Action Regulation Theory
- Hannes ZacherHannes ZacherInstitute of Psychology, Faculty of Biosciences, Pharmacy and Psychology, University of Leipzig
Action regulation theory is a meta-theory on the regulation of goal-directed behavior. The theory explains how workers regulate their behavior through cognitive processes, including goal development and selection, internal and external orientation, planning, monitoring of execution, and feedback processing. Moreover, action regulation theory focuses on the links between these cognitive processes, behavior, the objective environment, and objective outcomes. The action regulation process occurs on multiple levels of action regulation, including the sensorimotor or skill level, the level of flexible action patterns, the intellectual or conscious level, and the meta-cognitive heuristic level. These levels range from unconscious and automatized control of actions to conscious thought, and from muscular action to thought processes. Action regulation at lower levels in this hierarchy is more situation specific and requires less cognitive effort than action regulation at higher levels.
Workers further develop action-oriented mental models that include long-term cognitive representations of input conditions, goals, plans, and expected and prescribed results of action, as well as knowledge about the boundary conditions of action and the transformation procedures that turn goals into expected results. The accuracy and level of detail of such action-oriented mental models is closely associated with the efficiency and effectiveness of action regulation. One of three foci can be in the foreground of action regulation: task, social context, or self. A task focus is most strongly associated with high efficiency and effectiveness of action regulation, because it links task-related goals with relevant plans, behavior, and feedback. Action regulation theory has been applied to understand several phenomena in the field of industrial, work, and organizational psychology, including proactive work behavior, work-related learning and error management, entrepreneurship, occupational strain and well-being, reciprocal influences between personality and work, innovation, teamwork, career development, and successful aging at work.
Action regulation theory is a meta-theory on the psychological regulation of goal-directed behavior in the work context (Frese & Zapf, 1994; Hacker, 1971, 1998). It describes and explains cognitive and behavioral processes during work-related action sequences and the effects of work design and tasks on individual workers. As a meta-theoretical framework, action regulation theory allows integrating midrange theories that focus on human action (Frese, 2006). Over the past decades, action regulation theory has become an important basic theory in applied psychology, particularly in the field of industrial, work, and organizational psychology (Frese, Rank, & Zacher, 2017; Hacker, 2003; Zacher & Frese, 2018). This article first provides a brief historical overview of the development of action regulation theory. Second, the most important concepts of the theory are defined and explained, including actions and central characteristics of actions, the sequential and hierarchical structure of action regulation, the concept of complete tasks and actions, the action-oriented mental model, and different foci of action regulation. Finally, theoretical and practical implications of action regulation theory for the design of work tasks, worker stress and well-being, as well as positive psychological development and successful aging in the work context are outlined.
Brief Historical Overview
Action regulation theory was developed in the 1960s and 1970s in response to the dominant paradigm of behaviorism, which focused primarily on observed behavior as a reaction to environmental stimuli and neglected cognitive processes residing in the “black box.” In the United States, Miller, Galanter, and Pribram (1960) published an influential book Plans and the Structure of Behavior, in which they examined the cognitive underpinnings of complex actions. Additionally, research on cognitive and human factors in countries of the former Soviet Union, particularly Russia and Poland, had an influence on the development of action regulation theory (Leontjev, 1978; Tomaszewski, 1978). In Germany, Hacker (1971) published the seminal book General Work and Engineering Psychology in which he laid out the fundamental concepts and tenets of action regulation theory (Hacker updated and extended the book several times, see Hacker, 1998; Hacker & Sachse, 2014, for more recent versions). Hacker’s (1971) work had a significant influence on work psychology research in German-speaking countries over the following decades.
