When more is less: information overload and fatigue in live streaming commerce

Live streaming commerce (LSC) has rapidly expanded over the past decade, integrating the advantages of social commerce and e-commerce. According to ChinaIRN (2025), the total transaction volume of live streaming commerce reached 4.9 trillion RMB in 2023, marking a year-on-year increase of 40.48%. Additionally, the average annual spending per user rose to 8,660 RMB, reflecting a 17.03% growth compared to the previous year. Furthermore, Sohu (2022) stated that the number of live streamer accounts in China reached 140 million, and by the end of 2021, 7,661 companies had obtained live streaming business qualifications, representing a 17% increase compared to 2020. Despite this rapid expansion, competition within the industry has intensified. According to Imedia (2022), the growth rate of live online users in China declined from 16.5% in 2020 to 8.2% in 2021, while the growth rate of the Chinese LSC market size decreased from 226% in 2019 to 122% in 2020. Beyond the declining growth rate, LSC has also experienced a reduction in active user engagement, with discontinuance behavior emerging as a critical challenge for the industry. Discontinuance behavior poses a significant challenge, as it negatively impacts engagement and retention, as users who do not consistently engage with the platform are less likely to develop habitual usage patterns or long-term loyalty. Consequently, this may lead to lower retention rates, reduced user activity and diminished revenue generation for the platforms. Furthermore, inconsistent user engagement adversely affects content creators, who depend on a stable viewership to sustain their audience and revenue. Such LSC discontinuance can lead to significant losses for LSC platforms, sellers and content creators, as retaining users is essential for their long-term success and sustainable development (Mahmud et al., 2025). Therefore, to ensure the sustained development of LSC, it is crucial to further explore users’ discontinuance intention toward LSC.

While existing research has examined various aspects of LSC, most studies focus on the pre-adoption or consumption stage. For example, prior research explored factors influencing consumer purchase intention (Ma et al., 2022), impulsive purchase (Xu et al., 2020) or continuance purchase (Kuo and Hsu, 2022).

However, there remains a lack of research on LSC discontinuance, particularly regarding users’ cognitive and psychological responses. Similar to other social networking services (SNS), LSC may have some “dark sides.” Previous research has demonstrated that SNS usage can lead to unintended consequences, such as overload and fatigue. Nematzadeh et al. (2019) examined the LSC platform Twitch and proved that streams frequently attract large audiences, resulting in high message generation rates. They also highlighted that video content itself contributes to information overload. In the context of LSC, user fatigue remains an underexplored area, and its influence on switching intentions requires further investigation (Du et al., 2025). Scholars in the field of information systems have found that fatigue can lead to users’ discontinuous usage intentions (Lee et al., 2021). When users frequently feel fatigued from using the current LSC platform, they may discontinue its usage to avoid feeling fatigued and stressed. Within online social networks, excessive exposure to information impairs users’ ability to process content effectively, leading to cognitive strain. Information overload often results in users feeling overwhelmed and fatigued, triggering negative emotional responses (Chung et al., 2023).

LSC possesses distinct features, including real-time interaction, visualization, synchronicity, information complexity, and time pressure. While these characteristics can increase consumer purchase intention, they may also generate negative effects and lead to information overload. Prior research has not yet fully elucidated how these LSC specific features influence users’ internal psychological processes, ultimately leading to discontinuance intention. While enriching, existing studies are overly generic and largely confined to the initial adoption or consumption stage of LSC, limiting their ability to provide insights into discontinuance behavior. Also, limited studies explored the “dark sides” of the LSC features, particularly how these attributes influence users’ psychological states and discontinuance intentions.

Against those backdrops, this study aims to develop an overarching research framework that outlines the mechanism by exploring the relationships between live streaming commerce features, information overload, fatigue, and discontinuance intention. This study therefore addresses two key questions: how information overload in LSC contributes to consumer discontinuance intention, and which specific features (e.g., interactivity, visibility, synchronicity, information complexity, and time pressure) are the main contributors to information overload.

