Service robots continue to permeate and automate the hospitality sector. In doing so, these technological innovations pose to radically change current service production and delivery practices and, consequently, service management and marketing strategies. This study explores the various impacts of robotization in the sector by offering one of the first empirical accounts on the current state-of-the-art of service robotics as deployed in hospitality service encounters. The results suggest that service robots either support or substitute employees in service encounters. They also offer hospitality businesses a novel point of differentiation, but only if properly integrated as part of wider marketing efforts. Finally, the automation of tasks, processes, and, ultimately, jobs has serious socioeconomic implications both at the microlevel and macrolevel. Consequently, hospitality executives need to consider where and how to apply robotization to strike a balance between operational efficiency and customer expectations. Displaying ethical leadership is key to reaping the benefits of the robot revolution.

As artificially intelligent conversational agents (ICAs) become a popular customer service solution for businesses, understanding the drivers of user acceptance of ICAs is critical to ensure its successful implementation. To provide a comprehensive review of factors affecting consumers' adoption and use of ICAs, this study performs a systematic literature review of extant empirical research on this topic. Based on a literature search performed in July 2019 followed by a snowballing approach, 18 relevant articles were analyzed. Factors found to influence human‐machine cognitive engagement were categorized into usage‐related, agent‐related, user‐related, attitude and evaluation, and other factors. This study proposed a collective model of users' acceptance and use of ICAs, whereby user acceptance is driven mainly by usage benefits, which are influenced by agent and user characteristics. The study emphasizes the proposed model's context‐dependency, as relevant factors depend on usage settings, and provides several strategic business implications, including service design, personalization, and customer relationship management.

Park, Nicolau, and Fesenmaier proposed the Destination Advertising Response (DAR) model as a means to more effectively evaluate destination advertising campaigns by incorporating the key decisions or components (i.e., facets) that comprise a trip. While this model appears to be an attractive alternative to traditional destination advertising evaluation, little research has been conducted to examine its validity. The goal of this study is to evaluate the potential usefulness of the DAR framework based upon current understanding of the travel decision-making process and industry practice. Additionally, the framework is evaluated based on a series of empirical analyses that consider the impact of destination advertising on the destination decision as well as on several trip-related decisions. The implications of this model for destination advertising are substantial in that it provides a much richer foundation for the development of destination marketing strategies.

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Mobile devices, such as smartphones, are fast becoming the primary way for many travelers to access the Internet in search of travel-related information. While mobile devices provide travelers with ubiquitous access to the Internet, they also face limitations, such as small screens and slow loading times, which destination management organizations (DMOs) must consider when designing mobile websites. This study investigates the factors influencing the overall usability of mobile DMO websites. Based on a sample of U.S. travelers with mobile devices, findings indicate that design elements related to Ease of Use and Content contribute most significantly to the overall usability of mobile DMO websites. Also, travelers highly value mobile DMO websites that are well structured and organized, offer convenient services, and have an easy-to-understand appearance. Managerial implications and areas for further research are discussed.

This study proposes that the structure of visitor flows within a destination significantly influences the overall economic value generated by visitors. In particular, destination network metrics (i.e., density, in-degree centralization, out-degree centralization, betweenness centralization, and global clustering coefficient) for 29 Florida counties were derived from 4.3 million geotagged photos found on the photo sharing service Flickr and then correlated with visitor-related spending reported by the Florida Department of Revenue. The results of regression analyses indicate that density, out-degree centralization, and in-degree centralization are negatively correlated with total visitor-related spending within a destination, while betweenness centralization is found to have a positive relationship. Based on these findings, it is concluded that the economic value generated by tourism is constrained by the destination network structure of supply-side and demand-side interactions. Further, it is argued that a "network orchestrator" approach to management can be used to better manage economic impacts within a destination.

Transactions through mobile commerce for tourism-related products and services are increasing. This phenomenon can lead to impulse buying due to technological features and personal inclinations. However, few studies have shed light on the phenomenon empirically. The purpose of this study is to investigate what motivates buyers to purchase tourism products through mobile commerce and how these motives impact consumers’ impulse buying behavior. First, we interviewed participants to study their motivation for mobile commerce application use. Then, we extracted the motivation factors and examined how these factors affect impulse purchase intentions for tourism products through mobile commerce applications. To do this, we administered a questionnaire survey. In addition, fuzzy-set qualitative comparative analysis (fsQCA) provided in-depth analysis of factors that can influence impulse buying. Results show that convenience and ubiquity have an effect on perceived value. Furthermore, perceived value, notice of special promotion, and impulsiveness have a direct effect on impulse buying behavior. According to the results of the fsQCA, not only impulsiveness but also other factors can serve as antecedents to impulse buying behavior.