TEAM WORK IN THE 21

Team Work in the 21st Century: How new emerged Computer-Mediated Communication Tools affect Team Identification and Team Helping Behaviors

Melanie Schmidt

Master thesis, M.Sc. Human Resource Management University of Groningen, Faculty of Economics and Business

June 14, 2015 Student number: 2788128 Winschoterdiep 46, 9723 AC Groningen tel.: +31 (0) 644 44 77 10 email: m.schmidt.10@student.rug.nl Supervisor: David DeGeest

Abstract

So far, it is not clear what effect the use of computer-mediated communication tools (CMC-Tools) has on influence factors of team effectiveness such as team helping behaviors and team identification. Most findings about the influence of CMC-Tools on team identification rely heavily on laboratory studies, do not investigate virtual teams in their natural environment, or focus on classical categories of media proposed by the Media Richness Theory. Therefore, the leading research question of this study reads as follows: “How does

frequent use and perception of new emerged CMC-Tools influence team helping behaviors and is this relation mediated by team identification?. Based on previous findings, I

hypothesized that use and perception of new CMC-Tools has a positive impact on team helping behavior, and that this relation is mediated by team identification. The hypotheses were tested on a sample of 39 students working in virtual teams in an international student organization by using a mediated linear regression analysis. Furthermore, I classified CMC-Tools in four categories: Document Sharing CMC-Tools, Document Co-creation CMC-Tools, Meeting Tools, and Social Networking Tools. My results show that team identification mediates the relationship between all categories of CMC-Tools and team helping behavior, and that Meeting Tools and Social Networking Tools have a significantly positive effect on team identification. That implies that future research should focus more on new emerging tools in order to advise team managers how to use such tools successfully in order to increase team effectiveness.

Key words: computer-mediated communication, team identification, team helping

Frequent Use and Perception of Computer-Mediated Tools and its Influence on Team Identification and Team Helping Behaviors in Virtual Teams

Technology has become an important part in our daily lives, especially in work environments, and it offers organizations new ways of working together, as well as increasing performance, efficiency, and fast decision making. One of these ways are virtual teams which have emerged increasingly and with them the range of computer-mediated communication tools (hereafter, CMC-Tools). Those tools are supposed to facilitate communication and collaboration among people who are geographically dispersed or work in different organizations, and thus heavily rely on CMC-Tools (Gilson, Maynard, Jones Young, Vartiainen, & Hakonen, 2015; C. Lin, Standing, & Liu, 2008; Schweitzer & Duxbury, 2010; Zigurs, 2003). The influences of those tools on team processes have received only little attention by empirical research so far (Gilson et al., 2015). But since CMC-Tools affect working procedures and team processes, researchers and practitioners should know how the use of CMC-Tools influences processes like team helping behaviors and team identification which are known as important antecedents of team effectiveness (C. Lin et al., 2008; Organ, 1988).

which in turn impact team functioning and effectiveness positively (MacKenzie, Podsakoff, & Fetter, 1991; Organ & Ryan, 1995; Podsakoff, Podsakoff, MacKenzie, Maynes, & Spoelma, 2014; Podsakoff, Whiting, Podsakoff, & Blume, 2009; Schappe, 1998).

So far, it is not clear what influence the use of CMC-Tools has on influence factors of team effectiveness such as team helping behaviors and team identification. Furthermore, most findings about the influence of CMC-Tools on team identification rely heavily on laboratory studies (Schweitzer & Duxbury, 2010). In order to be able to make general statements about processes within virtual teams it is necessary to study them in their natural environment (C. Lin et al., 2008) because team identification needs time to develop (Ellemers, Spears, & Doosje, 2002) and therefore, is difficult to simulate in a laboratory study. Furthermore, the list of CMC-Tools has increased extensively and contains all kinds of different collaboration tools which are widely used in practice. However, many studies still focus on classical tools like emails or phone calls, and thus research does not seem to keep pace with the technological developments (Gilson et al., 2015). Nowadays, it is hard to imagine a world without technology, and many aspects of our daily work life rely on technology. This will increase in the upcoming years. That is why it is important for researchers and practitioners to know how and in what setting using technology, specifically CMC-Tools, in an organization influences team internal processes such as team identification and team helping behaviors which are known as important influence factors for team effectiveness (Gilson et al., 2015; C. Lin et al., 2008; Organ & Ryan, 1995)

thesis aims to answer reads as follows “How does the use and perception of new emerged

CMC-Tools influence team helping behaviors and is this relation mediated by team identification?”. This question will be answered by gathering data from virtual teams that

have been working together for several months within an international operating student organization, and which are familiar with new emerged CMC-Tools such as Google Docs or Skype.