This study contributes to the LSC literature by identifying the factors that lead to information overload in terms of LSC. This study also extends the body of knowledge by examining the role of user fatigue in driving user discontinuance intention through the lens of information overload, which can be useful for LSC platforms, sellers and streamers to improve their service and retain their users.

The structure of this research is illustrated as follows. First, relevant theories and definitions are introduced, along with the proposed hypotheses. Then, the research methodology is illustrated, followed by an analysis of research results and discussion. The findings from an online survey are analyzed using statistical methods, and their implications are subsequently presented. Finally, the limitations of the study and future research suggestions are provided.

The Stressor-Strain-Outcome (SSO) framework, introduced by Koeske and Koeske (1993), outlines a sequential process in which stress inducing stimuli (stressors) trigger negative emotions (strain), ultimately leading to adverse behavioral outcomes (outcomes). The SSO framework is a theoretical paradigm that explores the development of pessimistic behavior in individuals, specifically focusing on the influence of stressors and strain from a negative perspective (Ding et al., 2017). Researchers have applied the SSO framework across various information systems (IS) contexts, such as consumer experiences on social commerce platforms (Li et al., 2021).

In the context of LSC, recommendation algorithms often contribute to information overload, which can induce negative emotional responses and disruptive usage behavior (Li et al., 2021). Under the SSO framework, information overload serves as a stressor, leading to psychological fatigue (strain), which in turn influences users’ discontinuance intention (outcome). Previous research has demonstrated that the SSO framework is appropriate for studying user behavior from an individual perspective (Fu et al., 2020). The SSO framework can be used to investigate the causes of negative behavioral outcomes. Additionally, adopting the SSO framework is advantageous, since it clearly distinguishes general psychological strain from other behavioral results rather than combining different behavioral and psychological outcomes under the concept of strain (Fu et al., 2020). Therefore, the SSO framework is used as the main theoretical framework to explore the discontinuance intention of LSC users, particularly from the perspective of information overload.

Using real-time video live streaming, the LSC enables streamers to demonstrate products to customers (Chen et al., 2022). In contrast to conventional e-commerce, LSC is characterized by several features, including interactivity (Kang et al., 2021), visibility (Wongkitrungrueng and Assarut, 2020) and synchronicity (Zhang et al., 2019).

The unique features of LSC have been explored by various studies. Interactivity plays a crucial role in shaping user experiences, as it enhances the flow of information and emotions during the shopping process (Sun et al., 2019). During live streaming, users engage in interactions not just with the broadcasters but also with other consumers through the chat box. Visibility is a critical aspect of LSC, as it allows products to be presented to customers in a clear and intuitive manner. Through live demonstrations, consumers gain a better understanding of a product’s appearance and functionality, facilitating a more immersive shopping experience (Zhang et al., 2022). Synchronicity, a defining characteristic of LSC, distinguishes it from traditional e-commerce by enabling consumers to receive instant feedback on their inquiries. Therefore, consumers can gain rich information in time and effectively reduce their doubts (Xu et al., 2020).

Beyond these established LSC features, this study incorporates information complexity and time pressure as additional key factors influencing information overload. The LSC increases the visual complexity and provides more information to support buyers’ judgment (Liu et al., 2023). Streamers often introduce multiple products within a single session while simultaneously engaging with viewer comments, significantly increasing the volume and intricacy of the presented information. However, individuals’ cognitive capacities to process large volumes of information are limited. The quality and complexity of information are related to the generation of information overload (Zhang et al., 2023). As for time pressure, it is deemed as an essential situational factor influencing consumers’ decision-making behavior, and it refers to the inadequacy of the time available for information processing or decision-making (Lv et al., 2022). Zhang et al. (2024) emphasized that shorter live streams with a similar number of products are more likely to induce information overload than longer sessions. In LSC, streamers frequently employ time sensitive promotions and limited time offers, consumers may experience psychological pressure. Therefore, information complexity and time pressure serve as critical antecedents of information overload in the context of LSC.

