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The integration of social media and e-commerce has resulted in a rising phenomenon among individual content providers (ICPs), who used to offer free content, to provide consumers with paid content, such as online courses, Q&As or consultations. Despite the prevalence of ICPs’ content monetization, empirical research has rarely studied its underlying mechanism. This paper examines how the characteristics of free content contributed by ICPs on social media platforms influence their paid content sales, focusing on the perspective of human brand.

The empirical setting is an online knowledge exchange platform, where users are allowed to provide free content (e.g. answers) on the social media platform and launch paid content (e.g. lectures) on the e-commerce platform. A machine learning technique is employed to construct measures for the characteristics of free content, and fixed-effects estimation is presented to confirm which factors have a significant influence on the sales of paid content.

The empirical results show that the quality, diversity and expertness of free content have a significant positive impact on the sales of the ICP-paid content, with the brand popularity of ICP playing a mediating role.

This study is the first attempt to demystify the relationship between content contribution and ICPs’ content monetization from the perspective of human brand. The findings validate the effectiveness of the “Selling by Contribution” strategy and provide valuable insights for ICPs and social media platforms.

The purpose of this paper is to examine how different types of user experience in TikTok impact purchase intention via commitment to the influencer and commitment to the platform, with customer type included to determine moderating effects. Three types of user experience are considered: information experience, entertainment experience and parasocial-relationship-based experience.

This study collected 458 valid questionnaires from TikTok users, employing the structural equation modeling approach to examine the proposed research model.

Information experience, entertainment experience and parasocial-relationship-based experience are found to critically stimulate user commitment to the influencer and commitment to the platform, in turn driving TikTok-based purchase intention. Tests incorporating customer type reveal that commitment to the influencer more strongly influences the purchase intention of repeat customers, with commitment to the platform more likely to stimulate purchase intention among potential customers.

On a theoretical level, the paper is among the first to examine TikTok-based user purchase intention with customer type as a moderator. On a practical level, the results can guide marketers to effectively promote products using TikTok and inspire TikTok managers to develop customized strategies to stimulate initial and repeat sales.

TikTok is moving to the stage of commercialization and monetization by introducing e-commerce features. Although this move should cultivate particularly fertile ground for companies to sell products, TikTok user purchase behavior has yet to receive sufficient research attention, with little currently known about their purchase motivations. The current study uncovers the significant antecedents of users' purchase intention through TikTok, and further reveals the motivational differences among potential and repeat customers.

On Instagram, a verified badge (a blue checkmark) is used to confirm the authenticity of influencers' accounts for consumers. Yet, it is unclear whether followers trust the badge or are influenced by the influencer's large following. This research aims to investigate the impact of verified badges on followers' trust and behavioral intentions.

This research conducts three experiments to investigate the impact of the verified badge on consumer attitudes and behavioral intentions, recruiting participants from freelance recruiting website in all three experiments.

The results show that a verified badge can sequentially influence consumer trust, attitude and sharing intentions. Furthermore, the impact of the verified badge on trust is more pronounced among micro-influencers as opposed to macro-influencers, and it can mitigate the negative attitude toward commercial postings.

Based on trust transfer theory, this research is a pioneer in investigating the effectiveness of verified badges on social media. These findings contribute to the field of influencer marketing by considering influencers' characteristics and the commercial intent of postings as moderators. Additionally, the results offer managerial insights for developing influencer marketing strategies.

This study delves into how corporations make decisions about influencer marketing. Specifically, it examines the differences between human influencers, who carry the risk of scandals, and virtual influencers, a new and unpredictable realm, regarding their integration with social media platforms.

Using game theory and empirical data, the study explores crucial factors in influencer marketing, including influencer quality, reputation repair costs and the probability of R&D failures.

This study suggests that companies favor human influencers when the risk of scandal is low. However, competing companies switch to virtual influencers at different intervals as this risk increases. The costs, likelihood of scandals and competition intensity all play a role in a company's decision-making regarding technology management. Additionally, a higher chance of R&D failure can motivate a company to invest more in R&D to gain a competitive advantage over rivals that may suffer failures.