The contribution of this thesis to the literature is threefold. Firstly, it will bring more insights about the processes that new emerged CMC-Tools influence in virtual teams. Thus, the study aims to close the gap between research and fast emerging CMC-Tools in order to keep pace with the technological developments. Secondly, processes in virtual teams will be investigated in their natural environment which allows general statements about the relationship between CMC-Tools, team identification, and team helping behaviors. Thus, previous findings from laboratory studies can be confirmed or challenged. Thirdly, this study aims to provide managers of virtual teams with hand-on knowledge how to use CMC-Tools successfully in order to increase team effectiveness through enhancing team identification and team helping behaviors.

Literature Review & Hypotheses

would fall in between the two states (Schweitzer & Duxbury, 2010; Griffith, Sawyer, & Neale, 2003; Martins, Gilson, & Maynard, 2004). In recent years, research agreed on the existence of different degrees of virtuality of teams (Gilson et al., 2015) including among other attributes different levels of dispersion and the use of technology for communication (Charlier, 2012). These two attributes are the most common ones that can be found in various definitions (Charlier, 2012; Johnson, Bettenhausen, & Gibbons, 2009) and thus, the general definition of virtual teams proposed by Zigurs (2003) is still suitable regardless of the developments within the research field: “Virtual teams are a collection of individuals who are geographically and/or organizationally or otherwise dispersed and who collaborate via communication and information technologies in order to accomplish a specific goal” (Zigurs, 2003: 340).

management tools (e.g., Microsoft Project, Basecamp), and social networking (e.g., Yammer, Jive, Facebook)” (Gilson et al., 2014: 14) in their daily team work. All those tools can be classified as rich media according to Media Richness Theory. However, empirical research about how these new tools influence team work is still rare (Gilson et al., 2015; Koutsabasis, Vosinakis, Malisova, & Paparounas, 2012; Schweitzer & Duxbury, 2010). In order to keep pace with the development of technology and its influence on team work, research needs to focus on such new emerged tools to give evidence-based advise to managers how to use these new emerged CMC-Tools effectively to be able to increase performance and productivity.

New tools such as Google Docs have the advantage of asynchronous collaboration - meaning that team members can document their work at different times (Gilson et al., 2015) but their work is visible immediately to all collaborators. This triggers mutual tracking among members, which can result in an increase of individual performance. ‘Seeing my colleague working I get the need to also contribute to the team’s goal achievement.’ This fits to the findings of Suh and colleagues (2011) who found that computer-mediated communication has a positive effect on intragroup tie strength (Suh, Shin, Ahuja, & Kim, 2011). Furthermore, today’s CMC-Tools have many features that support team work such as reminders or task boards. Workman and colleagues (2003) found in their study that CMC-Tools that are classified as rich according to Media Richness Theory have a positive impact on team commitment. Team commitment as a social factor, has crucial influence on team outcomes like performance or job satisfaction and is similar to team identification. Since most of the new emerged CMC-Tools can be classified as rich media, and having the numerous possibilities in mind that these new tools offer, I propose the following hypothesis:

Organizational Citizenship Behavior (OCB) has been the interest of many studies since its first definition by Organ in the late 1980s. Back then, Organ (1988) defined OCB as “individual behavior that is discretionary, not directly or explicitly recognized by the formal reward system, and that in the aggregate promotes the effective functioning of the organization” (Organ, 1988): 4). OCBs such as team helping behaviors have been recognized as having positive influence on a number of important outcomes such as performance evaluation, organization effectiveness measurements, or reward allocation decisions (Podsakoff et al., 2009). Furthermore, it has been proven that OCB is negatively related to employee turnover, costs, and absenteeism (Podsakoff et al., 2009). This shows that helping behaviors of individuals in teams and in organizations have an important influence on team work outcomes in general, and therefore should be enhanced. When it comes to antecedents of OCB, many researchers have confirmed that team commitment, perception of fairness, and transformational leadership behaviors are positive influence factors on OCB (MacKenzie et al., 1991; Organ, 1988; Podsakoff et al., 2009).

Hypothesis 2: Team identification is positively related to team helping behaviors.

Prior research found that the use of technology has either a negative effect (e.g., Schweitzer & Duxbury, 2010; van der Kleij, Maarten Schraagen, Werkhoven, & De Dreu, 2009), or no effect (e.g. Han et al., 2011) on team performance. However, these studies were focusing on classical CMC-Tools such as email, discussion boards or video-conferences (Gilson et al., 2015). As stated before, team performance is highly correlated with OCB and thus with team helping behaviors (Podsakoff et al., 2009). Therefore, I assume that the found effects of the use of technology on team performance in previous studies apply to team helping behaviors as well. However, I could not find any studies that address this issue. Since these new emerged technologies offer a wide range of advantages such as easier management of tasks or tracking of results by the team leader, it might change the (negative) relationship between the use of those technologies and team outcomes such as performance or team helping behaviors.

