The depth of history and explanation as benefit and bane for psychological control theories

A longstanding debate has recently re-erupted in the self-regulation literature around the concept of self-efficacy. This article presents an argument that the debate emerges from a lack of understanding of the history of control theories within both the social and physical sciences and the various levels of explanation to which phenomena can be subjected. This history, coupled with the issues of determinism, materialism, and empiricism evoked by the deeper level of explanation that some versions of control theory provide, has led some critics to mis-apply non-psychological properties to control theories and obscure their usefulness. Here, the usefulness of a deeper control theory level of explanation is illustrated using comparisons with explanations found in goal-setting theory and social cognitive theory.     

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.     

The effect of feedback sign on task performance depends on self-concept discrepancies

Control theories claim that information about performance is often used by multiple goal systems. A proposition tested here was that performance information can create discrepancies in self-concept goals, directing cognitive resources away from the task goal system. To manipulate performance information, 160 undergraduates were given false positive or false negative normative feedback while working on a task that did or did not require substantial cognitive resources. Half of the participants were then given an opportunity to reaffirm their self-concepts following feedback, whereas half were not. Feedback sign positively related to performance only for those working on the cognitively intense task and not given a chance to reaffirm. Otherwise, feedback sign was negatively related to performance, albeit weakly.     

Change one can believe in: Adding learning to computational models of self-regulation

Theories of self-regulation describe motivation as a dynamic process of goal choice and goal striving. To facilitate those processes, individuals learn about themselves and their environment, which is an internal dynamic process. However, the precise nature of the relationship between these learning and motivational processes is not well specified. This article integrates formal models of learning, goal choice, and goal striving using a single information processing structure found in self-regulatory models of motivation. Results from two published studies ( and ) validate the model. In both cases, the integrated model accounts for findings that previous theories of self-regulation could not explain. Discussion focuses on additional tests to validate the model and on the value of incorporating formal models from the cognitive, learning, and motivational literatures to account for behavior in complex settings and over time.     

Using a Computational Model to Understand Possible Sources of Skews in Distributions of Job Performance

The typical assumption that performance is distributed normally has come under question in recent years (e.g., O'Boyle & Aguinis, 2012). This paper uses a dynamic, computational model of performance‐as‐results to examine possible sources of such distributions. That is, building off the classic model of job performance (Campbell & Pritchard, 1976), components of a dynamic model are examined in 4 separate experiments using Monte Carlo simulations. The experiments indicate that positively skewed distributions can arise from pure luck, multiplicative combinations of factors where 1 of those factors has a zero origin, Matthew effects associated with learning, and feedback effects of performance on resource allocation policies by external agents. The results are discussed in terms of explanations for positively skewed performance distributions and the use and expansion of the computational model for examining dynamic performance more generally.     

The dynamics of avoidance goal regulation

An avoidance goal is an undesired state from which a person seeks to distance themselves. Though important for understanding behavior, avoidance goals have received less attention than approach goals. In this paper, we present a dynamic, formal model that provides a framework for describing and predicting the dynamics of avoidance goal regulation. We conduct a series of simulations to examine the dynamic pattern of behavior that emerges from the model when an avoidance goal is pursued in isolation and when an approach goal is also present. Two versions of the model were examined. In the first, the avoidance goal is regulated by a positive feedback loop. In the second, the avoidance goal is regulated by a negative feedback loop. We find that the positive feedback model produces a pattern of runaway behavior, even in a scenario where an approach goal is also present. By contrast, the negative feedback loop model produces a stable pattern of behavior that is more consistent with existing theory. The findings provide an important step toward theoretical parsimony by demonstrating that avoidance goal regulation, like approach goal regulation, can be understood using a negative feedback control system framework. We discuss new insights provided by this model and its potential to spark empirical research.     

