Copyright by UILLIAM LEE FUERST 1979

AN INVESTIGATION INTO THE FACTORS THAT MAY AFFECT

THE PERCEIVED UTILIZATION OF COMPUTER-

BASED DECISION SUPPORT SYSTEMS

by

WILLIAM LEE FUERST? B*A.? M*B*A*

A DISSERTATION

IN

BUSINESS ADMINISTRATION

Submitted to the Graduate Faculty of Texas Tech University in

Partial Fulfillment of the Reouirements for

the Decree of

DOCTOR OF BUSINESS ADMINISTRATION

Approved

Accepted

August? 1979

1 ^

I wish to express my sineerest thanks to

ACKNOWLEDGMENTS

'.:.'yv

Paul Cheney?

Doua Andrews? and John Sennetti for their assistance ar\d

support durinsj the preparation o-*' this dissertation* Their

efforts have been extremely valuajble* I'd also like to

thank Larry Austin for his interest throusfhout my doctoral

work*

I am i reatly indebted to the individuals in the oil

companies who donated their time to participate in this

study•

Finally? very special thanks to my wife? Jsn? and

my children? Ginny and Aaron? for their patience? support?

and understand! n*3 throughout the development of this

dissertation*

11

TABLE OF C0NTE:NTS

ACKNOWLEDGMENTS • • * • * * . • * * * * * . > . * * . . : . i i

LISTGFTABLES • • • • • * • • • * * • • • » <• * • > > v

LISTOF FIGURES • • • • • • * • • * * • • • • » <• * • • vi

CHAPTER PAGE

I INTRGDUCTION * . * * • » • • • • * * • * * » • 1

MIS Research Frameworks • • « • • . > * . • 3

Framework for this Research , * * » * • » 6

Research Method * • • » • , > • » , , • • 8

GrsJanization of the Dissertation • • , > 9

II SURVEY OF RELEVANT LITERATURE . * . . * . * > 17

Introduction • • > • * . * + • • ; • * . - • 17

f!ecisiori SuPPOrt Systems ; . • » . • , » , 17

The Need for Behaviors! Research in MIS •> 22

Decision MakinsJ Environment , .;. • ^ • , , 26

Resistance to Chans'e + * , » » * , , , . 32

S i iTi i 13 r R e s e a r c 1 Efforts * * ^ • * • * • 35

III AREAS OF CONCERN » • • » * • * . * ; . * * * » , 46

I n t r 6 d I.J c t i o ri * * • • * * • » • • - » * ^ 46

Characteristics Analyzed in this Stijdy > 46

Areas of Concern • • , , • • » • » • , > 48

Characteristics of the Decision

fl clr:& V * • • • • • * + . » t t f A t."!

C h a r a c t e r i s t i c s o f t f • i e

.i. i i

Implementation Process • • * • 51

Characteristics of the Decision

Support System • » * » v • • • 53

Response Measurement » * : * : • • • • 56

Measurement TechniGues » , • • » • cr-j t >J

IV METHODOLOGY OF THE STUDY * * . * * * * * * * * 60

Pretest of the Instruments • » • • » , * 60

Me as u reme rit Tec f'li"i i au &s • < . • • * • » • * 61

Project Selection • < . * * * » * » • ' , » • 64

De s c r i p t i o n o f Ii e c i s i o i"i M a k. i r'l £5

E n v i r o n m e n t • , » < . • • , • , . * , , 65

Data Co 11 ectiori I"'rocedures > * » * • » * 68

Data Analysis Procedures * » • - • • • • 6

RESULTS OF THE STUDY t * * -t * : • • * ' . * • > t ^ -.J

I n t r o d u c t i o n • • * • • • • » * • • "'" • • / -^

Factors Affectin<^ General Use * • * ( . » * 74

Factors Affectinsi Specific Use * • • • • 77

VI GENERAL CONCLUSIONS AND SUGGESTIONS

FOR FUTURE RESEARCH * * • < • * * • > • > . > . * • 110

Limitations of the Study < . * * • > • • •110

General Implications » » • < . . * • » » till

S I.J si ii e s t i o ri s f or F u t u r e R e s e s v c h * • . * • 115

LIST OF REFERENCES * . * * . * * . » , , , » » , . , , 11.9

APPENDIX A - DATA GATHERING INSTRUMENT . . > . . . . . ,12?

