"A
Behavioral Theory of the Firm”
M. Cyert and J. G. March
Review by Tom Issaevitch
Introduction
As the title implies, this book is concerned with how firms behave and make decisions. The
authors point out that the standard profit maximizing micro-economic prescription for firm
behavior
max p. y  q.x  K
x, y , K
subject to f ( x, y, K )  0 (where p is the output price vector, y the output quantity vector, q
the input price vector, x the input quantity vector and f ()
the production function) is
untenable. Firms do not know their own production functions or their competitor’s production
functions with certainty. Firms do not know the future market demand curve, prices or any other
quantity of interest. Even with the recent introduction and wide scale adoption of more accurate
cost allocation schemes, ERP systems, large-scale databases and, sophisticated econometric
models, there remains one essential area of uncertainty (as opposed to quantifiable risk) --- the
behavior of the firm’s managers.
In the next section, I describe the main points of the book regarding firm behavior. In the
following section, I describe the results of the author’s models. Next, I consider the implications
of the author’s ideas to accounting. In the final section, I discuss how Cyert and March hold up
in the year 200.
Firm and Manager Behavior
There are three essential components that must be present in any decision: the goal, the possible
actions and the available information. It is important to note that these three components are
each bi-causally connected, i.e., feedback to each other.
The goals and possible actions
associated with a given decision clearly dictate the type of information one would want.
However, given that one almost never has all relevant information, the reverse causality also has
importance. The cost and availability of information determines the types of goals and actions
that a firm could consider having. In general, this is an extremely complicated problem to
optimize.
A main concern of The Behavioral Theory of the Firm is how the firm handles the biases,
self-interest and incompleteness of the information. In effect, firms respond to this imperfect
world by restricting the decision methodology, actions, actors, and goal creation. The authors
use the terms “adaptively rational system” as opposed to “omnisciently rational system” to
describe the firm and its reaction to shocks (which would not exist if the firm were omniscient).
An important feature of this view is that firms spend less time predicting, planning and
optimizing and more time achieving stability and trying to eliminate the need to predict.
However, this “sub-optimal” behavior does not imply simplicity. Quite the contrary, adaptation
and non-omniscience imply contingent actions, contingent goals and contingent organizational
structure.
With respect to the decision methodology that firms employ, firms rarely optimize. First,
they generally search for alternative actions and information only if an acceptable solution is not
readily apparent. With respect to goals (about which more will be discussed below), firms rarely
attempt to optimize expected profit or any version of such. Instead, a great deal of focus is spent
eliminating uncertainty or it’s effects, especially uncertainty that derives from the biases selfinterest introduces into the information decision-makers receive. Interestingly, this conservatism
persists even though, empirically, Cyert and March provide evidence that human beings are quite
good at anticipating and accounting for information biases.
Because the only conscious thought arising from firms comes from the employees and
because such employees often have conflicting goals, Cyert and March point out that the very
idea of goal creation in an organization cannot be taken for granted. Instead, goals are arrived at
through the joint negotiation of the employees of the firm. Thus, far from being static or abstract
(“this firm makes cars”), organizational goals depend on the characteristics, goals and abilities of
the employees. That a firm may have a long-term identity (“it makes cars”) depends on one of
the goals of current employees being to choose new employees who fit in with current goals
(presumably because they like making cars).
Even if the individual preferences of a firm could be perfectly aligned, the presence of
uncertainty and consequent need for adaptation render the notion of `firm goal’ problematic. In
general, there is no simple way to operationalize an overall firm goal into a series of harmonious
sub-goals. Because this decomposition is imperfect, there will inevitably be conflict between
these sub-goals. For example, two possible sub goals to profits maximization are cost cutting
and lowering price to increase demand. However, since cost cutting may result in lower quality,
demand may actually fall.
Models
Despite whatever connotations the word “Behavior” in a title may invoke, this is not a touch and
feely book. After describing the reasons for a rule of thumb/ain’t broke don’t fix it approach to
decision-making, the authors provide two mathematical models of decision-making and support
them with empirical data.
The model first is a duopoly model in which two firms (an incumbent and a younger
“splinter”) predict demand on competitor behavior using a “simple” auto-regression model for
conjectural variations (with later knowledge, we know that such nonlinear models may behave
very non-trivially, even if their simple structure would indicate otherwise). The model did quite
well in predicting the results of U.S Can (incumbent) and Continental Can (splinter) over the
long stretch 1913-1956.
