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Journal ArticleDOI

Passing the Buck in the Garbage Can Model of Organizational Choice

TL;DR: The authors reconstructs Cohen, March and Olsen's Garbage can model of organizational choice as an agent-based model and adds another means for avoiding making decisions, that of buck-passing difficult problems to colleagues.
Abstract: We reconstruct Cohen, March and Olsen's Garbage Can model of organizational choice as an agent-based model. In the original model, the members of an organization can postpone decision-making. We add another means for avoiding making decisions, that of buck-passing difficult problems to colleagues. We find that selfish individual behavior, such as postponing decision-making and buck-passing, does not necessarily imply dysfunctional consequences for the organizational level.The simulation experiments confirm and extend some of the most interesting conclusions of the Garbage Can model: Most decisions are made without solving any problem, organization members face the same old problems again and again, and the few problems that are solved are generally handled at low hierarchical levels. These findings have an implication that was overseen in the original model, namely, that top executives need not be good problem-solvers.

Summary (3 min read)

1 Introduction

  • The Garbage Can Model of organizational decision-making proposed by Cohen, March and Olsen in 1972 (henceforth GCM) [4] is possibly the most widely cited article in simulation-based Organization Science.
  • In the original article, verbal theoretical statements are followed by a fairly detailed explanation of the corresponding lines of computer code, and these details entail important theoretical assumptions.
  • And that both assumptions and consequences are deeply rooted in organizational theory and practice.the authors.
  • The original GCM has a means for avoiding a difficult problem, which consists of attaching it to another opportunity for decision-making.
  • Section (2) describes the main features of the original GCM, while section (3) expounds their agent-based setting.

3 An Agent-Based Garbage Can Model

  • The computational model designed by Cohen, March and Olsen [4] has been criticized for being a loose mapping of the underlying theoretical narrative [1].
  • Given these deficiencies, all conclusions concerning the meetings of participants and problems do not emerge out of the theoretical assumptions but are hard-wired in the model [1].
  • The GCM has a feature that makes it quite ahead of its time.
  • Two decades in advance, the GCM was specified as an agent-based model, and the authors claim that an agent-based implementation is more faithful to the spirit of the GCM than the original procedural implementation of Cohen, March and Olsen [4].
  • Agents eventually move by one square during one simulation step, either north, east, west or south of their current position.

4 Theoretical Improvements

  • The first one concerns the structures that can be imposed upon the model.
  • The second one concerns the mechanism by which flights take place.

5 What to Look For

  • Cohen, March and Olsen concluded from their simulations that organizational decisionmaking is characterized by eight properties, of which the following five were confirmed by subsequent tests [4] [8] [9]: 8 1. Only a few decisions solve problems.
  • Organizations make themselves busy with a few problems that present them- selves again and again.
  • Others have been added in order to provide a better picture of the decision process: 9In previous publications [8] [9], where the authors aimed at reproducing an agent-based GCM that would be as close as possible to the original model, they were bound to use Cohen, March and Olsen’s twenty-one indicators.
  • The average life of blocked decision processes, of pairs opportunity-problem and of pairs participant-problems, measured in terms of simulation steps; .

6 The Simulations

  • The authors carried out simulations with 100 participants, 100 opportunities, 100 solutions and 100 problems.
  • Whenever opportunities, solutions and problems died, they were immediately replaced with agents created with the same initial conditions.
  • Ability, efficiency and difficulty are assigned according to this rationale.
  • Hierarchical decision structure, hierarchical availability structure and hierarchi- cal access structure, with ability, efficiency and difficulty assigned with the opposite criterium as above.
  • So the decision-makers who are on top of a hierarchy are the least able to solve problems, they apply inefficient solutions and they make themselves busy with the easiest among available problems.

6.1 The Random Anarchy

  • In the random anarchy, if both flights by postponement and flights by buck-passing are allowed, then flights by postponement outnumber flights by buck-passing (1,036.11 vs. 767.03).
  • So flights by buck-passing generate more blocked decision processes (5.52 if only flights by buck-passing are allowed vs. 2.86 if both flights by postponement and by buck-passing are allowed), which in their turn generate more flights by buck-passing, and so forth.
  • More decisions by resolution occur when these blocked decision processes are unlocked.
  • Decisions cause both opportunities and solutions to be replaced, decreasing the probability of meeting again the same opportunity or the same solution.