APPENDIX B - LETTER REQUESTING PARTICIPATION . > . :. ,1.3^

LIST OF TABLES

TABLE PAGE

1 Independent and Dependent Variables in

MIS Research • • • • • • • 11

2 Characteristics of Decision Making Process • • 45

3 Freauency of Accuracy and General Use 83

4 Factors Affecting DSS Usa^e • • 85

5 FreQuency of Training and General Use* • • • * 86

6 Distribution of General Use and

Training S Accuracy • * • • * • • • • • * • * 88

7 FreQuency of Experience and Specific Use * • • 90

8 Freauency of Training and Specific Use • * • • 93

9 Freauency of Accuracy and Specific Use • • • • 95

10 Freouency of Relevancy and Specific Use* • * * 97

11 Distribution of Specific Use and

Training 8 Accuracy % Relevancy * • * 99


Training % Accuracy * • • * • • * * * * • * •lOl


Training S Relevancy • * • • • • • 103


Accuracy % Relevancy • * • • * • • * * • * • *105

15 Conditional Probabilities of Other Factors • *107

16 Factors with Low F-values for General Use * *108

17 Factors with Low F-values for Specific Use • •109

LIST OF FIGURES

FIGURE PAGE

1 Mana-aement Levels? Stability? and

Programmed Decision Making • • • • • • • • •

2 A Behavioral Model of System UsasJe • • • • •

3 A Framework for MIS Research Projects * * •

4 Model of the Determinants of I*S* Usa^e * •

5 A Descriptive Model of Information Systems *

6

7

8

9

10

11

12

13

14

15

16

17

18

A Framework for this Research • • • • • • *

Conceptual Structure of a Decision

Support System * * * * * * * * * * * * * * *

Model of Organizations and Their Environments

Model of Characteristics Affecting DSS Use •

Variables in the Business Environment * * *

Mean Responses of Accuracy and General Use *

Mean Responses of Training and General Use *

Mean Responses of Training & Accuracy

and General Use * * * * *

Mean Responses of Experience and Specific Use

Mean Responses of Training and Specific Use

Mean Responses of Accuracy and Specific Use

Mean Responses of Relevancy and Specific Use

Mean Responses of Training S Accuracy

10

12

13

14

15

16

43

44

59

72

84

87

89

92

94

96

98

I Relevancy and Specific Use * * * * * * * * * * 100

VI

19 Mean Responses of Training S Accuracy

and Specific Use * • • • * • • • * • • * • • • * 102

20 Mean Responses of Training X Relevancy

and S p e c i f i c Use • • * • • • * • • • • • • • • • 104

21 Mean Responses of Accuracy % Relevancy

and Specific Use 106

v n

CHAPTER I

INTRODUCTION

In the past twenty years? computer-based management

information systems have progressed from novel concepts to

commonly accepted phenomena* Many companies have employed

an MIS and continue to increase the number of information

systems within their organizations* Unfortunately? however?

there are many situations where information systems have

failed? or have not lived UP to initial expectations* These

failures are seldom a result of technical factors? for

technical problems? as researchers have pointed out? can

normally be rectified in a short period of time CAckoff?

1967f Dickson and Simmons? 1970? Lucas? 1975f McKinsey and

Company? 19683? rather it is behavioral resistance to the

implementation or use of the information system*

Before examining recent research frameworks that were

important in developing the framework for this study? it is

neccessary to define three components of an information

system and note their relationships* First? "decision

maker" refers to individuals at any level of the

organization who have decision making responsibilities*

Second? "management information systems" have no

universally accepted definition? for the purposes of this

study? a management information system (MIS) is defined as

an "integrated? man/machine system designed to support the

operations? management and decision making functions in an

organization" CDavis? 1974? page 43* One critical

characteristic which distinguishes a management information

system from a transaction processing system is managerial

decision making support* In fact? the transaction

processing system is a subsystem of the total MIS* Anthony

C19653 developed a pyramidal representation of the MIS? with

transaction processing as a basis for the operational?

tactical and strategic levels of management (Figure 1*

NoteJ All figures and tables in Chapter I are found at the

end of this chapter beginning on page 10)* Thus? throughout

the entire organization? the MIS is supportive of decision

making*

A special type of system for decision making support—a

decision support system—is the third component* A decision

support system (DSS)? a subsystem of the MIS? consists of

decision models which process and analyze data gathered by

the MIS for the purpose of supporting the decision making

responsibilities of managers at all levels of the

organization* These decision support systems have the

capability of being ouite advanced technologically* Because

many of the problems that arise regarding these systems are

behavioral problems CSenn? 1978? Sprague and Watson? 19753?

researchers and practitioners have emphasized the need for

research regarding the behavioral problems* It is the

purpose of this study to analyze certain characteristics of

the decision maker? the implementation process? and the

decision support system that affect ' the extent of

utilization of the decision support system*

MIS Research Frameworks

In response to the need for research regarding

behavioral problems and management information systems?

researchers have developed many frameworks? each suggesting

variables to be analyzed* The following frameworks were

especially applicable in the development of the research

framework used in this study*

Mason and Mitroff have identified several areas for

research in MIS by defining an information system as J

* * * consisting of at least one PERSON of a certain PSYCHOLOGICAL TYPE who faces a PROBLEM within some ORGANIZATIONAL CONTEXT for which he needs EVIDENCE to arrive at a solution (i*e*? select some course of action) and that the evidence is made available to him through some MODE OF PRESENTATION C1973? page 4753*

Given the key variables capitalized in the above definition?

