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The purpose of this paper is to understand the online communication strategies used by destination management organizations (DMOs) during a terrorist attack. In particular, this study analyzes Twitter use during seven terrorism incidents in six European cities (Paris, Brussels, Nice, Berlin, London and Barcelona) between 2015 and 2017.

Twitter content was collected via NCapture, a web browser extension of NVivo, one week prior to the attacks, the day of, and two weeks following to determine the timeframe in which DMOs communicated about the crisis, the types of messages being communicated, and whether these messages are effective. This study uses Coombs’ Situational Crisis Communication Theory as a guide to analyzing the effectiveness of the crisis communication strategies.

The findings of this paper indicate that DMOs are not effectively using Twitter during a terrorist attack. Few tweets relating to the attacks provided tourists with information regarding their safety, with the remaining only communicating as victims. Many DMOs went offline in the days immediately following the attacks and each DMO’s crisis communication on Twitter only lasted up to one week following the attacks.

This study provides insight into the ways DMOs are using social media for crisis communication. These results inform DMOs on their responsibility in communicating information during a terrorist attack. Messages of support are useful in the recovery stage, but tourists need information on how to stay safe and Twitter is often the first source people go to for information (Simon et al., 2014).

Recent tourism research has adopted social media analytics (SMA) to examine tourism destination image (TDI) and gain timely insights for marketing purposes. Comparing the methodologies of SMA and intercept surveys would provide a more in-depth understanding of both methodologies and a more holistic understanding of TDI than each method on their own. This study aims to investigate the unique merits and biases of SMA and a traditional visitor intercept survey.

This study collected and compared data for the same tourism destination from two sources: responses from a visitor intercept survey (n = 1,336) and Flickr social media photos and metadata (n = 11,775). Content analysis, machine learning and text analysis techniques were used to analyze and compare the destination image represented from both methods.

The results indicated that the survey data and social media data shared major similarities in the identified key image phrases. Social media data revealed more diverse and more specific aspects of the destination, whereas survey data provided more insights in specific local landmarks. Survey data also included additional subjective judgment and attachment towards the destination. Together, the data suggested that social media data should serve as an additional and complementary source of information to traditional survey data.

This study fills a research gap by comparing two methodologies in obtaining TDI: SMA and a traditional visitor intercept survey. Furthermore, within SMA, photo and metadata are compared to offer additional awareness of social media data’s underlying complexity. The results showed the limitations of text-based image questions in surveys. The findings provide meaningful insights for tourism marketers by having a more holistic understanding of TDI through multiple data sources.

This chapter discusses the current risk perception literature in the tourism field. The chapter critiques the literature and offers a solution through a more conceptual and operational definition of risk perceptions. Specifically, the inclusion of affective risk perceptions will be added to the literature via the risk-as-feelings hypothesis. Extension of the current literature will enhance research moving forward.

The chapter will provide a literature review, propose a conceptual model, and operationalize the risk perception variables.

The outcome of this chapter is to provide a conceptual model as a framework to address risk perception studies in tourism and hospitality in the future. The model will provide clear measurement scales to be tested.

This chapter gives a much needed theoretical and conceptual foundation to the study of risk perceptions in the travel and tourism literature.

This chapter begins with an exploratory approach to understanding how online branded video results in positive impressions among viewers. Scholars have examined the characteristics of videos that contribute to their appeal (e.g. Ashley & Tuten, 2015; Berger & Milkman, 2012; Botha & Reyneke, 2013; Dafonte-Gomez, 2014; Southgate, Westoby, & Page, 2010). Separate strands of literature have identified social practices and emotions likely to influence the perceptions of branded content. This chapter bridges the gap between those two strands by asking which social practices produce the emotions that lead to greater enjoyment of a video. Using a series of multiple regressions, we constructed a path analysis model linking key social practices and emotions that lead to positive evaluations of branded videos. The model provides strategic direction for the makers of online branded video.

