Workplace fear of missing out, organizational support and performance: the mediating role of work-related social media use

We apply the principles of conservation of resources (COR) theory to understand the role of WRSMU in the relationship between organizational support, fear of missing out and job performance. As a theory of employee motivation, the central premise of COR theory is that employees are motivated to protect resources and acquire new ones (Halbesleben et al., 2014; Hobfoll, 1989). Resources can be loosely defined as objects, conditions, or something of value to an individual (Hobfoll, 1989). Job resources are important job conditions underlying employee well-being and performance (e.g. Bakker et al., 2005; Bakker et al., 2004).

A closer look at the psychological process underlying the conservation and acquisition of resources reminds us of several principles of COR theory relevant to the current study. The first principle is the primacy of resource loss, which refers to the notion that a loss of resources is more harmful to an individual than a similar gain in resources. This means employees are motivated to avoid resource losses (Whitman et al., 2013). A second principle pertains to resource investment. This suggests that employees invest resources to protect against loss, recover from loss, and gain resources (Hobfoll, 2002). Research suggests that resource investment refers to both gaining and spending resources (Halbesleben et al., 2014).

Extending the principles of resource conservation and acquisition to the current study, we suggest that employees may use resources to protect and gain additional resources, and are motivated to avoid a potential resource loss. Several studies have suggested that the use of social media for work-related purposes can be seen as a resource that may help employees achieve individual or organizational goals (e.g. Bulgurcu et al., 2018). The facilitating conditions that assist employees and offer the opportunity to adopt and use new technology (Thompson et al., 1991; Venkatesh et al., 2003). Based on the unified theory of acceptance and use of technology (UTAUT) model, prior studies show that facilitating conditions are an essential antecedent for any system or technology use (Venkatesh et al., 2012). If the organization provides support or facilitates conditions, it can represent technological support and guidance provided by the organization to engage in work-related social media use (Bodhi, 2021). Moreover, prior studies show that organizational support is recognized as an essential factor that is significantly and positively related to any technology use (Venkatesh et al., 2012) or enterprise social media use (Bodhi, 2024). Furthermore, organizational support is an oft-cited psychological resource central to COR theory, as it is a resource that employees typically seek to protect and cultivate to further individual and organizational performance (Luqman et al., 2021).

Finally, our focus on FoMO is informed by COR theorizing because workplace FoMO highlights employees’ apprehension of missing out on valuable career opportunities, relative to other employees, when disconnected from work (Budnick et al., 2020). COR theory articulates that employee seek to avoid resource loss, repair such losses, and seek to gain new resources (Hobfoll, 1989). However, research drawing on COR theory has also cautioned against the reliance on technologies as excessive technology use may deplete resources, increase performance pressure, and lead to long hours (Dutta and Mishra, 2024). Based on this central assumption, we posit that workplace FoMO may motivate WRSMU as employees attempt to prevent missing out on valuable resources (e.g. information) while organizational support for social media can be viewed as an intangible resource that enables employees to gain additional resources (e.g. informational resources through WRSMU; Ellison et al., 2007). Moreover, drawing upon the Elaboration Likelihood Model (Petty and Cacioppo, 1986) and Social Influence Theory (Kelman, 1958), the use of technology as an informational resource in the area of health care (Bhagat and Kim, 2023). Moreover, based on COR theory, a recent study considers enterprise social media use as an informational resource that positively affects work performance (Bodhi, 2024). Thus, the present study considers WRSMU as an essential informational resource that may affect the performance of employees. Furthermore, the frequency of social media use may moderate these relationships as frequent technology use may deplete resources (Dutta and Mishra, 2024). We visualize the nomological network based on COR theory (See Figure 1). Below, we present empirical evidence to support our hypotheses.

