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To understand the mechanisms underlying social media discontinuance behavior, this study explores factors affecting social media discontinuance behavior from the perspective of social cognitive theory (SCT).

Based on SCT, this study puts forward a theoretical model incorporating habit, excessive use and negative emotions to predict social media discontinuance behavior. The proposed research model was empirically tested with 465 responses collected from WeChat users in China via an online survey. WeChat is one of the most popular social media in China. However, WeChat also faces the challenges of reduced or terminated usage among its users. Partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the data.

The research results in this study show that habit exerts a negative effect on social media discontinuance behavior, while exhaustion and regret have positive influences. In addition, habit positively affects excessive use, which further leads to negative emotions of social media exhaustion and regret. Moreover, gender moderates the relationship between habit and social media discontinuance behavior.

This study adds to the literature of information system (IS) use lifecycle by investigating user behavioral changes regarding a transition from habituated to excessive use and further to discontinuance behavior. This study also helps elucidate the complex role of habit by explaining social media discontinuance from the social cognitive view. Furthermore, this study advances the current understanding of gender difference in social media discontinuance in the Chinese context. The study also offers insights to practitioners on how to prevent individuals from discontinuing their use of social media.

Enterprises build online product community to expect users to contribute: opinion sharing (content contribution) and product consumption (product contribution). Previous literature rarely focused on both. The purpose of this paper is to explain user contribution mechanism by identifying content contribution and product contribution.

This research chose Xiaomi-hosted online product community (bbs.xiaomi.cn) and Huawei-hosted online product community (club.huawei.com) where users can freely share ideas and buy products at the same time. Data were crawled from 109,665 community users to construct dependent variable measurement, and 611 questionnaires were used to verify research hypotheses.

The results indicate that both cognitive needs and personal integration needs have a significant positive impact on browse behavior; social integration needs and hedonic needs have a significant positive impact on content contribution behavior. Browse behavior not only directly affects but also indirectly influences product contribution through content contribution behavior.

Findings of this research provide community managers with useful insights into the relationship between content contribution and product contribution.

This study explains the formation mechanism of user product contribution and reveals the relationship between user content contribution and product contribution in online product community. This paper provides a different way of theorizing user contributions by incorporating uses and gratifications theory into the “Motivation-Behavior-Result” framework.

As fertile soil for product promotion, online interest communities have gradually come into brands' view. However, existing research does not clarify whether brand engagement in consumer interaction is beneficial to the development of online interest communities. This study attempts to investigate the effects of brand engagement on the online interest community operation.

The authors propose a model that delineated the influence of brand engagement on consumers' citizenship behavior in the online interest community from the commitment-trust perspective. Scenario-based experiments were conducted and 536 data were collected by simple random sampling.

Results shows that a stronger perception of brand engagement has a positive influence on the relationship (trust and commitment) between the community and its users, which further influences online community citizenship behavior (feedback, advocacy and tolerance) of both posters and lurkers, especially for the posters. Although relationships are more complex, brand engagement activates the development of online interest communities to some extent.

This original study contributes to the commitment-trust theory by examining the impact of brand engagement on citizenship behavior via community commitment and trust in the online interest community context. In addition, this study compares the moderating effect of posters vs lurkers on the relationship between brand engagement and citizenship behavior in the online interest community.

This research aims to examine some nudges for creating psychological ownership in order to reduce misbehaviors, consequently encouraging subsequent users to demonstrate stewardship behaviors.

This research examined the sentiment of tweets (Study 1) to explore user experience and conducted two experiments (Studies 2 and 3) to test the hypotheses.

The misbehavior of the previous user in relation to the subsequent user's stewardship behavior was moderated by nudges based on self-investment and local identity. Perceived responsibility mediated the relationship between misbehavior and stewardship behavior as a result of nudges.

The findings of this study provide a framework for the transition from misbehavior to stewardship behavior in PMVs.

As a sociotechnical system, the metaverse has sparked heated discussion. However, concerns abound that the concept is “old wine in a new bottle” used for capital hype. The mixed definitions of the metaverse and unclear relationships between its technical features and user behaviors have greatly impeded its design and application. Therefore, the authors aim to sort out the metaverse definition and properties, analyze its technical features in various contexts and unveil the mechanisms leading to user behaviors.

