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This study aims to explore which of four chosen factors (i.e. privacy concerns, FoMO, self-disclosure and time cost) induce a feeling of strain among Facebook users in terms of social media fatigue (SMF), and if this occurs, whether it further influences such outcomes as discontinuance of usage (DoU) and interaction engagement decrement (IED).

Through an online structured questionnaire, empirical data were gathered to verify the research model, based on the stressor-strain-outcome (SSO) framework. The SEM technique was employed for assessing the hypothesized relationships.

The findings show that privacy concerns and time cost are strong antecedents of SMF and contribute significantly to its occurrence; while FoMO and self-disclosure do not exhibit any significant influence. Moreover, SMF positively and significantly affects DoU and IED.

This study enhances the existing body of knowledge on SMF and it can help: (1) individuals to be aware of risks and adjust their activities in balance with their well-being, and (2) social media (SM) managers to develop unique strategies to address the specific needs of SM users.

This research contributes to the limited literature on SMF by (1) introducing the concept of IED – as a consequence of SMF, and (2) creating measurement scales for IED.

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.

During the digital media era with an explosion of messages, the prevalence of what is known as “message fatigue” has grown. However, there is a lack of understanding toward message fatigue in using instant messengers. Based on the stressor-strain-outcome framework, this study provides a theoretical model to explore possible predictors and consequences of instant messaging fatigue.

The hypothesized model includes communication overload, social overload, instant messaging fatigue, technology and behavioral intention to use instant messaging. Three hundred and eleven responses are collected using an online survey. The authors conduct structural equation modeling to evaluate the hypothesized model and test the hypotheses.

This study reveals that (1) communication overload and social overload are positively associated with instant messaging fatigue and technostress; (2) higher levels of instant messaging fatigue and technostress are also related to a higher level of intention to discontinue usage; (3) technostress significantly mediates the relationship between instant messaging fatigue and intention to discontinue usage of instant messaging.

This study is limited to collect data from one university in the United States with a cross-sectional design. Future research should include other countries, different age groups and longitudinal methods to examine instant messaging fatigue.

This study extends existing findings on fatigue in using mobile communication by applying the stressor-strain-outcome framework to IM fatigue and improves the understanding of the potential negative aspects of instant messaging.

This study focuses on perceived overload from environmental stimuli and individual psychology and behavioral interactions. It constructs a theoretical model with overload as the key stressor based on the stressor-strain-outcome (SSO) model. The authors argue that system feature overload (SFO), information overload, and social overload lead to two psychological strains: fear of missing out (FoMO) and fatigue among users of short video platforms, affecting their discontinuous usage intentions.

To test the hypotheses, the authors conducted a questionnaire survey on 412 users' short video platform usage and empirically tested the constructed model using the research tool SmartPLS 3.3.2.

The results of data analysis showed that most of the hypotheses were supported. Specifically, system feature overload, information overload and social overload all positively affected FoMO. However, SFO and information overload significantly affected fatigue. There was no significant relationship between social overload and fatigue. In addition, both FoMO and fatigue negatively influenced users' discontinuous usage intentions.

The current research on user behavior in information systems tends to focus on the influence in the positive direction and less on the negative direction. The research on discontinuous usage intention (DUI) is a very new research topic. This research studies the influencing factors of users' discontinuous behavior from the perspective of perceptual overload. It provides a unique view for future short video platform user behavior research, with significant theoretical contributions and essential practice for short video platform operators to improve services.

Limited knowledge exists regarding the adverse effects of artificial intelligence adoption, including platforms like ChatGPT, on users’ mental well-being. The current research seeks to adopt the insight from the stressor-strain-outcome paradigm and a moderated mediation model to examine how technology anxiety moderates the direct and indirect relationships between compulsive use of ChatGPT, technostress, and life satisfaction.

Drawing data from a sample of 2,602 ChatGPT users in Vietnam, PROCESS macro was approached to test the moderated mediation model.

