Pan-Pacific Conference XXXIV. Designing New Business Models in Developing Economies

TABLE 1: Descriptive statistics, intercorrelations and reliabilities
Variables 1 2 3 4 5 6 7 8 9 10
1. Age (−)
2. Relationship .47** (−)
3. Gender −.21** −.15** (−)
4. Education −.31** −.15** .17** (−)
5. Job level .11* .16** −.05 .28** (−)
6. Tenure .68** .35** −.22** −.38** −.00 (−)
7. Supervision .25** .25** −.27** −.09* .42** .21** (−)
8. Turnover int. −.12** −.08 .01 −.03 −.12** −.02 −.05 (.76)
9. Breach .04 .06 −.01 −.13** −.20** .08 −.07* .50** (.85)
10. Violation .06 −.03 .00 −.17** −.13** .09* −.04 .42** .58** (.90)
Mean 36.27 0.56 0.44 2.70 2.02 7.62 0.54 2.80 2.52 2.04
SD 9.25 0.50 0.50 0.99 1.02 7.77 0.50 0.95 1.05 1.20
Notes: n = 238−560; Cronbach alpha's reported on the diagonal.
Control variables: Gender: 0 = male, 1 = female; Education: 1 = no formal qualification, 2 = upper secondary,
3 = post−secondary non−tertiary, 4 = first stage tertiary; Relationship status: 0 = not in a relationship, 1 = in a relationship; Job
level: 1 = operators, 2 = junior management, 3 = middle management, 4 = senior management; and Supervision responsibilities:
0 = not a supervisor, 1 = is a supervisor. *p < .05, **p < .01.
TABLE 2: Hierarchical regression results for the prediction of turnover intention
All respondents Union members Non-union members
Step 1 Step 2 Step 1 Step 2 Step 1 Step 2
Step 1 (control variables)
Age −.150* −.157** .011 −.043 −.185* −.176**
Relationship −.036 −.061 −.142 −.111 −.010 −.055
Step 2 (independent variables)
Breach .389*** .244** .445**
Violation .211*** .391*** .132*
F 2.315* 25.390*** 1.182 9.303*** 2.019 17.730***
ΔF 102.953*** 35.984*** 69.865***
R 2 .030 .307 .047 .338 .040 .320
ΔR 2 .277 .291 .280
Notes: n = 525 (all respondents), members (n = 174) and non−members (n = 349) of a union after listwise deletion. Standardized
β-coefficients are reported. *p < .05, **p < .01, ***p < .001.
TABLE 3: Differences in the contribution of the independent variables in the two models
Union members Non-union members
Variables
B SE B B SE B SE B-diff Z p
Control variables
Age −.004 .010 −.020 .007 .012 −1.974 .024*
Relationship −.207 .138 −.105 .101 .171 −1.824 .034*
Independent variables
Breach .211 .068 .413 .055 .087 7.170 .000**
Violation .258 .052 .122 .055 .075 5.060 .000**
Note: Unstandardized B-coefficients are reported; SE B = Std. error of unstandardized B-coefficient. Only significant control
variables are reported.
2 2
SE B−diff = √SE Bg1 + SE Bg2 [23], [24]; Z =
*p < .05; **p < .001
Limitations. Union instrumentality or commitment
were not investigated. This limit our understanding to
explain the strength of violation as a predictor of
turnover intention among union members (and nonunion
members). Violation as a moderator was not
examined.
Suggestions for future research. Future
investigations could consider union instrumentality
and union commitment to advance our understanding
how the influence of unions impact breach and
violation and how turnover intention is predicted in
such a model.
Conclusion. This study examined the effect of union
membership on turnover intention following
psychological contract breach and violation. This
Bg1−Bg2
2 2
√SE Bg1 +SE Bg2
14
[23], [24].
study evidenced that although the R 2 may not be
significant between the union and non-union
membership models, the internal structure may reveal
significant differences between the internal
regressions.
REFERENCES
References are available upon request.
Acknowledgement. The dataset used in this study is
based on a larger dataset, with the data collected by
students in 2016, for a postgraduate course in
research.