Mason and Mitroff suggested that MIS research should explore

the characteristics of an MIS by systematically manipulating

these variables*

Chervany? Dickson? and Kozar C19723 developed a

framework for conducting research^ in the area of management

information systems (Table 1)* They identified independent

variables relating to characteristics of the decision maker?

the decision environment? and the information system* They

contend that an investigation of these variables will lead

to knowledge about how a management information system

should be designed* The dependent variable they identified

was Quality of decision effectiveness? measured by cost?

profit? time? etc*

Schewe C19763 conducted a behavioral study utilizing an

attitudinal model to explore the relationship between user

attitudes and system usage (Figure 2)* He believed that a

favorable attitude toward the use of an information system

is very important in obtaining high system use* Usage of

the MIS was measured in two forms* (1) routinely generated

computer reports? and (2) personally initiated reouests for

additional information not ordinarily provided in routine

reports* The independent variables were grouped into six

classifications* MIS capability? user'education? atmosphere?

MIS refinements? other exogenous variables? and attitude

components* Excluding only five exogenous variables? which

were objectively determined? all perceived factors were

measured by means of a five-point? bipolar scale*

Cheney C19773 researched the effect that organizational

and information system characteristics have upon information

satisfaction? Job satisfaction? and system usage* He points

out the effectiveness of an MIS is dependent upon the degree

to which it is used in decision making? use of the system

referred to the extent users employed system generated data

in their decision making processes* The two objectives of

5

his study are incorporated into Figure 3t

1* to evaluate the impact of the MIS intervention

on the users and their decision environment

2* to investigate the relationship between certain

characteristics of the MIS department and the

successful implementation of information systems

Gingras C19743 explored the differences m

psychological characteristics between information system

users and information system designers* In addition? he

examined how the magnitude of the differences in

psychological characteristics and perception affected the

use of the information system* The framework presented in

Figure 4 presents the four basic factors deemed most

important in influencing the Quality of an information

system* technical factors? organizational factors? designer

factors? and user factors* Gingras states that these

factors? taken collectively? determine the Quality of the

information system? and thereby influence whether or not the

intended users will actually use the information generated*

Lucas C19753 developed the model presented in Figure 5?

and conducted an empirical study in an attempt to overcome

some of the difficulties in relating performance to the use

of an information system* According to the model?

performance is partially determined by personal factors such

as age and education? and partially determined by

situational factors such as length of time in a position*

The use of an information system is expected to be partially determined by situational and personal factors* For example? a young? highly educated decision maker may apply analytic tools to the output of an information system in an attempt to improve his performance? whereas an older worker may rely on intuition and experience C1975? page 9103*

In general? the results of this study supported the

descriptive model (Figure 5)? but as Lucas points out? more

research in this area is needed*

Framework for this Research

The framework for this research (Figure 6) was

developed after reviewing the frameworks previously

presented* There are four basic characteristics deemed most

important in influencing the use of a decision support

system*

1* characteristics of the decision maker

2* characteristics of the decision making

envi ronment

3* characteristics of the implementation

process

4* characteristics of the decision support

system*

Each of these characteristics can be divided into factors

which? taken collectively? can determine an overall measure

of the particular characteristic* A more precise breakdown

of the characteristics and factors includes:


3* age

b* years of education

c* educational background

d* years of experience with the company

e* years of experience in present position

f* cognitive style (heuristic vs* analytic)

2* characteristics of the decision making environment

a* stability

b* complexity

c* decision type (programmed vs* non-programmed)

3* characteristics of the implementation process

a* user involvement in the development of the

decision support system

b* user training in the use of the decision

support system

c* top management support of the decision

support system

4* characteristics of the decision support system

a* length of time the decision support system

has been in use

b* response time

c* distance between the user's work area and

the place where he interacts with the

decision support system

d* accuracy of output

e* timeliness of output

8

f* relevancy of output

g* format of output (personalized vs* structured)

h* mode of input/output (batch vs* on-line)

The response measurement is the decision maker's perceived

use of the decision suppport system* From these

measurements? it is possible to evaluate the above

char3cteristics in terms of their effect upon DSS usage* A

detailed discussion of each of the above factors is

contained in Chapter III*

Research Method

To gain information for this research? a field study

was conducted using corporations in the oil industry that

met the following criteria?

1* the decision support system had been in use within

the past six months to three years

2* the decision support system reauired a minimum of

six months to develop

3* the decision support system serves a minimum of

five decision makers

4* the decision support system is on-line

Decision makers at the operative level of the corporation

affected by the on-line decision support system were asked

to respond to statements regarding selected characteristics

of the decision maker? the implementation process? and the

decision support system* The decision making environment

characteristic was omitted from this study? Justification

for its omission will be provided in Chapter III* Data

collected from the corporations were analyzed to determine

the effect these characteristics had on the extent of

decision support system utilization*

Organizstion of the Dissertation

Chapter II contains a review of the literature

underlying this research* Chapter III contains the research

model developed from the framework (presented in Figure 6)