Hypothesis 3: The frequent use and perception of new emerged CMC-Tools has a positive influence on team helping behaviors.

Hypothesis 4: The relation between the frequent use and perception of new CMC-Tools and team performance is mediated by team identification.

The conceptual model showing the relations between the different variables and proposed effects are presented in Appendix A.

Methodology

In order to answer the research question, I conducted a correlational research study by gathering data from virtual teams that work in an international student organization. This organization uses a wide range of new emerged CMC-Tools like Google docs, Skype or WhatsApp. The teams have been working together for three to eleven months and consist of students from various study backgrounds living in different cities in Germany. The teams only meet twice a year for one weekend to kick off their work, conduct planning and team building exercises. Furthermore, these students are experienced in using technology for communication. Data about team helping behaviors, team identification and the frequent use and perception of using CMC-Tools was gathered through an online survey based on voluntary participation. The CMC-Tools that the organization uses are categorized in four categories: Document Sharing Tools, Document Co-Creation Tools, Meeting Tools, and Social Networking Tools according to Gilson et al.’s (2014) proposition.

Measures

Use and Perception of CMC-Tools. Because I could not find a suitable measurement

effectiveness, liability, usefulness, and importance of each of the four categories of CMC-Tools (Document Sharing CMC-Tools, Document Co-Creation, Meeting CMC-Tools, and Social Networking Tools) on a 6-point Likert Scale from 1 (lowest) to 6 (highest). Furthermore, I asked whether the team uses a WhatsApp group for internal communication and divided the Social Networking Tools into two sub-categories: task-related use and not task-related use or in other words to bond with their team (See entire survey in the Appendix including definitions of the categories). I summarized frequent use and the different perceptions to one construct for each category because their reliabilities were sufficient. Cronbach’s alpha for Document Sharing Tools was 0.87, for Document Co-Creation Tools was 0.87, for Meeting Tools was 0.78, for Social Networking Tools (task-related) it was 0.90, and for Social Networking Tools (not task-related) it was 0.80.

Team identification. Van der Vegt and Bunderson (2005) measured team

identification using four items from the affective commitment scale by Allen and Meyer (1996). They explained that affective commitment includes social identification because affective commitment concerns “identification with, involvement in, and emotional attachment to the [collective]” (Allen & Meyer, 1996: 253). Following Van der Vegt and Bunderson (2005), I measured team identification by asking the participants to what extent they “feel emotionally attached to their team”, “feel a strong sense of belonging to their team”, “feel as if the team’s problems are their own”, and “feel like part of the family in their team” (Van der Vegt & Bunderson, 2005: 538). The extent was measured on a 6-point Likert Scale from 1 (disagree strongly) to 6 (strongly agree). Cronbach’s alpha for this scale was 0.89.

Team helping behaviors. I assessed team helping behaviors through self-ratings using

been validated with data from diverse individuals that were working in a wide variation of organizational situations (Van der Vegt, 2005). The items were “I am always ready to help or to lend a helping hand to those around me.”, “I am willing to give of my time to help others who have work related problems.”, “I help other team members with heavy workloads.”, and “I help others who have been absent”. I asked the participants to rate to what extent they agree with these statements on a 6-point Likert scale from 1 (disagree strongly) to 6 (agree strongly). Cronbach’s alpha for this measurement was 0.86.

Control variables. Among others, the study of Chatman and Barsade (1995) suggests

that the age and gender of an individual affects their likelihood to engage in team helping behavior. That is why I included both as control variables in all analyses. Since the team varied in size, I included team size as an additional control variable because previous research showed a relation between team size and social factors (Ancona & Caldwell, 1992) such as team identification. I also controlled for team tenure because prior studies indicated effects of tenure on team outcomes (Ancona & Caldwell, 1992) but also because tenure is an indicator for how well individuals get along with the technology used within a team (Rapp, Ahearne, Mathieu, & Rapp, 2010).

Data Analysis

Results

The data was gathered through an online survey (see Appendix C) that was sent out to 92 students who work in virtual teams within an international student organization. Because completing the survey was voluntary, it had only a response rate of almost 36 percent. In total, I gathered responses of 39 individuals that work in fourteen different teams of various sizes. The sample consisted of students and recent graduates and had a mean age of 23.72 years with a standard deviation of 1.89. When it comes to gender the sample was quite balanced: 18 men and 21 women completed the survey. An average team consisted of 6.26 members with an average tenure of 8.51 months. Furthermore, all participants stated that they have an internal WhatsApp group.