With the advent of social media technologies FoMO has become a more central part of social and working life (Buglass et al., 2017). FoMO refers to an individual’s feeling of missing out on positive social experiences and potential social exclusion (Przybylski et al., 2013). Prior studies have found a positive relationship between FoMO and non-work social media use (Elhai et al., 2018; Roberts and David, 2020), digital device usage (Alt, 2017; Beyens et al., 2016), and social media engagement (Alt, 2017, 2018; Reer et al., 2019) in a general context. In organizational contexts, FoMO is typically referred to as workplace FoMO (Budnick et al., 2020). Budnick et al. (2020) define workplace FoMO as “pervasive apprehension that, relative to other employees, one might miss valuable career opportunities when away or disconnected from work.” Prior studies have stated that workplace FoMO is positively associated with information-seeking and social media engagement. Moreover, several studies have established a direct relationship between workplace FoMO and social media use (Tandon et al., 2021a, b; Van Zoonen et al., 2022). Workplace FoMO might serve as a motivational resource that triggers employees to engage in organizational-related communication (Budnick et al., 2020). Moreover, we argue that employees may be motivated to engage in work-related social media to avoid the feeling of missing out on valuable resources. Hence, we hypothesized that

Recent years have witnessed growing research attention to FoMO in disciplines such as management and behavioral sciences. Prior studies have extensively studied FoMO and its association with psychological outcomes such as well-being, especially in non-work settings (e.g. Elhai et al., 2020; Stead and Bibby, 2017). However, research has only scratched the surface of examining the relationship between workplace FoMO and work-related outcomes such as job performance. A notable exception is a recent study by Fridchay and Reizer (2022) who demonstrated that FoMO is negatively and significantly associated with overall job performance. Employees high in FoMO might be particularly alert to their technological devices and expand resources and attention to notification and technological interferences. This results in lower employee performance levels (Fridchay and Reizer, 2022). Bodhi et al. (2022) have stated that FoMO is negatively but insignificantly associated with innovative work performance. Furthermore, Budnick et al. (2020) suggest that FoMO may harm employees’ health and performance. Hence, based on the above, we hypothesized that:

Interestingly, while workplace FoMO may reduce employee performance (Fridchay and Reizer, 2022), workplace FoMO also increases WRSMU (Van Zoonen et al., 2022). However, in the presence of WRSMU, fear of missing out may positively influence routine performance, in statistical terms referring to competitive mediation (Hair et al., 2016). Conceptually, we suggest that while the negative relationship between FoMO and performance is rooted in the anxiety and diverts attention away from work tasks, FoMO may also trigger a compensatory mechanism by motivating WRSMU, allowing employees to build resources and acquire information that may aid their performance. In addition, especially concerning work-related use, we suggest that social media may not merely represent a distraction from tasks but may actually help employees to be informed and connected, enhancing task performance.

While the relationship between WRSMU and performance is not univocally positive, a recent meta-analysis indicated that using social media makes employees more productive (Wu et al., 2021). Conversely, if workplace FoMO motivates the use of social media for work, and such use represents important resources that support job performance, we could argue that FoMO enhances job performance through WRSMU. Hence, we suggest, drawing on COR principles, that the workplace FoMO represents the threat of missing out on valued resources, which motivates employees to obtain and protect informational resources through social media use (Van Zoonen et al., 2022). These resources, in turn, may contribute to employee performance (Bakker et al., 2004). Hence, we hypothesize:

Organizational support is essential for motivating the adoption and use of any technology or system (Eisenberger et al., 2020; Venkatesh et al., 2008). Organizational support refers to facilitating conditions that assist employees and offer the opportunity to adopt and use a new technology (Thompson et al., 1991; Venkatesh et al., 2003). Facilitating conditions are “the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system” (Venkatesh et al., 2003). In the context of technology use, providing support for users may be one type of facilitating condition (Venkatesh et al., 2003, 2008). Thus, organizational support refers to facilitating conditions in context to support related to technologies or system uses (Bodhi, 2021; Venkatesh et al., 2003). Guenzi and Nijssen (2020) stated that organizational support would help build skills and self-efficacy in using social media. Organizational support can be a valuable resource for employees to alleviate stress associated with fear, failure, or uncertainty surrounding technology use in organizations (Eisenberger et al., 2020). Importantly, organizational support, in general, is an important resource employees seek to protect and enhance (Halbesleben et al., 2014). Research has suggested that work-related social media communication can enhance occupational resources such as support (Oksa et al., 2021). Hence, in line with COR principles, we suggest that organizational support is an important antecedent to WRSMU, as employees can engage in such social media use to enhance supportive resources.

