 而不是单一的回应策略来减少损失。

本研究从理论上拓宽了关于网上曝光对中国酒店收入绩效的负面影响的知识。与此同时, 本研究的结果考察了不同细分市场的酒店的动态溢出效应。此外, 还扩展了现有的关于网络舆情危机的负面影响的研究结果。

Este estudio utiliza los datos reales de ingresos por habitación disponible (RevPAR) de 10 hoteles implicados en el incidente y cinco segmentos de mercado diferentes durante 2016-2019. Se utiliza el método de estudio de sucesos (ESM) para investigar el efecto de la exposición en línea en el rendimiento de los ingresos de los hoteles.

Utilizando como caso de estudio un vídeo que revela prácticas antihigiénicas en hoteles chinos de cinco estrellas, este estudio pretende comprender el impacto de la exposición online de fallos en el servicio sobre el rendimiento de los ingresos hoteleros en términos de gravedad, magnitud y duración, así como identificar las características y los factores de respuesta del hotel que influyen en la recuperación de los ingresos.

Este estudio confirma el importante efecto negativo de la exposición online, tardando los hoteles casi nueve meses en recuperarse totalmente. Los resultados indican que el tamaño del hotel, su antigüedad y la estrategia de respuesta desempeñan un papel importante en la reducción del impacto negativo. Además, este estudio revela los efectos indirectos dinámicos de la exposición online en diferentes segmentos del mercado hotelero. Estos efectos cambian de un efecto competitivo a un efecto contagioso con una disminución de las calificaciones de la categoría o clase hotelera.

Los revenue managers de los hoteles de categoría baja deberían tomar medidas eficaces para evitar posibles repercusiones negativas de los fallos en el servicio de otros hoteles. Los directores de hotel podrían considerar la sinergia de diferentes estrategias en lugar de una única estrategia de respuesta para minimizar las pérdidas.

Este estudio amplía teóricamente los conocimientos sobre el impacto negativo de la exposición online en los ingresos de los hoteles chinos. Además, los resultados examinan los efectos indirectos dinámicos en hoteles de diferentes segmentos. Además, amplían los resultados existentes sobre el impacto negativo de las crisis de opinión pública online.

While the economic benefits of the exhibition industry for the hotel sector have been addressed, the impact of exhibitions on individual hotels is unknown, especially when individual hotels’ star classification and locations are considered. This study aims to provide a better understanding of how room rates of different hotels change during different stages of the Canton Fair in China from a spatial-temporal perspective.

Room rates of 681 star-hotels within the city of Guangzhou before, during and after the Fair were extracted from websites. Through spatial interpolation and autocorrelation analysis and geographical detector (GeoDetector) technique, spatial and temporal patterns of hotel room rates and the interdependence between the convention center and the hotels with different star classification and locations were examined.

An inverse-U shape of room rate change was identified before, during and after the Fair, and the five-star hotels had the sharpest increase. Moreover, the distribution of hotel room rates followed the law of distance decay. The variation of hotel rates became larger when the distance to the convention center was larger. Spatial high-high clusters varied among hotels with different star classification.

This study contributed to the hotel literature by providing empirical evidence regarding how hotels with different star classification and locations were affected by events. This study also advanced the event literature by introducing GeoDetector. The findings of this study offered insights into the hotel location selection, pricing strategies and hotel collaboration with events.

虽然展览业对酒店业的经济效益已经得到解决, 但展览对单个酒店的影响尚不清楚, 尤其是在考虑单个酒店的星级和位置时。本研究旨在从时空角度更好地了解中国广交会不同阶段不同酒店的房价变化情况。

网站提取了广交会前、中、后广州市内681家星级酒店的房价。通过空间插值和自相关分析以及地理探测器（GeoDetector）技术, 研究了酒店房价的时空格局以及会议中心与不同星级和位置的酒店之间的相互依赖关系。

会前、会中、会后房价变化呈倒U型, 其中五星级酒店涨幅最大。此外, 酒店房价的分布遵循距离衰减规律。到会展中心的距离越远, 酒店价格的变化就越大。不同星级酒店的空间高-高集群存在差异。

该研究通过提供关于不同星级和位置的酒店如何受到事件影响的经验证据, 为酒店文献做出了贡献。这项研究还通过引入 GeoDetector 推进了事件文献。研究结果为酒店选址、定价策略和酒店与活动的合作提供了见解。

The purpose of this study is to determine the satisfaction of the guests who stay at hotels offering technology-supported products and services related to the services and products they receive by using the opinion mining technique.

