Impact of Using Social Media Networks on Individual Work-Related Outcomes

Abstract

This paper aims to determine the effects of using social networks on work-related outcomes. Observed work-related outcomes are job satisfaction, organizational commitment, and work performance. The moderating effects of gender and age of respondents on the given relations were also observed. In addition, this paper aims to consider the theoretical and practical implications of such research. The research was conducted in West Balkan countries: Bosnia and Herzegovina, Croatia, Montenegro, North Macedonia, and Serbia. Respondents were employed in organizations in these countries and 313 complete questionnaires were collected. The number of social media networks and somewhat frequency of social media networks usage and the number of photos has a positive effect on individual outcomes of employed persons. Daily time usage, frequency of posting photos, number of groups, and number of groups (active participant) have negative effects on individual outcomes of employed persons. Prolonged use of social media networks (during the day) can especially reduce job satisfaction while joining a large number of groups severely jeopardizes organizational commitment. Active participation in a number of groups significantly reduces salary satisfaction and organizational loyalty among male employees. Excessive use of social media network sites and frequent posting of images can reduce satisfaction with the nature of work and work performance among older employees. The discovered connections and influences have scientific and practical significance, which is explained in the paper.

1. Introduction

This paper aims to determine the effects of social media usage on the work-related outcomes of employed persons. In doing so, using social networks is observed in the general case, not just for work-related use. For work-related outcomes, job satisfaction, organizational commitment, and work performance of employees were taken. The following explains the existence of a gap concerning such and similar research, the need to fill it, as well as some details of the research process.

Online social media networks and usage is a common aspect of modern life, which is gaining importance [1]. According to Bunker, Saysavanh and Kwan [2], social media usage is becoming a part of everyday life, with people constantly switching between social media and offline activities. Using social media networks became one of the norms in social behavior, thanks to its opportunities and omnipresence [3]. Online social networking provides a wide range of interactions, communication, information, and knowledge sharing, and also has a significant impact on people’s working styles [4]. At the same time, increased dependence on social media, to meet individual needs, is directly proportional to the greater perception of media importance in life, and accordingly, the stronger effects of social media on the attitudes and behavior of individuals [5]. Given that employees are certainly social media users, the question can be asked: How does all this reflect on the organization, satisfaction, and performance of workers? A similar question is defined by Kock and Moqbel [6]: Does enhance social media usage, during and outside working hours, have an impact on job performance?

There is no doubt that the increasing usage of social media networking sites has brought revolutionary changes in the way individuals connect and interact with others, so organizations and employees need to embrace the benefits that come from these life-work social exchanges [7]. The emergence of social media and its technologies, brings a chance for organizations and practitioners, in terms of achieving benefits for employees [8]. As social media usage is inevitable in the work environment and business processes, it is clear that managers need to find ways to score the maximum from this [9]. In this sense, Mount and Garcia Martinez [10] believe that companies can take advantage of the increasing usage of social media, in the direction of achieving open innovation in all phases of this process: idea creation, R&D, and commercialization. Leftheriotis and Giannakos [11] also note that the introduction of social media in companies opens opportunities for new ways of communication between colleagues and users, ie customers, but at the same time, knowledge of social media usage for business purposes is very limited. The same authors found that the use of social media for work has positive effects on employee performance. The findings of Huang and Liu [12] support the idea that publicly available social media networks can have a positive impact on organizational processes and employee performance. Affective experience on social media networking sites has a positive effect on overall life satisfaction and offline well-being [13].

However, Saleem, Feng and Luqman [14] note that, as the use of social media networks has become an integral part of workers’ lives, and overuse can easily occur, which can have negative consequences. Research by Xue, Dong, Luo, Mo, Dong, Zhang and Liang [15], conducted in China, focused on how WeChat addiction affects the physical, mental and social health of users. The results show negative relations, which strengthen with longer usage, especially after three years. Keating, Hendy and Can [16] surveyed employees on the perception of the good and bad consequences of using social media. Younger employees report, at the same time, the most good and the worst perceptions of social media. Individuals use social media as a coping mechanism to release anger and gather social support, although this can also lead to criticism, feeling left out, and reducing self-esteem. The high usage of digital media by young children harms their subjective well-being, while the moderate usage of digital media has no particular impact in this regard [17].

Olfat, Tabarsa, Ahmadi and Shokouhyar [18] state that employees’ usage of social media networks does not necessarily have negative consequences, it can even indirectly bring some benefits to the organization. With this statement, the review of the effects of social media network sites goes back to the beginning. As a conclusion to these considerations, the finding of Babu, Hareendrakumar and Subramoniam [19] shows that the usage of social media for organizational purposes can have an adverse effect if time is spent in wain and the processes are delayed, but it can also have a beneficial effect if communication, cooperation, and trust are strengthened, as well as knowledge transfer and work performance. Therefore, the direction of action of social media usage on organizations and employees depends on the reason and manner of its usage.

Previous research on this issue has focused mainly on professional, work-related social media usage, for example, the effects of social media usage for work purposes [11,20,21], effects of social media usage to connect with coworkers [7,12,22], effects of social media usage to connect team members [23], effects of enterprise social network use [24,25].

The findings in recent references point to the need for further research in this area. Liang, Xin, Yan and Jianxiang [26] believe that there is limited research on how different social media platforms affect job satisfaction and work performance of employed persons. How social media affect employees’ attitudes, for example, job satisfaction is still not well-known [20]. So far, the influence that social networks (in general, not only online social networks) can have on work-related attitudes has been ignored [27]. Saleem, Feng and Luqman [14] state that a small number of studies address the negative effects of social media networks on work performance. According to Kühnel, Vahle-Hinz, de Bloom and Syrek [28], more research is needed to discover how social media usage at work (for personal purposes) affects employees’ well-being and job performance.

Based on the above, it can be noticed that the previous results of examining the effects of social media usage on job satisfaction and job performance, by employed persons, are significantly contradictory. In addition, these effects are often observed through the prism of social media usage for professional purposes. Finally, recent references tell about insufficient knowledge, and thus the need for further research in this area. With all this in mind, it is noticed the need to conduct research that would fill in the gaps. Thus, the focus of this paper is the effects of the social media usage of employees on their job satisfaction, organizational commitment, and work performance. In doing so, social media usage is observed in the general case, non-work-related use. In addition, social media usage is viewed through several special items, and job satisfaction and organizational commitment across individual dimensions. This is important to obtain more precise results, that is, to see the positive and negative effects, which may differ for individual impacts of social media usage items (independent variables) on job satisfaction, organizational commitment, and work performance dimensions (dependent variables). In addition, the moderating effect of gender and age of respondents on the observed relations is observed. These are important moderators, who have not been sufficiently examined for the given relations so far, which gives additional value to this paper. Thus, the theoretical contribution of the paper is that it has been determined how social network usage items affect the dimensions of job satisfaction, organizational commitment and work performance, by employed persons, emphasizing that these relationships are not sufficiently researched. In addition, these analyzes were performed for individual items and dimensions, and with moderators, which allowed a detailed review of the observed relations, which also has not been researched in this way so far, and with the observed moderators. At the end of the paper, the theoretical and practical implications of the research are presented. The research was conducted in the countries of the West Balkan (Bosnia and Herzegovina, Croatia, Montenegro, North Macedonia, and Serbia), and the respondents were employed persons.

