Control Theory

Careful observers of humans and other organisms noticed long ago that certain variables that should vary as environmental conditions change actually do not vary much within the organism. For example, store shelves remain stocked despite customers buying products. Control theory arose as one explanation for the mechanism that keeps variables stable.

Industrial and organizational psychologists find the explanation provided by control theory very useful for conceptualizing and understanding a great number of work-related phenomena.

The specific mechanism described by control theorists contains three parts:

  1. A function that translates the state of some variable (e.g., the state of stock on shelves) into a perception or signal that can be compared with a desired perception or reference signal (e.g., fully stocked) represented within the organism
  2. A second function that does the actual comparison, subtracting one signal from the other
  3. Positive differences from the second function, called the error signal, that are then passed to the last function, which translates the error signal into actions (e.g., restocking shelves) on the variable in question

If the control mechanism is operating properly, the actions bring the variable in line with the desired perception of that variable. That is, the actions reduce the discrepancy (i.e., error) between the perception of the variable and the desired state of the variable. As a result, the variable remains near the desired level despite outside influences, called disturbances, on the variable.

Anyone who has studied psychology is likely to be familiar with this mechanism as it applies to physiological variables such as hunger and thirst control. In this context, the term homeostasis is generally used to refer to the sameness (homeo) in state (stasis) of a variable over time. Others might be familiar with the concept through engineering circles. For example, it is the mechanism underlying temperature control systems in your home, as well as the systems that make “smart” appliances work, such as cruise control in automobiles or the popcorn setting on microwave ovens. In this context, one might hear the term cybernetic—a term coined by the mathematician Norbert Wiener, who described the mechanism formally with mathematics—or negative feedback loop (because the process reduces the error signal). Within the context of industrial and organizational psychology, all of these terms have been used, but the mechanism most often operates within what we call theories of self-regulation.

In psychological renditions of control theory, the basic control system (defined by the three functions described previously) is conceptualized within hierarchies of systems, and it is from this configuration that some of the more interesting phenomena emerge. Specifically, three additional elements are described in these psychological versions:

  1. The “actions” of higher-level control systems determine the reference values for lower-level systems, and the perceptions from lower-level control systems feed into higher-level control systems, allowing them to create more abstract and complex perceptions.
  2. The reference signals can be diverted back to the sending system as a means of anticipating or estimating the effects of the system’s actions. Usually this is called a feed-forward process; it is control theory’s conceptualization of human thinking.
  3. Some control systems monitor the operation of other systems and act on those systems by changing the three kinds of core functions described earlier. This is control theory’s conceptualization of learning.

With these additional elements, control theorists hope to understand a wide range of phenomena in psychology. Likewise, within the field of industrial and organizational psychology, control theory and its variants have been used to address many issues. For example, human factors researchers are interested in the processes by which humans control aspects of their immediate physical environment. Control theory has been used as a significant explanatory tool in that domain. In addition, control theory has been applied to understanding stress and affective processes within work domains. However, control theory’s most prominent presence in industrial and organizational psychology relates to motivation and goal-striving behavior within organizations.

Control Theory as a Theory of Motivation

To understand control theory’s relevance to motivation, one need only substitute the control theory notion of internally represented desired state (i.e., reference signal) with the term goal. Thus, control theory provides an explanation of how individuals achieve and maintain their goals, whether individuals bring these goals with them or acquire them from the work context. Indeed, another situation in which control theories are used is to describe when managers and supervisors are likely to communicate goals and desired behavioral patterns to their subordinate employees.

Elsewhere on this site, you can read about the relevance of goals to understanding human motivation and how goals have practical implications for performance and other organizationally relevant outcomes (e.g., absenteeism). The literature on goals— most developed without the benefit of control theory—has demonstrated robust, positive effects on motivation and performance for interventions based on goals and their properties. This has led some researchers to seek explanations for these goal effects (i.e., understand why goals have the effects they do) and to understanding how individuals coordinate the pursuit and maintenance of multiple goals more or less simultaneously. Researchers argue these understandings may provide better or unique applications that have not yet been considered, and control theory is considered a major source for developing these understandings.

Alongside goals, another concept that has received a great deal of attention is feedback, a complex concept. In industrial and organizational psychology, feedback generally refers to the information that supervisors or others give employees regarding their performance or actions. This kind of feedback has long been considered important in organizational contexts, and it is believed that interventions that increase feedback boost performance. Yet in this case, the empirical evidence is mixed, though generally positive (i.e., feedback interventions generally improve performance). Control theory has been used here as well as a vehicle for understanding the processes by which feedback has its effects (both positive and negative). Meanwhile, feedback is sometimes actively sought by employees; control theory is used to understand why and when that happens.

Across all applications, the concept that has received the most attention is the notion that information (i.e., feedback) may indicate discrepancies between perceptions and goals. These discrepancies, in turn, drive behaviors and the allocation of resources to reduce the discrepancies. For example, a perception of uncertainty regarding one’s performance is presumably responsible for feedback-seeking behavior among individuals who desire certainty. The information received from that feedback-seeking episode might, if it creates discrepancies with other work goals, motivate increased work.