In this research, 12,396 customer reviews on booking.com related to ten hotels belonging to a hotel chain using technology-supported products were evaluated with aspect-based sentiment analysis techniques.

As a result of this study, it has been determined that using technology in hotel businesses creates a positive impression on customer satisfaction. It has been determined that the enrichment of standard hotel business products such as beds and room lighting with technology, in a way that will not be very costly, affects the guests. In addition, it is interesting that technological features such as robots and room service robots, which are called “High & Technology” in this study, are evaluated by customers in the service process.

The hotel managements have the opportunity to evaluate the services we offer by analyzing their online comments and to see their own image from the eyes of the guests. Hotel businesses must learn about customer expectations for technologies with high investment costs. This study, which analyzes online customer reviews, enables tourism businesses that offer technology-supported products and services and invest in technology in service delivery, to understand how customers evaluate the service.

In this study, customer reviews of a hotel group operating in many countries belonging to a hotel group that enriches its standard products with technology and provides service with the concept of a “smart hotel” were examined. This study contributes to the understanding of customers' experience of using technological products in hotel businesses. This study contributes to the literature on customers' satisfaction with technological hotel products and services and the decision of hotels to invest in technology.

本研究通过使用意见挖掘技术旨在确定入住酒店的客人的满意度。这些客人接受酒店提供的产品相关的技术支持和服务。

在这项研究中, 使用基于特定方面的情感分析技术评估了 booking.com 上与属于连锁酒店的 10 家酒店相关的 12,396 条客户评论, 这些酒店均使用科技支持的产品。

作为这项研究的结果, 已经确定在酒店业务中使用科技会对客户满意度产生积极的影响。已经确定, 标准酒店商务产品（例如床、房间照明等）的丰富科技以不会非常昂贵的方式影响客人。此外, 客户感兴趣的是在本研究的服务过程中包括机器人和技术特征, 例如客房服务机器人, 作为“高科技”层面。

酒店管理层分析了客人的在线评论, 并有机会评估他们的服务并从客人的眼中看到自己的形象。酒店企业必须了解客户对高投资成本技术的期望。本研究分析了直接体验过的消费者的意见。因此, 研究结果将使决定投资服务技术的酒店企业受益。

在这项研究中, 我们对一家在许多国家经营的酒店集团的客户评论进行了调查。该酒店属于一家酒店集团, 该集团以技术丰富其标准产品, 并以“智能酒店”的概念提供服务。该研究有助于了解客户在酒店业务中使用技术产品的体验。该研究扩展了客户对酒店科技产品和服务的满意度的文献, 以及对酒店投资技术的决策做出贡献。

The purpose of this paper is to design an algorithm to predict hotel profitability by means of deep learning techniques.

The methodology consists of a multi-layered neural network that includes a lag of profitability as the input. Furthermore, other input variables are related to hotel and tourist destinations; the raw data for hotel and tourist destinations were collected from multiple public access data sources.

The results show that the proposed model has a high predictive capacity of hotel profitability in all the years studied (2005-2011), according to the performance metrics evaluated within the sample. Thus, the authors can conclude that deep learning algorithms can be a useful tool to evaluate hotel performance.

The algorithm designed in this research could be of interest to improve decision-making processes related to profitability, for example, in evaluating the creation of new hotels. Moreover, the model provides a quick and efficient analyses that could be of interest to investors and lenders. In particular, they could compare investment alternatives in the hotel sector. Also, according to the results, the location variables are important determinants of hotel profitability, and consequently, hotel managers should collaborate with the tourist destination managers to improve profitability. From an internal perspective, hotel managers should focus on the management of human resources.

This paper is the first empirical study that predicts hotel profitability using deep learning techniques. In addition, this methodology is applied to analyse hotel profitability, for the first time, in the Spanish market. This market is an ideal analytical framework because of its heterogeneity with respect to hotel supply in terms of seasonality and coastal characteristics, among others.