2. Theory and Hypothesis

2.1. Social Media Networks and Job Satisfaction

Public social media platforms, used for work and social related motivations, favorably affect employees’ job satisfaction. At the same time, private social media platforms, used only for socially related motivations, have positive effects on job satisfaction [26]. Two types of informal social networks (those related to instrumental purposes of information sharing and those related to expressive purposes of interpersonal trust) have positive effects on teachers’ job satisfaction [29]. However, Vyas and Pandey [8] come to a slightly different result, according to which social media usage has a beneficial effect on knowledge sharing, but there are no significant links between social media usage and job satisfaction.

The effects of social media usage on job satisfaction are mainly observed through the prism of labor relations. According to Demircioglu [20], the usage of social media for work purposes has a favorable effect on self-determination, which then enhances job satisfaction (according to this finding, the impact of social media is not direct, but indirect). Wang, Huang, Davison and Yang [23] found that social media usage within teams acts to assess employees’ stress, but also moderates the link between role conflict and job satisfaction, as well as the relationship between role stressors and job satisfaction. Some studies examine how interaction with coworkers on social media networks affects job satisfaction. According to Huang and Liu [12], coworkers’ connections on publicly available social media networks have a positive effect on job satisfaction and job performance. Likewise, there is a positive relationship between time spent on Facebook with coworkers, and job satisfaction, so it is recommended to use Facebook as a strategic platform to encourage job satisfaction [22]. Yang and Wong [7] examined whether cyberspace friendships between co-workers can grow into favorable organizational outcomes. In that sense, a model has been proposed that leads from friendship with colleagues on social media networks to better job embeddedness and job satisfaction.

The direction of influence can be reversed: (dis)satisfaction with work is projected on social media network sites. Thus, stress and dissatisfaction at work can lead to increased non-work-related use of social media [30]. In addition, expressing oneself on Twitter can be an indicator of needs and work (dis)satisfaction, among employees [31].

2.2. Social Media Networks and Organizational Commitment

When employees use social media networks, it helps them to establish more intense social interaction, while developing a sense of belonging between them [32]. Similarly, Labrecque [33] considers that social media usage facilitates and strengthens social interactions which in turn leads to greater affective organizational commitment. According to Tabarsa, Olfat and Shokouhyar [24], employees’ social usage of social media networks brings many benefits, such as increased job satisfaction and affective organizational commitment, but also some negative phenomena, for example, strengthening the destructive voice. In addition, structural position and social influence on social networks (in the general case) are related to organizational commitment [27].

Public social media networks have a positive impact on affective and normative commitment, but not on continuance commitment, while enterprise social media networks do not affect organizational commitment [18]. However, employees’ organizational commitment has a positive impact on their work-related usage of the relevant enterprise social media networks [25].

A study by Macintosh and Krush [21], among sales individuals, found that networking behaviors are related to job satisfaction and organizational commitment. The moderator role of gender was also examined: job satisfaction relates positively to professional networking for women, and positively to peer networking for men. Peer networking directly relates to organizational commitment to women. According to Kim and Scott [34], anonymous social media at work can favorably affect affective commitment and job satisfaction, with mediation quality of change communication and workplace freedom of speech. Finally, Kock and Moqbel [35] find that positive emotions (increased job satisfaction and organizational commitment), related to the use of social media networks, also contribute to increased job performance.

2.3. Social Media Networks and Work Performance

Social media usage by employed persons is likely to be associated with improved job performance [35]. Social media usage is significantly related to employee job performance [9] (here it should be borne in mind that respondents were employed in the IT sector, so this relation seems logical for this group). However, some studies show the opposite effect of social media usage on work performance. Thus, excessive use of social media networks positively influences cognitive-emotional preoccupation, and this encourages various conflicts, which then reduce the work performance of employees [14]. Using social media networks for personal purposes, during working hours, harms self-reported work performance. These effects are not so strong, which may be due to the subjectivity of the respondents [36]. Social media network addiction can compromise the execution of work tasks in nurses [37].

Some research indirectly indicates the impact of online social networks and social media on work performance. For example, exposure to an emotionally negative post reduces mood but increases executive functioning [38]. According to Kwahk and Park [39], social media networks help to form various human networks, which leads to the acquisition of new information and knowledge. In this way, the usefulness of transactive memory (a shared memory system, which is formed through interaction between people) is enhanced. Kwahk and Park [39] further showed that an individual’s transactive memory capability positively influences job performance. Hence, also, arises the indirect, potential link between social media and work performance. According to Zivnuska, Carlson, Carlson, Harris and Harris [40], social media addiction reduces work-family balance; social media reactions amplify job burnout, all of which adversely affect job performance.

Some studies deal with the impact of social media on academic achievement, which can be taken as the equivalent of work performance in an educational environment. For example, Twitter has the potential to improve learning outcomes [41]. The experiment, in which students were allowed to join a network that serves for social interaction and collaboration, found that such a network (which is characterized as small-world), is a predictor of learning achievement [42]. However, there are different results within this group of studies. In Hong Kong, outside-school social media behavior harms adolescents’ academic performance, while inside-school social media behavior has positive effects on their performance [43]. Among students in Russia, there is no relationship between time spent online and academic performance, while active integration in the online community of fellow students reduces performance [44]. Wakefield and Frawley [45] conclude that students’ academic achievement moderates the effects of school networking usage on learning performance: social networking usage particularly badly affects the performance of students who have lower academic success, while the performance of higher academic achievers is not significantly affected by social media usage. Finally, a meta-analysis by Huang [46], to estimate the relation between social media usage and academic achievement, showed small or negative correlations. The mean correlation is small for studies that take into account time spent, and about zero for studies measuring visiting frequency.

Based on the considerations presented in the introduction and theory, two hypotheses and two research questions are posed:

Hypothesis 1.

There are statistically significant correlations between some of the social media usage items and some of the job satisfaction, organizational commitment, and work performance dimensions, in employed persons.

Hypothesis 2.

There is a statistically significant predictive effect of some social media usage items on some of the job satisfaction, organizational commitment, and work performance dimensions, in employed persons.

