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Social media (SM) platforms tempt individuals to communicate their perspectives in real-time, rousing engaging discussions on countless topics. People, besides using these platforms to put up their problems and solutions, also share activist content (AC). This study aims to understand why people participate in activist AC sharing on SM by investigating factors related to planned and unplanned human behaviour.

The study adopted a quantitative approach and administered a close-ended structured questionnaire to gather data from 431 respondents who shared AC on Facebook. The data was analysed using hierarchical regression in SPSS.

The study found a significant influence of both planned (perceived social gains (PSGs) , altruism and perceived knowledge (PK)) and unplanned (extraversion and impulsiveness) human behaviour on activist content-sharing behaviour on SM. The moderating effect of enculturation and general public opinion (GPO) was also examined.

Sharing AC on SM is not like sharing other forms of content such as holiday recommendations – the former can provoke consequences (sometimes undesirable) in some regions. Such content can easily leverage the firehose of deception, maximising the vulnerability of those involved. This work, by relating human behaviour to AC sharing on SM, offers significant insights to enable individuals to manage their shared content and waning probable consequences.

This work combined two opposite constructs of human behaviour: planned and unplanned to explain individual behaviour in a specific context of AC sharing on SM.

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.

Social media has the potential to enable exchange of diverse opinions, foster dialogue on important social issues and exert positive influence on stakeholders and society. However, evidence is contradictory as to whether this is the case; it is possible that millennials' behaviors on social media are mainly driven by conservation (conformity and safety) or self-enhancement (power and achievement). In this research, the authors examine the extent to which different human values (self-transcendence, conservation, self-enhancement and openness to change) influence millennials' activities and behaviors on social media.

The authors conduct three separate surveys on Facebook, Twitter and Instagram with 491 millennials (18–34 years of age) in the USA, examining the influence of four higher-order values of the Schwartz human values model (open self-transcendence, conservation, self-enhancement and openness to change) on specific social media activities (consumption, self-focused and sharing nonpersonal content activities).

First, the authors find that for millennial users, human values significantly influence social media activities. Second, conservation values, followed by self-enhancement values, overshadow the expression of open self-transcendence values on social media. Thus, social media platforms may function more as agents of conservation and self-enhancement than agents of personal growth.

This is among the first studies to examine the influence of human values on social media and to find that human values such as conservation and self-enhancement have a strong influence on users' social media activities, while open self-transcendence values, which lead to expansion and growth, do not find genuine expression on social media.

This study aims to empirically test how sponsored video customization (i.e. the degree to which a sponsored video is customized for a sponsoring brand) affects video shares differently depending on influencer characteristics (i.e. mega influencer and expert influencer) and brand characteristics (i.e. brand establishment and product involvement).

This study uses a unique real-world data set that combines coded variables (e.g. customization) and objective video performance (e.g. sharing) of 365 sponsored videos to test the hypotheses. A negative binomial model is used to analyze the data set.

This study finds that the effect of video customization on video shares varies across contexts. Video customization positively affects shares if they are made for well-established brands and high-involvement products but negatively influences shares if they are produced by mega and expert influencers.

This study extends the influencer marketing literature by focusing on a new media modality – sponsored video. Drawing on the multiple inference model and the persuasion knowledge theory, this study teases out different conditions under which video customization is more or less likely to foster audience engagement, which both influencers and brands care about. The chosen research setting may limit the generalizability of the findings of this study.

The findings suggest that mega and expert influencers need to consider if their endorsement would backfire on a highly customized video. Brands that aim to engage customers with highly-customized videos should gauge their decision by taking into consideration their years of establishment and product involvement. For video-sharing platforms, especially those that are planning to expand their businesses to include “matching-making services” for brands and influencers, the findings provide theory-based guidance on optimizing such matches.

This paper fulfills an urgent research need to study how brands and influencers should produce sponsored videos to achieve optimal outcomes.

The main goal of viral marketing is to affect brands positively. But most studies concern the causes of an ad going viral, not its impact on brands. In this sense, this study aims to demonstrate and compare video ads' value drivers on brands and sharing, determining which antecedents maximize results on each, enabling the best ad performance for advertisers.

A survey was conducted with 368 respondents who watched viral video ads from five global companies on YouTube. The proposed model was tested using structural equation modeling in SmartPLS4.