Correlation Analysis

Table B1 (see Appendix B) represents all means, standard deviations, and Pearson correlations among the study variables. In support of Hypothesis 1, the results of this correlation analysis show that team identification was positively correlated with Document Sharing Tools (r = 0.324, p < .05), Document Co-creation Tools (r = 0.497, p < .01), Meeting Tools (r = 0.664, p < .01), and Social Networking Tools (not task-related) (r = 0.594,

p < .01). However, the correlation with Social Networking Tools (task-related) was not

significant. Furthermore, team identification was significantly positive correlated with team helping behaviors which is in line with Hypothesis 2. In addition, I was able to find positive correlations between team helping behaviors and the use and perception of Social Networking Tools (not task-related) (r = 0.340, p < .05) as well as Meeting Tools (r = 0.489,

p < .01) which supports my third hypothesis.

Tools (r = .489, p < .01), and Social Networking Tools (not task-related) (r = .347, p < .05). Additionally, Social Networking Tools (not task-related) were positively correlated with Meeting Tools (r = .583, p < .01), and Social Networking Tools (task-related) (r = .337,

p < .05). That means for example, that one unit increase of frequent use and perception of

Social Networking Tools (not task-related) leads to an increase of .583 units of frequent use and perception of Meeting Tools.

Regression Analyses

Table B2 (see Appendix B) represents the results of the regression analysis for team helping behaviors (M1), team identification (M2), and team helping behaviors controlling for team identification (M3). Each model has a sufficient explanation of variance (R²): M1 explains 30 %, M2 explains 61 %, and M3 explains 48 % of the respective variance. The coefficients of the regression presented in the table are standardized in order to allow comparability.

The first hypothesis proposed a positive relationship between the frequent use and perception of CMC-Tools and team identification. Even though, the correlation analysis found that almost all CMC-Tools were positively correlated with team identification, the regression analysis, as indicated in M2 in Table B2, showed that only Meeting Tools (b = 0.363, p < .05) and Social Networking Tools (not task-related) (b = 0.294, p < .1) were significant predictors of team identification. Looking at these results, the first hypothesis can be confirmed for Meeting Tools and Social Networking Tools (not task-related) but not for the other investigated tools.

In the third hypothesis, I expected that frequent use and perception of new CMC-Tools has a positive influence on team helping behaviors. The results of the regression analysis indicated in M1 in Table B2, however, show no significant effect. Therefore, the third hypothesis cannot be confirmed in this study.

Mediation Effect of Team Identification

In Hypothesis 4, I proposed that team identification mediates the relation between use and perception of CMC-Tools and team helping behaviors. Therefore, Table B3 (see Appendix B) presents the mediation effects of team identification. As shown in the table, the indirect effect was highly significant (p < .01) for Document Co-creation Tools (= 0.268), Meeting Tools (= 0.307), and Social Networking Tools (not task-related) (= 0.294). The indirect effect was moderately significant (p < .05) for Document Sharing Tools (= 0.15), and insignificant for Social Networking Tools (not task-related). However, all effects are positive. Furthermore, when the direct effect insignificant or smaller than the indirect effect, it can be assumed that a complete mediation is present (Shrout & Bolger, 2002). The results indicated in Table B3 show that this is the case for all investigated CMC-Tools. Thus, Hypothesis 4 can be confirmed for all CMC-Tools except Social Networking Tools (task-related).

Discussion

behaviors. In order to address this issue, this study aimed to answer the question how frequent use and perception of new emerged CMC-Tools affect team helping behavior and if team identification mediates this relationship in virtual teams. Therefore, I gathered data from members of virtual teams who work in an international student organization which uses a wide range of CMC-Tools. In order to make more specific statements, I classified those CMC-Tools in four categories: Document Sharing Tools, Document Co-creation Tools, Meeting Tools, and Social Networking Tools which were divided in related and not task-related use, and analyzed their influence on team identification and team helping behaviors.

I found that Meeting Tools and Social Networking Tools (not task-related) have a positive effect on team identification which in turn affects team helping behavior positively. Furthermore, I did not find a direct effect of frequent use and perception of CMC-Tools on team helping behaviors. However, I was able to show that team identification was fully mediating this relationship for all categories except Social Networking Tools (task-related). Therefore, I can conclude that an increase in use and perception of CMC-Tools can predict a rise of team helping behaviors because of increased team identification.