However, given the complexity of work contexts, many times behaviors and the allocation process result in conflicts, such that individuals may behave in ways that take them away from or steal resources needed for other goals. Thus, a person’s attention might be drawn to one goal in his or her hierarchy, although it is needed in another. If both goals are required for effective performance, it is in the interest of the employee and the employers to figure out how to balance or regulate competing demands for resources. Indeed, at this point, researchers are interested in simply understanding how control systems regulate (i.e., self-regulation). Worrying about how to optimize this regulation for specific outcomes requires a more thorough understanding of the processes involved.

Controversies Related To Control Theory

Although control theory has many adherents and variants within industrial and organizational psychology, it also has some strong opponents. One source of opposition may stem from its success. That is, the multiple uses and phenomena to which control theory has been applied have produced so many variations that critics complain it is difficult to know what control theory is and what it is not. Moreover, these variations often incorporate ideas and concepts used by other theories, leading critics to wonder whether control theory makes any unique contribution to the theoretical landscape. For example, goals were in psychologists’ lexicon before control theory was brought to the field; thus, some argue it is not useful to mix psychological constructs with the control theory labels commonly used by engineers. Control theorists counter that the theory’s unique contribution is to explain why goals have the effects they do, not necessarily what the effects are.

Recently, control theorists have concerned themselves with the concept of self-efficacy, a central construct in social cognitive theory. Self-efficacy, or the belief in one’s capacity to perform or act at a given level, is not a construct that is described within any version of control theory. However, self-efficacy measures capture the results of the feed-forward process described within control theory. Moreover, the results of the feed-forward process, as it is used within control systems, lead to similar—but not identical— predictions that social cognitive theory describes for self-efficacy. Yet the points of divergence are what theoreticians find most interesting, and they may be practically relevant as well. In this case, social cognitive theory predicts strong positive effects. In contrast, control theory predicts weak negative effects for self-efficacy on motivation and performance during goal striving when goals do not change and when feedback is ambiguous. Recent research supports control theory’s predictions, which other researchers are now seeking to verify.

Control theory has also been criticized for its complexity. Control theory is a dynamic theory of processes. Most theories in industrial and organizational psychology describe the relationships between variables, generally across individuals rather than across time. Variables that describe relationships across time do not specify the processes by which the relationships emerge. Dynamic process theories explain why factors covary (or don’t when it seems they should) over time. This makes control theory a very different kind of industrial and organizational theory. Indeed, this difference may be one of the main reasons it is appealing to so many researchers (i.e., it can be used to explain phenomena that other theories are not in a position to explain). Yet it is also difficult to reconcile with how one compares, contrasts, and tests typical theories in industrial and organizational psychology. Moreover, evidence has emerged that humans have difficulty predicting dynamic (i.e., changing) phenomena. Thus, trying to mentally simulate (i.e., think through) a dynamic theory’s predictions about dynamic phenomena may be difficult—all the more reason for such a theory, say its proponents.

The preceding paragraph implied that the complexity of control theory arises from the limitation of human minds, particularly those without much experience thinking about phenomena dynamically. However, it seems that by most criteria, control theory models become extremely complex as the number of control systems used to explain a particular phenomenon increases. Indeed, control theorists, presumably facile at thinking dynamically, either describe relatively simple models (single or only a few control systems) or render the models mathematically (i.e., computational models) that can be simulated. The latter approach is likely necessary because the control theory explanation is too complex to think through. One needs the computation tools of simulations to follow the implications of the control systems described. This is what engineers do, and psychologists are just beginning to use this process (especially in human factors research). It remains to be seen how useful the simulation tool will be to researchers examining motivation or to those wishing to apply control theory to specific organizational problems.

Control theory has a long history outside psychology. Many think it can have a long and fruitful history within the field of industrial and organizational psychology as well. How this

References:

  1. Austin, J. T., & Vancouver, J. B. (1996). Goal constructs in psychology: Structure, process, and content. Psychological Bulletin, 120, 338-375.
  2. Bandura, A., & Locke, E. (2003). Negative self-efficacy and goal effects revisited. Journal of Applied Psychology, 88, 87-99.
  3. Carver, C. S., & Scheier, M. F. (1998). On the self-regulation of behavior. New York: Cambridge University Press.
  4. Jagacinski, R. J., & Flach, J. M. (2003). Control theory for humans: Quantitative approaches to modeling performance. Mahwah, NJ: Lawrence Erlbaum.
  5. Powers, W. T. (1978). Quantitative analysis of purposive systems: Some spadework at the foundations of scientific psychology. Psychological Review, 85, 417-435.
  6. Vancouver, J. B. (2005). The depth of history and explanation as benefit and bane for psychological control theories. Journal of Applied Psychology, 90, 38-52.
  7. Wiener, N. (1948). Cybernetics; Or, control and communication in the animal and the machine. Cambridge: MIT Press.

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