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Short-form videos have gradually become important marketing tools for tourist destinations. However, chaotic sources and homogenized content have led to poor user experiences. Taking Kulangsu and Xi'an City Wall in China as examples, this study explored the influence of matching short-form video sources with destination types on user engagement and visit intention.

This study selected three short-form videos from different sources for each destination on TikTok and conducted an empirical research using a 3 × 2 experimental design to examine the proposed research model.

The results showed that the matching effect between short-form video sources and destination types will positively affect user engagement and visit intention. (1) the short-form videos with user-generated content (UGC) or professional user-generated content (PUGC) in hedonic destinations can obtain higher user engagement and visit intention; (2) the short-form videos with professionally generated content (PGC) or PUGC in utilitarian destinations can obtain higher user engagement and visit intention and (3) perceived credibility and perceived usefulness played mediating roles in these interactions.

This study considers short-form video sources as antecedent variables influencing user engagement and visit intention and confirms the matching effect between short-form video sources and tourism destination types. The findings will help researchers and marketers better understand the impact of short-form video on destination marketing.

Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary information disseminators is limited. This paper aims to bring an in-depth understanding of voluntary disseminators by answering the following questions: (1) What is the underlying mechanism by which some users are more enthusiastic to voluntarily forward content of interest? (2) How to identify them? We propose a theoretical model based on the Elaboration-Likelihood Model (ELM) and examine three types of factors that moderate the effect of preference matching on individual forwarding behavior, including personal characteristics, tweet characteristics and sender–receiver relationships.

Via Twitter API, we randomly crawled 1967 Twitter users' data to validate the conceptual framework. Each user’s original tweets and retweeted tweets, profile data such as the number of followers and followees and verification status were obtained. The final corpus contains 163,554 data points composed of 1,634 valid twitterers' retweeting behavior. Tweets produced by these core users' followees were also crawled. These data points constitute an unbalanced panel data and we employ different models — fixed-effects, random-effects and pooled logit models — to test the moderation effects. The robustness test shows consistency among these different models.

Preference matching significantly affects users' forwarding behavior, implying that SNS users are more likely to share contents that align with their preferences. In addition, we find that popular users with lots of followers, heavy SNS users who author tweets or forward other-sourced tweets more frequently and users who tend to produce longer original contents are more enthusiastic to disseminate contents of interest. Furthermore, interaction strength has a positive moderating effect on the relationship between preference matching and individuals' forwarding decisions, suggesting that users are more likely to disseminate content of interest when it comes from strong ties. However, the moderating effect of perceived affinity is significantly negative, indicating that an online community of individuals with many common friends is not an ideal place to engage individuals in sharing information.

This work brings about a deep understanding of users' voluntary forwarding behavior of content of interest. To the best of our knowledge, the current study is the first to examine (1) the underlying mechanism by which some users are more likely to voluntarily forward content of interest; and (2) how to identify these potential voluntary disseminators. By extending the ELM, we examine the moderating effect of tweet characteristics, sender–receiver relationships as well as personal characteristics. Our research findings provide practical guidelines for enterprises and government institutions to choose voluntary endorsers when trying to engage individuals in information dissemination on SNS.

This study examined how marketer- and user-generated photographs jointly influence consumers' online hotel booking.

Viewing photographs as stimuli that influence consumers' online hotel booking, this study proposes a research model and validates that using one quasi-experiment.

The findings of this study provide some empirical insights. Marketers can release room- and scene-related photographs. Users can release product- and social-related photographs. The interaction between room-related photographs by marketers and product-related photographs by users can promote energetic arousal and dominance and then promote online booking intention. The interaction between scene-related photographs by marketers and social-related photographs by users can promote energetic arousal and dominance and then promote online booking intention. Pleasure, energetic arousal and dominance can positively influence the attitude toward photographs. Pleasure and energetic arousal can positively influence the attitude toward photographs and then positively influence booking intention. Dominance can positively influence booking intention.

The findings of this study reveal significant interaction effects between marketer- and user-generated photographs on consumers' online booking. The findings will help researchers and marketers better understand the impact of photographs on consumers' online hotel booking.

Today, individuals use social media to express their opinions and feelings, which offers a living laboratory to researchers in various fields, such as management, innovation, technology development, environment and marketing. It is therefore necessary to understand how the language used in user-generated content and the emotions conveyed by the content affect responses from other social media users.

In this study, almost 700,000 posts from Twitter (as well as Facebook, Instagram and forums in the appendix) are used to test a conceptual model grounded in signaling theory to explain how the language of user-generated content on social media influences how other users respond to that communication.

