AD ALTA
JOURNAL OF INTERDISCIPLINARY RESEARCH
premium of the signed life insurance contracts and the average
monthly income from insurance intermediation. In order to
evaluate job performance of intermediaries, they were provided
with the margins where they indicated their potential sales
performance: 1 – high sales performance, 4 or 5 – low sales
performance, respectively.
Assessing the correlation relationship between the measure
encompassing the number of life insurance contracts per month
and intermediaries’ selling methods and their possession of the
analysed traits, it has emerged that all assessments of the selling
methods and personality traits are related with the measure of
life insurance contracts per month by positive, of average
strength (~ 0.5) and statistically significant correlation relations
(p < 0.05). This means that the more life insurance
intermediaries are customer-oriented, actively listen to and adapt
to each selling situation, and the higher is their level of
emotional intelligence and self-efficacy in their work, the more
life insurance contracts they conclude.
Table 4. Correlations between the dependent and independent
variables
ANC
AS
CO
AL
SE
EI
r
0,643
*
0,406
*
0,517
*
0,554
*
0,546
*
p
0,000
0,000
0,000
0,000
0,000
APC
r
0,584
*
0,444
*
0,545
*
0,605
*
0,599
*
p
0,000
0,000
0,000
0,000
0,000
AII
r
0,641
*
0,492
*
0,599
*
0,653
*
0,614
*
p
0,000
0,000
0,000
0,000
0,000
*correlation is statistically significant, with the level of statistical
significance at 0.01
The data presented in Table 4 show that the strongest
relationship has been established between the number of life
insurance contracts per month (ANC) and the method of
adaptive selling (r = 0.643, p < 0.05), whereas the weakest
relationship has been recorded between the number of life
insurance contracts per month (ANC) and customer orientation
(r = 0.406, p < 0.05).
It has been also found out that the assessments of the applied
selling methods and the analysed traits are related with the mean
measure of monthly premium of the concluded life insurance
contracts by positive, of average strength (~ 0.5) and statistically
significant correlation relations (p < 0.05). The strength of
interrelations of the analysed measures can be explained by the
fact that the more selling methods (adaptive selling, customer
orientation and active listening) are applied by life insurance
consultants in their work and the more of the analysed traits are
inherent to them (self-efficacy and emotional intelligence), the
higher is the average premium of the signed life insurance
contracts. The strongest relation has been identified between this
measure and self-efficacy (r = 0.605, p < 0.05), whereas the
weakest – between this measure and customer orientation (r =
0.444, p < 0.05).
The third result is very similar – all the assessments of the
analysed selling methods and personality traits of intermediaries
are related with the mean measure of monthly income from life
insurance intermediation by positive, of average strength (~ 0.5)
and statistically significant correlation relations (p < 0.05). The
strongest relation has been identified between the mentioned
measure and the level of self-efficacy (r = 0.653, p < 0.05),
whereas the weakest – between the mentioned measure and
customer orientation (r = 0.492, p < 0.05).
Based on the results from Spearman’s correlation analysis, the
research hypotheses H1-H5 have been accepted as it has been
identified that the more of the above-mentioned methods are
applied and the more of the analysed traits are inherent to
intermediaries, the better is their sales performance.
In order to examine the hypotheses H1-H5 in more detail, it has
been aimed to assess whether the methods of adaptive selling,
customer orientation, active listening applied by the sellers of
life insurance services and their self-efficacy and emotional
intelligence are directly positively related with high sales
performance and how the change in the dependent variables
determines the change in the values of independent variables.
In order to test the hypotheses, three models of multiple
regression have been developed. They help to evaluate the
influence of the selling methods and analysed traits on the
factors of sales performance. The obtained results have revealed
that self-efficacy (b = 0.460, p = 0.002 < 0.05) and adaptive
selling (b = 0.274, p = 0.004 <0.05) has statistically significantly
positive and statistically significant influence on the average
monthly income from insurance intermediation. Whereas,
customer orientation of life insurance intermediaries, the
application of work methods based on active listening and
emotional intelligence, according to this model of regression,
have no statistically significant impact on the average monthly
income from life insurance activities (customer orientation: b =
0.108, p = 0.194 > 0.05; active listening: b = 0.460, p = 0.721 >
0.05, emotional intelligence: b = 0.155, p = 0.292 > 0.05). The
coefficient of determination for the regression model is 0.516,
thus the developed model explains on average 51.6% of the
distribution of sales performance depending on the measures
related to it (Table 5).
Table 5. The influence of the analysed work methods and traits
on sales performance
V
a
ria
b
le
s
T
h
e d
ev
el
o
p
ed
equa
ti
o
n (
p
-
v
a
lue
s i
n
b
ra
ck
et
s)
T
h
e c
o
effi
ci
en
t o
f
d
et
erm
in
a
ti
o
n
(
R
2
(a
d
ju
ste
d
)
P
-v
a
lu
e o
f A
n
o
v
a
R
eg
re
ssi
o
n
AII
AII=0,414+0,274(0,004)*AS
-0,108(0,194)*CO-
0,051(0,721)*AL+0,460(0,00
2)*SE+0,155 (0,292)*EI
0,516
0,000
ANC
ANC=1,954+0,447(0,000)*A
S-0,122(0,194)*CO-
0,190(0,238)*AL+0,285(0,09
2)*SE+0,195 (0,241)*EI
0,380
0,000
APC
APC=1,473+0,132(0,220)*A
S-0,172(0,069)*CO-
0,239(0,138)*AL+0,510(0,00
3)*SE+0,376 (0,027)*EI
0,389
0,000
The average number of life insurance contracts per month is
statistically significantly positively and statistically significantly
influenced by adaptive selling (b = 0.447, p = 0.000 < 0.05),
while the average premium of the signed life insurance contracts
is influenced by self-efficacy (b = 0.510, p = 0.003 < 0.05) and
emotional intelligence (b = 0.376, p = 0.027 < 0.05). Other
dependent variables, according to the developed models of
regression (Table 7), do not have a statistically significant
influence on sales performance. The coefficient of determination
for the second and the third regression model accounts for 0.380
and 0.389, respectively, thus the developed model explains an
average of 38 percent of the distribution of sales performance
depending on the depending on the measures related to it.
Based on the results of three regressions, it can be stated that the
research hypotheses H1–H5 can be partially expanded by
examining the possible causal effect of sales factors on sales
performance. The obtained coefficients of determination are not
suitable for the statistically accurate prognosis of the variation in
the values of variables, but it would be possible to repeat this
research in the future by interviewing a larger number of
respondents.
6 Limitations of Research
Life insurance companies operating in Lithuania provide
services to both natural and legal persons, by offering products
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