The authors conduct a literature review on the definition, technical features and user behaviors of/in the metaverse.

First, the authors identify two main categories of the metaverse definition and find a mixed conceptualization. Second, the authors present technologies and technical features in the diverse contexts of the metaverse. Third, the authors summarize the effect of technical features on user behaviors from a sociotechnical perspective.

The authors analyze the definition, technical features, user behaviors of the metaverse and their theoretical foundations. Based on these findings, the authors propose a theoretical framework unveiling how social and technical elements affect user behaviors in the metaverse. In conclusion, the study offers a research agenda for future studies.

Based on cognitive evaluation theory and gamification affordances, this study aims to understand how gamification affordances influence users’ intention to engage in sustainable behaviour and how new trends in Ant Forest influence its impact on green intrinsic motivation to support sustainable behaviours.

The authors developed a research model to explore the mechanisms underlying gamification affordances, psychological needs and green intrinsic motivation. Partial least squares structural equation modelling was used to assess the survey data (n = 393) and test the research model.

The results show that different gamification affordances can satisfy users’ needs for autonomy, competence and relatedness, which positively influences their green intrinsic motivation and engagement in sustainable behaviours. However, some affordances, such as competition, might negatively impact these psychological needs.

This research updates information system research on environmental sustainability and the Ant Forest context. The authors provide a new framework that links gamification affordances, psychological needs and sustainable behaviour. The study also examines changing trends in Ant Forest and their implications.

Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.

We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.

The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.

Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.

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.

User discontinuance on short-video platform has become increasingly prevalent in recent years. Short-video discontinuance refers to reduced use, controlled use or suspended use of the short-video platform. In this study, we examined factors associated with discontinuance behavior on short-video platform.

From the perspective of stressor–strain–outcome (SSO), we put forward a theoretical model integrating perceived information overload and perceived system feature overload (stressors), dissatisfaction (psychological strain), flow experience and regret to explain discontinuance behavior on short-video platform (behavioral outcome). We collected 482 survey data from Douyin users in China, and empirically examined the proposed research model via Partial least squares structural equation modeling (PLS-SEM) technique.

Our results demonstrated that perceived system feature overload exerts a positive effect on perceived information overload. Perceived system feature overload has a stronger influence on dissatisfaction than perceived information overload. Regret increases user dissatisfaction, while flow experience decreases user dissatisfaction. We also discovered that dissatisfaction and regret have significant positive effects on discontinuance behavior. Interestingly, flow exerts no significant influence on discontinuance behavior.

This study enriches the body of knowledge on social media discontinuance by revealing the interaction and effects of flow experience, dissatisfaction and regret on discontinuance. This study also extends the understanding on the complex role of flow experience in leading to social media discontinuance. Additionally, this study deepens the research on the interaction between perceived system feature overload and perceived information overload as well as their different influences on negative emotion.

With over-the-top (OTT) streaming services rapidly transforming the media industry and saturating the market, the authors' study seeks to enrich the goal-directed behaviour model by exploring how perceived risks and descriptive norms influence OTT consumption.

Survey data from OTT subscribers were collected online to assess their risk behaviours. The 353 responses obtained were analysed with SmartPLS, validating the structural equation modelling (SEM) through structural and measurement model verification.

The authors' findings illustrate that descriptive norm, perceived behavioural control, as well as positive and negative anticipated emotion (NEM) and attitude, contribute positively to the desire to engage with OTT streaming services. Interestingly, the authors' study contradicts common assumptions, revealing that subjective norms do not significantly impact the propensity to utilise OTT services. This counterintuitive finding necessitates a reconsideration of prevalent theories and contributes to a nuanced understanding of OTT adoption determinants.

The data gathering for this study were conducted from the perspective of a single nation. Therefore, caution must be exercised when generalising this study's results.

The practical ramifications of this research are vast, providing OTT service providers and marketers with actionable insights to maximise user engagement and navigate perceived risks related to OTT service adoption and consumption.

This study's exploration of perceived risks and descriptive norms enhances the goal-directed behaviour model's breadth, facilitating a holistic comprehension of the constructs shaping OTT consumption behaviours. It would be the first attempt to combine perceptual, affective and behavioural factors and perceived risks to understand the user's predisposition to engage in OTT streaming services.