The second model is that of price-setting and output determination under stochastic
demand. The model showed remarkable ability to predict the pricing of a firm over a two-year
period. I am still puzzled by this close agreement given the difficulty of the task.
Impact on Accounting
The accounting system provides the information on which managers are evaluated and make
decisions. Cyert and March demonstrate that actual firm decision-making differs significantly
from the economic-based ideal of profit maximization. It therefore follows that economic-based
accounting systems (if present) may need to be modified to support the satisficing decision style.
Moreover, since this change in decision method stems primarily from the information quality due
to manager behavior (and not the accounting system --- if it were the accounting system, one
would change the accounting system rather than change the decision goals and methods), the
accounting system must have a strong manager monitoring function.
As mentioned above, adaptation and non-omniscience imply contingent actions, contingent goals
and contingent organizational structure. Thus, the organization is in constant flux and needs to
contain an extensive infrastructure to support and monitor the changes conditionality implies
while, at the same time, providing mechanisms that promote long-term stability. The AIS is a
crucial tool in this change infrastructure. For control and monitoring, we have on the fly cost
allocation, variance analysis and all other aspects of managerial control. For learning, the AIS
constitutes the historical repository of all past budgets (i.e., a monetary view of past decisions)
and transactions (i.e., the consequences of prior decisions) and studying the relationship between
the two facilitates learning. Finally, with regard to stability, historical data can yield long-term
benchmarks and standards, i.e., an “operating point” around which a stabilization goal can be
formed.
The nature of organizational goals also has a significant effect on the requirements of an
AIS. In particular, the accounting system must allow progress towards goals to be measured.
One cannot cut costs without first knowing what costs are.
Recent Developments
This book was first published in 1963. Since then, a profound information revolution has taken
place, and one may wonder how well Cyert and March hold up. Two aspects hold up quite well:
human interactions are still well beyond the capabilities of any accounting or information system
and rules of thumb remain a crucial element of control under uncertainty. On the other hand, we
now have a better understanding of just how complicated rules of thumb can be and it is not clear
(to me, at least) that implementing such rules is easier or superior to economic-based
optimization approaches. I now address the issues of control under uncertainty and rules of
thumb in more detail.
Spurred by engineering and the military, a systems revolution and manner of thinking
began in the 1950’s and it is clear that this influenced Cyert and March. By the 1960’s, control
of parametrically known stochastic linear systems was well understood.
Moreover, the
algorithms derived had significant robustness properties that led to optimistic beliefs concerning
the control of complicated (i.e., large, nonlinear and possibly uncertain) systems. However, this
optimism (particularly that which was placed in artificial intelligence) was misplaced.
Over the last three decades, “adaptive control” has emerged the main tool used to control
complicated uncertain systems. One of the interesting ingredients of adaptive control is the
wide-spread use of ad-hoc rules in lieu of a more rigorously based strictly Bayesian approach.
This has been necessitated by the extreme complication of the Bayesian approach and fits Cyert
and March’s insight to a tee. Thus, even the mathematical end of the spectrum has adopted a
rule of thumb approach. Even more support for Cyert and March’s position comes from the field
of robust control (now often viewed as a sub-field of adaptive control) in which the focus of
controlling uncertain plants shifts from optimality to stability.
On the other hand, rules of thumb have their own problems --- particularly when, as is
done often in The Behavioral Theory of the Firm, the decision variables become discrete. In
general, discrete decisions are more difficult than their continuous counterparts (often NP hard,
in fact) and many procedures that work on small toy problems fail spectacularly on larger
problems. While I do not argue with Cyert and March’s call to keep things simple, I merely
point out that choosing the right (or even reasonably good) rules of thumb may prove to be just
as hard as profit maximization.
Another difficulty with using nonlinear models (and the threshold models the authors use
are nonlinear) is that of structural instability and chaos. The former problem makes model
selection difficult. The later problem is probably generic when one considers that the models are
designed to operate under fluctuating demand.
It is quite common that so-called driven
nonlinear systems behave chaotically and management science has certainly become aware of
this fact.
