If We Produce Discrepancies, Then How? Testing a Computational Process Model of Positive Goal Revision



Within the self-regulation literature on goals, both discrepancy reduction and discrepancy production are considered important theoretical and practical processes. Yet, discrepancy production has only been examined in a limited number of goal-striving contexts, and the analytical strategies employed (e.g., difference scores) are difficult to interpret. This study extends discrepancy production research to multiple goal contexts where the goals are in conflict. Computational modeling and an organizational simulation were used to test a control theory explanation of discrepancy production. The occurrence of discrepancy production in the computational model and participants was assessed using hierarchical linear modeling. Comparing the data from the computational model with participants' data indicated a good fit. Implications of the findings and methods are discussed.