RQ1: Is there a moderating effect of gender of respondents on the relation between the social media usage items and job satisfaction, organizational commitment, and work performance dimensions, in employed persons?

RQ2: Is there a moderating effect of the age of respondents on the relation between the social media usage items and job satisfaction, organizational commitment, and work performance dimensions, in employed persons?

3. Method

3.1. Survey Instruments

Social media usage. Nine social media usage items were observed. Item SN1—The number of social media networks I use, means the number of social media networks used by the respondent and here the respondents gave grades from 1 to 6, where 1 means one social network, 2 means two social networks, and so on up to 6 which means more than five social networks. This item is logically imposed in the given analysis and this question was asked first. Item SN2—Frequency of social media usage, was formed based on the study [47], where the same question was asked, but only for Facebook. Here, too, the respondents gave grades from 1 to 6, with a larger number representing more frequent use of social networks.

Items SN3—Daily time usage (hours per day) (according to [47,48,49], SN4—Number of friends on social media networks (according to [47,48,49], SN5—Number of photos on social media networks (according to [49]), SN7—Number of groups on social media networks (according to [48,49]) and SN8—Number of groups in whose work I active participation, respondents rated with real values.

Item SN6—Frequency of posting photos on social media networks, respondents rated it with grades from 1 to 6, with a larger number representing more frequent image posting. This item is formed by analogy with item SN2—Frequency of social media usage, only here the frequency refers to posting photos. To all this was added item SN9—I use social media just for fun, which the respondents evaluated according to the five-point Likert scale (1—“I do not agree at all” to 5—“I completely agree”). This item should show whether the reasons for social media usage affect the observed individual outcomes of employed persons.

Job satisfaction. The Job Satisfaction Survey (JSS) was used to measure employee job satisfaction [50]. Respondents’ responses were recorded using a seven-point Likert scale. The questionnaire consists of 36 items and nine dimensions (Appendix A).

Organizational commitment. An instrument developed by Cook and Wall [51] was used to measure organizational commitment. Respondents’ responses were evaluated using a five-point Likert scale. The instrument has 9 items and three dimensions.

Work performance. Following the references [39,52,53], a questionnaire was used to measure work performance. Respondents’ responses were evaluated using a five-point Likert scale. The questionnaire has five items, which make up one dimension.

3.2. Participants and Data Collection

The participants were employed in organizations in five countries in the West Balkan: Bosnia and Herzegovina, Croatia, Montenegro, North Macedonia, and Serbia. These countries were selected because of their similarities in culture, language, economic development, and shared history, by expanding the research into five countries, the results obtained have broader applications. This sample was chosen in order to determine the unique results and relationships that apply to the observed region. Thus, the results are more important as they are valid for more countries. As we have said, this is possible due to the mentioned similarities of the observed countries.

Respondents completed the questionnaires online. A total of 313 validly completed questionnaires were collected. What is significant for this research, there are 98 male respondents (31.3%) and 215 female respondents (51.76%) in the sample. In addition, the sample was divided into younger respondents (up to 35 years of age), of whom there were 161 (51.4%), and older respondents (36 years of age and older), of whom there were 152 (48.6%). When examining the age of the respondents, the question was formulated so that the respondents choose a period of five years, which corresponds to their age (less than 30; 31 to 35; 36 to 40; 41 to 45; 46 to 50; 51 to 55; 56 and more). We set the limit at 35 years because it was achieved that both groups have an approximate number of respondents.

In addition to this, there are 35 respondents from Bosnia and Herzegovina (11.2%), 26 respondents from Montenegro (8.3%), 43 respondents from Croatia (13.7%), 17 respondents from North Macedonia (5.5%), and 192 respondents from Serbia (61.3%) in the sample. Finally, there are 45 high school respondents (14.4%), 22 vocational studies higher education (7.0%), and 246 faculty respondents (78.6%) in the sample.

4. Results

4.1. Descriptive Statistics

The results of descriptive statistics, for social media usage items, job satisfaction dimensions, organizational commitment dimensions, and work performance dimensions, are given in

Table 1. Descriptive statistics.

Items and Dimensions	Abbr.	N	Min	Max	Mean	Std. Deviation	Cronbach’s Alpha
Number of social networks I use	SN1	313	1	6	3.40	1.64	-
Frequency of social networks usage	SN2	313	1	6	3.19	1.59	-
Daily time use (hours per day)	SN3	313	0	20	2.50	1.888	-
Number of friends on social networks	SN4	313	0	9000	729.77	1212.48	-
Number of photos on social networks	SN5	313	0	4000	264.40	544.09	-
Frequency of posting photos on social networks	SN6	313	1	5	1.26	0.70	-
Number of groups on social networks	SN7	313	0	200	15.51	22.39	-
Number of groups in whose work I active participate	SN8	313	0	120	4.04	8.18	-
I use social networks just for fun	SN9	313	1	5	2.90	1.30	-
Pay	JS1	313	1.00	6.00	3.65	1.49	0.904
Promotion	JS2	313	1.00	6.00	3.85	1.60	0.928
Supervision	JS3	313	1.00	6.00	4.42	1.46	0.900
Fringe Benefits	JS4	313	1.00	6.00	3.98	1.59	0.921
Contingent Rewards	JS5	313	1.00	6.00	3.88	1.58	0.926
Operating Procedures	JS6	313	1.00	6.00	3.77	1.12	0.740
Coworkers	JS7	313	1.00	6.00	4.30	1.24	0.855
Nature of Work	JS8	313	1.00	6.00	4.64	1.29	0.912
Communication	JS9	313	1.00	6.00	4.41	1.19	0.836
Organizational identification	OCM1	313	1.00	5.00	3.69	1.21	0.868
Organizational involvement	OCM2	313	1.00	5.00	4.02	0.94	0.785
Organizational loyalty	OCM3	313	1.00	5.00	2.91	1.33	0.758
Work performance	WP	313	3.60	7.00	6.28	0.78	0.876
Valid N (list wise)		313

. In this table, you can see the names dimensions, abbreviations, mean, standard deviation, and Cronbach’s alpha for each dimension. Cronbach’s alpha values range from 0.740 to 0.928.

As it was said, for items SN3, SN4, SN5, SN7, and SN8, open questions were used, so these items were evaluated with real values by the respondents, which are presented in the results of the descriptive statistics.