In the 1980s and 1990s, Frese and colleagues introduced action regulation theory as a “German approach to work psychology” to a broader international audience (Frese & Sabini, 1985; Frese & Zapf, 1994). Since then, action regulation theory has been used to investigate numerous topics in industrial, work, and organizational psychology (see Zacher & Frese, 2018, for a comprehensive review of these applied topics), including team work (von Cranach, 1996); proactive work behavior (Frese & Fay, 2001); emotions, stress, and well-being (Zapf, 2002); entrepreneurship (Frese, 2009); errors in organizations (Hofmann & Frese, 2011); career development (Raabe, Frese, & Beehr, 2007); and successful aging at work (Zacher, Hacker, & Frese, 2016). Action regulation theory is distinct from, but shares some concepts and propositions with, other cognitive-behavioral theories, including control theory (Carver & Scheier, 1982) and goal setting theory (Locke & Latham, 1990, 2002; Zacher & Frese, 2018, provide a more detailed comparison of the theories).
Recent research in the area of self-regulation (a field closely related to action regulation theory) has focused increasingly on the dynamic process of action regulation (Lord, Diefendorff, Schmidt, & Hall, 2010; Neal, Ballard, & Vancouver, 2017). While people strive to attain desired outcomes (i.e., “approach goals”) and prevent undesired outcomes (i.e., “avoidance goals”), they often have to flexibly manage multiple competing demands on their time and personal resources (Neal et al., 2017). For instance, people have to make decisions on which goals or tasks they are able and want to pursue; they have to invest their physical, cognitive, and emotional energies to complete their tasks; and they might have to make changes to or disengage from certain goals and tasks based on the availability of personal and external resources and constraints.
Action and Central Characteristics of Action
Action is defined as goal-directed behavior (Hacker, 1985). More specifically, Hacker (1985) characterizes an action as the smallest psychologically relevant or self-contained (in terms of content and time) unit of behavior. Goals are mentally anticipated and desired results of action that have a motivational influence, because they set ideal standards for behavior and can “pull” behavior (Austin & Vancouver, 1996; Locke & Latham, 1990). To initiate an action, people first need to anticipate an ideal state (i.e., goal) and recognize a discrepancy between this ideal state and their current state or outcomes. With regard to the notion of discrepancy reduction, action regulation theory partially overlaps with propositions of control theory (Carver & Scheier, 1982; Lord & Levy, 1994). However, action regulation theory goes beyond control theory in that it assumes humans as active agents that set themselves more challenging goals and higher standards over time and with increased experience (Zacher & Frese, 2018). A goal is achieved through action and the results of action. The action is completed when the relevant goal has been attained and a discrepancy between the ideal state and the current state does not exist anymore.
While not all goals are conscious and not all actions are consciously regulated, a defining feature of an action is that its goal could principally be brought to conscious awareness (Hacker, 1998; Locke & Latham, 2013). Furthermore, action regulation theory assumes that actions are closely linked to and embedded in the objective (i.e., material, social, societal) environment. On the one hand, the environment can trigger and shape actions (e.g., effects of organizational culture on individual behavior; Schneider, Ehrhart, & Macey, 2013); on the other hand, actions can also shape the environment consistent with a person’s goals (e.g., job crafting; Rudolph, Katz, Lavigne, & Zacher, 2017; Wrzesniewski & Dutton, 2001). Action regulation theory assumes that, through their actions, reactions, and interactions with the environment, workers adapt and improve their cognitive representation of the environment (Frese & Sabini, 1985). Thus, action regulation theory proposes that actions contribute to the development of the human psychological system (e.g., action errors are considered learning devices that help improve a concept of reality; Frese & Keith, 2015). In contrast to behaviorist theories, cognitive processes such as goal development, planning, and feedback processing play an important role in actions regulation theory. At the same time, the theory differs from purely cognitive and information processing theories in that the links between cognitive processes, behavior, and the objective environment and objective outcomes of action play an important role.
