Self-efficacy, which is one's belief in one's capacity, has been found to both positively and negatively influence effort and performance. The reasons for these different effects have been a major ...topic of debate among social-cognitive and perceptual control theorists. In particular, the findings of various self-efficacy effects has been motivated by a perceptual control theory view of self-regulation that social-cognitive theorists' question. To provide more clarity to the theoretical arguments, a computational model of the multiple processes presumed to create the positive, negative, and null effects for self-efficacy is presented. Building on an existing computational model of goal choice that produces a positive effect for self-efficacy, the current article adds a symbolic processing structure used during goal striving that explains the negative self-efficacy effect observed in recent studies. Moreover, the multiple processes, operating together, allow the model to recreate the various effects found in a published study of feedback ambiguity's moderating role on the self-efficacy to performance relationship (Schmidt & DeShon, 2010). Discussion focuses on the implications of the model for the self-efficacy debate, alternative computational models, the overlap between control theory and social-cognitive theory explanations, the value of using computational models for resolving theoretical disputes, and future research and directions the model inspires.
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This article presents a theory of how people prioritize their time when pursuing goals with different deadlines. Although progress has been made in understanding the dynamics of multiple-goal ...pursuit, theory in this area only addresses cases where the goals have the same deadline. We rectify this issue by integrating the multiple-goal pursuit model-a formal theory of multiple goal pursuit-with theories of intertemporal motivation and choice. We examine the ability of four computational models derived from this general theory to account for participants' choices across four experiments. The models make different assumptions about how people determine the valence of prioritizing a goal (i.e., by monitoring distance to goal or time pressure), and whether the goal is subject to temporal discounting. In each experiment, participants performed a task requiring them to pursue two goals. Experiments 1 and 2 manipulated deadline and distance; Experiment 3 manipulated deadline and time pressure; Experiment 4 manipulated all three factors. Counter to the predictions of existing theory, participants generally prioritized the goal with the shorter deadline. We also observed weak, but positive effects of distance on prioritization (Experiment 2) and nonlinear effects of time pressure (Experiment 3). The model that best explained participants' decisions assumed that valence is determined by time pressure and the expected utility of a goal is subject to temporal discounting. This new model broadens the range of phenomena that can be accounted for within a single theory of multiple-goal pursuit, and improves our understanding of the interface between motivation and decision making.
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3.
Dynamic Self-Regulation and Multiple-Goal Pursuit Neal, Andrew; Ballard, Timothy; Vancouver, Jeffrey B
Annual review of organizational psychology and organizational behavior,
03/2017, Volume:
4, Issue:
1
Journal Article
Peer reviewed
Open access
Self-regulation is the dynamic process by which people manage competing demands on their time and resources as they strive to achieve desired outcomes, while simultaneously preventing or avoiding ...undesired outcomes. In this article, we review the current state of knowledge regarding the process by which people manage these types of demands. We review studies in the organizational, cognitive, social psychology, and human factors literatures that have examined the process by which people (
a
) manage task demands when working on a single task or goal; (
b
) select which tasks or goals they work on, and the timing and order in which they work on them; and (
c
) make adjustments to the goals that they are pursuing. We review formal theories that have been developed to account for these phenomena and examine the prospects for an integrative account of self-regulation that can explain the broad range of empirical phenomena examined across different subdisciplines within psychology.
This research develops and tests a formal process-oriented theory of leader goal striving. Drawing on self-regulation theory, we developed a computational model that explicates the core process ...mechanisms involved in a leader-subordinate dyadic goal pursuit system. We then extended this core model to incorporate action team features (i.e., negative external disturbances, deadlines, and task interdependence) to account for leadership behavior in action team context. We simulated our proposed model to generate predictions about trajectories of a critical leadership function (i.e., leader engaging in team task-specific actions) under different conditions of disturbances, deadlines, task interdependence, and leader attributes. The predicted relationships were then tested in a laboratory experiment. As predicted by the model, time-related factors, including disturbances and deadlines, had significant effects on trajectories of leader actions. Over time within a given task, leaders were more likely to take actions when further than closer to the deadline. Leaders were also more likely to take actions when external disturbances set task states back. In addition, leaders' time allocation was less evenly distributed across subordinates when the deadline was short (vs. long). We discussed the implications of the model and how future research can extend our model to account for more complicated goal pursuit and team processes.