Theoretical Implications

Meeting Tools enable video-conferencing and thus, also allow non-verbal communication explains why the results show a positive impact of Meeting Tools on team identification. Holton (2007) stated in her study that face-to-face interaction is an important part of team work and building trust. Meeting Tools simulate such face-to-face interactions and thus have positive influence on team identification as shown in the results. Thus, my study underpins the finding of Lin et al. (2008) that very rich CMC-Tools can help foster the relationships among members in virtual teams. However, I suggest extending Daft and Lengel’s Media Richness Theory by adding new categories that include groups of new emerged CMC-Tools.

The positive effect of Social Networking Tools on team identification can be explained because the examined sample consisted of students and recent graduates who belong to the ‘millennial generation’. They grew up with access to computer and multiple CMC-Tools and thus, have a different attitude towards technology including quicker adaption (Gilson et al., 2015; Gorman, Nelson, & Glassman, 2004). Social Network Tools are mostly used to share current events, pictures, videos, and thoughts which are not necessarily task-related. Nowadays, almost everybody of the millennial generation is having a Smartphone which is carried around every day and allows reachability, and thus social interaction, all the time and almost everywhere. Thus, the team is always “in your pocket” and therefore, you can say always present which seems to be beneficial for team identification in this case. In fact, previous studies showed that spending more time on social interactions leads to better relationships among team members (Johnson et al., 2009). In this study, I was able to show that the influence of those Social Networking Tools should not be underestimated and needs to be considered in further research.

more, how crucial team identification is for team helping behaviors. Even though this influence has been reported in prior studies, this study showed that it also applies for virtual teams. Additionally, I was also able to find a mediation effect of team identification in the relationship between using CMC-Tools and team helping behaviors. Even though, I could not find a direct effect of using CMC-Tools on team helping behaviors, it does not mean that CMC-Tools do not influence team outcomes. Therefore, existing theories are incomplete and I suggest that research should be extended in order to find more processes that are influenced by CMC-Tools.

Practical Implications

(Holton, 2001). Important to note at this point is that CMC-Tools can only have a positive impact when used actively and by all members of the team.

Limitations and Future Directions

It is important to mention a few limitations of this study. First of all, the showed results are based on a rather small sample size which makes it difficult to find significant effects. Studies with a larger sample size might be able to discover significant effects for CMC-Tool use. Since, I analyzed cross-sectional data I did not consider changes that appear over a longer time period such as increases or decreases in team helping behaviors or in team identification. Nevertheless, studies about commitment found that it tends to be stable over time (Workman et al., 2003). Furthermore, I collected single-source data which might not reflect reality properly. Especially, when it comes to rating one self’s team helping behaviors the answer might be influenced by social desirability because people want to “appear more altruistic and society-oriented than they actually are” (Chung & Monroe, 2003: 291).

Another limitation is that I examined individuals working in rather homogenous teams within a student organization which are used to work with CMC-Tools. Therefore, the found results may not be transferable to virtual teams in other working settings. Moreover, prior research found that different degrees of co-location also affect behaviors in virtual teams (Charlier, 2012), which has not been considered in this study. Furthermore, I neither controlled for task characteristics nor whether the tasks demand a certain amount of using CMC-Tools. Future research might focus on tasks characteristics as influence factor on using CMC-Tools, team identification, or team helping behaviors.

effect on team identification and using CMC-Tools. Previous research has proven that face-to-face interactions in the beginning of the team process have a positive influence on group processes such as relationship development, and emotional bonding between team members (Johnson et al., 2009).

Furthermore, there are several more influence factors that might affect using CMC-Tools, team identification, and team helping behaviors that have not been investigated in this study and thus, are indications for future research. For example, what influence do group norms have on these dynamics? Also, it might be of interest to investigate what effect team identification has on the use and perception of CMC-Tools? Another possible direction for future research is to examine how the all-time-approachability influences team processes, and whether the use of Social Networking Tools in a professional environment is advisable. Finally, I investigated teams which had a high degree of virtuality, and thus rely entirely on CMC-Tools. Therefore, it might be interesting for future research to analyze how CMC-Tools contribute or support processes in teams with a lower degree of virtuality.

Conclusion

References

Allen, N., & Meyer, J. (1996). Affective, continuance, and normative commitment to the organization: An examination of construct validity. Journal of Vocational Behavior, 49(3), 252–76. doi:10.1006/jvbe.1996.0043

Ancona, D. G., & Caldwell, D. F. (1992). Demography and design: Predictors of new product team performance. Organization Science, 3(3), 321–341. doi:10.1287/orsc.3.3.321

Bergami, M., & Bagozzi, R. P. (2000). Self-categorization, affective commitment and group self-esteem as distinct aspects of social identity in the organization. The British

Journal of Social Psychology / the British Psychological Society, 39(4), 555–577.

doi:10.1348/014466600164633

Charlier, S. (2012). A multi-level investigation of emergent leadership and dispersion effects in virtual

teams. University of Iowa.