When processing requirements exceed people’s capacity for processing information, information overload occurs (Bawden and Robinson, 2020). Research has investigated information overload across various research settings, particularly in online shopping, where it has been found to impact purchase intention and decision-making. According to Mittal (2017), consumers vary in both their ability and willingness to acquire and analyze information before making purchasing decisions. Consequently, not all consumers benefit equally from the vast amount of readily available online information. The increasing number of information sources has led to an overwhelming influx of information, making rational decision-making increasingly difficult (Bawden and Robinson, 2020).

Information overload can lead to several detrimental consequences. Excessive information may cause individuals to feel confused and impair their ability to retain and recall previously acquired information (Bawden and Robinson, 2020). Information overload can cause several dysfunctional outcomes, such as stress and anxiety, ultimately reducing consumer satisfaction, confidence, and decision clarity (Zhang et al., 2023). Researchers have also emphasized the need to further explore the impact of perceived information overload on users’ mental health and stress conditions (Chung et al., 2023). Since individuals experience varying levels of stress across different social networking systems (SNSs), future research should examine the platform specific antecedents and consequences of information overload (Lee et al., 2016). Therefore, in this study, information overload is conceptualized as a stressor within the SSO framework, serving as a key factor in understanding users’ discontinuance intentions in LSC.

Fatigue refers to a multidimensional negative affective state experienced by users due to prolonged exposure to platform stressors (Zhang et al., 2024). Several emotional changes, including anxiety, depression and burnout syndrome, can be brought on by fatigue (Du et al., 2025). In online environment, Zhang et al. (2016) demonstrated that perceived information overload is a significant contributor to user fatigue, which in turn leads to discontinuous usage behavior. Maier et al. (2015) found that fatigue reduces SNS engagement, leading users to reduce activity, temporarily disengage or even delete their accounts.

Furthermore, Zhang et al. (2016) showed that user dissatisfaction and social network fatigue enhance discontinuance intentions. Even though individuals may enjoy online interactions, excessive engagement can lead to psychological strain and mental exhaustion (Chen et al., 2020). Similar to SNS platforms, LSC fosters real time interaction between consumers, streamers, and fellow shoppers, providing users with a highly engaging and interactive experience. While this interactivity enhances user engagement, it can also increase cognitive load, making fatigue a critical factor in LSC discontinuance. Given its relevance in consumer behavior studies, this study incorporates fatigue as the strain within the SSO framework to better understand its role in LSC discontinuance intention.

Discontinuance intention refers to a user level choice to stop using or reduce the usage frequency (Chung et al., 2023). In this research, discontinuance intention is defined as the consumer’s intention to alter the current state of their system use either by reducing their level of engagement or permanently discontinuing participation in LSC. Discontinuance intention may be activated when the user faces stress from many different factors (Mahmud et al., 2025). Discontinuance intention has been widely researched, for example, Maier et al. (2015) investigated how platform-related stressors (complexity, ambiguity and invasion) contribute to users’ intention to discontinue SNS usage due to fatigue. Hong and Oh (2020) explored the underlying causes of discontinuance intention among users of the Facebook.

However, research on discontinuance intention in LSC remains limited. Zhang et al. (2023) studied viewers’ discontinuance intention toward entertainment live streaming platform and found that cognitive dissonance leads to users’ discontinuance intention. Chen and Li (2024) examined how expectation violations in human virtual streamer interactions impact consumers’ discontinuance behavior. Despite these studies, there is a lack of research on discontinuance intention within LSC, particularly from the perspectives of cognitive psychology and behavioral responses. This study seeks to fill this gap by examining the psychological mechanisms underlying LSC discontinuance intention, contributing to a more comprehensive understanding of user retention and engagement dynamics in live streaming commerce.

The Figure 1 captures the hypothesized model.

Information complexity refers to the number of distinct aspects or features included in a website, which may arise from increased diversity of information (Huang, 2000). The complexity of an online shopping site can be evaluated based on its density of content, breadth of product offerings and the degree of visual or textual congestion (Huang, 2000). There exists a nonlinear relationship between information complexity and users’ information processing capacity. Paul and Nazareth (2010) examined this relationship in group decision-making contexts and found that higher input complexity accelerates information processing demands, which may result in information overload.