Indeed, prior studies show a positive and significant relationship between organizational support (e.g. facilitating condition) and social media usage behavior (El Ouirdi et al., 2016). In addition, Pekkala and van Zoonen (2022) demonstrate that organizational support increases WRSMU. Moreover, Schmidt et al. (2016) reported a positive correlation between organizational support and the number of co-worker connections on social media. Hence, we propose that organizational support is an important resource that helps employees obtain additional (informational) resources through WRSMU. We hypothesize that:

Organizational support strengthens self-efficacy, increases employees' positive orientation, and supports individual and organizational goal attainment (Eisenberger et al., 2020). Prior studies have researched the impact of organizational support on employees' abilities and performance. A meta-analysis, covering twenty years of study, indicates that organizational support has a moderate but positive impact on employee performance (Riggle et al., 2009). These findings were later corroborated in a meta-analytical review of 558 studies on organizational support theory (Kurtessis et al., 2017). Thus, if employees receive high organizational support, they are more likely to perform better at their jobs (Zhong et al., 2016). Organizational support is a valued resource that could bolster employees’ confidence and ability to cope with demands and stressors at work (Jawahar et al., 2007), thus enhancing performance. Hence, we hypothesize:

We have already established that social media use in organizational settings may enhance employee performance (Jafar et al., 2019; Song et al., 2019; Sun et al., 2020). For instance, extant literature shows that WRSMU (e.g. information sharing, learning, and innovation) enhances overall employee performance (Jafar et al., 2019). In addition, we have also argued that organizational support is positively related to WRSMU. Conversely, we forward the assumption that organizational support may help employee obtain additional resources through WRSMU, which will be positively associated with their performance.

Various studies on social media use in organizations warn about excessive or addictive usage patterns. Indeed, building on COR theory, this may be problematic as frequent use of social media may lead to the depletion of resources due to demands for attention and information processing (Luqman et al., 2021; Yu et al., 2018). Hence, while WRSMU may facilitate routine and innovative performance at high frequencies, social media use may stifle performance. For instance, the high-frequency usage or problematic social media use leads to low self-control, difficulties in impulse control, and goal-oriented behavior (Lewin et al., 2022; Leijse et al., 2023). Wang et al. (2022) argued that the frequency of social media use may moderate the implications of WRSMU for employees’ creative performance, as it decreases the quality of interactions.

In addition, according to the resource conservation tenet of COR theory, a higher frequency and intensity of social media use may deplete resources, mitigating the benefits of WRSMU for routine and innovative performance. In line with this, research has demonstrated the moderating effects of the frequency of attention regulation through enterprise social media on the relationship between social-related enterprise social media use and collaboration (Zhang et al., 2023). We extend this reasoning to WRSMU and suggest that higher frequencies of social media use may ultimately mitigate the benefits of WRSMU for job performance by depleting available resources. Hence, in line with COR theory, drawing on the notion that excessive usage patterns may deplete rather than generate resources, we suggest that the frequency of social media use for work will moderate the relationship between WRSMU and work performance. Thus, leading to the following assumptions:

For this study, we invited respondents through e-mail in selected organizations. We used a purposive and random sampling approach for the data collection. First, we engaged in purposive sampling by identifying organizations that had implemented social media technologies. In these organizations, employees are enabled to access work-related social media, such as enterprise social media, for use at work. At first, 16 organizations were identified for the survey in northern and southern India. However, only 12 organizations’ HR managers or organizational channels agreed. We continued drawing a random sample of employees in these organizations using a simple random sampling approach, sending invites to a total of 300 individual participants. This resulted in a sample of working professionals employed at different organizations in the services industry (i.e. IT and ITeS; information technology enables services). We received responses from 267 employees. After discarding 32 responses due to unfilled responses, the final sample consisted of 235 employees. During the data collection process, the authors guaranteed respondents’ confidentiality and anonymity, encouraging them to provide genuine answers. Of our respondents, 68.9% were male, and their ages ranged between 18 and 54 years. These respondents worked at junior (36.2%), middle (51.5%) or senior (12.3%) level.

