Research Note 85-96 /

ASPECTS OF COGNITIVE COMPLEXITY THEORY AND RESEARCH

AS APPLIED TO A MANAGERIAL DECISION MAKING SIMULATION

ff~ Siegfried Streufert and Robert W. Swezey

(V) Behavioral Sciences Research Center

for

to

Contracting Officer's Representative

John Mietus

Leadership and Management Technical Area

William W. Haythorn, Chief

MANPOWER AND PERSONNEL RESEARCH LABORATORY

Newell K. Eaton, Acting Director

"T1C

,?1ELECTD

U.S. Am

LU Research Institute for the Behavioral and Social Sciences

September 1985

Approved for public release; distr'bution unlimited.

85 i ~4IS a
* U. S. ARMY RESEARCH INSTITUTE

FOR THE BEHAVIORAL AND SOCIAL SCIENCES

A Field Operating Agency under the Jurisdiction of the

Deputy Chief of Staff for Personnel

WM. DARRYL HENDERSON

EDGAR M. JOHNSON COL, IN

Technical Dircctor

-7 ; cr

-it.)

L This report, as wbmi"ed by the contractor. has been cleared fe, release to Defense Technical Information Center

II (DTIC) to comply with regulatory requirements. It has been given no primary distribution other than to DTIC

! |and will be available only through DTIC or other reference services such as the National Technical Information

Service (NTIS. The views. cpini,.ns, and/or findings contained in this report are those of the author (W and

should not be construej as an officia; Cepatlmeni of the Army position, policy, or decision. unless so designated

- by other offiscial documentatic'..

6,

PuI" ' . . .-.. : . .'/ . . " :. ), " . -... _. .: .-i - .i - ., - . - . - . ,
UNCLASSIFIED

SECURITY CLASSIFICATION OF THIS PAGE (When Dat Entered)

REPORT DOCUMENTATION PAGE BEFORE COMPLETING FORM

1. REPORT NUMBER 2. GOVT ACCESSION NO. IECIPIENT'S CATALOG NUMBER

ARI Research Note 85-96

4. TITLE (and Subtitle) 5 TYPE OF REPORT & PERIOD COVERED

-, ASPECTS OF COGNITIVE COMPLEXITY THEORY AND

RESEARCH AS APPLIED TO A MANAGERIAL DECISION

MAKING SIMULATION 6. PERFORMING ORG. REPORT NUMBER

SAI-82-03-178

" 7. AUTHOR(&) 8. CONTRACT OR GRANT NUMBER()

* Siegfried Streufert and Robert t. Swezey MDA 903-79-C-0699

9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK

Behavioral Sciences Research Center AREA & WORK UNIT NUMBERS

* Science Applications, Inc. 2Q162722A791

McLean, Virginia 22102

II. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE

U.S. Army Research Institute for the Behavioral September 1985

and Social Sciences, 5001 Eisenhower Avenue, 13. NUMBER OF PAGES

Alexandria, Virginia 22333-5600 124

14. MONITORING AGENCY NAME & ADDRESS(If different from Controlling Office) 15. SECURITY CLASS. (of this report)

15a. UNCLASSIFIED DECL ASSI FICATION 'DOWN GRADING

SCHEDULE

16. DISTRIBUTION STATEMENT (of thie Report)

-. Approved for public release; distribution unlimited.

17. DISTRIBUTION STATEMENT (of the abstract entered in Block 20, If different from Report)

IS. SUPPLEMENTARY NOTES

John Mietus, contracting officer's representative.

19. KEY WORDS (Continue on reverse aide if necessary and identify by block number)

Cognitive Complexity

Measurement

20. ASfTR ACT (Cmtte Man reverse eEs If nec.wer and Identify by block number)

2-This research note is a post-1977 review of the literature in the areas of

theory, research, and measurement of cognitive complexity. It updates the

previous major review effort of Streufert and Streufert (1978). Additional

discussion is devoted to the approaches selected for measuring cognitive complexity with a mini-computer based Management Assessment and Training Simulation System.,

D JAN 3 1473 E E OF I, OV S 1s OSOLETE UNCLASSIFIED

SECURITY CLASSIFICATION OF THIS PA:, E (Wher Data Entered)

iZ-
7.

0 ACKNOWLEDGEMENTS

The authors wish to gratefully acknowledge the help and guidance provided

by Dr. T. 0. Jacobs, project monitor on this research effort. Dr. John

Mietus, formerly of the U.S. Army Research Institute, also provided

considerable support on this project, as did Dr. Kenneth Unger of SAI,

and Ms. Sharon Miller of George Mason University.

0

0

S

iii

, - N.*•- - -.- -•
ASPECTS OF COGNITIVE COMPLEXITY THEORY AND RESEARCH AS APPLIED TO A

MANAGERIAL DECISION MAKING SIMULATION

BRIEF

Requirement:

There is a widely recognized need to provide top level Army managers

with better information and with tools to better utilize the information

* they have. This need exists, not only within battle situations, but also

within strategic and managerial situations. Top level decision making is

typically characterized by lack of complete information, multiple and

conflicting objectives, high levels of uncertainty, turbulent environments,

and decision outcomes that tend to be both costly and long range in their

implications. There is a substantial body of literature which suggests

o that many managers respond to turbulent environments in a manner different

from that which is predicted to lead to greater effectiveness.

This report establishes cognitive complexity theory as the basis for

a man-machine managerial assessment and training vehicle, employing

computer-based technology, that simulates complex information processing

and decision making requirements within a senior-level military management

context. This vehicle is termed the Management Assessment and Traininq

Simulation System. Participants' performance will be assessed using problem scenarios, and the results of these embedded assessments will be fed

back to participants. This feedback is intended to help participants to

better integrate and differentiate complex information.

* Procedure:

A literature review in the area of cognitive complexity is presented.

The review is organized into three basic sections, addressing in turn,

theory, research, and measurement. Within each of these sections, pre-1977

work is treated in an overview fashion, and more detailed reviews of post1977 studies are then presented. This review updates the previous major

review in this area (i.e., Streufert and Streufert, 1978).

Findings:

Based upon the review, a measurement strategy for assessing the

decision style utilized by participants in the Management Assessment

and Training Simulation System is identified. This approach includes

ten categories of measures which, together, are intended to provide a

wide range of insight into a person's, group's, or organization's style

of decision making. Further, several potential approaches for use as

v
-C

additional (outside) measures in the Management Assessment and Training

Simulation System are discussed. These include measures based upon the

* theoretical work of Elliott Jaques, as well as measures of simultaneous

information processing ability and of psychological load.

Utilization of Findings:

Measures identified as a result of the cognitive complexity litera-

* ture reviewed in this document are prime candidates for inclusion in

the development of a mini-computer-based Management Assessment and

Training Simulation System. The overall purposes of this system are

(1) to help managers better process information in

complex, turbulent environments, and

(2) to help managers better struoture their organizations so that human decision makers can appropriately

process information received.

*

vi

: -, ,.-.., -.. ..- -.--.-- , ,.. -.- -.. ..... -- -. ... - -- -.-- - - - - . .. 7 > :7- 5 i.
* TABLE OF CONTENTS

I. INTRODUCTION 1

II. COGNITIVE COMPLEXITY: THEORY, RESEARCH, MEASUREMENT 4

THEORY 4

A Short Review of Theory through 1977 4

Definitions 4

* Theoretical Positions 7

Recent Advances in Complexity Theory 14

RESEARCH

* A Summary of Complexity Research Efforts

through Early 1977 17

Recent Research 27

1. Communication 27

2. Attitudes, Attributions, and Attraction 27

3. Leadership 29

4. Information Orientation 29

5. Perception 29

6. Development and Personality 31

7. Clinical Applications 32

8. Performance 32

9. Decision Making 34

10. Training 47

Summary 48

MEASUREMENT 49

* Measures of Cognitive Information Processing 49

1. Measurement through Early 1977 50

2. Recent Efforts Concerned with Cognitive

Information Processing 61

Measures of Performance 65

* Decision Making Measures

1. Single Strategy Models 66

2. Multi-stage Models 68

Ongoing and Future Research 73

vii

. . .
o TABLE OF CONTENTS

(continued)

SUMMARY 74

III. COGNITIVE COMPLEXITY MEASURES SELECTED FOR USE IN THE

MANAGEMENT ASSESSMENT AND TRAINING SIMULATION SYSTEM 76

IV. ADDITIONAL APPROACHES AND MEASUREMENT TECHNIQUES

SELECTED FOR POTENTIAL USE IN THE MANAGEMENT

ASSESSMENT AND TRAINING SIMULATION SYSTEM 84

Level of Abstraction 84

Measurement 95

Simultaneous Information Processing 96

Subjective Psychological Load 97

REFERENCES R-I

LIST OF TABLE AND FIGURES viii

,iii

CO

0o

LI
LIST OF TABLE AND FIGURES

Page

TABLE 1. Interrelationships among Components of Complexity

* and Various Other Constructs ................. 22

Figure

1 Dimensions of Decision Style ..... ........... 46

2 Decision Styles by Measurement Technique Matrix 83

3 The Cooper-Harper (1969) Scale .... .......... 99

4 Spyker et al.'s (1971) Adaptation of the CooperO Harper Technique .... ................. . .100

ix

.-. "
I. INTRODUCTION

This documert is the sixth in a series which report on research

conducted by the Behavioral Sciences Research Center at Science

Applications, Inc., under Contract No. MDA 903-79-C-0699 with the

* U.S. Army Research Institute for the Behavioral and Social Sciences.

Other documents in the series include:

Baudhuin, E. S., Swezey, R. W., Foster, G. D. and Streufert, S.

An empirically derived taxonomy of organizational systems.

* (SAI Report No. SAI-80-091-178) McLean, VA: Science

Applications, Inc., 1980.

Davis, E. G., Foster, G. D., Kirchner-Dean, E. and Swezey, R. W.

An annotated bibliography of literature integrating organizational and systems theory. (SAI Report No. SAI-80-082-178)

* McLean, VA: Science Applications, Inc., 1980.

Streufert, S. and Swezey, R. W. Organizational simulation:

Theoretical aspects of test bed design. (SAI Report No.

SAI-80-010-178) McLean, VA: Science Applications, Inc.,

1980.

Swezey, R. W., Davis, E. G., Baudhuin, E. S., Streufert, S.

and Evans, R. A. Organizational and systems theories: An

integrated review. (SAI Report No. SAI-80-113-178)

McLean, VA: Science Applications, Inc., 1980.

* Atwood, M. A. and Swezey, R. W. Microprocessor considerations

for a management assessment and training simulation system.

TSAI Technical Memorandum 178-81-1) McLean, VA: Science

Applications, Inc., 1981.

* This report provides a discussion of the overall area of cognitive

complexity theory, research, and measurement as it applies to the

development of a computer-based Management Assessment and Training

Simulation System. There is a widely recognized need to provide top

0|
level Army managers with better information and -with tools to better

utilize the information they have. This need exists not only within

battle situations, but also within strategic and managerial situations.

Top level decision making is typically characterized by lack of complete information, multiple and conflicting objectives, high levels

of uncertainty, turbulent environments, and decision outcomes that

tend to be both costly and long-range in their implications. There

is a substantial body of literature which suggests that many managers

respond to turbulent environments in a manner different from that which

90 is Predicted to lead to greater effectiveness.

This effort establishes a man-machine managerial assessment and

training vehicle, employing computer-based technology, that simulates

C complex information processing and decision making requirements within

a senior level military management context. Participants' performance

will be assessed using problem scenarios and the results of these

embedded assessments will be fed back to participants. This feedback

*0 is intended to help participants to better integrate and differentiate

complex information.

Research already performed under this contract has established

* theoretical and methodological bases for the development of such a

simulation system. The system will allow for manipulation of management action to permit training procedures to aid in improving decision

making performance, and to provide diagnostic tools for managers.

S( The framework established for the simulation is found in two reports:

1. Literature Review (Swezey et al., 1980). This document

represents a review of current (post 1960) experimental and

*- theoretical research on characteristics, processes and

CS dimensions which are relevant to the objectives of this

effort. It was based upon a factor analytically generated

taxonomy of variables. The most relevant factor, multidimensional information processing, reflects individual

and organizational processes in open systems. It is concerned with information input into the system, the perception

2

_e. ( ....
of that input, its classification and organization, its

*differentiation and integration through the structure of

the organization, and the resulting output.

2. Simulation Specification (Streufert and Swezey, 1980).

This report deals with the characteristics of the simulation

from a theoretical perspective. It discusses various types

* of procedures which are available for simulation construction

and the reasoning behind choices made to achieve specific

goals. The report specifies how the simulation, type of

military unit, and setting selected may be utilized to

achieve the following purposes:

0 utilization of the simulation for training

purposes, including the matching of variable

characteristics to specific training needs

of the organizations under consideration,

and to the settings in which these organizations operate; and

0 utilization of the simulation as a potential

diagnostic assessment module for managers.

3

0J

' " " I
,9

II. COGNITIVE COMPLEXITY: THEORY, RESEARCH, MEASUREMENT

The last extensive review of cognitive complexity appeared as a

chapter in a book by Streufert and Streufert (1978), covering theory

and research up to the early months of the year 1977. Since that time,

* theory has been advanced by Scott, Osgood, and Peterson (1979) and by

Streufert and Streufert (1978; c.f., Streufert, 1978) among others. In

addition, about 300 research studies have been published in English, French,

German, and Japanese, not even considering an approximately equal

|O number of dissertations. Considerable new knowledge has been gained

both in the theoretical and research realms. Lesser advances have

been reported in measurement. This chapter will cover all three of

these areas, beginning with a review of the conclusions reached by

* Streufert and Streufert (1978), and continuing with developments

which have occurred since that time.

THEORY

A Short Review of Theory through 1977

Definitions

Before adequate communication about cognitive complexity is

possible, a variety of terms must be defined. Unfortunately, the

meaning of terms has at times varied from one writer to another,

leading to some degree of confusion in the literature. The following

terminology will be used in this paper (as used previously by

Streufert and Streufert, 1978).

.

.. . o. . - .. .. . - ..-... ..-.. ..-~ .-.- ... - - . . . - -.. . .. .- . - . . . .
Dimension: A bipolar semantic scale in a person's

* cognitive semantic space. The scale may have as few as

two points of discrimination among stimuli (i.e., the

poles), or it may have many more. The scale represents

an individual's grouping or ordering oJ those stimuli

which have meaning in the semantic space defined by the

endpoints of the scale. This last point may be eluci-

* dated by an example, similar to one used by Kelly (1955).

If an individual has in his cognitive space a dimension

(scale) of short-tall, the endpoints of that dimension

have meaning to the stimuli man or building, but do not

have meaning in relation to the stimulus weather.

* Discrimination: The process of dividing (or the

degree to which division has been accomplished) a

cognitive bipolar semantic dimension into parts (subsections) for the placement of stimuli which have

semantic relevance to the endpoints (poles) of that

dimension. Discrimination is meaningful only to the

* degree that sharp distinctions can be made, i.e., to

the degree that the distinctions can either be labeled

or to the degree that they can evoke differential outcomes in behavior. The minimum number of discriminations on any dimension is two (pole A vs. not-pole A;

or pole A vs. pole B). The maximum number of discrimin-

* ations on any dimension is limited only by the capacity

of the organism to meaningfully divide the semantic

space of any dimension.

The process of discrimination, althouth unidimensional, is related to the processes of differentiation and integration (see below). As in differeno tiation, it involves the dividing of a segment of

semantic space (here, of one dimension only); and as

in integration, it involves the assembling of various

semantic points (meaning) into a (here, unidimensional)

subsegment of semantic space.

Differentiation: The process of dividing cognitive

semantic space (or the degree to which this division has

been achieved relevant to specific stimulus configurations) into two or more orthogonal or oblique (but nearorthogonal) bipolar semantic dimensions - i.e., the

ordering of stimuli in intransitive fashion on two or

more scales in semantic space.

Inteqration: The process of relating a stimulus

configuration to two or more orthogonal or oblique

dimensions of semantic space (or the degree to which

this relating has been achieved) to produce a perceptual 5

I 

..

. -. 

. ... , ,. 

.

. ... ,.- -. 

. ,. 

.

. ... 

.-

-..

.. .. 

.

. .. 

..

- .. ,. 

-.

..

.

..

. .. .. 

..
,-

or behavioral outcome which is determined by the joint 6 (weighted or unweighted) demands of each dimension involved.

Hierarchical integration: The fixed, unchanging

relationship among dimensions with regard to a number of

stimulus configurations, producing a joint weighted or

unweighted, but stable, response to stimuli. Specific

* stimuli would always affect the same dimensions in the

same way.

Flexible integration: The varied, changing relationship among dimensions with regard to stimulus configurations, producing various diverse (over stimulus type,

* presence/absence, or frequency) weighted or unweighted,

more or less unstable, responses to stimuli.

Content: Represents the location of any specific

stimulus object or configuration on any specific

discriminated point on a cognitive dimension to which

O it is assigned by the individual (e.g., an attitude).

In other words, cognitive content is concerned with

the relationship of various stimulus objects to each

other on that dimension (as contrasted to the structural relationship among dimensions). Content represents

what a person thinks about a stimulus, not how he thinks

* about it.

Structure: Represents the differentiative or

integrative use of dimensions of semantic space with

regard to a specific stimulus object or configuration.

Structure is concerned with the number of dimensions

* and the number and pattern of relationships among them

(i.e., the organization of cognitive semantic space),

rather than the meaning of the specific dimensions

involved. In other words, while content is concerned

with what an individual thinks about a stimulus and

what response he makes to it, structure is concerned

with the cognitive processes underlying a response,

i.e., how he thinks about the stimulus.

Cognitive complexity-simplicity: Represents the

degree to which the entire and/or a subsegment of a

cognitive semantic space is differentiated and integrated.

i2.

C

" . - ' w • ." - " . .. - , , - . - - , " + - ' . " • ° • " . , . . .
*, Theoretical Positions

The reader familiar with some of the complexity theories should

be warned that he/she may notice that one theory or another appears

modified in this chapter from what a reading of the original manuscripts might have suggested. Changes are due to changes in terminology,

not changes in the content of the theories. By using the same terminology with regard to all of the complexity theories, all can be

brought to a "common denominator" making meaningful comparison among

the theoretical (and research) efforts possible. In the following

paragraphs each of the several theories published through 1977 will

be reviewed very briefly.

Kelly (1955) proposed a "Psychology of Personal Constructs." He

viewed his work as a guide for psychotherapy and client-therapist

interaction. His concept of personal constructs and the Role Concept

Repertoire (REP) Test, while not intended as a complexity approach,

have certainly been the basis for later theories in the area. Kelly's

'construct" is a bipolar dimension which results from an individual's

process of "construing or (cognitively) interpreting" events. Kelly

has considered dimensions in terms of similarity and contrast: If

two events or objects are viewed as similar and a third is viewed as

dissimilar, a construct (dimension) emerges. Constructs are proposed

to relate to each other in terms of ordinal hierarchical relationships,

but these relationships may be limited to certain areas (domains).

Location of objects or concepts within constructs may or may not be

fixed. The views of Kelly seem most closely related to Streuferts'

concept of differentiation (as defined previously)i although the potential for some (minimal) discrimination and integration is provided.

Distinctions between content and structure are not made.

7

~. . ,....,,...+, .' -..... .... ,~. +. + .... . .... - - ....- .-... .

, . .. .- . ...-..- .... ° .. . .. o.. --. . - ... .--,. .
The theories of Bieri (1961, 1966; Bieri et al., 1966) are based

0- on the work of Kelly. As was the case with Kelly, Bieri's work has

been concerned with the effect of an individual's cognitive orientation

on the judgments he or she makes in response to environmental stimulation. Bieri views complexity as a structural characteristic describing

* the use of psychological dimensions. According to Bieri (1968),

complexity is only concerned with social judgments and the individual's

"social versatility" in responding to inputs from other persons. The

degree of cognitive complexity is related to the number of dimensions

* available to an individual. The more dimensions that are present,

the greater the degree of cognitive complexity. Bieri discusses

differentiation both in terms of an individual's coqnitive structure

(the number of dimensions available to that person), and in terms of

4* the social stimulus environment (the number of dimensions possessed by

the stimulus). Social perception then, is an interaction between

stimulus complexity and structural (person) complexity. Bieri also

considers discrimination (called articulation by that author), i.e.,

* the process of making discriminations within dimensions, and a third

judgmental process (called discrimination by that author) which makes

unique distinctions among stimuli.

All in all, the efforts by Bieri tend into the direction of the

analytic rather than the synthetic. The theory describes how stimuli

are separated into meaningful categories on the basis of dimensions

or on the basis of the stimuli themselves. It should be noted that

the theory (in contrast to the early work of Kelly) is, however,

purely structural in orientation even though limited by its location

within the perceptual-social domain.

The Categorizing Theory of Zajonc (1960) is concerned with the

0 in the S-O-R relationship. Zajonc proposes that, given a set of

stimuli and a set of responses made to those stimuli, a determinate

correspondence between the elements of both sets can be derived.

8

O~
The value(s) of this correspondence are described as attributes which

can be inferred from a person's responses to a given set of stimuli.

The established stimulus set to response set relationship will determine the value of any relevant new stimulus to which a person is

exposed. Numbers of available attributes reflect differentiation.

AP Complexity reflects the degree to which classes of attributes in a

given cognitive structure can be subdivided.

The terminology of Zajonc (for example, the use of the term

*- dimension) is widely different from that of most other complexity

theorists. The descriptors (formulas) for each of the terms employed

are similarly different, allowing very little comparison with other

efforts. One of the major values of this approach is the impetus it

*provided for the subsequent theoretical formulations of Scott (1969,

1979) and associates.

The early cognitive structure theory of Scott (1969) was not only

9based on the work of Zajonc (1960), but combined that approach with

some-of the earlier formulations of Lewin (1936) and Heider (1946).

Earlier distinctions between personality content and structural

characteristics are elaborated by Scott into an encompassing theory of

*structural characteristics which has considerable implications for

social, personality, clinical, and to some extent, organizational

psychology. The definitions of content and structure advanced by

Zajonc are quite similar to those proposed here and in Streufert and

Streufert (1978). Scott was one of the first theorists to emphasize

that structural characteristics (e.g., differentiation) may be limited

to specific cognitive domains. Scott describes dimensions and discriminations on dimensions (there called attributes) as images (or

concepts of objects) representing combinations of objects' characteristics as points in multidimensional space, dimensionality, differentiation (within cognitive domains), and integration.

9

-20
N

The theory of Scott is extensive and complex. Again, the terminology does not match that of many other theoretical orientations.

A summary provided by Streufert and Streufert (1978) probably provides an accurate discussion of the Scott theory from the present

point of view (pp. 25-26).