6.2 The Competent Hierarchy

  • With respect to the relative frequency of flights by postponement and by buck-passing, the behavior of the competent hierarchy is opposite to that of the random anarchy.
  • In particular, it does not seem to square with common wisdom that in the competent hierarchy passing the most difficult problems to the least competent participants — those at the bottom levels — has beneficial consequences for the organization as a whole.
  • It happens simply because the bars of figure (6) represent ratios of oversights to resolutions while the white bars of figure (5) represent percentages of oversights to total decisions.
  • The data show that, contrary to the random anarchy, both the number of meetings and the number of meetings with items that have already been met differ considerably between opportunities and solutions.

6.3 The Incompetent Hierarchy

  • The incompetent hierarchy, by design, runs contrary to common wisdom.
  • In the incompetent hierarchy, similarly to the competent hierarchy but contrary to the random anarchy, flights by buck-passing, either alone or in conjunction with flights by postponement, are more effective than flights by postponement in increasing the proportion of decisions by resolution (compare the two bars in the middle to the first one from the left).
  • On the whole it appears that hierarchies are generally not efficient in fostering decisions by resolution, although incompetent hierarchies can perform fairly well if both postponement and buck-passing occur.
  • These three ratios are repeated, left to right, in the case only flights by postponement are allowed (P), in the case both flights by postponement and flights by buck-passing are allowed (P, B), in the case only flights by buck-passing are allowed (B), and in the case no flights are allowed at all (–).
  • As in the competent hierarchy and the random anarchy, the reason for meeting the same problems more often than the same opportunities and the same solutions is that problems are only involved in decisions by resolution, whereas opportunities and solutions are involved in all decisions.

7 Conclusions

  • In fact, the authors found that the most efficient structure for the GCM is neither the kind of hierarchy suggested by common sense, nor the “organized anarchy”.
  • In fact, if decisions by oversight are important for obtaining legitimacy, then one may suggest that top managers should be good at obtaining legitimacy rather than at solving problems.
  • So one may speculate that organizations should possibly be designed on the basis of criteria that are apparently opposite to those suggested by common wisdom, namely, leaving those who are good at solving problems at the bottom of the hierarchy while promoting the poorest problem-solvers to the top.
  • In fact, this organizational arrangement reaches the highest ratio of decisions by resolution to decisions by oversight if both flights by postponement and flights by resolution are allowed, and in this arrangement flights are most effective in limiting the number of decisions by oversight that must be made at high hierarchical levels.

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Munich Personal RePEc Archive
Passing the buck in the garbage can
model of organizational choice
Fioretti, Guido
University of Bologna
4 August 2009
Online at https://mpra.ub.uni-muenchen.de/16977/
MPRA Paper No. 16977, posted 27 Aug 2009 12:18 UTC

Passing the Buck in the Garbage Can Model of
Organizational Choice
Guido Fioretti
University of Bologna
Alessandro Lomi
University of Lugano
August 4, 2009
Abstract
We reconstruct Cohen, March and Olsen’s Garbage Can model of organiza-
tional choice as an agent-based model. In the original model, the members of an
organization can postpone decision-making. We add another means for avoiding
making decisions, that of buck-passing difficult problems to colleagues. We find
that selfish individual behavior, such as postponing decision-making and buck-
passing, does not necessarily imply dysfunctional consequences for the organiza-
tional level.
The simulation experiments confirm and extend some of the most interesting
conclusions of the Garbage Can model: Most decisions are made without solving
any problem, organization members face the same old problems again and again,
and the few problems that are solved are generally handled at low hierarchical
levels. These findings have an implication that was overseen in the original model,
namely, that top executives need not be good problem-solvers.
Keywords: Organizational Decision Making, Garbage Can Model, Postponing De-
cisions, Buck-Passing
1

