Abstract
Purpose
Affective events theory (AET) highlights the importance of work events as antecedents of distinct emotions, attitudes, and work behavior. However, few attempts have been made to systematically classify positive and negative work events. The aim of this study was to develop a comprehensive taxonomy of affective work events to provide a common frame of reference for future research and to improve communication among researchers regarding research on affective work events.
Design and Methodological Approach
Positive and negative affective work events were sampled from employees using a diary study design. We used concept mapping methodology as an exploratory approach to analyze the data on affective work events.
Findings
Two hundred eighteen employees reported 559 positive and 383 negative affective work events. We identified four positive and seven negative event clusters. Each event cluster showed a unique relationship with distinct affective states, even when controlling for the occurrence of events without clustering and trait affect. The results support the validity of our taxonomy.
Implications
This study contributes to previous literature by providing a comprehensive yet parsimonious classification of both positive and negative affective work events. The affective work event clusters found reflect personal values of agency and communion. This classification of affective events as reflecting agentic and communal values provides a starting point for the integration of findings from previous studies.
Originality and Value
The taxonomy developed in this study provides an integrative approach and a basis for future research to more differentially investigate relationships proposed by AET.
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Notes
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.
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We thank Cynthia Fisher, Sabine Sonnentag, Wendong Li, and Anya Johnson for their helpful suggestions and comments on an earlier version of this manuscript.
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S. Ohly and A. Schmitt contributed equally to this work. Authorship is in alphabetical order.
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Ohly, S., Schmitt, A. What Makes Us Enthusiastic, Angry, Feeling at Rest or Worried? Development and Validation of an Affective Work Events Taxonomy Using Concept Mapping Methodology. J Bus Psychol 30, 15–35 (2015). https://doi.org/10.1007/s10869-013-9328-3
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DOI: https://doi.org/10.1007/s10869-013-9328-3