Any perception by a person based on the phenomenological

world results in an image which represents a point on one or

more dimensions (attributes) of cognitive space. Where, on

any dimension, the image falls depends on the number of seg-

* ments of the dimension (degree of articulation of the attribute). The number of independent dimensions (attributes)

into which a person sorts information reflects the degree

to which he differentiates the specific cognitive domain

into which he has placed the perceived stimuli.

* It should be noted that Scott views both dimensionality

and discrimination (in his terms, attributes and articulation)

as parts of the differentiation concept. In this way he

differs from other theorists (e.g., Driver & Streufert, 1966;

Schroder, Driver & Streufert, 1967; Streufert, 1970) who

view discrimination as a separate process.

Scott's view of 'integration' also differs from that

of other theorists who nave been primarily concerned with

that concept (e.g., Driver & Streufert, 1966; Harvey,

Hunt, and Schroeder, 1961; Schroder et al., 1967; Streufert,

1970). While all writers would agree that integration refers

• to the manner in which images are related, Scott includes a

much greater number of cognitive operations in his

'integration' concept. For example, if (to use

one of his integrative processes) various attributes

(dimensions) are highly correlated with integrative

processes) various attributes (dimensions) are

* highly correlated with 'affective-evaluative consistency,' then this form of association would be

viewed by other theorists as the absence of complexity. Integration theorists would argue that

For purposes of saving space, Scott's distinction between attributes

and dimensions is not reported in this paper. For some more detail,

see the discussion of Scott's recent theoretical statements below and

the original sources.

10

- .t.......
integration must follow differentiation. The use

*of divergent verbal labels for what is otherwise

known as the good-bad (evaluative) dimension would

suggest to them that identity (unity) of these

attributes has been learned, and that a differentiation process did not take place before the association

was made. Alternatively, the structure which once was

* differentiated may have become resimplified through a

process that may be called hierarchical (Streufert,

1970), as distinguished from what Schroder et al.

(1967) called integration proper, and what Driver and

Streufert (1966) and Streufert (1970) have discussed

as flexible integration.

A final distinguishing characteristic of Scott's

theory is his repeated emphasis (e.g., Peterson &

Scott, 1974; Scott, 1963) on the limitations of complexity across cognitive domains (cf. also Cohen &

Feldman, 1975). He questions the assumption of the

existence of structural types, i.e., the description

of a person as 'simple,' 'complex,' etc. He considers

it to be probable that the number of persons who have

consistent structural characteristics among many areas

of their experience is quite small, and further suggests

that such individuals may well be pathological. Scott

states, however (personal communication, 1975), that

* the attempt to describe such types is of value if

-developed empirically, rather than on an a priori basis.

Recent evidence (Peterson & Scott, 1974; Scott, 1974)

suggests the existence of at least a limited typography:

Some degree of generality of cognitive style across

domains was obtained. Which style is utilized in a

* particular situation appears to be dependent upon an

interaction between the structural characteristics of

the person and the characteristics of the situation.

Impression Formation has been an interest of several complexity

theorists (e.g., Bieri, 1955). Generally, it is suggested that

persons who are complex (if applicable to the theory within a relevant

domain) should form more veridical impressions (Bieri, 1955) or should

include information that may, on the surface, appear contradictory

(Streufert and Driver, 1967), than persons whose perceptual capacity

or style reflects greater unidimensionality. In other words, such

Persons should respond less to the primacy or recency orientation

*I

--..-> i-- 1 ...-",i.i ... o# '" . ."'" .: " = ." " " .- '' , ". '" , 

" 11 .
suggested and/or obtained by researchers associated with Asch (1946;

Anderson and Barrios, 1961; and Luchins, 1957, 1953). Crockett (1965)

and associates have carried out an extensive research program on

impression formation. Their theoretical conceptions of complexity

are based on the primacy-recency paradigm. Crockett's work is primarily

derived from the developmental psychology of Werner (1957). Differentiation and discrimination (articulation) are said to follow the

developmental process, resulting in "increased interdependence of

elements" through integration into a hierarchically organized system.

• Complexity implies a cognitive system which contains a larger number

of elements and the greater integration of those elements into a

hierarchical system of relationships. The relative number of constructs in a cognitive system defines the degree of cognitive differentiation.

Crockett's concept of differentiation has much in common with

those of the authors discussed above. It should be noted, however,

that his definition of integration is hierarchical, i.e., nonflexible in the sense considered by the Harvey et al. and the Schroder

et al. and the Streufert and Streufert theories (see below).

Crockett's work is to some degree concerned with the generality of

cognitive complexity; in otherwords he does not assume that complexity

is necessarily the same from one domain to another.

Harvey, Hunt and Schroder (1961) proposed their "Systems Theory"

* as a developmental descriptive approach to behavior at four diverse

levels of cognition. The System 1 person was viewed as a "yea sayer,"

accepting the demands, mores, folkways, and fads of his or her source

of training without much question. The System 2 person, in contrast,

is considered to be a "nay sayer," rebelling against the imposition

of authority, i.e., not accepting the simple good-bad orientation of

established norms. At the developmental level of System 3, the

person is able to view alternatives as acceptable, resulting in

%--1-
greater tolerance and displaying somewhat of a "nice guy" image. The

Systerr 4 person not only views alternatives, but relates them structurally to superordinate concepts, goals, etc. The authors suggest

that persons may develop through all stages to reach System 4 or may

get arrested at any one stage or in a transition between stages.

Development through the stages is seen as representing development

toward initially greater differentiation and later greater integration.

Harvey et al. use the term "concrete" to describe the Stage 1 and the

term "abstract" to describe the Stage 4 person. Hunt (1966) has

added a "sub 1" stage to describe the person who is less than unidimensional (the good-bad dimension of the Stage 1 person is replaced

by an inclusion/exclusion principle. With this addition, Hunt has

added a form of "discrimination" to the theoretical formulation by

0 showing that discrimination does not exist in the "sub 1" stage.

While the theory of Harvey et al. does include some structural

characteristics, it is clearly confounded with content: for example,

* Stage 1 suggests authoritarianism, Stage 2 implies rebellion, and

Stage 3 often can represent an attitude of tolerance (rather than

tolerance based on potential alternate dimensional interpretation).

The theory tends to place "value" on the level to which a person

* advances: it is a "good thing" to be System 4 and a "bad thing" to

be sub-1.

Early interactive complexity theory (Driver and Streufert, 1966;

*Schroder, Driver, and Streufert, 1967; Streufert and Driver, 1967;

Schroder, 1971) and its later versions (e.g., Streufert, 1970)

propose that effective cognitive complexity is not only a function of

a person's structural dimensionality, but depends as well on current

Cenvironmental conditions. The theory proposes (an earlier and a later

modified version of) a family of inverted U-shaped curves relating

environmental complexity (e.g., information load) to differentiative

13
and integrative performance. Different persons, representing different

degrees of cognitive complexity would reach diverse levels of differentiative/integrative performance as long as environmental conditions

are optimal. Lesser or no differences would be expected when the

environment is greatly overloading (excessive environmental complexity

* in terms of load and/or other variables) or when the environment

deprives the individual of needed input. A number of environmental

variables are considered. The approach is entirely structural and

deals with differentiation and integration separately, suggesting

• that the two may (particularly in terms of measurement) not covary

at all times. It is assumed (Streufert, 1970) that integration is

probably best based on a moderate amount of (non-excessive) differentiation. The interactive complexity theory, as its name suggests,

* is the only one of the earlier complexity theories which specifically

deals with environmental (stimulus) effects as equally important in

relation to structural person variables. In addition, it moves clearly

away from the interpersonal domain and explores complexity effects in

* other (e.g., non-social, decision making, etc.) domains as well.

Recent Advances in Complexity Theory

o Two recent books are widely concerned with complexity theory.

One is a volume by Scott, Osgood and Peterson (1979) which expands

upon the earlier work of Scott. The other is a book by Streufert

and Streufert (1978) which revises interactive complexity theory and

adds a host of predictions about the effects of cognitive complexity

and environmental complexity on a number of behaviors.

Streufert and Streufert (1978) developed their theoretical

*views on the basis of the interactive theories of Schroder, Driver,

and Streufert (1967) and the more than fifty research manuscripts

published by that research group in the period between 1967 and 1977.

in addition, the complexity theory advanced by Streufert and Streufert

14

.p ~.P / ' " -"" " 
was specifically extended to decision making (Streufert, 1978) and to

environmental problems (Streufert, Nogami, and Streufert, 1980). The

theory views effective cimensionality (as did Schroder et al.. 1957)

as a joint effect of individual (group and, potentially, organizational)

differences in information processing structure and of the characteris-

• tics of the current environment in which an individual (group or

organization ) must function. A number of information processing

characteristics are proposed with a series of associated measures.

Differential predictions for differing environmental conditions and

* for individual (group or organizational) differences are advanced.

For example, a family of inverted U-shaped curves relating environmental complexity to strategic performance is proposed. The different

levels of that curve represent diverse differentiative/integrative

* capacity. The curves differ from those proposed by Schroder, Driver,

and Streufert (1967) by a conceptualization of a common optimal level

on the environmental complexity (for example information load) dimension for both more and less complex persons. The older theory had

* assumed that more complex persons would perform optimally at a

higher level of environmental complexity.

The major advance of the Streufert and Streufert formulations

* are found in their examination of a number of other kinds of performance beyond the strategic (or planning) behaviors expected from

more multidimensional decision makers or decision making groups. The

theory considers the appropriateness of specific levels of a variety

of behaviors (performance) with regard to particular task or environment demands and advances more than 100 predictions relating cognitive

structure to various fields within personality, social and orraniza- I

tional psychology. Because of the rather large number of hypotheses

and proposition generated, a review of such detail would Qo far beyond

the scope of this paper. The interested reader is refered to the

oricinal source documents.

15 
In their most recent book, Scott and associates (Scott, Osgood

and Peterson, 1979) maintain a Zajonc based approach to complexity,

but refine and clarify their conceptualizations of cognitive structure,

in general, and cognitive complexity (as used in this paper), in

specific. The authors continue Scott's emphasis on cognitive domains

and describe complexity in domain specific terms. The description is

based on a geometric model of multidimensional space founded on

euclidian geometry. Objects (conceptual or perceptual) are defined by

their projections into dimensions (called attributes by Scott). Two

otjects, projected onto identical discriminated segments of all

dimensions to which they are assigned, are indistinguishable, even

if they have different names. Correspondingly, two dimensions which

order or classify all objects in the same way are also indistinguishable and considered identical.

The geometric model measures the similarity or the degree

c- distinctiveness of two cognitive domains. If, for example, a

-ackward nation is described as having untapped resources and as

ocssessing great natural beauty, but a technologically advanced nation

is described as a military threat and as a political democracy, then

the two represent cognitions from diverse domains. Following Zajonc

(1960), the complexity of an object is viewed as the number of

(different) ideas a person has about it. Viewed geometrically,

complexity represents the number of different dimensions onto which

an object is projected.

Angles among lines in the geometric model are determined by the

ex erienced or imagined characteristics of objects in a domain.

Together these lines constitute the multidimensional space in which

all objects are accommndated and to which any new object (stimulus)

may be assigned. The dimensionality of this space is, geometrically,

tne number of dimensions worth of space required to accommodate all

o~jects. Osychologically. it represents the independent considerations

rouait to bear by a person appraising a set of objects or cognitions.

16
The model sand its measurement) differs from others in making a

* distinction between attributes which may be obliquely related and

cimensions encompassing the attributes which must be orthogonal.

Some theorists would view such a distinction as artificial, obtained

in the interest of mathematical neatness, but unfortunately, not

* representative of human structural cognition (e.g., Streufert and

Streufert, 1978). Scott's approach differs from those efforts,

however, by not considering systematic variation of the objects in

potential perceptual space. In other words, such problems as "stressors"

0 originating through specific conditions of environmental complexity

are not considered.

RESEARCH

A Summary of Complexity Research Efforts through Early 1977

A detailed review of research on the effects of complexity has

* been conducted by Streufert and Streufert (1978). The interested

reader who wishes to obtain detailed information is refered to that

source. This chapter will merely summarize the conclusions reached

by that review.

If consistency, as has been suggested, is indeed the "hobgoblin

cf little (undifferentiated) minds," then one might expect a negative

relationship between consistency seeking and complexity. it appears

that consistency is negatively related to cognitive complexity, no

matter how complexity is measured. Research data also suggest that

cognitively more complex subjects form more complete and more balanced

impressions of others when presented with some form of an impression

formation task. Differences among more complex and less complex

subjects can. however, be decreased or eliminated by a number of

environmental conditions or instructions, e.g., stress. information

overload, or a "set to evaluate."

17
Earlier theoretical propositions suggested that complex individuals

should be more open to information (of all kinds) than their less complex (but in all other aspects equal) counterparts. While some

researchers appear to have obtained data in support of this assumption,

more careful experimental design has shown that information orientation interacts with stimulus/stressor conditions. Apparently less

complex persons are more bound by the information obtained from the

environment: they search more (than complex persons) when they

experience information deprivation, but they search less when they

are already overloaded. More complex persons tend to rely, in part,

on their own integrative efforts and consequently are not as externally

information bound. In addition, complex subjects seek more novel

information and search across a greater number of information categories.

Research on attitudes and potential for social influence has been

carried out both in restricted (sensory deprivation) and in normal

environments. Generally it has been found that attitudes of less

complex persons are less moderated by differing considerations and are

somewhat resistant to change. If, however, the information provided is

made salient (e.g., in sensory deprivation), attitude change is more

easily obtained for less complex persons. Interpersonal attraction

appears to be greatest among persons of higher levels of cognitive

complexity. However, similar complexity (no matter at which level)

can also be useful in increasing attraction (at lower levels, similar

content, e.g., attitudes, appears to be a precondition, however).

Several researchers have investigated whether complex persons

are more flexible and/or more creative. While the data on this issue

cannot be considered conclusive, they at least suggest that a tendency

toward greater flexibility exists, allowing the kind of flexible

behavior that can and often does result in acquiring additional

cognitive complexity.

78

0
Efforts to investigate the tendency toward extreme judgments

have been reported by a number of early researchers. Two diametrically

opposed theoretical arguments have been advanced. Harvey and associates

(e.g., White and Harvey, 1965) believe that the greater number of

judgmental dimensions involved should produce an "averaging response"

0 in the more complex persons, allowing less complex respondents to

respond with more extreme scores when the selected scales are salient.

On the other hand, Nidorf and Argabrite (1970) believe that the

available multidimensionality should make complex persons more con-

* fident, allowing them to respond in more extreme fashion. Unfortunately,

the data do not allow us to select one or the other of these views as

accurate: inconsistent results have been obtained by various researchers.

Research on problem solving and decision making has, however,

produced quite consistent results. It appears that more complex

subjects search for more different kinds of information when they are

faced with a decision making problem and are less certain when they

* have made a decision (for which no immediate correct/incorrect outcome

information is available). More complex subjects also reach higher

levels of strategic action and of planning than their less complex

counterparts, yet these discrepancies are restricted to conditions of

o intermediate environmental load (and other environmental complexity)

levels. Similar data are obtained for information utilization. It

appears that higher levels of strategic or planning performance is a

linear function of the number of complex persons in a decision making

*group.

Training to differentiate and/or integrate a single domain of

relatively simple tasks appears to meet with some success. Single

sets of instructions on how to perform in more complex fashion did,

however, produce even more unidimensional responding in less complex

subjects.

19

9,
Several theorists have suggested that cognitive complexity

should show some relationship to leadership. Comparison of leadership

styles indicates that more vs. less complex leaders apparently

emphasize different kinds of the leadership styles listed by Stogdill

(1962). Considerable discussion about a potential tie between Fiedler's

* (1958) Least-Preferred Coworker (LPC) Scale and measures of complexity

has also appeared in the literature. Both the score a person obtains

on the LPC and the variability of responses on the LPC have been

advanced as supposed indicators of cognitive complexity. The argu-

• ment that a person who sees some values (based on multiple dimensionality) in even the least preferred coworker might also score higher

on measures of differentiation, appears, at first thought, to have

some credibility. Data relating LPC to various measures of complexity

C: are, however, quite inconsistent. Since some researchers obtained

positive; others, negative; and yet others, no relationship, the

possibility of interaction with third variables certainly exists.

* Cognitive complexity has been shown to relate to the ability of

clini-cians to interact successfully with patients or clients. Again,

a match in complexity was helpful and greater complexity of the

clinician was an aid in "reaching" the patient. Some preliminary

* research has also suggested that elevated GSR measures were obtained

from complex subjects and that schizophrenics generally scored low in

cognitive complexity.

An interesting aspect of the various research efforts is the

common predictive success for various complexity measures that, in and

of themselves, fail to intercorrelate highly. It appears that complexity

as a style may indeed be an overall phenomenon, that the various

theories describe potentially quite diverse (summative) parts of that

phenomenon and that the measures (see below) tend to focus on separate,

yet coactive or interactive, components of complexity which together

tend to produce an overall effect.

20
in a major review effort in the area of cognitive style,

Goldstein and Blackman (1978) identified a number of constructs

that reflect cognitive complexity or potentially related styles.

For comparison purposes, they also consider authoritarianism,

field dependence/independence, and dogmatism. A table, showing

correlation values among these measurements which have been obtained

by various researchers was presented by Goldstein and Blackman

(p. 215 and following). Parts of that table are here reported in

somewhat modified form. Goldstein and Blackman did not distinguish

between measurement based on conceptual systems theory (e.g.,

Harvey et al., 1961) and interactive (integrative complexity

theory) (Shroder et al., 1967). Data obtained from those different

points of view and associated (differentiative) measurement efforts

C are now separated. In addition, segments of the table are partially

relabeled to reflect the terminology used in this paper. Some data

that had been omitted by Goldstein and Blackman has been added.

21

q.

i-
TABLE 1. INTERRELATIONSHIPS AMONG COMPONENTS OF COMPLEXITY

*AND VARIOUS OTHER CONSTRUCTS

(adapted from Goldstein and Blackman, 1978)

Study Instruments Correlation Sample

1. Differentiative Complexity X Conceptual Systems Complexity

Harvey (1966) Rep Test As expected Summary of other

TIB Test data

Hunt (1962b) Adaption of Rep

Test .37 136 6th-12th

grade boys

SIE

Epting &

Wilkins (1974) Bieri Rep Test .31 90 undergraduates

Conceptual

Systems Test

Bieri Rep Test -.31 90 undergraduates

PCT

Smith &

* Leach (1972) NS 27 unspecified

Bieri Rep Test

TIB Test Significant 27 unspecified

Hierarchical

measure of cognitive com-

* plexity (Mann-Whitney

U = .50)

TIB Test

2I

22

*' v ' ' ' ' ' ' " " ' - " " " ' ' ' ' . . ' '. .' . .' . .. ' ' . ' .. .. " -. " -. . " ' - , . . - . , , . " '

P"","°- ".. ""- _" ." "t -..; '""- ' ''- -,' . '' ,' " . "/ ..- - ''" .'"" " - ""."" ''" "'-"." " '" " , " """"".
. . .

q!

TABLE 1 .INTERRELATIONSHIPS AMONG COMPONENTS OF COMPLEXITY ...

(continued)

Study Instruments Correlation Sample

*2. Differentiative Complexity X Integrative Complexity

Streufert

(1970) Rep Test Low and sometimes negative Summary of

other data

SCT

Vanno (1965) Modified Bieri

Rep Test NS 1113 male undergraduates

Streufert

(1972,

unpublished) SCT, Scored for

integration Rep .12 340 undergraduates

* SCT, Scored for

differentiative Rep +.69 340 undergraduates

3. Differentiative Complexity X Field Dependence

Elliott (1961) Modified Bieri

Rep Test NS 128 male underR FT graduatesI

Modified Bieri

*Rep Test NS 128 male undergraduates EFT

*i

4

0

23I
TABLE 1. INTERRELATIONSHIPS AMONG COMPONENTS OF COMPLEXITY...

* (continued)

Study Instruments Correlation Sample

* 4. Conceptuai Systems Complexity X Field Dependence

Stewin (1976) ITI, TIB Test NS 100 11th-graders

Group EFT

Wolfe,

* Egleston &

Powers (1972) PCT NS 32 undergraduates

EFT --. - - - - . . . . .- .- .- . .-. . . ..-- . . ..-- - - - . . . . . . . . . . . . . . . . . . . . . . . . . .

5. Integrative Complexity X Field Dependence

Stewin (1976) PCT

Group EFT NS 100 11th-graders

6. -Dogmatism X Differentiative Complexity

Bieri (1965) Dogmatism Scale .27 Females, unspecified

* Modified Rep Test NS Males, unspecified

Pyron (1966) Dogmatism Scale NS 80 undergraduates

Modified Rep Test

Starbird &

Biller (1976) Dogmatism Scale NS 180 undergraduates

* Bieri Rep Test (F Test)

7. Dogmatism X Conceptual Systems Complexity

harvey (1966) Dogmatism Scale As expected Summary of other

TIB Test data

Rule &

Hewitt (1970) Dogmatism Scale .23 91 male under45 ITI NS 113 female undergraduates

24

* A
TABLE 1. INTERRELATIONSHIPS AMONG COMPONENTS OF COMPLEXITY.

(continued)

Study Instruments Correlation Sample

* 8. Dogmatism X Integrative Complexity

Schroder,

Driver &

Streufert

* (1967) Dogmatism Scale Low Summary of other

SCT or IFT data

Schroder &

Streufert

(1962) Dogmatism Scale NS 147 male highschool students

SCT

Streufert &

Driver (1967) Dogmatism Scale NS 124 male undergraduates

IFT

9. Authoritarianism X Differentiative Complexity

Bieri (1965) F Scale .45 Females, unspecified

Modified Rep Test NS Males, unspecified

Pyron (1966) 28-item F Scale NS 80 undergraduates

Modified Rep Test

Vannoy (1965) 10 original and

10 reversed

F-scale items .20 113 male undergraduates

Modified Bieri

Rep Test

25

f
TABLE 1. INTERRELATIONSHIPS AMONG COMPONENTS OF COMPLEXITY...

(continued)

Study instruments Correlation Sample

10. Authoritarianism X Conceptual Systems Complexity

Harvey (1966) F Scale As expected Summary of other

TIB Test data

Rule &

Hewitt (1970) 28-item F Scale .39 91 male undergraduates

ITI .29 113 female

undergraduates

----------------------------------------------------------------------

!I. Authoritarianism X Integrative Complexity

Schroder,

Driver &

Streufert

(1967) F Scale .25-.55 Summary of other

SCT or IFT data

Schroder &

Streufert

(1962) 30-item F Scale .34 147 male highschool students

SCT

Streufert

& Driver

(1967) F Scale .18 124 male undergraduates

IFT

Vannoy (1965) 10 original and

10 reversed

P-Scale items NS 113 male undergraduates

--------------

SCT

26

-...... ......
Recent Research

About half of the 600 or so manuscripts which have become available

on cognitive complexity since the latter part of 1977 are dissertations.