This study provides insights into how corporations manage social media influencer marketing in the digital age. It contributes to marketing theory and technology management decisions by offering a fresh perspective on the relationship between corporate reputation and influencer marketing strategy.

This study offers valuable perspectives into a relatively uncharted area of marketing strategy. It employs game theory and empirical analysis to introduce a fresh method of comprehending the dynamics of influencer marketing, its impact on corporate reputation management and its interaction with social media.

Young consumers are increasingly using online reviews and celebrity influence to make purchase decisions. The purpose of this study is to ascertain the influence of online customer reviews, celebrity influencer’s attractiveness, celebrity influencer’s credibility on female millennials’ purchase intention of beauty products.

To validate the research questions and hypotheses, data were obtained from young female consumers using an electronic self-administered survey questionnaire that was close ended. A total of 203 valid responses were obtained from which data were analysed by making use of structural equation modelling Mplus and the Statistical Package for the Social Sciences version 28.

The obtained results showed that the seven hypotheses of the study were positive. However, two hypotheses were negative, namely, celebrity influencer attractiveness did not have a significant influence on the attitude of consumers; and brand loyalty was not significantly correlating with young female consumers’ purchase intention of beauty products.

Given that millennials are known to be active users of social media and often consult online peer product reviews, marketers and practitioners of beauty industry should improve the effectiveness and usability of beauty influencers and online reviews to attract female millennial consumers.

This research contributes to understanding young female consumers’ attitudes towards purchasing beauty products, especially the combined influence of group influence (online reviews) and media influence (celebrity beauty influencers) on such attitudes.

To address the challenges encountered in disaster responses, optimize resource utilization, minimize environmental and social impact, and ensure transparency and accountability, it is essential to review humanitarian supply chains and incorporate sustainability considerations. Humanitarian organizations can enhance their ability to deliver timely and effective assistance to those in need by continuously improving supply chain practices. Consequently, this work explores the convergence of two fast-growing domains: sustainability and humanitarian supply chain management (HSCM).

The authors conducted a systematic literature review of peer-reviewed articles to identify the prominent research trends and themes from the two domains' interactions. The extant literature is represented under the theory, context, characteristics, and research method (TCCM) framework. The authors have utilized a stakeholder theory perspective to identify coordination and collaboration among the various stakeholders.

This study's review findings reveal five future research directions formulating this study's central themes: the role of environmental sustainability, coordination, and collaboration in building effective HSCs; the role of humanitarian aid for the responsive HSC; the influence of big data predictive analytics on the HSC performance; development and empirical validation of sustainable HSC performance framework; the role of HSC stakeholders in building effective and efficient HSCs.

There is no existing academic literature review available on sustainable HSCM. This review fills this void by fostering discussion about sustainable humanitarian supply chains where the authors notably propose the TCCM framework in the context of sustainable HSCM, followed by a stakeholder network.

Social media has played a pivotal role in polarizing views on Russia–Ukraine conflict. The effects of polarization in online interactions have been extensively studied in many contexts. This research aims to examine how multiple social media sources may act as an integrator of information and act as a platform for depolarizing behaviors.

This study analyzes the communications of 6,662 tweets related to the sanctions imposed on Russia by using textual analytics and predictive modeling.

The research findings reveal that the tweeting behavior of netizens was depolarized because of information from multiple social media sources. However, the influx of information from non-organizational sources such as trending topics and discussions has a depolarizing impact on the user’s pre-established attitude.

For policymakers, conflict mediators and observers, and members of society in general, there is a need for (1) continuous and consistent communication throughout the crisis, (2) transparency in the information being communicated and (3) public awareness of the polarized and conflicting information being provided from multiple actors that may be biased in the claims being made about the conflict crisis.