The survey items were adapted from existing literature and it measured on five-point Likert scale “strongly disagree = 1” to “strongly agree = 5”. The items are listed in  appendix

Workplace Fear of missing out (FoMO) was measured with a five-item scale previously reported by Budnick et al. (2020) and Tandon et al. (2021a). A sample of these items was “I get worried when I might miss important work-related updates.” The Cronbach’s alpha values is 0.85. Organizational support was measured with a four-item scale from Thompson et al. (1991) and Bodhi (2021). A sample of these items was “A guidance is available to me for selection of different social media platform”. The Cronbach’s alpha values is 0.87. Innovative work performance was measured using three items previously reported by Janssen and Van Yperen (2004), Ali-Hassan et al. (2015) and Zhang et al. (2021). A sample of these items was “Create new ideas for improvements.” The Cronbach’s alpha values is 0.85. Routine work performance was measured using three items from Janssen and Van Yperen (2004) and Ali-Hassan et al. (2015). A sample of these items was “I always complete the duties specified in my job description.” The Cronbach’s alpha values is 0.81. Work-related social media use (WRSMU) was measured with a six-item scale previously reported by Bodhi et al. (2023). A sample of these items was “Social media has become part of my daily routine.” The Cronbach’s alpha value is 0.86. Frequency of social media use (FSMU): Employees were asked to provide the frequency of using social media during work time to interact, communicate, and share information. We used a single-item reading: “When you are at work, how often do you use social media?” (a) Never (b) About once a day (c) 2–5 times a day (d) 6–10 times a day (e) Every hour (Phillips and Wisniewski, 2021; Swirsky et al., 2021). Beyond conceptual differences, we opted for this classification over, for instance, time spent in minutes, given known measurement error due to respondent recall of technology use (Araujo et al., 2017). Finally, we included several control variables: Prior studies have emphasized that job performance may be affected by gender and age (Bernerth and Aguinis, 2016; Siders et al., 2001). Thus, the present study has controlled “gender” and “age” as control variables to mitigate the confounding impact of such variables in the analysis.

To test the reliability and validity of study constructs, we employed a confirmatory factor analysis on partial least squares structural equation modeling (PLS-SEM) 3.0. We also utilized PLS-SEM 3.0 to test the structural model (hypotheses testing). We utilized PLS-SEM as the method of data analysis because (a) it is less restrictive and has more statistical power than covariance-based SEM (CB-SEM), and (2) it estimates complex models without imposing distributional assumptions on the data (Hair et al., 2016). The reliability and validity results are shown in Table 1 and Table 2. Moreover, the variance inflation factor (VIF) values have been calculated to check multicollinearity issues (Table 2). Furthermore, the Harman’s single-factor test was also performed before hypothesis testing to check common method bias (CMB). Additionally, we utilized a common latent factor (CLF) test and compared the standardized regression weights of all measurement items of the model with and without CLF. The differences in standardized regression weights were less than 0.20, which confirms CMB is not a concern (Archimi et al., 2018) in the present study. Subsequently, the path analysis was performed, and the results are shown in Tables 3 and 4. The path analysis (SEM) considered the bootstrapping approach as per the guidelines of Hair et al. (2016). Furthermore, the interaction plots for moderation analysis are exhibited in Figure 3.

First, we evaluated the construct’s validity and reliability. Cronbach’s alpha and composite reliability values were more than 0.80, indicating good construct reliability and internal consistency (Hair et al., 2019). The average variance extracted (AVE) values for all constructs are above 0.50, which implies good convergent validity (Fornell and Larcker, 1981). Factor loadings were higher than 0.7, suggesting good convergent validity, exceeding the recommended value, i.e. 0.70.

Moreover, discriminant validity was examined as recommended by Fornell and Larcker (1981). We compared the value of squared roots of AVEs to its applicable construct’s correlations, and the square roots of AVE scores were higher than the construct’s correlations, indicating good discriminant validity.

Furthermore, we assessed the discriminant validity of our study constructs. In this vein, the heterotrait-monotrait ratio (HTMT) values are evaluated. The scores of study constructs were all under 0.85 (Henseler et al., 2016), which supports the discriminant validity of the constructs. Additionally, we evaluated VIF values presented in Table 2 to check multicollinearity issues and found that the VIF values were not higher than the cut-off value of 3.0 (Hair et al., 2016). Hence, multicollinearity is not an issue for this study.