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Despite decades of research, there is little empirical or theoretical consensus around how job insecurity shapes job performance. This article introduces an ecumenical, dynamic, and computational ...model of the job insecurity-job performance relationship. That is, rather than representing a single theoretical perspective on job insecurity effects, the model includes three key mechanisms through which job insecurity is theorized to impact performance-stress, social exchange, and job preservation motivation-and grounds these in a self-regulatory computational architecture. The model incorporates multiple, dynamic feedback loops that include job performance and job insecurity, as well as individual difference and contextual constructs to project the immediate, short-term, and long-term effects of changes to job security and other important variables. Simulations of the model demonstrate that a self-regulating representation of human information processing can produce effects consistent with the major propositions in the job insecurity literature. Moreover, interrupted time-series simulations of a new job insecurity threat reveal how, when, and why performance can stabilize above, near, or below baseline performance levels, sometimes for counterintuitive reasons. Additionally, the model shows how the frequently reported, cross-sectional, negative relationship between job insecurity and job performance can be explained by job performance's influence on job insecurity. The results imply important considerations and directions for future job insecurity research and demonstrate the value of a formal, dynamic systems approach to theorizing.
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Theories are the core of any science, but many imprecisely stated theories in organizational and management science are hampering progress in the field. Computational modeling of existing theories ...can help address the issue. Computational models are a type of formal theory that are represented mathematically or by other formal logic and can be simulated, allowing theorists to assess whether the theory can explain the phenomena intended as well as make testable predictions. As an example of the process, Locke’s integrated model of work motivation is translated into static and dynamic computational models. Simulations of these models are compared to the empirical data used to develop and test the theory. For the static model, the simulations revealed largely strong associations with robust empirical findings. However, adding dynamics created several challenges to key precepts of the theory. Moreover, the effort revealed where empirical work is needed to further refine or refute the theory. Discussion focuses on the value of computational modeling as a method for formally testing, pruning, and extending extant theories in the field.
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Recent reviews of the training literature have advocated directly manipulating self-efficacy in an attempt to improve the motivation of trainees. However, self-regulation theories conceive of ...motivation as a function of various goal processes, and assert that the effect of self-efficacy should depend on the process involved. Training contexts may evoke planning processes in which self-efficacy might negatively relate to motivation. Yet the typical between-persons studies in the current literature may obscure the effect. To examine this issue, 63 undergraduate students completed a series of questionnaires measuring self-efficacy and motivation before 5 class exams. Self-efficacy was negatively related to motivation and exam performance at the within-person level of analysis, despite a significant positive relation with performance at the between-persons level.
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8.
Rhetorical Reckoning Vancouver, Jeffrey B.
Journal of management,
03/2012, Volume:
38, Issue:
2
Journal Article
Peer reviewed
This comment is a response to Bandura’s guest editorial (Journal of Management, Vol. 38, no. 1, January 2012) on the functional properties of perceived self-efficacy. The focus of this comment is on ...the limitations inherent in natural language (i.e., verbal) theories and critiques, which the research regarding self-efficacy has highlighted and Bandura’s editorial underscores. Specifically, it is argued that Bandura’s comment is replete with rhetorical fallacies and theoretical contradictions. Several examples are described to both provide a tutorial on rhetorical sleight of hand and to set the record straight. Computational modeling and logical reasoning are presented as an alternative approach to better scientific theorizing and critique.
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We develop and test an integrative formal model of motivation and decision making. The model, referred to as the extended multiple-goal pursuit model (MGPM*), is an integration of the multiple-goal ...pursuit model (Vancouver, Weinhardt, & Schmidt, 2010) and decision field theory (Busemeyer & Townsend, 1993). Simulations of the model generated predictions regarding the effects of goal type (approach vs. avoidance), risk, and time sensitivity on prioritization. We tested these predictions in an experiment in which participants pursued different combinations of approach and avoidance goals under different levels of risk. The empirical results were consistent with the predictions of the MGPM*. Specifically, participants pursuing 1 approach and 1 avoidance goal shifted priority from the approach to the avoidance goal over time. Among participants pursuing 2 approach goals, those with low time sensitivity prioritized the goal with the larger discrepancy, whereas those with high time sensitivity prioritized the goal with the smaller discrepancy. Participants pursuing 2 avoidance goals generally prioritized the goal with the smaller discrepancy. Finally, all of these effects became weaker as the level of risk increased. We used quantitative model comparison to show that the MGPM* explained the data better than the original multiple-goal pursuit model, and that the major extensions from the original model were justified. The MGPM* represents a step forward in the development of a general theory of decision making during multiple-goal pursuit.
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Understanding the processes involved when pursuing multiple goals over time is a central question for motivational theorists. A dynamic, computational model integrating theories of goal striving and ...goal choice is presented to account for data emerging from Schmidt and DeShon's (2007) multiple-goal-pursuit protocol. The simulated results match the results reported in their study, including the finding that relative discrepancy from the goals positively predicted resource allocation early on but negatively predicted it toward the end of the session. Variance in parameters in the model also accounted for individual differences found in the data. Discussion focuses on the theoretical contribution of formally integrating elements of self-regulation theories, further empirical work needed to test the model, and further theoretical work needed to continue the integration process exemplified here.
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