21COE, University of Tokyo

MMRC Discussion Paper No. 113

MMRC
DISCUSSION PAPER SERIES

MMRC-F-113

Recovering the garbage canOrderly/disorderly paradox
Graduate school of Economics, University of Tokyo
Nobuyuki Inamizu
February 2007

21COE, University of Tokyo

MMRC Discussion Paper No. 113

Recovering the garbage canOrderly/disorderly paradox
Graduate school of Economics, University of Tokyo
Nobuyuki Inamizu
February 2007

1. Introduction
Cohen, March, and Olsen (1972) developed a simulation model on decision making inorganized anarchies. In organized anarchies, an organization is a collection of four elements (choice
opportunities, problems, decision makers, and solutions), and a decision is an outcome of theinteractions of these four streams. Choice opportunities are viewed as garbage cans. Various kinds ofproblems, decision makers, and solutions move in and out of choice opportunities, as if garbage werethrown into cans. When the total energy of the decision makers in a choice opportunity exceeds therequirements to solve the problems, the choice is made, as if clearing out a full garbage can.
Generally, the garbage can decision process works in such a way that the combinations of thefour elements randomly change, and decisions are made depending on timing (e.g., Weick 1979;
Hatch 1997; Daft 2004). A condition for this decision process is “unsegmented” structures, in which
problems, decision makers, and solutions can move freely among choice opportunities; that is, adisorderly decision process is considered to emerge from a disorderly structure.
Bendor, Moe, and Shotts (2001), however, examine the simulation model of Cohen et al. (1972)
and criticize this generally accepted view. They clarify that decision makers (and occasionallyproblems) move together in a single pack, and decisions made are not dependent on timing under theunsegmented structures. They regard this process as an orderly decision process; that is, an orderly1Nobuyuki Inamizu

decision process emerges from a disorderly structure.
This paper reexamines the simulation model and the garbage can model studies. I rewrite thesimulation model written originally in FORTRAN and examine the results reported by Cohen et al.
(1972). When rewriting, I used Fortran 90, Microsoft Excel, and a multi-agent simulator KK-MAS 1. I
also correct the rounding error and the strange setting of an initial value.
This paper shows that the simulation results are paradoxical. As shown in cell A of Table 1,
under the unsegmented (disorderly) structures, the orderly decision process is observed as shown by
Bendor et al. (2001). As shown in cell B in Table 1, under the hierarchical (orderly) structures, thedisorderly decision process is observed, which is not referred by Bendor et al. (2001).

Table 1: Interpretation of the simulation results

Disorderly(unsegmented)
Structure

Orderly(hierarchical)

Decision process
Orderly
Disorderly
A
C
Bendor et al. (2001)
Generally accepted view(illusion)
B
This paper

This paper suggests that these paradoxical simulation results are observable in actualorganizations. The case studies corresponding to cell B of Table 1 have been reported by the original
authors. The hierarchical structures mean, by definition, that the number of accessible choice
opportunities differs between each problem and decision maker. For example, March & Romelaer(1976), studying the decision process of a university, report that the people in administrative
positions had to devote their energies to various choice opportunities and the professors could engage
in the specific choice opportunity related to their own interests. This represents a hierarchicalstructure. As a result, March and his colleague observed the random movements of problems anddecision makers, and the decisions depending on timing.
This paper presents a case corresponding to cell A of Table 1. This case illustrates theemployees’ behavior at a Japanese firm introducing the concept of the nonterritorial office, in which
no one has a specific desk and there are no partitions. This type of office can be considered to make

1

KK-MAS is a simulator to run multi-agent simulation and was developed by Kozo Keikaku Engineering Inc.
(http://www.kke.co.jp/index.html).
2

Recovering the garbage canthe structure unsegmented. Although we might assume that the employees would sit randomly in thisoffice, I observed that they got together and sat in clusters for discussions. In addition, the employees
can solve problems efficiently in this office.
Finally, this paper shows that the generally accepted view is a mere illusion created by thesubsequent studies of Cohen et al. (1972). When describing the simulation results, the original
authors have accumulated and omitted key sentences in order to create the illusion without running
the simulation model. The original authors created the illusion of the garbage can model, and Bendor
et al. (2001) criticize the illusion.