including those characteristics and factors thought to have

a significant impact on DSS usage? with each factor

articulated as an are3 of concern* In addition? studies

that have included similar factors are presented* The

general measurement technioues also are discussed*

Chapters IV and V include the research methodology and

results of the study? respectively* Finally? Chapter VI

contains conclusions and implications of this research and

suggests future research possibilities*

10

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CHAPTER II

SURVEY OF RELEVANT LITERATURE

Introduction

The purpose of this chapter is to provide the proper

foundation for the research conducted in this study* - It

includes a General discussion oft

!• decision support systems

2* behavioral considerations

3» the decision environment

4» resistance to change

5* similar research effortsf including the

variables studiedf measurement techniques

and results*

Decision Support Systems

Sprague and Uatson C19763 have identified certain

characteristics of decision support systemsJ

!• The DSS is designed specifically to support

decision making* Attention to information

flowsf report structure? and data base design

is specifically related to this primary

objective•

2* The DSS is interactive to allow the manager

or his representative fast access to models

17

18

and data* The interactive capability is

not necessarily to provide immediate access

to minutes-old datar but? rather? to dive

access to data and models at a speed which

matches the thought processes of the manager*

3* The DSS is flexible enough to satisfy the

decision makin:^ requirements of many types

of managers: those in different functional

areasf at various managerial levels? and with

different management styles*

4* The DSS is an integrated set of data and

models that allows the models to work

together? and thus avoid suboptimization

whenever possible*

5* The DSS is dynamic enough to keep itself

UP to date without maJor or freouent ad

hoc revisions*

6* The DSS is sophisticated? usind modern

information processing and management

science technioues whenever appropriate*

These characteristics are Generally applicable to decision

support systems? although specific systems may vary from

installation to installation* From these characteristics?

Spradue and Watson developed the conceptual structure of a

decision support system presented in Figure 7* (Note* all

figures and tables are found at the end of the chapter

19

beainnind on pa^e 43*) This conceptual structure is divided

into three major subsystems: the data base subsystem? the

decision model's subsystem? and the decision maker

subsystem*

Redardind the data base subsystem? much of the data

available results from the organization's transactions in

any of the functional areas* Additionally? data can be

obtained from external sources and other internal sources

besides transactions* In the decision model's subsystem?

there are conceptually three levels of models--strate:3ic ?

tactical? and operational—designed to support the primary

decision making responsibilities of top? middle? and lower

management* Model-buildind blocks? usually in the form of

modeling aids? not complete models? are used to aid in the

buildind of the various decision models* Examples of these

model-buildind blocks are simple and multiple regression

analysis? time series analysis? rate of return calculations?

and analysis of variance techniques* In the decision maker

subsystem? a command landuade must be available to interact

with the system* In this subsystem rests all of the

behavioral considerations redardind the implementation and

use of the decision support system*

Althou:3h not specifically mentioned in the Sprasiue and

Uatson model of a DSS? most decision support systems are

designed to be interactive* For example? Keen L19761

advocates the use of interactive decision support systems*

20

He indicates that the DSS approach is based on the following

assumptions about effective decision making and the role of

the computer within the problem-solving process:

1* The computer must support the manager but

not replace his Judgment* It should not try

to provide the "answer" nor impose a

predefined analysis seouence*

2* The main payoff from computer support

is in semistructured tasks* A

semi-structured task describes situations

where parts of the analysis have sufficient

potential for systematization for the

computer to be of value? but where the

decision maker's insidht and Judgment are

needed to control the process*

3* Effective problem solving is essentially

interactive and is enhanced by a dialogue

between man and machine* The user explores

the problem situation? responds to feedback

from the system? and exploits both his own

strengths of experience and insight (often

intuitive) and the system's analytic and

informational power*

It is on this last assumption that Keen places emphasis:

the use of interactive problem solving* He advocates a

"modest system' which implies a rande of strategies for

21

decision support at all levels of the organization* The

major factors involved are*

1* Decree of structure in the task to be supported -

Structure makes interactive dialogue possible?

even desirable* Conversely? in tasks that lack

the structure and the opportunity for

predefining the General seauence of the man-

machine dialogue? the intermediary is the only

practicable interface* However? he can be

effective only if he can provide necessary

turnaround*

2* Number of system users - If the system is to

support many users? then there is likely to be

substantial savins of effort and response time

if the user accesses the system directly*

3* Difficulty in training - The intermediary eases

the burden of training* This may be

especially important for top managers*

4* Level in the organization - Once we have a

:3eneration of mana:3ers who were exposed to direct

use of computers in elementary school? we can

obviously expect executives to be more willing

to sit at a terminal and type or use a li^ht

pen* At the moment? many managers are simply

unwilling to use a system* Once adain? it

should be stressed that the system is what

0 9

they see it to be and if the economic payoff

Justifies the cost? then there may be an

immediate payoff in usind the intermediary*

5* Software overhead - Some DSS interfaces are

harder to build than the underlying system*

The user dialogues cannot be predefined and

the problem structure is too broad to allow

an adeauately General interface* The inter

mediary may be costly? but at the same time

he may be much cheaper? more reliable and

efficient than a Pseudo-Endlish command-driven

interface that irritates managers because it

prevents them from assessing a problem in the

way they wish*

If designers will consider these factors upon development of

a system? "support" for decision making can be further

advanced*

The Need for Behavioral Research in MIS

In the past decade? behavioral research in MIS has

Gained importance* Many researchers advocate the need for

further research* Bostrom and Heinen C1976I1 point out that

the introduction of a new MIS dives rise to three behavioral

Questions: (1) what are the behavioral problems? (2) what

are the causes of the behavioral problems? and (3) what can

we do to solve the behavioral problems? i*e*? eliminate the

23

causes? Much time has been spent in answering Question

number one* In Bostrom and Heinen's words? this is the

"storytelling" phenomenon? in which managers "proclaim" the

problems associated with the new MIS* Recently? researchers

have turned to Question number three in an attempt to

improve the number of successes in MIS implementation*

Unfortunately? Question number two has received relatively

little attention? but it seems that the causes of the

problems (*2) should be determined before attempting to

solve the problems (#3)*

This line of reasoning is consistent with Senn's C19783

belief that although the real reason for processing data is

to assist users? we do not accommodate them very well? and?