Chatman, J. A., & Barsade, S. G. (1995). Personality, organizational culture, and cooperation: Evidence from a business simulation. Administrative Science Quarterly, 40(3), 423–443. doi:10.2307/2393792

Chung, J., & Monroe, G. (2003). Exploring social desirability bias. Journal of Business Ethics, 291– 302. Retrieved from http://www.jstor.org/stable/25075038

Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571. Retrieved from http://www.jstor.org/ stable/2631846

Ellemers, N., Spears, R., & Doosje, B. (2002). Self and social identity. Annual Review of Psychology,

53, 161–186. doi:10.1146/annurev.psych.53.100901.135228

Geister, S., Konradt, U., & Hertel, G. (2006). Effects of process feedback on motivation, satisfaction, and performance in virtual teams. Small Group Research. doi:10.1177/1046496406292337 Gilson, L. L., Maynard, M. T., Jones Young, N. C., Vartiainen, M., & Hakonen, M. (2015). Virtual

Gorman, P., Nelson, T., & Glassman, A. (2004). The millennial generation: A strategic opportunity.

Organizational Analysis, 12(3).

Griffith, T. L., Sawyer, J. E., & Neale, M. A. (2003). Virtualness and knowledge in teams: Managing the love triangle of organizations, individuals, and information technology. MIS Quarterly,

27(2), 265–287. Retrieved from http://www.jstor.org/stable/30036531

Han, H. J., Hiltz, S. R., Fjermestad, J., & Wang, Y. (2011). Does medium matter? A comparison of initial meeting modes for virtual teams. IEEE Transactions on Professional Communication,

54(4), 376–391. doi:10.1109/TPC.2011.2175759

Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling. Retrieved from http://www.afhayes.com/ public/process2012.pdf

Holton, J. A. (2001). Building trust and collaboration in a virtual team. Team Performance

Management, 7(3/4), 36–47. doi:10.1108/13527590110395621

Johnson, S. K., Bettenhausen, K., & Gibbons, E. (2009). Realities of working in virtual teams: Affective and attitudinal outcomes of using computer-mediated communication. Small Group

Research, 40(6), 623–649. doi:10.1177/1046496409346448

Koutsabasis, P., Vosinakis, S., Malisova, K., & Paparounas, N. (2012). On the value of virtual worlds for collaborative design. Design Studies, 33(4), 357–390. doi:10.1016/j.destud.2011.11.004 Lin, C., Standing, C., & Liu, Y. C. (2008). A model to develop effective virtual teams. Decision

Support Systems, 45(4), 1031–1045. doi:10.1016/j.dss.2008.04.002

Lin, C.-C., & Peng, T.-K. (2010). From organizational citizenship behaviour to team performance: The mediation of group cohesion and collective efficacy. Management and Organization

Review, 6(1), 55–75. doi:10.1111/j.1740-8784.2009.00172.x

Lurey, J. S., & Raisinghani, M. S. (2001). An empirical study of best practices in virtual teams.

Information and Management, 38(8), 523–544. doi:10.1016/S0378-7206(01)00074-X

performance. Organizational Behavior and Human Decision Processes, 50(1), 123–150. doi:10.1016/0749-5978(91)90037-T

Martins, L. L., Gilson, L. L., & Maynard, M. T. (2004). Virtual teams: What do we know and where do we go from here? Journal of Management. doi:10.1016/j.jm.2004.05.002

Maznevski, M. L., & Chudoba, K. M. (2000). Bridging space over time: Global virtual team dynamics and effectiveness. Organization Science, 11(5), 473–492. doi:10.1287/orsc.11.5.473.15200 Organ, D. W. (1988). Organizational citizenship behavior: The good soldier syndrome. Lexington,

MA: Lexington Books.

Organ, D. W., & Ryan, K. (1995). A meta-analytic review of attitudinal and dispositional predictors of organizational citizenship behavior. Personnel Psychology, 48(4), 775–802. doi:10.1111/j.1744-6570.1995.tb01781.x

Podsakoff, N. P., Podsakoff, P. M., MacKenzie, S. B., Maynes, T. D., & Spoelma, T. M. (2014). Consequences of unit-level organizational citizenship behaviors: A review and recommendations for future research. Journal of Organizational Behavior, 35, 87–119. doi:10.1002/job.1911

Podsakoff, N. P., Whiting, S. W., Podsakoff, P. M., & Blume, B. D. (2009). Individual- and organizational-level consequences of organizational citizenship behaviors: A meta-analysis.