2. Description of the Garbage Can Simulation ModelClassical theories of choice in organizations have three assumptions: 1) decision makers know
all outcomes of all alternatives, 2) they share the same goal, and 3) they have consistent and precise
preferences. Theories of bounded rationality relaxed the first assumption, and theories of conflictrelaxed the second. Most theories of organizational choice, however, do not relax the thirdassumption. One of the few theories relaxing it is the garbage can model (March & Olsen, 1986).
Cohen et al. (1972) develop the garbage can model for describing decision making in organizedanarchies. Organized anarchies are organizations characterized by problematic preferences, unclear
technology, and fluid participation. In this circumstance, an organization is a collection of choices
looking for problems, issues looking for decision situations in which they might be aired, solutions
looking for issues to which they might be the answer, and decision makers looking for work. A
decision is an outcome of the complex interactions of these four independent streams within an
organization. Cohen et al. (1972) considered that participants take part in decisions with changing(inconsistent and imprecise) preferences and make decisions by timing of choices, problems, andparticipant availability.
Since such a model of organizational decision making must concern itself with a complicatedinterplay among problems, solutions, decision makers, and choice opportunities, it is difficult to build
a mathematical model. Then, Cohen et al. (1972) translate the situations of decision making into a
computer simulation model and examine how decisions are made.
The image of the simulation model is as follows: Choice opportunities are viewed as garbagecans in the model. Various kinds of problems, energies, and solutions are dumped by participants into
choice opportunities, as if they threw garbage into cans. When the total energy in a choice
opportunity exceeds the requirements to solve the problems there, the choice is made, as if a full3

Nobuyuki Inamizu

garbage can were cleared out.
Figure 1 illustrates the flow chart of the simulation model. The model has five fixed parameters:
1) number of time periods, 20; 2) number of choice opportunities, 10; 3) number of decision makers,
10; 4) number of problems, 20; and 5) the solution coefficients for the 20 time periods, 0.6 for eachperiod. The solution coefficient defines the effective energy devoted by decision makers (discussed
later).
The model has eight variables (also see Table 2). This paper especially focuses on “Accessstructure” and “Decision structure.” Access structure is a list of choice opportunities to which the
problem has access. This structure has three types: 1) Unsegmented (each problem has access to all
choice opportunities), 2) Specialized (each problem has access to only one choice opportunity), and
3) Hierarchical (the number of accessible choice opportunities differs among each problem). In thesame manner, decision structure is a list of choice opportunities to which the decision maker hasaccess. This structure has three types: 1) Unsegmented (each decision maker has access to all choice
opportunities), 2) Specialized (each decision maker has access to only one choice opportunity), 3)
Hierarchical (the number of accessible choice opportunities differs among each decision maker).
The 324 cases are obtained by considering the possible combinations of the six variables except
energy requirement (ER) and effective energy (EE). For each case, simulations are conductedobeying the following rule:
1. Choice opportunities and problems enter following ec and ep 2.
2. Decision makers and unresolved problems are attached to choice opportunities not made,following A, D, and allocation assumptions. The assumptions allocate problems and decision
makers to the choice opportunity closest to a decision (EE-ER is minimized).
3. ER of each choice opportunity is obtained based on L.
4. EE of each choice opportunity is obtained based on E and the solution coefficient. To be specific, itis the sum of the energies devoted by decision makers to choice opportunity, deflated by thesolution coefficient 0.6.
5. If ER-EE is zero or below, the choice opportunity is decided, and the problems are resolved.
However, if ER-EE is more than zero, it becomes opposite.

2

A choice opportunity and two problems enter per time period over the first 10-time periods.
4

Recovering the garbage canStart
Set one of the combinationsof variables (*1)

Read fixed parameters：
Preiods(20), Choice opportunies(10)Problems(20), Decision-makers(10),Solution coefficient(0.6)

Set as T=1 ("T" represents periods).
Enter a Choice opportunity and two problems,
followeing "ec" and "ep." (*2)

Initial setting of Choice
opportunities
1) Entry time(ec)、2) Energy Requirement(ER)=1.1

Allocate1) Decision-makers
2) Unsolved problems
to Choice opportunities not made, following"A," "D" and "allocation assumption (*3)."

Initial setting of Problems
1) Entry time(ep)、2) Access-structure(A)3) Load(L)Initial setting of Decision-makers
1) Decision-structure(D)2) Energy distribution(E)Calculate total of "ER" in each
Choice opportunity, based on "L."Calculate total of "EE" in each Choice opportunity,
based on "E" and Solution coefficient.

＋

0 or －ER-EE

The Choice opporutunity is notmade, and the problems there
are not solved. (The Choice
opportunity holds deficit ofenergy (ER-EE). )The Choice opportunity is
made, and Problems there aresolved.

Did you execute about all
Choice opportunities？

No

Yes
T=T+1
Yes

T <= 20
No

Change the combination of variables

No

Did you execute about all
possible combinations?
Yes
Exit

Figure 1: The flow chart of the simulation model. The number of all possible combinations is324 because ec and ep have two types and A, L, D, and E have 3 types respectively (*1). All choice
opportunities and problems enter over the first 10 periods (*2). The assumptions allocate problems
and decision-makers to the choice opportunity closest to a decision (EE-ER is minimized) (*3). (Enta,
1987, p. 107, revised by the author)

5

Nobuyuki Inamizu

Table 2: The variables of the simulation model
Variable

Definition

Energy Requirement (ER)The energy required to make a choice:
The initial value = 1.1

Effective Energy (EE)

The sum of the energies which decision makers have devoted,
deflated by the solution coefficient:
The initial value = 0.0

Entry time of choice
opportunity (ec)

The calendar time at which that choice opportunity is activated.
Two types:* One choice opportunity enters per time period over the first 10
time periods.