The results of this study demonstrated that product category involvement is essential for viral advertising. Furthermore, the entertainment value is the most relevant antecedent of sharing, but it does not affect brand equity; it is the social value responsible for brand equity.

Marketing managers should create ads that simultaneously generate entertainment and social values, maximizing sharing and branding effects. However, if only one of the two effects (brand/share) is achieved, then the advertiser will fail to obtain maximum performance.

The mainstream of viral marketing research is focused on antecedents of sharing. However, sharing is not enough to provide brand effects and return on investment of advertisement. This study reveals that different consumers’ values drive sharing and brand equity, suggesting that firms should consider a dual value generation strategy regarding the performance of viral video ads. On the other hand, this research conciliates the extant literature about the phenomena with the importance of product category involvement.

El objetivo principal del marketing viral es influir positivamente en las marcas. Pero la mayoría de las investigaciones se refieren a las causas de que un anuncio se vuelva viral, no a su impacto en las marcas. En este sentido, esta investigación tiene como objetivo demostrar y comparar los impulsores de valor de los anuncios de video en las marcas y su viralización, determinando qué antecedentes maximizan los resultados en cada uno, permitiendo el mejor rendimiento publicitario para los anunciantes.

Se realizó una encuesta con 368 participantes que vieron anuncios de video virales de cinco empresas globales en YouTube. El modelo estructural se analizó mediante ecuaciones estructurales basada en mínimos cuadrados utilizando SmartPLS4.

Los resultados demostraron que la participación en la categoría de productos es esencial para la publicidad viral. Además, el valor de entretenimiento es el antecedente más relevante de compartir, pero no afecta el valor de la marca; es el valor social responsable del valor de la marca.

Los gerentes de marketing deben crear anuncios que generen simultáneamente entretenimiento y valores sociales, maximizando los efectos de uso compartido y de marca. Sin embargo, si solo se consigue uno de los dos efectos (marca/participación), el anunciante no conseguirá obtener el máximo rendimiento.

La corriente principal de la investigación de marketing viral se centra en los antecedentes de compartir. Sin embargo, compartir no es suficiente para proporcionar efectos de marca y ROI de publicidad. Este estudio revela que los diferentes valores de los consumidores impulsan el intercambio y el valor de la marca, lo que sugiere que las empresas deberían considerar una estrategia de generación de valor dual con respecto al rendimiento de los anuncios de video virales. Por otro lado, esta investigación concilia la literatura existente sobre los fenómenos con la importancia de la participación de la categoría de productos.

病毒式营销的主要目标是对品牌产生积极的影响。但大多数研究关注的是广告走红的原因, 而不是它对品牌的影响。在这个意义上, 本研究旨在证明和比较视频广告对品牌和分享的价值驱动因素, 确定哪些前因能使每一个因素的结果最大化, 为广告商带来最佳的广告效果。

对368名受访者进行了调查, 他们在YouTube上观看了五家全球公司的病毒视频广告。在SmartPLS4中使用结构方程模型 对提议的模型进行了测试。

结果表明, 产品类别的参与对于病毒式广告来说是至关重要的。此外, 娱乐价值是分享的最相关前因, 但它并不影响品牌资产; 对品牌资产负责的是社会价值。

营销经理应该创造同时产生娱乐和社会价值的广告, 使分享和品牌效应最大化。然而, 如果只实现两种效果（品牌/分享）中的一种, 广告商将无法获得最大的绩效。

病毒式营销研究的主流是关注分享的前因后果。然而, 分享并不足以提供品牌效应和广告的投资回报率。本研究揭示了不同消费者的价值观对分享和品牌资产的推动作用, 表明企业应该考虑关于病毒视频广告表现的双重价值产生策略。另一方面, 本研究将现有的文献与产品类别参与的重要性结合在一起。

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.

The purpose of this paper is to examine the information flows, in terms of content and process, underpinning the sharing of knowledge by managers and owners. Such an examination reveals similarities and differences that will influence the generation and dissemination of knowledge used in tourism business operations and contribute to innovation.

This paper examines information flows within the theoretical and methodological framework of social network analysis. The findings were derived from a quantitative study of tourism managers and owners of a tourism hub in South-West England.

