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As scholarly research in online purchasing increases in size and scope, understanding the manner in which consumers engage during online purchasing in hotels is critical. The purpose of this study is to provide an analysis of the current online purchasing research pertaining to the hotel industry.

A content analysis was conducted of 85 peer-reviewed articles published between 2006 and 2016 in hospitality and tourism journals to uncover the most critical aspects of online purchasing in hotels. Keyword searches and specific search parameters (e.g. literature time frame and locus of search) guided the review of the articles selected for the analysis.

This study recognizes that the discrete transaction per se represents the focal element in the hospitality scholarly research in online purchasing. It also recognizes the importance of the overall encompassing hospitality experience in creating and appropriating value for all stakeholders. Finally, the review found a strong orientation toward self-reported survey data as indicative of online transactions and the steps that precede them online.

The study recognizes the present focus on discrete transactions and recommends expanding the focus to tap into more comprehensive purchasing processes that are mediated by technology.

The analysis presented here offers practitioners insight into the value chain member and consumer behaviors that could be feasibly converted into actionable managerial practices.

In contrast to the reviews discussing online purchasing, this study provides a unique broad analytical perspective on the relationships among buyers, sellers, products, retail interfaces and consumer decision processes that characterize the hotel online purchasing environment, as reflected in the past 10 years of hospitality and tourism literature.

This study aims to explicate consumers’ intentions to use online food delivery systems (OFDS) subscription services. The study revisited the unified theory of acceptance and use of technology.

A typical methodology that involved a confirmatory factor analysis, followed by structural equation modeling, was used to test the hypotheses using a sample of 573 OFDS users from the USA.

The results revealed that social influence has the most significant impact on consumers’ intentions to use OFDS subscription services, while effort expectancy and perceived security have relatively lower impacts on consumers’ intentions to use OFDS subscription services. In addition, the study revealed the role of compatibility and convenience orientation in shaping consumers’ OFDS system perceptions (e.g. performance and effort expectancy).

The results provide several theoretical and managerial implications and open new avenues for future research. The study advances the literature by validating the set of antecedents of important core perceptions (e.g. performance expectancy and effort expectancy). The study also provides implications for two types of practitioners, such as OFDS and restaurants.

To the best of the authors’ knowledge, this is the first study to examine consumers’ intentions to use OFDS subscription services. This study is also the first to examine key factors influencing consumers’ intentions to use OFDS subscription services.

本研究旨在阐明消费者使用在线订餐（OFDS） 订阅服务的意图。该研究重新审视了 Unified Theory of Acceptance and Use of Technology 理论（UTAUT2）。

本研究采用典型的量化研究方法, 包括确认性因子分析和结构方程建模, 并使用来自美国的573名OFDS用户的样本来测试假设。

结果显示, 社会影响对消费者使用OFDS订阅服务的意图具有最显著的作用, 而努力期望和感知安全对消费者使用OFDS订阅服务的意图影响较小。此外, 研究揭示了兼容性和便利性取向在塑造消费者对OFDS系统感知（例如, 性能和努力期望）方面的作用。

研究结果提供了多方面的理论和管理启示, 并为未来研究开辟了新的途径。本研究通过验证重要核心感知（例如, 性能期望和努力期望）的前因完善了相关文献。另外, 本研究还为OFDS和餐厅等两类从业者提供了重要启示。

本研究是第一个调查了消费者使用OFDS订阅服务意图的研究, 也是首次研究了影响消费者使用OFDS订阅服务意图的形成因素。

As social distancing procedures can be facilitated by various hotel technologies, the purpose of this paper is to investigate the extent to which consumers develop perceptions of value regarding the use of certain hotel technologies for social distancing in hotels.

Drawing from the social exchange theory, this study conceptualized the benefits of using technologies for social distancing, health risks, social rewards and privacy concerns as antecedents of value of using technologies for social distancing in hotels. The structural model was validated by using data from more than 1,000 nationwide US consumers.

Benefits and consumers’ privacy concerns of using technologies for social distancing in hotels were the strongest predictors of value. Social rewards also had a significant but relatively lower effect on value. Health risks was found to have no influence on value.

The study is the first to examine the role of technologies in mitigating the effects of coronavirus. Thus, it extends the information technology and hospitality literature by examining the role of these technologies in safeguarding individual and public health.

The purpose of this study was to validate a conceptual model that examined consumers’ intentions to use hotel interactive technologies (HINT) and their conversion behaviors in hotels. The model was built on consumers’ participation in consumer–firm interactions, their level of innovativeness and their perceived benefit of using interactive technologies as antecedents of intentions and conversion.

The conceptual model was built upon the service-dominant (S-D) logic, technology adoption, social psychology and marketing theory. Using structural equation modeling, the model was validated using a nationwide sample of 841 consumers who have stayed in hotels that offered interactive technologies.

