Research Questions 3 addresses the relationship of team learning activities with TMM-TM (Research Question 3: How are team learning activities related to TMM-TM?). Research Question 4 addresses the relationship of TMM-TM with team performance (Research Question 4: How is TMM-TM related to team performance?). The two research questions are investigated together in one analysis as TMM-TM is central in both research questions. Variables included in the investigation of Research Questions 3 and 4 are displayed in Table 16. The sample of n3 = 304 members of N3 = 63 teams was available for calculations with
respect to Research Question 3. Calculations with respect to Research Question 4 are based on N4 = 54 teams, whereas N4 is a subsample of N3 consisting of those teams for which team
supervisor ratings were available (see 4.1.).
Table 16
Variables Included in the Investigation of Research Questions 3 and 4
Variable name Variable type
Team size CV
Teamwork time CV
Knowledge sharing IV – team learning activity; Research Question 3 Task reflection IV – team learning activity; Research Question 3 Basic reflection IV – team learning activity; Research Question 3 Team process reflection IV – team learning activity; Research Question 3 Storage and retrieval IV – team learning activity; Research Question 3 TMM-OC DV – Research Question 3; IV – Research Question 4 TMM-SC DV – Research Question 3; IV – Research Question 4 TMM-MC DV – Research Question 3; IV – Research Question 4 TMM-PC DV – Research Question 3; IV – Research Question 4 Effectiveness DV – team performance; Research Question 4 Efficiency DV – team performance; Research Question 4 Innovativeness DV – team performance; Research Question 4
4.5. Research Questions 3 and 4: Team performance, TMM-TM, and team 90 learning activities
4.5.1. Analyses
All measured variables are theoretically meaningful at the team-level. TMM-TM and team performance were directly measured at the team-level, with one measurement per team for each variable. Team learning activities and control variables were measured at the individual level. One way to deal with this kind of data is to aggregate the information gathered from individuals to the team-level by calculating the team mean. However, this kind of data aggregation ignores the measurement precision within each team, which depends on team size and the degree of similarity of ratings within a team (Heck & Thomas, 2009). Therefore, a multilevel modelling approach was applied taking into account within-group measurement precision by decomposing manifest variables measured at the individual level into two uncorrelated latent variables separately representing variance of manifest variables at individual and team-level (Muthén & Muthén, 2010). Hypotheses were tested using path modelling at the team-level based on unbiased estimates of the between-teams covariance matrix. No modelling was conducted at the individual level, as independent and dependent variables are theoretically meaningful at the team-level and dependent variables, as measured at the team-level, have no variance at the individual level.
A requirement for performing data analysis at the team-level based on data gathered from individuals is the presence of considerable variance at the team-level (Bliese, 2000). This requirement was tested through evaluation of the intraclass correlation coefficient ICC(1), which indicates the proportion of a variables’ variance that lies between groups (Heck & Thomas, 2009). ICC(1) values ranged from .14 to .76 (see Table 17), confirming that modeling at the team-level is justified (Heck & Thomas, 2009).
Twolevel path modeling at the team-level applying robust maximum likelihood estimates was performed using the Mplus 6 software package (Muthén & Muthén, 2010). To avoid multicollinearity, four separate models were formulated with respect to the investigated team learning activities, as these were highly correlated (see Table 17). Knowledge sharing was included in Path Model 2. Task reflection and storage and retrieval were entered together in Path Model 3, as these two variables were least correlated among team learning activities (r = .10, p > .05). Paths coefficients between storage and retrieval and TMM-TM variables were fixed to zero as no relations were expected. An alternative model was tested in which these parameters were freed. Basic reflection was included in Path Model 4. The path coefficient between basic reflection and TMM-OC was fixed to zero as no relation was expected. An alternative model was tested in which this parameter was freed. Team process reflection was entered in Path Model 5. Team performance variables, TMM variables, and control variables
4.5. Research Questions 3 and 4: Team performance, TMM-TM, and team 91 learning activities
were held constant throughout the four models. The path coefficient between TMM-SC and team innovativeness was fixed to zero as no relation was expected. An alternative model was tested, in which this parameter was freed. Covariance between residuals of the dependent variables of team performance was accepted in the model. This is reasonable as past research has shown different dimensions of team performance to be closely related (e.g. Bateman, Wilson, & Bingham, 2002; Cacioppe & Stace, 2009; Van Woerkom & Croon, 2009). Acceptable model fit was considered to be given if the chi-square Test was not significant and alternative fit indices met the indicated criteria (see 4.2.1.). Model fit was acceptable for all four models (Path Model 2: χ2 = 16.35, df = 16, p = .43; CFI = 1.00; TLI = 0.99; SRMR (between) = 0.080; RMSEA = 0.009; Path Model 3: χ2 = 17.00, df = 23, p = .81; CFI = 1.00; TLI = 1.16; SRMR (between) = 0.062; RMSEA = 0.000; Path Model 4: χ2 = 16.51, df = 17, p = .49; CFI = 1.00; TLI = 1.02; SRMR (between) = 0.075; RMSEA = 0.000; Path Model 5: χ2 = 10.00, df = 16, p = .87; CFI = 1.00; TLI = 1.20; SRMR (between) = 0.060; RMSEA = 0.000).