Industrial and Organisation Research on Self-Regulation: From Constructs to Applications

L’autorégulation rencontre actuellement du succès en psychologie industrielle et organisationnelle. Les travaux théoriques et empiriques englobent des processus allant de l’entrée dans l’organisation à la sortie et à la réembauche. Les interventions et les concepts clés de l’autorégulation dans le monde du travail sont recensés en insistant sur la validité interne et de construction. Quelques concepts comme l’efficacité personnelle et l’implication ont bénéficié d’un grand intérêt de la part des psychométriciens et semblent constituer des cibles de premier ordre lors des interventions. Néanmoins, ces concepts restent entachés d’hypothèses dont la validité n’est pas garantie. D’autres concepts, en particulier la rétroaction et la divergence, souffrent de significations sensiblement différentes dans la littérature sur l’autorégulation, ce qui nuit à la compréhension et à la communication entre les universitaires et les praticiens. On a lancé des interventions relevant des principes de l’autorégulation; celles‐ei ont ensuite étéévaluées avec sérieux: il est apparu qu’elles avaient un impact sur un ensemble de variables pertinentes du point de vue organisationnel comme l’amélioration des performances et la réduction de l’absentéisme. Malheureusement, les interventions sont rarement étudiées de façon détaúllée et systématique, ce qui ne permet pas de tirer des conclusions sur les aspects de l’intervention qui sont pertinents du point de vue de la causalité. La discussion insiste sur les lacunes dans la connaissance et l’appréhension des processus de l’autorégulation dans les contextes organisationnels, ainsi que sur la façon dont la discipline pourrait tenter de combler ces lacunes. The self‐regulation perspective is currently well received in the industrial and organisational psychology literature. Theoretical and empirical work span processes ranging from organisation entry to exit and reentry. Key self‐regulation constructs and interventions in work contexts are reviewed with a focus on construct and internal validity. Some constructs, such as self‐efficacy and goal commitment, have received substantial psychometric attention and seem important targets for interventions. Nonetheless, potentially unwarranted assumptions remain regarding these constructs. Other constructs, particularly feedback and discrepancy, have acquired substantially different meanings within the self‐regulation literature that inhibit understanding and communication among scholars and practitioners. Interventions based on self‐regulatory principles have been developed, and rigorous tests of these interventions have been conducted. These interventions were found to influence a range of organisationally relevant outcomes such as increasing performance and reducing absenteeism. Unfortunately, studies of comprehensive interventions are rare and often lacked controls, making it difficult to draw conclusions regarding what aspects of the interventions are causally relevant. Discussion focuses on the gaps in the field's knowledge and understanding regarding self‐regulatory processes in organisational settings and how the field might attempt to fill those gaps.     

Analyzing Goal-Striving Processes and a Test of the Generalizability of Perceptual Control Theory

Theories that articulate dynamic processes are relatively rare, but methods for testing the theories are even rarer. This study illustrates two methods for examining goal-striving processes and a tool for collecting dynamic data. The first method tests a hypothesis regarding what variable the participants are attempting to maintain. The second method involves creating multilevel models used to describe the dynamic data generated by study participants, which can be used to test between- and within-subject manipulations or differences. The tool is a research simulation of a manager's role in scheduling subordinates in a hospital wing. Together these methods and the tool are used to test the generalizability of perceptual control theory in explaining striving for cognitive goals. The results confirm the viability of a control theory accounting of goal striving and highlight the potential of the methods and the research tool in future research.     

The changing signs in the relationships among self-efficacy, personal goals, and performance

The common interpretation of the positive correlation among self-efficacy, personal goals, and performance is questioned. Using self-efficacy theory (A. Bandura, 1977), it was predicted that cross-sectional correlational results were a function of past performance's influence on self-efficacy, and using control theory (W. T. Powers, 1973), it was predicted that self-efficacy could negatively influence subsequent performance. These predictions were supported with 56 undergraduate participants, using a within-person procedure. Personal goals were also positively influenced by self-efficacy and performance but negatively related to subsequent performance. A 2nd study involving 185 undergraduates found that manipulated goal level positively predicted performance and self-efficacy positively predicted performance in the difficult-goal condition. The discussion focuses on conditions likely to affect the sign of the relationship among self-efficacy, goals, and performance.