Since this study relies on cross-sectional survey data collected from employees, we performed different tests to find any concern regarding the common method bias. First, Harman’s single test was employed, and it observed that the maximum covariance explained by a single factor is 36.65%, which is far less than 50%. Second, to limit the response bias, we also examined the correlation matrix and found none of the associations exceeded 0.90 (Pavlou et al., 2007). Third, during the data collection process, authors guarantee respondents' confidentiality and anonymity, encouraging them to provide genuine responses (Mahmood et al., 2019). Hence, it concluded that method bias is not a concern in the present study.

Direct effect. Figure 2 shows that workplace FoMO is positively related to social media use (β = 0.39, t = 7.29, p = 0.00), while the effect of workplace FoMO on routine performance (β = 0.07, t = 1.12, p = 0.26) and innovative work performance (β = 0.01, t = 0.08, p = 0.97) are not significant. Thus, hypotheses H1 is supported, and hypotheses H2a and H2b are not supported. Organizational support is positively related to social media use (β = 0.23, t = 2.98, p = 0.01), moreover, while the effect of organizational support on routine performance (β = 0.30, t = 5.29, p = 0.00) and innovative work performance (β = 0.28, t = 4.30, p = 0.00) are positive and significant. Hence, hypotheses H4, H5a and H5b are supported.

Mediation analysis. The path analysis of indirect effect illustrates in Table 4, shows WRSMU is significant and fully mediates the association between workplace FoMO and routine performance (β = 0.10, t = 2.88, p = 0.01); and innovative work performance (β = 0.09, t = 3.39, p = 0.001). Thus, hypotheses 3a and 3b are supported. Moreover, WRSMU is positively, significantly, and partially mediating the association between organizational support and routine performance (β = 0.05, t = 2.84, p = 0.01); innovative work performance (β = 0.05, t = 2.12, p = 0.01). Hence, hypotheses H6a and H6b are supported.

Moderation analysis. The present study also examined the moderating role of FSMU. The moderation analysis revealed that FSMU significantly but negatively moderates between WSMU and RP (β = −0.13, t = 2.66, p = 0.01). Moreover, work-related social media use is better for routine performance, especially when the frequency of WRSMU is low (β = 0.33, t = 4.50, p = 0.00) rather than high (β = 0.13, t = 1.95, p = 0.05) (Figure 3). However, FSMU did not moderate between WSMU and IP (β = −0.09, t = 1.58, p > 0.10). Hence, hypothesis H7a is supported, and H7 b is not supported.

The present study examined the mediating role of WRSMU in the association between workplace FoMO and organizational support and employee performance. Furthermore, the moderating role of FSMU in the association between WRSMU and performance. Our PLS-SEM findings revealed that workplace FoMO is positively and significantly associated with innovative and routine performance through WSMU. Workplace FoMO was not directly associated with innovative or routine performance. In contrast, the results demonstrate a direct and positive association between organizational support and innovative and routine performance. Furthermore, the results indicate that organizational support is positively associated with innovative and routine performance, suggesting partial mediation. Finally, we highlight that the FSMU moderates the relationship between WRSMU and routine performance, such that the relationship between WRSMU and performance is stronger when the frequency of social media use is low (rather than high). The frequency of social media use did not moderate the relationship between WRSMU and innovative performance. These findings have several implications for theorizing about the role of social media use in organizational contexts.

This study focused on the central role of WRSMU in underlying employee performance. Several studies have explored this relationship in the past, suggesting that WRSMU was positively related to job performance through informational benefits (Jafar et al., 2019), social exchange theory (Chen and Wei, 2020), increased job satisfaction (Moqbel et al., 2013), and social capital (Ali-Hassan et al., 2015; Cao et al., 2016). However, others demonstrated negative relationships with job performance, especially due to excessive social media usage patterns (Yu et al., 2018; Zivnuska et al., 2019). This study sheds new light on the role of WRSMU. Specifically, utilizing COR principles, we suggest that social media can act as a significant resource within the organizational context. COR theory posits that individuals strive to acquire, retain, and protect their valuable resources. Our findings suggest that WRSMU emerges as a resource that employees leverage to mitigate the potential resource loss associated with workplace FoMO. Furthermore, WRSMU can help employees capitalize on the resource gains provided by organizational support. This mechanism is positively associated with routine and innovative performance.

