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This study aimed to identify distinctive characteristics of hotel guests and understand their perception of guestroom technologies (GRTs) in hotels by utilizing the theory of consumer innovativeness and the social influence theory.

The data were collected from 268 hotel guests. The K-means clustering algorithm was employed to identify participants based on their views on the significance of technologies provided in guest rooms. A multivariate analysis of variance was applied to investigate if there were significant differences among clusters regarding social influence on hotel bookings, technology innovativeness and technology expertise and knowledge.

Two clusters were identified: technology compassionates and casual users of technology. Findings revealed that technology compassionates are more influenced by their friends when booking a hotel compared to casual users of technology. The ability to link up multiple wireless mobile devices, accessible outlets and mobile websites were the most critical GRTs for technology compassionates.

Technology should be considered a crucial part of the hotel guest experience. Hoteliers ought to continue investing in smart technologies to improve their guests' experiences. GRTs can reduce overhead staff costs while giving guests more control over their stay by utilizing everyday items like smartphones and offering them more power over their lodging experience.

This study advances the existing literature on GRTs by identifying which GRTs produce the most customer satisfaction. Moreover, this study explores the impact of social influence, innovativeness as a personality trait and having expert knowledge of technologies on preferences for GRTs.

The purpose of this paper is to present an overview of revenue management (RM) studies that focus on information technology (IT) and consumer behavior published between 2008 and 2018.

In total, 112 articles published in 17 journals were identified and analyzed.

This study shows the importance of IT and RM and focuses on the consumer perspective. It also emphasizes that technology is not the enemy of humans: it complements and adds value to their existing jobs.

Book chapters and conference proceedings related to IT and RM were not included in this study. Besides, only journal papers published in English were included in the study. The categorizing of subjects can be seen as subjective.

This study helps researchers discover articles from 2008 to 2018 and helps hospitality executives interested in RM technologies from the demand side to use these findings in their business environment.

Based on the interaction between service providers (hotels) and users (consumers) on IT and RM platforms, the paper identified eight key components that have been relevant over the past decade.

本论文旨在介绍2008年至2018年之间的财务管理（RM）研究中涉及信息技术（IT）和消费者行为的文献综述。

本研究样本为发表在17个期刊的共112篇文章。

研究结果指出了IT和RM的重要性, 以及对消费者方面的重视。此外, 本研究还指出了技术不是人类的敌人– 技术能够弥补以及对人类原有的工作增添价值。

本研究未将涉及IT和RM的书和会议文章纳入样本。此外, 只有英文的期刊文章构成研究样本。对研究样本的主题归类是主观性的。

本论文梳理了2008年至2018年发表的文献, 以及帮助酒店实践者们对RM科技从需求方面更了解其商务环境。

本论文基于服务供应者（酒店）和用户（消费者）在IT和RM交互平台上, 提出了过去十年中相关的八大关键因素。

The purpose of this study is to examine hotel guests’ attitudes toward guest room technologies (GRTs) and determine whether hotel guests’ characteristics and attitudes regarding GRTs vary according to hotel guest typologies.

The data were gathered from a sample of 508 hotel guests who had stayed in a hotel in the past 12 months via a self-administered survey on Qualtrics survey software. The analysis of the study consisted of two main research steps: identification of cluster groups via the K-means cluster analysis algorithm and discriminant analysis; and performing a series of chi-square analyses to determine whether hotel guests’ characteristics and attitudes vary according to obtained hotel guest typologies.

Results indicated significant attitudinal (e.g. internet payment preference) and demographic (e.g. age) differences among the obtained hotel guest typologies regarding their attitudes toward GRTs.

The results provide valuable guidance and a pragmatic approach for those hotel managers that aim to generate tailored marketing strategies for guest segments that are interested in GRTs.

This study concentrates on GRTs with a market segmentation approach by using advanced statistical procedures. It contributes to the body of related research literature by offering empirical evidence where the study evaluates the impact of the availability of new GRTs on guest decision-making based on the principles of the theory of planned behavior. Practitioners will be able to use the presented findings to generate marketing and pricing strategies with respect to the technological needs and wants of each typology.

本论文主要研究酒店顾客对客房科技（GRTs）的态度以及检验顾客特点和背景情况对GRTs的态度是否有不同的影响。

研究样本包括508位在过去12个月内消费过的酒店顾客, 样本通过在线自助式问卷来采集。本论文的分析步骤分为两步：（1）通过K-means聚类分析和判别分析以确立群组, 以及（2）一系列Chi-square分析以判定酒店顾客特点和态度是否根据获得的顾客背景情况而有差别。

研究结果表明在获得的酒店顾客背景情况中, 态度型因子（比如网络支付喜好）和人口统计类型因子（比如年龄）对于酒店顾客GRTs态度有显著差异。

研究结果对酒店经营者针对不同细分市场对GRTs的喜好来制定个性化营销战略有着珍贵指导和实践的启示意义。

本论文主要通过一系列高级统计操作来研究GRTs以及市场细分方法。研究结果对相关文献有着显著价值, 对以计划行为理论 （Theory of Planned Behavior）为基础, 检验新型GRTs对顾客决策行为的影响提供了实践研究。行业实践者能够借鉴研究结论来制定与科技需求和细分市场需求相关的营销和定价战略。

酒店技术；客房技术；房间内部技术；市场划分；付款意愿；决策

纸张类型–研究论文

This study aims to gain an understanding of hotel experiences during the pandemic by examining sentiments of guests posted online.

