Jason L. Stienmetz

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.

Tourism is central to late-modern life, and tourism research that threatens this centrality is prone to media attention. Framed by sociotechnical transitions theory, we introduce the concept of ‘shadowcasting’ to show how tourism knowledge disseminated through the media, combined with public comments on its reporting, cast shadows that co-constitute imagined futures. We illustrate shadowcasting through a mixed method approach that demonstrates how media reporting and public comments on a recent paper on autonomous vehicles in tourism emerged and diverged from the original paper. Our findings reveal that issues around sex and terrorism were sensationalised, generating diverse public discourses that challenge linear visions of future transport efficiency. Our concluding discussion indicates other tourism research contexts that are most inclined to shadowcasting.

The advent of increasingly pervasive automation of front-of-house restaurant service processes calls for a cross-cultural examination of employee roles in robotised service encounters. Through an ethnographic approach this study explores robotised service encounters in two culturally distinct contexts: the US and Japan. Five roles service employees may assume are observed to varying degrees of importance depending on cultural context: enabler, coordinator, differentiator, educator, and innovator. The roles of enabler and coordinator seem the most dominant in Japan, while in the US the future of work in restaurants seems more skewed towards the roles of educator and innovator. Implications for hospitality management are discussed, and an agenda for future research is presented.

A survey of 780 UK residents was conducted to identify the extent to which perceived peer-to-peer (P2P) accommodation development is associated with changes in community members’ well-being from economic, social and environmental perspectives, and to understand in which circumstances P2P listings have positive and negative effects on community members’ well-being. Partial least squares analysis demonstrates that the perceived positive community impacts of P2P accommodation are more pronounced than the perceived negative impacts. Additionally, weak but statistically significant effects of perceived P2P accommodation prevalence on residents’ social and environmental well-being are observed. Based on these findings and in accordance with social exchange theory, both policy makers and the P2P accommodation sector should develop strategies to enhance the perceived positive impacts on residents’ well-being and mitigate the perceived negative impacts.

Abstract
Purpose
The impact of demand fluctuation during crisis events is crucial to the dynamic pricing and revenue management tactics of the hospitality industry. The purpose of this paper is to improve the accuracy of hotel demand forecast during periods of crisis or volatility, taking the 2019 social unrest in Hong Kong as an example.

Design/methodology/approach
Crisis severity, approximated by social media data, is combined with traditional time-series models, including SARIMA, ETS and STL models. Models with and without the crisis severity intervention are evaluated to determine under which conditions a crisis severity measurement improves hotel demand forecasting accuracy.

Findings
Crisis severity is found to be an effective tool to improve the forecasting accuracy of hotel demand during crisis. When the market is volatile, the model with the severity measurement is more effective to reduce the forecasting error. When the time of the crisis lasts long enough for the time series model to capture the change, the performance of traditional time series model is much improved. The finding of this research is that the incorporating social media data does not universally improve the forecast accuracy. Hotels should select forecasting models accordingly during crises.

Originality/value
The originalities of the study are as follows. First, this is the first study to forecast hotel demand during a crisis which has valuable implications for the hospitality industry. Second, this is also the first attempt to introduce a crisis severity measurement, approximated by social media coverage, into the hotel demand forecasting practice thereby extending the application of big data in the hospitality literature.

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.

Design is now considered a crucial activity in contributing to the success of tourism enterprises as well as destinations. This article builds upon the ideas first introduced in the two edited books, namely Design Science in Tourism and Analytics in Smart Tourism Design, which brought the conceptual and methodological foundations for designing tourism places to the forefront of tourism literature. Specifically, this article first introduces the intellectual background that dates back to Clare Gunn's seminal work on Vacationscape, which has evolved into a systematic approach that incorporates tools developed in psychology, behavioral economics, marketing, management and more recently data sciences. It then describes the tourism design system as a general framework, followed by a discussion on the nature and role of smart tourism in enhancing this framework. The article then introduces the Curated Series on Tourism Design by identifying a group of articles published in the Journal which address many essential issues shaping the future of the tourism industry.

This open access book is the proceedings of the International Federation for IT and Travel & Tourism (IFITT)’s 28th Annual International eTourism Conference, which assembles the latest research presented at the ENTER21@yourplace virtual conference January 19–22, 2021. This book advances the current knowledge base of information and communication technologies and tourism in the areas of social media and sharing economy, technology including AI-driven technologies, research related to destination management and innovations, COVID-19 repercussions, and others. Readers will find a wealth of state-of-the-art insights, ideas, and case studies on how information and communication technologies can be applied in travel and tourism as we encounter new opportunities and challenges in an unpredictable world.