Entry time of problems (ep)The calendar time at which that problem is activated.
Two types:* Two problems enter per time period over the first 10 time periods.

Access-structure (A)A list of choice opportunities to which the problem has access.
Three types:
1) Unsegmented: each problem has access to all choice
opportunities.
2) Specialized: each problem has access to only one
choice opportunity.
3) Hierarchical: the number of choice opportunities towhich each problem has access differs.

Load (L)The energy required to solve a problem.
Three types: 1) light, 2) moderate, and 3) heavy.

Decision structure (D)A list of choice opportunities to which the decision maker has access.
Three types:
1) Unsegmented: each decision maker has access to all
choice opportunities.
2) Specialized: each decision maker has access to only
one choice opportunity.
3) Hierarchical: the number of choice opportunities to which
each decision maker has access differs.

Energy Distribution (E)The distribution deciding how much energy each decision maker has.
Three types: 1) equal energy, 2) important people more energy, and
3) important people less energy.

The above rule induces three types of decisions. If the choice opportunity having problems (ER> 0) is decided, the decision is based on the resolution. The decisions are also made even if the
choice opportunity has no problems. Cohen et al. (1972) consider two types of these decisions. The
first is “decision by oversight,” which is made before decision makers enter the choice opportunity.
The second is “decision by flight,” which is made after all problems in the choice opportunity leave
6

Recovering the garbage canthere.

3. Generally Accepted View of the Garbage Can Model
3.1. Original Authors
From the simulation model, Cohen et al. (1972) draw the implications that decision makers,
problems, and solutions move around choice opportunities and their combinations randomly change(“Random Movements”) in the garbage can decision process. They state, “A major feature of thegarbage can process is the partial uncoupling of problems and choices. … choices are made only
when the shifting combinations [italics added] of problems, solutions, and decision makers happen to
make action possible” (p. 16).
Cohen et al. (1972) also insist that decisions are made depending on timing 3 and do not always
solve problems. They state, “Quite commonly this [decision making] is after problems have left agiven choice arena or before they have discovered it (decisions by flight or oversight)” (p. 16). This
does not mean, however, that decisions are always made by flight and oversight. When interpretingthe meaning of “depending on timing” strictly, it is reasonable to consider that decisions are made byrandom combinations of the three decision styles (“Random Decision Styles”). Cohen et al. (1972)
state, “it is clear that the garbage can process does not resolve problems well. But it does enablechoices to be made and problems resolved [italics added], even when the organization is plagued withgoal ambiguity …” (p.16).
The subsequent studies by the original authors insist that this decision process can be observed
typically under the unsegmented structures. Cohen, March, and Olsen (1976) state, “In situations inwhich load is heavy and the structure is unsegmented, intention is lost in context dependent flow ofproblems, solutions, people, and choice opportunities” (p.37). March and Olsen (1986) state, “In theabsence of structural constraints within a garbage can process, solutions are linked to problems, anddecision makers to choices, primarily by their simultaneity” (p.17). March and Olsen (1989) state, “inpurest garbage can situation we assume that any problem and any decision maker can be attached to
any choice” (p.13).

3.2. Standard Textbooks
Standard textbooks on organizational theory reflect the implications stated by the original
3

Cohen et al. (1972) do not use the word “depending on timing.” However, Cohen et al. (1976) state,“outcomes are frequently sufficiently dependent on elements of exogenously determined timing …” (p.37).
7

Nobuyuki Inamizu

authors of the garbage can model. These textbooks often use the word “random” and “disorderly” forexplaining the garbage can decision process.
Weick (1979) states as follows:
A crucial variable that is emphasized in this model is timing. It is assumed that there is acontinual stream of people, solutions, choices, and problems that flow in an organization. Every
now and then some clusters of these elements coincide, and a decision is produced. In otherwords, problems may attach themselves in first to one choice situation and then to another, andthe same holds true for people and solutions. (p.21)
Hatch (1997) states as follows:
In the garbage can model, problems, solutions, participants, and choice opportunities are
independent streams of events that flow into and through organizations, much like a random[italics added] selection of waste gets mixed together in a garbage can. Whenever solutions,participants, and choice opportunities connect, a problem may be identified or solved. Because of
the randomness [italics added] of the process, however, choices may be made without solving aproblem, some problems are never solved, and solutions may be proposed where no problem
exists. (p.278)
Daft (2004) states as follows:
With the concept of four streams, the overall pattern of organizational decision making takes on arandom [italics added] quality. … Organization decisions are disorderly [italics added] and not
the result of a logical, step-by-step sequence. Events may be so ill-defined and complex thatdecisions, problems, and solutions act as independent events. When they connect, some problems
are solved, but many are not. (p. 467)