This paper incorporates the balance theory, in a dyadic system to analyze the ways in which guests were motivated to restore a position of balance during the unprecedented COVID-19 crisis. Qualitative content analysis was used to detect thematic patterns of hotel experiences based on examining online reviews shared by actual guests of two major hotel brands – one more closely associated with convenience-driven automation (high-tech) and the other known for providing more guest–employee interaction (high-touch).

The analysis of the reviews yielded six main themes: “purpose of visit,” “COVID safety concerns,” “technology adoption,” “COVID limitations,” “exceeded expectation” and “hospitality of staff.” Staff displaying a welcoming attitude was the main factor in creating a convivial experience for guests at both hotel brands, but the technology was not highlighted as much in guests’ reviews. Despite the pandemic, guests of both hotel brands had similar levels of enjoyment regarding their hotel experiences regardless of the high-touch or high-tech nature of the operations.

User-generated content often reflects the opinions of those who are very satisfied or not satisfied at all. Different data collection techniques could be used to get a “big picture” view of the balance between high-touch and high-tech experiences.

The findings offer support to researchers and practitioners who advocate that high-touch and high-tech can indeed co-exist, and that these distinct service delivery modes do not have to be mutually exclusive.

This paper provides new trajectories that can broaden the approaches undertaken by hospitality/tourism scholars and practitioners based on user-generated content. This study is one of the first to adopt the lens of the balance theory, in a dyadic system, to investigate how guests may be psychologically motivated to balance their perceptions and expectations during a time of crisis.

A review of past scholarly work on pricing issues in hospitality has revealed a lack of focus on customers’ demographic profiles. However, research in other disciplines reveals that understanding price perception differences among groups of customers with different demographics, including culture, is an important consideration when offering pricing strategies. The purpose of this paper is to contribute to the body of pricing research by exploring the effect of hotel guests’ demographics on their perception of hotel room prices.

Through Qualtrics, data were collected from 414 respondents who stayed at a mid-scale hotel within the past 24 months. The respondents’ perceived value (PV), perceived fairness (PF) and willingness to pay (WTP) for hotel rooms were examined with MANOVA and ANOVA tests to determine the effects of customer demographics on these variables.

Age, gender and marital status showed a significant effect on PV while age, gender and culture significantly affected PF. However, none of these variables significantly affected WTP. The culture of origin and the culture raised-in influenced PV, PF and WTP similarly.

This study reconciles several divergent results from previous studies and extends the scope of others by introducing different scenarios to each of the three dependent variables. To the best of the authors’ knowledge, it is also the first research study on this subject to evaluate more than two cultures and their effects on the independent variables.

The purpose of this study is to develop a typology of social media messages to compare the effectiveness of different message strategies.

In total, 1,837 messages from 12 hotel brand Facebook pages were content-analyzed. Applying both correspondence analysis and multivariate analysis of variance, the study compared message strategy across hotel-scale levels and explored the effectiveness of different message strategies.

A typology of four-type message format and six-type message content was developed. The picture message was the best message format. Product, brand and involvement messages were shown to be more effective than information, reward and promotion messages. Promotion message was the least effective message content type.

The major limitation of this study is the generalizability owing to the sample selection process. There is also the limitation on exclusion of control variables, selection of the three effectiveness measures and evolving social media technology.

The typology of Facebook message strategy developed in the study provided guidelines for hotel marketers to create messages on Facebook pages and track effectiveness. Hotels should also take full advantage of the picture format and product, brand and involvement contents.

This study created a new typology of social media message strategy consisting of two dimensions. It also provided empirical evidence to support the application of message strategy theory in the hotel social media marketing area.

This study examined the antecedents of technostressors as well as how customers' perceived convenience and technostressors of using a check-in/out kiosk influence their behavioral intention in a full-service hotel setting.

Using survey data collected from 630 hotel customers, hypotheses were tested via structural equation modeling and multi-group analysis.

The results showed that perceived usefulness of a check-in/out kiosk had direct effects on both technostressors (i.e. work overload and role ambiguity), and that perceived ease-of-use had indirect effects on the technostressors, via perceived usefulness. The findings showed that both role ambiguity and perceived convenience significantly influenced intention to use a check-in/out kiosk. Intention to use was positively associated with intention to revisit a hotel providing the kiosk. These findings were equivalent across the younger and older groups.

