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Computers in Human Behavior 36 (2014) 340–349

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Computers in Human Behavior

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p h u m b e h

Effects of support and job demands on social media use and work outcomes

http://dx.doi.org/10.1016/j.chb.2014.03.061 0747-5632/� 2014 Elsevier Ltd. All rights reserved.

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Peerayuth Charoensukmongkol ⇑ International College, National Institute of Development Administration, 118 Moo3, Sereethai Road, Klong-Chan, Bangkapi, Bangkok 10240, Thailand

a r t i c l e i n f o a b s t r a c t

Article history:

Keywords: Social media Social exchange Social support Social capital Media synchronicity theory Job performance

Studies related to the use of social media in the workplace are still somewhat scarce despite their increas- ing popularity in social media research. This paper aims to investigate how employee perceptions of a workplace related to coworker support, supervisor support, and job-related demands can determine the degree of attachment some employees feel to social media use at work. The study also explores some consequences of social media use at work by analyzing its associations with job satisfaction, job perfor- mance, and cognitive absorption. The data was collected through the snowball sampling technique of 170 employees in Thailand and analyzed using partial least squares regression. For the factors predicted to influence social media use at work, the analysis found that coworker support and job demands are positively associated with social media use intensity, while supervisor support is negatively associated with it. The analysis also found a positive association between job satisfaction and job performance and social media use at work. An indirect relationship between social media use and cognitive absorption was also found through the mediating effect of job satisfaction. Overall, the evidence suggests that social media use at work may not necessarily lead to negative job-related outcomes.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Leading online social media sites such as Facebook, Twitter, MySpace, Pinterest, Instagram, and so forth have become an inte- gral part of the daily activities of many people around the world. In the academic arena, various aspects related to social media use have received the preponderance of attention from scholars. One of the main focuses in research is the impact of social media use intensity on psychological and societal outcomes (Oh, Ozkaya, & LaRose, 2014; Reinecke & Trepte, 2014). However, most of this research was mainly conducted in educational institutions and used students as subjects (Chang & Heo, 2014; Kalpidou, Costin, & Morris, 2011; Kirschner & Karpinski, 2010). So far, less is known about the effect of social media use in organizations. Studies conducted in this context are important as some organiza- tions have become concerned about employees’ access to social media sites during work hours. Some argued that social media can interrupt work and affect employee performance. Currently, a lack of empirical evidence exists concerning this impact to guide organizational policies regarding the use of social media in the workplace.

The objective of this study, which attempts to fill this research gap, is twofold. First, some factors that can influence the degree to which employees believe that social media is important for them at work are explored, with specific focus on the role of social sup- port within an organization. Two aspects of social support that are focused on are coworker support and supervisor support; these two factors were selected since coworkers and supervisors are per- sons who not only closely interact with employees in a workplace but also influence their behavior (Bakker & Bal, 2010; Schreurs, Hetty van Emmerik, Günter, & Germeys, 2012). Moreover, as the use of social media is mainly driven by the degree of social connec- tion that people have with others (Sacks & Graves, 2012), the first research question is whether the quality of the relationships that employees develop with people in an organization can influence how they perceive the importance of social media in the work- place. In addition, this research also focuses on the impact of some job characteristics on social media use at work. Specifically, the perceived importance of social media in terms of favorable or unfa- vorable work conditions with respect to job demands is explored.

The second objective of this research is to investigate the rela- tionship between social media use intensity at work and job-related outcomes of employees. Following a study by Moqbel, Nevo, and Kock (2013), two job-related outcomes that this research empha- sizes are job satisfaction and perceived job performance. These two factors are selected because research has shown that they are

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considered key indicators that can determine the success of an orga- nization. In order to extend the study of Moqbel et al. (2013), one additional job-related outcome in this research is the cognitive absorption that employees have toward their work. This outcome factor is selected as it reflects ‘‘the intensity of focus and immersion experienced by the employees when working’’ (Ho, Sze-Sze, & Chay Hoon, 2011: p. 26). Specifically, the author aims to explore if the degree of social media use at work can affect the degree to which employees can focus on work activities. Moreover, the study was conducted using samples from Thailand. As previous studies on social media were mainly conducted in the United States, it is neces- sary to determine whether these results would be replicated in dif- ferent cultures. Specifically, Thailand is a country where social media is very popular among people of all ages. The number of social media users in Thailand has grown significantly, as recent statistics showed that in 2013, there were about 18 million social media users in Thailand, about 27 percent of the total population (Millward, 2013). This increase in social media usage in Thailand makes the country appropriate for social media research.

The samples used for this research (employees working in ser- vice and manufacturing industries) were obtained through the snowball sampling method. Even though using this nonprobability sampling technique may raise some concerns regarding the repro- ducibility of the findings in other contexts, results from this study will add to the existing literature, in which there is a paucity of evi- dence regarding some factors behind the use of social media in the workplace and related job outcomes. In addition, the results will also provide implications to managers about policies toward the use of social media during work.