Finally, I give a few comments on the relation between firm structure and the need for
adaptability. It is well known that most firms are hierarchical. The common explanation,
hierarchies division of labor (with particular emphasis on division of skills and power) and span
of control, is a static one. However, because hierarchies are well suited to adaptation, one could
also provide a dynamic explanation. By well suited to adaptation, I mean in a structural sense --hierarchies are tree-structures and the easy addition or deletion of nodes in a tree (i.e., changes in
the tree structure such as adding a subdivision or merging two subdivisions) has been much
exploited by computer science.
“Complex Organizations”
C. Perrow
Introduction
This book is concerned with how the interaction between individual behavior, organizational
structure and, the environment leads to firm behavior in complex organizations (although much
of the discussion concerns corporations, other types of organizations are considered). A major
theme of the book is the importance of considering all three levels and the interaction between
them. But the author is also concerned with within level descriptions and spends a good deal of
time describing and strongly criticizing the many prior management theories that focus attention
on single given level or on two adjacent levels. As the book progresses, there is less criticism
and more Perrow, but it is only in the final chapter that Perrow is mostly presenting his own
theory. The rest of this review is organized as follows. In the next section, I discuss Perrow’s
thesis in more detail. I conclude with a brief section analyzing the book in light of what we have
learned in the three decades since it’s initial publication.
Book Outline
Perrow starts off with a general introduction to the types of transaction and agency problems that
bureaucracy solves. First, by bringing external functions under internal control, one avoids
transaction costs. Once internalized, anonymity, independence and professionalism of hiring
reduce the problems of nepotism (which leads to power cliques through employees owing their
hirer a debt) and bigotry. Perrow also describes incentives and the consequences of poor
contract design. An interesting example is that of outsourcing tax collecting and allowing the
agent to keep collections above a certain level. This obviously leads to an incentive to overtax
mitigated only by the tax collectors fear of retribution. A contract that avoids this problem is the
straight salary --- the entrepreneur (tax collector) is now a bureaucrat.
Perrow then describes various features of organizations and institutions (henceforth often
referred to as firms for brevity). They have hierarchical structure and control, overt and covert
rules and procedures that operationalize firm knowledge and learning.
Firms also have
individuals with their own aspirations. While firms have the capacity to act rationally in an
uncertain environment (Bernard would say they are the only elements of society capable of such
rationality), this does not mean that they are optimally efficient or that individuals cannot subvert
them to their own ends. In particular, there is a well-caricatured tendency of the “ins” to
preserve their status even at the expense of overall firm wellfare.
Perrow spends some time defending hierarchy. First, hierarchy is essential for task
specialization (at least for human agents). Perrow also points out that hierarchy does not
preclude decentralized decision and, in fact, can respond to external events flexibly with, e.g.,
task groups. He also makes an interesting observation that tall thin hierarchies actually may have
more decentralized decision-making. Essentially structure (hierarchy) follows function, rather
than the converse, and so flat hierarchies are flat precisely because it is easy for a manager at one
level to control many employees at the next level down. This implies not only that the tasks
these employees perform must be simple and easily monitored but also that it is not possible for
these employees to have much intellectual input into the firm (who has the time to listen?).
Part of the image problem hierarchies face is caused by the fact that their wide-spread
introduction and the invention of scientific management went hand in hand. Since scientific
management was a main impetus for the wide adoption of hierarchies (of course, hierarchies
existed before scientific management) hierarchies may be tainted with the worst aspects often
attributed to scientific management, e.g., worker as robot or Bernard’s belief that they required
little pay. Thus, as a counter point, Perrow maps out in detail the evolution of views of the
worker from robot to intelligent human. Hierarchy is still needed.
After this introduction, Perrow proceeds to analyze a number of different organizational
and managerial theories. In general, as he progresses further through the book, Perrow’s distaste
for the theories he describes decreases. His progression also follows the three divisions he
studies: human, structure and the environment. The models or schools of thought he reviews are:
the human relations model; the neo-Weberian model; the institutional school.
The Human Relations School
The human relations school may be caricatured as “happy workers are productive
workers”. Perrow goes to great lengths to point out that all evidence put forth to link worker
satisfaction to productivity fails on closer inspection (including a number of early metaanalyses). There are simply too many confounding variables. More importantly, the human
relations school suffers from its too narrow focus. The confounding variables are not random,
but rather determined by firm structure and the environment. Despite Perrow’s objections, the
human relations model still (as far as I can tell) holds considerable importance management
theory. In part, this is due to the improved results that have been made possible by recognizing
the importance of controlling for environmental factors.