Sequential-Hierarchical Structure of Action Regulation
Sequential Structure of Action Regulation
Action regulation theory assumes that people’s actions unfold across five cyclical phases: goal development and selection, orientation or mapping the environment, plan development and selection (planning), monitoring of execution, and feedback processing (Frese & Zapf, 1994). The first three phases develop or retrieve information necessary for action regulation. The following phases implement the action plans and collect action-relevant feedback. Feedback processing, in turn, may inform continued goal develop, selection, or disengagement. It is important to note that this idealized action regulation sequence does not have to be followed in a rigid way. For instance, sometimes it may be necessary to skip certain steps (e.g., develop a plan without searching for goal-relevant information), repeat steps (e.g., develop a new goal if the former goal turns out to be difficult or impossible to achieve), or to go back and forth between steps (Frese & Zapf, 1994).
In the first action regulation phase, workers develop and select goals that they intend to pursue. Goals can be either internally generated (i.e., self-set) based on broader values, motives, and expectations (DeShon & Gillespie, 2005) or assigned by others (e.g., supervisor, organizational management). If assigned by others in the form of work tasks, individuals have to redefine these tasks and turn them into personal goals (Hackman, 1970). The success of this redefinitions process is dependent on various individual (e.g., experience) and contextual (e.g., clarity of task) factors. Goals can be either consciously or subconsciously represented (Bargh & Barndollar, 1996; Latham & Piccolo, 2012). Regarding the latter, it is possible that organizational environments trigger actions subconsciously. Moreover, goals can range from short-term goals (e.g., work goal for this afternoon) to longer-term goals (e.g., life goals). People differ in their characteristic way of developing and pursuing goals (Frese, Stewart, & Hannover, 1987). In addition, research has shown that certain goal orientations (e.g., approach or avoidance goals) can be primed in experimental studies (Ballard, Yeo, Neal, & Farrell, 2016).
Goals are hierarchically structured (Volpert, 1982). Thus, the attainment of lower-order goals may contribute to higher-order goals, and higher-order goals can help establish continuity among lower-order goals. Each goal can have multiple subgoals, sub-subgoals, and so forth; and each goal is linked to a cyclical action unit with the five action regulation phases. For instance, the goal of publishing a scientific manuscript entails several subgoals (e.g., finding collaborators, literature search, carrying out a study, drafting the different sections). At the same time, publishing a manuscript can be a subgoal of the higher-order goal of getting promoted. The more lower-order goals exist, the more orientation, planning, monitoring, and feedback processing are necessary. Research on goals has shown that the nature of goals and coordination of multiple goals is linked to the efficiency and effectiveness of action regulation. For instance, research on goal setting theory has consistently shown that specific and challenging goals have the strongest effects on performance, if goals are realistic, accepted, and feedback is provided (Locke & Latham, 2002). In contrast, vague goals (e.g., “do your best”), too easy or too difficult goals, and multiple competing or contradictory goals typically lead to poorer performance.
Conceptual and empirical research on multiple goal pursuit is a relatively new development in the area of self-regulation (Neal et al., 2017; Sun & Frese, 2013; Unsworth, Yeo, & Beck, 2014; Vancouver, Weinhardt, & Schmidt, 2010). Researchers in this area are interested in why and when people prioritize some goals over others. For instance, in a conceptual paper, Unsworth et al. (2014) derived a set of seven principles of multiple goal pursuit, which refer to goal structure and activation, goal alignment, goal-based informational and affective value, goal-performance discrepancies, expectancy, and goal shielding. In an experimental study, Ballard et al. (2016) investigated why people depart from optimality when pursuing multiple goals. They found that people are more risk averse when they pursue multiple “approach goals” (i.e., attaining desired outcomes). In contrast, people are more risk seeking when they pursue multiple “avoidance goals” (i.e., avoiding undesired outcomes). The second action regulation phase, mapping the environment or orientation, involves that individuals search for goal-relevant information in their memory as well as in the objective physical and social environment (Frese & Zapf, 1994). The process of searching for information can be more or less active, ranging from deliberate and conscious efforts to an unconscious and intuitive understanding of situations. The retrieval, recognition, and understanding of relevant information depend on both individual (e.g., experience with a task) and contextual factors (e.g., transparency of signals). Based on the information retrieved from memory or obtained from environmental signals, individuals regulate their actions. Action-relevant information includes previous experiences and expertise, possible execution opportunities and constraints, availability of relevant tools and methods, and important boundary conditions for goal attainment. This information enables individuals to make predictions about the likelihood of successful goal attainment. Moreover, it can help them coordinate individuals’ actions with those of supervisors and colleagues (Hacker, 2003). If workers develop adequate, action-relevant mental representations of their tasks, goals, and associated boundary conditions, the action process becomes more efficient and effective. In contrast, when individuals do not retrieve information accurately or too slowly, their information search does not lead to relevant action, or information is processed in a biased way, their performance may suffer.