They have not been included in this review. Consideration of complexity

research published in the last four years is limited to journal publications and chapters where either the quality of design, data collection,

and analysis was sufficient to merit consideration, or where the weight

of several papers with similar results (despite limited quality) would

suggest that a reliable conclusion may have been reached. Discussion

of the research will be achieved through use of a number of subheadings.

1. Communication.

Hale (198Q) has shown that complex persons are more effective

at a communication dependent task (describing a complex tinker-toy

design) than are unidimensional individuals. Complexity was also

positively related to interaction frequency (Zalot and Adams, 1977).

Part'of the greater success of more complex persons may be due to their

greater ability to be intimate with others (a finding that holds only

for integrators, but not for differentiators (Neimeyer and Banikiotes,

1980)). Finally, more complex persons, as compared to their less

complex counterparts, are more resistant to persuasive attacks if

inoculated (Cronen and Lafleur, 1977).

2. Attitudes, Attributions, and Attraction.

Bhutani (1977) reported that attitude change is more easily

achieved in complex individuals. This result is probably due to

0greater consideration of additional (including novel and unexpected)

information, resulting generally in greater evaluative moderation

(c.f., Linville and Jones, 1980). Such moderation, incidentally,

appears to apply more in familiar than in unfamiliar contexts.

27
Similar data are also reported by Okeefe and Brady (1980) who found

that non-complex subjects were much more likely to polarize after

thought about a subject matter.

Findings of this nature would, of course, make the concept of

cognitive complexity more interesting to applied researchers who use

attitudes and intentions for specific ends, e.g., researchers concerned with marketing. Research has generally confirmed that complexity

is directly related to attitudes or attributions which are product

relevant. For example, Durand (1980) obtained results indicating that

complexity is related to affect and dispersion of affect ratings

for brands of toothpaste and automobiles. Specifically, consumers

with less differentiative ability tended to be more alienated (Durand

and Lambert, 1979; c.f., Durand, 1979). In part as a result, less

complex subjects formed more extreme (but potentially alienated)

attitudes and tended to be more confident about those attitudes

(Mizerski, 1978). These data are reminiscent of the earlier work of

Sieber and Lanzetta (1964) with decision making and complexity.

Moderation of attitude may impinge on the attractiveness of

persons. In line with previous findings (discussed earlier), greater

complexity may make a person more attractive to both more and less

complex people. While previous research (above) had shown that it is

of advantage to counselors to be complex (multidimensional) if they

are to be attractive to clients, the more recent data (reported by

Davis, Cook, Jennings, and Heck, 1977) reverse the direction of

source and target of attractiveness: more complex clients appear

to be more attractive to both more and less complex counselors. The

generality of the attractiveness findings in earlier research and the

Presently discussed efforts appear to suggest that the relationship

between complexity and attractiveness to others appears to be a

quite reliable phenomenon that can likely be generalized to other

situations, e.q., supervisor-employee settings.

28
3. Leadership.

The interest in the relationship between leadership and

cognitive complexity has continued in recent years, testing

whether the assumption of Mitchell (1970) that there is a

clear relationship between these variables is defensible.

Generally, the data either do not support (or provide only very

limited support) for the proposed relationship (e.g., Arnette, 1978;

Schneier, 1978; Vecchio, 1979; Weiss and Adler, 1981).

4. Information Orientation.

Recent data continue to support the earlier finding that

complex persons are more widely information oriented, conditions

permitting. Research indicates that some other variables, such as

Machiavellianism and social intelligence can be partialed out without

loss to the complexity effect on information orientation (e.g., Hussy,

1979). Complex persons (here managers) were also found to be more

effective in terms of information utilization (Hendrick, 1979).

5. Perception.

How information received by a person is perceived has been

of continued interest to complexity researchers. Part of that

interest probably stems from the "social perception" orientation of

most of the earlier complexity theories. The data obtained by a

host of researchers support the notion that complex persons are

"better" at perception, i.e., will take more information into account,

will fo-m more rounded impressions, and so forth. Many of the findings are explained by researchers in terms of a "good" vs. "bad" way

to be, i.e., it is good to be complex, bad not to be complex. This

notion, however, has no basis, in fact. Not all situations and all

tasks require or even warrant complexity, particularly if it is a

oervasive style that cannot be "turned off" when inappropriate.

29

ID
Research supporting the greater breadth of information orientation for complex Persons has been obtained from a divergent range of

settings and tasks. For example, complex persons seem to spread their

cognitive categories more evenly across observed others, regardless

of the role in which those others are perceived (Okeefe and Delia, 1978

i978). Perceiving others in such fashion reflects potential

differentiation and at least some integration, leading to less

rejection of inconsistency in received information (Wojciszke, 1979)

and more oDenness to inconsistent verbal messages (Domanque, 1978).

As a result, Polarization of attitudes after perception and thought

is lessened for the more complex subjects (Okeefe and Brady, 1980).

Yet, it is not only the external cues which appear to be perceived

differently by more complex subjects; the cues are also integrated

into their perceptual framework in a more extensive fashion. As

a result, the more complex persons appear to base their evaluation

of others on (perceived) internal motivational characteristics

rather than on just external behavioral characteristics. Consequently,

* the quality and quantity of hypotheses about the behavior of others

are-likely to increase and the number of questions raised about the

underlying causes of another's behavior are likely greater for complex persons (Holloway and Wolleat, 1980). Greater quality and

* diversity of hypotheses and questions would decrease the need for

evaluation as a sole determinant of Perception, again resulting in

greater complexity (Wojciszke, 1979). Not surprisingly, specific

social perceptual complexity appears to be greater for females

than for males (Zalot and Adams, 1977).

A number of researchers have focused on the characteristics of

the stimulus, or upon its relationship to the perceiver, as related

to the utilization of a person's potential complexity. It appears

that close emotional involvement with another is likely to reduce A

the complexity of perception under some (but not all) conditions.

Generally, individuals whom one knows less, or with whom one is less

30
* involved, may be Derceived in a more complex fashion. For example,

Wojciszke (1979) found that little known, ambivalently, or even

negatively valued persons are perceived in a more complex fashion

than well known, positively valued persons. However, once negative

valuation turns into dislike, complexity of perception appears to be

reduced. Cioata (1977) reported that persons are significantly more

complex in evaluating liked than disliked persons and are more complex in evaluating themselves than others. A somewhat inconsistent

result was reported by Horike (1978) suggesting that a V-shaped

relationship exists between complexity of perception and degree of

acquaintance. Since this author manipulated acquaintance in the

laboratory, it is not clear whether the data are comparable to those

of other researchers. Finally, absence of information and absence

of interest with regard to others (here, political candidates) tends

to reduce the complexity of perception (Mihevc, 1978).

6. Development and Personality.

A number of authors continue to research the relationship

of cognitive complexity to development (in Piagetian and other

terms). Generally, the findings suggest that cognitive complexity

can increase through childhood years and may be related to stages of

development proposed by Piaget and others (e.g., Beagles and

Greenfield, 1979; Chandler, Siegel, and Boyes, 1980; and Delia and

Clark, 1977). Developmental differences appear to lead to specific

0, behavioral characteristics which can, in part, be assigned to

personality content. For example, Bruch, Heisler, and Conroy

(1981) have shown that more complex persons display greater

content knowledge, greater delivery skills, and more assertivef# ness when placed into difficult situations. Differences were

not obtained in more simple situations. Other findings suggest

that persons who are cognitively complex score higher on ego

identity (see the section on clinically oriented research below).

31

4.. ..-..... ....-..-.... .. .. ........ ......
It has been argued repeatedly that complex persons should

be more creative (but not necessarily on simple creativity tests)

when creativity is measured in applied settings. Research by Quinn

(1980) has supported these assumptions: a significant difference in

cognitive complexity was obtained between creative writers and matched

controls. No differences between writers with different degrees of

creativity was obtained (this result is likely due to the author's

selection of a complexity test which measures only differentiation).

7. Clinical Applications.

Personality measurement as it relates to clinical applications

has generated a number of relationships to cognitive complexity.

Complex persons who scored higher in ego development (Vetter, 1980),

in both the U.S. and in Germany, tended to feel less alienated

(Durand and Lambert, 1979), and proved to be more emotionally stable,

but potentially more anxious (Cioata, 1977). The finding on anxiety

is, however, contradicted by other research (Raphael et al., 1979).

Part of the reason for the differential findings may be the adaptation

of the respective person to his or her particular problem or situation.

For example, experiencing an emotional handicap may increase cognitive

complexity (Vace and Burt, 1980).

8. Performance.

* The previously discussed research topics have been focused

on the stimulus, or perception, and on personality outcome. We now

turn to behavior, focusing first on general performance, and continuing

(in the next section) with decision making performance as a special

O case.

One would not expect that all kinds of performance in all

environments would necessarily be affected by cognitive complexity.

32
Indeed, several studies show no relationship. For example, Wolfe

and Chacko (1980) found that complexity did affect the perception

of a business qame environment, but did not produce any changes in

performance outcome. On the other hand, complexity does appear to

have considerable influence on performance measures in a variety of

other task settings. Jones and Butler (1980) report significant

correlations between complexity and global indices of job performance

among Navy personnel. Hendrick (1979) found that less complex persons

took twice as long as complex persons to complete a problem solving S

task. More complex groups interacted at a faster pace and demonstrated

better cue utilization. In yet other research, complexity predicted

performance in a fault diagnostics task (Rouse and Rouse, 1979) and

related to risk taking in traffic situations (VanEye and Hussy,

1979). The conclusions reached by Hussy and Scheller (1977) sum up

the results of a number of studies concerned with performance.

These authors concluded on the basis of their own research that

variables involved in cognitive complexity are probably the most

S predictive and discriminative for problem solving tasks.

Following the earlier demonstration of environmental effects

on performance and their interaction with cognitive complexity, a

O number of researchers have more recently explored the effects of

"overload" and related variables in tasks which differ from those

employed by Streufert and associates. The data reliably suggest

that excessive load is detrimental across a number of diverse tasks.

For example, Rotton, Olszewski, Charleton, and Soler (1978) report

that overload (via loud noise, loud speech) reduces the ability to

tolerate frustration, and the ability to differentiate among roles

occupied by persons. White (1977) concludes that less complex persons

become overloaded and show the effects of overload sooner than more

complex persons (this data appears to be in contradiction to the

majority of findings on complexity, load, and performance which has

suggested no significant differences between more and less complex

33
* persons in optimal environmental input levels. in a review of 75

publications relating environmental complexity (including load) to

performance, Shalit (1977) concluded that effectiveness of coping

appears inversely related to the complexity of the situation. It

should be noted, however, that the majority of the reviewed research

efforts have concentrated on overload only, and did not consider the

effects of less than optimal load (or other environments).

9. Decision Making.

In a series of studies by Suedfeld and associates (e.g.,

Suedfeld and Tetlock, 1977; Porter and Suedfeld, 1981), the conceptualizations of political and literary figures across several

centuries were analyzed and related to decision making outcome and

similar measures. The data indicate that a lowering of differentiative and integrative complexity (e.g., in the content of speeches

made) precedes hostility (e.g., the decision to go to war), and that

failure to increase complexity after the end of a crisis (here,

revolution) results in failure (removal of the leadership which has

successfully completed the revolutionary process). In addition,

it appears that complexity decreases with illness and in the five

years prior to death, but otherwise increases with age.

Following the arguments of Suedfeld and the earlier work

of Driver (1962); Levi and 7etlock (1980) analyzed the period pre-

*ceding the Japanese decision to go to war (World War II). They found

relatively weak evidence for cognitive simplification as the decision

to engage in warfare was made, but showed that the discussions held

during decision making meetings at that time were representative of

9 lower levels of complexity than the meetings where these decisions

were presented to the emperor for approval.

34

S: : : : : .:_::% :: :: ::.::: :.: - :: - ::..: : " " " " : • : "
The previous work of Streufert, confirming a family of

inverted U-shaped curves relating environmental complexity to strategic

(and planning) performance (with different levels of the family of

curves representing diverse degrees of cognitive complexity), continued

to be replicated during this period. Interesting are the additional

data showing a weak relationship of cognitive complexity to Type A

coronary prone behavior, but showing, in addition, that greater

cognitive complexity produces greater arousal under challenge

(measurement of heart rate and systolic/diastolic blood pressure).

This arousal discrepancy between more and less complex persons could

not be explained via the low order correlation of complexity with

Type A (Streufert, Streufert, Dembroski, and MacDougal, 1979). Other

research did indicate, however, that time urgency (a component of

Type A behavior) is able to depress differentiation and integration

in decision making, even under optimal load conditions (Streufert,

Streufert, and Gorson, 1981). Research by Harren, Kass, Tinsley,

and Moreland (1979) has related complexity to career choice; work

by White (1977) indicates that a task in which a person must

analyze the social structure of a group on the basis of partial

information is performed better by complex subjects when the

number of relationships that must be estimated is relatively large.

a. Single Strategy Decision-Oriented Approaches.

Decision situations often may present themselves as

being either well structured or ill structured. Wellstructured decision problems usually require only routine

transformations which may take the form of algorithms

or heuristics. An algorithm may be thought of as an

operation that guarantees a solution in a known situation with a finite number of steps. Heuristics may be

thought of as more generalized, outlined rules of

thumb which have proven historically to be useful, but

35

,

" ' ' . • " "". : - '
'C

r

which may not guarantee success (MacCrimmon and Taylor,

•1976). Heuristics may be internal to the dcision ma!,e.r

(such as "ethics" or "common sense") or they may be

imposed by the environment (such as company policy or

conventional wisdom). Algorithms are typically

internalized from the environment via education or

experience. Toda (1976) suggests that these repeatedly

used approaches often become automatic and can be

disadvantageous or detrimental if they lose their

relevance in a rapidly changing world. Svenson (1979),

on the other hand, sees them as simplifying strategies

which a decision maker may use in a complex, multiattribute alternative situation to arrive at a decision

more easily.

ll-structured problems are more common and

demand that a decision maker exert more effort to

find effective strategies for solving them. Illstructured decision situations are those which are

characterized by uncertainty, complexity and/or

conflict (MacCrimmon and Taylor, 1976). The

* effort to explain how these conditions are contended with has produced works suggesting a

variety of techniques which might be used to

reduce or cope with them. Jones, Schipper, and

CHolzworth (1978) suggested that four intrinsically

available decision strategies exist regarding

probablistic "cues." They hypothesized that a

decision would be based on: (1) the sum of cue

values which is largest among alternatives,

(2) the largest cue average, (3) the largest

single cue, or (4) the alternative with the most

cues. Similarly, Olshavsky (1979) presented five

36

-
-, 7 

* stratecic models. In the Additive model, the overall

worth of each alternative is first assessed and then

a final ordinal comparison is made on the basis of

this index. The Additive Difference model involves

pair-wise comparisons of the alterna-ives in distance

terms along separate dimensions, followed by a summation across differences. Attribute Dominance concerns

one alternative dominating another simply in number

of attributes. The Conjunctive model is applied

when a multiattribute alternative surpasses a

standard or cutoff level; and the Lexicographic

model reouires that attributes are first ordered

according to importance, than all alternatives are

evaluated on the first attribute, with those not

exceeding the cutoff level excluded. If more than

one alternative 'emains, the second most important

attribute is selected and the alternatives are

evaluated on that cutoff limit. The process contines until only one alternative remains.

Svenson (1979) identified seven strategies or

o decision rules. Those represented by Jones, et al.,

and by Olshavsky were called by Svenson "rules

without commensurability," meaning that attractiveness of attributes may not be compared or counterbalanced in a situation. Svenson expanded the list

by adding rules which do allow commensurability.

Her Ordinal Attractiveness model provides for maximizing the number of attributes with greater

attractiveness: elimination by least attractive

aspect, and choice by more attractive aspect. She

also identified an Ordinal Attractiveness Difference

model.

37

(
7'

At a higher level of representation, Svenson

introduced the concept of "utility." Her Interval

Attractiveness (utility) and Commensurability rule

allows for both addition of utilities where decision

is based on a summation of all utilities for each

alternative, and for addition of utility differences

when a decision is based on differences between the

utilities of different alternatives on the same

attribute. Finally, Svenson suggested a Ratio

Attractiveness and Commensurability rule which

relates to subjectively weighted utilities models.

Such models imply that the utility of each aspect

should be weighted by the subjective probability

of its occurrence when summing the utilities for

an alternative.

Articles dwelling on singular strategies

seem to be subsumed within the Svenson perception.

For example, Larson's (1980) work on Expected

Utility and Subjective Weighted Utility would fall

under Svenson's Interval and Ratio Attractiveness

categories. Park's (1978) Sequential Conflict

Resolution model, which was based on earlier

Elimination by Aspects models, and his Satisficing

Plus model can also be placed in the higher level

• representations.

Svenson has suggested that noncommensurate

riles represented simpler levels of cognitive

* operation while the commensurate rules represented

more complex levels. She also noted that to

implement the higher order, complex strategies,

more information was needed. She recommended

38

0NI
* verbal protocol (subject verbalizing the thought

process as it proceeds) and information search

tracing, such as eye movement or questions asked,

as processes to identify the information gathering

activities used in reaching a decision. She felt

that they would provide enough information to infer

the process used. However, she stopped short of

inferring detailed predictions about the cognitive

complexity of a decision maker relative to the

complexity of the decision process used. Her

methods demonstrated fluctuation between simpler

and complex strategies rather than a preferred

level dependent on an individual decision maker.

She suggested that this may reflect the effort to

simplify through heuristics on one point when a

decision maker feels overwhelmed, and alternately,

that the decision maker who feels no overload may

0 display stimulation seeking by more detailed

evaluation, using more complex rules.

Wright (1979) traced strategies to determine

the level of "effort" associated by a decision

maker using various strategies considered to differ

in complexity. He found no significant difference

reported by subjects using rules with different

* levels of complexity. This would seem to counter

the temptation to assume that the noncommensurate

strategies, assumed to be simpler, are primarily

used by subjects with limited cognitive resources,

O or that commensurate strategies are available only

to those with wider ranging cognitive resources.

39

S --ii - 1 ..1> -11L. L - - --.i i> '." .> i, - '- 1. i - -,i > "'i> .1 - , i " ----- iZ1i1i
Svenson concluded that it is difficult to

generalize over different types of decision problems

since different subjects perceive the same objective

decision problem in different ways, and they react in

relation to their own perceptions. Identical rules

may result in different final decisions for different

subjects. Svenson's and Huber's (1980) work

ultimately led them to conclude that the studies of

individual decision rules are not productive because

decision making is a multi-stage process with

differing levels of complexity at different stages.

Einhorn and Hogarth (1981) suggested that a

0 multi-method approach might be more fruitful; and

Milburn (1976), and Park (1978) also agreed that

rules do not adequately account for decision flexibility. Park describes decision making rules as

0 overlapping and crudely ordered phases with interrelated decisions at each step, indicating a complex

process which demands a more integrated model.

Park adds that decision rules taken alone and studied

* for prediction or description assume that decisions

are made without regard for the cognitive capacity

("bounded rationality") of the decision maker, and,

thus, are of questionable value by themselves.

b. Multi-stage Processing.

A reasonable next step toward a more complex

* representation of decision making is shown in works

which attempt to model how the various decision rules

identified, but found wanting, in the previous section of this report are combined into strategies or

0

40

0i

.................... .1
9

* pre-planned sequences of goals to arrive at a

decision. Efforts at this level try to identify

which rules are applied and what factors relate

to changes among the rules.

Perrault and Ross (1977) used verbal protocol techniques to determine whether the simple

linear (noncommensurate) rules were sufficient

in a multiattribute condition. They found that

0 linear concepts showed little evidence that they

are really descriptive enough to account for

decisions in multiattribute situations. They

found that the more complex Lexiocographic models

were more appropriate when evaluation of alternatives is required. Olshavsky (1979) attempted to

determine the effect of multiattribute and of multialternative dimensions on various decision strategies

employed, and found that as number of decision

alternatives increased from three to twelve,

subjects typically switched from one-stage compensatory strategies to multi-stage processes

* involving screening and then evaluating remaining

alternatives, with weighting processes as subroutines. He assumed that the strategy chosen was

contingent upon the number of alternatives and

* attributes of the alternatives, and that the more

complex strategies came into play when the numbers

of each increased. However, he also found wide

variations with respect to the numbers both of

0 alternatives and of attributes that caused

complexity levels to change.

41

.1* . ." . .. . . .

. . .
Christensen-Szalanski (1978) viewed strategy

* selection as contingent upon the characteristics

of the decision task, and also as contingent upon

the characteristics of the decision maker. He

acknowledged that each person has a repertoire of

methods for dealing with problems and making

decision, but also suggested that in western

cultures most educated people believe that the

more thoroughly and systematically one approaches

* a decision (problem) the greater are the chances

of being correct. That is, more analytic, formal

strategies are seen as having a higher probability

of being correct. Christensen-Szalanski assumed

that the level and style of a strategy implemented

would be related to the decision maker's conception

of greatest expected net gain in a financial

decision making taks. He concluded that the benefit

of "correctness" would lead to longer time to the

solution, and that the longer time would reflect the

confidence of the subject in the decision or solution

selected. Further, the more "value" to De gained in

a situation would make more complex strategies worth

the effort to employ them. This, in turn, would

increase the subject's confidence in a solution or

decision.

Such results are compatible with Svenson (1979),

Park (1978), and Olshavsky (1979); all of whom

suggested that effort minimization, where more

complicated mechanisms are only applied where

necessary, appears to be a common outcome.

Olshavsky also noted that information overload

could lead to simpler strategy applications. Such

42
works. however, raise questions about when and why

decision strategies are switched in complexity

level by decision makers, as none of them are able

to predict level change, but merely to acknowledge it.

They may, however, lend credence to Park's (1978)

*model of Operationalized Satisficing Plus strategy

which suggests that simplified representations of

problem or decision situations are created by

"chunking," or re-categorizing dimensions, arid, then

*alternately reducing and choosing from among

remaining alternatives. Park suggests that his

model showed significant prediction capability

as compared with unsequenced decision rule models.

The unsequenced rules, Parks feels, represent only

pieces of the overall process, while his representation appears more comprehensive.

Going beyond simple efforts to identify conditions relevant to sequencing decision rules,

Einhorn and Hogarth (1981) have recognized the

possibility of the sequential use of cognitive

processes within decision makers. This suggests

that multi-method efforts will be needed to reveal

and model individual decision processes in full.

Attention, memory, cognitive representation, conflict resolution, learning, feedback effects, and

even creativity and concept formation: all are

seen as intertwined in the decision process and

must be considered and integrated into studies for

a complete picture of decision making as a process

to emerge.