In the context of LSC, streamers integrate product and service information directly into the background of live streams, enhancing information complexity while providing buyers with additional details to aid decision-making (Tong et al., 2022). Meanwhile, LSC consumers receive real time information from both streamers and other viewers via visual communication and bullet screen comments, further amplifying information complexity. Accordingly, this article proposes that:

Time pressure is defined as consumers’ perception of insufficient time for information processing or decision-making (Lv et al., 2022). It is considered a critical situational variable that significantly influences consumers’ decision-making processes. Consumers’ decision-making process can be accelerated by time pressure (Peng et al., 2019). When under high time pressure, the impact of emotions on impulsive purchases is amplified.

When consumers face high time pressure, information overload tends to intensify, as individuals have less time to process and evaluate information effectively (Peng et al., 2019). In the context of LSC, streamers often create a sense of urgency and scarcity by limiting inventory and imposing time constraints, encouraging consumers to make immediate purchasing decisions. Therefore, this research proposes that:

Visibility is defined as the extent to which live streaming facilitates product demonstration for potential consumers (Sun et al., 2019). In LSC, visibility is primarily realized through real time video demonstrations, enabling streamers to showcase products, communicate detailed features and demonstrate correct usage scenarios. Previous research has emphasized that LSC visibility enhances consumer trust by offering comprehensive product information. However, the visual nature of live streaming means that increased visibility also corresponds to a higher volume of visual stimuli. As visibility increases, the volume of information cues also rises, making it more challenging for consumers to identify key information amidst the abundance of details (Stohl, 2016). As a result, visibility may lead to information overload, as the influx of visual cues can exceed consumers’ limited cognitive capacity to process and evaluate them efficiently. Therefore, this research proposes that:

Interactivity, a key characteristic of LSC, fosters user engagement by encouraging active communication and transactional behaviors. Interactivity in LSC can be examined from three perspectives (Sun et al., 2019). First, high density information exchange occurs when streamers respond to customer comments and notifications displayed on the screen, providing real time updates and essential information. Second, performative interactivity involves streamers explaining products directly to the audience while engaging with viewers. Third, persuasive merchandizing involves the repetitive reinforcement of key selling points through scripted or emphatic marketing language. Nevertheless, interactivity in LSC provides a greater amount of information in comparison to traditional e-commerce. This can also result in an overwhelming amount of information or low quality information, such as meaningless emotions or behaviors, flooding the live streaming room (Kang et al., 2021). Additionally, consumer-to-consumer interactions through chat features further amplify information density, as LSC aggregates input from multiple sources. Accordingly, this study proposes the following hypothesis:

In the context of LSC, consumers submit inquiries and receive feedback simultaneously, making synchronicity a critical feature that enhances the speed of interaction. Synchronicity allows consumers to obtain instant responses from streamers or fellow viewers (Li et al., 2021). For streamers, it facilitates the rapid identification of consumer queries and enables real time responses through verbal explanations or live product demonstrations (Wang et al., 2019). However, when consumers receive a large volume of information cues simultaneously, they require additional time to process and evaluate the content effectively. Higher synchronicity levels may impair comprehension, as individuals may not have sufficient time to thoroughly analyze the information being presented. Accordingly, this study proposes the following hypothesis:

Human decision-making is limited by cognitive constraints, available information and time. Therefore, an excess of information diminishes the decision maker’s ability to allocate attention effectively, leading to a poverty of attention (Wan and Liu, 2025). Information overload influences consumer perceptions and has been identified as a contributing factor to social network fatigue. An overwhelming volume of information is a primary source of psychological stress and has been directly linked to social media fatigue (Liu et al., 2021).