本论文旨在设计一种数算制度通过深度学习的机制来预测酒店盈利性。

本论文采用多层神经网络、以盈利时间区间作为单位, 来进行计算。此外, 其他关于酒店和旅游目的地的数据因子也包含在研究范围内；研究样本包括酒店和旅游目的地的原数据, 这些数据通过多方公开数据渠道获得。

研究结果表明提出的数算制度模型对于所有年份（2005-2011）的酒店盈利性研究有显著预测功效。此判定是由数据样本的效益矩阵得出。因此, 我们能够形成结论：深度学习的数算制度可以作为衡量酒店效益的有力工具。

本论文设计的数算制度对于提高盈利性的决策过程有很大意义, 比如评估新酒店建成后效益等。此外, 本论文设计的模型对于投资者和贷款方做出快速和有效分析有着显著意义。特别是这个模型能够使得他们在酒店业中对多个投资方案做横向比较。此外, 根据结果表明地理位置因素对于酒店盈利性占据重要位置, 因此, 酒店经理应该与旅游目的地经理协作来提高酒店盈利性。从酒店内部管理角度出发, 酒店经理应该着重人力资源的管理。

本论文是首个实证研究通过深度学习技术来预测酒店盈利性。此外, 这种研究方法也是首次在西班牙市场实证分析酒店盈利性。西班牙市场是理想的分析样本, 因为其由于季节性和海岸特点的酒店市场的多样性。

The purpose of this paper is to evaluate the hotel selection problem of airlines for their hotel and airline alliance (HAA) to develop potential customers of airlines. This paper will propose a hybrid mathematics evaluation model to help airline to select an optimal hotel with both qualitative and quantitative criteria.

To solve the hotel selection problem of airlines for their HAA, this paper focuses on the implementation of the NGT, Fuzzy TOPSIS and MCGP models in the hotel selection process. Initially, the NGT was used to create HAA decision-making criteria based on the literature review and expert opinions, and it was found that scale and scope possibility, brand value, tourism attraction, operating cost and industrial conditions are the most important criteria. Later, the Fuzzy TOPSIS method was used to obtain the general normalized fuzzy preference and to compute the closeness coefficients of each alternative hotel with respect to each criterion. Third, five tangible constraints were incorporated into the Fuzzy TOPSIS-MCGP model to calculate the optimal hotel with LINGO software.

Airline managers can use the proposed model to form a clear view of how to choose the most suitable hotel to cooperate with to outperform their competitors. Having access to this information allows airline managers to take steps to perform better and improve the performance of the partnership, helping them to gain more confidence in their decision-making capabilities while reducing investment risks.

This is the first paper that has adopted Fuzzy TOPSIS-MCGP to select hotel for their HAA from the airline’s point of view. The major contributions of this study are as follows: an efficient and simple evaluation framework is proposed for handling vagueness and uncertainty in real-world hotel selection problems; the advancement of treating uncertainty in the MCDM process; the fuzzy TOPSIS-MCGP method is extended for such problems, taking into account tangible and intangible criteria; airline managers can now make decisions in choosing to select the best hotel for their HAA that meets the airline's business goals and passenger demands; hotel operators are flexible in selecting their airline partnership, thus creating greater profit for both parties.

饭店和航空公司之间横向联盟的选择模型：NGT, fuzzy TOPSIS和MCGP方法的综合应用

本文的主要目的是在协助驾驶评估酒店选择的问题, 并通过由酒店与航空公司的合作联盟HAA, 开发整合的潜在客户。评估模型, 以帮助航空公司选择同时满足定性和定量标准的最佳酒店。

这些研究集中在规模和范围的可能性, 品牌价值, 旅游吸引上力, 运营成本和产业条件上。第二个步骤是日期近似近似最佳解排序技术（fuzzy TOPSIS）计算每家替代酒店与理想解决方案的接近度系数。规划方法（MCGP）选择最佳酒店, 同时选择方法同时考虑酒店的定性和定量标准, 并且从未在酒店选择文献中被采用过。