The Journal of Applied Psychology, 94(1), 122–141. doi:10.1037/a0013079

Rapp, A., Ahearne, M., Mathieu, J., & Rapp, T. (2010). Managing sales teams in a virtual environment. International Journal of Research in Marketing, 27(3), 213–224. doi:10.1016/j.ijresmar.2010.02.003

Schappe, S. P. (1998). The influence of job satisfaction, organizational commitment, and fairness perceptions on organizational citizenship behavior. The Journal of Psychology, 132(3), 277– 290. doi:10.1080/00223989809599167

Schweitzer, L., & Duxbury, L. (2010). Conceptualizing and measuring the virtuality of teams.

Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental studies: new procedures and recommendations. Psychological Methods, 7(4), 422–445. doi:10.1037/1082-989X.7.4.422

Suh, A., Shin, K., Ahuja, M., & Kim, M. S. (2011). The influence of virtuality on social networks within and across work groups: A multilevel approach. Journal of Management Information

Systems. doi:10.2753/MIS0742-1222280111

Van der Kleij, R., Maarten Schraagen, J., Werkhoven, P., & De Dreu, C. K. W. (2009). How conversations change over time in face-to-face and video-mediated communication. Small

Group Research, 40(4), 355–381. doi:10.1177/1046496409333724

Van der Vegt, G. S. (2005). Effects of perceived skill dissimilarity and task interdependence on helping in work teams. Journal of Management. doi:10.1177/0149206304271382

Van der Vegt, G. S., & Bunderson, J. S. (2005). Identification learning and performance in multidisciplinary teams: The importance of collective team identification, 48(3), 532–547. Retrieved from http://www.jstor.org/stable/20159674

Workman, M., Kahnweiler, W., & Bommer, W. (2003). The effects of cognitive style and media richness on commitment to telework and virtual teams. Journal of Vocational Behavior,

63(2), 199–219. doi:10.1016/S0001-8791(03)00041-1

Appendix A: Conceptual Model

The following conceptual model shows the relations between the different variables as well as the expected correlations that are used in this study:

Figure A1: Conceptual Model showing the proposed relations between the three variables.

The conceptual model below shows the standardized regression coefficients for the relationship between frequent use and perception of CMC-Tools and team helping behaviors mediated by team identification:

Figure A2: Standardized regression coefficients for the relationship between frequent use and perception of CMC-Tools and team helping behaviors mediated by team identification.

Notes: DS = Document Sharing Tools, DC = Document Co-creation Tools, MT = Meeting Tools, ST1 = Social Networking Tools (task-related), ST2 = Social Networking Tools (not task-related); Direct Effects of frequent use and perception of CMC-Tools on team helping behavior in parentheses; † p < .1, * p < .05, ** p < .01

Frequent use and perception of

CMC-Tools

Team Identification

Team Helping Behaviors

Appendix B: Results of Analysis

Means, Standard Deviations, and Correlations

Variable Mean SD 1 2 3 4 5 6 7 8 9 10 11 1. Age 23.72 1.891 1 2. Gender 1.54 .505 -.195 1 3. Team Size 6.26 1.916 -.125 .153 1 4. Tenure 8.51 1.699 .325* -.024 .096 1 5. Team Identification 4.551 1.096 .258 -.016 -.229 -.075 1

6. Team Helping Behaviors 4.910 .744 .154 -.096 -.233 -.155 .633** 1

7. Document Sharing Tools 5.174 .698 .214 -.034 .226 .025 .324* .231 1 8. Document Co-Creation

Tools 5.179 .676 .177 -.044 .069 .032 .497

**

.177 .559** 1

9. Meeting Tools 4.928 .616 .063 .026 -.100 -.185 .664** .430** .213 .489** 1 10. Social Networking Tools

(task-related) 3.672 1.117 .085 -.173 -.127 -.358

*

.176 .271 -.065 -.164 .232 1 11. Social Networking Tools

(not task-related) 5.051 .695 .127 -.051 .033 -.148 .594

**

.340* .294 .347* .583** .337* 1

Notes: Sample Size: n = 39

**

p < .05, two-tailed

**

Table B2

Results of Regression Analysis Team Helping Behaviors (M1) Team Identification (M2) Team Helping Behaviors (M3) Independent Variables b p b p b p (Constant) 1.772 .368 -4.296* .054 3.720* .051 Age .066 .716 .129 .346 -.020 .901 Gender -.035 .830 .060 .624 -.076 .604 Team Size -.217 .205 -.230† .078 -.064 .686 Tenure -.046 .801 .010 .942 -.053 .744 Document Sharing Tools .257 .204 .097 .518 .193 .283 Document Co-Creation Tools -.138 .541 .158 .353 -.244 .233 Meeting Tools .347 .122 .363* .034 .105 .618 Social Networking Tools (task-related) .107 .586 -.001 .995 .107 .535 Social Networking Tools (not task-related) .064 .759 .294† .066 -.133 .494 Team Identification .668** .005 R/R² .553/.306 .781/.610 .693/.480

Notes: Sample Size: n = 39; † p < .1, * p < 0.5, ** p < 0.1

b represents the standardized coefficients with its respective p-values.

