Page 60 - Azerbaijan State University of Economics

THE JOURNAL OF ECONOMIC SCIENCES: THEORY AND PRACTICE, V.82, # 1, 2025, pp. 52-69

1.3. The equaton for future hope variable:
= + + +

32
31

3
1.4. The equaton for dependent (Life satisfaction) variable:

`
= + + + +

1

3

2
Where:
• a1, a2, a3 – coefficients showing the effect of job insecurity on mediation
variables
• d21, d31, d32 – mediation coefficients shows the relationship between variables
• b1, b2, b3 – shows the effect of mediation variables on life satisfaction
`
• c - shows a direct impact of job insecurity on life satisfaction
• e – are the residuals of equations.
In the equation, the coefficient c shows the direct effect of job insecurity on life
satisfaction. In this model, there are several ways to describe the relationship of the
explanatory variable to the dependent variable.
1. Job insecurity → Goal growth → Life satisfaction, Indirect1 = a1*b1
2. Job insecurity → Social impact → Life satisfaction, Indirect2 = a2*b2
3. Job insecurity → Future hope → Life satisfaction, Indirect3 = a3*b3
4. Job insecurity → Goal growth → Social impact → Life satisfaction, Indirect4
= a1*d21*b2
5. Job insecurity → Goal growth → Future hope → Life satisfaction, Indirect5
= a1*d31*b3
6. Job insecurity → Social impact → Future hope → Life satisfaction, Indirect6
= a2*d32*b3
7. Job insecurity → Goal growth → Social impact → Future hope → Life
satisfaction, Indirect7 = a1*d21*d32*b3
2. Total Indirect effect
7
= ∑ (1)

=1
3. Total effect:
7
`
= = + ∑ (2)

=1
RESULTS AND DUSCUSSİON
Results: This study employed Hayes’ PROCESS Macro Model 6 to examine the direct and
indirect effects of job insecurity on life satisfaction among unemployed individuals in
Azerbaijan. Two versions of the model were constructed: (1) treating job insecurity (JS) as
a categorical variable, and (2) treating it as a discrete variable to assess its impact using
continuous scoring.

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