It has been suggested that brands and products often assume a role in selfies (Ham, 2014) where the expression of brands and products provokes consumer emotions that bring about greater engagement (Tsai and Men, 2013) and contributes to the interactivity with the brands. This study aims to understand how the selfie phenomenon could mobilize the interactivity between brands and target audiences, in a way that could be used as a marketing tool by companies.

A netnographic research methodology was used for the current study because it is a method specifically designed to study online communities (Kozinets, 2010). The experiences of brand selfie postings on Instagram were studied by analyzing users’ selfies to predict brand usage. A purposive sample of Instagram users was chosen, and from these, a total of 74 brand selfies were analyzed.

This study provided an understanding of consumer behavior and marketing practices in the social marketplace through a detailed exploration of the data using visual and textual analysis. The main finding of this study is that consumers both consume and produce brand meanings in digital platforms; hence, companies should view them not only as passive receivers of messages, but also potential generators and co-creators of brand messages.

An important limitation of this study is that it only examines a small number of cases, and conclusions can only be limited to the specific sample chosen. A future research endeavor could of course be carried out to include a larger sample audience for investigating the effect of brand selfies and the potential purchase decisions of peers following exposure. Theoretically, this study provided further insight into the selfie phenomenon and specifically as a marketing tool and not just a new social trend.

The growing trend in the selfie phenomenon along with social networking sites (hereinafter SNSs) have attracted the attention of both users and marketing experts in terms of consumer–brand relationship (Zhu and Chen, 2015). In line with this current trend, many studies have attempted to understand the influential impact of the selfie phenomenon through SNSs. Studies on the motivation of selfie postings (Pounders et al., 2016) and selfie-posting behavior on SNSs (Kim et al., 2016) have been carried out; however, how brand selfies posted on SNSs appeal to non-users and how they interact with them remain unclear. Consequently, the intention of the current study is to provide some insight in this area.

Social media platforms are important channels to create a favourable customer experience. The purpose of this paper is to investigate the types of experiences customers can have with the branded content on social media.

Data were collected from 20 participants using semi-structured interviews. Thematic analysis was used to analyse the qualitative data.

The results identify seven types of branded content experience which are evoked when customers interact with branded content on social media. The results also suggest that branded content experience acts as a driver of consumer engagement with branded content which eventually leads to customers' sense of virtual community.

The findings provide theoretical implications for content creators. Further research should aim at comparing the branded content experience on different social media platforms and across different product categories.

This study contributes to customer engagement and experience literature in social media content by enhancing the understanding of branded content experience concept and its conceptual relationship with customer engagement in the social media context.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2019-0333

Although recent research appreciates that consumers increasingly interact with brands in brand communities and that brand engagement is an important and complex phenomenon in brand communities, little is known about the nature of individuals’ brand engagement in brand communities. This study aims to identify brand community members’ segments in terms of their brand engagement within the community; help us understand if these segments use a different approach in the development of brand loyalty; and develop mechanisms that can be used to identify members of these segments.

The paper adopts a quantitative approach and uses a total of 970 responses from members of Facebook brand pages in three popular languages on Facebook (English, French and Spanish). Data are analysed with structural equation modelling, integrating FIMIX-PLS and POS-PLS.

The results reveal that cognitive, affective and behavioural engagement dimensions play a different role in driving brand loyalty. Three different segments of engaged consumers exist (emotional engagers, thinkers and active engagers). Variables related to the perceived value of the brand community provide initial explanations as to the differences of the consumer groups.

The data were collected from a specific type of brand communities (Facebook-based, company-managed brand communities) and are self-reported.

This work demonstrates the heterogeneity of brand community members in terms of their brand engagement profile and the effect of this profile on the formation of behavioural brand loyalty. Suggestions on identifying members of these segments based on the value that they get from the community are offered.

This work extends the brand engagement and brand community literature. It is the first work that provides this nature of actionable suggestions to the teams supporting brands with brand communities.