2. Background and hypotheses

2.1. Social media

Social media is defined by Kaplan and Haenlein (2010: p. 61) as ‘‘a group of Internet-based applications that build on the ideologi- cal and technological foundations of Web 2.0 and that allow the creation and exchange of User Generated Content.’’ Social media has gained significant popularity worldwide because it not only allows users to maintain personal relationships with family, friends, and colleagues but also provides them with opportunities to make new social connections (Raacke & Bonds-Raacke, 2008). In addition to the use of social media for personal networking, peo- ple can access social media for other purposes, such as information seeking and entertainment (Park, Kee, & Valenzuela, 2009). More recently, social media has also been applied for business and mar- keting purposes to advertise products and services online (Kaplan & Haenlein, 2010).

Despite the benefits that social media provides, concern has been increasing regarding its potentially negative impact on users. In particular, concerns related to social media addiction have recently been raised (Andreassen, Torsheim, Brunborg, & Pallesen, 2012; Griffiths, 2012). A clinical report showed that some people are prone to developing social media addiction disorder (defined as being unable to refrain from checking one’s social media) (Karaiskos, Tzavellas, Balta, & Paparrigopoulos, 2010); this behavior dramatically interferes with their daily lives since they cannot focus on their jobs and/or other responsibilities. In addition, empirical research on social media has reported various outcomes. For example, Kalpidou et al. (2011) conducted a study on the impact of Facebook-use intensity on self-esteem using a sample of seventy undergraduate students. They found that increased time spent on Facebook correlated with lower self-esteem. A study by Kirschner and Karpinski (2010) on the effects of Facebook-use intensity on academic performance found that students who spent

more time on Facebook not only spent less time studying but also had poorer academic performance compared with students who spent less time on Facebook. On the other hand, Kim and Lee (2011) conducted a study about the relationship between the num- ber of Facebook friends and the subjective well-being of university students and found a positive link between the two factors. A study by Reinecke and Trepte (2014) found that social media tended to enhance the psychological well-being of subjects who used it as a form for authentic self-presentation.

A recent study by Moqbel et al. (2013) is considered to be the pioneering work on the impact of social media use in an organiza- tion on job-related outcomes, including job satisfaction, job perfor- mance, and organizational commitment. By using a sample of 193 employees in the United States, they found that social media use intensity was positively associated with job performance and orga- nizational commitment through the mediating effect of job satis- faction. Generally, their results provided support regarding the positive effect of social media use in an organization. Despite these new findings, it is still necessary to obtain additional evidence in a different context. Moreover, to date, some of the workplace factors that lead workers to believe that social media use is important for them remain undefined.

2.2. Social support and social media use intensity at work

Social support is widely conceptualized in research as ‘‘the functions performed for the individual by significant others, such as family members, friends, and colleagues’’ (Schreurs et al., 2012: p. 263). Although this conceptualization encompasses sup- port from various sources, this research focuses on support from coworkers and supervisors as they are the individuals who have the most influence on employees’ behaviors within an organiza- tion. Specifically, the author argues that the level of interpersonal support employees perceive from their coworkers and from their supervisors can determine the degree to which employees feel that social media is important for them at work. However, these two aspects of social support at work may have different effects on the intensity of social media use in an organization.

First, with respect to the role of coworker support, this study hypothesizes that coworker support can increase the intensity of social media use at work. Coworker support was defined in litera- ture as ‘‘the extent to which one’s coworkers are helpful, can be relied upon in times of need, and are receptive to work-related problems’’ (Menguc & Boichuk, 2012: p. 1360). Accordingly, the main reason why perceived high levels of support from coworkers can increase social media use at work is because good relationships among colleagues make employees feel connected to one another, which in turn motivates them to communicate and interact more often (Fay & Kline, 2011). Social media can serve as an online plat- form that makes it more convenient for employees to connect with their colleagues (Raacke & Bonds-Raacke, 2008). Instead of face-to- face interaction, employees may use social media to discuss work and nonwork issues with each other regardless of where they are located within or outside an organization (Skeels & Grudin, 2009). The positive association of coworker support and social media use intensity is also consistent with a study by Oh et al. (2014) that found a connection between perceived social support and social media use. Therefore, our hypothesis is as follows:

H1. Coworker support will positively associate with social media use intensity at work.

While coworker support was hypothesized to increase social network use at work, the study predicts that the relationship between supervisor support and social media use intensity at work will be negative. Supervisor support reflects the degree to which

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employees perceive that their supervisor cares about their well- being. In particular, supervisors are considered to have control over rewards and punishments of employees. Thus, the degree to which an employee perceives that the supervisor cares about his or her well-being can determine the employee’s behavior in the work- place (Ertureten, Cemalcilar, & Aycan, 2013). In particular, the con- tribution of supervisor support to employee behaviors can be explained by the social exchange theory, suggesting that ‘‘employ- ees who perceive their organizational environment as supportive will feel obligated to reciprocate with behaviors that are beneficial to the organization’’ (Zhang & Jia, 2010: p. 747). Moreover, studies related to the leader-member exchange theory have showed that employees who received good treatment from their supervisor tended to avoid counterproductive behaviors and care more about how their work and work-related behaviors benefit the organiza- tion (Tse, Huang, & Lam, 2013). Accordingly, when employees receive favorable treatment from their supervisor, they are less likely to spend time during work hours accessing their social media accounts because they may consider this behavior inappropriate and unfair to the supervisor. Therefore:

H2. Supervisor support will negatively associate with social media use intensity at work.

