Predictors of Time 2 Behaviour

A hierarchical regression was conducted with Time 2 behaviour as the dependent variable. For exploratory purposes, all TPB variables (intentions, PBC, attitude and subjective norm) were entered followed by the non-TPB variables significantly correlated with Time 2 behaviour (past behaviour, LSE, neuroticism, employee level and union membership).

40 The approach was in accordance with Baron and Kenny (1986) and was the same as that adopted by Rhodes et al. (2005) in their investigation into the moderating role o f personality within the TPB.

Intentions and PBC were entered at step 1 and together explained a non-significant 3.3% of the variance in Time 2 behaviour (F change 2,58 = 0.98, p = 0.38). Intentions

and PBC explained independently 3% and 1.9% of the variance in Time 2 behaviour, respectively41. Neither variable had a significant beta weight at this step. Subjective norm and attitude were added at step 2 and explained a non-significant 2.8% of the variance in Time 2 behaviour (F change i ,56 = 0.83, p = 0.44). No variables had

significant beta weights at this step. Past behaviour, LSE, neuroticism, employee level and union membership were entered at step 3 and explained a significant 31.4% of the variance in Time 2 behaviour (F change 5,51 = 5.11,/? = 0.001). In descending order, employee level (fi = 0.35 , p < 0.05) and neuroticism (fi = -0.27, p < 0.05) were significant independent predictors of Time 2 behaviour and explained respectively 20.8% (F change 1, 55 = 15.68, p < 0.001) and 6.3% (F change 1, 54 = 5.09, p < 0.05) of the

variance in Time 2 behaviour. The findings suggest that managers and employees scoring lower on neuroticism were significantly more likely to engage in LBs at Time 2 than non-managers and employees scoring higher on neuroticism (see Table 5.6)42. The influence of employee level and neuroticism on Time 2 behaviour was independent of the TPB variables.

The validity of the model was analysed. None of the cases had a Cook’s distance greater than 1 or a leverage value greater than three times the average leverage value, suggesting that none of the cases were exerting excessive influence over the model (Cook & Weisberg, 1982; Stevens, 1992). Mahalanobis distances were examined and all were acceptable (Barnett & Lewis, 1978). Nearly all (97.2%) cases had standardised residuals between -2 and +2 and 99.2% had standardised residuals between -2.5 and +2.5. These percentages meet Field’s (2000) recommendations and

^ ‘Independently’ in this context means entering each predictor on its own, without controlling for the other one.

42 To acknowledge the approach adopted by authors such as Norman and Conner (2006), a hierarchical regression was conducted with the non-TPB variables entered before the TPB variables. Past behaviour, LSE, neuroticism, employee level and union membership were entered at step 1 and explained a statistically significant 33.8% o f the variance in Time 2 behaviour (Fchange 5,55 = 5.61 , p < 0.001). Employee level (fi = 0.32, p < 0.05) and neuroticism (fi = -0.29, p < 0.05) were significant predictors o f behaviour. Subjective norm and attitude were entered at step 2 and explained a non­ significant 3.3% of the variance in Time 2 behaviour (Fchange 2 ,53 = 1.38,/? = 0.26). Employee level (fi = 0.36, p < 0.05) Mid neuroticism (fi = -0.28, p < 0.05) remained significant at this step. Intentions and PBC were entered at step 3 and explained a non-significant 0.4% o f the variance in behaviour (F

change 2 ,51 = 0.15, p = 0.86). Employee level (fi = 0.35, p < 0.05) and neuroticism (fi = -0.27, p < 0.05) remained significant at this step. The beta weights for the variables at the final step were the same irrespective o f the order in which the variables were entered.

suggest that the model represents a reasonable fit to the sample data. The Durbin Watson statistic (2.02) was close to 2, suggesting that errors of prediction were independent of each other (Field, 2000). The presence of multicollinearity between independent variables was assessed. None of the VIFs was greater than 10 and the tolerance statistics were all well above 0.2, suggesting the absence of concerning levels of multicollinearity (Menard, 1995; Myers, 1990). The calculated value of adjusted R2 (0.264) and the observed value of R2 (0.374) suggests that if the model were generated from the population rather than the sample, it would explain approximately 11% less of the variance in behaviour. The cross validity of the model is therefore quite poor.

Table 5.6: Regression Analysis of Predictors of Time 2 Behaviour

Step Predictor R2 A R2 F _fi Step 1 fi Step 2 fi Step 3 1 Intentions 0.03 0.03 0.98 0.14 0.17 0.08 PBC 0.06 0.05 0.00 2 Attitude 0.06 0.03 0.90 -0.17 -0.23 Subjective norm 0.12 0.03 3 Past behaviour 0.37 0.31 3.39 0.18 LSE 0.10 Neuroticism -0.27* Employee level 0.35* Union membership 0.01 * p < 0.05

The accuracy of a regression model decreases as the number of independent variables entered increases (Field, 2000). The sample size here was moderately small for the number of independent variables. The regression was repeated entering LSE, past behaviour and union membership individually at step 3 (i.e., in three separate regressions). LSE was entered at step 3 and explained a statistically significant 9.2% of the variance in Time 2 behaviour (F change i, 55 = 5.96, p < 0.05) and was the only

variable with a significant beta weight at this final step (ft = 0.33, p < 0.05). This \

suggests that the higher an employee’s LSE, the more likely they are to engage in LBs at Time 2 and that LSE has a direct effect on Time 2 behaviour independent of the TPB variables.

Conner and Armitage (1998) suggest that more research is needed that examines whether past behaviour has a direct independent effect on behaviour after taking account of the TPB variables. The regression was repeated with only past behaviour entered at step 3. Past behaviour explained a significant 12.2% of the variance in Time 2 behaviour at step 3 (F change i, 55 = 8.23, p < 0.01) and was the only variable with a significant beta weight at this final step (ft = 0.37,/? < 0.01). This suggests that the more employees had engaged in LBs in the past, the more likely they were to engage in LBs at Time 2, and that past behaviour has a direct effect on Time 2 behaviour independent of the TPB variables.

Entering only union membership at step 3 confirmed that it explained a significant 10.1% of the variance in Time 2 behaviour (F change 1,55= 6.59,/? < 0.05) and was the only variable with a significant beta weight at this final step (ft = -0.33, p < 0.05). This suggests that union members were less likely to engage in LBs at Time 2 than non-union members, and that union membership has a direct effect on Time 2 behaviour independent of the TPB variables.