3.3. Academic Articles and Works
Many academic articles and works regard the garbage can decision process as disorderly.
Kingdon (1984) assumes the combinations of the four elements would randomly change: “Thesolutions and problems that come to the fore might change from one meeting to the next, as given
participants attend or fail to attend” (p. 86). Although the studies casting doubt on the garbage candecision process have been published since the late 1980s (e.g., Pinfield, 1986; Levitt & Nass, 1989;
Mezias & Scarselletta, 1994), they share the view that the model itself illustrates the disorderly
association of the four elements.
Many academic articles and works assume that the unsegmented structures cause this disorderly
8

Recovering the garbage candecision process. For example, Grandori (1984) states as follows:This is consistent with the model and research results of Cohen, March, and Olsen (1972) andMarch and Olsen (1976), in which they consider conditions of extreme lack of knowledge(unclear preferences, technologies, and participants) in which decision processes arecharacterized by “unsegmented access structures.” In this particular case, the connections amongchoice opportunities, participants, problems, and solutions - i.e., decisions - are simply a functionof timing. (p. 200)
Padgett (1980) tries to accommodate the garbage can model to hierarchical organizations, and thisidea itself shows that many studies assume the garbage can decision process can be observed
typically under the unsegmented structures.
To sum up, the generally accepted view of the garbage can model is that the unsegmented
structures lead to a disorderly decision process (random movements and random decision styles).

4. Criticism from Bendor et al. (2001)
Bendor et al. (2001) examine the simulation model of Cohen et al. (1972) and criticize thegenerally accepted view of the garbage can model. The criticism to the simulation model would be
the most crucial though they examine the garbage can studies extensively.
First, Bendor et al. (2001) point out that the unsegmented structures lead not to random
movements but to “Single Packed Movement” in the simulation model. Single packed movementmeans that decision makers and problems move together from choice to choice, and that the
combinations of the four elements do not randomly change. Second, they point out that theunsegmented structures lead not to random decision styles but to “Single Decision Style,” whichmeans that all decisions are made by only one decision style. They report that all decisions are madeby resolution under light and heavy load, and are made by flight under moderate load. Therefore,
Bendor and his colleagues criticize the simulation process as the remarkable order.
Bendor et al. (2001) propose through a deductive process that the simulation model should bediscarded for its invalidity. They examine the correspondence between the simulation model and thebase theory (“organized anarchies”), and point out that the inappropriate rules of the model produce
the paradoxical result. Eventually, they conclude that the generally accepted view is an inappropriate
mix of the simulation model and the base theory, and that the simulation model should be apart fromthe base theory and should be replaced by a new one. This is the recycling plan of the garbage canstudies proposed by Bendor et al. (2001).
9

Nobuyuki Inamizu

Olsen, one of the original authors, provides several arguments against this criticism through an
inductive thought (Olsen, 2001). He points out that the simulation model of Cohen et al. (1972) isonly one of the simulation models having been proposed, and that the significance of the model
should not be exaggerated. Besides, he insists that the garbage can model is still effective forstudying organizational behavior because a disorderly decision process can be seen in actualorganizations.
This paper will examine the results of the original simulation model again. Cohen et al. (1972) iscited 899 times 4 and is more significant than the other garbage can simulation studies 5. Therefore,
the criticism from Bendor et al. (2001) has a great impact. This paper, however, reconsiders it froman inductive viewpoint. First, we should confirm whether a disorderly decision process (random
movements and random decision styles) can be observed in the simulation model if Olsen's argument
was appropriate. Second, we should confirm whether an orderly decision process (single packed
movement and single decision style) can be observed in actual organizations though Bendor et al.
(2001) regard the simulation model as no significant to study.

5. Retest of the simulation model
As the source code is given in the appendix of Cohen et al. (1972), I could reconstruct thesimulation model precisely. To examine whether the simulation model were reconstructed precisely, I
used the measures of “Problem activity 6,” “Decision maker activity 7,” and “Decision difficulty 8.” I
used these measures because 1) Cohen et al. (1972) describe the computational algorithms of thesemeasures in the source code, and 2) they accurately report the results of these measures. Table 3
shows the results of the reconstructed simulation model. Although some differences from Cohen et al.
(1972) can be seen in detail, almost the same result is obtained. Therefore, we can conclude that thesimulation model is reconstructed precisely 9.
4

The retrieval result from “Web of Science” on February 4, 2007.
There are few studies on the garbage can model using simulation. I can find only Anderson and Fischer(1986), Masuch and LaPotin (1989), and Takahashi (1997). Besides, these papers have been cited only several
times.
6
Problem activity is the total number of time periods. A problem is activated and attached to a choice, summed
over all problems.
7
Decision maker activity is the total number of times. Any decision maker shifts from one choice to another.
8
Decision difficulty is the total number of time periods during which a choice is activated, summed over all
choices.
9
Normally, the numerical results are the same because the same random numbers are used. The differences of
the results might be caused from a rounding error. The figures in the Table 3 are the ones after correcting therounding error. I reconstructed the simulation model with Fortran90, Microsoft Excel, and a multi-agent
simulator KK-MAS and obtained the same results respectively.
5

10

Recovering the garbage canTable 3: The examinations of the reconstructed model's precisenessMeasures