Consumers’ information system habit and hedonic motivations influenced their participation in consumer–firm interactions when using HINT. In turn, participation and innovativeness influenced conversion behavior, while innovativeness and perceived benefit of using interactive technologies influenced intentions to use such technologies.

This study extends the S-D logic, technology adoption, social psychology and marketing literature by validating a model that blends system perceptions, consumer characteristics and information system-related behaviors to explicate intentions and conversion. Thus, this study illustrates the modeling/evaluation of such blended models.

The study provides hoteliers a layout of the factors influencing consumers’ intentions to use interactive technologies and conversion. It also explains how participation in consumer–firm interactions and perceived benefit have contrasting roles in influencing consumers’ intentions and conversion behavior.

This study examined two distinct concepts that reflect the value co-created in hotel settings due to technology-based consumer–firm interactions: consumers’ intentions to use interactive technologies and their actual conversion behavior. The study also recognized the pivotal role of participation in influencing conversion and emphasized the contrasting roles of participation and perceived benefit in influencing longer-term (i.e. intentions) and short-term (i.e. conversion) behavior.

The purpose of this study was to investigate the impact of several hotel promotional factors and consumers’ behavioral and demographic characteristics on their actual use of specific interactive information systems in hotels. The specific systems examined in this study were a hotel’s website, mobile app, push notification system, kiosk, smart TV in room, and tablet at front desk or in room.

A survey was conducted with a sample of 841 respondents who had stayed in a hotel that had interactive information systems. Logistic regression models were designed with the promotional factors (e.g. hotel staff encouraging purchasing products, push notifications or information presented on mobile devices or kiosks, seeing or hearing about other consumers using systems, advertising and press releases), behavioral variables (e.g. frequency and duration of stay) and demographic variables (e.g. gender and age) as independent variables. The independent variables were the individual systems used by guests.

The various promotional factors had a differential effect on consumers’ use of various interactive information systems. Information provided on mobile devices, staff encouraging purchasing and press releases and blogs, along with age and duration of stay, was found to have the highest impact on system usage.

This study examines for the first time, as per the authors’ knowledge, the actual use behavior of several hotel interactive systems, thus advancing the technology adoption literature. This study also utilizes a comprehensive list of hotel promotional factors that are able provide theoretical and empirical insight into the use of interactive systems, which was explained predominantly based on system perceptions and consumers’ characteristics.

本论文旨在研究若干酒店营销因素和消费者行为特征和统计人口特征对真正使用互动性系统的影响。本论文主要研究的主体包括, 酒店网站、移动APP、推送信息系统、自助服务机器、房间智能TV、以及前台或房间的平板电脑。

取样方式为问卷调查, 其样本数量是841位曾在酒店使用过互动系统的顾客。逻辑回归模型结合营销因因子（如酒店人员销售产品、推送信息、或者移动设备或者自助机上显示的营销信息、经由其他消费者介绍、广告、新闻稿等）, 行为特征变量（如酒店居住频率和长短）, 以及统计人口变量（如性别和年龄）作为因变量。因变量包括顾客使用的 独立系统。

多个营销因子对消费者使用多个互动性信息系统有着不同的影响。其中, 移动设备上的营销信息、人员销售、新闻稿和博客、以及消费者年龄和酒店居住长短对系统使用有最显著的影响。

本论文首次检验酒店互动性系统的真实使用情况, 因此对科技使用文献有显著价值。本论文还全面检验了一系列酒店营销因子, 从理论和实践角度来检验互动系统使用情况, 延展了之前对系统感知和消费者特性的理解。

关键词：互动科技、实际科技使用、酒店、逻辑回归

研究论文

The unprecedented development of hotel-branded mobile applications (apps) has been instrumental in facilitating the rich guest–hotel interactions, thus contributing to a high personalization of services. For true personalization, guests need to provide personal information via apps. Yet, no study to date has addressed how guests develop intentions to use such apps given the current personalization and privacy challenges. Therefore, this study aims to investigate hotel guests’ intentions to use hotel apps to access personalized services.

Drawing from personalization-privacy theory, this study conceptualized perceived personalization and privacy concerns as distinct constructs while recognizing two different privacy concerns constructs: general and app-specific privacy concerns. To build a comprehensive structural model that is appropriate for explicating intentions to use hotel apps, this study incorporates consumer psychology and information systems theoretical streams that provide constructs that unequivocally capture the unique set of consumer–app interactions in highly experiential settings such as hotels (e.g. innovativeness and involvement). Using a nation-wide sample of hotel guests from the USA, the model was validated using confirmatory factor analysis and structural equations modeling.

The predictors explained 79 per cent of the variability in the intentions to use hotel apps to personalize hotel services. The strongest predictor of intentions was involvement, followed by app-related privacy concerns and perceived personalization.