为了帮助评估评估合适的酒店和建立合作联盟, 因此本文提出了NGT-Fuzzy TOPSIS-MCGP模型, 以帮助决策的决策者实现替代的酒店。在此模型中, 决策者通过最后, 在名目人群技术（NGT）确定客观的酒店选择规范, 然后他们可以根据模糊近似最佳解排序技术（TOPSIS）确定标准权重, 并计算模糊的TOPSIS-MCGP模型中, 决策制定者可以使用多选择目标规划（MCGP）, 通过设定每个目标的期望水准寻找最佳酒店。

这是第一篇以航空的角度, 同时采用模糊TOPSIS-MCGP方法选择合适的酒店的论文。本文最主要的贡献是: 1. 提出了一种有效而简单的评估框架, 用于处理现实世界中酒店选择问题中的模糊性和不确定性。2. 在处理MCDM过程中不确定性方面的进展；模糊TOPSIS-MCGP方法针对此类问题进行了扩展, 同时考虑了有形和无形的标准。3. 航空公司经理现在可以做出决定, 选择适合其HAA的最佳酒店, 借以满足航空公司的业务目标以及乘客的需要。4. 酒店运营商可以灵活选择航空公司合作伙伴关系, 从而为双方创造更大的利润。

饭店, 航空公司, 名目人群技术（NGT）, 最佳解排序技术（TOPSIS）, 多选择目标规划（MCGP）, 横向联盟

El modelo de selección Para alianzas horizontales entre hoteles y aerolíneas (Haa): una aplicación integrada de los métodos NGT, fuzzy TOPSIS y MCGP

El objetivo principal de este documento es evaluar el problema de selección de hoteles de las aerolíneas para su HAA (hotel airline alliance) a fin de desarrollar clientes potenciales para las aerolíneas. Este documento propondrá un modelo híbrido de evaluación matemática para ayudar a la aerolínea a seleccionar un hotel óptimo con criterios cualitativos y cuantitativos.

Para resolver el problema de selección de hoteles de las aerolíneas para su HAA, este documento se centra en la implementación de los modelos NGT, Fuzzy TOPSIS y MCGP en el proceso de selección de hoteles. Inicialmente, el NGT se utilizó para crear criterios de toma de decisiones de HAA basados en la revisión de la literatura y las opiniones de expertos, y se descubrió que la escala y la posibilidad de elección, el valor de la marca, la atracción turística, los costes operativos y las condiciones industriales son los criterios más importantes. Posteriormente, se utilizó el método Fuzzy TOPSIS para obtener la preferencia fuzzy general y normalizada y calcular los coeficientes de cercanía de cada hotel alternativo con respecto a cada criterio. En tercer lugar, se incorporaron cinco restricciones tangibles al modelo Fuzzy TOPSIS-MCGP para calcular el hotel óptimo con el software LINGO.

Los gerentes de aerolíneas pueden usar el modelo propuesto para tener una visión clara de cómo elegir el hotel más adecuado para colaborar con el fin de superar a sus competidores. Tener acceso a esta información permite a los gerentes de las aerolíneas tomar medidas para gestionar mejor y mejorar el resultado de la alianza, lo que les ayuda a ganar más confianza en su capacidad de toma de decisiones y al mismo tiempo reducir los riesgos de inversión.

Este es el primer documento que adopta el modelo Fuzzy TOPSIS-MCGP para seleccionar un hotel para su HAA desde el punto de vista de la aerolínea. Las principales contribuciones de este estudio son las siguientes: 1. Se propone un marco de evaluación eficiente y simple para manejar la imprecisión y la incertidumbre en los problemas de selección de hoteles del mundo real. 2. El avance del tratamiento de la incertidumbre en el proceso MCDM; extiende el método fuzzy TOPSIS-MCGP a tales problemas, teniendo en cuenta criterios tangibles e intangibles. 3. Los gerentes de aerolíneas ahora pueden tomar decisiones al elegir el mejor hotel para su HAA que cumpla con los objetivos comerciales de la aerolínea y las demandas de los pasajeros. 4. Los operadores de hoteles son flexibles en la selección de su asociación de aerolíneas, creando así mayores ganancias para ambas partes.