in fact? know little about these people* Senn further

explores the possibility that information systems should be

developed with focus on the individual user's reQuirements

rather than on the average user* This could be a rather

difficult task? however? since users have diverse

backgrounds and attributes*

Other authors have realized the importance of

behavioral problems in MIS usade* Dickson and Simmons

C19703 identified three types of dysfunctional

behavior—addression? projection? and avoidance—and

suddested ways to minimize the behavioral problems that may

accompany the introduction of a management information

system* Specifically? they isolated five organizational

24

factors? which? when affected by resistance to change caused

by the introduction of management information systems?

caused dysfunctinal behavior:

1* Most complex organizations have definite

departmental boundaries and divisions of

formal responsibility? and changes in these

boundaries often occur in connection with the

introduction of a new information system*

2* The effect on the informal structure of an

organization? with its values? ethical codes?

and special working relations? also is important*

3* Personal characteristics and backgrounds of

the particular members of organizations will

affect behavior toward the new system* These

factors include ade? length of service?

attitude toward the computer? and organizational

level*

H

It

i

4* The members of an organization are more likely

to respond favorably to a proposed change if

the managerial climate maintains open

communication and permits all Grievances to

be heard*

5* The method employed to introduce change may be

the most important variable affecting its

likelihood of success*

Srinivasan and Dascher C1976I1? as well as Ackoff

25

111976:]? Arayris C1971J? and Swanson C1977D? believe there is

drowind recognition of the user's importance in system

design* Lucas C19753? after conducting empirical research

involving over 2000 information system users in 16

organizations? concluded that most information systems have

failed because organizational behavior problems in the

desidn and operation of computei—based information systems

have been ignored*

Spradue and Watson C1975D have developed a conceptual

structure of a decision support system that exists as a part

of an MIS (Fidure 7)* They believe there are a dreat number

of well-developed models available for decision makers? but

that many of them have not been used as much as one midht

expect* They suddest that characteristics within the

decision makers are possibly the main reason for this

disuse *

Chervany? Dickson? and Kozar C1972D have identified the

II

s

following settings for the development of information

systems:

1* the variables affectind the performance of an

information system be catalogued and the

relationships amend them be understood*

2* deneral principles to be followed in all

information system analysis and desidn be

developed and universally employed*

3* the user of the information system be formally

26

incorporated into the analysis and desidn process*

They foresee that employment of a combination of *2 and *3

will improve the state of affairs in developing management

information systems* Meanwhile? they emphasize that

research is needed to identify and analyze the variables

affectind performance and usade of an information system*

Decision Makind Environment

Several studies have been conducted redardind the

decision makind environment and its relationship with the

decision maker* One of the maJor areas of concern redards

the different types of decisions to be made? in which the

decisions have been classified as prodrammed or

nonprodrammed* The key aspect differentiatind prodrammed or

nonprodrammed decisions is the ability of the individual to

pre-plan the decision makind process* Prodrammed decisions

are repetitive in nature? well-defined? and usually have

previously established decision rules for solvind them* On

the other hand? nonprodrammed decisions are unioue?

ill-defined? and occur only on an occasional or one-time

basis* This is consistent with Simon's distinction between

prodrammed and nonprodrammed decisions:

Decisions are prodrammed to the extent that they are repetitive and routine? to the extent that a definite procedure has been worked out for handlind them so that they don't have to be treated "de novo" each time they occur* Decisions are nonprodrammed to the extent that they are novel? unstructured? and conseouential* There is no cut-and-dried method of handlind the problem

3

27

because it hasn't arisen before? or because its precise nature and structure are elusive and complex? or because it is so important that it deserves a custom-tailored treatment*. By nonprodrammed I mean a response where the system has no specific procedure to deal with situations like the one at hand? but must fall back on whatever deneral capacity it has for intellident? adaptive? problem-oriented action C1960? pade 2513*

Different environments reouire different decision

processes and? conseauently? different information systems*

Additionally? the environment concerns not only the internal

environment within the ordanization? but the external

environment as well* The relationships between the

ordanization and its environments have been developed by H

Emery and Trist C1965I1? as shown in Fidure 8* This model S %

indicates processes within the ordanization (Lll)? exchandes nj fH rt

between the ordanization and the environment (L12 and L21)? J

and processes throudh which parts of the environment become E B

related to each other (L22)* Lll and L12 can be controlled J

somewhat throudh plannind? whereas L21 can be analyzed

throudh the use of forecastind techniQues? diven assumptions

about L22* The stronder the environment? the dreater the

possibility of variance* Thus? forecastind becomes much

more difficult due to the variability and number of chandes

in the environment* In fact? the more sidnificant the L22

process? the less useful it is to desidn or redesidn

information systems on the basis of historical experiences

of the information systems? rather? it is necessary to base

the desidns on assumptions about future characteristics*

28

These assumptions about future characteristics can be

considered on two dimensions:

1* whether the variation of problems is hidh or low

2* whether the intellidence-desidn-choice is

analyzable? and thus possible to prodram*

These relationships are represented in Table 2* From this

representation? certain types of decisions can be denoted*

In Box 4? the dedree of variation in problems in hidh and it

is not possible to analyze the solution process* In Box 3?

problems vary? but solution processes can be divided into

subprocesses and analyzed* Box 2 represents problems which

are fairly easy to recodnize? but the solution process is

difficult* Finally? Box 1 sidnifies standard problems that

are solved by standard operatind procedures* Manaders are

interested in movind their decisions toward Box 1* Emery

and Trist identify three ways to achieve this movement:

1* Increase control over environment so as to

decrease the variation in encountered problems*

2* Increase differentiation by dividind problems into

smaller parts that can be worked on separately

by specialists? with economies of scale*

3* Use modelind to extend the set of analyzable

problems and increase the area that is subject

to plannind*

Ordanizations can use these three ways to increase their

ability to interact with the environment to their own

s

53

.13

29

advantade*

Child C1972I1 claimed that three environmental

conditions are particularly important* environmental

variability? environmental complexity? and environmental

illiberality• Environmental variability refers to the

dedree of chande which characterizes environmental

activities relevant to an ordanization's operations*

Environmental complexity refers to the heterodeneity and

rande of environmental activities which are relevant to the

operations of an ordanization* The dedree of threat from

external competition? hostility or even indifference that

faces ordanizational decision makers in the achievement of

their doals is referred to as environmental illiberality*

Child emphasizes that environmental research should be

oriented toward these three conditions of variability?

complexity? and illiberality*

Duncan C19723 attempted to clarify uncertainty concepts

s

0 3 H S

by relatind two dimensions of ordanization

environments—complexity and dynamism—to a manader's

perception of uncertainty* Redardind complexity? the

simple-complex dimension was defined as the number of

factors taken into consideration in decision makind* The

dynamism dimension (static-dynamic) was defined as the

dedree to which the factors in the decision makind

environment chande over time* To measure uncertainty?

Duncan included the followind dimensions:

30

1* lack of information redardind the environmental

factors associated with a diven decision

makind situation

2* lack of knowledde about the outcome of a

specific decision in terms of how much the

ordanization would lose if the decision

were incorrect

3* the ability or inability to assidn

probabilities as to the effect of a diven

factor or the success or failure of a decision

unit in performind its function

Both the uncertainty dimensions and the environmental

dimensions were defined in terms of ordanizational members'

perceptions* The results of Duncan's study indicated that

decision makers in a simple? static environment experienced

the least amount of perceived uncertainty* On the other

hand? decision makers in a complex? dynamic environment were

H W

S

r a

33

reported to have the hidhest decree of perceived

uncertainty*

Emery Z19671 developed four ideal types of

environments* Additionally? for each type of environment?

he identified the types of behavioral responses which are

necessary for survival* These are summarized as follows:

1* Placid-randomized—doals are relatively stable

and" are randomly distributed throudh the

envi ronment *

31

2*

Behavioral reQuirements—tactics-stratedy • * *

"attemptind to do one's best on a purely

lodical basis*"

Placid-clustered—doals remain stable but

they tend to hand todether in "lawful" ways*

This structurind enables parts of the

environment to potentially serve as sidns

of other parts*

Behavioral reQuirements—tactical response to

each sidn in the environment becomes

dysfunctional* Thus? stratedies become

necessary to subordinate tactical responses

to hidher order doals*

3* Disturbed-reactive—the basic type-two

environment remains relatively unchanded

but more than one system (ordanization or

ordanism) of the same "kind" is present*

Thus? responses or movements within the

environment by a system will likely be

accompanied by responses (potentially

competitive and hostile) from other like

systems *

Behavioral reQuirements—stratedies utilized

in a type-two environment must be broadened

to include competitive stratedies and tactics*

4* Turbulent fields—sidnificant variance arises

IM*

3

P •a

<4

32

from the environmental field itself in addition

to that which arises from the simple interaction

of like systems (ordanizations or ordanism) in

the environment* Reactions precede action*

Behavioral reQuirements—diven "present"

adaptive processes? time of adaptation increases

"beyond all bounds of what is practical*"

Other authors have identified selected variables in the

decision makind environment as beind worthy of continued

research* Some authors CBennis? 1966? Duncan? 1971? Sayles?

196411 have dealt with interaction variables between

ordanizations as a component of environmental complexity*' A

few CAldrich? 1971? Thompson? 1967D have determined that as

the heterodeneity of interactind ordanizations decreases?

the probability that the actions of one ordanization will be

accepted by the others increases* Still others CLawrence

and Lorsch? 1967? Emery and Trist? 1965? Burns and Stalker?