However, in further analyzes (correlation and regression analysis) it was necessary to use indirect estimates for these items. For each item separately, real values are sorted by size, from smallest to largest. Then, the respondents and their real values were divided into five groups: I Respondents who gave a very low grade to the observed item (this group of real grades is assigned an indirect grade (1); II Respondents who gave a low grade to the observed item (this group of real grades is assigned an indirect grade (2); III Respondents who gave the observed item an average grade (this group of real grades is assigned an indirect grade (3); IV Respondents who gave a high grade to the observed item (this group of real grades is given an indirect grade (4) and V Respondents who gave a very high grade to the observed item (this group of real grades was given an indirect grade 5).

4.2. Correlation Analysis

First of all, a correlation analysis was performed between the dependent variables (job satisfaction, organizational commitment, and work performance). These results are given in

Table 2. Coefficients of correlation between the job satisfaction, organizational commitment and work performance dimensions.

	JS1	JS2	JS3	JS4	JS5	JS6	JS7	JS8	JS9	OCM1	OCM2	OCM3	WP
JS1	-
JS2	0.894 **	-
JS3	0.701 **	0.752 **	-
JS4	0.899 **	0.872 **	0.737 **	-
JS5	0.887 **	0.901 **	0.785 **	0.904 **	-
JS6	0.636 **	0.583 **	0.595 **	0.626 **	0.676 **	-
JS7	0.641 **	0.646 **	0.678 **	0.657 **	0.710 **	0.595 **	-
JS8	0.505 **	0.554 **	0.554 **	0.483 **	0.584 **	0.406 **	0.583 **	-
JS9	0.677 **	0.718 **	0.725 **	0.662 **	0.744 **	0.601 **	0.750 **	0.640 **	-
OCM1	0.639 **	0.680 **	0.671 **	0.651 **	0.700 **	0.436 **	0.608 **	0.708 **	0.721 **	-
OCM2	0.453 **	0.511 **	0.540 **	0.470 **	0.517 **	0.250 **	0.405 **	0.595 **	0.542 **	0.793 **	-
OCM3	0.465 **	0.496 **	0.462 **	0.468 **	0.514 **	0.302 **	0.388 **	0.527 **	0.482 **	0.729 **	0.645 **	-
WP	0.087	0.130 *	0.084	0.092	0.136 *	0.025	0.121 *	0.249 **	0.152 **	0.192 **	0.350 **	0.101	-

* p < 0.05; ** p < 0.01.

. Pearson correlation was used, * p < 0.05; ** p < 0.01. The vast majority of correlations in Table 2 are statistically significant and positive, especially those that exist within the same construct. This speaks to the closeness of job satisfaction dimensions as well as organizational commitment dimensions. As stated in the Introduction, in this paper, all dimensions are nevertheless observed individually because the goal was to look at the observed relations in detail. Ultimately, high correlations can show a lot, but not necessarily: for example, an individual may be satisfied with a salary, but not with coworkers, and vice versa; someone else may have high organizational involvement, but would easily leave the organization in case of a better offer.

Coefficients of correlation between the social media usage items and job satisfaction, organizational commitment, and work performance dimensions, are given in

Table 3. Coefficients of correlation between the social media usage items and job satisfaction, organizational commitment, and work performance dimensions.

	JS1	JS2	JS3	JS4	JS5	JS6	JS7	JS8	JS9	OCM1	OCM2	OCM3	WP
SN1	0.130 *	0.173 **	0.163 **	0.129 *	0.119 *	0.105	0.126 *	0.106	0.135 *	0.113 *	0.058	−0.020	0.050
SN2	0.076	0.018	0.010	0.033	0.011	0.077	0.000	0.030	0.022	0.025	−0.020	−0.045	−0.032
SN3	−0.062	−0.099	−0.081	−0.107	−0.098	−0.025	−0.076	−0.065	−0.012	−0.025	−0.060	−0.041	−0.036
SN4	0.046	0.086	0.041	0.058	0.033	0.003	0.061	0.081	0.031	0.053	0.018	−0.071	0.051
SN5	0.053	0.065	0.077	0.018	0.044	0.055	0.046	0.112 *	0.099	0.092	0.086	0.045	0.085
SN6	−0.058	−0.088	−0.065	−0.075	−0.065	0.025	−0.042	−0.060	−0.057	−0.008	−0.008	−0.040	−0.054
SN7	−0.091	−0.129 *	−0.041	−0.078	−0.106	−0.058	−0.005	−0.080	−0.081	−0.134 *	−0.116 *	−0.184 **	−0.007
SN8	−0.114 *	−0.128 *	−0.084	−0.106	−0.104	−0.039	−0.082	−0.094	−0.108	−0.122 *	−0.055	−0.118 *	−0.007
SN9	−0.019	−0.017	−0.102	−0.018	−0.049	0.009	−0.011	−0.058	0.000	−0.045	−0.005	0.002	0.010

* p < 0.05; ** p < 0.01.

. Pearson’s correlation was used, * p < 0.05; ** p < 0.01. Statistically significant coefficients of correlation in Table 3 are indicated by bold font and shaded fields.

4.3. Regression Analysis

The predictive effect of the social media usage items (independent variables) on job satisfaction, organizational commitment, and work performance dimensions (dependent variables), was examined using multiple regression analysis (

Table 4. Regression analysis (independent variables: social media usage items; dependent variables: job satisfaction, organizational commitment, and work performance dimensions).

					Indep.
Depend.	SN1	SN2	SN3	SN4	SN5	SN6	SN7	SN8	SN9	R2	F	Sig.
					β
JS1	0.152	0.137	−0.157	−0.019	0.062	−0.052	−0.081	−0.080	−0.031	0.062	2238	0.020
JS2	0.225	0.063	−0.173	0.021	0.062	−0.065	−0.143	−0.056	−0.016	0.095	3518	0.000
JS3	0.196	0.059	−0.172	−0.058	0.092	−0.053	−0.034	−0.074	−0.101	0.073	2635	0.006
JS4	0.172	0.099	−0.184	0.010	0.017	−0.050	−0.061	−0.074	−0.024	0.063	2258	0.019
JS5	0.164	0.074	−0.170	−0.029	0.068	−0.049	−0.110	−0.043	−0.057	0.061	2184	0.023
JS6	0.130	0.105	−0.125	−0.063	0.068	0.021	−0.082	−0.003	0.005	0.034	1182	0.306
JS7	0.159	0.020	−0.128	0.005	0.030	−0.015	0.039	−0.112	−0.002	0.041	1440	0.170
JS8	0.100	0.084	−0.142	0.006	0.130	−0.059	−0.090	−0.056	−0.067	0.057	2046	0.034
JS9	0.160	0.023	−0.061	−0.048	0.114	−0.056	−0.071	−0.081	0.004	0.050	1785	0.070
OCM1	0.129	0.041	−0.079	0.000	0.099	−0.004	−0.146	−0.060	−0.049	0.056	1995	0.040
OCM2	0.090	0.008	−0.103	−0.033	0.127	−0.005	−0.164	0.039	−0.010	0.038	1346	0.212
OCM3	0.025	−0.003	−0.033	−0.095	0.135	−0.043	−0.191	0.004	−0.021	0.050	1783	0.071
WP	0.052	−0.030	−0.050	0.003	0.100	−0.053	−0.030	0.014	0.018	0.017	0.587	0.807

). The results in Table 4, for which there is a statistically significant predictive effect, are indicated by bold font and shaded fields.