Hotel, Aerolínea, Técnica de grupo nominal (NGT), Técnica Para el orden de preferencia por similitud a solución real (TOPSIS), Programación de objetivos de opción múltiple (MCGP), Alianza horizontal

Trabajo de investigación

The purpose of this study was to investigate relationships among the experiential value of hotel apps, the cognitive and affective evaluation of hotel apps users, hotel apps users’ satisfaction and their endorsement for the hotel apps. Specifically, this study examined the relationships that enhance hotel guests’ experiences through hotel apps.

The measurement items were developed through extensive literature review. This study used a web-based survey to test an integrated model of the experiential value. With a total of 320 usable samples, partial least squares structural equation modeling was carried out to identify key “driver” constructs and validate the proposed model.

A significant relationship was found in the playfulness of hotel apps and hotel guests’ cognitive and affective evaluations of the hotel apps, which positively influence hotel guests’ satisfaction and their endorsement for the hotel apps. Hotel apps should create fun and entertainment features in the hotel apps so that the users of hotel apps can be enjoyable during their usage. In addition, providing hotel apps users with time saving and easy use of the hotel apps can affect their satisfaction and endorsement for the hotel apps.

This study confirmed the positive links among hotel apps users’ experiential value, their cognitive and affective evaluation of the hotel apps, their satisfaction of using the hotel apps and their endorsement for the hotel apps. This study also revealed that hotel apps can be hotels’ effective communication tool that enhances existing and potential customers’ overall experiences.

项关于体验价值的综合模型

摘要

本论文旨在研究关于酒店APP体验价值, 对酒店APP用户的认知和情感评估, 用户满意度以及用户支持之间的关系。具体而言, 本研究探索了如何通过酒店手机APP使用来提高用户体验的理论关系。

测量条目通过详尽的文献综述来产生。本研究运用了网络调研来测量体验价值的一项综合模型。由320项有效样本, 偏最小二乘法结构方程建模（PLS-SEM）来鉴定关键“驱动”构象以及验证提出的模型。

研究发现酒店APP的娱乐性对顾客的APP的认知和情感评估都起到了显著性作用, 进而对顾客满意度和酒店APP支持度产生正面影响。研究建议酒店APP创造有趣以及娱乐产品功能, 从而让酒店APP用户从使用中获得乐趣。此外, 为酒店APP用户提供省时方便的服务可以影响用户满意度和对酒店APP的支持。

本研究验证了酒店APP用户体验价值, 对酒店APP的认知和情感评估, 用户对使用酒店APP的满意程度, 以及对酒店APP支持的正相关性。本研究进而发现酒店APP可以作为提升酒店现有和未来用户全面体验的有效工具.

This study aims to take boutique luxury hotels as its research subject to enrich the view on the self-positioned image of luxury hotels and simultaneously compare this image with the one perceived by customers. It also investigates whether a gap exists between the two images.

The best-rated boutique luxury hotel in Hong Kong is selected as the case hotel. Through the interpretation and discussion of high-frequency wordlists and semantic co-occurrence network charts, major topics in the hotel’s self-presented image and customers’ perceived image are identified accordingly.

Five dimensions (event making, exquisite food, excellent amenities and services, special function venue and promotion) used by hotels to form their boutique luxury image are recognised. Between hotels’ self-positioned image and customers’ perceived images, minor similarities such as the recognition of excellent amenities and services were confirmed but considerable differences were identified, indicating the ineffective marketing by the boutique luxury hotel despite its success in terms of ranking. Managerial suggestions on how to address the image discrepancy were proposed.

This study contributes insights into hotel image discrepancy among social media platforms in luxury hotel segments by adding the category of boutique luxury hotels. It also identifies the implications for enhancing the development of a hotel image to meet customers’ needs and expectations.