2.3. Job demands and social media use intensity at work

In addition to the role of social support in the workplace on the perceived importance of social media, the characteristics of a given job can also determine the level of social media use intensity at work. In particular, this work proposes that strenuous job demands are one of the main determining factors behind social media use. Job demands refer to any physical, psychological, social, or organiza- tional aspects of a job that create psychological strains for employ- ees (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). Some examples of job demands include high-volume workloads, role con- flict, and other unfavorable working conditions. Research has shown that job demands are critical factors that make employees experi- ence work-related stress and burnout (Demerouti, Bakker, & Fried, 2012). For this reason, it can be possible that employees who expe- rience high job demands may perceive that social media is impor- tant for them during work. This argument can be supported by the job demands–resources model (Hausser, Mojzisch, Niesel, & Schulz-Hardt, 2010), which suggests that employees who experi- ence a high degree of stress due to job demands tend to need some type of support to help them deal effectively with external stressors. Accessing social media can serve as one solution to help employees relax and take breaks from their stressful work surroundings. Accordingly, employees who are involved with highly demanding jobs are proposed to be more likely to access social media compared to those in less stressful positions. Therefore:

H3. Job demands will positively associate with social media use intensity at work.

2.4. Social media use intensity during work and job satisfaction

Locke (1976: p. 1304) defined job satisfaction as ‘‘a pleasurable or positive emotional state resulting from the appraisal of one’s job or job experiences.’’ Since employees are considered one of the most critical assets of an organization, firms tend to be concerned about the level of satisfaction that employees have toward their jobs. In particular, studies have shown that employees who were unsatisfied with their jobs not only demonstrated counterproduc- tive behaviors in a workplace but also had a high tendency to leave the organization (Dong, Mitchell, Lee, Holtom, & Hinkin, 2012).

Conversely, research has shown that employees who develop favorable attitudes toward their jobs are more likely to work pro- ductively and contribute more to their workplace (Bouckenooghe, Raja, & Butt, 2013; Yunxia & Jianmin, 2010). In this regard, job sat- isfaction can be considered one major factor that affects employee work performance. Therefore:

H4. Job satisfaction will positively associate with job performance.

The chance to access social media at work can affect employee satisfaction. On one positive side, occasionally using social media can help employees feel relaxed during work. In addition, access to social media in a workplace can allow employees to have more opportunity to connect to their family and friends both inside and outside their organization (König & Caner de la Guardia, 2014). This social interaction is crucial since it can help employees allevi- ate work-related stress (Schreurs et al., 2012). In particular, this positive contribution is also in line with literature related to social support theory, which shows the positive influence of employee attitudes toward their jobs and good relationships at the workplace (Gaan, 2008; Singh, Suar, & Leiter, 2012). This positive contribution of social media is also consistent with a study by Moqbel et al. (2013), which argued that social media can promote job satisfac- tion of employees as it helps them achieve work-life balance and reduce work-family conflict (Michel, Kotrba, Mitchelson, Clark, & Baltes, 2011). Therefore:

H5. Social media use intensity at work will positively associate with job satisfaction.

2.5. Social media use intensity at work and cognitive absorption

According to Schaufeli, Bakker, and Salanova (2006: p. 702), engagement refers to ‘‘a more persistent and pervasive affective– cognitive state that is not focused on any particular object, event, individual, or behavior.’’ It reflects the degree of vigor, dedication, and absorption that employees have about performing their jobs. Vigor refers to the degree of effort that people invest in their jobs; dedication refers to the level of involvement that people have toward their job; absorption refers to the degree to which people are fully concentrated and happily engrossed in their work (Schaufeli, Salanova, González-romá, & Bakker, 2002; Schaufeli et al., 2006). Specifically, the current study focuses on the absorp- tion aspect of work engagement, which is considered a cognitive aspect of engagement that reflects the psychological state in which employees are ‘‘absorbed in a job so much that everything else is forgotten’’ (Babcock-Roberson & Strickland, 2010: p. 316). The cog- nitive aspect of work engagement is crucial since it has a strong influence on the level of dedication and involvement that people put to their work activities (Ho et al., 2011). Generally, people who are highly absorbed in a job tend to feel psychologically attached to it and tend to perceive that time passes by quickly while they are doing the task (Schaufeli et al., 2006). For this rea- son, employees who are highly absorbed in their jobs tend to be more dedicated to work and are more likely to devote themselves to the performance of their tasks (Babcock-Roberson & Strickland, 2010; Lin, 2010). Existing studies support the concept that employ- ees who are highly engaged in the performance of their jobs tend to report higher work commitment and performance (Bakker & Bal, 2010; Bakker, Schaufeli, Leiter, & Taris, 2008). Therefore:

H6. The level of cognitive absorption that employees demonstrate during work will positively associate with job performance.

To date, there is no empirical evidence regarding the link between social media use intensity and the degree to which people feel psychologically engaged in their jobs. On one hand, some

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research has shown that greater social media intensity can inhibit the ability of people to focus their attention on work activities (Kirschner & Karpinski, 2010). From this reasoning, it can be less likely that the use of social media at work would have a positive contribution to the level of cognitive absorption that employees display toward their work. However, it is possible that using social media at work can help employees in some way develop this cog- nitive absorption. This paper suggests that instead of a direct asso- ciation between cognitive absorption and social media intensity, there rather is a relationship that is mediated through job satisfac- tion. A number of empirical studies have shown that when employees are satisfied with their jobs, they are more likely to feel attached to their work (Mohr & Zoghi, 2008; Zatzick & Iverson, 2011). The job satisfaction that employees achieve through the chance to access social media during work to balance their work- life activities can cause employees to develop favorable attitudes toward their job. As employees are happy with their jobs, they are more likely to enjoy working and can have a high tendency to feel attached to their work. Therefore:

H7. There is no significant direct relationship between social media use intensity at work and the level of cognitive absorption that employees display toward their work.