The third phase, planning, consists of plan development and selection. Plans have been described as bridges between thoughts and actions (Miller et al., 1960). They are mental simulations of the behavioral steps (also called transformations or operations) that are necessary to attain a goal and can be more or less detailed and complex. A list of subgoals constitutes a simple plan (Locke & Latham, 2002). Moreover, the planning process may involve the development of one or more backup plans that can be put in place in case an initial plan fails or is increasingly considered to be less likely successful (Napolitano & Freund, 2016). Generally, detailed planning is considered an effective strategy in the work context. However, when detailed plans are followed in an overly rigid manner, they can become ineffective when goals are complex and when situational requirements change (Baker & Nelson, 2005). Plans are also inefficient when planning entails the disproportionate investment of cognitive effort (Mumford, Mecca, & Watts, 2015). Action regulation theory suggests that so-called best-workers or superworkers develop more elaborate and proactive task-oriented plans that allow them to better deal with errors, interruptions, and other challenging work situations (Frese & Zapf, 1994).
The fourth phase, monitoring of execution, involves comparisons between goals, associated plans, and the actual execution of goal-directed behavior. This comparison draws heavily on individuals’ working memory capacity and general mental ability. Moreover, during the execution of behavior, workers may be required to deal with unexpected barriers and constraints (or new opportunities), adapt their goals and plans accordingly, and coordinate action efficiently with regard to the limited time and resources available (Frese & Zapf, 1994). Efficient and effective action regulation may be impaired by the intrusion of distracting thoughts, cognitive overload, and attention problems that reduce the accuracy of plan execution.
Finally, the last step of the cyclical action sequence entails that individuals process feedback that may signal to them that the goal has been attained or not, and that the goal may need to be revised or dropped (i.e., goal disengagement; Haase, Heckhausen, & Wrosch, 2013). Feedback can be internally or externally generated and provides workers with goal-relevant information (e.g., discrepancy between ideal and current state, or progress made). Feedback can be more or less detailed and timely, and it can be either positive or negative. Similar to behavioristic and social-cognitive theories (Bandura, 2001), action regulation theory suggests that positive feedback is beneficial in terms of maintaining or repeating behavior. In contrast, the theory proposes that negative feedback is a useful device to stimulate and facilitate learning, innovation, and personal development, as long as it is task related and provides clear information (Frese & Keith, 2015; Kluger & DeNisi, 1996). Feedback processing may occur during and after the execution of behavior. Anticipated feedback (i.e., feedforward, or people’s ideas and expectations regarding the feedback they likely would receive) and the feedback received during action execution are most important for efficient action regulation, because these forms of feedback can lead to immediate corrections of faulty actions (Hacker, 1998).