酒店的自我定位形象与顾客感知形象——以香港某精品豪华酒店为例

本研究试图以精品豪华酒店为研究对象, 丰富豪华酒店自我定位形象的视角, 同时将其与顾客感知的形象进行比较, 考察二者之间是否存在差距。

本文选取香港评分最佳的精品豪华酒店为案例酒店。通过对高频词表和语义共现网络图的解读和讨论, 识别出酒店自我呈现形象和顾客感知形象中的主要话题。

酒店利用五个维度（活动打造、精致的食物、优质的设施和服务、特殊的功能场所和促销）来塑造其精品豪华形象。在酒店的自我定位形象和顾客的感知形象之间, 发现了一些细微的相似之处, 如对优质设施和服务的认可, 但差异之处相当大, 表明尽管精品豪华酒店取得了优秀的排名, 但其营销效果不佳。本文提出了解决形象差异的管理建议。

本研究通过增加精品豪华酒店类别的案例, 有助于深入了解豪华酒店细分市场中社交媒体平台之间的酒店形象差异。本文还确定了促进酒店形象发展的影响, 以满足客户需求和期望。

Imagen auto-posicionada del hotel versus imagen percibida por los clientes: un estudio de caso de un hotel boutique de lujo en Hong Kong.

Este estudio se esfuerza por tomar a los hoteles boutique de lujo como tema de investigación para profundizar en el conocimiento sobre la imagen de los hoteles de lujo y compar el posicionamiento presentado por el hotel con el que perciben los clientes. También investiga si existe una brecha entre las dos imágenes.

Para el caso se selecciona el mejor hotel de lujo calificado en Hong Kong. A través de la interpretación y discusión de listas de palabras de alta frecuencia y gráficos de redes de coincidencia semántica se identifican los principales temas en la imagen presentada por el hotel y la imagen percibida de los clientes.

Se reconocen cinco dimensiones (creación de eventos, comida exquisita, excelentes comodidades y servicios, lugar de funciones especiales y promoción) utilizadas por los hoteles para formar su imagen de lujo boutique. Entre la imagen auto-posicionada de los hoteles y las imágenes percibidas por los clientes, se confirmaron pequeñas similitudes, como el reconocimiento de excelentes comodidades y servicios, pero se identificaron diferencias considerables, lo que indica la comercialización ineficaz del hotel boutique de lujo a pesar de su éxito en términos de clasificación. Se propusieron sugerencias gerenciales sobre cómo abordar la discrepancia de imagen.

Este estudio aporta información sobre la discrepancia de imagen del hotel entre las plataformas de redes sociales en los segmentos de hoteles de lujo al agregar la categoría de hoteles boutique de lujo. También identifica las implicaciones para mejorar el desarrollo de una imagen de hotel que satisfaga las necesidades y expectativas del cliente.

This study aims to examine the effects of user-generated photos (UGPs) and review valence (RV) on hotel guests’ perceived service quality, perceived price, perceived overall image and booking intention.

An online experiment where respondents were randomly assigned to one of the six conditions in a 2 (UGPs: provided vs not provided) × 3 (RV: positive vs neutral vs negative) between-subjects factorial design was used. The data of the study was collected from the travelers who used an online hotel review site to book a hotel at least once in the past 12 months. An independent sample t-test and analysis of variance were used to analyze the data of this study.

The results indicated that UGPs and RV significantly influenced hotel guests’ service quality, price, overall image perceptions and booking intention. The interaction effects of UGPs and RV indicated that positive online hotel reviews with UGPs had higher impact on hotel guests’ service quality, price, overall image perceptions and booking intention than neutral and negative online hotel reviews with UGPs.

The understanding of the effects of UGPs and RV on guests’ price, service quality, overall image perception and booking intention can help hotel managers and social media website designers to better promote the hotel and provide efficient online hotel booking environment.

This study builds the relationships between UGPs and RV and hotel guests’ perceived price, perceived service quality, perceived overall image and booking intention, which are crucial factors regarding online hotel marketing.

评估用户生成的照片对酒店客人价格、服务质量、整体形象感知和预订意愿的影响

本研究旨在探索用户生成的照片 (UGP) 和评论效价 (RV) 对酒店客人感知服务质量、感知价格、感知整体形象和预订意图的影响。

本研究采用受试者间因子设计进行了一项在线实验, 其中受访者被随机分配到 2（UGP：提供与未提供）× 3（RV：阳性 vs. 中性 vs. 阴性）中的六个条件之一。该研究的数据是从过去 12 个月内使用在线酒店评论网站至少预订一次酒店的旅行者那里收集的。使用独立样本 t 检验和方差分析 (ANOVA) 来分析研究数据。