The findings indicate that compulsive use of ChatGPT exhibited a substantial and positive impact on technostress, while technostress was found to have a negative influence on life satisfaction. Moreover, although compulsive use of ChatGPT did not show a significant direct effect, it indirectly impacts life satisfaction via technostress. Remarkably, technology anxiety was found to significantly moderate both direct and indirect associations between compulsive use of ChatGPT, technostress, and life satisfaction.

Based on the findings of this research, some practical implications are provided.

The research offers a fresh perspective by applying the stressor-strain-outcome perspective to provide empirical evidence on the moderated mediation effects of technology anxiety and technostress on the relationship between compulsive use of ChatGPT and users’ life satisfaction. The research thus sheds new light on artificial intelligence adoption and its effects on users’ mental health.

An increasing number of users join and become immersed in WeChat official accounts, but many users quit using these services as well. Nevertheless, most of the previous studies mainly focussed on the usage behavior. The purpose of this paper is to fill the gap by examining factors affecting users’ unfollow intentions for WeChat subscriptions in a Chinese context.

Structural equation modeling is used in our study. A field survey with 260 WeChat users is conducted to test the research model and hypotheses.

The results show the following interesting key findings: first, the effect of actual cost on users’ unfollow intentions is larger than the effect of opportunity cost; second, users’ unfollow intentions will decrease with the increase of users’ perceptions of information usefulness; third, the results of the control variables showed that only landing frequency has a negative effect on users’ unfollow intentions; and fourth, users’ demographic differences are also examined in regard to how they may affect users’ unfollow intentions.

First, this paper studies factors influencing users’ unfollow intentions for WeChat subscriptions from a social exchange theory perspective; the authors considered both extraneous factors and users’ internal perception factors potentially affecting users’ unfollow intentions, which has rarely been researched. Furthermore, the authors examined significant differences among users’ demographic characteristics in affecting users’ unfollow intentions. The results of the study provide a more comprehensive understanding of the influencing factors of users’ unfollow intentions.

This study aims to investigate the influence of three key categories of perceived entrepreneurial obstacles (perceived loss of financial resources, perceived loss of customer demand and perceived loss of social support) on entrepreneurial behavior tendency through fear of failure and negative emotion to shed light on why Chinese entrepreneurship has fallen into a decline from the individual level.

A sample of 256 Chinese makers who were achieving their innovative ideas in makerspaces was used to test the research model. Then, the structural equation modeling was adopted for data analysis.

The results indicate that fear of failure is the strongest psychological barrier to entrepreneurial behavior tendency and the strongest trigger for negative emotion; both negative emotion and fear of failure are affected by entrepreneurial obstacles of perceived loss of financial resources and perceived loss of social support. However, perceived loss of customer demand is not the inducement for both fear of failure and negative emotion.

This study adopts stressor-strain-outcome framework in studying entrepreneurship to help understand what prevent potential entrepreneurs from stepping into entrepreneurship. In addition, this study offers a new insight into entrepreneurship by emphasizing the decisive impact of inhibitive factors on personal entrepreneurship.

The purpose of this paper is to explore the effects of excessive social media use on individual job performance and its exact mechanism. An extended stressor–strain–outcome research model is proposed to explain how excessive social media use at work influences individual job performance.

The research model was empirically tested with an online survey study of 230 working professionals who use social media in organizations.

The results revealed that excessive social media use was a determinant of three types of social media overload (i.e. information, communication and social overload). Information and communication overload were significant stressors that influence social media exhaustion, while social overload was not a significant predictor of exhaustion. Furthermore, social media exhaustion significantly reduces individual job performance.

Theory-driven investigation of the effects of excessive social media use on individual job performance is still relatively scarce, underscoring the need for theoretically-based research of excessive social media use at work. This paper enriches social media research by presenting an extended stressor–strain–outcome model to explore the exact mechanism of excessive use of social media at work, and identifying three components of social media-related overload, including information, communication and social overload. It is an initial attempt to systematically validate the casual relationships among excessive usage experience, overload, exhaustion and individual job performance based on the transactional theory of stress and coping.