43
c. Computer-Based Decision Support.

Recent advances in the area of computer-based

decision support deserve mention. One of these,

termed Decision Support Systems (DSS), has been

reviewed by Watkins (1982). According to Watkins,

information supplied by a DSS must be selective in

or 

that 

economically 

not all possible 

represented 

information 

in a given 

sets may 

data 

be 

base.

feasibly I

Watkins has suQQested that discovery of perceptual

complexity (dimensionality) of information items,

and the subsequent categorization of decision makers

having the same perceptions of those information

items, is a first step in the ultimate design of an

effective DDS. Through the use of multidimensional

scaling in a field setting, Watkins has shown the

feasibility of creating relatively homogeneous groups

of decision makers according to the content and number

of dimensions associated with various information items.

Further results of the research have suggested that

information can be tailored to classes of users,

which has cost-benefit implications as well as the

potential to improve the quality of the resultant

decisions.

If decision makers' perceptions of information

are able to influence the decision process, information

system designers need an understanding of the way in

which perceptions affect that process. This understanding

seems particularly critical for top-level decisions

which are complex, unstructured, and have long-range

implications. Perhaps perceptual commonalities can

be found among decision makers to enable the formation

44

. .. . .,... ..
of relatively homogeneous groupings of decision

makers. Such a finding would allow information

reports to be tailored to groups of decision makers,

as opposed to the more costly, and perhaps infeasible,

tailoring of reports to individuals.

It has been argued that DSSs should be tailored

to decision activities rather than decision makers

due to potentially costly design changes caused by

* frequent turnover of decision makers. While this

argument may be valid at the operational or management control level, it is less important at top

management levels, which are generally characterized

O by greater stability and less turnover than are the

lower levels of the organizational hierarchy.

A second effort, an overall approach to the issue

* of computer compatibility with decision style, termed

SIMTOS, was described by Strub and Levit (1974).

According to this approach, the concept of decision

style, while rooted in cognitive and personality

theory, has found application in computer system

desion as a basis for decision aiding. As used in

an information system context, decision style may

be defined as the characteristic and self-consistent

o

way an individual uses information in the decision

making process. A model of decision style was

developed to classify eight styles according to

three dimensions.

45

CO
qACTIVE

• INTUITIVE

ABSTRACT CONCRETE

0 LOGICAL

PASSIVE

Figure 1. Dimensions of Decision Style

The model hypothesizes that individuals differ in

the way they acquire and organize information: some

use concrete information (e.g., maps, personnel

figures) more than abstract information (e.g.,

policy). Individuals also differ in the way they

assimilate and process information: some follow

heuristic patterns (i.e., they are more intuitive),

others strictly follow established decision rules

or algorithms (i.e., they are logical). Finally,

some take vigorous, aggressive and forthright

action. They are active, while others are more

conservative in their activities and are considered

passive.

The methodology for assessment of decision

style, developed by Strub and Levit, centers around

a diagnostic inventory called the Decision Style

Measurement Instrument (DSMI), an instrument designed

for determining individual differences in information

processing among decision makers, using a methodology

pioneered by Briggs-Myer (1962) for the type

Indicator.

46

€ 46

-. . .
Research by Pask (1971) and Morris (1967)

illustrates that if there is a mismatch between

decision style and mode of information presentation, large decrements in cognitive task performance

can be expected. Decision makers need information

* Oconsistent with their information processing

characteristics, not information that is determined by computer system constrair"s (Henke,

Alden, and Levit, 1972).

10. Training

If complexity can develop, and if, as described above,

o instructions in simple tasks may allow an otherwise less complex

person to respond similarly to a more complex person, then complexity may by trainable. Theoretical points of view on training

vary, yet, in all probability, none of the theorists reviewed

0 would predict a rapid and overall training potential. Little

research on training effects has been performed. The results of

the few completed studies are equivocal. For example, Sauser and

Pond (1981) were not able to obtain any change in complexity with

. their combination of training procedures. On the other hand,

Cronen and Lafleur (1977) using an inocculation/persuasion paradigm were able to obtain some increase in overall complexity with

massive attacks on truisms. Whether the results reported by these

authors are, however, due to a real increase in complexity or may

be explained by learning of procedures and/or arguments cannot be

determined without further research. Generally speaking, the area

of complexity training is probably the least researched area of

cognitive and environmental complexity.

One study (Stabell, 1978) did investigate directly the

relationship between training-oriented requirements and applications

47 "~ * 
of cognitive complexity. Stabell has correctly suggested that much

4' work needs to be accomplished to define the task characteristics

associated with cognitive decision making and how these characteristics

interact with performance success in decision making tasks. Stabell

found that the volume and breadth of information source use in the

* problem finding phase of the decision making process are positively

related to the integrative complexity of information environment

perception, and thus underlines the importance of detailed task

analysis and task modeling in research on individual differences.

Summary

Clearly, much of the earlier, and a considerable amount

0of the later, research on cognitive complexity has focused on perception with only minor, if any, interest in the interactive effects

of environment and a person's (group's) cognitive structure. Some

of the later research based on interactive complexity theories

(Schroder, Driver, and Streufert, 1967; Streufert and Streufert,

1978) has taken a more interactive, and consequently applicable

approach. Generally, the reported research, based on the latter

theories, is strongly supportive of the assumption that cognitive

complexity has considerable impact on information processing and on

the outcomes of that effort, both in the social and non-social,

both in the perceptual and the performance realms. However, as

discussed earlier, not all research has supported the contention

C

that complexity is causal of or related to specific perceptions

or behaviors. Such an all encompassing effect of complexity should

not be expected. Differentiation and/or integration should occur

only in environments where these structural characteristics can be

appropriately applied and where they are useful to understand and/or

solve the problems at hand.

48

; " - -' "° • ." .. "" " .. : , ._ .:~ L ..... ' : i-i
MEASUREMENT

In dealing with the complexity literature, one finds that the

utilized measurement techniques can effectively divided into two

relatively distinct categories: (1) measures of cognitive information

• processing, yielding scores of differentiation and/or integration in

the comprehension and organization of (typically social) stimuli; and

(2) measures of differentiation and integration in performance,

reflecting strategic action and long range planning. Measures

* developed during the early stages of the various complexity theories

are typically of the first kind, designed to select more or less

complex persons from some population. Measures of performance,

decision making, and so forth, as a rule, were developed later when

questions of the relationship between the complexity of input

processing and output were raised. This discussion will deal with

the two kinds of measures separately.

Measures of Cognitive Information Processing

Measures of cognitive information processing, most often focusing

on perceptual modes of cognitive processing, have been primarily

designed as selection instruments to distinguish between persons

differing in complexity. While some of the measures focused on

differentiation, others have attempted to capture integrative style,

and yet others appear to concentrate on discrimination (i.e., upon

6 single dimensions). Generally, research has demonstrated that the

intercorrelation among certain groups of measures may be high, yet

correlations among the various groupings of measures may be quite

low (e.g., Vannoy, 1965). The reason for such low intercorrelations

may be found in the different components of complexity that tend to

be assessed by the divergent groups of measures (one would, for

example, not expect tests of differentiation and integration to

correlate very highly). While it is true that differentiation is a

49
necessary, but not sufficient, precondition for the capacity to

integrate, the integrative process achieving (temporary or even

exploratory) single outcomes of the structural cognitive effort

would register as low complexity on any test of (purely) differentiation, yet would produce high complexity scores on (purely) measures

* of integration. Streufert, and Streufert (1978) have observed that

"persons selected on the various complexity measures (which often

appear uncorrelated) tend to behave strikingly similar to others of

the same complexity level across a number of tasks. Common behavior

* for more complex subjects and common behavior for more simple subjects

tends to be the rule, diverse behaviors tend to be the exception.

One might then propose that different tests of complexity, even

though appearing on different factors in a number of factor analyses

0 may in effect measure sub-components of a common multidimensional or

multicomponent phenomenon" (p. 50). The present discussion will

first present a short review of those measures, and will then discuss

development and research efforts on measures of cognitive information

* processing that have been published in the last few years.

1. Measurement through Early 1977

• The oldest, and probably most frequently utilized (modified),

measure of complexity is Kelly's (1955) Role Concept Repertoire (Rep)

test. In Bieri's (1965) modification, the test was specifically

designed to measure differentiation, limited to the perceptual social

Cdomain. More than half of the research published on complexity over

the years has used Bieri's version of the Rep as the only, or

primary, selection instrument.

In general, the Rep Test is administered as follows: The subject

is provided with a grid which contains a number of spaces (e.g., 10)

for the person to be judged (columns), each labeled with a role title

considered to be personally relevant to the individual (e.g., yourself,

50
father, boss, friend), and including both liked and disliked persons.

'1 A corresponding number of rows is provided for constructs. In some

research using the Rep Test, these constructs are generated by the

subject (as in Kelly's original test), while in other studies, the

constructs (bipolar dimensions of similarity-contrast) are provided

• by the experimenter. It has been demonstrated by some researchers

(Jaspars, 1964; Tripodi and Bieri, 1963) that the indices of complexity derived from own and provided constructs are comparable.

However, others (e.g., Kuusinen and Nystedt, 1972) have reported

* results indicating that considerable differences between the effects

of the two kinds of constructs may be obtained. Results appear to

depend upon such factors as the type of provided constructs which are

compared with individual constructs. Metcalfe (1974), on the other

• hand, found no differences between own and provided constructs for

complexity (i.e., hierarchical structure) and for differentiation,

but concluded that the use of own constructs is preferable, because

his obtained correlations between results based on own and provided

* constructs were statistically significant, but not high. It appears,

then; it may safely be assumed, in most cases, that the results

obtained with the use of own vs. provided constructs are fairly comparable, although not necessarily identical.

0

Ir the subject-generated construct procedure, the subject

identifies each of the roles in the columns with a real person.

Then he is asked by the experimenter to consider three of these

persons (which three are specifically designated) at a time. The

subject generates the constructs by indicating, for each triad he

considers, a way in which two of the persons are similar and the

third is different. Different triads are considered in this fashion

until all construct rows are filled. Each time the subject produces

a construct, he places a check in the cells of the matrix under the

two similar persons and leaves blank the cell of the differing person.

After all rows have been labeled with constructs, the subject

51 S

.-~... ~ ....... . . ..... ......... ... < - ,.% . . ... .... .... . - .. .. .... ., , . .- ... . ..-, . . ,-... 
reconsiders all dimensions and places additional check marks in the

cells of those persons (in addition to the two original ones) who are

also similar on that construct. This procedure yields a matrix of

check patterns which respresents how S perceives and differentiates

a group of persons relative to his personal constructs (Bieri, 1955).

40

Scoring is accomplished by comparing each construct row with each

other construct row, for a particular person. All possible comparisons for all rows and all persons (e.g., 450 in a 10 x 10 matrix)

are made, with a score of one (for example) given for every exact

agreement of ratings on any one person (Bieri et al., 1966). The

scores for all comparisons are then summed, yielding a total score.

(In a 10 x 10 matrix, the highest possible score would be 450,

indicating that the subject rated all persons the same way on all

constructs.) The higher the total score for a subject, the lower his

level of complexity, since the high score is indicative of the fact

that he uses all his constructs in the same way, that they all have

the same meaning to him. In other words, he is more unidimensional.

A low-scoring subject is considered higher in complexity, using

dimensions differently. Scoring procedures on th, Rep Test differ

among experimenters, but the interpretation of complexity as

inversely related to total score is consistent.

Multidimensional Scaling (MDS) (Schroder, 1971) is perhaps the

most mathematically sophisticated attempt to measure differentiating

ability. In the MDS format, the subject typically is asked to make

judgments of similarity or preference between pairs of complex objects.

The resulting matrix is analyzed to determine the number of dimensions

the subject probably used to generate his ratings. MDS has high predictive validity for differentiating ability, but not for planning

performance, as it does not account for integration. MDS is relatively

easy to administer and can be computer scored.

52

- . . . . JAxk.r r a a a
| , 

_ _

It has been hypothesized that the number of dimensions yielded

in a MDS analysis relates to the individuals differentiating ability,

and that the weightings of the dimensions yielded in the MDS analysis,

or their obliqueness, relate to the individual's integrating ability.

Although MDS studies have yielded some interesting results, it is

* unclear whether MDS will solve the measurement problem for integrative

complexity theory. The parallel between dimensionality and differentiation is promising, but the relationship between the weightings of

the dimensions and integration is unLear. Another realistic difficulty

* is the expense involved in the computer processing of each subject's

similarity ratings.

Early data have demonstrated considerable predictive validity

* and sufficient reliability for the Rep test and some of its derivatives. One scoring modification (Smith and Leach, 1972) has been

shown to produce positive correlations with Harvey's (see below)

This I Believe (TIB) test, a measure derived from Harvey, Hunt, and

* Schroder's (1961) Systems Theory predictions.

The TIB Test (Harvey, 1964) has been used to test integrative

complexity through the subject's relative degree of absolution0 evaluativeness, positivity-negativity, etc. on certain beliefs.

In the TIB Test, the subject is required to complete, in two or three

sentences, phrases beginning with "This I believe about ...." The

dashes include referents to friendship, guilt, majority opinion,

myself, compromise, and people. Harvey (1964) reports high predictive

and construct validity and interrater reliability scores above .90.

The major criticism levied against the TIB Test is that it confounds

structure and content (Schroder, 1971). This criticism points out

S

a violation of the major theoretical consideration underlying the

cognitive-oriented simulations.

5

• 53
The "categorizing" measure of Zajonc (1960) has been widely used

* in earlier work on cognitive complexity. Respondents are first asked

to read a letter which was supposedly written by an applicant for a

job. They are asked to try to get a general idea of what kind of

person the applicant is. They are then given a set of 52 blank cards.

• One characteristic which the respondents feel would describe the

applicant is written on each card. As many cards as possible are to

be used. Respondents are then told to sort the cards into as many

broad groupings as they feel are appropriate. After completion of

* this effort, each group of cards is studied to see whether it can

be broken down into subgroups. These groupings and subgroupings are

used to determine the level of inclusion of "attributes," the basis

for the computation of the complexity score. As with the work of

0 Kelly, Bierie, and associates with the Rep test, this approach deals

with differentiative complexity in a perceptual social domain.

Scott has developed a number of structural measures; however

only his measurement of complexity is of interest here. Typi ally,

Scott's measures are also most relevant to the perceptual real

however, some are located in a different domain. For one his major

measurement techniques, for example, Scott utilizes ons as

stimulus concepts instead of persons.

Scott bases nis measures on information theory (Attneave, 1959).

His formula for differentiation is a measure of the quantity of

information obtained from a modified sorting task (Scott, 1959, 1962a,

1962b, 1962c, 1963b, 1966, 1969). Scott asks subjects to generate

a list of "important" nations (or other persons), or provides subjects with such a list. Subjects are then asked to sort the nations

into (potentially overlapping) groups on the basis of some attribute

they oossess in the mind of the subject. Absence or presence of the

attribute is determined via inclusion of the nation in a specific

group. If subjects obtain only one grouping, then two distinctions

54
XI

are made. Nations are viewed as possessing, or not possessing, a

6 particular characteristic, i.e., they are placed on a single

dichotomous dimension (in Scott's terminology, attribute). If the

subject sorts nations into two groups (with overlapping membership),

then four distinctions may be made. For k independent groups, the

maximum number of distinctions would be 2-, permitting description

of the information contained in the sorting outcomes via logarithms

to the base of 2 (Scott, 1962a). Scott makes a number of additional

assumptions. He suggests that two groupings (even if named

differently) which have identical members (and nonmembers) are

empirically seen as representing the same attribute (dimension). He

further proposes that groups with no overlapping members are likely

to represent antithetical attributes (dimensions) or form different

categories on the same dimension. In either case, no differentiation

is implied.

The experimenter would be most certain that differentiation did

actually occur when a subject orders groups in different ways along

different dimensions (intransitivity). This would occur most clearly

where there is 50 percent overlap among dichotomous attributes

(dimensions) into which the stimuli (nations) are sorted. The measure

of absolute complexity can be expressed by the formula (Scott, 1962a):

•0p H = pi log2 : = log 10 2n -znlogn - n 1 g2ni

where

• n = the number of objects (nations) obtained from the subject;

ni = the number of objects that appear in a particular combination of groups; and

=p ni/n : the proportion of objects falling in the ith group

combination.

55
Further, Scott obtains a measure for the relative complexity of a

* Qsubject's sort by correcting for the number of nations generated

(Scott, 1962a):

R - logH2n

109

Perhaps influenced by Scott's interest in measurement techniques

for cognitive structures, several of his associates have also published measures which are of some interest. Wyer (1964) developed a

measure of differentiation based on a person's attributed rating

matrix (not unlike the Rep Test). Differentiation is defined as the

number of distinct concepts in the cognitive domain, i.e., the

number of distinctively rated stimuli. For example, if on a number

of attributes (dimensions) persons are always rated in the same

order, then only one dimension is present. To the degree to which

any point on the dimensions is used more than once to place a person,

and to the degree to which that placement is unique, a score for

differentiation is given. If, on the other hand, two persons are

olaced together at that point who are also placed together on other

points of other attributes, then differentiation is scored only once.

Wyer also presents two measures of integration. Integration is

defined as the degree to which concepts and attributes contained in

the cognitive domain are interrelated. Measure 1 calculates the

number of subject responses which would infer other responses; e.g.,

if placing a person on Scale-point 3 on Scale A implies that he will

then also place him at point 1 on B; 6, on C, etc., then the placement

on Scale A can be inferred from two other placements: Score = 2.

The effort necessary for calculating all these vales would be

enormous, so Wyer limits himself to calculating only inferences for

placement of persons on the three dimensions which the subject

claimed were most important.

56
Wyer's second measure of integration again uses the three most

* important scales. Subjects are aksed to indicate the probability

(0-1.0) that a person scoring high or low on each of these three

dimensions would also score high or low on the other dimensions

which the subject had generated (total of 10 dimensions, so there are

* 7 left for this purpose). For each pairing of one of the three "most

important" with one of the seven other dimensions, the differences in

the probabilities for the statements of high or low similarity were

calculated. For example, if the probability that a person scoring

• high on dimension 1 (most important) is also high on dimension 7 is

.9, and the probability that he is low is .1, then the difference is

.9 - .1 = .8. If they are equally probably, then the probability is

.5 - .5 = 0. The number of pairs which showed differences of greater

* than .5 was taken as a measure of interrelatedness of the structure

(integration).

Unfortunately, Wyer's integration measures fail to correlate

• meaningfully with integration measures derived from interactive

complexity theory (the latter have been widely validated). It is

likely that the calculations utilized by Wyer are not appropriate

for obtaining assessments of the flexible integrative capacity

considered by Schroder et al. (1967) and by Streufert and associates

(1970).

Crockett (1965) developed the Role Category Questionnaire,

again a measure of differentiation complexity in the perceptual social

domain. Crockett's measure of complexity (differentiation) is a

count of the number of concepts that are used to describe different

persons. The subject is asked to identify eight persons he knows.

Half of them must be older than he; half, peers; half must be liked;

half, disliked; half must be male; and half, female. The subject

spends a few minutes comparing his persons mentally, and then

57
describes each of the eight persons (with a three minute time limit

* oer person). The measure of complexity is represented by the

number of different interpersonal constructs which the subject uses

in the description. High complex subjects are above the median

split of the distribution obtained from all subjects; those below

* the median are low in complexity.

Harvey, Hunt, and Schroder (1961) utilized a number of measures

(often in multiple combination) to determine a person's "abstractness"

* based on their systems theory. The tests include Harvey's This I

Believe (TIB) test, Schroder and Streufert's (1962) Sentence Completion Test (also, and possibly more appropriately, known as Paragraph

Completion Test) (both requiring subjects to respond with several

* sentences to presented conflict dilemmas), along with some forced

choice techniques in which subjects select between alternate solutions

to conflict dilemmas. While the TIB and the Sentence (Paragraph)

Completion Test can be scored for structural characteristics only

* /see below), Harvey et al. did confound content and structure in

their scoring procedures as dictated by their theoretical assumptions.

As used by these authors, these measures cannot be considered pure

measures of cognitive complexity although they have been utilized

for that purpose by researchers involved in interactive complexity

theory (see below). In addition, scoring the measures as dictated by

systems theory has produced limited reliability coefficients. The

advantage of the efforts by Harvey et al. is the expansion of complexity domains into areas other than social perception. Subsequent

researchers have used this advance to considerable advantage.

As reported by Goldstein and Blackman (1978), the Interpersonal

Topical Inventory (ITI) is a forced-choice instrument developed as a

measure of integrative complexity. It is a modification of an

instrument developed in 1959 by Schroder and Hunt (cf. Schroder,

1971). On the ITI the subject is presented with six stems: "When I

58

" . ', ' I " '. - --* .. .". 
am criticized..., " "When I am in doubt..., " "When a friend acts

differently toward me..., " "This I believe about people...,"

"Leaders ... ," and "When other people find fault with me...." For

each stem, the subject is presented with six pairs of responses, and

is asked to complete the sentence by indicating his choice of one of

the responses from every pair.

Tuckman (1966) presented data from over 100 Naval recruits

indicating significant differences in the SCT-measured level of

abstractness for subjects that were classified on the basis of the ITI.

He also presented data indicating a significant relationship (C = .54)

between the SCT and ITI; and Suedfeld, Tomkins, and Tucker (1969)

reported a significant correlation of .19 between the SCT and the ITI

for a sample of 178 undergraduates. It should be noted that significant

relationships between the ITI and measures such as the SCT (PCT) are

significant only when the latter is scored according to the conceptual

systems approach of Harvey et al., 1961. Correlations disappear when

comparisons are made between ITI and the SCT (PCT) or the IFT scored

according to interactive complexity theory approaches.

Researchers concerned with interactive complexity theory have

primarily employed subjective measures to assess the complexity of

their subjects. The most frequently used subjective test for complexity

developed by researchers in this group is the Sentence Completion Test

(Schroder and Streufert, 1962). Subjects write paragraph length

(three to four sentences in a 2.5 to 4 minute period, depending on

the population) responses to each of a number of incomplete sentences,

such as "When I am criticized...." The sentence stems are selected

to Provide conflict settings to which subjects can respond unidimensionally or multidimensionally. Scoring of the tests is

relatively easy, and one-day training will typically result in interrater reliabilities of above +.85. More extensively trained personnel

tend to obtain reliabilities in the low 90s. Test-retest reliability 5

0 59 .,
7- 1 T. 7j

of the measure (if the tests are administerd properly) is near .85.

0 The scores obtained on the two highest responses are usually taken as

an index of the subject's complexity.