H8. Job satisfaction will positively associate with the level of cog- nitive absorption that employees have toward their work.

H9. Job satisfaction will mediate the positive relationship between social media use intensity at work and cognitive absorption during work.

2.6. Social media use intensity during work and job performance

Following Moqbel et al. (2013), this research also predicts a positive relationship between social media use intensity and job performance. Specifically, Moqbel et al. (2013) argued from the vantage of work-life balance that employees’ satisfaction that is rooted in social media access in a workplace is a major reducer of employee stress and absenteeism, which will subsequently help them achieve higher levels of performance. In addition, social net- work research posits that ties people develop with others through networking can be a good source of critical information, advice, and assistance that individuals can use to perform their jobs (Sparrowe, Liden, Wayne, & Kraimer, 2001). Chow and Chan (2008) also argued that the quality of social capital as reflected by connections that people build with others can facilitate knowl- edge sharing within a network of people. Based on the social cap- ital theory, using social media at work can have a positive impact on work performance because social media makes it become more convenient and easier for employees to obtain advice from friends or colleagues who are in their social media network. This benefit of social media also coincides with the media synchronicity theory, which posits that communication performance will be enhanced when a variety of media are used (Dennis, Fuller, & Valacich, 2008). According to Cao, Vogel, Guo, Liu, and Gu (2012: p. 3940), ‘‘social media are exactly a combination of different media, provid- ing the ideal combination of media capabilities for knowledge transfer.’’ They also argued that social media can enhance work performance because it serves as a communication channel where explicit and implicit knowledge can be effectively transferred among employees (Cao et al., 2012). Therefore:

H10. Social media use intensity at work will positively associate with job performance.

However, the mere use of social media during work may not be a single factor that directly affects the job performance of employees. It is more likely that the positive association between these two fac- tors could be mediated through the level of job satisfaction that employees have from using social media during work. Employees who are satisfied with their jobs are more willing to work effec- tively, generally leading to higher job performance (Smayling & Miller, 2012). This indirect contribution of social media and social networking is consistent with the study by Moqbel et al. (2013) that found that job satisfaction positively mediated the relationship between social media use intensity and job performance among employees in the United States. Therefore:

H11. Job satisfaction will mediate the positive relationship between social media use intensity at work and job performance.

3. Methodology

3.1. Measures

Following the study by Moqbel et al. (2013), the main depen- dent variable, social media use intensity during work, was measured using the modified version of the scale originally developed by Ellison, Steinfield, and Lampe (2007). The original scale was designed specifically to measure perceptions people have regard- ing their personal levels of attachment to Facebook. Therefore, to be consistent with the previous research, the authors performed wording modifications by replacing ‘‘Facebook’’ with ‘‘social net- working’’ and included Facebook and MySpace as examples to clar- ify the public type of social media. Sample items include ‘‘At work, social networking sites have become part of my daily routine’’ and ‘‘At work, I feel out of touch when I haven’t logged onto social networking sites for a while’’.

Supervisor support was measured using a scale developed by Eisenberger, Huntington, Hutchinson, and Sowa (1986). It consists of five items. Sample items include ‘‘My work supervisor really cares about my wellbeing’’ and ‘‘My supervisor cares about my opinions’’.

Coworker support was measured using a scale developed by Tang (1998) that consists of six items. Sample items include ‘‘My coworkers are very helpful when I encounter difficulties with my work’’ and ‘‘When I encounter a problem I usually seek help from my coworkers’’.

Job demands was measured using five items from the Job Con- tent Questionnaire survey developed by Karasek et al. (1998). This construct was measured in terms of quantitative workload (e.g., work hard, work fast).

Job satisfaction was measured using a scale developed by Cammann, Fichman, Jenkins, and Klesh (1983). The scale consists of three items. Sample items include ‘‘All in all, I am satisfied with my job’’ and ‘‘I like working for my current organization’’.

Job performance was measured in terms of subjective perfor- mance. The scale for job performance was adopted from Rehman (2011). It consists of three questions. Sample items include ‘‘I am very satisfied with my performance in my current job’’ and ‘‘My per- formance in my current job is excellent’’.

Cognitive absorption was measured using six items from Utrecht Work Engagement Scale developed by Schaufeli et al. (2006). Sam- ple items include ‘‘Time flies when I am working’’ and ‘‘I am immersed in my work’’.

All question items for social media use intensity at work, cow- orker support, supervisor support, job demands, job satisfaction, job performance, and cognitive absorption were scored on a five- point frequency scale, ranging from 1 (strongly agree) to 5 (strongly disagree). These constructs were measured as reflective latent variables.

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In addition to the main independent variables, this study con- trolled for organizational factors and demographic factors that can influence the endogenous variables. Control variables for social media use intensity at work include age, gender, educational level, working class, job position, job tenure, salary, organizational policy about the use of social media at work, and the degree to which the use of social media is related to work. Control variables for job satisfaction, job performance, and cogni- tive involvement include age, gender, educational level, working class, job position, job tenure, salary, coworker support, supervi- sor support, and job demands.