Table B3

Mediation Effect of Team Identification

Direct Effects on Team

Helping Behavior

Indirect Effect of Team Identification

Document Sharing Tools .257 .150**

Document Co-Creation Tools -.138 .268**

Meeting Tools .347 .307**

Social Networking Tools (task-related) .107 .079** Social Networking Tools (not task-related) .064 .294**

Appendix C: Survey

Document Sharing Tools

Document sharing tools are online collaboration tools that are designed to allow individuals to upload and collaborate on documents that are stored online. Popular examples include Dropbox, Google Drive, and Sharepoint. Please note that this does not include programs like Google Documents or using email to send attachments of a document to collaborators.

How often do you use document sharing tools for working on your tasks? (1) Never / not applicable

(2) Less than once a month

(3) Once a month (4) Once a week

(5) A few times a week (6) Daily

How useful do you perceive document sharing tools for working on your tasks? (1) not useful at all

(2) mostly useless

(3) somewhat useless (4) somewhat useful

(5) mostly useful (6) very useful

How effective do you perceive document sharing tools in order to fulfill your tasks? (1) Completely ineffective (2) Mostly ineffective (3) Somewhat ineffective (4) Somewhat effective (5) Mostly effective (6) Completely effective

How much do you like using document sharing tools in order to fulfill your tasks? (1) I don’t like it at all

(2) I like it a little.

(3) I like it moderately (4) I like it.

(5) I like it very much. (6) I love it.

How important do you consider document sharing tools in order to fulfil your tasks? (1) Not at all important

(2) A little important

(3) Important, but not necessary

(4) Important enough to be necessary

(5) Very important (6) Extremely important

Document Co-creation tools

Document Co-creation tools are tools that allow you to co-create and co-edit documents or visuals in real-time and at the same time with your team members. Examples are Google Docs and Google Sheets, Prezi or Scribblar.

How effective do you perceive document co-creation tools in order to fulfill your tasks? How much do you like using document co-creation tools in order to fulfill your tasks? How important do you consider document co-creation tools in order to fulfill your tasks?

Meeting Tools

Meeting Tools are tools that help you meet with your team through video and audio conferencing. Examples are Google Hangout, Skype, Join Me.

How often do you use meeting tools for working on your tasks? How useful do you perceive meeting tools for working on your tasks? How effective do you perceive meeting tools in order to fulfill your tasks? How much do you like using meeting tools in order to fulfill your tasks? How important do you consider meeting tools in order to fulfill your tasks?

Social Networking Tools

Social Networking Tools allow you to collaborate and interact with your team members through a social network. Popular examples are Facebook, WhatsApp or Jive.

Do you have a WhatsApp or Facebook Group for your team?

How often do you use this group to communicate with your team colleagues … … formal (task-related)? … informal (not task-related)? How useful do you perceive social networking tools …

… for working on your tasks? … for connecting with your team colleagues? How effective do you perceive social networking tools in order to …

… fulfill your tasks? … connect with your team colleagues? How much do you like using social networking tools in order to …

… fulfill your tasks? … connect with your team colleagues? How important do you consider social networking tools in order to …

Mediator Variable Team Identification

Please indicate how much you agree or disagree with the following statements about your

identification with your team.

 I feel emotionally attached to this team.  I feel a strong sense of belonging to this team.  I feel as if the team’s problems are my own.  I feel like part of the family in this team. (1) Disagree Strongly (2) Disagree (3) Tend to Disagree (4) Tend to Agree (5) Agree (6) Agree Strongly Control Variables

Age: In which year were you born?

Gender: What is your gender? (Choice between female, male)

Team Size: How many people are working in your team?

Tenure: How many months have you been working in this team?

Team: In which team are you working? (Dropdown Menu)

Outcome Variable Team Helping Behavior

Please indicate how much you agree or disagree with the following statements about your

team helping behavior.

 I am always ready to help or to lend a helping hand to those around me.

 I am willing to give of my time to help others who have work related problems.  I help other team members with heavy workloads.