The Neo-Weberian School
The role of the individual in firms is an important focus of the early part of the book.
Perrow dismisses the Bernardian view that leaders get their authority and worker cooperation
from moral authority. He also dismisses the Weberian view that workers are simply cogs in the
firm’s hierarchical machine of structure and rules and for whom cooperation is not an issue. The
neo-Weberian school attempts to fill in the machine with human beings.
In Simons model, we have introduced the now famous “boundedly rational” man. The
firm’s structure and standards (a “smoothly oiled machine”) combined with the firm’s goals and
the instructions of it’s leaders provide aids that allow managers to cope and make satisficing
decisions. In particularly, stability (with some slow adaptation allowed) becomes an important
goal in the face of environmental uncertainty. Goal alignment is achieved through bargaining
among the managers and the corresponding proper incentives. Most control is unobtrusive, in
part passively enforced by the firm’s structure and, in part enforced by controlling the way
employees think.
The neo-Weberian school goes a long way towards a theory of organizational behavior.
However, for the most part, the neo-Weberian school does not consider environmental factors.
There are exceptions, e.g., Cyert and March, who recognize the importance of an uncertain
environment in leading to organizational adaptation and the need for an appropriate structure and
behavior. However, at the level of their analysis, the environment is just some random black
box. They do not classify or study a range of environments.
The Institutional School
The last set of models Perrow critiques belong to the institutional school. The main idea
is that the function of the organization determines its structure. Perrow points out the danger of
this feature of firms. If too much function has been passively relegated to letting the structure
handle it (i.e., the firm operates largely on autopilot), the firm will be slow to recognize and
adapt to change. Thus, in particular, unobtrusive controls are not enough. Perrow focuses a
good deal of attention on organizations that have “taken on a life of their own”.
The institutional school backs up its main idea with an extensive array of field data
documenting organizational failures arising from structure. It also makes an effort to identify the
important components of firm morphology.
The final contribution of the institutional school that Perrow chooses to highlight is the
identification of the importance of the environment. Not all firms ossify and fail to adapt to
environmental changes --- some adapt quite well. Probably a good deal of the difference is
caused by the uncertainty in the environment at the time the firms structure was established (an
unchanging original environment will probably result in an in-adaptable structure) and how well
the firm adapted it’s original structure to the original environment (a close match will also
probably lead to poor firm adaptability). While Perrow applauds this understanding of the
importance of the environment in understanding structure, he faults the school for not
recognizing the role organizations have on the environment. This fact, which every marketing
major would applaud, is the subject of Perrow’s final chapter.
The Environment
Perrow does not offer a general theory of environment --- structure --- human interactions.
Instead, his chapter on the environment starts with of a number of industry case studies.
However, he then goes on to study more abstractly a specific type of environment --- the network
of firms that have developed under post war international capitalism.
Networks, in the form of economy-wide input-output models, were nothing new to
economics in 1972. However, these network models generally stayed at the level of the network
and did not consider the effects of inter-firm networks on firms or visa-versa.
Perrow
emphasizes the interaction (feedback, basically) between the two different levels.
The Current State
The importance of the overall environment is now recognized in a number of different areas. It
may even represent a paradigm shift in artificial intelligence (AI) in which decades of failure are
now believed to be explained by the fact that AI had ignored context. Likewise, the application
of a broad arsenal of graph-theoretic techniques to problems of social science has been a minor
industry over the last few decades. Most of these analyses have been static ones, however, (e.g.,
clique decompositions, percolation thresholds) and I suspect Perrow would not be satisfied (nor,
for that matter, Cyert and March with their emphasis on adaptation). Studying dynamic networks
has been a pet project of mine and I believe such studies will find many new insights.
Ironically, recognizing the importance of environmental factors has allowed the human
relations school to improve its methodology in searching for motivating factors. Likewise,
behavioral research (neo-Weberian, to Perrow) has had some success in identifying and
understanding the heuristics and biases used by managers (and others). It is clear that the field of
social science has benefited from Perrow’s work.