1 Introduction
The Garbage Can Model of organizational decision-making proposed by Cohen, March
and Olsen in 1972 (henceforth GCM) [4] is possibly the most widely cited article in
simulation-based Organization Science. It is also the best known example of a piece
of organizational theory developed through computer simulation. In the original arti-
cle, verbal theoretical statements are followed by a fairly detailed explanation of the
corresponding lines of computer code, and these details entail important theoretical as-
sumptions. Simulation results are presented as the implications of the theory, and the
code is made publicly available as an appendix.
However, in the subsequent decades the example of the GCM has been rarely im-
itated. A large parte of Organization Theory ignored Computational Science, and the
GCM itself has been seldom discussed in its computational details. Its conclusions
have been quoted as pertaining to a paradoxical world, and the GCM has been under-
stood as the prototype of what an organization should not be.
With this article we want to show that the GCM highlights surprising but logical
consequences of sensible assumptions, and that both assumptions and consequences
are deeply rooted in organizational theory and practice. We do so by re-writing the
GCM as an agent-based model, which is a straightforward operation because the GCM
is perhaps the first example of an organization theory developed explicitly through
hypotheses about the behavior of discrete objects (our agents) rather than hypotheses
on relations among variables.
In reproducing the original GCM we realized that the original model is at the same
time incomplete and redundant. It is incomplete in the scope of the hierarchical struc-
tures that it assumes, and at the same time redundant in the kinds of structures that it
allows to the experimenter. The model is also redundant in the number of indicators
that it adopts as measures of performance. We corrected these obvious shortcomings
by limiting the model to those structures that produce interesting results, by enabling
all agents in the model to adopt these structures, and by devising a minimum number
of indicators that capture all interesting properties of the model.
The original GCM has a means for avoiding a difficult problem, which consists of
attaching it to another opportunity for decision-making. We interpreted this mechanism
as postponing decision-making, and we remarked that the literature [10] has identified
two means for avoiding a difficult problem, namely, (i) postponing decision-making,
and (ii) passing it to someone else. The original GCM did not implement buck-passing,
but our agent-based GCM can easily do it. We found the surprising implication that or-
ganizations may be more similar to markets than previously thought. In fact, it appears
that selfish behavior, such as postponing decisions as well as buck-passing, may be
beneficial for the organization as a whole. As in the case of markets, a kind of invisible
hand seems to be at work.
The rest of this article is organized as follows. Section (2) describes the main
features of the original GCM, while section (3) expounds our agent-based setting. Sec-
tion (4) illustrates our extensions to the basic GCM. Section (5) points to the new issues
that our extended GCM identifies and allows to investigate. Section (6) illustrates our
results. Finally, section (7) discusses our results and embeds them within wider con-
siderations.
2

2 Cohen, March and Olsen’s Garbage Can
According to Cohen, March and Olsen [4], Garbage Can -like decision situations are
induced by the simultaneous presence of three elements. The first is fluid participa-
tion. Fluid participation means that the attention that participants typically dedicate to
any one issue is highly variable. This notion also captures the observation that orga-
nizational members tend to enter and exit decision situations according to processes
that are not necessarily related to the problems at hand. The second factor is unclear
decision technology. Unclear decision technology refers to the fact that causal rela-
tions underlying specific organizational decision problems are frequently ambiguous,
and only ex-post are reconstructed in the form of well specified means-end chains [11]
[13]. The third factor is problematic preferences, a term that Cohen, March and Olsen
introduced to capture the general tendency of decision makers to discover their pref-
erences through action rather than acting on the basis of pre-defined and unchanging
preferences [4]. Organizations characterized by fluid participation, unclear decision
technologies and problematic preferences were labeled by Cohen, March and Olsen
“organized anarchies” [4].
Four classes of agents populate the GCM: participants (decision-makers), choice
opportunities, solutions and problems. All these agents exist independently of one an-
other and, although they might disappear as a consequence of decision-making, their
existence is independent of time. Note that the assumption that solutions exist inde-
pendently of problems is a clear departure from the assumptions of rational decision-
making, implying that solutions are schemes that decision-makers apply to any problem
they meet rather than specific responses to specific problems.
According to the GCM, decision situations characterized by fluid participation,
unclear decision technology and problematic preferences generate three possible out-
comes, only two of which are decision styles:
1
The first decision style is characterized by the fact that a problem is actually
solved. This is called decicion-making by resolution. It is the only decision style
considered legitimate by the theory of rational decision-making [16]. Accord-
ing to the GCM, decisions are made by resolution if: (i) the participants to the
decision process are sufficiently able; (ii) a sufficiently efficient solution is avail-
able to them, and (iii) the problems that they are called to solve are sufficiently
simple.
The second decision style is defined by decisions that are made without any
attention to existing problems. It is just sufficient that a participant, a choice
1
Our interpretation of resolution, oversights and flights rests on the verbal description of the GCM made
by Cohen, March and Olsen at the beginning of their paper [4]. Subsequently, Cohen, March and Olsen
start to call flights “a third decision style. This happens because, at a certain point, they assume that
all flights generate resolutions: “Some choices involve both flight and resolution some problems leave,
the remainder are solved. These have been defined as resolution, thus slightly exagerating the importance
of that style. As a result of that convention, the three styles are mutually exclusive and exhaustive with
respect to any one choice. We shall see that assuming that all flights cause resolutions is by no means
a “slight exageration. Apart from this, calling flights “a decision style” creates a sharp divide between
the introductory conceptual claims and the computational model. This confusion is responsible of many
misunderstandings in the subsequent litterature.
3