Cohen et al. (1972)

Reconstructed model

Corrected modelLight load

114.9

114.8

109.1

Moderate load

204.3

201.3

192.5

Heavy load

211.1

210.0

225.3

Light load

60.9

61.0

62.0

Moderate load

63.8

66.0

78.2

Heavy load

76.6

76.9

65.7

Light load

19.5

19.5

18.3

Moderate load

32.9

34.1

42.6

Heavy load

46.1

46.1

36.5

Mean problem activity

Mean decision maker activity

Mean decision difficulty

When examining the source code, I realized a strange setting. The initial value of Energy
Requirement (ER) of choice opportunities was set at 1.1 (see Table 2) as if there were problems in the
choice opportunity from the start. Then, I corrected the value from 1.1 to 0.0. Table 3 shows theresults of this corrected simulation model. Although great differences from Cohen et al. (1972) canbe seen at some points, we should consider these results as true ones.
First, under unsegmented access and decision structures, single packed movement and single
decision style are observed. Figure 2 10 shows that decision makers gather and solve problems
immediately under light load. Figure 3 shows that, under heavy load, decision makers and problems
move together from choice to choice, and decisions are made only by flight. These results show
single packed movement and single decision style pointed out by Bendor et al. (2001). However, theresult that all decisions are made by flight under heavy load is different from Bendor et al. (2001).
This is because I corrected the initial value of ER.

10

Following Bendor et al. (2001), I scaled the figures down by half for simplification: Five choice
opportunities, ten problems, five decision makers, and ten periods. The essence of the results does not changeeven though they were scaled down.
11Nobuyuki Inamizu

1

Chice opportunities
3
Prob
DM

2

Period 1

4,9,Period 2

Prob

DM

7,10,

1,2,3,4,5,

Resolution

4

5

1,2,3,4,5,
Resolution

Resolution

Period 3

Resolution

Resolution

Period 4

Period 5

Prob

DM

2,8,

1,2,3,4,5,

Prob

DM

3,5,

1,2,3,4,5,
Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Resolution

Prob

DM

1,6,

1,2,3,4,5,

Period 6

Period 7

Period 8

Period 9

Period 10

Parameter setting
Access structure = Unsegmented
Decision structure = Unsegmented
Load = Light
Energy distribution = Equal energy

Not yet entered

Prob

DM

4,9,

5,

Resolution

Active choice opportunity.
Problem 4 and 9 (for example) are inside.
Decision maker 5 (for example) is inside.

Oversight
Decided by resolution

Decided by oversight

FlightDecided by flight

Figure 2: A simulation process under Unsegmented strcutures / Light load

12

Recovering the garbage can1Chice opportunities
3
Prob
DM

2

Period 1

4,9,
Prob

Period 2DM

4

5

1,2,3,4,5,
Flight4,7,9,10, 1,2,3,4,5,
FlightFlightFlightFlightProb
DM
2,3,4,5,7,
1,2,3,4,5,
8,9,10,FlightProb
DM
3,4,5,7,9,
1,2,3,4,5,
10,

Period 3

Period 4

ProbDM
1,2,3,4,5,
1,2,3,4,5,
6,7,8,9,10

FlightFlightFlightFlightPeriod 5

ProbDM
1,2,3,4,5,
1,2,3,4,5,
6,7,8,9,10

FlightFlightFlightFlightPeriod 6

ProbDM
1,2,3,4,5,
1,2,3,4,5,
6,7,8,9,10

FlightFlightFlightFlightPeriod 7

ProbDM
1,2,3,4,5,
1,2,3,4,5,
6,7,8,9,10

FlightFlightFlightFlightPeriod 8

ProbDM
1,2,3,4,5,
1,2,3,4,5,
6,7,8,9,10

FlightFlightFlightFlightPeriod 9ProbDM
1,2,3,4,5,
1,2,3,4,5,
6,7,8,9,10

FlightFlightFlightFlightPeriod 10

Parameter setting
Access structure = Unsegmented
Decision structure = Unsegmented
Load = Heavy
Energy distribution = Equal energy

Not yet entered

Prob

DM

4,9,

5,

Resolution

Active choice opportunity.
Problem 4 and 9 (for example) are inside.
Decision maker 5 (for example) is inside.

Oversight
Decided by resolution

Decided by oversight

FlightDecided by flight

Figure 3: A simulation process under Unsegmented structures / Heavy load.

13

Nobuyuki Inamizu

Second, under hierarchical access and decision structures, random movements and random
decision styles are observed. Figure 4 shows that the combinations of decision makers and problems
are shifting, and that decisions are made sometimes by resolution and sometimes by oversight andflight under moderate load 11. Table 4 shows the proportion of each decision style under each structure.
The proportion of resolution is low under the hierarchical structures though resolution has a majority
under the specialized and the unsegmented structures. The number of times of each decision style isalmost equal under the hierarchical structures though the proportion of oversight is relatively low.