4.4. Gender of Respondents as a Moderator

The results of the correlation analysis between the social media usage items and job satisfaction, organizational commitment, and work performance dimensions, specifically for males and females, are given in

Table 5. Correlation of coefficients between the social media usage items and job satisfaction, organizational commitment and work performance dimensions, specifically for males and females.

Gender		JS1	JS2	JS3	JS4	JS5	JS6	JS7	JS8	JS9	OCM1	OCM2	OCM3	WP
Male	SN1	0.093	0.164	0.176	0.094	0.078	0.114	0.124	0.047	0.061	0.121	0.030	0.024	0.036
	SN2	−0.059	−0.019	−0.065	−0.144	−0.056	−0.096	−0.048	0.054	0.031	0.068	−0.037	0.002	−0.103
	SN3	−0.223 *	−0.245 *	−0.230 *	−0.329 **	−0.290 **	−0.176	−0.158	−0.056	−0.077	−0.045	−0.060	−0.069	0.043
	SN4	0.028	0.065	0.007	−0.026	−0.009	0.009	−0.015	−0.035	0.028	0.058	0.053	−0.132	0.071
	SN5	−0.029	0.003	0.011	−0.094	−0.046	−0.050	−0.041	0.123	0.045	0.119	0.124	0.012	0.059
	SN6	−0.187	−0.276 **	−0.258 *	−0.215 *	−0.182	−0.058	−0.149	−0.052	−0.194	−0.018	−0.037	−0.023	−0.092
	SN7	−0.096	−0.081	−0.140	−0.160	−0.145	−0.187	−0.039	−0.076	−0.121	−0.176	−0.166	−0.294 **	0.114
	SN8	−0.301 **	−0.266 **	−0.278 **	−0.289 **	−0.255 *	−0.163	−0.189	−0.197	−0.265 **	−0.247 *	−0.201 *	−0.304 **	0.038
	SN9	0.008	0.033	−0.014	0.074	0.035	0.042	0.071	−0.039	0.223 *	0.161	0.137	0.057	0.098
Female	SN1	0.173 *	0.210 **	0.179 **	0.172 *	0.165 *	0.115	0.144 *	0.142 *	0.182 **	0.135 *	0.080	−0.024	0.033
	SN2	0.164 *	0.068	0.062	0.140 *	0.072	0.173 *	0.037	0.042	0.039	0.038	0.000	−0.046	−0.032
	SN3	0.040	−0.002	0.003	0.023	0.021	0.065	−0.021	−0.048	0.039	0.016	−0.045	−0.004	−0.118
	SN4	0.067	0.111	0.063	0.106	0.064	0.007	0.098	0.129	0.041	0.063	0.010	−0.038	0.029
	SN5	0.129	0.138 *	0.135 *	0.109	0.128	0.129	0.107	0.135 *	0.151 *	0.121	0.088	0.087	0.062
	SN6	0.000	−0.003	0.029	−0.009	−0.013	0.072	0.008	−0.073	0.009	−0.012	0.004	−0.058	−0.021
	SN7	−0.067	−0.124	0.014	−0.020	−0.065	0.014	0.023	−0.069	−0.051	−0.101	−0.087	−0.124	−0.092
	SN8	−0.024	−0.053	0.001	−0.014	−0.022	0.024	−0.030	−0.048	−0.037	−0.060	0.008	−0.032	−0.056
	SN9	−0.036	−0.044	−0.141 *	−0.062	−0.090	−0.009	−0.046	−0.069	−0.089	−0.124	−0.064	−0.025	−0.023

* p < 0.05; ** p < 0.01.

. Hierarchical regression analysis was used. Pairs with a confirmed moderator effect are marked with a bold font and shaded fields.

4.5. Age of Respondents as a Moderator

The results of the correlation analysis between the social media usage items and job satisfaction, organizational commitment, and work performance dimensions, specifically for younger and older respondents, are given in

Table 6. Correlation of coefficients between the social media usage items and job satisfaction, organizational commitment, and work performance dimensions, specifically for younger and older respondents.

Age		JS1	JS2	JS3	JS4	JS5	JS6	JS7	JS8	JS9	OCM1	OCM2	OCM3	WP
Younger	SN1	0.109	0.202 *	0.171 *	0.144	0.173 *	0.122	0.160 *	0.241 **	0.171 *	0.208 **	0.149	0.092	0.120
	SN2	0.102	0.031	0.039	0.053	0.052	0.180 *	0.066	0.144	0.105	0.078	−0.009	0.018	−0.026
	SN3	−0.047	−0.063	−0.050	−0.098	−0.062	−0.010	−0.017	0.058	0.042	0.016	0.011	0.001	0.097
	SN4	0.029	0.087	0.009	0.062	0.033	0.030	0.057	0.155 *	0.028	0.106	0.084	0.039	0.003
	SN5	0.002	0.039	−0.026	−0.041	−0.008	−0.003	0.014	0.114	0.035	0.104	0.130	0.132	0.043
	SN6	−0.011	−0.039	−0.028	−0.086	−0.057	0.096	0.000	0.081	0.033	0.044	0.078	−0.016	0.063
	SN7	−0.129	−0.203 **	−0.195 *	−0.138	−0.207 **	−0.123	−0.108	−0.133	−0.157 *	−0.182 *	−0.093	−0.205 **	−0.005
	SN8	−0.100	−0.141	−0.151	−0.121	−0.098	−0.056	−0.072	−0.062	−0.050	−0.091	−0.028	−0.155 *	−0.008
	SN9	−0.028	−0.066	−0.065	−0.035	−0.069	0.039	0.059	−0.092	0.022	−0.078	−0.074	−0.119	−0.099
Older	SN1	0.094	0.113	0.156	0.073	0.038	0.033	0.081	0.011	0.105	0.018	−0.016	−0.107	−0.004
	SN2	0.014	−0.021	−0.025	−0.016	−0.052	−0.066	−0.077	−0.074	−0.071	−0.034	−0.018	−0.098	−0.031
	SN3	−0.126	−0.171 *	−0.125	−0.155	−0.163 *	−0.088	−0.153	−0.193 *	−0.078	−0.076	−0.138	−0.074	−0.182 *
	SN4	0.025	0.063	0.070	0.027	0.013	−0.060	0.053	0.035	0.036	0.000	−0.037	−0.161*	0.103
	SN5	0.071	0.071	0.185 *	0.048	0.077	0.082	0.065	0.138	0.172 *	0.079	0.050	−0.029	0.135
	SN6	−0.094	−0.129	−0.101	−0.060	−0.069	−0.034	−0.075	−0.215 **	−0.150	−0.058	−0.106	−0.064	−0.166 *
	SN7	−0.058	−0.055	0.135	−0.020	−0.004	0.008	0.094	−0.015	0.008	−0.081	−0.145	−0.162 *	−0.009
	SN8	−0.130	−0.117	−0.011	−0.093	−0.110	−0.023	−0.092	−0.134	−0.173 *	−0.154	−0.088	−0.083	−0.005
	SN9	−0.016	0.028	−0.144	−0.007	−0.033	−0.026	−0.077	−0.017	−0.023	−0.012	0.077	0.121	0.121

