The Moderating Effect on Perceived Available Job Alternatives on the Relationship

In this paragraph, PAJA is discussed as part of the total conceptual model. Before elaborating on the observed moderating effects of PAJA it is important to first highlight the positive relation between PAJA and TI.

As mentioned earlier this relationship was not hypothesized because of mixed findings in earlier studies and also because of the lesser research relevance from a practical and theoretical point of view. The non-direct, but intervening effect of this variable was deemed more interesting by the researcher. This line of thought is supported by Hulin et al. (1985) who recommend a more marginal role for this variable. “Salaried” employees’ reported data show a positive relationship between PAJA and TI. The strength of this relationship is moderate; but this relationship is in line with findings of Mobley (1977). Based on his theory the concept of alternatives is part of the various sequential steps before having intentions to quit. As mentioned earlier, most “salaried” employees reported having perceptions of available job alternatives. As most “salaried” employees reported slight agreement in having turnover intentions, the researcher can only conclude that these employees have a specific labor market strategy. This is in line with the search theory (Morrell et al., 2001) and concurs with the assertion of Negrin et al. (2004) whereby it is concluded that searching for and having external opportunities, increases the employees’ bargaining power when trying to achieve market conformity in terms of wages and rewards. As dissatisfaction with pay was reported by the respondents, it can be concluded that in these times of crisis while operating in “crisis-survival” mode, “salaried” employees strategically start contemplating available job alternatives. Based on the regression test it is validated that JS together with PAJA are responsible for explaining 38.7% of the variation in TI.

As the positive PAJA to TI relationship is not the most relevant matter in the scope of this research, it is more important to look at the moderating effect of PAJA. Based on the reported data there is a significant moderating effect on the JS to TI relationship.

Levels of perceptions about available job alternatives do have effect on how “salaried” employees’ job satisfaction levels relate to their turnover intention. This finding complies with findings of earlier similar studies from Price (1977); Hulin (1985) and Wheeler (2007). These researchers argued for an intervening effect; a non-direct relation and a moderating effect of PAJA, when looking at the JS to TI relationship.

The findings do not concur with the findings of Kankanamge (2010) who found an insignificant moderating effect. Kankanamge argued that employees’ lack of knowledge about the labor market yielded an insignificant moderating effect on the JS to TI relationship.

In relation to the research context of this study, the researcher notes that the current local labor market is slowly growing as result of the economical growth. Announced private sector developments in related upcoming industries like gold mining, oil refining and power generation can have influenced perceptions of available job alternatives. However, as already mentioned, perception does not mean having factual information of the labor market.

The interpretation of the moderating effect can be complex, as three variables are being related to each other. The reader is referred back to Figure 18 in chapter 4. The visual explanation makes it clear that the negative JS to TI relationship is being conditioned by PAJA. While keeping focus on the PAJA variable during interpretation we can conclude that the TI of “salaried” employees is always higher when high levels of PAJA are reported than when low levels of PAJA are reported. This observation does not change dramatically whether the job satisfaction is high or low. This is also explained by the earlier mentioned significant relationship between PAJA and TI and a weak, but still significant relationship between PAJA and JS.

Overall, this means that even if “salaried” employees’ JS is high, their TI will be higher when they report high PAJA in comparison to when they report low PAJA. This means that an employee who is overall satisfied with pay, promotion, supervisor, co-worker and nature of work and with high perceptions of available job alternatives will still have higher intentions to quit his

job in comparison with a satisfied employee with low perceptions of available job alternatives. On the other hand, it also means that “salaried” employees reporting low JS will also report lower TI when they do not perceive available job alternatives in comparison with when they did perceive available job alternatives. Thus, unsatisfied “salaried” employees will show lesser intent to leave the organization if they do not perceive that there are available job alternatives.

The following table is a representation of the turnover intention values presented in Figure 17 wherein the JS to TI relation is being conditioned by three levels of PAJA. Similarly, three levels of job satisfaction are being displayed: low; medium and high. Medium is equal to the mean of the related variable, low is 1 standard deviation smaller than the mean and high is 1 standard deviation higher than the mean. Looking at the table we see that overall for nine different scenarios the turnover values can be determined. Overall, we see that the lowest turnover intention values are for employees who reported high JS and low PAJA. The highest turnover intentions values are for employees who reported low JS and high PAJA. The JS-TI relationship is strongest in the case high PAJA and weakest in the case of low PAJA.

Table 20: Turnover Intention values based on the Moderated JS to TI relationship JS

LOW MEDIUM HIGH

4.7 _{3.8 3.0}

HIGH

P

AJ

A

low-high medium-high high-high

4.0 3.4 2.7

MEDIUM

low-medium medium-medium high-medium

3.4 2.9 2.4

LOW

low-low medium-low high-low

Source: Author generated table. Note: e.g., “low-low” means low JS and low PAJA (read from top to right)

Lastly it can be noted that based on the last sequential model (model 4) in the hierarchical regression the value of the interaction term (-.222) is significant and adds a bit more predictive power to the model. The reader is referred back to Table 18, page 62.