Table 4: The proportion of each decision style
Access and Decision structures
Specialized

Hierarchical

Unsegmented

(%)

(%)

(%)

Decision styles
Resolution

Oversight

51.7

38.4

70.7

(125)

(131)

(246)

48.3

20.5

5.2

(117)
Flight

0.0

41.1

(0)
Total

(70)

100.0

(140)
100.0

(242)

(341)

(18)
24.1
(84)
100.0
(348)

Note: Figures in parentheses are base number of times for the percentages. The figure in each cell of
the table is the sum when Access and Decision structures are constant and the other parameters (ec,ep, L, E) are variable.

Under the hierarchical structures, the choice opportunities which each problem and decision
maker can enter are different respectively. Therefore, even if problems or decision makers intend tomove together to another choice opportunity, some problems or decision makers cannot move there.
As a result, the cluster of problems or decision makers breaks up. As such a process develops, thecombinations of problems and decision makers in each choice opportunity change, and decisions are

11

This result does not depend on load.
14

Recovering the garbage canmade depending on timing. This result is not referred by Bendor et al. (2001).

1

Chice opportunities
3
Prob
DM

2

Period 1

Prob
Period 2

4,9,

1,2,3,4,5,

DM

Prob

DM

1,2,3,

4,7,9,10, 4,5,

Oversight
Period 3

Oversight

Period 6

Period 7

Period 8

Period 9

Period 10

Prob

DM

1,2,

1,

Prob

DM

1,2,

1,

Prob

DM

1,2,

1,

5

Prob

DM

Prob

DM

9,10

5,

3,4,5,7,

1,2,3,4,

Resolution

Period 4

Period 5

4

Prob

DM

Prob

DM

2,3,4,

1,2,

5,7,8,

3,4,

Oversight

Resolution

FlightProb
DM
3,4,5,6,7,
2,3,4,
8,

Oversight

Resolution

FlightProb
DM
3,4,5,6,7,
2,3,4,
8,

Oversight

Resolution

FlightProb
DM
3,4,5,6,7,
2,3,4,
8,

Oversight

Resolution

FlightProb
DM
3,4,5,6,7,
2,3,4,
8,

Prob

DM

1,2,

1,

Prob

DM

Oversight

Resolution

FlightProb
DM
3,4,5,6,7,
1,2,3,4,
8,

Prob

DM

Oversight

Resolution

FlightResolution

1,2,

1,

1,2,

Parameter setting
Access structure = Hierarchical
Decision structure = Hierarchical
Load = Moderate
Energy distribution = Equal energy

Not yet entered

Prob

DM

4,9,

5,

Resolution

Active choice opportunity.
Problem 4 and 9 (for example) are inside.
Decision maker 5 (for example) is inside.

Oversight
Decided by resolution

Decided by oversight

FlightDecided by flight

Figure 4: A simulation process under Hierarchical structures / Moderate load.

15

Nobuyuki Inamizu

The genuine results of the simulation model are as follows: 1) the unsegmented structures leadto the orderly decision process (single packed movement and single decision style), and 2) the
hierarchical structures lead to a disorderly decision process (random movements and random decisionstyles).

6. Hierarchical Structure Case
The original authors examined the decision making of American universities and translated its
essence into the garbage can model. In some works, case studies of university decision making arepresented (e.g., Cohen & March, 1974; Cohen & March, 1976; March & Romelaer, 1976). I
reexamined these case studies and realized that these studies are about a disorderly decision process
led by hierarchical structures.

6.1. Disorderly Decision Process in Universities
The original authors describe the decision process of universities as disorderly. First, theydescribe random movements of people (carriers of problems and energies). For example, March andRomelaer (1976) note that actors wandered in and out as the decision process developed, and that adifferent group was involved at each stage (overlapping to some degree with some previous stages).
Second, they describe random decision styles. Although March and Romelaer (1976) note thatdecisions were made by oversight and flight because of random movements, they also report that theissues addressed by that university (e.g., eliminating the program in Speech) were resolved eventually.
Therefore, they regard the decision process as a mixture of the three decision styles rather than as
being full of oversight and flight. Finally, they describe this decision process in terms of a bizarre
soccer game: “Consider a round, sloped, multi-goal soccer field on which individuals play soccer.
Many different people (but not everyone) can join the game (or leave it) at different times. Somepeople can throw balls into the game or remove them. Individuals while they are in the game try tokick whatever ball comes near them in the direction of goals they like and away from goals they wish
to avoid” (p. 276). This metaphor represents the disorderly decision process.