4.5.2. Results
Means, standard deviations, ICC (1) values and team-level correlations with respect to the variables included in the investigation of Research Questions 3 and 4 are shown in Table 17. Path Models 2-5 are depicted in Figures 10-13. Standardized model estimates for Path Models 2-5 are displayed in Table 18. Path coefficients between TMM and team performance variables are identical by two decimal places throughout Path Models 2-5. Therefore, separate modelling results are only reported with respect to the relations between TMM-TM variables and their predictors.
In support for Hypothesis 18, Path Model 2 showed significant positive relations between knowledge sharing and TMM-SC (β = .51, p < .01), TMM-MC (β = .42, p < .01), and TMM-PC (β = .45, p < .05). However, no significant relation between knowledge sharing and TMM-OC was found. Thus, partial support is given with respect to Hypothesis 18. The hypothesis is supported with respect to TMM-SC, TMM-MC, and TMM-PC, but not supported with respect to TMM-OC.
Likewise, partial support is given with respect to Hypothesis 19. In support for the hypothesis, Path Model 3 showed significant positive relations between task reflection and TMM-SC (β = .43, p < .01), TMM-MC (β = .29, p < .05), and TMM-PC (β = .55, p < .01). Concerning TMM-OC, no significant relation was found. Thus, Hypothesis 19 is supported with respect to TMM-SC, TMM-MC, and TMM-PC, but not supported with respect to TMM-
4.5. Research Questions 3 and 4: Team performance, TMM-TM, and team 92 learning activities
OC. Storage and retrieval was also included in Path Model 3, whereas path coefficients between storage and retrieval and TMM-TM variables were fixed to zero as no relations were expected. To validate this assumption, an alternative model freely estimating these paths was tested (Path Model 3.1, see Appendix A.6.). No significant paths between storage and retrieval and TMM-TM were found. Furthermore, chi-square difference testing showed no significant improve in model fit for the alternative model (χ2diff = 4.40, df = 4, p > .05).
Hypothesis 20 is also partially supported by the data. In Path Model 4, basic reflection was found to be significantly positively related to TMM-SC (β = .50, p < .01) and TMM-PC (β = .69, p < .01). However, no significant relation was found with respect to TMM-MC. Thus, Hypothesis 20 is supported with respect to TMM-SC and TMM-PC, but not supported with respect to TMM-MC. The path coefficient between basic reflection and TMM- OC was fixed to zero since no relation was expected. To validate this assumption, Path Model 4 was compared to an alternative model freely estimating this path (Path Model 4.1, see Appendix A.6.). No significant path between basic reflection and TMM-OC was found in the alternative model. Moreover, chi-square difference testing showed no significant improve in model fit for the alternative model (χ2diff = 0.61, df = 1, p > .05).
Partial support is also given with respect to Hypothesis 21. In support for the hypothesis, significant positive relations between team process reflection and TMM-SC (β = .54, p < .01), TMM-MC (β = .35, p < .05), and TMM-PC (β = .52, p < .01) were found in Path Model 5. However, no significant relation between team process reflection and TMM-OC was found. Thus, like Hypotheses 18 and 19, Hypothesis 21 is supported with respect to TMM- SC, TMM-MC, and TMM-PC, but not supported with respect to TMM-OC.
Hypotheses 22 to 25 state positive relations between TMM-TM variables and team performance variables. Hypotheses 22 and 23 were not supported since no significant relations were found between TMM-OC and team performance variables as well as between TMM-SC and team performance variables. The path coefficient between TMM-SC and team innovativeness was fixed to zero since no relation was expected. To validate this assumption, Path Model 2 was compared to an alternative model freely estimating this path (Path Model 2.1, see Appendix A.6.). No significant path between TMM-SC and team innovativeness was found in the alternative model. Moreover, chi-square difference testing showed no significant improve in model fit for the alternative model (χ2diff = 0.12, df = 1, p > .05).