Hierarchical Structure of Action Regulation
In addition to the sequential process of action regulation, action regulation theory proposes that action is regulated on different mental levels. For instance, Hacker (1971) originally proposed three distinct yet interconnected levels, whereas Frese and Zapf (1994) described four levels of action regulation: the sensorimotor or skill level, the level of flexible action patterns, the intellectual or conscious level, and the level of meta-cognitive heuristics. These levels can be arranged along a dimension ranging from unconscious and automatized control of actions to conscious intellectual processes, and on another dimension ranging from muscular action to thought processes (Frese & Zapf, 1994). Action regulation at lower levels in the hierarchy is more situation specific, requires less cognitive effort, and movements are more elegant and parsimonious.
The hierarchical organization of these levels implies that action sequences on lower levels can be triggered and regulated by higher levels. For instance, the sequence of observable behaviors at the lowest level (e.g., cutting vegetables in the kitchen) follows from a higher-order goal and planning (e.g., preparing a meal). These hierarchies are relatively weak, however, such that higher levels do not completely determine action regulation on lower levels, and results obtained at lower levels may lead to changes at higher levels (e.g., cutting one’s finger leads to a change in goals; Frese & Zapf, 1994; Hacker, 2003). In addition, over time and with experience, action regulation can be “shifted” from one level to another. For instance, when actions are automatized with practice in a redundant environment (e.g., operating a truck), they are shifted to the lower sensorimotor level or level of flexible action patterns that do not require attention and cognitive effort (Lord & Levy, 1994). In contrast, when actions need to be better understood or problems need to be solved (e.g., after an error has occurred), action regulation can be shifted to higher intellectual levels that require conscious attention and concentration.
At the sensorimotor or skill level, highly automatized movement patterns and cognitive routines are regulated (e.g., typing on a keyboard, driving a car). These processes are not associated with independent and conscious goals but are usually triggered by regulation processes at higher levels. However, consciously changing or interrupting these automatized action programs requires cognitive effort. Feedback at this level involves automatically generated kinesthetic and proprioceptive signals regarding motor movement coordination.
The level of flexible action patterns entails action regulation based on automatized schemata or scripts that can be either conscious or semiconscious (e.g., performing a routine medical checkup, serving a customer). At this level, workers process information from the environment according to well-established rules. Flexible action patterns can be activated from memory based on only a few signals from the environment, and they are then typically carried out as a whole without the investment of much cognitive effort. Moreover, the action programs can be flexibly adapted to specific situations (e.g., different patients or customers).
At the intellectual level, employees consciously regulate new or complex actions. This entails the development and selection of new and challenging goals and detailed action plans. Feedback processing at this level requires the analysis and evaluation of novel and complex information. While action regulation at the intellectual level requires attention and cognitive effort, it can be routinized through practice and shifted to lower levels of action regulation.
Finally, the level of meta-cognitive heuristics (which was not explicitly included in Hacker’s, 1998, original work) involves the use of more abstract, less task-oriented templates, strategies, and heuristics to guide action regulation (Frese & Zapf, 1994). These meta-cognitive heuristics enable individuals to solve similar problems in an efficient and effective way. For example, workers could use selection, optimization, and compensation strategies to deal successfully with high job demands and limited job resources, and to invest their personal resources optimally (Baltes & Baltes, 1990; Moghimi, Zacher, Scheibe, & Von Yperen, 2017).
Complete Tasks and Action
A core concept in action regulation theory is the notion of complete (versus partial or fragmented) tasks and actions. Complete tasks and action entail that workers regulate their actions across all five phases of the action regulation sequence as well as at different and alternating mental levels of action regulation (a related concept in job characteristics theory is “task identity”; Hackman & Oldham, 1976). For example, instead of merely executing behavior, workers are also involved in preparatory activities (i.e., goal and plan development and selection, requesting and retrieving relevant information) as well as feedback processing (Hacker, 1986). With regard to the hierarchical structure, complete tasks and actions require action regulation on the sensorimotor level, the level of flexible action patterns, the intellectual level, and the meta-cognitive heuristics level. As complete tasks require high levels of decision making, responsibility, and learning, they are more likely to contribute to worker health, well-being, and positive development in the work context (Hacker, 1986; Hackman & Oldham, 1976).