In an attempt to gain responses which are more relevant to the

S0 domain differences discussed by Driver and Streufert (1969), and

Streufert and Driver (1967), Streufert and associates have modified

the stems so that responses can be obtained for the following domains:

(a) social complexity, (b) nonsocial complexity, (c) perceptual com-

* plexity, (d) executive complexity. Inter-correlations among these

domains are typically .4 to .6. It should be noted that the test is

scorable for both differentiation and integration separately.

Scoring for differentiation alone produces low socres for integrators.

A second test that is used with some frequency is the Impression

Formation Test (Streufert and Driver, 1967; Streufert and Schroder,

1963). As Crocket and associates have established, complex persons

* tend to integrate conflicting blocks of univalent information; less

compTex subjects, however, tend to respond with either primacy or

recency, depending on the manipulation. This finding has been useful

in establishing criteria for estimating interpersonal perceptual

o complexity on the basis of subjects' responses (cf. Streufert and

Driver, 1967).

Attempts have been made to develop a number of objective measures

of differentiation and integration. While some progress has been made

(particularly recently), these tests are not yet quite ready for

general use. The difficulty encountered in developing such measures

is due to the individual differences in the content of domains. It

is necessary to measure cognitive complexity in terms of each

individual's own content and structure, permitting no overall test

format. While the subjective measures employed by this research

group (Schroder and associates; and Streufert and associates) have

60
yielded very high reliability and predictive validity across a

0 number of domains, the objective tests so far have not fared as well.

Consequently, they will not be considered here.

2. Recent Efforts Concerned with Cognitive Information Processing

Development of new measures of cognitive complexity has not been

widely attempted during the last five years. Three sets of authors

have reported new measures; however, all are either limited in

usefulness or as yet insufficiently developed to be a significant

contribution to the literature. For example, Metcalfe (1978) reports

that his work on the Smith and Leach Hierarchical Complexity Index

based on a 30-month test-retest correlation shows that measure to be

somewhat reliable, but likely not exceptionally valid. Hussy (1977)

reports an effort to develop seven separate measures of cognitive

complexity (in German), but admits that the proof of reliability and

validity for those measures is limited. Laucht and Krohne (1978)

report similar problems with their test.

A number of researchers have considered the interrelationship

among different measures of cognitive complexity. The concern with

potentially lacking relationships was probably created by the results

of several factor analyses reported in the mid-seventies suggesting

low level relationships among complexity measures (for an explanation of those levels, see Streufert, and Streufert, 1978). Generally,

the results obtained have been supportive of reasonable interrelationships among measures. For example, Okeefe, Delia, and Okeefe

(1977) report that more complex subjects (selected on the Rep test)

perform impression formation tasks by including information of more

negative valence than do less complex subjects. The impression

formation task employed is the basis of the Impression Formation Test

utilized by interactive complexity theorists (Streufert and Driver,

1965). Raphale, Moss, and Rosser (1979) related the Sentence

61

• "' . -. > " ,L>. . . .'.1-i . . .. 1".1 . . . .. 1. . . '. ' '1'

. -'' " i"""" ' " " ' ' " " " " " ' " ""'
7 1 , - % - '7

Completion Test (Paragraph Completion Test), as used by Hunt, to the

*" impression formation measure and found that more complex subjects

perform better on higher level aspects of impression formation than

do less complex subjects.

* An interest in reexamining the reliability and validity of

established (and previously validated) measures of complexity has

continued as well. The results of these efforts demonstrate that

the reliability and validity levels do hold up across time (and

* diverse sub-populations). For example, Schneier (1979) reports

highly significant test-retest reliability and convergent as well

as discriminant validity for the Rep Test across populations, sex,

college major and level in organizational hierarchies. Lesser levels

* of reliability have, however, been reported when different populations

(other than American, European, and related cultures) were tested.

For example, Ohbuchi and Horike (1978) tested 40 male Japanese

students. They reported reliability for measures of discrimination,

• but less consistency for a measure of dimensionality (differentiatioq). Indeed, differences among cultures and subcultures in complexity are clearly present and need to be examined further. Even

within U.S. populations, such differences can be found. For example,

* Hogan and Mookherjee (1980) demonstrated considerably more variance

in blacks than in whites, particularly black females.

Work concerned with specific measures of cognitive complexity

* has dealt with improving available tests (for example, Bell and

Keen, 1980); has proposed a method for obtaining additional information fror the Rep by scoring during the elicitation of the response;

and has considered the relationship of complexity across domains

* (Poole, 1978).

Previous work, often based on factor analysis procedures, had

indicated that cognitive complexity shows little relationship to 0

62

..........................................
other personality or attitudinal measures. Indeed, such relationships

0 should not exist: as long as a complexity measure is purely structural

it should assess a style of dealing with information regardless of the

content of that information. Recent efforts by a number of researchers

have generally confirmed that relationships between cognitive com-

* plexity and other measures of cognitive styles are negligble or nonexistent and that relationships to measures of personality content

and attitudinal content do not exist. For example, Kostlin-Gloger and

Rottmair (1979) obtained no relationship between complexity (Rep)

* and reflectivity/impulsivity. Several sets of researchers have

explored relationships of complexity with measures of conservativism

and liberalism, but found no correlations which differed meaningfully

from zero (e.g., Schneider, Kohler, and Wachter, 1979; Sidanius,

* 1978). Exploring the relationship of complexity to conservativism

has been particularly interesting since Messick in an early Factor

Analysis (in the 1950s) had shown that U.S. political conservatives

utilized only one dimension of judgment in political perception,

* while liberals appeared to utilize two dimensions. It may well be

that'conservativism has changed since that time and that conservatives

and liberals are now relatively equal in the number of dimensions

utilized.

Hasse, Lee, and Banks (1979) employed the constructs of

Polychronicity and Monochronicity to describe an individual's ability

to handle stress stemming from stimulus-intense information overload.

The construct regards the degree of order, regulation, and structure

which one applies or requires in a situation to be indicative of

a poly- or monochronic coping style. Characteristics of these

constructs are presented below.

"61

~63

L . . . . .-.
Monochronicity Polychronicity

Structure required Flexible; little need for structure

Unable to assimilate new Able to assimilate new information

information rapidly rapidly

Less tolerant of ambiguity Tolerant of ambiguity

* Low degree of distress from High degree of distress from

information overload information overload

Select specific stimulus Employ multiple dimensions leading

from complex situation to longer time and greater effort

to arrive at choice or solution

Hasse et al., in developing an Index of Polychronicity,

supported its construct validity via two factor analyses, yielding

five orthogonal and interpretable factors termed: Information

* Overload, Interpersonal Overload, Change Overload, Activity Structure,

and Temporat Structure. To test the validity of the construct, Index

scores were compared to the Otis-Lennon measure of intellectual

functioning and to the Bieri Grid. The Polychronic-Monochronic

designations were determined to relate to IQ and complexity, but

wer not seen as identical to either. However, the authors suggest

that further investigation could relate their concepts more directly

to cognitive complexity or cognitive style.

Several attempts have been made to correlate Witkin's

construct of field independence with integrative complexity: all

with limited success. The tool most often used in such studies

is the Embedded Figures Test (Witkin, Goodenough, and Oltman, 1979). q

It is believed that one reason for the low correlations between

scores on this test and those obtained on complexity measures is

the purely perceptual nature of field independence/dependence construct and measurement tools.

Greater reationships among measures can be expected when they

are designed to measure similar structural phenomena, whether or rot S

64

. . .. . . . .. . .
they were developed on the basis of the same theoretical constructs.

Smith and Evans (1980) explored the relationship between two measures

of that kind: the Rep, as a measure of cognitive differentiation; and

a test of Constellatoriness, i.e., a measure to construe elements in

a stereotypical and undifferentiated way. The measures are negatively

related to each other and cannot be considered as distinct variables.

Measures of Performance

For the purposes of this section, a distinction among measures

developed earlier and those developed in later years will not be made.

Part of the reason for this approach is the rather small number of

measurement techniques that are available and the limited set of

theoretical approaches that have generated them. Another reason

for the lack of distinction is the specific applicability of the

measures to the present project. Separating the measures into distinct categories would, in this case, likely hinder communication.

-Early work by Driver and by Streufert was based on the analysis

of simulation procedures. Later efforts by Suedfeld added post hoc

analysis measures to relate complexity to political performance in

* the "real world." Measures of performance have, in nearly all cases,

focused on scoring complex decision making. Only recently have

efforts by Streufert considered measurement in simpler performance

tasks. In all of these research efforts, however, the perceptual

- social domain has been abandoned for executive social and executive

non-social domains. In addition, the measurement efforts have a

distinct applied character.

Early work by Driver (1962) utilized the Inter Nation Simulation

of Guetzkow and associates to measure decision making characteristics

of more or less complex decision makers. Environmental variation

was not considered or was considered only in minimal terms. The

65

F- "+. - - -. . 6 I.. ...+. - -" .- . .: - '.", .-"-'-'. . . . ", ,.= v ' , , > ' ['
INS is a free simulation (c.f., Fromkin and Streufert, 1976) and

• -consequently is not amenable to precise and controlled researci, (see

Streufert and Swezey, 1980). Driver was forced to count the frequency of events occurring across a number of simulation runs and to

calculate mean discrepancies from linear or curvilinear relationships

among specified variables. Nonetheless, this method did produce a

number of data sets which showed differences among decision making

groups; and particularly, differences between teams of more complex

decision makers and teams of less complex decision makers.

Decision Making Measures

1. Single Strategy Models

Articles previously discussed under the single strategy

model section of the Decision Making portion of this review can be

viewed as describing rules applied in decision situation and as

suggesting hierarchies or orders of complexity with which the rules

might be organized. They tend to relate the complexity level of

the strategy with the characteristics of the situation or problem.

The characteristics of the problem tend to be treated as

aspects of uncertainty, conflict, and/or complexity. The measurements

at this level aim at attempting to determine whether certain

strategies or rules are preferred, or used more often, or whether

amounts of uncertainty, conflict, or complexity will predict the

selection of a rule. Uncertainty has been tested to determine rules

employed to reduce or cope with it. Gambling simulations are frequently used for this purpose, as they were by Larson (1980), and by

Payne and Braunstein (1978). These situations were designed to

measure the accuracy of prediction of specific models, and results

are interpreted only in terms of the model's relative usefulness.

Although they provided varying levels of uncertainty in their gambles,

66

. . , . . . - .. - . - . . . . . a . • %L ta ... J & a . . . . . . . . . . . . . . ., . ., j 
f ,

there is little to be generalized from them in terms of complexity of

* "the gamble, or how complexity in the gamble might have effected the

decisions made. Perrault and Russ (1979), for example, provided

subjects with a salesman evaluation situation, where subjects were

asked to decide which of five salesmen should be paid a bonus, based

* on multiple attributes differing among the salesmen. It was determined that the lexiocographic (see our earlier discussion of this

model) levels of rules were employed in complex situation. The

lexiocographic styles of decision rules were identified as being more

* complex, requiring more information, and requiring more time and

effort.

Payne (1976) improved this situation by adding an explicit

* information search requirement to his apartment selection decision.

Using both the information search and verbal protocol tracing methods,

Payne found that selected rules changed when the situation changed -

from a two-alternative level to a more complex multialternative task.

* However, he interpreted the change as one which provided for simple,

quick elimination of alternatives, and reported use of only limited

amounts of information. Payne did not report an identifiable

difference in complexity of the situation.

0

Christensen-Szalanski (1978) defined and described strategies

as higher in complexity or lower in complexity. He used a financial

problem where subjects were asked to predict outcomes and also to

* report which of the defined strategies best described their decision

making methods. In this work, complexity level of the chosen

strategy was contingent upon the complexity of the situation.

Unfortunately, although it was recognized that decision maker

characteristics bear heavily on selected techniques, the subjects in

this study were deliberately homogeneous, which eliminated any

information about the decision maker effects.

S

~67
2. Multi-stage Models

The single strategy decision making models have assumed that

a "best" rule applied in a situation, although the rule might consist

of several steps. The multi-stage approach assumes that strategies

consist of sets of rules, as opposed to sets of steps within a rule.

Measures at the multi-stage level attempt to demonstrate conditions

which produce a particular strategy, and conditions which produce

changes in the levels of strategy complexity. As Park (1978)

suggested, they attempt to describe the whole process rather than

the specific choice mechanisms.

Park identified two strategy levels: a conditional

elimination-simplifying-evaluation process, which was displayed

first, and was followed by a second stage, a "satisficing plus"

strategy (see earlier discussion). Park noted that at the first

level, only crude cognitive categories were applied, while at the

second level, the cognitive categories were refined on the same

product dimensions. Park provided insight into models which

might be applied to multidimensional decisions (Elimination by

Aspects types, followed by Satisficing Plus types), but did not

provide the connection needed to the cognitive structure or style

of the decision maker.

Olshavsky (1979) based his work on Park's model and

probed further to determine the validity of Park's contingency

assumptions, and to identify experimentally the effects of the

number of dimensions on complexity of the selected strategy.

Olshavsky's results partially confirmed Park's observations,

but found that more time was required to reach decisions in

the more complex conditions. This would tend to confirm the

assumption that a cognitively complex person actually processes

a greater volume of information, and produces fewer decisions

8-68

I J
per unit time, than does the person responding at lower levels

*of cognitive process. Olshavsky suggested that latency differences

may have occurred at the perception level, but that other explanations

(such as reading time for more attributes, and addition of extra

cut-off levels, which also require time to implement) could be

* equally valid explanations.

Huber (1980) related strategy production to cognitive

process. Huber employed the concept of Elementary Information

* Processes which was defined as constituents of the decision

maker's general problem-solving repertory, or the "vocabulary"

from which varieties of strategies are formed. This approach

has some similarity to the complexity concept, but is limited

to types of skills used. Interestingly, Huber found that skill

implementation depended directly upon task variables.

Streufert and Streufert (1981) have recently consolidated

their theoretical position into the establishment of nine categories

or "styles" of decision making. These categories follow.

6

,I

*, - " ' " " " -" '," ' !- ."" .. 69,- >.' " ,-, > -.- t' ." , , """ " " '"' "" "" '
Category 1: The low unidimensional decision maker. On the

* "average, this person uses a categorical (e.g., good vs. bad) judgment

in response to a stimulus. Degrees of judgment (e.g., A is better

than B, but not as good as C) are rarely, or never, available. The

dimension utilized is usually the same with regard to nearly all

1 stimulus situations, but could occasionally vary with the domain

employed.

Category 2: The normal unidimensional decision maker. This

* person utilizes a single dimension in response to any particular

stimulus, but can easily consider "shades of gray" (i.e., discrimination of points along one dimension). If different dimensions are

employed for different stimulus situations, the person is probably

* not aware that he or she is utilizing different dimensional judgments

(e.g., utility in a business stimulus setting; good vs. bad in a

religious setting, etc.)

* Category 3: The general differentiator. This person does

(with awareness employ two or more dimensions in response to a single

stimulus (or stimulus set), but either views these dimensions as

non-interrelated (e.g., a person is like this when A happens and like

o that when B happens), or such a differentiator would pick and choose

one of the dimensional outcomes for his or her actions. In other

words, integration does not take place except in extremely limited

situations.

Category 4: The closed-hierarchial-differentiatior. We

are here combining the effect of closedness with the process of

hierarchial information processing (the absence of processing

flexibility). While the processes involved are oblique, they are not

necessarily so widely separated in the decision making process to

justify independent categories. Hierarchical processing of information from input to output (perception to decision making) suggests

70

-~~~~~~~~~~~~~~~~~..-..-..--.. . r ..-.... ..-.. -.. --...- '-........-,.,..-.....-.....,,">. " ....--. , ."
that a set of relationships has been learned, or is otherwise given,

" that determines the outcome in advance. For example, the process may

say "if event A occurs, it may be responded to by either X or Y. Which

of the two is appropriate depends on the simultaneous occurrence or

nonoccurrence of B."

Closedness indicates that the pre-learned process is not,

in-and-of-itself, subject to modification. Relearning of a new process

would have to follow the same pattern of learning that was established

when the initial acquisition took place, or would at least, require

major (probably negative reinforcement) impact experiences.

The closed hierarchial differentiator, then, employs two or

more dimensions in response to a single stimulus, dimensions that are

predtermined and that have predetermined characteristics or rules

governing which dimensions are selected.

Category 5: The excessive differentiator. Differentiation

into-finer and finer sub-dimensions can take place nearly ad infinitum.

Some decision makers tend to generate an inordinate number of alternative possibilities of responding, consequently responding very late

or not responding at all. Integration does not take place at all for

such persons.

Category 6: The low level integrator. Developing beyond

the general differentiator, the low level integrator is able to close

(for decision making) and reopen (for reconsideration or for additional

decision processes). Such a person will differentiate incoming

information, i.e., view a stimulus on more than one dimension, as

the differentiator did, but will see no need to make a decision

choice based on only one of these dimensions. Rather, some superordinate concept (dimension, etc.) may be used to combine outcomes

from the two separate dimensional judgments into a single decision

output (or several related outputs).

71

l .L .-1 . -,, , - - , ...., , - . .-.. - - - . , -, ,. ..-'... ,.-, -. ,. .. . -: .. , , > . ..,... .-
Category 7: The high level integrator. As in Category 6,

i •flexibility to be open, to close, and to re-open is again given. The

difference here is the number and interactive characteristics of the

superordinate concepts that are used to relate the different "readings"

from the various dimensions on which a stimulus is perceived. (Note

that one of those superordinate categories may well be a time perceived consequence in the sense considered by Jaques, 1978).

Category 8: The closed hierarchial integrator. Again, we

* are combining closedness with hierarchial functioning (for the reasons

listed earlier). Here, the decision maker has learned (or has

otherwise determined) specific complex conditional statements in

response to specific relationship between stimuli and decision

* outputs. He is using an (often weighted) complex branching technique

to arrive at a fixed decision. He is not likely to re-open to

reconsider his decisions or to alter his style in the face of input

that does not quite fit preestablished patterns. Most likely such

an input would be distorted to fit. Changes in the dimensional

location of certain stimuli are likely to be rejected, particularly

if they require a modification of several relationships in the

hierarchial structure of conceptual relationships.

Category 9: The non-closing integrator. This person is

simultaneously quite capable, yet decisively ineffective. The nonclosing integrator is usually a flexible integrator with high level

integrative capacity (c.f., Category 7), but without the ability to

close temporarily for decision making. This is a person who

generates an inordinate number of complex interpretations and

decision potentials, taking a large number of concerns into account.

Because he or she comes to so many different conclusions, none of

which seems quite good enough (because there are still so many other

things to consider and integrate), decisions will rarely be made. If

they are made, they tend to span over long time periods (on the

average).

72

k

P

- - - -- I -' -
I

Ongoing and Future Research

Suedfeld, based on the work of Schroder and Suedfeld, 1971

developed a method of scoring protocols for complexity of perception

and complexity of communication. The scoring system is based on the

* procedures used in the Sentence (Paragraph) Completion Test of

Schroder and Streufert (1962). Statements are scored for both

differentiation and integration. All of these approaches (Driver,

Streufert, Suedfeld) have been shown to have considerable predictive

* (or in the case of the work of Suedfeld, post hoc) validity.

Development of strategy and long range planning scores in complex

experimental simulations was based directly on evidence of differen-

* tiation and integration among decisions and decision categories leading

to strategic outcomes. In simple tasks, evidence of the (cognitive

or performance related) differentiative and/or integrative processes

is not directly observable, and scoring for strategic action per se

is viewed as implicative of complex information processing (taking

a nuter of cognitive dimensions into account when engaging in an

action decision).

Recent efforts by Streufert and Streufert (1982)

have led to the development of a simple hand-eye coordination task

which allows for strategic behavior. The task is based on a video

game permitting the introduction of various levels of environmental

complexity via difficulty levels manipulated on two separate variables.

Subjects are forced repeatedly to make decisions about their future

actions, permitting more or less strategic actions and reflecting

more or less planning for the future. Scoring for complexity of

performance in such a task is based on the utilization of strategy.

in addition (and parallel to experimental simulation techniques),

other measures (concerned, for example, with risk taking and with

success in the task) can also be collected.

0 73

• . - -
While the performance measures employed in simple tasks and

* in various complex tasks are reliable and have been shown to have

predictive validity, they have not been correlated with each other.

One such effort is currently underway. Complexity of performance in

an experimental simulation (Streufert and associates) will be related

• to performance in the simple task described above. Performance on

both tasks will be predicted from cognitive complexity scores on the

sentence completion test and an objective measure which is currently

under development. The research is not yet far enough advanced to

* estimate what the obtained levels of relationships might be.

SUMMARY

CThe most striking characteristic of theory, measurement, and

research on cognitive and environmental complexity is the wide

variety of approaches that have been and still are used to come to

terms with structural dimensionality. A surprising (and comforting)

* aspect of these efforts is the considerable overlap in predictions

and fn the actual data obtained. One can only conclude that the

various approaches to cognitive complexity must tap somewhat

diverse parts of a single or a widely everlapping phenomenon.

Certainly, in the case of the concepts and measures of differentiation

and integration this is clearly the case. Buc, apparently, the

commonality goes much further.

UEqually striking is the success in predictions for performance

across a number of tasks and in a number of diverse settings (as long

as multidimensior-''ty is usEfL'I or required). A warning should,

however, again be sounded: there certainly are many situations where

the use of multidimensionality for either perception or performance

may be inappropriate. The successful person, group, or organization

should not only be able to differentiate and integrate, they should

also know when such efforts are likely to be useful and appropriate

74

*.. . '- -
and when they are not. The degree to which such knowledge, such an

ability or such a style can be trained is still in question. We know

that some training in a specific domain is possible. We do not know

how long such training will continue to be effective, and we do not

know whether or how it will spread from one specific domain to another.

* Some of the findings reported earlier in this discussion would suggest

that training can be achieved at least in some domains under some

conditions. Yet, since in only a few pieces of research, training

has been explored, that conclusion must remain tentative. The finding

that cognitive complexity, at least under conditions of arousal,

relates differentially to physiological responsivity could suggest

some greater differences between persons classified as cognitively

complex and those ciassifed as less so. Only future research can

resolve those concerns.

7

* 75

- . . . .