Extending developments in linguistics, this study shows that users react negatively to content that uses self-inclusive language. This study also shows how emotional content characteristics moderate this relationship. The additional information provided indicates that while most of the findings are replicated, some results differ across social media platforms, which deserves users' attention.

This article extends research on Internet behavior and social media use by providing insights into how the relationship between self-inclusive language and emotions affects user responses to user-generated content. Furthermore, this study provides actionable guidance for researchers interested in capturing phenomena through the social media landscape.

This paper aims to explore the causal relationship of user-generated content (UGC) on trust in UGC (TUGC), destination image (DI) and tourist visit intention (VI) guided by the stimulus-organism-response (SOR) theory. This work further examined the mediating effect of TUGC and DI between UGC and VI.

Data were collected through online and personal-administered surveys and randomized sampling. This work employed partial least squares structural equation modeling (PLS-SEM) to test the proposed model empirically.

In line with the SOR Theory, this work found UGCs that induce positive emotions and connection to the users motivate VI rather than UGCs that are predominantly factual. Furthermore, UGCs are considered reliable, authentic and less biased than brand-generated content. The findings of this work contribute to the theoretical understanding of UGC to VI in a destination.

This work proposes that destination marketers prioritize UGC that evokes positive emotions and connections with users, as it is more effective in encouraging VI. Strategies such as incentivizing content creators, improving online presence and engaging influencers can maximize UGC. Enhancing online traffic quality, visibility and interaction and implementing content policies are crucial for UGC's effectiveness. Marketers should align destination products with tourists' interests and collaborate with influencers for affiliate marketing to increase tourist-generated UGC. Furthermore, improved connectivity encourages UGCs about the destination.

In tourism marketing, UGC has become a valuable information source for tourists in making informed travel decisions. UGC is a tourist-generated content that offers factual information and authentic experiences through images, videos or text posted through social media platforms. UGC is considered more reputable than travel firms and the mainstream media as an information source. Due to the limited works on UGC in the literature, the influence of UGC on tourists' VIs has remained unexplored at the time of writing. This work bridges this gap by empirically examining the impact of UGC on Gen Z tourists' VI guided by the SOR theory.

Social participation and user-generated contents have engendered an era when “any receiver can be a provider.” Although studies have emphasized on increasing the number of subscribers conducive to platform success, the issue regarding why viewers drop their registered YouTuber channels has been less addressed. This article aims to present and empirically test a causal model to account for the pattern of discontinuous intention of attention to YouTuber channels.

Inspired by the expectation–disconfirmation theory, the study proposes and examines a research model by using an empirical quantitative approach. The proposed model considers channel and YouTuber facets, as well as potential moderation effects of viewing seniority.

Analysis of a sample of 406 questionnaires revealed that ads interference is not a significant reason for discontinuation of viewing a channel, in contrast to insufficient playfulness and inconsistency. Regarding YouTubers’ features, both interaction inadequacy and negative self-disclosure are significant determinants of perceived dissatisfaction and discontinuation of viewing. The effects of determinants of discontinuity depend on viewers' seniorities, except for negative self-disclosure.

While existing studies have focused mainly on revealing the determinants associated with the behavioral intention of viewing YouTuber channels to increase self-media performance, this research contributes insights into the literature investigating why existing viewers stop following a certain YouTuber channel. From a psychological perspective, this study demonstrates the value of modeling discontinuous behaviors toward YouTuber channels in the domain of social marketing.

The study investigates the factors that influence young consumers (Gen Zs and Ys) in emerging markets to engage fashion ads of non-luxury fashion retail small- to medium-size enterprises (SMEs) on social media. Through a desk assessment of practice and the phenomenon's available evidence in the extant literature, four main drivers were delineated, reviewed and subsequently tested to influence young consumers' behavioural engagements of emerging markets' fashion SMEs' social media contents.

A non-probability sample of 1,150 respondents (Gen Y and Z combined) in Ghana, an emerging market, formed the sample for the study. The respondents assessed four empirically identified antecedents (sales campaigns, relevant sales-related information, catchy and inspiring product/brand photo/video and consumer-generated contents) that are likely to influence their behavioural engagement on social media platforms (Instagram, Facebook, WhatsApp and Twitter). SmartPLS (version 3.3.3) was employed to perform partial least square structural equation modelling.

The results showed that to engage fashion-related ads, particularly from non-luxury fashion SMEs, young consumers consider sales campaigns, cues from consumer-generated contents, as well as quality and inspiring videos and photos. Less attention is given to relevant sales-related information.