Action-Oriented Mental Model and Foci of Action Regulation
Over time and with increased experience, workers develop action-oriented mental models that include cognitive representations of the input conditions, goals, plans, results of action, and knowledge about boundary conditions of action at different levels of the action regulation hierarchy (Frese & Zapf, 1994; Hacker, 1985). An action-oriented mental model contains unconscious movement schemata, routinized yet flexible action schemata, representations of complex and conscious intellectual processes, and generalized meta-plans and heuristics. These elements across the four levels of action regulation constitute the knowledge base of action regulation. Action-oriented mental models guide workers until the action sequence is completed. The accuracy and level of detail of action-oriented mental models determines the efficiency and effectiveness of action regulation (Frese & Zapf, 1994).
Three different foci can be in the foreground of action regulation (Frese, 2007; Zacher & Frese, 2018). A focus on the task entails that workers analyzes the task content (e.g., redundancy of elements) and context (e.g., opportunities to perform). A strong task focus links task-related goals with relevant plans and behavior, as well as task-relevant feedback. Therefore, a strong task focus is associated with high efficiency and effectiveness of action regulation.
A focus on the social context of action regulation involves that workers consider how other people or groups may influence the processes of goal development and selection, mapping the environment, planning, monitoring of execution, and feedback processing. A focus on the social context can facilitate or constrain the efficiency and effectiveness of action regulation, depending on the nature and importance of social relationships. For instance, research on self-monitoring (Snyder, 1974) has suggested that a social focus during action regulation can improve task performance, whereas research on emotion work, particularly emotional demands and dissonance, suggests negative effects of a social focus during action regulation (Zapf, 2002).
Finally, a focus on the self during action regulation means that workers concentrate on the implications of their actions on the self (e.g., emotions, self-beliefs). Research suggests that self-regulatory processes can have positive effects on work outcomes (Latham & Locke, 2007). At the same time, a self-focus may distract from the task at hand and thus have a disruptive function during action regulation (Kluger & DeNisi, 1996; Sonnentag, 1998).
Theoretical and Practical Implications of Action Regulation Theory
Action regulation theorists have suggested that actions in the context of monotonous work tasks can lead to impaired health and well-being (Hacker & Richter, 1984). At the same time, researchers have acknowledged that actions can be important contributors to “personality development,” which is conceived broadly to include not only changes in narrow personality traits, but also positive changes in knowledge, skills, abilities, and other factors such as self-efficacy beliefs and control orientations (Bandura, 1986; Leontjev, 1978). Accordingly, action regulation theory has several important implications for work design and individual workers (Frese & Zapf, 1994; Hacker, 2003). In the following, we focus on theoretical and practical implications for work design, strain and well-being, learning and development, and successful aging at work (for additional implications, see Frese & Zapf, 1994; Zacher & Frese, 2018).
First, the complexity and completeness of tasks (i.e., level of task-related challenge) determines the extent to which action regulation contributes to positive personality development. Complete tasks enable workers to experience different phases of action regulation and to regulate actions at different mental levels. Thus, complete tasks can help improve competencies and motivate workers (Frese & Zapf, 1994; Hackman & Oldham, 1976). In contrast, partial or fragmented tasks are problematic because they do not allow workers to make use of different skills and abilities, which can lead to losses in competencies and feelings of boredom and demotivation over time (cf. “use-it-or-lose-it hypothesis”; Salthouse, 2006).