S-. -. . . . . . . .
6]

III. COGNITIVE COMPLEXITY MEASURES SELECTED FOR USE IN THE

MANAGEMENT ASSESSMENT AND TRAINING SIMULATION SYSTEM

Streufert and associates (e.g., Streufert, Clardy, Driver,

Karlins, Schroder, and Suedfeld, 1965) developed a series of controlled

experimental simulations, designed to measure the effects of specific

variables on performance. Selection of participants into homogeneous groups of more complex vs. less complex (e.g., Streufert

and Schroder, 1965; Streufert and Driver, 1965) or into mixed

groups (e.g., Stager, 1967) using the sentence (paragraph) completion

test, permitted more precise measurement of performance across groups

exposed to identical progressing environements. Development of

experimental and quasi-experimental simulation techniques (c.f.,

Streufert and Swezey, 1980) justified the parallel development of a

number of measures of performance which appear to be responsive to

(a) changes in the complexity of the environment, and (b) differences

in the cognitive complexity of decision makers. In the present circumstance, it also appears important to obtain measures of decision

making outcomes which may be affected by both presence and absence

of cognitive complexity. The measure selected for utilization in

the present situation, thus, are designed to cover all areas of

decision making stylistics (both structural and content oriented)

without overlap. This form of measurement provides the researcher

with a wide range of insight into a person's, group's, or organization's style of decision making. The selected measures are

*

1. Decision categories. These are the number of

categories that are viewed as independent by the decision maker. In

the military, this may, for instance, be an infantry attack, calling

* in bombers, Naval shelling, etc. Comparisons based on the number of

76
decision categories used are meaningful only if (a) the resources are

constant across decision makers, and if (b) training or knowledge

(familiarity with the setting) is equivalent. Decision categories

can be meaningfully measured in some simple and most complex tasks.

* 2. Spread across decision categories. Here the concern

is with the degree to which a decision maker favors specific decision

categories and rarely uses other categories. Again, the measure can

apply to both simple and complex tasks.

3. Number of decisions. The number of (independent)

decisions made per unit time. In some simple tasks, the number of

decisions may be replaced by the number of actions.

4. Number of integrations. The number of relationships

between decisions in different decision categories where one decision

is used as the basis for another. Number of forward integrations

reflects relationships where a decision at an earlier point in time

is mdde to allow (in strategic sequence) for the possibility of the

later related decision. Number of backward integrations reflects

relationships where a later decision is based on a previous decision,

even though the previous decision had been made for an unrelated

reason. This measure is more useful in complex multidimensional

tasks. Equivalent use of strategy measurement can be developed for

some simple tasks.

5. QIS (Quality of Integrated Strategies). This measure

is sensitive to the length (over time) of complex strategic planning

in complex tasks, and to integration, and to the complexity (interactive multiplicity) of the strategies carried out over time. A

time frame measure can be developed for simple tasks as well,

although it tends to show little equivalence to the QIS measure.

77
6. Number of respondent decisions. The number of decisions

*which are made in direct response to information received. A subcategory, number of retaliatory decisions, reflects respondent

decisions that reflect a 1:1 orientation to the information received.

In this case, there is no use of the respondent (here, retaliatory)

decision in any overall strategy. This measure is equally useful

in both simple and complex tasks.

7. Characteristic response and response speed to information. The degree to which information received results in more

respondent, or more differentiated/integrated decision making, and

the average time taken from receipt of information to the response.

The measure is useful in both simple and complex tasks.

8. Quality (if immediate response is required). Situations

and information inherent in situations differ in the degree to which

immediate responding is needed or unnecessary if success is to be

achieved. Here the concern is with a situation in which only

immediate responding is likely to lead to success (response

adequacy). The measure is relevant in both simple and complex tasks.

9. Quality (if novel strategy is required). Situations

that are unpredictable and in rapid flux require reconsideration of

previous established patterns and re-adaptation to the changed

environment. Here, concern is with the degree to which a decision maker

can adapt to rapid and unexpected modifications of the situation and

can respond appropriately to obtain an adequate success level. The

measure is relevant to complex tasks and may be relevant to some

simple tasks.

10. Quality (if learned pre-established strategy is

required). Situations containing many components and contingencies

that are relatively stable and allow a well-practiced, yet complex,

78

I 1

78 -78

-- . .. .. o

", . ---. .-.-.. '-" " --. "-- , . "...-".. . .-.. ..-.. . .. ... .-.... . .". -,. .-.. . . ... -.. . . . - - "-- .L .-
response pattern to a series of expected or familiar stimuli require

* "the responses rated highly here. The measure is relevant to many

complex tasks, and may be relevant to some simple tasks.

The following formulas reflect the decision processes and

* their measures as discussed above.

1. Decision categories:

* P

ISc

1

where

c = the number of categories employed,

p = any period of time of interest (e.g., a playing

period in the simulation during which some

variable was manipulated at a specific level).

2. Spread across decision categories:

P

2 (d ) + (d -d)

01 Ca dCb)+Cd Ce

where

d = the number of decision,

d Ca = the number of decisions from the category or

categories representing the upper ten percent

of decision frequency,

dcb = the number of decisions from the category or

categories representing the lower ten percent

of decision frequency,

dcd : the number of decisions from the category or

categories representing the remaining upper

40 percent of decision frequency, and

dce the number of decisions from the category or categories representing the remaining lower

40 percent of decision frequency.

* 79

iT >:~i- i. i i - ;: : i i -= i ° ::: . .: ° :>i~*1L
3. Number of integrations:

p. P +i

Z f or (if b

1 1

where

if = the number of connections between decisions of

one category with decisions of another category,

reflecting pre-planning of the later decisions

as the previous decisions is made as a (strategic)

necessary antecedent to the later decision, and

ib = the number of connections between a later decision

of one category and an earlier decision of another

category, where the outcome of the previous decision is used for the purpose of achieving the

goals of the later decision, where the relation-

* ship between these decisions was, however, not

planned when the earlier decision was made.

Which of the two integration measures is utilized (or

whether both are utilized) should depend on the interest of the

* researcher or trainer/assesser; i.e., is strategic planning of interest

or is-general strategic behavior of interest.

4. Numbe- of decisions:

P

rd

where

d the number of decisions.

8

* 80 4
5. QIS (Quality of Integrated Strategies):

P

-W (I + n + n

-ip f)

where

W = the length of time dimension of any forward

integration between the decision points connected

by that integration,

n = the number of other forward integrations connecting

P to the decision representing the beginning point

of the integration in question, and

n = the number of other forward integrations connecting to the decision representing the endpoint of the

integration in question.

The number of integrations, np and nff here includes all

forward integrations linked to a relevant decision point in chain

sequences via several decision points (i.e., the linked decision points

are part of a continuing strategic decision sequence).

6. Number of respondent decisions:

where

r any decision made within a given time period

(depending on the speed, i.e., time compression,

of the simulation) after the receipt of relevant

information and made in direct response to that

information.

81
n , 

 . i. ._ : ; I W_ %17 V %r. ._ K 7 %7. N7.i _ ; i ,. o . , L L ..

7. Response speed:

P

s tr

1

r

p

where

tr = the elapsed time between information received and

a subsequent respondent decision to that information, if such a response is made, and

r = the number of respondent decisions made during the

time period from 1 to P.

8. Quality (if immediate response is required):

Measured by external criteria, e.g., ratings by

experts or superiors.

9. Quality (if novel strategy is required):

Measured by external criteria, e.g., ratings by

experts or superiors.

10. Quality (if learned pre-established strategy is required):

Measured by external criteria, e.g., ratings by

experts or superiors.

w i Figure 2 relates this measurement approach to the nine decision

making styles posited by Streufert, and Streufert (1981). Also, shown

within cells are expected outcomes for various styles.

mj

'A

82

, ' > ' : 1 :v. : 9 . '. ' v x -A f-- ...,-"-. ' ..?,?,,i T2v ,-v -- :- ,,', -
It. IL -. 0 Ak_

2 4 5 9 s SSYLI USED IA DEIISION SPREAD ACROSS NUMBER NUMBER QIS NUMER OF RESPONSE TO OIJALITY IF OIJAL17Y IF OUA. IT LEARNED

DEIIO CATEGORIES DEC ISION OF OF RESPODEND WININO IMMEDIATE NOVEL SIRATEGI (PRE-ESIABLISHED)

MATING CATEGORIES DECISIONS INTEGRATORS ECISIONS INFORiATION RESPONSE IS IS REOUIRED STRATEGY IS

toLI UNI- F. MASSED ER MATCHING HOME VERY LOw VGI RESPONDENT. HDER. BUT AY LOW LOW

GIMENSIONAL. FEK0 INCOINS APID ESPOND INCORREC

CATEGORIES INFORMATIO IF RESPONSE ISN'T

IN REPERTOIR

UNIDI NMSIONAL FEW MASSEI IN PATCHIN VERY FEW VERY Low HIGH RESPONDENT. MODERATELY HIGH. LO MODERATE

CER 'TN INCOMING SNORT RAPID MA RESP. INCORR. GROUP INGS INFORMAT ION RANGE OR I MAPPROPRIATREL Y

If RESPONSE 15 HITT

. ..... ____________IN | REPERTOIRE

GENEAR TRA 1bAR ALV. RAEVRON [ AVERAGE PEA SIAIOR-RAIIOL. LOA PIIOERATE MODERATELY MAORERATELT VIOH MACERATE MAVOIRATI."

IOPFFERS- TIAOO SORE SELF VS EANRAT INTEGRA71 . PEA RESPONDENT SEDA TO AlG I ME NR DECISIONS ARE joKM EVE SPREAO -- INTEGRATED __-__---..1 - _ 

CLOSED DEPENDS ON DEPENDS ON AVERAGE VERY FEW. SA VERY LOW MADERATELY WIDER RAPID. HIGH LU N.SRATELY HIGH

H IERARCHICAL HIERARCHY AIERARCHY PRE -OETERRINE VISA POTENTIAL

DIFFEREN- RELATIONS=IPS DISTORTION T IATOG

ENCEM DIFFEREN- ALL R DINERS AN NO PREDICTION FEW VERY FEW VERY EOw MODERATELT SIVW MODERATE LOW MODERATIELOW '. IE ' - - SMORE RANGE LOW (100 SLON)

LO LEEL MODERATE AS AVERAGE. SOME HIGR SNDRI-RAGE LOW TO MODERATE HIDER, SPEED. MODRATELY MORERATELY MOVERATTI HIGH

INTEGRATOR PREDICTION EFFECT SF DOE RESPONENT MODERATE MORE LIKELY LO HIGH

______ ___ INFORMATION DECIS. INTEGRATED INTEGRATED

HIGH LEVEL MODERATI MARE EEN, AVERAGE. LESS HI-SHORT AND HIGH MODERATE MODERATE SPEED. ILO HIGH MODEAILI HIGH

INTEGRATOR DEPENOING ON AFFECTED BY LONG RANGE. MANY INTEGRATED OR

(FLEXIBLE) SIRAT. SEDUEAIC INFORMATION RESPONDENT DECI- RESDONO..REPEN

GROUPINGS, MAY D]0NS INTEGRATED ON PERCEIVED

CHANGE WH TIE IIDATION

HIERARCHICAL DEPENDS ON DEPENDS OR AVERASE MOERAIEDLV HIGH, HIGH T E- MATTES. RAPID. VUIRRATO MOERAELV RATELY HGH

(CLOSED) MIERARCHY HIERARCHY DEPENDS ON HIFR DETERMINED VIVA POTENTIAL LER

ITEGRATO PRE-DETEATIIED RELATION- DISTORTION

RELATIONSHIPS SHIPS - IMAN.LSIYI RO-CO To FEW. EXCIPT NN [OON LoN. EXCEPT FEW. BUT LONG- MODERATE UEIN LOW DELAYED LOW LON LON

INTEGRATTI WHE IN IN GROUPINGS TUNI RANGE AND DA TO 0 IAN.

PING CLUSTERS jVALUE OF A . _RESPONDENT

ASSUMING EUIVALENT KNOWALEDGE.

TRAINING. OTHER SKILLS, ETC.

Figure 2. Decision Styles by Measurement Technique Matrix

0]

*83

J!,
X]

IV. ADDITIONAL APPROACHES AND MEASUREMENT TECHNIQUES

SELECTED FOR POTENTIAL USE IN THE MANAGEMENT

ASSESSMENT AND TRAINING SIMULATION SYSTEM

It is currently the intent, in developing the Management

Assessment and Training Simulation System, to provide for the

collection of information from users on three additional construct

measures, if feasible. These measures, which are briefly discussed

in order below are Level Abstraction, Simultaneous Information

Processing, and Subjective Psychological Load.

Level of Abstraction

Characteristics of individuals, as presented by the social

sciences, are typically depicted as a quantitative expression of

continuity in the form of a normal curve. The implication of such

a distribution is that one is describing a single parameter of a

psychological or social phenomena. Multiple parameters, or discontinuity, as expressed by multi-modal distributions, is a less common

approach, and one which may include the characteristic of cognitive

abstraction and associated behavior as the capacity to do work. A

* large number of theoretical and research papers have been published

on this topic by Jacques and his coworkers (c.f., Jacques, Gibson,

and Isaac, 1978; Rowbottom, 1977; Jacques and Stamp, 1981).

Based on a variety of quantitative and qualitative research in

the areas of organizations and human capacity, a number of levels of

abstraction or capabilities (originally five, then extended to seven

by later work) are hypothesized by Jacques and associates to be a

fundamental cognitive characteristic of people. These levels of

84 T
abstraction are said to range from concrete ideation and performance

at the lowest level to higher levels of human functioning addressing

classes of classes or infinite sets within ioeations. Essentially,

human cognitive development is perceived to occur in stages which are

discontinuous, thus dividing the population into multi-modal distribution groups.

Evidence, on the establishment of five levels of abstraction,

with the addition of two further levels, have been generated by the

study of people functioning (i.e., working) in organizations. More

recent research has suggested the existence of six and seven levels

by an analysis of work within bureaucratic hierarchies (Jacques

and Stamp, 1981). These higher levels require individuals to intermesh a wide range of disciplines across a variety of environments

extending from a local level to an international one. Researchers

in the area of levels of abstraction note the possible existence of

more than five levels, but have not been able to classify them nor

obtain enough evidence of their existence. The discussion that

follows, therefore, will be primarily limited to the original five

levels, however, levels six and seven will be presented where appropriate.

Level One: The primary emphasis is on concreteness.

Activities are prescribed and performed according to strict rul's

and procedures. Human performance is dominated by a process of operations on objects, or generally referred to as a skill. The situation

or environment where these skills are performed, based primarily on

intuition of the individual, is dominated by a high level of uncertainty.

Level Two: Behavior and ideation at this level is hypothesized

to result from an increasing degree of ambiguity as evidenced by incomplete prescriptions, rules, and procedures. The ambiguity of the

environment is perceived by an individual as having a flexible rule

system where inductive thought processes can be used to complete

objectives in a relatively concrete situation.

85
Level Three: Increasingly introduced at this level is use

of systematic thinking and performing. The environment is characterized

by an increased certainty as perceived by the individual, allowing

behavior to occur in serial form. The ideation of an individual allows

for extrapolation from specific instances to those more general.

Level Four: Cognitive activity becomes more abstract

leading to hypothesis testing and innovation. Generalizations begin

to be made on the basis of a few concrete examples, with a concomitant

* increase in uncertainty.

Level Five: Theory construction and general rule making

become firmly established at this level, across a wide spectrum of

0 domains. The environment is related to an intuitive, inductive way,

which increases the uncertainty of what is known of the universe.

These levels of abstraction have been formulated through the

observation of people performing or behaving at a variety of levels

within organizational hierarchies. From these observations,

researchers in this field have hypothesized that work behaviors are

probably reflective of a distribution of the capacity to do such work.

S There further appears to be a universality of these observations in

the form of a discontinuous distribution of these capacities.

Within each level of functioning, people are thought to function

according to a dominant mode of operating. The dominant mode of

operating is further thought to interact with existing, but less

dominant modes. Modes of operating, those that are dominant and

those less so, are also discontinuously distributed within each level

of abstraction or work-capacity stata. Further, operational modes

increase in number at successively higher levels of abstraction, with

a maximum of five modes operating at the fifth level. These modes

are briefly presented below.

* 86

S. . . .
Mode one: competent, persistent, attention to detail

* "(i.e., proceduralists or pragmatic specialists)

Mode two: pragmatic, organizational ability - self

and others (i.e., practioners or pragmatic generalists)

Mode three: information gatherers and organizers,

* planning ability, effective use of personnel (i.e.,

system setters or theoretical generalists)

Mode four: intellectually able, creative, subtle,

excelling in research and staff consultancy roles

(i.e., structuralists or theoretical specialists)

Mode five: originality in approach to problem

solving, routine work not consistent with this

level (i.e., originators)

C Within each level, therefore, evidence seems to exist to indicate

only mode one is operating at level one; modes one and two operating at

level two; and so on, through the five modes operating at level five.

While people will predominatply function in one specific mode within

a level, operating modes will fluctuate in response to a particular

problem, or change as a function of a temporary individual characteristic, such as a mood. For example, an individual who predominantly

works as a system setter (see mode three) at level four, may, for a

particular task, function in a very concrete mode (see mode one)

relative to the other three modes at this level. Operating modes

and levels are hypothesized to form a full system of work capacity

into five levels within 15 components (modes) within the levels.

C

Related to both the level an individual is working on within an

organization and that person's capacity to do work, is the temporal

frame within which a person can plan and execute specific, goaldirected activities. This temporal frame is thought of as a cognitive

ability as well as a requirement of one's position %ithin an

organizational hierarchy. The extent or quartity of a person's work

capacity is time related. The farther forward in time an individual

is able to plan and formulate goals, progress, and carry them out to

87
completion, the greater than person's capacity. The research in

* levels of abstraction have suggested that a temporal frame exists that

has cut-off points at three months, one year, two years, five years,

and ten years. These time bands correspond to the five levels of

abstraction in human mental activity. As mentioned earlier, the

* levels may be extended to a sixth and seventh strata, with a temporal

cut-off of 20 years. The cut-offs correspond to each level, such that:

Time Span Level

20 years 7

10 years 6

5 years 5

• 2 years 4

1 year 3

3 months 2

1

It has been suggested that the level of abstraction and its

level of extension of context, or temporal cut-off, at which a person

functions is correlated with the maximum temporal frame with which the

* individual can cope. While all modes are used within a given level by

a person, only one mode will be dominant and tend to be dominant for

a particular person. A qualitative distinction can be made of the

modes in relation to time span. The more concrete modes are based

* more on past experience and the more abstract modes are based more

upon future developments. Modes, therefore, provide an interplay

between organized experience and future contexts. An individual can I

move from dominance of one mode to that of another as the need to rely

* directly upon concrete experience or future goals in solving a particular problem.

8

* 88 "

- .--.- ..- --. - - - -".-..- .. -. :- • " - . "" ' " . :% ' ", _~-"" - .- ".",:- .' :. ' . --
The levels of abstraction theory posits that the very ability

Swhich allows an individual to handle the higher levels of abstraction

is the same ability which enables him to plan and work longer into the

future, to take on and to successfully plan and progress longer projects.

In other words, this ability allows a person to line and act within a

more extended temporal frame.

Jacobs (i98i) has attempted to operationalize these levels for

the Army hierarchy. Jacobs' interpretation of the levels are briefly

presented below.

I -- Concreteness. At this level, the individual is

concerned with specific shop floor tasks. The worker would be given

a specific item to build and would be given an example (i.e., build

me one of these). For someone doing data collection, specific interview questions would be provided (i.e., ask this question).

II -- Coping with tasks with ambiguity. At this level,

the individual will be given a job but without the exact example, or

will be told to do, but with the notion that adaptation may be

required (e.g., in manufacturing: I want 1000 of these per week.

Supervisor may decide this week to do 850 because of problems, and

then to catch up next week with 1150 or 1200 or so.) For an interviewer, broader latitude would be given to collect information by

either developing one's own interview schedule or one's own probing

questions. MILITARY: Mission type orders. This occurs first at

company level.

III -- Trend extrapolation. This is the first level of

systems functioning. The individual at this level is aware of the

world of trends, and adapts to the future through extrapolating trends.

Example: Departmental manager who monitors shifting load vs. resources

and people. He anticiaptes ne9ds for tools, etc., may manage 250-300

89
people in industry. MILITARY: Probably at battalion level. This is

the first level at which a commander will tailor a task force for a

combat mission. The underlying dimension is the capability to tailor

combat power. The commander has learned from experience in coping

with mission requirements, operating the system.

IV -- Jump logic. Here, trends no longer work. The

individual must be able to handle extrapolations of trends, but must

also be able to construct a world in terms of what is missing. This

is the level at which the first real creativity occurs. Industrial

example: Design some jigs and fixtures for me to improve procedures.

The incumbent says, "No. That is not the way to do it. You can't

get there from here." He then starts all over with a new process

and breakes the old trend because the old trend would not extrapolate

to cover the new conditions. The new process is a quantum jump.

Example: Get more secretarial efficiency by harder driving, etc.,

in the face of manpower survey people who define upper limits of

secretaries to basics, and the increasing flow of secretaries to

headquarters levels in lower ratios. Break the system trends by going

to word processors with many terminals, so scientists who can type

can put the information in the word processor, and the secretary can

then do the manipulation to format and print without having to type

the whole thing from scratch. Editing functions could be shared.

MILITARY: Colonel (and brigade) is the first level at which there is

real experimentation with tactics -- discontinuous alternative means

for doing missions.

V -- Open-ended top. The context within which the individual

works is no longer fixed. It is open. The individual now has a concern

with strategic considerations. Industrial example: The incumbent is

asking questions such as, "What business should we be in?" or "What

product should we have?" (as opposed to how much of a specific product).

At this level, the individual will be managing subsidiary companies of

D 9 -

:-" ... '" ,° .' - " -' ' . , :A-- ----. . .h " .'. , '- - , - -, -' ,-,., , a , - - -" I" . . . . . ;L- .-W.
different types, e.g., aluminum, trucking, etc., as trading entities.

At this level, for the first time the individual makes, and is expected

to make, strategic input to seniors so as to assure that operational

purposes at his own level can be accomplished. MILITARY: The Major

General (Division Commander) will be the first level at which the

commander suggests the strategic implications of operations, and

participates in the formulation of operations, at least partly, in

terms of how operations and more general strategy interact.

VI -- Transition to constructs being social systems.

This is the level of corporate executives who practice "hands off

management." Types of concerns at this level are vertical integration,

for example. Individual sub-entities are managed without regard to

the technical content of their operations. The strategic planning

at this level must be such that it gives level V companies room to

operate. Types of decisions: For an iron company as a subordinate

entity: Should that company go into pellitizing, or should the

conglomerate go into steel manufacturing and do the entire operation

in one place? MILITARY: This is the corps commander, and it is at

this level, for the first time, that one finds the integration of

joint service operations, and the conceptualization of the "air-land

battle."

VII -- Transition to extrapolating social, technical, and

0 political systems as they relate to the future of the organization.

MILITARY: The interfacing of CSA with the Congress.

Both complexity theory and the work on levels of abstraction

1 address and make predictions about people's behavior based on the

study of individual differences. Essentially, people develop and

perform in their environments in consistent ways. The individual's

perception of the world, as mediated by cognitive functions, allows

•0 him to function in a variety of circumscribed ways. Complexity theory

* 91

V NI
examines the individual variables as interactive elements within a

I ° complex environment. Variables within the environment, therefore,

are seen to influence a person's performance or behavior by eithe;

being harmonious or discordant with a person's cognitive functioning.