In contrast to Hypotheses 22 and 23, Hypothesis 24 was fully supported by the data. TMM- MC was significantly positively related to team effectiveness (β = .32, p < .01), team efficiency (β = .37, p < .01), and team innovativeness (β = .30, p < .05). Partial support was
4.5. Research Questions 3 and 4: Team performance, TMM-TM, and team 93 learning activities
found with respect to Hypothesis 25. TMM-PC was significantly positively related to team innovativeness (β = .21, p < .05), but not related to team effectiveness and efficiency. Hence, Hypothesis 25 is supported with respect to team innovativeness, but not supported with respect to team effectiveness and efficiency.
With respect to the investigated control variables, two constant results were found throughout Path Models 2-5. (1) Team size significantly positively predicted TMM-SC (Path Model 2: β = .46, p < .01; Path Model 3: β = .38, p < .05; Path Model 4: β = .35, p < .05; Path Model 5: β = .31, p < .05). (2) Teamwork time significantly positively predicted TMM-OC (Path Model 2: β = .32, p < .01; Path Model 3: β = .33, p < .01; Path Model 4: β = .34, p < .01; Path Model 5: β = .42, p < .01). Moreover, teamwork time was the only significant predictor of TMM-OC. Other results concerning control variables differed to some extent between the path models. A significant negative path between teamwork time and TMM-SC was found in Path Models 4 (β = -.24, p < .05) and 5 (β = -.22, p < .05). A significant positive path between team size and TMM-PC was found in Path Model 3 (β = .29, p < .05). Path Model 2 showed a significant positive relation between teamwork time and TMM-MC (β = .19, p < .05).
4.5. Research Questions 3 and 4: Team performance, TMM-TM, and team learning activities 94
Table 17
Descriptive Statistics, ICC(1) Values, and Between Teams Correlation Matrix (Research Questions 3 and 4)
Variable M SD ICC(1) 1 2 3 4 5 6 7 8 9 10 11 12 13 1. Team size 5.70 2.19 .76 2. Teamwork time 24.16 13.52 .50 -.16 3. Knowledge sharing 4.34 .25 .22 -.48** .06 4. Task reflection 4.24 .31 .24 -.42** .07 .86** 5. Basic reflection 3.84 .27 .14 -.30* .37** .26* .41**
6. Team process reflection 3.10 .36 .18 -.30* .36** .66** .67** .65**
7. Storage and retrieval 3.97 .49 .38 .03 .46** .12 .10 .40** .39** 8. TMM-OC .46 .35 -- -.01 .32* -.18 -.08 .33** -.03 .27* 9. TMM-SC 1.17 .50 -- .21 -.08 .26* .18 .18 .30* -.19 -.11 10. TMM-MC .50 .41 -- .00 .16 .39** .25* .24 .43** .24 .07 .14 11. TMM-PC .54 .35 -- .06 .04 .24 .36** .40** .35** .13 -.22 .31* .07 12. Effectiveness1 4.32 .48 -- -.01 .03 .44** .25 .20 .33* -.04 -.09 .22 .32* .10 13. Efficiency1 3.78 .59 -- -.06 .01 .43** .17 .19 .32* .04 -.14 .05 .35** .02 .73** 14. Innovativeness1 3.59 .70 -- .19 .17 .05 .14 .12 .39** .16 .07 .11 .34* .20 .49** .30* Note. N3 = 63 teams. 1 N 4 = 54 teams. * p > .05, ** p > .01, two-tailed.
4.5. Research Questions 3 and 4: Team performance, TMM-TM, and team 95 learning activities
Table 18
Model Estimates of the Between Teams Path Models 2-5
TMM- OC TMM- SC TMM- MC TMM- PC TMM- OC TMM- SC TMM- MC TMM- PC
Predictors Path Model 2 Path Model 3
Team size -.09 .46** .24 .29 -.04 .38* .15 .29* Teamwork time .32** -.01 .19* .06 .33** -.06 .19 .05 Knowledge sharing -.26 .51** .42** .45* Task reflection -.20 .43** .29* .55**
Path Model 4 Path Model 5
Team size .03 .35* .10 .27 -.01 .31* .10 .18 Teamwork time .34** -.24* .08 -.23 .42** -.22* .06 -.14 Basic reflection -- .50** .23 .69** Team process reflection -.25 .54** .35* .52**
Team performance, Path Models 2-5
Predictors Effectiveness Efficiency Innovativeness
TMM-OC -.10 -.18 .07
TMM-SC .13 -.04 --
TMM-MC .32** .37** .30*
TMM-PC -.01 -.05 .21*
Note. Model estimates between predictors and TMM-TM variables are based on N3 = 63teams, model estimates between predictors and team performance variables are based on N4 = 54 teams.Standardized path coefficients are reported. Model fit Path Model 2: χ2 = 16.35, df = 16, p = .43; CFI = 1.00; TLI = 0.99; SRMR (between) = 0.080; RMSEA = 0.009; Path Model 3: χ2 = 17.00, df = 23, p = .81; CFI = 1.00; TLI = 1.16; SRMR (between) = 0.062; RMSEA = 0.000; Path Model 4: χ2 = 16.51, df = 17, p = .49; CFI = 1.00; TLI = 1.02; SRMR (between) = 0.075; RMSEA = 0.000; Path Model 5: χ2 = 10.00, df = 16, p = .87; CFI = 1.00; TLI = 1.20; SRMR (between) = 0.060; RMSEA = 0.000.