The main finding was that network structure characteristics determine the flow of information within owners’ and managers’ social networks. The owners of smaller businesses received information from several sources and, therefore, had fewer structural constraints and reported larger structural holes. In comparison, the managers had more brokerage opportunities to disseminate the information within their social networks.

This paper highlights knowledge sharing between tourism business managers and owners in an open network structure. First, an open network structure builds innovation through the provision of nonredundant information. This is determined through the effective size of structural holes and the dissemination of information through brokerage roles. Second, the knowledge capability of a destination is built up through the social networking of managers and owners. The generation and dissemination of knowledge in a tourism destination are facilitated by the social networking activities of managers and owners.

Managers and owners of tourism businesses require knowledge through information to assist with innovative business practices. The practical implication of this is that the social networks of managers and owners have different network characteristics, and that these differences result in consequences for the innovation of business practices. Another practical implication relates to the importance of managers in knowledge dissemination based on having several brokerage roles in the tourism destination.

These findings are important because an understanding of social networks and the flow of information is one of the keys to determining the influences on knowledge sharing within tourism destination knowledge networks of owners or managers and their potential contributions to innovation.

This study aims to identify the groups of value cocreators in the context of social media in the retail banking industry and resources that predict customer membership among different groups of value cocreators.

This study reviewed the literature and developed measurement instruments for the constructs of interest. Data were collected from 406 customers in an emerging market in 2019 and analyzed using latent profile analysis.

This study identified three profiles of value cocreators on social media based on the actual practices of resource integration that enliven value cocreation. Second, this study explains the differences in the performance of resource integration practices to cocreate by the types of resources that customers integrate into social media. Third, this study fills the need for knowledge of value cocreation in different contexts and industries (e.g. banks).

This study analytically relates a set of resources to the variety and intensity of the value cocreation practices adopted by bank customers in interactive environments. The emphasis on how value cocreation practices in online environments combined with customer resources (e.g., a person-centered approach) allows to identify unique profiles of value cocreators on social media. The findings inform managers of the profiles of cocreators, which customers are more attractive as value cocreators on social media, and which resources managers should help customers develop to increase cocreation on social media.

This research explores the differential effects of pixel-level and object-level visual complexity in firm-generated content (FGC) on consumer engagement in terms of the number of likes and shares, and further investigates the moderating role of image brightness.

Drawing on a deep learning analysis of 85,975 images on a social media platform in China, this study investigates visual complexity in FGC.

The results indicate that pixel-level complexity increases both the number of likes and shares. Object-level complexity has a U-shaped relationship with the number of likes, while it has an inverted U-shaped relationship with the number of shares. Moreover, image brightness mitigates the effect of pixel-level complexity on likes but amplifies the effect on shares; contrarily, it amplifies the effect of object-level complexity on likes, while mitigating its effect on shares.

Although images play a critical role in FGC, visual data analytics has rarely been used in social media research. This study identified two types of visual complexity and investigated their differential effects. We discuss how the processing of information embedded in visual content influences consumer engagement. The findings enrich the literature on social media and visual marketing.

Posting and sharing about food on social media has surged in popularity amongst younger generations such as Millennials and Generation Z. This study aims to analyse and compare food-tourism sharing behaviour on social media across generations. First, this study specifically investigates the factors influencing the intention to share food experiences on social media; second, it examines the impact of sharing intention on actual behaviour and loyalty; and third, it determines whether Millennials and Generation Z differ in these relationships.

A survey was carried out of Millennial and Generation Z travellers who shared food experiences on social media. Structural equation modelling (SEM) and multi-group analysis were performed to examine the cause-and-effect relationship in both generations.

The findings reveal differences in motivation, satisfaction, sharing intention, sharing behaviour and loyalty between generations (Millennials and Generation Z).

This study contributes to the literature on the antecedents of food-sharing behaviour in online communities by indicating factors that influence the sharing of culinary experiences and brand or destination loyalty across generations. Suggestions for future research include exploring online food-sharing behaviour through cross-cultural comparisons in various regions.

As Millennials and Generation Z will expand their market share in the coming years, the findings of this study can help improve marketing strategies for culinary tourism and generate more intense food experiences for both generations.

The outcome of the research provides new insights to develop a conceptual model of food-sharing behaviour and tourism on social media by drawing comparisons across generations.