* p < 0.05; ** p < 0.01.

. Hierarchical regression analysis was used. Pairs with a confirmed moderator effect are marked with a bold font and shaded fields.

5. Discussion

5.1. Discussion of the Results of the Correlation Analysis

The results of the correlation analysis (Table 3) show that statistically significant correlations were concentrated on several social media usage items. The influence of item SN1—Number of social media networks, which has a positive effect on most job satisfaction dimensions, as well as on OCM1—Organizational identification, is emphasized. According to [54], just as more television channels allow open choice, so more social networks provide more choice for communication, so using more social networks gives users more opportunities to meet different needs in this process of communicating. Accordingly, the number of social media networks used by a person can speak of a greater desire for communication, about that person’s openness, extroversion, involvement in the world around them, as well as the desire to see and be seen. Such people are more likely to achieve greater overall satisfaction, and thus be more satisfied with the job and more easily identify with the organization in which they work. In this section, the results are consistent with the results of research where there is a positive relationship between social media usage and job satisfaction [26,29], as well as social media usage and organizational commitment [32,33].

In addition, the influence of items SN7—Number of groups and SN8—Number of groups (active participant) was expressed, especially on the organizational commitment and JS1—Pay and JS2—Promotion. In doing so, these impacts are negative. Regarding the number of groups on social networks, Velasquez and La Rose [55], find that belonging and active use of a larger number of groups on social networks can be associated with social and political activism, in terms of establishing a platform for expressing dissatisfaction. From this, it can be concluded that there is some connection between the number of groups on social networks and feelings and expressions of dissatisfaction. Furthermore, it is easy to assume that analogous relationships also exist in the context of (dis) job satisfaction. It is difficult to say why this is happening, but it is very possible that the number of groups on social media networks (active and passive participation) can distract employees, in terms of too much focus on other people, their jobs, organizations, successes, and opportunities of those other people and groups. Seeing all this, an individual can receive the impression that other organizations have higher salaries and better opportunities for advancement, and they then become jealous, dissatisfied, and less identified, to the extent that they are ready to leave the organization in case of a good offer. Now, these findings can be considered similar to the findings of studies where adverse effects of social media usage were detected [14,15,36]. However, differences occur concerning research that speaks to the affirmative relationship between social media usage and organizational commitment [24,32,33,34].

There may be a relation in the opposite direction here: unfavorable opportunities for advancement and weak commitment to the organization lead the individual in search of something else (and what he considers better). Such an individual is easier to join several groups on social media networks, with the hope that something will be found there, seen and that, finally, something will “happen”... A person can do this consciously, with such intentions, or they can do it unconsciously, not linking their business dissatisfaction and desire for change with joining a larger number of groups. This direction of action has been discovered in some previous research: job satisfaction on social media usage [30,31], and organizational commitment to enterprise social media usage [25].

There is another statistically significant and positive correlation: between SN5—Number of photos and JS8—Nature of work. In order to explain this phenomenon, it is useful to note here that Li and Xie [56], in their study, noticed that social media profiles, which have more photos, have greater interaction with other profiles, and thus a stronger sense of belonging and community connections. Based on this result, it can be concluded that the pictures are posted by people who want to show something and communicate more, and when they want to show something and communicate it, it is mostly because they want to brag in a way. Posted images are certainly affirmative for the person posting them (in most cases). As the number of images increases, the probability that the person is more satisfied with their life grows, and that, among other things, includes and implies satisfaction with the nature of the work they do. In addition, with the increase in the number of images, the chances are higher that some images are directly or indirectly related to the job, which further intensifies the previous discussion. Finally, considering that statistically significant influences occur in a smaller, but still significant number of cases, it can be stated that hypothesis H1 has been confirmed.

5.2. Discussion of the Results of the Regression Analysis

The results of the regression analysis (Table 4) are generally consistent with the results of the correlation analysis. Thus, item SN1—Number of social media networks has statistically significant predictive effects for those dimensions in which there were also statistically significant correlations. The same applies to the effect of item SN7—Number of groups, and these relations have been previously discussed. On the other hand, now there are no effects of item SN8—Number of groups (active participant). Therefore, the number of groups proved to be a more influential variable than active participation in these groups. Just joining a larger number of groups on social networks can already indicate certain dissatisfactions, expressing that dissatisfaction, desire for change and the change search, and then a low organizational commitment. Active participation in groups is only a physical manifestation of those desires and it depends on how much time a person has and how much they want to communicate in groups.

As in the correlation analysis, there is a statistically significant correlation between SN5—Number of photos and JS8—Nature of work. Regression analysis also revealed a positive predictive effect of SN5—Number of photos on OCM3—Organizational loyalty. This finding is in line with the explanations given in the discussion of the results of correlation analysis and further confirms them: posting pictures sends a message about strong belonging and connection with the community, then a message of satisfaction in a broader sense, as well as satisfaction with the nature of work, and from all that it follows that loyalty to the organization. This result is consistent with the results of research where the impact of social media usage on organizational commitment is favorable [24,32,33,34], although it should be said that these studies mainly examine affective organizational commitment.

The biggest difference concerning the results of the correlation analysis is the statistically significant and negative predictive effect of item SN3—Daily time usage on a larger number of job satisfaction dimensions. According to [57], increased time spent on social media platforms may be associated with some symptoms of depression, behavioral problems, and addiction. Furthermore, using social media too much during the day certainly takes a significant amount of time, which physically leaves such users with less time for work, thoughts, and ambitions of work, and finally, the necessary rest. As a result, it is possible that people who spend a lot of time on social media, due to psychological problems and lack of time, do their job worse, and are therefore less satisfied with the job. Job satisfaction and work performance are known to be in a positive interdependent relationship [58]. This is especially reflected in fewer opportunities for advancement and compensation in any form, which can be seen in the dimensions on which item SN3—Daily time usage has a statistically significant negative effect. In addition, all this adversely affects the satisfaction of superiors and the very nature of work, which acts as a logical consequence. Similar to the negative effects of the number of groups on social media networks, there may be an action in the opposite direction: dissatisfaction with work (especially compensation, opportunities for advancement, and superiors) can initiate greater use of social media networks, to divert thoughts from work and find some other pleasures. Some previous research, for example [14,15,17], also shows that addiction and too much social media usage can lead to adverse consequences, in a general sense.