4.5. Research Questions 3 and 4: Team performance, TMM-TM, and team 96 learning activities
Figure 10. Path Model 2: Team-level path model of the relations between team performance variables, TMM-TM variables, knowledge sharing, and control variables. Normal arrow path, p < .05; dashed arrow path, p = not significant (p > .05). Only significant standardized path coefficients are reported.
Figure 11. Path Model 3: Team-level path model of the relations between team performance variables, TMM-TM variables, task reflection, storage and retrieval, and control variables. Path coefficients between storage and retrieval and TMM-TM variables are fixed to zero. Normal arrow path, p < .05; dashed arrow path, p = not significant (p > .05). Only significant standardized path coefficients are reported.
4.5. Research Questions 3 and 4: Team performance, TMM-TM, and team 97 learning activities
Figure 12. Path Model 4: Team-level path model of the relations between team performance variables, TMM-TM variables, basic reflection, and control variables. Normal arrow path, p < .05; dashed arrow path, p = not significant (p > .05). Only significant standardized path coefficients are reported.
Figure 13. Path Model 5: Team-level path model of the relations between team performance variables, TMM-TM variables, team process reflection, and control variables. Normal arrow path, p < .05; dashed arrow path, p = not significant (p > .05). Only significant standardized path coefficients are reported.
4.5. Research Questions 3 and 4: Team performance, TMM-TM, and team 98 learning activities
4.5.3. Additional analyses – Testing for mediation
In addition to testing the formulated hypotheses, it was analyzed whether TMM-TM mediates between team learning activities and team performance. Indirect effects testing for mediation were estimated if, (1) a significant path was found between a team learning activity and a TMM-TM variable and (2) the TMM-TM variable significantly predicted a team performance variable (see Hayes, 2013). With respect to Path Model 2, support for a mediation effect of TMM-MC between knowledge sharing and effectiveness (β = .14, p < .05) as well as between knowledge sharing and efficiency (β = .16, p < .05) was found. Specific indirect effects between knowledge sharing and innovativeness through TMM-MC (β = .13, p = .06) and TMM-PC (β = .09, p = .09) were not significant. However, the sum of these indirect effects was significant (β = .22, p < .01), indicating that, taken together, TMM-MC and TMM-PC mediate between knowledge sharing and innovativeness.
Testing indirect effects with respect to Path Model 3, it was found that TMM-MC mediates between task reflection and efficiency (β = .11, p < .05) and that TMM-PC mediates between task reflection and innovativeness (β = .12, p < .05). The indirect effects of task reflection through TMM-MC on effectiveness (β = .09, p = .07) and innovativeness (β = .09, p = .14) were not significant. However, the sum of indirect effects of task reflection on innovativeness through TMM-MC and TMM-PC was significant (β = .20, p < .05), indicating that, taken together, TMM-MC and TMM-PC mediate between task reflection and innovativeness.
In Path Model 4, a significant indirect effect of basic reflection through TMM-PC on team innovativeness was found (β = .15, p < .05), indicating that TMM-PC mediates between basic reflection and team innovativeness.
With respect to Path Model 5, support for a mediation effect of TMM-MC between team process reflection and efficiency was found (β = .13, p < .05). The indirect effect of team process reflection through TMM-MC on effectiveness was not significant (β = .11, p = .06). Specific indirect effects between team process reflection and innovativeness through TMM-MC (β = .10, p = .16) and TMM-PC (β = .11, p = .10) were also not significant. However, the sum of these indirect effects was significant (β = .21, p < .05), indicating that, taken together, TMM-MC and TMM-PC mediate between team process reflection and team innovativeness.