The results indicate that workplace FoMO and organizational support are important antecedents to WRSMU. We suggest that workplace FoMO signals the potential to miss out on important informational resources, motivating employees to engage in WRSMU to reduce the potential of missing out. Hence, we extend the notion that employees are motivated to avoid resource loss (Halbesleben et al., 2014) to argue that employees are also motivated to avoid missing out on valuable resources. The findings further highlight that workplace FoMO is positively related to routine and innovative performance through WRSMU. Hence, we demonstrate that WRSMU may operate as an important resource that benefits job performance. Hence, using COR as our framework, we synthesize earlier findings by connecting the notion that FoMO is positively associated with WRSMU (Van Zoonen et al., 2022) and that social media use may enhance employee productivity (Wu et al., 2021).

It should also be noted that workplace FoMO does not directly affect routine or innovative performance. Research that demonstrated a link between workplace FoMO and motivation and health outcomes called for further exploration of the relationship between FoMO and performance (Budnick et al., 2020). In line with previous studies (Fridchay and Reizer, 2022), we find that workplace FoMO is only indirectly related to performance. The absence of a direct relationship between FoMO and performance seems to suggest that FoMO relates positively to performance only when it compels employees to engage in WRSMU to keep themselves informed and connected.

Conversely, the findings indicate that organizational support is positively associated with WRSMU. These findings suggest that organizational support for social media can be viewed as intangible resources that help employees obtain more resources, i.e. use social media for work. We argued that support may alleviate stress and reduce anxiety related to technology use in organizations (Eisenberger et al., 2020). This is especially important in the context of social media use that has often been described as a technology of accountability due to the visibility they afford (e.g. Treem, 2015). When support is high, employees are more likely to utilize social media for work, which benefits routine and innovative performance. Hence, taken together, this study demonstrates that COR theory provides a valuable framework for developing an in-depth understanding of WRSMU.

Finally, this study contributes to research on the potentially adverse implications of social media in organizations by examining the moderating role of frequency of social media use. Research has indicated that WRSMU may have negative consequences for employees and organizations (e.g. Yu et al., 2018, 2022). Negative implications are mostly associated with excessive usage patterns (Cao et al., 2016). Our findings only partially support this idea by demonstrating that negative moderation exists between WRSMU and the frequency of social media use on routine performance. Specifically, we show that the positive impact of social media on routine performance is stronger when the frequency of social media use is low. However, we do not find a negative relationship (as opposed to a less strong positive relationship) at high social media frequencies. In addition, we could not confirm a negative moderation for innovative performance. Overall, this suggests that while low to moderate social media use may be beneficial for routine performance, we do not find that high usage frequencies lead to negative implications for performance. Arguably, the high use frequencies reported in our sample were not high enough to detect an interaction effect. Future studies should explore the extent to which user frequencies are related to negative ramifications of social media use in the workplace, or the conditions under which such effects exist.

The present study has several implications for employees and organizations. First, this study confirms that WRSMU positively influences employees' routine and innovative work performance. As such, we would encourage organizations and employees to consider how social media technologies can be embedded within organizational processes. The findings indicate that providing organizational support may increase social media use. In addition, research showed that social media training and experience with social media are important antecedents for WRSMU (Pekkala and van Zoonen, 2022). As such, it would behove organizations to offer employees social media training and help them gain experience with using social media technologies for work.

Second, the results indicate that the relationship between WRSMU and routine performance is stronger when the frequency of social media use is low, rather than high. This indicates that the benefits of social media use for work may decrease when the frequency of social media use becomes too high. As such organizations should be wary of excessive usage patterns among employees. Similar to how other communication technologies in organizations ought to be used, managers and employees should aim at establishing social norms that promote healthy connectivity expectations and behaviors.

As with any study, several limitations need to be considered. First, the data reported in this study are cross-sectional and self-reported. This limits our opportunities to draw causal conclusions from the data. Furthermore, it is not possible to examine temporal dynamics or changes over time. In addition, the data are self-reported, which introduces measurement bias such as social desirability bias. Future research should study the antecedents and consequences of WRSMU using longitudinal and multi-sourced data. For instance, longitudinal data allows for studying the directionality of relations and draws conclusions beyond correlations. Multi-sourced research designs could include content analysis of employees’ social media data to examine work-related communication behavior and link that to survey data (van Zoonen and Treem, 2019).