Age was measured in years. Gender was measured as a dummy variable (females = 0; males 1). Educational level was measured using an ordinal scale (1 = less than a bachelor’s degree; 2 = bachelor’s degree; 3 = master’s degree; 4 = doctoral degree). Working class was measured as a dummy variable (white-collar workers = 0; blue-collar worker = 1). Job tenure was measured as the number of years that respondents had worked for their organizations. Job position was measured using an ordinal scale (1 = junior staff; 2 = senior staff; 3 = junior man- ager; 4 = middle-level manager; 5 = senior-level manager). Salary was measured as monthly payment that employees received. Organizational policy about the use of social media at work was measured as a dummy variable (allow = 1; do not allow = 0). The degree to which the use of social media is related to work was measured using an ordinal scale ranging from 1 (not related at all) to 5 (highly related).

Table 1 Descriptive statistics of respondents.

Age (in years) Mean: 28.69 Standard deviation: 5.72

Gender Male: 64 (38%) Female: 106 (62%)

Education Below bachelor’s degree: 19 (11%) Bachelor’s degree: 109 (63%) Master’s degree: 40 (23%) Doctoral degree: 2 (1%)

Type of organization Manufacturing: 73 (43%) Service: 97 (57%)

Working class White collar: 159 (94%) Blue collar: 11 (6%)

Job position Junior staff workers: 111 (65%) Senior staff workers: 19 (11%) Lower-level managers: 19 (11%) Middle-level managers: 17 (10%) Senior-level managers: 4 (3%)

Salary (in Thai Baht) Mean: 26,647 Standard deviation: 18,398

Job tenure (in years) Mean: 3.35 Standard deviation: 2.8

Policy towards the use of social media at work Allowed: 118 (69%) Not allow: 52 (31%)

The degree to which the use of social media is related to work

Not related: 50 (29%)

A little bit related: 40 (24%) Moderately related: 57 (34%) Pretty much related: 17 (10%) Highly related: 6 (3%)

3.2. Samples and data collection

A self-administered questionnaire was used to collect data from respondents. In order to obtain a diverse set of samples from various organizations, a snowball sampling technique was used (Oh et al., 2014). In this research, graduate students who took the research methodology class were asked to distribute questionnaires to their colleagues at their workplace. Question- naire distribution was voluntarily undertaken by students without any compensation or extra class credit. A total of 250 questionnaires were taken and distributed by students; 170 com- pletely filled surveys were returned, yielding a 68 percent response rate.

The final sample is composed of 64 males (38 percent) and 106 females (62 percent). Mean age is 28.69 years old (standard devia- tion = 5.72). For educational level, 19 had not received their bach- elor’s degrees (11 percent), 109 held bachelor’s degrees (63 percent), 40 held master’s degrees (23 percent), and 2 held doctoral degrees (1 percent). For type of organization, 97 respondents reported that they worked in the service sector (57 percent) while 73 reported that they worked in the manufacturing sector (43 per- cent). For working class, 159 were white-collar workers (94 per- cent) and 11 were blue-collar workers (6 percent). For job position, 111 were junior staff workers (65 percent), 19 were senior staff workers (11 percent), 19 were lower-level managers (11 percent), 17 were middle-level manager (10 percent), and 4 were senior-level managers (3 percent). Mean salary is 26,647 Thai Baht (standard deviation = 18,398). The mean job tenure was 3.35 years (standard deviation = 2.8). For policy towards the use of social media at work, 118 reported that their firm allowed social media access (69 percent), while 52 reported that their firm did not allow (31 percent). For the degree to which the use of social media is related to work, 50 reported that it was not related (29 percent), 40 reported that it was a little bit related (24 percent), 57 reported moderately related (34 percent), 17 reported pretty much related (10 percent), and 6 reported highly related (3 percent). Descriptive statistics for the respondents are reported in Table 1.

3.3. Analysis strategy

This study uses partial least-squares (PLS) regression for the analysis. PLS was selected for the analysis because it offers more flexibility in comparison with covariance-based standard error of the mean (SEM) techniques. Specifically, PLS does not require data to be normally distributed (Fornell and Bookstein, 1982). An addi- tional advantage of PLS is that it allows smaller sample sizes com- pared to other SEM techniques (Chin and Newsted, 1999). PLS analysis was performed using WarpPLS version 3.0 (Kock, 2012).

4. Results

Prior to PLS model estimation, it is important to perform a series of analyses. Firstly, construct reliabilities were evaluated using Cronbach’s alpha (a) and composite reliability coefficients. The results, as shown in Table 2, indicated that all coefficients exceeded 0.7 as recommended by Fornell and Larcker (1981). Secondly, the convergent validity of latent variables was evaluated using factor loadings. The results indicated that all factor loadings were greater than 0.5, which is satisfactory as suggested by Hair, Black, Babin, and Anderson (2009). Next, the test for discriminant validity was performed using average variance extracted (AVE). As recom- mended by Fornell and Larcker (1981), the square root of the AVE of each construct must be greater than other correlations

Table 2 Construct reliability indicators.