This study defines LSC fatigue as a detrimental emotional response resulting from prolonged engagement in LSC activities. Fatigue is perceived as a subjective and unpleasant sensation of exhaustion that encompasses various aspects, including duration, unpleasantness and intensity (Lee et al., 2016). Cao and Sun (2018) emphasized that information overload arises when individuals are required to process information beyond their cognitive limits, inducing stress and negative emotions. As users continuously receive an overwhelming stream of information, they may experience mental fatigue. Such overload surpasses users’ cognitive processing capacity, ultimately triggering emotional exhaustion. Accordingly, this study proposes the following hypothesis:

Previous studies have identified social network fatigue as a crucial psychological factor contributing to negative user behaviors, such as reduced engagement or complete disengagement (Hwang et al., 2019). Fatigue has received considerable attention in social network research, with studies exploring its impact on various aspects of user behavior, including user engagement (Zhang et al., 2020), usage intention (Niu et al., 2022) and usage intensity (Zhu and Yao, 2025). Negative psychological states that users experience when using social networks, such as stress or fatigue, have been recognized as key determinants of discontinuance behavior in social networks (Luqman et al., 2017). Zhang et al. (2016) demonstrated that users’ fatigue caused by overload during the usage process led to discontinuance intention. Accordingly, this study posits that fatigue experienced within the LSC context may significantly influence users’ discontinuance intention.

H7. Fatigue increases live streaming commerce users’ discontinuance intentions.

All constructs were measured using items adapted from prior validated scales. To ensure contextual relevance, minor adjustments in wording were introduced (e.g., replacing “social media” with “live streaming commerce”). The adapted items were then reviewed by two academic experts to ensure content validity. The scale for information complexity was adapted from Huang (2000), and the scale for time pressure was adapted from Lv et al. (2022). The scales of visibility, synchronicity, and interactivity were adapted from Sun et al. (2019), Li et al. (2021) and Ma et al. (2022), respectively. The scale of information overload was adapted based on the research of Lee et al. (2016), and the scales for fatigue and discontinuance intention were adapted from Lee et al. (2016) and Lin et al. (2020). All items were measured using a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). The measurement items for each construct were summarized in  Appendix.

China is recognized as the largest LSC market globally, with over 400 million people engaging in LSC. Thus, this study chose Chinese LSC users as the respondents. An online questionnaire survey was conducted via Wenjuanxing (Link to Questionnaire Stars can meet your various questionnaire/form needsLink to the webcite of wjx.), a widely used professional data collection platform in China. Wenjuanxing has been extensively utilized by Chinese researchers for academic surveys. The minimum sample size was determined using G-power software. An effect size of 0.15 (medium) and the statistical power of 0.80 were used to ensure that the research had sufficient power to identify the desired effect. The calculation yielded a minimum sample size of 92 participants (see Figure 2). However, given the self-administered nature of the survey, a larger sample was collected to enhance data reliability. A screening question was posed at the start of the survey: “Have you ever engaged in live streaming shopping?” Only participants who answered “yes” were eligible to proceed. Out of 561 respondents, 414 confirmed prior engagement in LSC, making the final sample size 414.

Participants were given approximately 15–20 min to complete the questionnaire. Only those who passed the screening question were permitted to continue with the full survey. Table 1 presents the demographic characteristics of the sample. Females accounted for 58.5% of respondents. The majority (50.5%) were aged 35–55 years. Additionally, 37% of respondents held a bachelor’s degree. Most participants (36.7%) reported spending 3–5 h per week watching live streaming commerce.

This study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) for data analysis using SmartPLS 4.0.1.3. PLS-SEM is particularly useful in the initial phases of theory building as it allows for the modeling of latent variables, even when working with samples of small to medium sizes (Chin et al., 2003). PLS-SEM is well suited for exploratory research, making it an appropriate method for this study, given the limited research on information overload in LSC. Thus, SmartPLS was chosen to assess the research model.

The measurement model was evaluated using indicator loadings, Cronbach’s α, composite reliability (CR) and average variance extracted (AVE), as summarized in Table 2. All items have a loading above 0.7, which meets the acceptable criterion (Chin, 1998).

The Cronbach’s alpha and composite reliability values for all items were above 0.7, while the average variance extracted (AVE) values were greater than 0.5. This indicates a satisfactory level of reliability and convergent validity (Chin, 1998). The latent variables have CR values greater than 0.8 and Cronbach’s alpha value greater than 0.7, which indicates acceptable internal consistency (Nunnally and Bernstein, 1994).

The AVE was calculated to evaluate the convergent validity, and the findings indicate that the AVE values exceed 0.6, suggesting that over 60% of the variability in the indicators can be explained by the latent variables.