Second, the design of work tasks also has implications for workers’ experienced strain and well-being. Action regulation theorists have argued that to reduce strain and improve well-being, work needs to be designed such that it provides workers with challenging tasks (i.e., regulation requirements) and control (i.e., regulation possibilities), as well as reduced stressors in the work environment (i.e., regulation problems; Zapf, 2002). Action regulation theorists further distinguish between three broad categories of work-related stressors that lead to action regulation problems (Frese & Zapf, 1994). Regulation obstacles are events or conditions that make it difficult or impossible to attain a goal (e.g., interruptions, lack of information or equipment). Regulation uncertainty may be due to a lack of knowledge or available information on how to attain a goal, which plan is most likely to be successful, and whether feedback is useful. Finally, overtaxing regulation describes a situation in which work demands are too high (e.g., time pressure) or signals are too intense (e.g., information overload), disrupt the action sequence, and cause strain and lower well-being (Frese & Zapf, 1994).
Third, action regulation theory further has implications for learning and training in work and organizational contexts (Frese & Keith, 2015). Learning and training lead to improved and more differentiated action-oriented mental models, which are important prerequisites for efficient and effective work behavior. So-called superworkers have superior knowledge and skills, a deeper understanding of tasks, use more active and long-term strategies, and structure their work situations so that they receive useful feedback. In addition, superworkers are more sensitive to relevant signals from the environment and perceive signals, differences between signals, and errors more accurately (Hacker, 1985). At the beginning of learning processes, actions are regulated on the conscious intellectual level. Over time and with practice in redundant work environments, action regulation shifts to lower levels for more automatized processing and routinized actions. Establishing action regulation routines allows for additional cognitive operations to be performed at higher levels (e.g., creative thinking), because automatized operations do not require a lot of attention (Gielnik, Frese, & Stark, 2015; Ohly, Sonnentag, & Pluntke, 2006). Action regulation theory has been used to develop training programs in the domains of leadership (Frese, Beimel, & Schoenborn, 2003) and entrepreneurship (Gielnik, Frese, Kahara-Kawuki, et al., 2015; Glaub, Frese, Fischer, & Hoppe, 2014). This research has shown that efficient and effective action regulation contributes importantly to leadership success and the startup of new businesses.
Finally, researchers have integrated action regulation and life-span developmental theories to better understand and derive implications for successful aging at work (Frese & Stewart, 1984; Zacher, 2015; Zacher et al., 2016). For instance, in their “action regulation across the adult lifespan” (ARAL) meta-theoretical framework comprising 35 testable research propositions, Zacher and colleagues (2016) analyzed workers’ action regulation from a life-span developmental perspective to explain the effects of age-related changes in cognitive abilities (i.e., fluid and crystallized intelligence), personality, socioemotional goal priorities, and contextual factors on the regulation of action across different phases and levels. Furthermore, these researchers analyzed aging and development in the work context from an action regulation theory perspective. To this end, they explained how workers’ action regulation may impact their developmental outcomes, including age-related changes in cognitive abilities and personality characteristics. For example, based on the use-it-or-lose-it hypothesis from the life-span developmental literature (Salthouse, 2006), they suggested that complete tasks and actions may help older workers maintain cognitive abilities and openness to experience with increasing age. Zacher and colleagues (2016) further integrated concepts from action regulation theory with life-span theories of motivation, including the model of selection, optimization, and compensation (Baltes & Baltes, 1990) and the motivational theory of life-span development (Heckhausen, Wrosch, & Schulz, 2010), as well as theories on socioemotional experience, including socioemotional selectivity theory (Carstensen, Isaacowitz, & Charles, 1999) and the strength and vulnerability integration model (Charles, 2010).
This article reviewed the history, basic concepts and tenets, and theoretical and practical implications of action regulation theory. Developed in the 1960s and 1970s, action regulation theory is an important basic theory for applied psychology, and particularly industrial, work, and organizational psychology. The theory provides an integrative framework that describes and explains the sequence and structure of action regulation, as well as the notion of complete tasks and actions. Moreover, the theory examines the role of action-oriented mental models and different foci of action regulation (on the task, social context, or self) in work and organizational contexts. Action regulation theory has important implications for work design, worker stress and well-being, and learning, as well as positive development and successful aging in the work context.
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