SN CWS SPS JDM JSAT JPFM CA

Composite reliability .909 .947 .9 .868 .852 .879 .851 Cronbach’s alpha .879 .936 .848 .81 .737 .793 .789

Note: SN = social media use intensity at work, CWS = coworker support, SPS = supervisor support, JDM = job demands, JSAT = job satisfaction, JPFM = job performance, CA = cognitive absorption.

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involving that construct in order for discriminant validity to exist. The results were also satisfactory. Table 3 reports Spearman corre- lations among variables as well as reliability and discriminant validity indicators of latent variables.

Finally, the test for the possible presence of multicollinearity among the indicators was performed using full Variance Inflation Factor (VIF) statistics. The full VIFs in the model ranged from 1.128 to 2.203, which is considerably below the critical value of 3.3 as suggested by Petter, Straub, and Rai (2007). In addition, Kock and Lynn (2012) argued that the full VIF test can serve as a technique that captures the possibility of common method vari- ance (Lindell & Whitney, 2001) in the PLS model. According to Kock and Lynn (2012), the full VIF test may be seen as a vari- ance-based SEM similar to the common method bias test used in covariance-based SEM. They suggested that common method bias can be a serious issue if the full VIF value is higher than 3.3. In this study, the test results suggested that all of the full VIF values were considerably lower than the critical value.

Results from the PLS analysis that included all control variables are presented in Fig. 1. The standardized coefficient and t-values were calculated using a jackknifing resampling procedure. This resampling method was performed to help minimizing problems associated with the presence of outliers due to errors in data col- lection (Chiquoine & Hjalmarsson, 2009). The author also used ranked data in the estimation in order to deal with an outlier issue. In particular, WarpPLS 3.0 allows users to select an option whereby all the data is automatically ranked prior to the SEM analysis in order to conduct the analyses with only ranked data. When data is ranked, typically the value distances that typify outliers are sig- nificantly reduced, effectively eliminating outliers without decreasing the sample size (Kock, 2012).

Table 3 Correlations among latent variable and discriminant validity indicators.

SMUI CWS SPS JDM JSAT JPFM CA

SMUI (.791) CWS .05 (.831) SPS �.08 .434** (.833) JDM .09 �.048 �.008 (.754) JSAT .133 .401** .399** �.165* (.812) JPFM .195* .223** .166* .197* .368** (.841) CA .144 .205** .285** .041 .459** .335** (.7) AGE �.228** �.071 .028 .095 .036 .003 .188* GEN �.069 �.144 �.137 .033 �.151* �.03 �.138 EDU �.048 .019 .002 .111 �.127 .053 �.03 SMRW .559** �.087 .033 .008 .08 .133 .221* WC �.004 �.013 �.018 �.031 .026 .119 .018 JPOS �.132 �.117 �.042 .192* �.09 �.007 .079 JTN �.087 �.032 �.038 .131 .059 .041 .142 OPSN .236** .076 .127 �.074 .221** .061 .113 SAL �.148 .02 �.004 .223** �.129 .11 �.124

Spearman correlation coefficients are reported; square roots of average variance abstrac SN = social media use intensity at work, CWS = coworker support, SPS = supervisor supp CA = cognitive absorption, AGE = age, GEN = gender (male = 1), EDU = education, SMRW WC = working class (blue-collar worker = 1), JPOS = job position, JTN = job tenure, OPSN = ** Notes: Significant level at 1% respectively. * Significant level at 5% respectively.

Given the statistical methods outlined above, the nine hypoth- eses either met or did not meet the criteria for statistical signifi- cance as described below. To summarize quickly, hypotheses 1–6 and hypotheses 8–10 showed significant relationships between social media use and the other factor(s) measured; hypotheses 7 and 11 did not reveal significant relationships. Other than hypoth- esis 11 (predicting an indirect relationship between social media use intensity during work and job performance, as mediated by job satisfaction), all hypotheses were confirmed by the data obtained. The details are as follows:

– Hypothesis 1 predicted a positive link between coworker sup- port and social media use intensity at work. The result revealed a positive and significant relationship between them (b = .124; p < .05). Thus, hypothesis 1 is supported.

– Hypothesis 2 predicted a negative link between supervisor sup- port and social media use intensity at work. The result indicated a negative and significant relationship between them (b = �.172; p < .05). Thus, hypothesis 2 is supported.

– Hypothesis 3 predicted a positive link between job demands and social media use intensity at work. The analysis also showed that they were positively and significantly associated (b = .13; p < .05). Thus, hypothesis 3 is supported.

– Hypothesis 4 predicted a positive association between job satis- faction and job performance. The analysis showed that their relationship is positive and significant (b = .204; p < .05). Thus, hypothesis 4 is supported.

– Hypothesis 5 predicted a positive relationship between social media use intensity at work and job satisfaction. The results indicate a positive and significant relationship between the two variables (b = .144; p < .05). Therefore, hypothesis 5 is supported.

– Hypothesis 6 predicted a positive link between cognitive absorption and job performance. The result is positive and strongly significant (b = .372; p < .001). Thus, hypothesis 6 is supported.

– Hypothesis 7 predicted that there is no direct relationship between social media use intensity at work and cognitive absorption. The result indicated that even though these two variables are positively related, the association is not statisti- cally significant (b = .073; p = .238). Therefore, hypothesis 7 is supported.

