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The paper’s main goal is to examine the relationship between the video marketing of financial technologies (Fintechs) and their vulnerable website customers’ brand engagement in the ongoing coronavirus disease 2019 (COVID-19) crisis.

To extract the required outcomes, the authors gathered data from the five biggest Fintech websites and YouTube channels, performed multiple linear regression models and developed a hybrid (agent-based and dynamic) model to assess the performance connection between their video marketing analytics and vulnerable website customers’ brand engagement.

It has been found that video marketing analytics of Fintechs’ YouTube channels are a decisive factor in impacting their vulnerable website customers’ brand engagement and awareness.

By enhancing video marketing analytics of their YouTube channels, Fintechs can achieve greater levels of vulnerable website customers’ engagement and awareness. Higher levels of vulnerable customers’ brand engagement and awareness tend to decrease their vulnerability by enhancing their financial knowledge and confidence.

Fintechs should aim to increase the number of total videos on their YouTube channels and provide videos that promote their customers’ knowledge of their services to increase their brand engagement and awareness, thus reducing their vulnerability. Moreover, Fintechs should be aware not to over-post videos because they will be in an unfavorable position against their competitors.

This research offers valuable insights regarding the importance of video marketing strategies for Fintechs in promoting their vulnerable website customers’ brand awareness during crisis periods.

The present article encourages urban tourism researchers use pre-recorded (like YouTube, TikTok and security camera footage) and self-recorded video data in research. The author highlighted the benefits of doing so for urban tourism scholars, as well as ways in which these investigators can use the observational video analysis technique to produce convincing findings and advance their field.

To accomplish the purpose, the author reviewed 25 scholarly articles on the topic from several fields.

One benefit of observational video analysis research (OVAR), the author highlighted, was the ability of scholars in different locations to simultaneously observe interactions, the focus of the study, in their natural setting and discuss them. This practice is not possible with traditional ethnographic research. Also, one way the author mentioned researchers can accomplish rigor in their OVAR project is through multimodal transcription. With multimodal transcription, verbal and non-verbal happenings in videos are transliterated and later analyzed.

It is hoped because of the present article, increased use of the technique in urban tourism research will be seen.

The present article is the first, to the best of the author’s knowledge, to detail how rigor can be accomplished in OVAR in urban tourism.

Fueled by the soaring popularity of the digital medium, consumers are increasingly relying on dynamic images to inform their decisions. However, little is known about how changes in the presentation of movement impacts these decisions. The purpose of this paper is to document whether and how movement speed–a fundamental characteristic of dynamic images in the digital medium–influences consumers' risk judgments and subsequent decisions.

Three experimental studies investigate the impact of movement speed displayed in the digital medium, focusing on different risk-laden domains including health (pilot study), gambling (Study 1) and stock market decisions (Study 2).

The authors find that faster movement speed displayed in the digital medium elevates consumers’ feelings of risk and elicits cautionary actions in response. The authors reveal a mechanism for this effect, showing that faster movement reduces feelings of control over outcomes, which predicts greater feelings of risk.

Future work could expand upon these findings by systematically examining whether certain individuals are more susceptible to movement speed effects in the digital medium. Research could also investigate whether different ways of experiencing movement speed (e.g. physical movement) similarly influence risk judgments and whether movement speed can have positive connotations outside of risky domains.

The authors offer important insights to marketing practitioners and public policymakers seeking to guide consumers’ judgments and decisions in risk-laden contexts through the digital medium.

By showing how movement speed alters judgments in risk-laden contexts, the authors contribute to literature on risk perception and the growing body of literature examining how moving images shape consumers’ behaviors.

Social media has progressively upgraded an interactive domain via online sociability and information-sharing. This study aims to formulate an information-sharing intention model by identifying the decisive role of intrinsic and extrinsic motivations.

Empirical data from 508 participants were collected to examine the structural model using structural equation modeling.

Results indicate that information-sharing intention is strongly promoted by intrinsic and extrinsic motivations. Furthermore, perceived herding, perceived crowd and intrinsic motivation boost substantially extrinsic motivation. Perceived herding is of utmost importance to extrinsic motivation, whereas emotional appeal and informative appeal are of paramount importance to intrinsic motivation. Moreover, source trust and exhibitionism are underlying motivations for intrinsic motivation.

The findings provide useful guidelines for practitioners to urge users into information-sharing via social media.

This study contributes significantly to the current literature by developing an effective mechanism of information-sharing through social media based on the motivational theory.

This paper aims to explore factors contributing to music popularity using machine learning approaches.

A dataset comprising 204,853 songs from Spotify was used for analysis. The popularity of a song was predicted using predictive machine learning models, with the results showing the superiority of the random forest model across key performance metrics.