While previous research has examined Russia–Ukraine conflict from a variety of perspectives, this is the first study to examine how social media might be used to reduce attitude polarization during times of conflict.

The present study investigates the impact of opinion leadership and spirituality from three types of social media influencers (SMIs) on individuals’ intentions to conduct recycling. This research is driven by the opinion leadership theory demonstrated by influencer marketing.

This research applies a between-subject experiment to measure the impact of the proposed model. Each participant was exposed to a different influencer: an attractive influencer (Treatment 1, n = 101), an expert influencer (Treatment 2, n = 94), a religious influencer (Treatment 3, n = 99) and a control condition (Treatment 4, n = 102). An ANOVA post-hoc analysis was conducted to further assess the impact dynamics of each influencer based on different demographics such as age, income and level of education. More than 95% of the samples consist of Muslims.

Findings revealed the different dynamics of the effect of opinion leadership and spirituality on the intention to recycle from utilising different types of influencers. Samples derived from a high socio-economic background and exposed to the religious influencer (Treatment 3) have a relatively higher mean score. In general, younger participants with lower incomes and levels of education have less tendency to conduct recycling.

This research attempts to fill the gap in the impact of influencer marketing on green behaviour adoption with the inclusion of spirituality, which has been largely ignored in this context. It offers insights from the perspective of a developing economy that has one of the largest percentages of social media users in the world and from a country that regards a relationship with God as important.

The primary objective of this research is to provide a precise interpretation of the constructed machine learning model and produce definitive summaries that can evaluate the influence of investor sentiment on the overall sales of non-fungible token (NFT) assets. To achieve this objective, the NFT hype index was constructed as well as several approaches of XAI were employed to interpret Black Box models and assess the magnitude and direction of the impact of the features used.

The research paper involved the construction of a sentiment index termed the NFT hype index, which aims to measure the influence of market actors within the NFT industry. This index was created by analyzing written content posted by 62 high-profile individuals and opinion leaders on the social media platform Twitter. The authors collected posts from the Twitter accounts that were afterward classified by tonality with a help of natural language processing model VADER. Then the machine learning methods and XAI approaches (feature importance, permutation importance and SHAP) were applied to explain the obtained results.

The built index was subjected to rigorous analysis using the gradient boosting regressor model and explainable AI techniques, which confirmed its significant explanatory power. Remarkably, the NFT hype index exhibited a higher degree of predictive accuracy compared to the well-known sentiment indices.

The NFT hype index, constructed from Twitter textual data, functions as an innovative, sentiment-based indicator for investment decision-making in the NFT market. It offers investors unique insights into the market sentiment that can be used alongside conventional financial analysis techniques to enhance risk management, portfolio optimization and overall investment outcomes within the rapidly evolving NFT ecosystem. Thus, the index plays a crucial role in facilitating well-informed, data-driven investment decisions and ensuring a competitive edge in the digital assets market.

The authors developed a novel index of investor interest for NFT assets (NFT hype index) based on text messages posted by market influencers and compared it to conventional sentiment indices in terms of their explanatory power. With the application of explainable AI, it was shown that sentiment indices may perform as significant predictors for NFT sales and that the NFT hype index works best among all sentiment indices considered.

This study aims to answer two significant questions: What are the relative consumer and firm-level effects of marketing through metaverse compared to conventional marketing endeavours? What are the current trends in utilizing the metaverse as reported in the recent literature?

This study uses a systematic literature review methodology, using a Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart to synthesize existing research. A total of 35 articles written in English were selected and analysed from two databases, Web of Science and EBSCO Host.

The findings indicate that consumer-level effects of the metaverse include consumer loyalty and brand attachment. The firm-level benefits are decentralization and cost reductions. The paper proposes a framework indicating variables that could attenuate or enhance the association between immersive components of the metaverse and their resultant effects.

This study contributes to understanding the role of metaverse in marketing practices related to the marketing mix components. The study conceptualizes a novel framework for the metaverse and its resultant effects.