6.2. Hierarchical Structures in Universities
When carefully considering the cases reported by the original authors, we realize that the cases
are about hierarchical structures. The original authors report that people in administrative positions
had to devote their energies to various choice opportunities, and that the professors not in a16

Recovering the garbage cansignificant position could engage in the specific choice opportunity related to their own interests.
March and Romelaer (1976) report that as administrative actors (deans, chair people, provosts, andthe like) were busy, their attention is divided among various concerns and a multitude of decisionsituations. Administrative actors also changed their positions more rapidly than the issues wereresolved. However, there were some people devoting more energy to the choice opportunity than thepeople filling in administrative positions. Cohen and March (1976) state, “some people consistently
spend more time than others. Some problems are always there. There are important structural andnormative constraints on the access and decision structures” (p. 175). Therefore, we can categorize
these cases as ones under hierarchical structures.
To sum up, the simulation result of the disorderly decision process under hierarchical structures
is paradoxical but can be observed in the decision making process of universities reported by theoriginal authors of the garbage can model.

7. Unsegmented Structure Case
7.1. Outline of the CaseAn unsegmented structure case is the nonterritorial office of a Japanese company in thetelecommunications industry. The company’s corporate marketing division originally assigned one
desk to each employee and used partitions to hinder the line of vision. In 2001, the division moved toa new type of office. The first feature of the new office is open-plan setting (removing highpartitions). We can see at a glance all the employees in the new office because small plants and plantpots are used instead of partitions. The second feature is free-address setting (replacing assigned
desks by freely available ones). The employees can work anywhere at any time in the new office.
Even the department heads and the section chiefs cannot have their own rooms and desks. The
employees take their notebook computer, look for an empty place, and start working. At the end of
the day, they clear their desks and leave for home. The third feature is the computerized database(enabling to monitor most of the business documents on the intranet). Unless the employees can carry
their belongings and gain information for business anywhere, they cannot change their location daily.
The executive being in charge of the office relocation thoroughly scanned the document to solve thisproblem. The employees could reduce their belongings by this thorough computerization. Then, theexecutive made each employee have an individual homepage and open it on the intranet. The
individual homepage contains the owner’s detailed self-introduction, as well as business documents
and materials. The self-introduction consists of qualifications, favorite jobs, and records of the17Nobuyuki Inamizu

projects he or she has carried out. As a result, the employees could acquire computerized documents
or information anywhere through each employee’s homepage and intranet when necessary. In thismanner, the employees can move freely in the office.
This case is based on the interviews, observations of that division’s office. I interviewed theexecutive being in charge of the office relocation (the interview lasted for two hours on June 4, 2004).
At this interview, I explained the garbage can model and showed the simulation process as acomputer animation 12. Then we discussed the correspondence between the simulation results and theemployees’ behaviors in the new office.

7.2. Orderly Decision Process in the Nonterritorial Office
The executive said that the employees work near the person with whom they want to consult,and that the members of the same project sit together, though we assume that they sit randomly in theoffice. I could observe that an employee sat next to his senior to learn how to work, and another sat
with the members involved in the same project. In addition, before the relocation, the employees had
to reserve the conference room and to wait in order to have a meeting. After the relocation, they haveto only look for vacant spaces in the office for meeting. I could hear from an employee that he wasable to have a business meeting without reserving the conference room.
The executive said that the employees became able to solve problems instantly after the office
move, because they can sit together and work jointly. Before the office relocation, it was difficult for
the employees to solve problems through discussion with their colleagues, because each of themworked separately at its own desk. Besides, after the relocation, even if they require some documents
urgently, they do not have to examine and to report later because they can immediately extract
information through the intranet. Even if they have something that they could not understand, they
can search for and contact those being familiar with that problem through each employee's homepage
immediately.

7.3. Unsegmented Structures in the Nonterritorial OfficeSince the arenas for decision making and for performance of the duties are usually conference
rooms and desks (seats), we can consider them as choice opportunities. We can also regard
employees as carriers of problems and energies. Therefore, the access and decision structures would
12

I reconstructed the simulation model with a multi-agent simulator, KK-MAS, which is excellent for drawing
the simulation process as a computer animation.
18

Recovering the garbage canbe considered as structures deciding which seats or conference rooms are available to each
employee 13 (see Figure 5).

Employee
Employee: A carrier of problems and energies

Seat: A structure deciding which spaceeach employee can occupy

Employee

Seat
Seat

Employee

Seat

Conference
room

AND

Conferenceroom: Choice opprtunities

Before the office relocation:
1) Each could use only one preassigned seat.
2) To have a meeting, they had to gather at theconference room. However, they had to wait for the room
to become vacant.

(a) Before the office relocation

Employee
Employee: A carrier of problems and energies

Seat: A structure deciding which spaceeach employee can occupy

Employee

Seat
Seat

EmployeeAND

Conferenceroom: Choice opprtunities

Seat

Conferenceroom

After the office relocation:
1) Each can use all vacant seats.
2) To have a meeting, they only have to find a vacant
space. Therefore, they can gather immediately.