Past research on self-employment and health yielded conflicting findings. Integrating predictions from the Stressor-Strain Outcome model, research on challenge stressors and allostatic load, we predict that physical and mental health are affected by self-employment in distinct ways which play out over different time horizons. We also test whether the health impacts of self-employment are due to enhanced stress (work-related strain) and differ for man and women.

We apply non-parametric propensity score matching in combination with a difference-in-difference approach and longitudinal cohort data to examine self-selection and the causal relationship between self-employment and health. We focus on those that transit into self-employment from paid employment (opportunity self-employment) and analyze strain and health over four years relative to individuals in paid employment.

Those with poorer mental health are more likely to self-select into self-employment. After entering self-employment, individuals experience a short-term uplift in mental health due to lower work-related strain, especially for self-employed men. In the longer-term (four years) the mental health of the self-employed drops back to pre-self-employment levels. We find no effect of self-employment on physical health.

Our research helps to understand the nonpecuniary benefits of self-employment and suggests that we should not advocate self-employment as a “healthy” career.

This article advances research on self-employment and health. Grounded in stress theories it offers new insights relating to self-selection, the temporality of effects, the mediating role of work-related strain, and gender that collectively help to explain why past research yielded conflicting findings.

This paper aims to discuss major influencing factors causing users’ mobile social media fatigue and divides them into three hierarchies, including causal factors, intermediary factors and outcome factors. The study also sorts out connections between different levels of factors, thus providing effective guidance for the sustained development of social media.

Based on the grounded theory and by collecting data through in-depth interviews, the authors use open coding, axial coding and selective coding to analyze major influencing factors of users’ mobile social media fatigue, build a model using the software NVivo 11, organize and analyze mobile social media fatigue behavior and identify the relationships by combining the interpretive structural model and explore connections among the factors.

The influencing factors of mobile social media fatigue behavior conform with the stressors-strains-outcomes (SSO) theoretical framework, where stressors (S) include the five factors of fear of missing out, perceived overload, compulsive use, time cost and privacy concerns; strains (S) include the five factors of a low sense of achievement, emotional anxiety, reduced interest, social concerns and emotional exhaustion; outcomes (O) include the six factors of neglect behavior, diving behavior, avoidance behavior, tolerance behavior, withdrawal behavior and substitution behavior.

It focuses on the discussion of the interactions between users’ stressors, strains and outcomes without fully considering the impact of social environment and educational background on social media fatigue behavior. This study only focuses on one social media platform in the Chinese context, namely, WeChat. We reply on the qualitative research method to construct the relationships between social media fatigue factors because we were mainly interested in how users would respond psychologically and emotionally to social media fatigue behavior.

The study has extended the application of the SSO theory. Additionally, the research method and model used in this paper may serve as guidelines to other interested scholars who intend to explore relevant variables and conduct further research on the influencing factors of social media fatigue. In analyzing the causality of social media fatigue, the study has integrated the intermediary factor strain to display users’ strains from social media stress with a more detailed path discussion on the causality of social media fatigue, which has not received broad attention in previous research literature on social networking services users’ use.

In this study, text data are collected in a diversity of forms combined, allowing respondents to answer questions without being limited by the questions in the questionnaire, which helped us to identify new variables of social media fatigue. As a result, we were able to dig out the fundamental causes of social media fatigue and potential connections between the factors. Relevant scholars, users and businesses may analyze, manage and forecast users’ social media fatigue behavior by analyzing the type of social media stress and users’ state, providing guidance for the proposal of corresponding management strategies.

Most relevant studies focus on the sustained use of social media, and there is a scarcity of studies on social media fatigue in China. There is very limited research that conducts model analysis of social media fatigue through the integration of stressors, strains and outcomes.