196111 have analyzed the task environment? and have

determined that ordanizations become more receptive to

chande when the task environment becomes more dynamic*

Resistance to Chande

Followind the consideration of the decision makind

environment? it is appropriate to re-emphasize the maJor

•rea of concern in all decision makind situations: chande*

Chande will be met with resistance? for people have a fear

33

of the unknown* This phenomenon can be observed most

readily in the implementation of computei—based syst ems

Much has been written about resistance to chande? the

followind authors' beliefs are representative*

Ardyris C:i9713 has identified six concepts redardind

resistance to manadement information systems? in which the

MIS provides the followind:

1* reduction of space of free movement

2* psycholodical failure and double bind? since

the system makes the decisions

3* leadership based more on competence than on Hi;

power? in which emphasis is placed upon the

use of valid information and technical

competence

4* decreasind feelinds of essentiality

5* reduction of intra- and inter- droup politics

6* new reQuirements for conceptual thinkind*

Because of these factors? user/manaders will tend to resist

the MIS*

Lawrence C1954I1 wrote a classic article redardind

resistance to chande? which can be adapted to a situation

redardind the implementation of a manadement information

system* A major point in this article is that resistance is

not related to technical chande? and that most of the

resistance can be avoided altodether if manadement

understands the nature of resistance to chande and if thi

34

individuals involved participate in makind the chande*

Lawrence further explores this concept by developind the

followind points:

1* Participation as a device is not a dood way to

think about the problem? in fact? thinkind this

way may cause problems* The real key is to

understand resistance to chande*

2* The chande^persons resist is not so much

technical chande as it is social chande—

chandes in human relationships*

3* Resistance is usually created because of

certain blind spots and attitudes which staff

specialists have as a result of their

preoccupation with the technical aspects of

new ideas and methods*

4* Manadement can do certain thinds? includind:

(1) emphasizind new standards of performance

for staff specialists? (2) encouradind them to

think in different ways? (3) makind use of the

fact that sidns of resistance can serve as a

practical warnind sidn in directind and timind

technolodical chandes? and (4) shiftind their

own attention from technical aspects of

chande such as schedules and work assidnments

and the like to a discussion of how these items

affect the development and receptiveness to

chande*

One of the especially interestind phenomenon of most MIS

implementation processes pertains to *3 above* That is? in

many cases? implementation of the system is often a

responsibility of technically trained people who lack

appreciation for behavioral problems* Thus? manadement

should take the initiative to concentrate on the anticipated

and actual behavioral problems durind implementation and

operation of a new MIS*

Similar Research Efforts

Several research efforts were important in the

construction of this author's study* These are presented

below*

Schewe C1976I1 developed the behavioral model of system

usade presented in Fidure 2 (Chapter I)* The basis of this

model is that favorable attitudes toward the use of an

information system is central to obtainind hidh use of a

computer system* However? accordind to Schewe's theory?

attitudes toward such usade are related to the user's

beliefs about the MIS dimensions and other MIS-related and

situational objects* Thus? the research conducted to

support the model identified six classifications of

independent variables: MIS capability? user education?

atmosphere? MIS refinements? other exodenous variables? and

attitude components* Each of these classifications were

36

sub-divided into several contributind factors* Use? the

dependent variable? can be divided into two forms: routinely

Generated computer reports and personally initiated reQuests

for additional information not ordinarily provided in

routine reports* ReQuests were used in this study*

Measurement of the variables in the Schewe study was

performed usind primarily a five-point? bipolar scale?

measurind the respondent's perceived dimensions* The data

were collected from ten food processind companies? and

analyzed usind step-wise redression* Althoudh a few

specific relationships were supported in the redression

analysis? the major findind indicated no sidnificant

relationships between attitudes and system usade behavior*

In Lucas' study II19753 redardind the performance and

use of an information system? the descriptive model

presented in Fidure 5 was developed* Accordind to the

model? performance and use are functions - of several

different factors* Lucas identified the followind

functions:

U = f(P?S?I?D?A)

and f (S ? I ? D ? U)

where U is use? P is performance? S is situational 'factors?

I is personal factors? D is decision style? and A is

attitudes and perceptions about the Quality of the ''system*

These factors were studied as independent variables in a

field research project* To dather data redardind most of

37

these variables? Questionnaire items were developed in which

participants responded alond an appropriate scale*

Step-wise multiple redression analysis was used to predict

performance and use*

The results of this study denerally supported the

descriptive model* One of the most important implications

from the results is that different personal? situational and

decision style variables affect the use of systems* Lucas

believes that such an implication ardues for more flexible

systems to support different user's needs* Another

implication drawn from this study is that desidners should

consider includind user research in the development of

information systems* The most appropriate vehicle for

datherind such user information is the Questionnaire survey*

n J

Swanson C1974I1 conducted empirical research redardind

manaderial involvement in the desidn and implementation of

manadement information systems* The research approach was

H I 3 3

to interview manaders from a company about their involvement

with and appreciation for a specified information system*

The MIS appreciation was based on Questionnaire items

relatind to certain characteristics of the system? for

example? timeliness? relevancy? accuracy? readability and

adeQuacy* MIS involvement also was based on Questionnaire

items redardind the use of the specified system* The

Questions soudht to determine the averade freouency of use

of such thinds as the initiation of chandes of files

38

prodrams or format* Both appreciation and involvement were

measured usind either a five- or six-point scale* The data

Gathered was analyzed usind nonparametric procedures that

classified users as "appreciative" or "unappreciative*" The

results of Swanson's study indicated that manaders who

involved themselves with the MIS appreciated the system?