opportunity and a solution are there: no problem is solved, because no prob-
lem is considered. Cohen, March and Olsen called this decision style by over-
sight. We interpret decisions by oversight as due rituals that confirm the legiti-
macy of an organization, as highlighted by the neo-institutional litterature [12]
[7]. They make sense because any organization is embedded in a wider society,
that requires them. As a typical example one may think of a firm that complies
with screening procedures in order to obtain a favorable classification by a rating
agency, though these procedures do not provide any immediate benefit. More in
general, compliance to safety, environmental, fiscal and many other institutional
rules helps gaining acceptance, recognition and trust by stockholders, banks, the
Government and the general public.
The third outcome, flight, is no decision in itself. It is a means to escape from too
difficult a problem.
In Cohen, March and Olsen’s GCM, participants shy away from a difficult problem
by removing the most difficult problem from the agenda of the current choice oppor-
tunity to attach it to another choice opportunity, one that will be due at a later time.
We interpret this procedure as postponing decision-making. Once the most difficult
problem is no longer under consideration, a participant can easily make a decision on
the remaining problems.
The participants in the GCM are characterized by an “ability” as as decision-
makers
2
, the solutions are endowed with “efficiency”, and problems have a “diffi-
culty”
3
. Let A
i
denote the ability of the ith participant. Let e
j
denote the efficiency
of the j th solution. Let D
k
denote the difficulty of the kth problem. Let us consider a
generic opportunity for decision-making and let us denote it by an index l.
A decision is made by resolution if at least one participant, at least one solution and
at least one problem are attached to opportunity l, and if the sum of the abilities of these
participants, multiplied by the efficiency of the most efficient among these solutions, is
greater than or equal to the sum of the difficulties of these problems:
II
l
A
i
!
max
jJ
l
e
j
kK
l
D
k
(1)
where I
l
is the set of participants on opportunity l, J
l
is the set of solutions on oppor-
tunity l and K
l
is the set of problems on opportunity l.
In contrast, a decision is made by oversight if at least one participant and at least
one solution are attached to opportunity l, but no problem is attached to l. Neither
the ability of participants nor the efficiency of solutions matter in this case. If several
solutions are available, one of them is selected at random.
There remains the case where at least one participant, at least one solution and at
least one problem are attached to opportunity l, but condition 1 is not satisfied. In this
case, participants are blocked on an opportunity plagued by too difficult problems.
On such occasions, participants may decide to get rid of difficult problems. A flight
occurs when participants succeed to attach the most difficult problem to a different
2
Ability” was actually called “energy” in the original model
3
“Difficulty” was also called “energy” in the original model
4

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Frequently Asked Questions (2)
Q1. What contributions have the authors mentioned in the paper "Passing the buck in the garbage can model of organizational choice" ?

In this paper, the authors reconstruct the Garbage Can model of organizational choice as an agent-based model and show that selfish individual behavior, such as postponing decision-making and buck-passing, does not necessarily imply dysfunctional consequences for the organization. 

In order to restore the original meaning and richness of the GCM, the authors made an effort to present and extend the GCM by making reference to more recent streams of research in organizational decision-making. This possibility did exist in the original GCM, but it was not explored by Cohen, March and Olsen. Their extended GCM suggests that flights — both by postponement and by buckpassing — are beneficial to the organization, since they avoid that the members of an organization waste their time with problems that they can not solve. This conclusion may strike as paradoxical, because it suggests that self-centered behavior might be beneficial to the organization as a whole.