The analysis identifies crucial genre and audio features influencing music popularity. Additionally, genre specific analysis reveals that the impact of music features on music popularity varies across different genres.

The findings offer valuable insights for music artists, digital marketers and music platform researchers to understand and focus on the most impactful music features that drive the success of digital music, to devise more targeted marketing strategies and tactics based on popularity predictions, and more effectively capitalize on popular songs in this digital streaming age.

While previous research has explored different factors that may contribute to the popularity of music, this study makes a pioneering effort as the first to consider the intricate interplay between genre and audio features in predicting digital music popularity.

The current study aims to explore the determinants of user intentions towards fitness YouTube channels, employing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and Uses and Gratifications Theory (UGT) as theoretical frameworks.

Symmetric and asymmetric analyses were employed for data analysis, utilizing partial least squares-structural equation modeling (PLS-SEM) for symmetric analysis and fuzzy-set qualitative comparative analysis (fsQCA) for asymmetric analysis.

The study revealed significant impacts of most UTAUT2 determinants and all UGT determinants on user intentions. Additionally, the fsQCA results supported the concept of equifinality, indicating that various configurations of causal combinations can predict a high level of behavioral intention. These findings underscore the significance of comprehending user motivations and factors related to technology and social media in the context of maintaining or increasing followership and viewership for fitness content providers.

The findings suggest that individuals with high expectations and facilitating conditions, as per UTAUT, and heightened hedonic and socializing motivations, in line with UGT, are more inclined to follow fitness YouTube channels. This study offers valuable insights for fitness content creators and marketers navigating the complexities of the digital age.

Public service announcements (PSAs) have been shown to be effective instruments that raise awareness, educate society, and change behaviors and attitudes. Many governments and organizations have utilized PSAs on social media to promote online safety among children and youth. However, we have limited understanding of the range of topics that these PSAs address and how they present their content to audiences. This study provides an inventory of the types of online safety topics that current PSAs address and a catalogue of the types of persuasive features employed by PSAs.

A content analysis of 220 YouTube PSA videos on online safety was conducted. Various topics under the umbrella of online safety were identified. Guided by the prospect theory and exemplification theory, different persuasive features employed in the PSAs were sought.

The findings highlight that the primary focus of these PSAs is on online safety behaviors and general instructions on online hygiene. Interestingly, nearly half of the videos employ a neutral frame, while a significant portion provides no evidential support. Additionally, video length was associated with the number of views and likes it gathered but not with the number of comments.

The inventory of PSAs can help researchers, practitioners, and policymakers better understand the type of content being produced and disseminated online as well as identify topics that are either over or under-represented. Further, the catalogue of the types of persuasive features employed by PSAs would be helpful in guiding research, practice, and policymaking in the context of creating effective online safety videos.

Social media offers better prospect for travellers to seek for travel information, choose a location and share their personal travel experiences. The current study aims to examine how tourists gather information from YouTube shorts and its influence on their intention to use it for selection of an ecotourism destination.

The conceptual model of the study is constructed on information adoption model (IAM). An adaptive questionnaire was utilised to gather 374 valid responses. Partial least square structural equational modelling (PLS-SEM) was utilised for data analysis.

The results showed a positive significant relationship between all the constructs of IAM. The findings also show significant mediating effect of attitude and moderating effect of involvement between information quality and adoption also between source credibility and information usefulness.

This study will help destination marketers by providing valuable insights to them to promote their destinations more effectively on social media platforms. This study will also help travel influencers in understanding what are the factors they should focus on while providing information about ecotourism destination. It will additionally help the local economy and conveys a message to travellers about responsible travel behaviour when selecting or visiting ecotourism destination.

This is the very first attempt to investigate the adoption of YouTube shorts information and formulating behavioural intentions to utilise it for ecotourism destination selection.

The experience of leaving the real world and entering a virtual service environment makes many individuals happy. This study heeds the call by multiple researchers to conceptualize, interpret and illustrate the impact of the perceived service experience in the metaverse in a holistic way. In particular, this study aims to understand how the consumption of experiences is perceived in a metaversal space.

The authors analyze mega virtual live events with famous artists broadcast in virtual worlds. The authors take a big data approach and include two studies to gain insight into the online public audience’s perceptions and experiences in the metaverse. In the first study, the authors analyze text from YouTube with Leximancer. In the second study, the authors go one step further to refine the conceptual model from Study 1. The authors scrutinize additional Facebook comments using seeded Latent Dirichlet Allocation (LDA).

The findings reveal that the meta service experience (MEX) encompasses four dimensions: immersion, metascape, immediacy and hedonism.

This research provides important guidance not only for consumer behavior scholars but also for service marketers and event planners. The study proposes research opportunities to advance service experience research in the metaverse.