The values of the corrected determination indexes R² (Table 3) are low but are statistically significant in a large number of cases. The highest value of R² is shown by the dimension JS2—Promotion, which means that social media usage has the greatest impact on opportunities for advancement: SN1—Number of social media networks positively, and SN3—Daily time usage and SN7—Number of groups negatively, which was previously discussed. Taking into account all the results of the regression analysis, it can be concluded that hypothesis H2 has been confirmed.

5.3. Discussion of the Moderating Effects of Gender of Respondents

According to the results from Table 5, the strongest impression is that items SN3—Daily time usage and SN8—Number of groups (active participant) significantly reduce certain job satisfaction dimensions in males, while these items in females do not have any specific impact. The previously presented discussions of the way items work related to the scope of usage of social media networks and the number of groups on social media networks in which they actively participate, obviously, mostly applies to male employees. It should be noted that item SN8—Number of groups (active participant) showed a greater impact (negative) in male employees than item SN7—Number of groups, while regression analysis showed the opposite, for the whole sample. In any case, using social media networks too much during the day, as well as active participation in a large number of groups on social media networks, has a particularly adverse effect on job satisfaction in male participants. Such behavior especially diverts men’s attention and thoughts from work, making them less engaged, effective, and productive at work, and more jealous of some other people, their jobs, earnings, rewards, privileges at work, etc. Men are more likely to follow what they see and learn on social media, are more likely to pay higher fees, and are more prone to dissatisfaction and the search for alternatives if they feel something is missing. Longer usage of social media networks and frequent comparisons with others can easily remind them of what they are dissatisfied with. The degree of active usage of social media networks has a particularly unfavorable effect on organizational loyalty among men. All this is happening because men feel a greater obligation to provide money and material security for their families than women do. To further understand these results and discuss them, the findings of the study by Huang, Kumar and Hu [59] show that achievement vanity is more emphasized in men.

The next impression is the emphasized positive effects of items SN1—Number of social media networks and SN2—Frequency of social media usage in women, while these effects are weaker in men, even negative in the case of item SN2—Frequency of social media usage. The discussion of the impact of item SN1—Number of social media networks, presented for the results of the correlation analysis, is mostly valid for female employees. Thus, the number of social media networks and the frequency of their usage contribute more to women feeling involved in social activities, being part of the community, to find some satisfaction in it, and then all of this is reflected favorably on satisfaction with certain aspects of work.

It is also interesting that item SN6—Frequency of posting photos can significantly reduce the satisfaction of JS3—Supervision, for males. Frequent posting of photos can be an indicator of dissatisfaction with superiors, in the case of male employees. Men, probably, consciously or unconsciously, more or less successfully, in this way tend to reduce frustration due to bad relationships with superiors. It should also be noted that item SN9—I use social media networks just for fun can very favorably affect the satisfaction of JS9—Communication and enhanced OCM1—Organizational identification, in males. If men use social networks just for fun, then it is not an indicator of dissatisfaction as when they use social networks for too long and when they participate in the work of a larger number of groups. It seems that such men are relaxed and that their entertainment on social media networks is an indicator that they do not have a problem with communication in the organization, that they are satisfied with that aspect of work, and that they are quite strongly identified with their organization. The usage of social media networks exclusively for entertainment, among women, has no special significance and effect on dependent variables. Based on the above, it can be concluded that the moderating effect of gender of respondents is present in a small but significant number of cases and is on average emphasized. This answered the research question RQ1.

5.4. Discussion of the Moderating Effects of Age of Respondents

According to the results from Table 6, it is noticed that items SN3—Daily time usage and SN6—Frequency of posting photos have a significantly less favorable effect on JS8—Nature of work and WP—Work performance, with older employees. Older employees are less native to social media networks, so long usage of social media networks during the day affects them more than younger employees, who are more accustomed to living and working in such an environment. Older employees are more distracted from work by social media networks, and less time for rest has a less favorable effect on them than on younger employees. In such conditions, older employees become less satisfied with work and less efficient in terms of work performance. At first glance, this result may seem contrary to the result that older persons are less associated with problematic social media usage [60]. However, the absence of problematic social media usage does not mean that social media usage in the elderly has no impact (unfavorable) on job satisfaction and work performance.

In addition, two phenomena are interesting here. First, the negative effects of SN6—Frequency of posting photos in older employees. It should be reminded that this item also negatively affects the dimension JS3—Supervision, in males. At the same time, regression analysis showed some positive predictive effects of item SN5—Number of photos. The question arises: why in some groups of respondents the number of photos on social media networks seems favorable, and the frequency of posting photos seems negative? It was previously explained that the number of photos indicates a certain satisfaction, which is shared with others through the photos. Now, this explanation expands as follows: posting photos at relatively long intervals speaks of stability and satisfaction with what has been posted, while relatively frequent posting of photos speaks of instability, the desire to find the best pictures, the need to change something, to constantly point out and prove something, and all that indicates dissatisfaction. Secondly, these are negative effects on WP—Work performance in older employees. The WP—Work performance dimension in previous analyzes did not show any statistically significant results, which is significantly consistent with the results of Huang’s [46] meta-analysis. Therefore, these negative effects of SN3—Daily time usage and SN6—Frequency of posting photos have a special weight. It follows that some aspects of overuse of social media networks may reduce work performance in some groups of employees, and it has been shown that these are older employees.

It should be noted that items SN1—Number of social media networks and SN2—Frequency of social media networks usage have more emphasized positive effects in younger employees, while in older employees these relations do not matter (similar relationships exist between women and men respondents). It is more common for younger people to use multiple social media networks and access them frequently. In that way, they connect with the environment, have the opportunity to communicate and be visible. Through this connection, among other things, they demonstrate their commitment to the work they do and the organization in which they work (there is a strong, positive impact on JS8—Nature of work and OCM1—Organizational identification).