Discriminant validity was assessed using the Fornell–Larcker criterion, which requires that each construct’s AVE square root be greater than its correlation with other constructs. Table 3 presents evidence indicating that the values located on the diagonal of the table are greater in magnitude than the values located off the diagonal. This demonstrates an adequate degree of discriminant validity.

Given that all questionnaire responses were self-reported, common method bias was assessed using Harman’s one-factor test. Harman (1976) indicates that common method bias is considered significant if a single factor explains more than 50% of the variance, and the results indicate that none of the factors account for the majority of the overall variance. The results showed that no single factor explained the majority of the variance. Additionally, variance inflation factor (VIF) scores were examined as an alternative test. The VIF values ranged from 1.29 to 1.573, well below the recommended threshold of 3.3, confirming that common method bias is not a concern (Kock, 2015).

Overall, the outcomes of the instrument validity tests indicated that the measurement model demonstrated acceptable reliability and validity.

Following the suggestions of Hair (2017), we present the path coefficients, standard errors, t-values and p-values for the structural model by using a resampling bootstrapping approach with 10,000 samples (Ramayah et al., 2016).

Figure 3 and Table 4 represent the results of the structural model, the results of path analysis indicate that information complexity significantly influences information overload (β = 0.187, p < 0.001), visibility has a significant positive influence on information overload (β = 0.222, p < 0.001), thus, H1 and H3 are supported. Interactivity (β = 0.119, p < 0.05) and time pressure (β = 0.09, p < 0.05) showed significant positive relationships with information overload, therefore H2 and H4 are supported. Information overload has a positive impact on fatigue (β = 0.295, p < 0.001) and fatigue has positive impact on user discontinuance intention (β = 0.121, p < 0.01). Thus, H6 and H7 are supported.

A bootstrapping approach was employed using 10,000 samples to create and evaluate the confidence ranges for indirect effects. The findings indicate that fatigue (β = 0.036, p < 0.05) acts as a mediator between information overload and the discontinuance intention.

In this study, gender, age and time spent on LSC were included as control variables to examine the potential influence of individual differences on fatigue and discontinuance intention in LSC. The results indicate that gender significantly affects both user fatigue and discontinuance intention in LSC. Age has a significant effect on fatigue but not on discontinuance intention. Time spent on LSC per week did no significant effect fatigue and discontinuance intention.

Based on the SSO framework, this study provides a deeper understanding of users’ discontinuance intention in LSC, particularly from the perspective of cognitive psychology and behavioral responses. This study develops a comprehensive research framework that explores the mechanisms underlying the relationships among live streaming commerce features, information overload, fatigue and discontinuance intention. The results indicate that information complexity, visibility, time pressure and interactivity are positively associated with information overload, which in turn, leads to user fatigue and ultimately contributes to discontinuance intention.

The findings confirm that information overload significantly contributes to fatigue, aligning with previous research (Cao and Sun, 2018; Lee et al., 2021). The overwhelming influx of information through digital systems can exhaust cognitive resources, impairing decision quality and increasing stress (Wan and Liu, 2025). Meanwhile, Zhang et al. (2022) found that information overload increases users’ fatigue in terms of social media, which lead to users’ switching intention. Despite extensive literature on information overload in online environments, limited research has investigated its impact on cognitive factors (e.g., fatigue) in LSC. Meanwhile, this research finds that users’ fatigue is positively related to discontinuance intention. Fatigue is identified as a negative psychological process driven by information overload, which in turn leads to user disengagement from LSC. If users experience negative feelings, such as fatigue, they might alter their responses to prevent the emergence of the undesirable situation and free themselves from emotional disability, resulting in the discontinuance behavior. Users experiencing fatigue may seek to avoid negative emotions by reducing or ceasing their engagement with LSC, opting instead for alternative shopping methods.