(b) After the office relocation
Figure 5: An interpretation of the office relocation

13

Although we have to divide access structure and decision structure normally, we put them together in a
structure deciding which space each employee can occupy. The employees not only devote their energies todealing with their task, but also report problems to the others. Therefore, we can consider the employees as
carriers of problems and energies. Weiner (1976) also adopts the same view.
19Nobuyuki Inamizu

It could be considered that access and decision structure were almost specialized before theoffice relocation because each seat (choice opportunity except conference rooms) was assigned toeach employee (problem or decision maker). In such a case, as the employees could not use othervacant space, the members engaged in related business had to wait for the conference room to
become vacant before they could arrange even a casual meeting. That is, they had to wait for the
choice opportunity that all members could access to become activated (see Figure 5 (a)).
It could be considered that access and decision structures became unsegmented after the officerelocation because all the employees could choose any seats freely. In such a circumstance, if there
are vacant seats or space, they can gather there and discuss immediately. They do not need to wait forthe specific choice opportunity (the conference room) to become activated (see Figure 5 (b)). As aresult, they can solve problems instantly.
In all, the members would be able to gather and to solve problems in the reformed office. Thismight correspond to the simulation results under the light load and the unsegmented structures.

8. Generally Accepted View as an Illusion
As stated so far, the unsegmented structures lead to single packed movement and single decisionstyle, and the hierarchical structures lead to random movements and random decision styles.
Therefore, we can assume that there are no grounds for the generally accepted view (random
movements and random decision styles caused by the unsegmented structures).
I will point out that the generally accepted view is a mere illusion having been created by thesubsequent studies of the original authors. When describing the simulation results, the original
authors have accumulated and have omitted keywords or sentences, to make the illusion without
running the simulation model.
First, it is a mere illusion that the unsegmented structures lead to random decision styles. Cohenet al. (1972) state as the simulation results, “Resolution of problems as a style for making decisions is
not the most common style, except under conditions where flight is severely restricted (for instance,
specialized access)” (p. 9). March and Olsen (1986) state, “Resolution of problems is not the mostcommon decision style, except where load is very light or problems and decision makers [italics
added] are severely restricted in movement” (p.18). March (1994) states, “Resolution of problems is
not typical except … when there are severe restrictions on the movements of problems, solutions, anddecision makers [italics added]” (p. 202). First, the original authors discussed only the restriction on
problems’ movements as a condition for random decision styles. They have brought, however, the20Recovering the garbage canmovements of decision makers and solutions into the argument without retesting the simulation
model of Cohen et al. (1972).
Second, it is a mere illusion that the unsegmented structures lead to random movements. Cohenet al. (1972) state as the simulation results, “a typical feature of the model is the tendency of decision
makers and problems to track each other through choices. … both decision makers and problems tend
to move together from choice to choice [italics added]” (pp. 9-10). March and Olsen (1986), however,
only state, “decision makers and problems tend to track one another through choices” (p.18), as afeature of the unsegmented structures. March (1994) only states, “decision makers, problems, andsolutions tend to track each other through the system” (p.202), as well. First, the original authors
pointed out that “tracking each other” means “moving together (single packed movement).” However,they have omitted the sentence about single packed movement and have left only the sentence“tracking each other.” As a result, “tracking each other” might have become considered
unconsciously as random movements.

9. Conclusion
Table 5 summarizes the reconsideration of the dispute stirred up by Bendor et al. (2001). The
genuine results of the simulation model are as follows: (1) a disorderly decision process (random
movements and random decision styles) emerges from an orderly structure (the hierarchicalstructures) and (2) an orderly decision process (single packed movement and single decision style)emerges from a disorderly structure (the unsegmented structures). These simulation results areparadoxical but can be observed: (1) Hierarchical structure cases have been reported by the original
authors (e.g., Cohen and March 1974; March and Romelaer 1976) and (2) an unsegmented structurecase study is the nonterritorial office presented in this paper. The original authors have created theillusion of the generally accepted view of the garbage can model, and Bendor et al. (2001) criticize
this illusion. The case studies reported by the original authors and the simulation result presented by
Bendor et al. (2001) are in different cells in Table 5. Therefore, they are inconsistent with each other.
The former case studies are supported by the simulation result of this paper, and the latter simulation
result could be supported by the case study in this paper.

21

Nobuyuki Inamizu

Table 5: Genuine results of the garbage can studies
Simulation process(movements / decision styles)

Case study

Orderly(hierarchical)

Disorderly (random / random)This paper

University decision making
Cohen and March (1974)
March and Olsen (1976)

Disorderly(unsegmented)

Orderly (single-packed / single)
Bendor et al. (2001)

Nonterritorial officeThis paper

Structure

Considered inductively, it is premature to decide that Cohen et al.’s (1972) simulation model has
no significance for study. A recovery plan for the garbage can studies would be to reconsider their
theoretical background from the paradoxical simulation results. Why the disorderly decision process
is observed under hierarchical structures makes an interesting research question. Another recovery
plan would be to draw implications for making sense of complex organizational behavior from theparadoxical simulation results. In this paper, the office relocation of the company was considered as acase of unsegmented structures and a light load. The company, however, might be faced with a heavyload. The employees might always allow difficult problems to pass without solving them. Otherwise,
the managers might reduce the load or temporarily create segmented structures. In this way, thesimulation model provides useful suggestions to add depth to the considerations of organizational
behavior.

22

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