Multidimensional styles are able to function in an integrative fashion I. when task and environmental variables are conducive to such functioning.

Increases or decreases in environmental complexity, such as information

load, can reduce integrative behavior to that closely resembling

respondent performance. With information load stabilized, specific

tasks require a certain style of behavior, independent of the innate

or learned cognitive functioning of the person. More cognitively

complex individuals attempting a simple, unidimensional task may not

perform as well as (i.e., as efficiently) as a less cognitively

0 complex person. The work on levels of abstraction, however, seems to

minimize the complexity of the environment. Rather, in this discipline,

an individual cannot perceive the world from any other level of

ability other than the one he is functioning on. Some problems may

require analysis of the situation into so many details as to go beyond

the potentiaiities of persons of lower levels of capacity. Under such

circumstances the person feels overwhelmed by the problem, becomes

disorganized, and inevitably fails.

Time-span has been hypothesized to be a measure of work in the

levels-of-abstraction literature. The more an individual can focus

further into the future in terms of planning and progressing toward a

goal, the higher capacity for work or the higher level of abstraction

he is working on. Complexity theory presents a somewhat analogous

concept of multidimensionality and integrative processing. Multidimensionality depends on the numbers of dimensions in the cognitive

domain and the degree if discrimination of these dimensions. Integrative processing reflects how dimensions are related within a cognitive

domain. The greater number of dimensions an individual perceives I& within his environment, the more multidimensional he is. The greater

92

F-- -~~~~~~~. ...- ''.." ...'-,................ .....................- '.'. ".--.--..".................. .. "' -, " -"'-" "'_"r'# _ " "' ' ' '' -" 1 -" "" " , "''"'"" , "" " "' . " -, '"i, ., i . .- .... i d 1.-',, , , ,, ,' ' 1 I L I1,,
C

the number of perceived relations between these dimensions, the more

integrative an individual is. Combining multidimensional processes

with integrative processes leads to greater cognitive complexity.

Greater cognitive complexity could possibly be in part equated with

the higher levels of abstraction, and conversely, low cognitive

complexity may correspond somewhat to low levels of abstraction.

In simple one-to-one responding, information input is directly translated into a behavioral output (i.e., respondent decision making).

Respondent behavior occurs more frequently with persons of more

unidimensional structure and generally under less than optimal

environmental conditions. At the first level of abstraction, where

time-spans are below three months, tasks are assigned in concrete

terms and carried out in direct physical contact with the output. C

If there is no immediate perceptual contact with the output, no work

is done at this level.

Differentiated responding, according to Complexity Theory,

requires a stimulus to be perceived on a number of different dimensions,

and requires a response on several of these dimensions simultaneously

(or subsequently) within a limited period of time. These responses,

however, are not usually related to each other via some plan or

strategy. Finding corresponding levels of abstraction which are

analogous to more cognitively complex strategies becomes difficult

because the complexity of the environment is minimized in the former,

C and is integral to the latter. However, the third level of abstraction involves imaginal scanning and aspects of behavior at this level

may possibly be experienced by the differentiated individual. At the

third level, time-span limits are seen at one or two years, where

it becomes impossible physically to oversee or to imagine all at once

the whole of a person's area of responsibility. The scope of activity

has become too wide for this, although it still is possible to do so

by mentally scanning the whole, one bit at a time. The instructions

IL at this level tend to be in conceptual terms of load data, programs,

£ 93

. . .. .. . . • . . . .. .. . . , -. . . . • o - ". 
F

indices, etc. The interplay between project and output, therefore,

has become qualitatively more complex. Feedback is in terms of comparing what is happening in various parts of the output region with

equivalent parts in various parts of the subjective project.

0 Integrated responding implies, for complexity theory, that a

number of cognitions based on various dimensions occur resulting in

one or more responses which are related to each other in a planned or

strategic fashion. This kind of response is most often seen in

0 persons who are multidimensional integrators, and occurs with

greatest frequency under moderate (i.e., optimal) information load

conditions.

Possibly juxtaposed to the integrative decision makers is the

fifth level of abstraction. At this level, a five to ten-year timespan is hypothesized. There is no possibility of having other than

limited contact with the concrete reality of the total field of

responsibility. The person operating at this level would be preoccupied in longer range futures. The cognitive activity at the fifth

level is one of intuitive theories built up from experience. Specific

experiences are generalized and absorbed for use as part of a general

formulation of decision making.

A more superficial analogy can be made between these theories

in terms of temporal perspective. For example, in complexity theory,

maximum response levels can be reached by any organism (although this

will vary by organism) in a specified time within which responses must

be made. Because respondent behavior is made on the basis of a simple

input to response relation, more respondent behavior can be expected

in a shorter time. Integrative behavior, requiring greater cognitive

effort, using larger numbers of information items, would be expected

to take longer. Correspondingly, low levels of abstraction require

4 shorter time frames because of the nature of the work; a simple

94
one-to-one correspondence. Higher levels of abstraction require

greater capacities to process a more diverse information, and consequently, necessitate longer time frames.

Measurement

Goodman (1967) has operationalized measures for use in

assessing Jacques' constructs. Two of these measures, anticipated

for use in the Management Assessment and Training Simulation System,

are

a. Time Span of Multiple Task Roles.

1. Considering your job as a whole, how far does

your job permit you to plan ahead? (Write

in time, e.g., 1 day, 2 weeks, 4 months,

3 years.)

..... average time

..... longest time

2. For some decisions, we learn about the results

of the decision right away, for others, we

must wait for the results. Considering your

job as a whole, what is the

..... average time

..... longest time

you must wait before you learn the results of

a decision that you made.

b. Levels of Abstraction.

Jobs differ in terms of how much time they require

the individual to spend on planning for certain

activities and actually doing certain activities.

What percent of your time do you spend on

. planning activities

.. ..... doing activities

1009

95 - : : -" . : . '- .- i i ii ' . .i. . .
Simultaneous Information Processing

Sternberg (1981) has identified four approaches to understanding

mental abilities: cognitive correlates, which relates test performance

to tasks believed to tap basic information-processing abilities;

cognitive components, which constructs cognitive process models of

tasks from standard psychometric tests; cognitive training, which

trains individuals in a particular skill, and examines subsequent

performance; and cognitive contents, which examines the differences in

knowledge structures between experts and novices. The major implication of these approaches is that they can relate test performances to

specific mental processes.

In the cognitive correlates approach, according to Sternberg,

subjects are required to perform tasks that are believed to measure

basic human information processing ability. Here, information processing is generally defined as the sequence of mental operations and

their products involved in performing a cognitive task. Such tasks

include, among others, the Posner and Mitchell (1967) letter-matching

task, in which subjects are asked to state as quickly as possible

whether the letters in a pair, such as "A a," constitute a physical

match (which they do not), or in another condition, a name match

(which they do); and the S. Sternberg (1969) memory scanning task.

As reviewed by Chiles (1978) and by O'Donnell (1975), in the

so-called "Sternberg task" the basic approach is that a user is required

to learn a set of positive stimuli (so-called because their appearance

calls for a positive response). Members of the positive set, frequently

letters of the alphabet, are presented one at a time: generally, on

half of the trials the stimulus is a member of a negative set. On the

appearance of a letter, the operator is instructed to respond as

quickly as possible by depressing a "yes" key if the letter is a member

of the positive set and a "no" key if it is a member of the negative

96 SP
set. Under appropriate conditions, a linear relation exists between

the size of the positive set (typically 1 to 8) and reaction time. The

psychological theory behind the use of this taks is that average reaction

time with a given number of stimuli in the positive set can be broken

down into three parts: (1) stimulus encoding, (2) memory scan, and

(3) response selectior and execution. For a given set of conditions,

the first and third parts are assumed to be constant, whereas the second

part is interpreted to be a direct reflection of memory scan speed

and/or memory load. Thus, changes in the y-intercept value (i.e., the

response time for the primary task alone) are assumed to reflect changes

in the perceptual and/or response aspects of the task. Changes in the

slope of the curve are assumed to reflect changes in the rate at which

memory is scanned and/or the amount of memory load involved. In other

words, the y-intercept value serves the same function as a measure

from a secondary -oading task as described previously; the higher the

intercept (i.e., the longer the average response time), the greater the

assumed loading produced by the primary task. In addition, a change

in the slope of the response-time curve might be interpretable as a

reflection of the amount of memory load added by the primary task.

The value of this task as a loading task in the usual sense has been

borne out by the results of preliminary studies conducted thus far.

However, relationships with complexity theory are yet to be demonstrated.

if feasible, this technique, or a modification thereof, will be

considered for use in the Management Assessment and Training Simulation

System.

Subjective Psychological Load

Measurement of psychological load is an important aspect in the

study of managerial decision making. The Cooper-Harper (1969) technique

(see Ellis, 1978) is probably the premier technique for subjective

97
assessment of this construct, whereas the Sternberg technique (see

aoove) purports to measure it more objectively.

According to Ellis, the Cooper-Harper rating scale was develoned

to assess handling qualities of aircraft and is such an important

0 scheme for subjective assessment of psychological load that it is

widely accepted as the standard scale for such purposes.

Cooper and Harper's scale is reproduced in Figure 3.

Spyker and colleagues (1971) have modified this technique to

obtain subjective ratings on their workload experiments. The subjects

were presented with a series of six questions and were asked to

indicate an answer to each one by choosing one of a limited number

(5 to 9) of phrases describing opinions: each answer was allocated

a numerical value that corresponded to the position it would have on

a scale of the Cooper-Harper type. Two of Spyker's sets of questions

and answers are shown in Figure 4.

According to Ellis (1978), if a rating scale for workload is to

0 be successful, it is likely that it will have been constructed along

lines similar to those of the Cooper-Harper scale. Of course, the

Cooper-Harper scale has been used in connection with workload measurement, and so the question arises whether it is an adequate scale for

workload rating. The answer was provided by Geratewohl (1976).

"Althoigh workload is seen as inextricably tied to the assessment of

such characteristics as compensatory system monitoring and precision

of control, judgements of perceptual or mental effort involved in this

process are generally not obtained. Hence, subjective ... ratings of

handling qualities, as accurate as they may be in regard to control

desirability or difficulty, do not contribute to workload determinations, since they are only loosely connected to task demands."

98
0o

DEMANDS ON TH' PIL'- !N - ADEQUACY FOR SELECTED TASK DEANSONTa IL

AEQUIR ED T AIRRAFT INARACTERISTICS SELECTED TASK OR REQUIREL PILOOR REQUIRED OPERATION' I OPERATION- RATING

Excellent til compensation SHionly oesirable not a factor 'o oesired performance

Good >iot conipensation

Neglioible aeficiencies not a factor for 2

Iesired oe'formance

pair - Some mildly Minimal oilot comunpleasant deficiencies sensation reQuirec

for oesireo oerform- ante

YES .

Minor out annoying Desired performance

oeficiencies requires mooerate 4 p ilot c Omnensation

satisfactory : De'iciencies I Mooerately objectionable Adequate performance

wtnout NC warrant oeficiencies requires consideraDle

imDrovement' imorovement - pilot comnensation

Very oojectionable but Aoequate performance

tolerable deficiencies requires extensive 6

oilot compensation

Major deficiencies AOeouate performance not

attainacle with maximumn tolerable pilot comnensa- .s tion; controllability not

adequate in ouestion

oerformance NC

obtainable .-

ItDr a )eficiencies Major deficiencies Consioerable pilot com-

.Jeavler eouire sensation is reouireo

-lot xorkload?l imorovemen t for control

Major deficiencies Intense oilot comoensai tion is reouiret to

-- retain control

'S t -jr ma imorovement nda to ry major oeficiencies Control will be lost ouri rg s ome portior of10i

:ontrcaole' L reouired operation

D'lot

iecisions 'Definition of required operation involves oesignation of flight onase and/or

subonases with accompanying conditions.

Figure 3. The Cooper-Harper (1969) Scale

(from Ellis, 1978)

to 99

%
II. In my opinion control over the simulated aircraft was:

] Extremely easy to control with excellent precision (0.5)

E Very easy to control with good precision (2.5)

* [f] Easy to control with fair precision (4.5)

- Controllable with somewhat inadequate precision (5.5)

- Controllable, but only very unprecisely (7.5)

• [] Difficult to control (8.0)

[ Very difficult to control (8.5)

Nearly uncontrollable (9.0)

O E! Uncontrollable (10.0)

III. In my opinion the demands placed on me as the pilot were:

• Completely undemanding, very relaxed and comfortable (2.5)

E Largely undemanding, relaxed (3.5)

Mildly demanding of pilot attention, skill, or effort (5.5)

, Demanding of pilot attention skill or effort (6.5)

] Very demanding of pilot attention, skill, or effort (7.5)

E Completely demanding of pilot attention, skill, or effort (8.5)

E Nearly uncontrollable (9.0)

. Uncontrollable (10.0)

Figure 4. Spyker et al.'s (1971) Adaptation of the

Cooper-Harper Technique

100

A-
The following points, however, have been noted by Ellis (1978)

about this approach.

a. The scale is more than one of pure comparison.

Whereas a user can be expected to place a number of stimulus

(configurations) in order of desirability, his Cooper-Harper rating

for any of them is intended to be repeated whatever the qualities of

the other configurations under assessment. Thus, if one example is

given a rating of 4 in an experiment where all others lie between 6

and 8, it should also be rated 4 if its rivals were to lie between

1 and 3.

b. Despite this, the scale is essentially a comparative

one and so does not present the user with an unreasonably difficult

task.

c. The user is drawn towards the eventual rating through

a step-by-step process. The value judgments that he makes are

presented as a series of decisions. The dichotomous choices at each

stage of the decision "tree" are fairly simple, and once the

stimulus configuration under assessment has been placed within the

value "boundaries" the user has to choose one of only three values.

d. The scale is aimed towards the practical application

of the configuration under assessment. The user's judgments are all

made in the context of the defined task.

e. The Cooper-Harper rating does not provide a complete

* assessment. It gives a merely shorthand guide to the load configuration.

f. The scale is very practicalbe. Once learned, it is

easy to use and so it is suitable not only for laboratory experiments

* but also for user-oriented conditions. A user can give a rating and

• 101
make a few cryptic comments while he is performing a task, a circumstance

in which he cannot be expected to go through an assessment ritual that

is long and complicated.

g. The Cooper-Harper scale uses workload in a very specific,

but limited manner. Workload is always related to the task; overall

workload is judged against a standard of tolerability ("Is adequate

performance attainable with a tolerable workload?) Other workload

decisions are based on the concept of compensation (compensation is

defined as "The measure of additional effort and attention required to

maintain a given level of performance in the face of deficient stimulus

characteristics").

h. The scale is ordinal. Naturally enough, researchers

would prefer the scale to be a linear or interval one, and so have

criticized it. Nevertheless, the construction of a practical scale of

demonstrated linearity has not yet been achieved, and the many

* advantages of the Cooper-Harper outweigh its disadvantages. Some

researchers take means and standard deviations of Cooper-Harper ratings,

and although it might be convenient to express results in this way,

caution should always be exercised when manipulating the numbers

derived from this scale. For example, an average rating from a number

of users might obscure the fact that one of them gave a much lower (or

higher) rating than the others. The reasons for this isolated result

may be simple, but should not be ignored.

If feasible, a modification of this approach will be designed for

use in the Management Assessment and Training Simulation System.

102
REEENE

0

06
REFERENCES

Anderson, N. H. and Barrios, A. A. Primacy effects in personality

impression formation. Journal of Abnormal and Social Psychology,

1961, 63, 346-350.

Arnett, M. D. Least preferred co-worker score as a measure of

cognitive complexity. Perceptual and Motor Skills, 1978, 47,

567-574.

Asch, S. E. Forming impressions of personality. Journal of Abnormal

and Social Psychology, 1946, 41, 258-290.

Attneave, F. Applications of information theory to psychology.

New York: Holt, 1959.

Atwood, M. A. and Swezey, R. W. Microprocessor considerations for a

management assessment and training simulation system. (SAI

Technical Memorandum 178-81-1) McLean, VA: Science Applications,

Inc., 1981.

Baudhuin, E. S., Swezey, R. W., Foster, G. D., and Streufert, S.

An empirically derived taxonomy of organizational systems. (SAI

Report No. SAI-80-091-178) McLean, VA: Science Applications, Inc.,

1980.

Beagles-Roos, J. and Greenfield, P. M. Development of structure and

strategy in two-dimensional pictures. Developmental Psychology,

1979, 15, 483-494.

Bell, R. C. and Keen, T. R. A statistical aid for the grid administrator. International Journal of Man-Machine Studies, 1980, 13,

143-150.

Bhutani, K. A study of the effect of some cognitive and personality

factors on attitude change. Indian Educational Review, 1977, 12,

50-60.

Bieri, J. Cognitive complexity-simplicity and predictive behavior.

Journal of Abnormal and Social Psychology, 1955, 51, 263-268.

Bieri, J. Complexity-simplicity as a personality variable in cognitive

and preferential behavior. In D. W. Fiske and S. R. Maddi (Eds.),

Functions of varied experience. Homewood, IL: Dorsey, 1961.

Bieri, J. Cognitive complexity: Assessment issue in the study of

cognitive structure. Unpublished manuscripts, 1965.

R-1
Bieri, J. Cognitive complexity and personality development. In 0. J.

Harvey (Ed.), Experience, szructure, and adaptability. New York:

Springer, 1966.

Bieri, J. Cognitive complexity and judgment of inconsistent information.

In R. P. Abelson, E. Aronson, W. J. McGuire, T. M. Newcomb, M. J.

Rosenberg, and P. H. Tannenbaum (Eds.), Theories of cognitive

consistency. Chicago: Rand McNally, 1968.

Bieri, J., Atkins, A. L., Briar, S., Leaman, R. L., Miller, H., and

Tripodi, T. Clinical and social judgment: The discrimination of

behavioral information. New York: Wiley, 1966.

Bruch, M. A., Heisler, B. D., and Conroy, C. G. Effects of conceptual

complexity on assertive behavior. Journal of Counseling Psychology,

1981, 28, 377-385.

Chandler, M., Siegel, M., and Boyes, M. The development of moral

behavior: Continuities and discontinuities. International Journal

of Behavioral Development, 1980, 3, 323-332.

Chiles, W. D. Objective methods. In Assessing Pilot Workload, AGARD,

233. NATO: Neuilly Surseine, France, February 1978, pp. 54-77.

Christensen-Szalanski, J. J. Problem solving strategies: A selection

* mechanism, some implications, and some data. Organizational

Behavior and Human Performance, October, 1978, 22(2), 307-323.

Cioata, E. Relationship between cognitive complexity and integrative

constants of personality: Emotional stability and affective meaning

of stimulation. Revista de Psihologie, 1977, 23, 331-348.

Cohen, H. S. and Feldman, J. M. On the domain specificity of cognitive

complexity: An alternative approach. Proceedings of the Annual

Convention of the American Psychological Association, 1975.

Cooper, E. and Harper, R. Jr. The use of pilot ratings in the evaluation of aircraft handling qualities. AGARD, 567. Paris, April 1969.

Crockett, W. H. Cognitive complexity and impression formation. In.

B. A. Maher (Ed.), Progress in experimental personality research

(Vol. 2). New York: Academic Press, 1965.

Cronen, V. E. and LaFleur, G. Inoculation against persuasive attacks:

A test of alternative explanations. Journal of Social Psychology,

1977, 102, 255-265.

Davis, C. S., Cook, D. A., Jennings, R. L., and Heck, E. J. Differential client attractiveness in a counseling analogue. Journal of

Counseling Psychology, 1977, 24, 472-476.

R-2
Davis, E. G., Foster, G. D., Kirchner-Dean, E., and Swezey, R. W.

* An annotated bibliography of literature integrating organizational and systems theory. (SAI Report No. SAI-80-082-178)

McLean, VA: Science Applications, Inc., 1980.

Delia, J. G. and Clark, R. A. Cognitive complexity, social perception,

and the development of listener-adapted communication in six-,

* eight-, ten-, and twelve-year-old boys. Communication Monographs,

1977, 44, 326-345.

Domangue, B. B. Decoding effects of cognitive complexity, tolerance

of ambiguity, and verbal-nonverbal inconsistency. Journal of

Personality, 1978, 46, 519-535.

Driver, M. J. Conceptual structure and group processes in an internation simulation. Part One: The perception of simulated nations.

Princeton, NJ: Princeton University and Educational Testing

Service, ONR Tech. Rep. No. 9, NR 171-055 and AF Tech. Rep. AF

49(638)-742, and Res. Rep. NIMH Grant M 4186, 1962.

Driver, M. J. and Streufert, S. Group composition, input load and

group information processing (Institute Paper, 142). Institute

for Research in the Behavioral, Economic and Management Sciences,

Purdue University, 1966.

* Driver, M. J. and Struefert, S. Integrative complexity: An approach

to individuals and groups as information processing systems.

Aaministrative Science Quarterly, 1969, 14, 272-285.

Durand, R. M. Cognitive complexity, attitudinal affect, and dispersion in affect ratings for products. Journal of Social Psychology, 1979,

S 107, 209-212.

Durand, R. M. The effect of cognitive complexity on affect ratings

in retail stores. Journal of Social Psychology, 1980, 110, 141-142.

Durand, R. M. and Lambert, Z. V. Cognitive differentiation and

alienation of consumers. Perceptual and Motor Skills, 1979, 49,

99-108.

Einhorn, H. J. and Hogarth, R. M. Behavioral decision theory: Processes of judgment and choice. Annual Review of Psychology, 1981,

• 32, 53-88.

Elliott, R. Interrelationships among measures of field dependence

ability and personality traits. Journal of Abnormal and Social

Psychology, 1961, 63, 27-36.

S R-3
Ellis, G. A. Subjective assessment. In Assessing Pilot Workload.

AGARD, 233. NATO: Neuilly Surseine, France, February 1978, pp. 11-22.

Epting, F. R. and Wilkins, G. Comparison of cognitive structural

measures for predicting person perception. Perceptual and Motor

Skills, 1974, 38, 727-730.

* Fiedler, F. E. Leader attitudes and group effectiveness. Urbana:

University of Illinois Press, 1958.

Fromkin, H. L. and Streufert, S. Laboratory experimentation. In

M. Dunnette (Ed.), Handbook of Organizational and Industrial

Psychology. Chicago: Rand McNally, 1976.

Gerathewohl, S. J. Definition and measurement of perceptual and

mental workload in aircrew and operators of Air Force weapon

systems: A status report. In Higher Mental Functioning in

Operational Environments. AGARD CP-181. Paris, April, 1976.