Regarding LSC characteristics, the results indicate that the information complexity, visibility, time pressure, and interactivity increase information overload, which subsequently leads to user fatigue. Paul and Nazareth (2010) examined how information complexity affects decision-making in group settings, demonstrating that increased complexity leads to information overload. In terms of LSC, streamers tend to emphasize products and service details, which further increases the information complexity. Furthermore, visibility, time pressure, and interactivity are found to positively impact information overload, contributing to user fatigue. Previous research has mainly focused on exploring the positive sides of LSC, such as the interactivity and visibility would increase purchase intention (Ma et al., 2022; Sun et al., 2019). However, this study challenges the conventional assumption that ‘more is better’ in context of LSC, since interactivity and visibility also cause information overload and increase fatigue. Contrary to our expectations, synchronicity was not a significant predictor of information overload in LSC, while previous research suggested that higher synchronicity may decrease human understanding since people may not have enough time to fully process relevant information. This finding may be explained by selective attention theory, which posits that individuals focus selectively on key information while disregarding less relevant details. In LSC, viewers primarily focus on streamers’ responses and product demonstrations, often ignoring other consumers’ comments. This self-filtering mechanism allows users to focus on essential information without becoming overwhelmed. Moreover, consumers do not necessarily need to process all available information during LSC sessions; rather, they prioritize key factors influencing purchase decisions. Therefore, although synchronicity shortens information processing time, it does not necessarily lead to information overload.

In summary, this study confirms that information overload functions as a stressor, leading to fatigue and, ultimately, discontinuance intention in LSC. By systematically examining the relationships among LSC features, information overload, fatigue, and discontinuance intention within the SSO framework, this research offers valuable theoretical and practical insights.

This study empirically explored and extended the proposed SSO framework in the LSC industry by exploring the relationship between LSC features and information overload, which can further drive user fatigue and lead to consumer discontinuance intention. This study shows that LSC features such as time pressure, visibility, interactivity, and information complexity can lead to negative outcomes, such as information overload. By identifying information overload as the primary stressor, this study expands the application of the SSO framework in the emerging LSC sector, confirming that information overload induces user fatigue and ultimately results in discontinuance intention.

This study offers a novel perspective on LSC discontinuance intention, an area that remains underexplored in current literature. Previous studies on LSC have primarily focused on positive outcomes of LSC features, such as purchase intention, user acceptance and impulsive purchase (Ma et al., 2022; Sun et al., 2019). Ding et al. (2025) investigated unfollowing intention in terms of tourism live streaming commerce, but they still mainly focus on the comparison between the current LSC and the alternatives. However, unintended consequences, such as user fatigue and discontinuance intention, require further exploration to achieve a more comprehensive understanding of LSC. It is among the first empirical studies to validate the relationships among LSC features, information overload, fatigue, and discontinuance intention, paving the way for further research on the drawbacks of LSC engagement.

Moreover, this study enhances the understanding of LSC discontinuance behavior by identifying the psychological mechanisms that drive disengagement. This study finds that discontinuous usage functions as an adaptive response strategy used by LSC users to avoid feeling fatigued. This study demonstrates how incorporating knowledge from the field of social psychology can improve the understanding of new commerce methods. Future studies should further investigate the negative implications of LSC features to develop more user-friendly live streaming environments.

This study provides several practical implications for LSC users, sellers, and platforms. LSC users should recognize that excessive engagement with LSC may lead to negative experiences, such as information overload and fatigue. Therefore, they can mitigate information overload and fatigue by limiting their viewing hours or utilizing screening functions to filter out nonessential information, allowing them to focus only on key content.

For LSC sellers, they should be aware that even though LSC can be an effective method to sell products, the features of LSC also need to be used carefully to avoid negative outcomes, such as information overload. Streamers should prioritize quality over quantity in interactions, as excessive engagement can overwhelm consumers. For example, during live streaming, streamers should organize their content into structured segments and highlight essential messages to maintain meaningful interactions without overwhelming the viewers. Meanwhile, streamers should adopt methods to alleviate consumers’ fatigue, since fatigue significantly affects users’ discontinuance intentions. For example, streamers can adopt gamification engagement (e.g., surprise prizes or rewards) to sustain viewer engagement and alleviate cognitive strain.

