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

Violation, conceptually different to breach [8], is an
“emotional and affective state that may … follow
from the belief that one’s organization has failed to
adequately maintain the psychological contract” [8,
p. 230]. Breach, a rational and mental
calculation [8], has a positive linear relationship to
feelings of violation evidenced in a meta-analysis
(r = .52) [4], as well as a segmented relationship [1].
The average observed effect size of violation
predicted by breach examined with global measures
of breach was significantly larger (r̅ = .47)
compared to the composite measure (r̅ = .38) [4].
Intention to quit is a common response to a negative
event [18]; thus, a negative event (breach), may
increase an individual’s intent to leave. Breach has a
positive linear relationship to turnover intention
(r = .42) [4]. The average observed effect size using
a global measure of breach (r̅ = .37) predicting
turnover intention was not significantly different
compared to the composite measure (r̅ = .31) [4]. A
moderate relationship between breach and intention
to quit (r̅ = .33), inclusive of both approaches in
measuring breach, have also been reported [19]. A
linear segmented positive relationship was also
found between breach (using a composite measure)
and turnover intention [1].
The following relationships, differently
operationalized to Rigotti’s (2009) [1] study, are
proposed:
H1: Breach assessed with a global measure has a
nonlinear relationship to (a) turnover intention, (b)
violation, and (c) team altruism.
H2: More variance is explained by threshold models
in (a) turnover intention, (b) violation, and (c) team
altruism compared curvilinear models.
RESEARCH DESIGN
Approach. A cross-sectional design with an online
questionnaire was followed.
Sampling and participants. The convenience
sample consisted of 549 employees; the mean age
was 36.3 years (SD = 9.34), tenure 7.61 years
(SD = 7.85), and work experience 12.8 years
(SD = 9.1). The sample consisted predominantly of
males (56.5%), low-skilled workers (41.0%), and
employees with upper secondary education levels
(31.5%).
Measuring instruments. Breach and violation were
measured with Robinson and Morrison’s [20]
scales. Turnover intention was measured using
Roodt’s [21], [22] scale. Team altruism was
measured with Van Wyk’s [23] scale with items
rephrased to assess individuals’ altruistic behavior.
Five-point Likert response scales were used for all
items. Intercorrelations and reliabilities are reported
in Table 1.
TABLE 1: Intercorrelations and Cronbach’s alphas
1 2 3 4
1. Breach (.92)
2. Team −.43* (.95)
altruism
3. Turnover
int.
.44* −.29
*
(.76)
22
4. Violation .47* −.26 .40* (.90)
*
M 2.61 3.75 2.74 2.01
SD 1.17 0.78 1.01 1.19
n = 548–549. *p < .001. Reliabilities on the
diagonal.
The correlations between breach and violation
(r = .47, p < .001) and turnover intention (r = .44,
p < .001) were similar to previous studies, ranging
between r = .52 [4] and r = .54 [1] for violation, as
well as r = .33 [19] and r = .42 [4] for turnover
intention.
Analyses. A CFA revealed an acceptable fit to the
data (Satorra-Bentler χ 2 (370) = 822.018, CFI = .950,
SRMR = .052, RMSEA = .047, and RMSEA 90%
CI: .043–.051; robust values are reported).
Hierarchical regressions, with breach centered
(mean) [1], [7], were used for linear- (Step 1) and
quadratic models (Step 2). Initial parameters of the
threshold models 2 were obtained from Step 1 of the
hierarchical regressions; bb1 was set at −1.
SPSS 23’s nonlinear regression function was used
to estimate optimal parameter values and regression
statistics [24]. Control variables were excluded
similar to [1]. R 2 s were compared with partial F-
tests.
RESULTS
Regression results (Table 2) evidenced that breach
explained 18% (team altruism), 19% (turnover
intention) and 22% (violation) variance in linear
models (Step 1). All curvilinear relationships (Step
2), with small explained variances (between 0.2% and
0.4%), were insignificant, thus not explaining an
improved fit to the data. Hypotheses 1 a-c are rejected.
Parameter values and segmented regression results
are reported in Table 3. The inclusion of a knot
(threshold) for all variables led to an improved fit
(i.e., increased R 2 ) to the data. The effect of breach on
turnover intention is intriguing. Rigotti [1] and this
study evidenced a positive relationship. However, in
this study, a decrease in intensity in turnover intention
(bb1 = −.196) followed after the threshold
(knot = 2.684), compared to Rigotti’s [1] study where
an increase in intensity (bb1 = .68) was observed
following the threshold (knot = 2.84). The effects of
breach on violation in these studies followed a similar
pattern, except for an earlier threshold (knot = 1.917)
revealed in this study.
A comparison between linear and threshold models
revealed an increase in explained variance (R 2 ) team
altruism (18.2% to 18.7%), turnover intention (19.4%
to 19.8%) and violation (21.6% to 22.5%); Rigotti
(2009) [1] also reported more explained variance (R 2 )
in turnover intention (8% to 11%) and violation (24%
to 36%).
A comparison of the explained variance between
discontinuous linear and threshold models are
2 Model specified:
ba0 + ba1*breach + bb1*(breach−knot1)*(breach ≥ knot1)