For younger employees, item SN7—Number of groups has a much more unfavorable effect on most job satisfaction and organizational commitment dimensions. This is now in line with the results of the regression analysis for the whole sample, where item SN7—Number of groups has a stronger adverse effect than item SN8—Number of groups (active participant). In younger respondents age does not have a negative impact on dependent variables due to the time spent during active participation in groups (as in men), it is about the fact that only membership in a number of groups indicates a certain search for some alternative opportunities, as in life in general, so in business. Young people can be more affected by this because they still have time for some changes. For older respondents, eventual membership in a larger number of groups does not have such an impact, it cannot disturb them to such an extent and jeopardize their satisfaction with the existing job. Similar to the previous moderator, it can be stated here that the moderating effect of the age of respondents is present in a small but significant number of cases and is on average emphasized. This answered the research question RQ2.

5.5. Summary of Results

The influences and actions of the observed social media usage items can be summarized (systematized) in the following way. Item SN1—The number of social media networks has a positive effect on most job satisfaction dimensions and on OCM1—Organizational identification, which is especially emphasized among women and younger employees. Item SN2—Frequency of social media usage shows similar effects, only to a lesser extent.

Item SN3—Daily time usage has an adverse effect on most job satisfaction dimensions, and this is especially true for men and older employees, while for older employees it also reduces WP—Work performance. Item SN5—Number of photos has a positive effect on JS8—Nature of work and OCM3—Organizational loyalty, while item SN6—Frequency of posting photos has a negative effect on JS3—Supervision in males and a negative effect on JS8—Nature of work and WP—Work performance at older employees.

Items SN7—Number of groups and SN8—Number of groups (active participant) have negative effects on JS1—Pay, JS2—Promotion, and organizational commitment dimensions. The unfavorable effect of SN7—Number of groups is more emphasized in the whole sample and in younger employees, while the unfavorable effect of SN8—Number of groups (active participant) is more emphasized in males, especially on OCM3—Organizational loyalty.

6. Conclusions

6.1. General Conclusion

If the results are generalized, it can be concluded that SN1—Number of social media networks and slightly less SN2—Frequency of social media usage and SN5—Number of photos have a positive effect on individual outcomes of employed persons. SN3—Daily time usage, SN6—Frequency of posting photos, SN7—Number of groups, and SN8—Number of groups (active participant) have negative effects on individual outcomes of employed persons.

It should be noted that using social media networks for too long (during the day) can especially reduce job satisfaction while joining a large number of groups strongly jeopardizes organizational commitment. Active participation in a number of groups significantly reduces salary satisfaction and organizational loyalty among male employees. Excessive usage of social media networks and frequent posting of images can reduce satisfaction with the nature of work and work performance among older employees. It should certainly be borne in mind that most of the observed relations may have the opposite direction: certain, existing job dissatisfaction and lower organizational commitment may contribute to increased use of social media networks or some aspects of social media networks.

The results and discussion show that the impacts of social media usage on job satisfaction, organizational commitment, and work performance of employed persons may not be so strong, but they are certainly significant and complex. First of all, the nature of the observed relationships is such that it was not realistic to expect a large number of strong and statistically significant relationships, given that the observed outcomes of employed persons are influenced by numerous other organizational and individual variables. However, precisely because of that, the determined statistically significant effects stand out even more, and the obtained results have a special significance. In addition, it was shown that the detected impacts are complex: they can be positive and negative, significant for certain groups of respondents, and without significance for some other groups of respondents. For example: using more social media networks has some beneficial effects, but long-term usage has adverse effects; influences The number of photos and The frequency of posting photos have the influence of opposite direction; the action of The number of groups and The number of groups (active participant) is of the same direction, but of different intensity in certain segments of the sample. Therefore, the observed influences will depend on numerous, specific nuances of using social networks. In general, it can be concluded that social networks provide a modern form of socialization with a large number of people and that it provides people with a platform for expression and exchange of information, and depending on the context may positively or negatively affect certain things.

6.2. Theoretical and Managerial Implications

Discovered connections and influences have scientific and practical significance. The scientific significance is that the observed relations have not been sufficiently examined in employed persons so far, as well as the fact that significant effects have been discovered between specific social media usage items and dimensions of individual outcomes of employed persons. Research on individual social media usage items and individual outcomes dimensions, certainly proved to be very useful, even necessary, due to the variable and complex relations, which are precisely discovered and defined in this way. In addition, analyses with the introduction of moderators provide originality of work and additional useful results. The impact of social media on all aspects of human lives is inevitable and growing. Researching them gives scientists of all fields an insight into possible influence development and a roadmap for future research. This is important so academics can develop a sure boundary of healthy social media habits. In that sense, the theoretical implication of this research is that it opens space and indicates the possibilities and directions of some new, necessary and significant research related to different effects of social media on work, work performance, and employee satisfaction. All this certainly, makes this paper provide a significant contribution to theoretical considerations in the field of social media networks on human resources and human behavior.

The practical significance of the research is that leaders and managers in organizations can understand how social media usage affects their employees. Moderate usage of social media networks is desirable, which contributes to increased job satisfaction and organizational identification. However, using social media networks for too long, participating in a large number of groups and frequent posting pictures are not desirable and can be an indicator of reduced satisfaction, lower commitment, and lower work performance (real or potential), especially for certain groups of employees. Managers should monitor the activities of their employees on social media networks, understand these actions, and then, following the results presented here, take appropriate actions to direct these behaviors for the benefit of the organization and the individual. Practically, companies’ management could direct employees towards the usage of those social media networks that do not require a high level of user involvement: in this way, the positive and negative effects of social media networks would be used to a greater extent. In addition, since job applications often ask candidates for links to their social media network, HR managers can pay attention to the number of groups, the number of images, the frequency of uploading images, etc. In the general case, social media is constantly evolving and evolving, and providing a deeper insight into its influences can be beneficial in preventing some of its negative impacts. Changes that have taken place with the rise of social media networks have led to many changes in communication and thus in business. Social media also had many positive sides and managers have to be prepared to take advantage of them and implement them into training and development. This research, with the mentioned possibilities of the practical application of the results, can significantly contribute to the improvement of various individual work-related outcomes of employed persons, from the aspect of the overall use of social media.

6.3. Limitations and Future Research Paths

The limitation of the research is that it was carried out in West Balkan countries, so the obtained results are primarily valid for this region. However, similar effects can be expected to exist in other countries. Therefore, as well as due to the theoretical and practical significance of the obtained results and their complexity, one of the proposals for further research is the implementation of similar studies in some other countries and regions. In addition, suggestions for further research are as follows: determining the impact of social media usage on some other elements of organizational behavior (for example, communication satisfaction, trust at work, organizational civic behavior, etc.), observing dependent variables in these relations as constructs of higher-order (for example, job satisfaction, organizational commitment as one dimension), introduction to the analysis of some other moderators (for example, level of education, position in the organization, etc.), analysis of the impact of data on whom respondents engaged with on social networks.