For LSC platforms and managers, greater attention should be given to the “dark sides” of LSC, particularly the negative impact of information overload on consumer well-being. Platforms should offer flexible user settings to allow consumers to customize their experience. For example, users should have the option to disable live chat, enabling them to focus solely on the streamer’s content when feeling overwhelmed. Meanwhile, users’ attempts to discontinue LSC platforms should be monitored and addressed to reduce user attrition. Table 5 summarizes the research conclusions and implications.

Despite its contributions, this study is subject to several limitations that provide opportunities for future research improvement. First, data collection relied on an online survey, which captures user perceptions but may lack insights into the real time process of information overload and discontinuance behavior. Future research could adopt experimental designs to observe and measure how information overload develops and influences discontinuance behavior dynamically. Additionally, factors such as personal characteristics should be incorporated into experimental studies to enhance internal validity. Second, the sample primarily consists of LSC users in China. Future research should consider LSC users in different cultural contexts. Third, this study used cross-sectional data to test the research model. The questions of whether users generate discontinuance intention may change over time. Therefore, future studies should adopt longitudinal analyses to explore user discontinuance intention in the context of live streaming commerce. This study explored negative aspects of China’s live streaming commerce, focusing on how information overload can lead to user fatigue and ultimately result in discontinuance intention. As the market becomes increasingly saturated and competition intensifies, it is important for future research to explore the potential factors that lead to the declining trend in this industry.

This study is among the few that systematically investigate both the antecedents and consequences of information overload in the context of live streaming commerce, thereby advancing theoretical understanding in this emerging field. Using the SSO model, this study examines how key features of LSC (information complexity, time pressure, visibility, interactivity and synchronicity) contribute to information overload, which leads to fatigue and ultimately increases discontinuance intention. The results confirm that information complexity, time pressure, visibility, and interactivity have significant positive effects on information overload, whereas synchronicity does not exhibit a statistically significant relationship. Furthermore, the findings demonstrate that information overload leads to user fatigue, which subsequently contributes to discontinuance intention.

Information complexity (Huang, 2000):

1. The information on live streaming commerce is complex.

2. The information on live streaming commerce is crowded.

3. The information on live streaming commerce is large scale.

Time pressure (Lv et al., 2022):

1. I must hurry if I am to buy products recommended by live streaming.

2. I feel pressured to buy products recommended by live streaming quickly.

3. I do not have enough time to buy products recommended by live streaming.

Visibility (Sun et al., 2019):

1. Live streaming shopping provides me with detailed pictures and videos of the products.

2. Live streaming shopping makes the product attributes visible to me.

3. Live streaming shopping makes information about how to use products visible to me.

Interactivity (Ma et al., 2022):

1. The streamers were very happy to communicate with viewers.

2. The streamers actively responded viewers’ questions.

3. The streamers answered viewers’ questions and requests in time.

4. The streamers provided relevant information for viewers’ inquiries.

Synchronicity (Li et al., 2021):

1. When I am watching live streaming, the platform processes my comments inputs very quickly.

2. When I am watching live streaming, seeing comments sent by other viewers is very fast.

3. When I am watching live streaming, I am able to see others’ comments without any delay.

4. When I am watching live streaming, the platform is very quick in responding to my comment’s inputs.

Information overload (Lee et al., 2016):

1. I am often distracted by the excessive amount of information on live streaming commerce.

2. I am overwhelmed by the amount of information that I process on live streaming commerce.

3. I feel that there is more information than I could synthesize on live streaming commerce.

4. There is too much information on live streaming commerce, so I find it a burden to handle.

5. I find that only a small part of the information on live streaming commerce is relevant to my needs.

Fatigue (Lee et al., 2016):

1. Sometimes I feel tired when using live streaming commerce.

2. Sometimes I feel bored when using live streaming commerce.

3. Sometimes I feel drained from using live streaming commerce.

4. Sometimes I feel worn out from using live streaming commerce.

Discontinue intention (Lin et al., 2020):

1. In the near future, I will use live streaming commerce far less than today.

2. In the near future, I will use another online shopping methods.

3. In the near future, I will unregister from current live streaming commerce.

4. If I could, I would discontinue the use of live streaming commerce in the near future.