Based on the findings, hotels can implement effective strategies to reduce technostressors associated with a check-in/out kiosk and focus on enhancing the factors that influence customer acceptance of the system. This is especially important given the increased emphasis on self-service technology since the onset of the COVID-19 pandemic.

This research contributed to the relevant literature by developing a check-in/out kiosk acceptance model using a multi-theoretical approach, and empirically testing it within the full-service hotel domain. It fills the knowledge gap regarding the antecedents and outcomes of technostressors in the hospitality research literature by providing empirical evidence.

The purpose of this study is to explore whether five factors drawn from the unified theory of acceptance and use of technology (UTAUT) and UTAUT2 significantly influence customers' intention to use hotel in-room voice assistants (VAs). It further examined culture as a moderator of the relationships between the five factors and customers' intention to use.

The authors collected data from US and Singapore to examine cultural differences in customer acceptance of in-room VAs. All hypotheses were tested via structural equation modeling and multi-group analysis.

The results showed that performance expectancy, social influence and hedonic motivation significantly affected customers' intentions to use in-room VAs, while effort expectancy and facilitating conditions did not. The results confirmed that culture did not play a substantial role in moderating the relationships between these factors and intentions to use.

This study established that the instrument and structural paths in the research model were equivalent across two samples from different countries. The findings may not generalize to other countries as the data arises from customers in the US and Singapore.

The findings provide important implications for hotel operators and vendors seeking to enhance customer acceptance of in-room voice technology.

This study addresses the gaps of extant research by developing and testing a research model to better understand the influential factors of in-room VA adoption within the hotel domain.

The dynamic yet volatile nature of tourism and travel industry in a competitive environment calls for enhanced marketing intelligence and analytics, especially for those entities with limited marketing budgets. The past decade has witnessed an increased use of user-generated content (UGC) analysis as a marketing tool to make better informed decisions. Likewise, textual data analysis of UGC has gained much attention among tourism and hospitality scholars. Nonetheless, most of the scholarly works have focused on the singular application of an existing method or technique rather than using a multi-method approach. The purpose of this study is to propose a novel Web analytics methodology to examine online reviews posted by tourists in real time and assist decision-makers tasked with marketing strategy and intelligence.

For illustration, the case of tourism campaign in India was undertaken. A total of 305,298 reviews were collected, and after filtering, 276,154 reviews were qualified for analysis using a string of models. Descriptive charts, sentiment analysis, clustering, topic modeling and machine learning algorithms for real-time classification were applied.

Using big data from TripAdvisor, a total of 145 tourist destinations were clustered based on tourists’ perceptions. Further exploration of each cluster through topic modeling was conducted, which revealed interesting insights into satisfiers and dissatisfiers of different clusters of destinations. The results supported the use of the proposed multi-method Web-analytics approach.

The proposed machine learning model demonstrated that it could provide real-time information on the sentiments in each incoming review about a destination. This information might be useful for taking timely action for improvisation or controlling a service situation.

In terms of Web-analytics and UGC, a comprehensive analytical model to perform an end-to-end understanding of tourist behavior patterns and offer the potential for real-time interpretation is rarely proposed. The current study not only proposes such a model but also offers empirical evidence for a successful application. It contributes to the literature by providing scholars interested in textual analytics a step-by-step guide to implement a multi-method approach.

The current study aims to investigate hotel guests’ intention to use virtual reality (VR) and willingness to pay more for hotels that have VR applications (e.g. virtual room tour) when booking a hotel.

Through a theoretical lens of stimuli–organism–response (S-O-R), relationships among an individual’s performance expectancy, effort expectancy, social influence, utilitarian motivation, hedonic motivation, perceived value, intention to use VR and willingness to pay more for VR were tested using partial least square-structural equation modeling.

Performance expectancy, social influence, utilitarian motivation and hedonic motivation affect the perceived value of VR. An individual’s perceived value of VR affects his/her intention to use VR and willingness to pay more for a hotel that has VR contents (e.g. virtual room tour) available during the hotel booking process.

Through the S-O-R framework, this study provided insights into hotel guests’ intention to use VR and explored how their intentions lead to their willingness to pay more for a hotel if VR is available during the reservation or hotel selection process.

探索VR应用对酒店收益管理的影响

本论文旨在检验酒店客人使用VR和愿意预定提供VR应用（比如, 参观虚拟房间）的酒店房间。

通过基于S-O-R理论基础, 本论文搭建了模型, 描述个人绩效期望、努力期望、社交影响、实用型动机、和享乐型动机、感知价值、VR使用意图、和VR溢价支付意愿等相互关系, 使用PLS-SEM方法检测模型。

研究结果表明, 绩效期望、社交影响、实用型动机、和享乐型动机对VR的感知价值都有影响。个人对VR感知价值对其使用VR和愿意预定提供VR应用（比如, 参观虚拟房间）的酒店房间。