What Makes Us Enthusiastic, Angry, Feeling at Rest or Worried? Development and Validation of an Affective Work Events Taxonomy Using Concept Mapping Methodology

A table providing details on the literature overview on affective work events can be provided by the authors upon request.

Affective event clusters are coded as dichotomous variables (0 = event of the respective cluster was not reported, 1 = event was reported). The coefficients in Table 3 can be interpreted as follows: The predicted score in the dependent variable (distinct positive/negative affective states) increases or decreases by the respective estimated value for one unit increase in the respective affective event cluster (event from this cluster is reported vs. not reported). Hence, the regression slope represents the difference in distinct positive/negative affect between observations when the respective affective event was reported vs. was not reported. For instance, the predicted score in enthusiastic increases by 0.48 when an event from the cluster goal attainment, problem solving, task-related success is reported compared to when an event from this cluster is not reported.

Based on the results of the second clustering suggesting separate clusters for problem solving and overload (see Table 2), we replicated the hypothesis testing by adding problem solving and overload as distinct clusters in our taxonomy (a total of 13 event clusters). However, it appeared that in contrast to the other 11 work event clusters, problem solving and overload as separate clusters were unrelated to any of the five distinct affective states and did not explain any variance in affect. This confirms our approach to decide on a final taxonomy with 11 affective work events.

Interestingly, four very similar positive event clusters were identified in the success model of job stress (Grebner et al. 2010) using content analysis of employees narratives.