The three significant drivers of engagement found in the current study provide managerial knowledge for non-luxury fashion SMEs in emerging markets. Videos and still pictures must be of high definition and quality. Short and long promotional campaigns may drive positive behavioural engagements. Interactivity between fashion SMEs and young consumers is encouraged as it precipitates the positive engagement behaviours enabled by social media. The study concludes with actionable recommendations for the non-luxury fashion SME sector in emerging economies.

The study is the first of its kind to ascertain what drives young consumers' engagement with non-luxury fashion SMEs on social media. It provides managerial insights and guidance to SMEs in emerging markets on effective social media fashion retailing targeted mainly at digital natives, the dominant generational cohorts on social media in most emerging economies.

Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and short-term perspectives, which includes brand diffusion, user-generated content (UGC), opinion leaders and brand events’ impact.

This study uses a mixed-method including text mining, keyword analysis and social network analysis to explore the brand formation process of four popular WHSs in Beijing, namely, the Palace Museum, Great Wall, Summer Palace and Temple of Heaven and more than 10,000,000 users’ data on Sina Weibo has been implemented to uncover the underlying social media branding mechanism.

The results show that the number of postings keeps in a stable range in most months, but, in general, there are no common rules for changing trends among the four WHSs; long-term high-frequency keywords related to history and culture account for a higher percentage; different kinds of accounts have varying impacts on information diffusion, in which media accounts lead to a bigger influence. However, more followers do not necessarily mean more interactions and most of the interaction ratio is much lower than 0.01000; brand events facilitate brand dissemination and have an impact on the creation of UGC.

This study is valuable for destination marketers to deeper understand brand diffusion and formation and provides valuable insights for developing effective destination marketing strategies.

Unlike previous studies that only concern a few parts of destination brand formation via social media (e.g. brand diffusion, brand events or opinion leaders’ impact), this study takes a more comprehensive perspective by systematically analyzing the brand formation process of WHSs on social media. By considering both long-term diffusion and short-term representative events, this study provides a more holistic understanding of the branding mechanism.

The aim of this research is to explore content, traffic and visibility on four social platforms to boost social visibility.

The study explores content, traffic and visibility in the context of Spanish beer brands. A sample of 3,332 beer brands' social media (SM) sites, specifically the four most commonly used platforms amongst Spaniards, was analysed. An inductive content analysis by a panel of experts identified the main contents. A cluster analysis then divided the significantly different beer brand SM sites, and a Kruskal–Wallis test confirmed the significant differences by content and traffic. To determine and predict SM visibility, a binary logistic regression was conducted.

The findings reveal that traffic is not significantly correlated with social visibility. Moreover, the SM sites with the highest traffic show significant leisure content. Twitter is significantly different network in traffic and content, whilst YouTube is the best for boosting social visibility.

The study's findings constitute valuable information in understanding how content, traffic and visibility are correlated and help in managing brands' public presence and exposure on SM.

This study contributes to the existing literature by exploring four SM platforms (Twitter, Instagram, YouTube and Facebook), two dimensions of SM interactions (traffic and social visibility) and three main focal points of contents (leisure, product and promotion). This research bridges the gap amongst content, traffic and social visibility and ascertains how to gain traffic and boost social visibility.

This study aims to investigate the influence of the reviewed establishment’s price level and the user’s social network size and reputation status on consumers’ tendency to post more visual imagery content. Furthermore, it explores the moderating effects of user experiences and geographic distance on these dynamics.

This study adopts a multi-method approach to explore both the determinants behind the sharing of user-generated photos in online reviews and their internal mechanisms. Using a comprehensive secondary data set from Yelp.com, the authors focused on restaurant reviews from a prominent tourist destination to construct econometric models incorporating time-fixed effects. To enhance the robustness of the authors’ findings, the authors complemented the big data analysis with a series of controlled experiments.

The reviewed establishments price level and the users reputation status and social network size incite corresponding motivations conspicuous display “reputation seeking” and social approval motivating users to incorporate more images in reviews. “User experiences can amplify the influence of these factors on image sharing.” An increase in the users geographical distance lessens the impact of the price level on image sharing, but it heightens the influence of the users reputation and social network size on the number of shared images.

As a result of this study, high-end establishments can increase their online visibility by leveraging user-generated visual content. A structured rewards program could significantly boost engagement by incentivizing photo sharing, particularly among users with elite status and extensive social networks. Additionally, online review platforms can enhance users’ experiences and foster more dynamic interactions by developing personalized features that encourage visual content production.

This research, anchored in trait activation theory, offers an innovative examination of the determinants of photo-posting behavior in online reviews by enriching the understanding of how the intricate interplay between users’ characteristics and situational cues can shape online review practices.