结果表明, UGP 和 RV 显着影响酒店客人的服务质量、价格、整体形象认知和预订意愿。 UGP 和 RV 的交互作用表明, 与 UGP 的中性和负面在线酒店评论相比, 带有 UGP 的正面在线酒店评论对酒店客人的服务质量、价格、整体形象感知和预订意愿的影响更大。

了解UGPs和RV对客人价格、服 务质量、整体形象感知和预订意愿的影响, 可以帮助酒店管理者和社交媒体网站设计师更好地宣传酒店, 提供高效的在线酒店预订环境。

本研究建立了UGP和RV与酒店客人感知价格、感知服务质量、感知整体形象和预订意愿之间的关系, 这些是在线酒店营销的关键因素。

When shopping for hotels online, consumers usually follow a sequential process of search, click-through and book. How to maximize consumer conversion on the path to purchase and prevent potential customers from giving up the online search remains an important topic to hotel marketers and online travel agents (OTAs). The purpose of this study is to understand how informational cues displayed in an online hotel search process, including quality indicators, brand affiliation, incentives (discounted price and promotion) and position in the search results, influence consumer conversion from one stage to another.

The authors collected clickstream data of hotel search from Expedia. The data include information on individual consumers’ click-through and booking, as well as events leading up to the conversions (or failure to convert) from search, click-through to book. It contains 940,164 hotels searched and displayed in 39,574 online search queries made by users in a regional US market between November 1, 2012 and June 20, 2013. The modeling strategy comprised the Heckman model and random effects model, which integrated sequential consumer behavior in different problem-solving stages while accounting for heterogeneity across different hotels online.

The authors find that consumers rely on informational cues displayed online to make decisions about hotel booking. Specifically, consumers tend to click through hotels with higher consumer-generated ratings and industry-endorsed ratings. However, they tend to rely on consumer-generated ratings rather than industry-endorsed ratings when committing to a booking. Moreover, consumers are strongly responsive to incentives (discounted price and promotion) when clicking-through and booking a hotel. Finally, the likelihood of consumer conversions from search to click-through and booking is higher for hotels with brand affiliation and higher positions in the search results.

This research provides critical managerial implications of online search for hotel marketers and OTAs. The results inform hotel marketers and OTAs on how consumers respond to informational cues displayed in their search process and how these informational cues influence consumer conversion from one stage to another. The sequential problem-solving process of search, click-through and booking disclosed in this study also helps hotel marketers to identify customer conversion opportunities using effective informational cues.

当在线酒店预定时, 消费者往往遵循一系列流程, 搜索, 点击查询, 到最后预定。对于酒店营销商和线上旅游社（OTAs）来说, 如何最大化提高消费转化, 使得消费者不会半途中断, 最后预定酒店, 是一个重要话题。本论文的研究目的就是理解酒店在线搜索过程中, 信息线索如何影响每个阶段的消费转化, 其中涉及的因素有：信息质量、品牌、激励（折扣和促销）、以及搜索结果排名等。

研究样本数据采集于Expedia酒店搜索点击流。其中包括个人消费者点击和预定信息、以及由搜索、点击查询到预定过程中的消费转化（或者中途转化失败）的各种事件。样本容量包括940,164家酒店, 其涉及到由美国局部市场消费者在2012年11月1日到2013年6月20日之间做出的39,574条搜索结果。 我们采用Heckman模型和随机效应模型来整合不同线性时间上的消费者行为, 同时考虑不同酒店的多样性。

研究发现消费者使用在线信息线索来做酒店预订决策。具体来说, 消费者倾向于对于消费者评价高和行业认证高的酒店进行点击查询。然而, 相比行业认证, 消费者更倾向于借鉴消费者评价, 来做出最后预定决策。此外, 在点击查询和预定时, 消费者对于激励（折扣和促销）反应强烈。最后, 品牌和搜索排名靠前的酒店往往获得从搜索、点击查询到最后预定中更高的消费转化率。

本论文对酒店营销商和OTAs有重要的在线搜索启示。研究结果向酒店营销商和OTAs证明消费者在搜索过程中对信息线索如何反应, 以及这些信息线索如何影响每个阶段之间的消费转化。本论文展示的从搜索、点击查询、到预定的线性决策过程对于酒店营销商们有着重大帮助, 帮助其使用信息线索找出各种消费转化机遇。