AGE GEN EDU SMRW WC JPOS JTN OPSN

(1) .03 (1) .114 .019 (1)

* �.084 �.08 �.14 (1) .144 .151* �.138 .149 (1) .208** .156* .134 �.062 .076 (1) .425** .02 .062 .052 .116 .23** (1) �.039 �.061 �.046 .279** .112 �.1 �.029 (1) .229** .151* .46** �.302** �.052 .554** .255** �.15

ted are in parentheses. ort, JDM = job demands, JSAT = job satisfaction, JPFM = job performance. = social media use related to work. organizational policy about the use of social media at work (allow = 1), SAL = salary.

Fig. 1. PLS results. Notes: ���, ��, � indicate significant level at 0.1 percent, 1 percent, and 5 percent, respectively; solid lines represent significant results. SN = social media use intensity at work, CWS = coworker support, SPS = supervisor support, JDM = job demands, JSAT = job satisfaction, JPFM = job performance, CA = cognitive absorption; control variables are pointed to all endogenous variables.

346 P. Charoensukmongkol / Computers in Human Behavior 36 (2014) 340–349

– Hypothesis 8 predicted a positive link between job satisfaction and cognitive absorption. The result showed that the associa- tion is positive and strongly significant (b = .372; p < .001). Thus, hypothesis 8 is supported.

– Hypothesis 9 predicted an indirect relationship between social media use intensity during work and cognitive absorption as mediated by the variable of job satisfaction. In order to test the mediating effect, the method suggested by Preacher and Hayes (2004) was performed in WarpPLS 3.0. The analysis shows a positive and significant result (b = .054; p < .05). This finding confirms the mediating effect of job satisfaction on the positive link between social media use intensity at work and job performance. Therefore, hypothesis 9 is supported.

– Hypothesis 10 predicted a positive link between social media use intensity at work and job performance. The result shows that they are positively and significantly related (b = .126; p < .05). Thus, hypothesis 10 is supported.

– Finally, hypothesis 11 predicted an indirect relationship between social media use intensity during work and job perfor- mance, as mediated by job satisfaction. Although the result from the analysis is positive, it is not statistically significant (b = .042; p = .069). Therefore, hypothesis 11 is not supported.

Lastly, the significance of the relationships between control variables and key dependent variables can be described as follows:

– Social media use intensity at work positively associated with the degree to which the use of social media is related to work (b = .537; p < .001) and organizational policy that allows social media access at work (b = .119; p < .05); the result also indi- cated that social network use intensity at work is higher in females than in males (b = �.17; p < .01).

– Job satisfaction positively associated with coworker support (b = .308; p < .001), supervisor support (b = .226; p < .05), but negatively associated with job demands (b = �.158; p < .05).

– Job performance positively associated with salary (b = .233; p < .05) and job demands (b = .26; p < .01); moreover, blue-col- lar workers reported higher job performance than white-collar workers (b = .1; p < .05).

5. Discussion

This research investigated some factors that may explain why employees perceive that social media is important for them at work, as well as to explore some job-related outcomes associated with social media use during work. For the factors that lead to social media use at work, the analysis found evidence that social support in a workplace tended to associate strongly with the degree to which employees attached to social media during work. Specifically, employees who perceived that their coworkers were supportive tended to develop a greater attachment to social media at work. On the other hand, employees who perceived that their supervisor was supportive tended to have less attachment to social media. In addition, the study also found evidence of a positive link- age between the level of job demands and social media use inten- sity. In particular, employees who experienced unfavorable working conditions tended to be those who perceived that social media was important for them at the workplace. Regarding the job-related outcomes of social media use intensity at work, the study found supporting evidence about its positive association with job satisfaction, job performance, and cognitive absorption. However, while the analysis confirmed its direct association with job satisfaction and job performance, the association with cogni- tive absorption was found to be mediated through job satisfaction.

In particular, the results regarding the job-related outcomes of social media use intensity in a workplace are consistent with the results from the work by Moqbel et al. (2013) that used samples from the U.S. Here, the author found similar and consistent results in samples of the Thai workplace. However, instead of the indirect effect that social media use intensity had on job performance through job satisfaction, the present study found strong support for a direct relationship between them, but not through the medi- ating effect of job satisfaction. Importantly, the positive associa- tions between social media use intensity on the key dependent variables were still significant even though the model controlled for other factors that strongly influenced job-related outcomes.

Moreover, this study contributes to the previous research by adding the consideration of the possible impact of social media use at work on the ability of employees to focus on their tasks.

P. Charoensukmongkol / Computers in Human Behavior 36 (2014) 340–349 347

Interestingly, the evidence supported the positive link between the two factors, contradicting the argument that the use of social media can hamper the ability of people to concentrate on their work (Kirschner & Karpinski, 2010). As predicted, this positive link appeared to be mediated through satisfaction that employees had with their job instead of a direct association. This result suggests that just using social media may not be a sufficient condition for people to focus better on their task; rather, it could create favor- able conditions for improving focus on job-related tasks. For the scope of this research, the satisfaction that employees have from the opportunity to better balance their work lives and their per- sonal lives may be among the various conditions that allowed them to concentrate with more involvement on their jobs.