* Goldstein, K. M. and Blackman, S. Cognitive style: Five approaches

and relevant research. New York: Wiley, 1978.

Goodman, P. S. An empirical examination of Elliott Jaques' concept

of time span. Human Relations, May 1967, 20(2), 155-170.

• Hale, C. L. Cognitive complexity-simplicity as a determinant of

communication effectiveness. Communication Monographs, 1980, 47,

304-311.

Harren, V. A., Kass, R. A., Tinsley, H. E., and Moreland, J. R.

Influence of gender, sex-role attitudes, and cognitive complexity

on gender-dominant career choices. Journal of Counseling

Psychology, 1979, 26, 227-234.

Harvey, 0. J. Some cognitive determinants of influencibility.

Sociometry, 1964, 27, 208-221.

Harvey, 0. J. (Ed.) Experience structure and adaptability. New York:

Springer, 1966.

Harvey, 0. J., Hunt, D. E., and Schroder, H. M. Conceptual systems

and personality organization. New York: Wiley, 1961.

Hasse, R. F., Lee, D. Y., and Banks, D. L. Cognitive correlates of

polychronicity. Perceptual and Motor Skills, August, 1979, 49(l),

271-282.

Heider, F. Attitudes and cognitive organization. Journal of

* Psychology, 1946, 21, 107-112.

* R-4

.. . , . . , . .. .. . .. ' . . . ., .. o , - + .
Hendrick, H. W. Differences in group problem solving behavior and

effectiveness as a function of abstractness. Journal of Applied

Psychology, 1979, 64, 518-525.

Henke, A. H., Alden, D. G., and Levit, R. A. An analysis of human

cognitive styles, Honeywell Document F0141, 2 volumes, 1972.

Hogan, H. W. and Mookherjee, H. N. Some developmental and racial

dimensions of cognitive complexity. Social Behavior and Personality,

1980, 8, 85-89.

Holloway, E. L. and Wolleat, P. L. Relationship of counselor conceptual

level to clinical hypothesis formation. Journal of Counseling

Psychology, 1980, 27, 539-545.

Horike, K. Studies on person perception (1): The relationship of

cognitive complexity to social interaction. Tohoku Psychologica,

Folia, 1978, 37, 102-115.

Huber, 0. The influence of some task variables on cognitive operations in an information-processing decision model. Acta Psychologica,

August, 1980, 45(1-3), 187-196.

Hunt, D. E. Personality patterns in adolescent boys. Progress

Report No. 7. Grant M 3517. Syracuse University, 1962.

Hunt, D. E. A conceptual systems change model and its application to

education. In 0. J. Harvey (Ed.), Experience, structure, and

adaptability. New York: Springer, 1966.

Hussy, W. A study in operationalization and quantification of

* cognitive complexity. Archiv fur Psychologie, 1977, 129, 288-301.

Hussy, W. Analysis of the need for information during a modified

prisoner's dilemma game. Zeitschrift fur Experimentelle und

Angewandt Psychologie, 1979, 26, 561-572.

* Hussy, W. and Scheller, R. Predictive value of cognitive variables

in information processing. Archiv fur Psychologie, 1977, 129,

226-241.

Jacques, E., Gibson, R. 0., and Isaac, D. J. Levels of abstraction

in logic and human action. London: Heinemann, 1978.

Jacques, E. and Stamp, G. Level and type of capability in relation

to executive organisation. First Year Technical Report. U.S.

Army Procurement Agency, Europe, 1981.

Jacobs, T. 0. Operationalization of Jacques' levels of comolexity.

Memorandum. U.S. Army Research Institute, PERI-ML, April, 1981.

R-5
Jaspars, 17th International J. M. Individual Congress cognitive of Psychology, structures. Amsterdam, Proceedings 1964. of the

Jones, A. P. and Butler, M. C. Influence of cognitive complexity on

the dimensions underlying perceptions of the work environment.

Motivation and Emotion, 1980, 4, 1-19.

Jones, D. P., Schipper, L. M., and Holzworth, R. J. Effects of

amount of information on decision strategies. Journal of General

Psychology. April, 1978, 98(2), 281-294.

Kelly, G. A. The psychology of personal constructs. Vol. 1: A

theory of personality. New York: W. W. Norton, 1955.

Kostlin-Gloger, G. and Rottmair, I. Are reflective children more

highly structured cognitively? Zeitschrift fur Entwicklungsosychologie

und Padagogische Psychologie, 1979, 11 12-15.

Kuusinen, J. and Nystedt, L. Individual versus provided constructs,

40 cognitive complexity, and extremity of ratings in person perception.

University of Stockholm: Reports from the Psychological Laboratories,

1972, No. 365.

Larson, J. R. Exploring the external validity of a subjectively

weighted utility model of decision making. Organizational Behavior

and Human Performance, December, 1980, 26(3), 293-304.

Lauclht, M. and Krohne, H. W. Studies on the validity of the Role

Construct Repertory Test as a measure of cognitive complexity.

Archiv fur Ps\chologie, 1978, 130, 212-235.

Levi, A. and Tetlock, P. E. A cognitive analysis of Japan's 1941

decision for war. Journal of Conflict Resolution, 1980, 24, 195-211.

Lewin, K. Principles of topological psychology. New York: McGrawHill, 1936.

Linville, P. W. and Jones, E. E. Polarized appraisals of out-group

members. Journal of Personality and Social Psychology, 1980, 38,

689-703.

Luchins, A. S. Primacy-recency in impression formation. In C. I.

Hovland (Ed.), The order of presentation in persuasion. New Haven:

Yale University Press, 1957, pp. 33-61."

Luchins, A. S. Definitiveness of impressions and primacy-recency in

communications. Journal of Social Psychology, 1958, 48, 275-290.

* , R-f6
.

MacCrimmon, K. R. and Taylor, R. N. Decision making and problem

solving. In M. D. Dunnette (Ed.), Handbook of Industrial Psychology,

Rand McNally College Publishing Co., Chicago, 1976.

Metcalfe, R. A. The validity, long-term reliability, generality,

robustness, and inter-relatedness of selected Rep Grid indices of

cognitive structure. Journal of Experimental Education, 1978, 47,

* 134-139.

Metcalfe, R. J. Own vs. provided constructs in a Rep test measure

of cognitive complexity. Psychological Reports, 1974, 35, 1305-1306.

Mihevc, N. T. Information, valence, and cognitive complexity in the

* political domain. Journal of Psychology, 1978, 99, 163-177.

Milburn, T. W. and Billings, R. S. Decision-making perspectives

from psychology: Dealing with risk and uncertainty. American

Behavioral Scientist, September/October, 1976, 20(l), 111-126.

C Mitchell, T. R. The construct validity of three dimensions of

leadership research. Journal of Social Psychology, 1970, 80,

89-94.

Mizerski, R. W. Causal complexity: A measure of consumer causal

attribution. Journal of Marketing Research, 1978, 15, 220-228.

Morris, W. T. Intuition and relevance. Management Science, 1967,

1-4(4), B-157-B-165.

Neimeyer, G. J. and Banikiotes, P. G. Flexibility of disclosure

and measures of cognitive integration and differentiation.

o Perceptual and Motor Skills, 1980, 50, 907-910.

Nidorf, L. J. and Argabrite, A. H. Cognitive complexity and the

tendency to make extreme judgments. Perceptual and Motor Skills,

1970, 31, 478.

O'Donnell, R. D. Secondary task assessment of cognitive workload in

alternative cockpit configurations. Higher Mental Functioning in

Operational Environments. AGARD Conf. Prepring No. 181, London,

1975.

Ohbuchi, K. and Horike, K. On consistency of cognitive complexity

between different grids. Japanese Psychological Research, 1978,

20, 177-182.

O'Keefe, D. J. and Brady, R. M. Cognitive complexity and the

effects of thought on attitude change. Social Behavior and

Personality, 1980, 8, 49-56.

R-7

',--II . - ...-..... I- . ,. . ,..,. . . . ..-- -'..-. .. . . .- - - . ''I . -- -.
O'Keefe, B. J. and Delia, J. G. Construct comprehensiveness and

cognitive complexity. Perceptual and Motor Skills, 1978, 46,

548-550.

O'Keefe, B. J., Delia, J. G., and O'Keefe, D. J. Construct

individuality, cognitive complexity, and the formation and

remembering of interpersonal impressions. Social Behavior and

* Personality, 1977, 5, 229-240.

Olshavsky, R. W. Task complexity and contingent processing in

decision making: A replication and extension. Organizational

Behavior and Human Performance, December, 1979 24(3), 300-316.

* Park, C. W. A seven-point scale and a decision-maker's simplifying

choice strategy: An operationalized satisficing-plus model.

Organizational Behavior and Human Performance, April, 1978, 21(2),

252-271.

Park, C. W. A conflict resolution choice model. Journal of Consumer

6 Research, September, 1978 5(2), 124-137.

Pask, G. A cybernetic experimental method and its underlying philosophy.

International Journal of Man-Machine Studies, 1971, 3, 279.

Payne, J. W. Task complexity and contingent processing in decision

• making: An information search and protocol analysis. Organizational

Behavior and Human Performance, August, 1976, 16(2), 366-387.

Payne, J. W. and Braunstein, M. L. Risky choice: An examination of

information acquisition behavior. Memory and Cognition, September,

1978, 6(5), 554-561.

0

Perrault, W. D. and Russ, F. A. Comparing multiattribute evaluation

process models. Behavioral Science, November, 1977, 22(6), 423-431.

Peterson, C. and Scott, W. A. Generality and topic specificity of

cognitive styles. Unpublished manuscript, University of Colorado,

1974.

Poole, M. E. Exploration of relationship inherent in linguistic,

cognitive, and verbal processing domains. Psychological Reports,

1978, 43, 639-647.

Porter, C. A. and Suedfeld, P. Integrative complexity in the

corresponding of literary figures: Effects of personal and

societal stress. Journal of Personality and Social Psychology,

1981, 40, 321-330.

Posner, M. I. and Mitchell, R. Chronometric analysis of classification.

*, Psychological Review, 1967, 74, 392-409.

R-8 0
Pyron, B. A factor analytic study of simplicity complexity of social

* ordering. Perceptual and Motor Skills, 1966, 22, 259-272.

Quinn, E. Creativity and cognitive complexity. Social Behavior and

Personality, 1980, 8, 213-215.

Raphael, D., Moss, S. W., and Rosser, M. E. Evidence concerning the

* construct validity of conceptual level as a personality variable.

Canadian Journal of Behavioural Science, 1979, 11, 327-339.

Rotton, J., Olszewski, D., Charleton, M., a,.d Soler, E. Loud speech,

conglomerate noise, and behavioral aftereffects. Journal of

Applied Psychology, 1978, 63, 360-365.

Rouse, W. B. and Rouse, S. H. Measures of complexity of fault

diagnosis tasks. IEEE Transactions on Systems, Man, and Cybernetics,

1979, SMC-9, 720-727.

Rowbottom, R. Social analysis: A collaborative method of gaining

* usable scientific knowledge of social institutions. London:

Heinemann, 1977.

Rule, B. G. and Hewitt, D. Factor structure of anti-Semitism, selfconcept and cognitive structure. Personality, 1970, 1, 319-332.

* Sauser, W. I. and Pond, S. B. Effects of rater training and

participation on cognitive complexity: An exploration of

Schneier's cognitive reinterpretation. Personnel Psychology,

1981, 34, 563-577.

Schneider, J. F., Kohler, A., and Wachter, H. Conservatism and

* cognitive complexity. Psychological Reports, 1979, 44, 981-982.

Schneier, C. E. The contingency model of leadership: An extension

to emergent leadership and leader's sex. Organizational Behavior

and Human Performance, 1978, 21, 220-239.

Schneier, C. E. Measuring cognitive complexity: Developing reliability,

validity, and norm tables for a personality instrument.

Educational and Psychological Measurement, 1979, 39, 599-612.

Schroder, H. M. The measurement and development of information

processing systems. Management Information Systems, 1971, 14, 811-829.

Schroder, H. "., Driver, M. J., and Streufart, S. Human information

processing. New York: Holt, Rinehart, and Winston, 1967.

Schroder, H. M. and Streufert, S. The measurement of four systems

of personality structure varying in level of abstractness: Sentence

completion method (ONR Tech. Rep. No. 11). Princeton, NJ: Princeton

University, 1962.

R-9
Schroder, H. M. and Suedfeld, P. (Eds.) Personality theory and

* information processing. New York: Ronald Press, 1971.

Scott, W. A. Cognitive consistency, response reinforcement and

attitude change. Sociometry, 1959, 22, 219-229.

Scott, W. A. Cognitive complexity and cognitive flexibility.

* Sociometry, 1962, 25, 405-414. (a)

Scott, W. A. Cognitive consistency, response reinforcement and

attitude change. In N. F. Washburne (Ed.), Decisions, values

and grouDs. New York: Pergamon Press, 1962. (b)

* Scott, W. A. Coqnitive structure and social structure: Some

concepts and relationships. In N. F. Washburne (Ed.), Decisions,

values and groups. New York: Pergamon Press, 1962. (c

Scott, W. A. Conceptualizing and measuring structural properties

of cognition. In 0. J. Harvey (Ed.), Motivation and social

Q interaction. New York: Ronald Press, 1963.

Scott, W. A. Brief report: Measures of cognitive structure.

Multivariate Behavioral Research, 1966, 1, 391-395.

Scott, W. A. Structure of natural cognitions. Journal of Personality

* and Social Psychology, 1969, 12, 261-278.

Scott, W. A. Varieties of cognitive integration. Journal of

Personality and Social Psychology, 1974, 30, 563-578.

Scott, W. A., Osgood, D. W., and Peterson, C. Cognitive structure:

Theory and measurement of individual differences. Washington,

D.C.: V. H. Winston and Sons, 1979.

Shalit, B. Structural ambiguity and limits to coping. Journal of

Human Stress, 1977, 3, 32-45.

Sidanius, J. Cognitive functioning and socio-politico ideology:

An exploratory study. Perceptual and Motor Skills, 1978, 46,

515-530.

Sieber, J. E. and Lanzetta, J. T. Conflict and conceptual structure

as determinants of decision making behavior. Journal of

Personality, 1964, 32, 622-641.

Smith, A. I. and Evans, D. R. Construct structure associated with

alcohol dependent behavior in males. Psychological Reports,

1980, 47, 87-99.

R-10
Smith, S. and Leach, C. A hierarchical measure of cognitive complexity.

(0O British Journal of Psychology, 1972, 63, 561-568.

Spyker, D. A., Stackhouse, S. P., Khalafalla, A. S., and McLane, R. C.

Development of techniques for measuring pilot workload. National

Aeronautics and Space Administration Report No. NASA-CR-1888.

November, 1971.

Stabell, C. B. Integrative complexity of information environment

perception and information use: An empirical investigation.

Organizational Behavior and Human Performance, 1978, 22, 116-142.

Stager, P. Conceptual level as a composition variable in small

* group decision making. Journal of Personality and Social

Psychology, 1967, 5, 152-161.

Starbird, D. H. and Biller, H. B. An exploratory study of the

interaction of cognitive complexity dogmatism and repressionsensitization among college students. Journal of Genetics

O Psychology, 1966, 128, 227-232.

Sternberg, R. J. Testing and cognitive psychology. American

Psychologist, October, 1981 36(10), 1181-1189.

Sternberg, S. Memory-scanning: Mental processes revealed by

* reaction-time experiments. American Scientist, 1969, 4, 421-457.

Stewin, L. Integrative complexity: Structure and correlates.

Alberta Journal of Educational Research, 1976, 22, 226-236.

Stogdill, R. M. New leader behavior description subscales. Journal

I* of Psychology, 1962, 54, 259-569.

Streufert, S. Complexity and complex decision making: Convergences

between differentiation and integration approaches to the prediction of task performance. Journal of Experimental Social

C Psychology, 1970, 6, 494-509.

Streufert, S., personal communication, 1972.

Streufert, S. The human component in the decision-making situation.

In B. King, S. Streufert, and F. E. Fiedler (Eds.), Managerial

i control and organizational democracy. Washington, D.C.: V. H.

Winston and Sons and John Wiley, 1978, 215-230.

Streufert, S., Clardy, M. A., Driver, M. J., Karlins, M.,

Schroder, H. M., and Suedfeld, P. A tactical game for the

analysis of complex decision making in individuals and groUDS.

Psychological Reports, 1965, 17, 723-729.

R-11

C-

-............................. - - -. - -
Streufert, S. and Driver, M. J. Conceptual structure, information

* load and perceptual complexity. Psychonomic Science, 1965, 3,

249-250.

Streufert, S. and Driver, M. J. Impression formation as a measure of

the complexity of conceptual structure. Educational and Psychological

Measurement, 1967, 27, 1025-1039.

Streufert, S., Nogami, G. Y., and Streufert, S. C. Crowding and

incongruity adaptation. In I. G. Sarason and C. D. Spielberger

(Eds.), Stress and anxiety, Vol. 7. Washington, D.C.: Hemisphere

Publishing Corporation, 1980, 185-202.

* Streufert, S. and Schroder, H. M. The measurement of four systems of

personality structure varying in the level of abstractness:

Impression formation method (ONR Tech. Rep.). Princeton, NJ:

Princeton University, 1963.

Streufert, S. and Schroder, H. M. Conceptual structure, environmental

* complexity and task performance. Journal of Experimental Research

in Personality, 1965, 1, 132-137.

Streufert, S. and Streufert, S. C. Behavior in the complex environment.

Washington, D. C.: V. H. Winston and Sons and John Wiley, 1978.

* Streufert, S. and Streufert, S. C. Stress and information search in

complex decision making: Effects of load and time urgency. ONR

Technical Report No. 4, 1981.

Streufert, S. and Streufert, S. C. 7ffects of load stressors on

performance in a multidimensional visual motor task. Hershey, PA:

* Pennsylvania State University Technical Report to the Office of

Naval Research No. 6, 1982.

Streufert, S., Streufert, S. C., Dembroski, T. M., and MacDougall,

J. M. Complexity, coronary prone behavior and physiologcal"

response. In D. J. Oborne, M. M. Gruneberg, and J. R. Eiser

* (Eds.), Research in psychology and medicine. Vol. 1. London:

Academic Press, 1979, 206-218.

Streufert, S., Streufert, S. C., and Gorson, D. M. Time urgency and

coronary prone behavior: The effectiveness of a behavior pattern.

Basic and Applied Social Psychology, 1981, 2, 161-174.

Streufert, S. and Swezey, R. W. Organizational simulation: Theoretical

aspects of test bed design. (SAI Report No. SAI-80-010-178)

McLean, VA: Science Applications, Inc., 1980.

R-12
Strub, M. H. and Levit, R. A. Computer compatibility with decision

style: Eddies in a bit stream. Proceedings of the Human Factors

Society, 1974, pp. 46-49.

Suedfeld, P. and Tetlock, P. E. Integrative complexity of communications in international crisis. Journal of Conflict Resolution,

1977, 21, 169-184.

Suedfeld, P., Tomkins, S. S., and Tucker, W. H. On relations among

perceptual and cognitive measures of information processing.

Perception and Psychophysics, 1969, 6, 45-46.

Svenson, 0. Process descriptions of decision making. Organizational

* Behavior and Human Performance, February, 1979, 23(1 , 86-112.

Swezey, R. W., Davis, E. G., Baudhuin, E. S., Streufert, S., and

Evans, R. A. Organizational and systems theories: An integrated

review. (SAI Report No. SAI-80-113-178). McLean, VA: Science

Applications, Inc., 1980.

Toda, M. The decision process: A perspective. International Journal

of General Systems, 1976, 3, 79-88.

Tripodi, T. and Bieri, J. Cognitive complexity as a function of own

and provided constructs. Psychological Reports, 1963, 13, 26.

Tuckman, B. W. Integrative complexity: Its measurement and relation

t6 creativity. Educational and Psychological Measurement, 1966, 26,

369-382. (a)

Tuckman, B. W. Interpersonal probing and revealing and systems of

0 integrative complexity. Journal of Personality and Social Psychology,

1966, 3, 655-664. (b)

Vace, N. A. and Burt, M. A. Assessment of cognitive complexity with

emotionally handicapped children. Behavioral Disorders, 1980, 6,

26-31.

Vannoy, J. S. Generality of cognitive complexity-simplicity as a

personality construct. Journal of Personality and Social Psychology,

1965, 2, 385-396.

Vecchio, P. A test of the cognitive complexity internretation of the

least perferred co-worker scale. Educational and Psychological

Measurement, 1979, 39, 523-526.

Vetter, M. Ego development and cognitive complexity. Zeitschrift

fur Entwicklungspsychologie und Padagogische Psychologie, 1980, 12,

* 126-143.

R-13
Von Eye, A. and Hussy, W. On the contribution of variables of cognitive

complexity to the identification of risk groups in traffic.

Schweizerische Zeitschrift fur Psychologie und ihre Anwendungen,

1979, 38, 58-70.

Watkins, P. R. Perceived information structure: Implications for

decision support system design. Decision Sciences, 1982, 13, 38-59.

Weiss, H. M. and Adler, S. Cognitive complexity and the structure of

imnlicit leadership theories. Journal of Applied Psychology, 1981,

66, 69-78.

Werner, H. Comparative psychology of mental development. New York:

International Universities Press, 1957.

White, B. J. and Harvey, 0. J. Effects of personality and own stand

on judgment and production of statements about a central issue.

Journal of Experimental Social Psychology, 1965, 1, 334-347.

White, C. M. Cognitive complexity and completion of social structures.

Social Behavior and Personality, 1977, 5, 305-310.

Witkin, H. A., Goodenough, D. R., and Oltman, P. K. Psychological

differentiation: Current status. Journal of Personality and

Social Psychology, 1979, Vol. 37, No. 7, 1127-1145.

W-.jciszke, B. Affective factors in organization of cognitive structures

ih the context of interpersonal perception. Polish Psychological

Bulletin, 1979, 10, 3-13.

Wolfe, J. and Chacko, T. I. Cognitive structures of business game

players. Simulation and Games, 1980, 11, 461-476.

Wolfe, R., Egleston, R., and Powers, J. Conceptual structure and

conceptual tempo. Perceptual and Motor Skills, 1972, 35, 331-337.

Wright, W. F. Properties of judgment models in a financial setting.

Organizational Behavior and Human Performance, February, 1979,

23( ), 73-85.

Wyer, R. S. Assessment and correlates of cognitive differentiation

and integration. Journal of Personality, 1964, 32, 395-509.

Zajonc, R. B. The process of cognitive tuning in communication.

Journal of Abnormal and Social Psychology, 1960, 61, 159-167.

Zalot, G. and Adams, W. J. Cognitive complexity in the perception

of neighbors. Social Behavior and Personality, 1977, 5, 281-283.

R-14

• . -- >:i:

i