Decision-Making Processes in the Workplace
The article mentions Daniel Kahneman without explaining much about him. We will get to know him much better in the next section when we start to think about thinking.
Sometimes the most well-structured decision-making processes go awry, not because
of the process itself, but because of the participants or the environment. This article shows us what can go wrong and how to get things back on track to meet
your TOR deliverables.
The article discusses obstacles to improved decision-making, including "cognitive limitations, heuristics and biases and individual inclinations". Heuristics are mental shortcuts individuals use to solve problems. These have great use, for instance, telling humans to run when they see a saber-toothed tiger without thinking too much about the decision. The choice of which cat to adopt from a shelter today may require less use of heuristics and more cognitive exercise.
Results
Simple Slope Analyses
Simple slope analyses were performed to explore interactions emerged in the SEM. In relation to DEM, job resources and estimated H1b moderator (DEM × job resources → extra-role performance), results showed that for higher levels of job resources (+1 SD above the mean) there was a stronger positive relationship between DEM and extra-role performance (B = 0.425, t = 3.96, p < 0.001), whereas this relationships was less strong for lower levels of job resources (-1 SD below the mean: B = 0.180, t = 2.03, p < 0.05). A graphical representation of the moderation effect is presented in Figure 3, which shows how participants high in DEM benefit more from job resources when these are high, eventually resulting in higher extra-role performance.
FIGURE 3. Relationship between job resources and extra-role performance for low versus high decision environment management (DEM) employees.
Considering moderation related to hypothesis H2b (DMCy × job demands → in-role performance), the simple slope revealed that for low levels of job demands, DMCy is strongly and positively related to in-role performance (-1 SD under the mean: B = 0.551, t = 4.06, p < 0.001) and it becomes non-significant for higher levels of them (+1 SD above the mean: B = 0.184, t = 1.11, p = 0.268). Figure 4 shows that high levels of in-role performance of participants high in DMCy do not coincide with in-role performance levels of subject low in DMCy when job demands are low.
FIGURE 4. Relationship between job demands and in-role performance for low versus high decision-making competency (DMCy) employees.
A graphical representation of the moderation effect of Hypothesis H3b (DEM × exhaustion → extra-role performance) is presented in Figure 5. It shows that extra-role performance is higher when DEM is high (versus low) for low exhaustion condition, whereas for subjects low in DEM the trend inverts. The interaction effect is significant for all the levels of the moderator (+∖- 1 SD), but, contrary to the first moderation pattern, the interaction effect follows a decremental trend: For low levels of exhaustion (-1 SD below the mean), DEM has a stronger positive relationship with extra-role performance, (B = 0.538, t = 5.11, p < 0.001), whereas the strength of this relationship is halved for higher levels of exhaustion (+1 SD above the mean: B = 0.246, t = 2.47, p < 0.05).
FIGURE 5. Relationship between exhaustion and extra-role performance for low versus high decision environment management (DEM) employees.