First, this study’s extended theoretical framework was well supported, as it captures relevant elements of the mobile commerce ecosystem (e.g. personalization and privacy), thus extending the classic paradigmatic approach to information systems adoption beyond system beliefs. Second, this study clarifies the distinct roles of personalization and privacy in the context of hotel apps, which has not been examined in the context of m-commerce in hospitality. Third, the study clarifies the role of involvement as the most critical factor that can influence guests’ intentions to use hotel apps when personalization options and privacy concerns exist.

This study offers hotel decision-makers a mapping of the factors, leading to use of hotel apps for purchasing personalized hotel services.

This study provides a first theoretical perspective on the hotel app utilization behaviors that have not been studied so far, but carry a strong strategic and financial significance for the hotel industry (direct distribution, brand consolidation and extensive contact with guests).

Facial recognition systems represent a viable solution to today’s hotels’ security and service challenges. The purpose of this study was to build and empirically validate a conceptual model that examined consumers’ willingness to create a profile based on biometric information disclosed via facial recognition systems.

Data were collected from 421 US general population consumers who stayed in hotels. The study used a confirmatory factor analysis to test the measurement model and a structural equation modeling approach to empirically validate the structural model.

It was found that the benefit of information disclosure was the strongest predictor of value of disclosure and that value of disclosure and privacy concerns influenced consumers’ willingness to disclose biometric information. In turn, consumers’ willingness to disclose biometric information and their desire to be loyal to hotels influenced consumers’ willingness to create a profile.

To the best of the author’s knowledge, this is the first study to examine profile creation and biometric information disclosure via facial recognition systems in hotels, a technology that is likely to disrupt the current authentication and service quality models in hotels. This study also advances the literature by expanding the scope of the privacy calculus by adding social rewards, and by elucidating the role of desires in service contexts.

The purpose of this study is to provide an overview of how artificial intelligence (AI) and robotics can and will be utilized by the hospitality industry, providing a glimpse of what their use will look like in 2030.

The paper reviewed both academic and trade literature to provide an overview of how robots will affect the hospitality industry during the 2030s.

Experts predict that by 2030, robots will make up about 25 per cent of the “workforce” in the hospitality industry. The paper also explains the industry challenges the robots will solve, as well as other benefits they provide. One of the findings is that the adoption of robots by the industry will be a disruptive paradigm shift. It will create successful new hospitality companies while putting others out of business. Finally, this paper discusses how to keep the hospitality in hospitality businesses, when machines replace employees.

This paper is one of the first to discuss the disruption that robots will cause in the industry. One of the findings is service delivery systems will need to be redesigned to maximize the benefits of robots, while still maintaining the hospitality of a customer service orientation.

This study aims to examine hotel guests’ acceptance of technology agency – the extent to which they would let artificial intelligence (AI)-based systems make decisions for them when staying in hotels. The examination was conducted through the prism of several antecedents of acceptance of technology agency, including perceived ethics, benefits, risks and convenience orientation.

A thorough literature review provided the foundation of the structural model, which was tested using confirmatory factor analysis, followed by structural equation modeling. Data were collected from 400 US hotel guests.

The most important determinant of acceptance of technology agency was perceived ethics, followed by benefits. Risks of using AI-based systems to make decisions for consumers had a negative impact on acceptance of technology agency. In addition, perceived loss of competence and unpredictability had relatively strong impacts on risks.

The results provide a conceptual foundation for research on systems that make decisions for consumers. As AI is increasingly incorporated in the business models of hotel companies to make decisions, ensuring that the decisions are perceived as ethical and beneficial for consumers is critical to increase the utilization of such systems.

Most research on AI in hospitality is either conceptual or focuses on consumers’ intentions to stay in hotels that may be equipped with AI technologies. Occupying a unique position within the literature, this study discusses the first time AI-based systems that make decisions for consumers. The value of this study stems from the examination of the main concept of technology agency, which was never examined in hospitality.

The recent development of online food delivery systems (OFDS) consolidated the restaurant industry’s representation in the electronic distribution landscape. The purpose of this study is to examine consumers’ intentions to use OFDS.

A comprehensive structural model was developed based on UTAUT2 and extended the model with three additional constructs: impulse buying tendency, congruity with self-image and mindfulness. Data were collected from 605 US respondents. Confirmatory factor analysis and structural equation modeling were used to test the model.

Performance expectancy was the strongest predictor of intentions to use OFDS, followed by congruity with self-image. Low-magnitude predictors included habit and mindfulness, while impulse buying tendency had a negative impact on intentions to use OFDS.

The study validates a comprehensive yet parsimonious conceptual model that explains consumers’ intentions to use OFDS. The model brings together constructs that capture the essence of the online food ordering tasks and the consumers’ cognitive processes that inform such tasks.

This study offers substantial practical implications for two types of practitioners: OFDS developers and restaurants and provides a mapping of the factors influencing consumers’ intentions to use OFDS.

This study provides a first theoretical perspective on consumers’ intentions to use OFDS, which have not been studied so far. Studying such intentions provides insight into consumers’ adoption behaviors, which are critical to the success of OFDS.