In addition, COR theory is a relevant framework for studying WRSMU. However, beyond workplace FoMO and organizational support, the framework leaves room for the inclusion of other resources that may be drained, or gained, in the context of social media use. For instance, we did not consider how social media use may expand finite resources of employees, leading to communication or information overload (Zhang et al., 2023) or work-life conflicts (Zivnuska et al., 2019). In addition, we did not consider personal characteristics such as self-regulatory focus (Luqman et al., 2021). Moreover, organizational support or supervisor support may be used as a moderator in future studies.

Moreover, the study relies on employees from a variety of different organizations. While this may improve the generalizability, it limits opportunities to consider organization-specific conditions or obtain supervisor-rated performance metrics. A case study in one organization may help to advance our understanding of WRSMU as it will allow examination of organization-specific factors such as social media policies, leader-member exchange, and social networks. Ultimately, we support calls for expanding the theoretical and methodological repertoire to study social technologies in organizations (Leonardi and Vaast, 2017).

Finally, it is notable that FSMU did not moderate the relationship between WRSMU and innovative performance. Arguably, frequency plays a more complex role in influencing these relationships. For instance, high-frequency usage or problematic social media use may lead to low self-control, difficulties in impulse control, and goal-oriented behavior (Lewin et al., 2022; Leijse et al., 2023). Future research could explore why high-frequency social media use does not necessarily enhance the relationship between WRSMU and innovative performance. One promising avenue is to examine the potential double-edged effects, such as information overload, which may counteract the benefits of increased communication and idea exchange. Perhaps industry differences based on creativity and social media intensity provide a good starting point for such exploration. For instance, a recent report shows that the sports industry uses 19.8 weekly posts for user engagement, followed by media, health, and beauty sectors (Rival IQ, 2025).

Social media technologies have become increasingly popular in organizations, affording a wide range of communication and collaboration opportunities (Safadi, 2024). The findings of this study contribute to theorizing about the role of these technologies in shaping the way employees work and perform job tasks. By leveraging the core tenets of COR theory, we conceptualized how workplace FoMO and organizational support inform innovative and routine job performance through WRSMU. We demonstrate that work-related social media plays a central role in helping employees prevent potential resource loss and help gain additional resources. Furthermore, we find that WRSMU positively influences routine and innovative performance. Interestingly, the positive relationship between WRSMU and routine performance becomes weaker at higher frequencies of social media use, suggesting moderate and mindful use of social media for work might particularly improve workforce productivity.

This research did not require IRB approval because it involved a minimal-risk survey among consenting adults, did not collect sensitive personal data or personally identifiable information, and was conducted in accordance with the ethical principles outlined by the Finnish National Board on Research Integrity (TENK) and the Declaration of Helsinki. According to these guidelines, such research does not require prior ethical review when participants are fully informed, and participation is voluntary.

1. I get worried when I might miss important work-related updates.

2. I get anxious when I miss out on an opportunity to make important business connections.

3. When I go on vacation, I continue to keep tabs on what is happening at work.

4. I worry that I will miss out on important work-related news.

5. When I have a good time during work hours, it is important for me to share the details online (e.g. updating status).

1. Guidance is available to me for a selection of different social media platforms.

2. A specific person is available for assistance related to technical issues with social media.

3. My co-worker frequently supports me when I face difficulties related to social media use.

4. I frequently support my co-worker when I face difficulties related to social media use.

1. Social media has become part of my daily routine.

2. I use social media to share work plan/objective information with colleagues.

3. I use social media to arrange meetings with colleagues about work projects.

4. I use social media to share work-related information with colleagues.

5. I use social media to share documents and files with colleagues within the organization.

6. I feel I am part of the social media community.

1. I always complete the duties specified in my job description.

2. I always meet all the formal performance requirements of my job.

3. I always fulfil all responsibilities required by my job.

4. I often fail to perform essential duties (r). *

1. Create new ideas for improvements.

2. Search out novel working methods.

3. Transform innovative ideas into useful applications.

4. Mobilize support for innovative ideas. *

1. When you are at work, how often do you use social media?

   (a) Never (b) About once a day (c) 2–5 times a day (d) 6–10 times a day (e) Every hour

*Deleted due to weak factor loading.