In addition to the evidence of the job-related outcomes associ- ated with the use of social media at work, this research also makes an additional contribution to literature by identifying some factors that motivate employees to feel attached to social media in an organization. This contribution is crucial, as research concerning this is currently lacking. Although several studies have identified some factors that explain why people tend to use social media more or less often (Chang & Heo, 2014), none has explored factors in a workplace that determine social media use intensity at work.

From a theoretical perspective, the overall findings about the associations between social media use at work, job satisfaction and performance, and various other work-related factors are in line with the job demand-resource model, which emphasizes the role of resources that employees can rely on to help them effectively deal with stressors at work. In this regard, employees may consider social media as a means by which they can maintain personal con- nections with family, friends, and colleagues. The quality of the relationships that employees maintain with these individuals in their social network is regarded as a source of support for them in terms of advice, caring, and empathy. In collectivist cultures such as that of Thailand, where people tend to value social connec- tions, employees may be more likely to perceive social media’s importance as a way of obtaining support from coworkers (Nadkarni & Hofmann, 2012). These cultural factors can also explain why access to social media in a workplace tended to asso- ciate positively with job satisfaction and job performance. As human life is driven by social needs, the ability to maintain per- sonal connections with friends while at work can be a crucial factor that allows employees to balance their work/life activities more effectively. Employees who are fully satisfied in their personal lives are more able to concentrate on their work. The findings also coin- cide with research related to a social capital theory and a theory of media synchronicity that posited that online social media is an effective communication tool that allows people to share informa- tion and benefit from knowledge transfers among friends in their network (Cao et al., 2012). This is another primary reason why access to social media can enhance performance of employees. These findings taken collectively explain the positive contribution that use of social media during work has on job-related outcomes. Results regarding these positive contributions are also consistent with research related to job characteristics that suggests that orga- nizations should provide favorable working environments for employees to help them develop positive attitudes towards their work and organization (Biswas, 2011; Zatzick & Iverson, 2011).

Moreover, the negative linkage between supervisor support and the intensity of social media use at work is consistent with social exchange theory that emphasizes the role of treatment that employees receive from managers on employee behaviors in a workplace. Specifically, employees who perceived that their super- visor was supportive and cared about their well-being were found to have less attachment to social media while at work. This finding, therefore, suggest a crucial implication. If managers believe that using social media at work is counterproductive and want to

reduce this behavior, it is important for them to provide adequate support to employees. Perceived support from supervisors can per- suade employees to refrain from using social media at work as they perceive that doing so is not fair to the organization. On the con- trary, employees that have a negative perception of their supervi- sors may develop a cynical attitude, and subsequently feel motivated to spend more time on social media at work to express their negative job-related attitudes or complain about their super- visors on their social media site.

5.1. Limitation and future research directions

Firstly, the data used in this research is cross-sectional. Using cross sectional data in the analysis makes it difficult to justify the direction of causality between the constructs (Maxwell & Cole, 2007). For example, while social media use intensity was hypothesized to affect job performance, it is possible that employ- ees with poor job performance have less opportunity to spend time accessing social media at work since they may need to spend more time improving their performance. This is a common limitation experienced in previous social media research (Chang and Heo, 2014). Secondly, it is possible that using a self-evaluation question- naire to collect the data may cause some bias or inaccuracy in the measurements. Thirdly, the use of a snowball sampling technique to obtain respondents may cause bias in sample selection. While this sampling technique is used when researchers have no way to obtain a representative sample, it is susceptible to issues regard- ing the degree to which the results can be replicated in further studies. Future works may employ qualitative analysis and include triangulating the sources of data to strengthen the findings. More- over, a study based on small-scale data collection from only two industries may limit the generalizability of the results. Future stud- ies may need to expand the sampling frame in order to cover more samples by using respondents from different industries.

The current research also offers some direction for future studies. Although this research provides new evidence that extend our understanding about social media use at work, more research ave- nues need to be explored. Future studies may investigate the impact of social media access at work on other job-related outcomes. Researchers may focus on the behavioral and emotional aspects of job engagement, in addition to the psychological aspect of engage- ment explored in the present study. Equally important, it is also important to explore other antecedents that cause employees to feel that social media is necessary for them in a workplace. Finally, since to date research on social media has tended to be limited to a single country (that is, each study tends to focus on a single country, even if multiple countries are covered by the breadth of studies), it is important for future studies to conduct a cross-cultural analysis to compare the effects of social media between samples from different countries in order to determine if culture can influence the results. A single study that examines social media use across cultures will use the same methodology and study design across the cultures, allow- ing for better comparison. For example, researchers may investigate if the role of social support can influence social media use intensity of employees in individualist cultures.

6. Conclusion

In conclusion, this research expands our understanding about the motivations social media is used in the workplace, and the con- sequences of this use. Despite research limitations, the study pro- vided some evidence that organizational factors including coworker support, supervisor support, and job demands were among the key reasons that explained why employees felt a greater or lesser attachment to social media at work. However,

348 P. Charoensukmongkol / Computers in Human Behavior 36 (2014) 340–349

the study also provided support that using social media in a work- place does not necessarily result in negative outcomes at work. Overall, these findings suggested that organizations may allow employees to access social media, as it may help employees allevi- ate work-related stress, accordingly helping them perform their work more effectively.

Acknowledments

This research received financial support from the International College of National Institute of Development Administration. The author is very grateful to two anonymous reviewers for valuable comments and suggestions. All remaining errors and omissions are the author’s responsibility.

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