Kyung Hyan Yoo

Use and impact of online travel reviews

Consumer-generated content (CGC) is growing in importance. Especially online travel reviews written by consumers are ever more available and used to inform travel-related decisions. A Web-based survey of users of the most prominent travel review site, TripAdvisor, was conducted to investigate how other travellers’ reviews inform the trip planning process. Since current CGC statistics show generational and gender differences, the study also aimed at examining whether those carry over into the realm of travel review use. The results show that reviews are used mostly to inform accommodation decisions and are currently not used much for en route travel planning. Gender differences were found for perceived impacts of reviews, with females reaping greater benefits from using reviews, especially in terms of enjoyment and idea generation. Age differences occurred across a variety of perceptions and use behaviours. Implications for travel marketing and travel information systems design are provided.

Comparison of Deceptive and Truthful Travel Reviews

As the use of online reviews grows, so does the risk of providers trying to influence review postings through the submission of false reviews. It is difficult for users of online review platforms to detect deception as important cues are missing in online environments. Automatic screening technologies promise a reduction in the risk but need to be informed by research as to how to classify reviews as suspicious. Using findings from deception theory, a study was conducted to compare the language structure of deceptive and truthful hotel reviews. The results show that deceptive and truthful reviews are different in terms of lexical complexity, the use of first person pronouns, the inclusion of brand names, and their sentiment. However, the results suggest that it might be difficult to distinguish between deceptive and truthful reviews based on structural properties.

Trust in Travel-related Consumer Generated Media

This study investigated the factors influencing trust in travel-related CGM and, in turn, the degree to whcih trust affects the benefits and impacts of using CGM in the course of planning pleasure trips. An online survey of US Internet users was conducted with a total of 1170 individuals responding to questions regarding their perceptions and use of CGM for travel planning. The findings show that CGM use is widespread and that trust depends on the type of Website on which the CGM is posted and perceptions of other CGM creators. Also, those who have greater trust in CGM report greater impacts and derive greater benefits from their CGM use.

Creating More Credible and Persuasive Recommender Systems: The Influence of Source Characteristics on Recommender System Evaluations

Whether users are likely to accept the recommendations provided by a recommender system is of utmost importance to system designers and the marketers who implement them. By conceptualizing the advice seeking and giving relationship as a fundamentally social process, important avenues for understanding the persuasiveness of recommender systems open up. Specifically, research regarding the influence of source characteristics, which is abundant in the context of humanhuman relationships, can provide an important framework for identifying potential influence factors. This chapter reviews the existing literature on source characteristics in the context of human-human, human-computer, and human-recommender system interactions. It concludes that many social cues that have been identified as influential in other contexts have yet to be implemented and tested with respect to recommender systems. Implications for recommender system research and design are discussed.

Travel opinion leaders and seekers

While opinion leadership has been recognized as important in tourism, there has been very little empirical research investigating the phenomenon. Given new developments in social media technologies, it is especially important to understand whether travel opinion leadership and seeking are drivers of specific social media perceptions and behaviours. Based on an online survey of US online travellers, this paper seeks to identify travel opinion leaders and seekers and their characteristics. Further, the research conducted investigated linkages between travel opinion leadership/ seeking and travel social media use. The findings suggest that travel opinion leadership and seeking are distinct but connected. Both opinion leaders and seekers are technology savvy, young, educated, involved in travel planning and engaged in social media use for travel. What distinguishes opinion leaders is their greater travel experience and greater trust in official sources of travel information.

Special section on generative smart tourism systems and management: Man–machine interaction

Tourists today can search information on their target regions, estinations, restaurants, and entertainment programs in realime, and often choose the places where people share their xperiences (Oliveira and Carlos, 2016). With the advent of smart echnologies, tourism is moving towards a new era that includes n ‘on-demand economy’ and a ‘sharing economy.’ These new henomena are based on Information and Communication Techologies (ICT), which have a significant influence on the operating ethods and processes involved in current travel-related indusries (e.g. AirBnB.com, Couchsufing.com, and Uber.com) (Gretzel, oo, Sigala, & Xiang, 2015). The on-demand economy implies instantaneousness” and “transparency” (Forbes.com, 2015). Varous applications enable the processing of travelers’ requests nstantly and transparently. Travelers can decide while they are on he move, such as “booking a hotel room” as they simultaneously heck hotel room availability and prices. Conversely, the sharing conomy focuses specifically on allowing the sharing of assets (e.g. ouses, cars, parking lots, etc.), thereby enabling a collaborative onsumption (Economist.com, 2013). This peer-to-peer rental has ecome cheaper and more convenient when facilitated by new echnologies. These phenomena have opened a new paradigm in he tourism industry, called ‘smart tourism.’ Explicitly, we can state hat smart means “optimized for a specific need” (Gretzel, Sigala, iang, & Koo, 2015) supplied by individual assets in a specific conext either on demand or real-time basis. With the growth of innovative businesses in tourism, travelelated activities and electronic commerce certainly require an nfrastructure, such as knowledge-based systems and management Werthner and Ricci, 2004), cloud computing (Gretzel, Sigala et al., 015), re-engineering processes (Law, Buhalis, & Cobanoglu, 2014), nd smart tourism systems (Werthner, Koo, Gretzel, & Lamsfus, 015). Because of the new systematic approach, tourism businesses re becoming more affordable. Werthner et al. (2015) stated that mart tourism should be understood as having the overall ingreients of smartness and systems integration with machine and anagement. We also assert that the notion of smart tourism ystems and management lies in digital networks, platforms, and evices that integrate current systems, connected technologies and achines for anyone, anywhere, and anytime while all travel rel-

Source Factors in Recommender System Credibility Evaluation

Although recommender system research in the last decade has provided significant insight into how users interact with and evaluate systems, the social role of recommender systems as advice givers has been largely neglected. By conceptualizing the advice seeking and giving relationship as a fundamentally social process, important avenues for understanding the persuasiveness of recommender systems open up. Specifically, research regarding the influence of source characteristics, which is abundant in the context of human-human communication, can provide an important framework for identifying potential influence factors. This chapter reviews the existing literature on source factors in the context of human-human, human-technology, and human-recommender system interactions. It also discusses system credibility evaluation in light of the increasing popularity of social technology. It concludes that many social cues that have been identified as influential in other contexts have yet to be implemented and tested with respect to recommender systems. Implications for recommender system research and design are discussed.

Measuring the Credibility of Recommender Systems

Recommender systems promise to support travelers in complex decision-making processes; however, whether a recommendation is seen as credible advice and actually taken into account not only depends on travelers’ perceptions of the recommendation but also the system as the advice-giver. Trust has been identified as an important factor in online relationships but it is often focused on security issues that are of lesser relevance for recommender systems. It is argued that conceptualizations of trust in terms of credibility are more important to evaluate the persuasiveness of recommender systems. The findings of a study to develop and test credibility measures for recommender systems are presented and implications for future research are discussed.