those manaders who were uninvolved were unappreciative*

Barkin C1974I1 conducted a laboratory experiment

involvind a production simulator in which decision makers'

codnitive style was the focus of the research* In this

study? two different experimental droups were identified*

The droups received the critical decision makind information

either as a separate part of a report? or mixed in the

report with other information that was relatively

unimportant* Results indicated that the amount of data

selected from the reports varied dependind upon the user's

codnitive style*

Bariff and Lusk C19773 proposed that the measurement

and evaluation of user's codnitive style and related

personality traits midht provide an effective means for

attainind successful manadement information systems* They

suddest that the development of deneralized user preferences

for report desidn from limited interviews with users by

system analysts is more subjective than results provided by

.•5

established psycholodical tests* Thus? the authors

rec ommend the use of psycholodical tests as a step towardi

39

more systematic MIS desidn*

Vasarhelyi C19773 conducted research primarily

redardind codnitive style in interactive decision makind*

The four basic areas considered in his research as the main

catedories of behavioral factors in man-machine interaction

were: (1) codnitive characteristics (decision style)? (2)

communication characteristics (perceptions? inputs? and

outputs)? (3) emotional characteristics (frustrations and

fears)? and (4) demodraphic characteristics (ade? education?

and sex)* Usind both parametric and nonparametric

statistical techniQues? Vasarhelyi determined the followind

deneral results:

1* Firms can hire hidhly educated manaders of

either sex*

2* Heuristic manaders are more desirable in

situations where information is expensive*

3* If an individual in a manadement position is

experienced with computers and has a positive

attitude toward them? he will use man-machine

decision systems and tend to be satisfied

with them*

4* Users (manaders) who have only slidhtly

nedative attitudes toward computers before the

utilization of a man-machine decision system can

H

I

be converted to likind them*

Specifically redardind codnitive style? Vasarhelyi

40

determined that analytic decision makers should have

interactive systems tailored to emphasize Quantitative data?

to allow more time for each interaction? and to facilitate

interactive use* In contrast? he determined that heuristic

decision makers reouire tailored systems which emphasize

Qualitative data? are flexible in nature? and allow more

interactions with less time per interaction* Generally?

these results provide support for relatind system desidn to

decision style*

Robey and Zeller C1978I1 analyzed the implementation of

the same information system in two different departments of

the same company (one department which adopted and

successfully used the system? the other which rejected the

system with the system endind in failure)* In both

departments? the technical features of the system and the

work performed were identical* An attitude Questionnaire?

supplemented with an interview? was the primary data

datherind techniaue* The data were analyzed with the

nonparametric Mann-Whitney U test to compare the acceptind

and reJectind droups* Of the seven areas of concern

M m 0

identified—performance? interpersonal relations ?

ordanizational chandes? doals? support from others?

user-developer relationships? and urdency and

importance—only performance and urdency and importance were

statistically sidnificant in terms of differences in

attitudes between the adoptind droup and the reJectind

I

41

droup* More specifically? the adoptind droup's attitudes

toward performance and urdency and importance were more

favorable toward the information system than were the

reJectind droup* Thus? it appears from these results that

user concern is the primary condition of implementind and

improvind MIS user performance* Additionally? Robey and

Zeller concluded with several important factors in MIS

implementation:

1* At the individual level? certain attitudes

were found to be more important than others*

2* Lack of involvement by system developers is

not sufficient to ensure failure if the vital i

function of explainind the system to ultimate ^ nv

users was performed* 9

3* Strond manadement support is instrumental I? £3

in system adoption* ^

9

Benbasat and Schroeder C1974I1 conducted laboratory <

experiments to relate characteristics of an information

system and a decision maker to the resultind decision makind

performance* The independent variables used were: form of

reportind presentation? decision makind aids? exception

reportind? number of reports available? decision makind

style? and knowledde of a functional area* These

independent variables can be classified as characteristics

describind the information system and variables representind

decision maker characteristics* Performance was measured

42

usind the dependent variables of cost performance? time

performance and the number of reports reQuested* The data

was analyzed usind analysis of variance? with the followind

conclusions obtained:

1* Some type of processind either decision aids?

Graphical presentation? or both? should be

used for performance-oriented? decision makind

experiments*

2* The MIS desidner should recodnize that several

variables will have a main effect on the number ' i

of reports reQuested by the user* J

3* Decision makind style and the dedree of ; •k

.'I

functional knowledde also tend to affect il

the number of reports reQuested* tt

As a final recommendation? Benbasat and Schroeder emphasize w

that continued research efforts are important to aid in the X

development of a theory of MIS desidn*

In this chapter? the relevant literature redardind

decision support systems? the decision environment?

resistance to chande? and behavioral MIS research has been

reviewed to provide a proper foundation* Followind this

review? the specific areas of concern for this writer's

study will be presented in Chapter III*

43

fl 1

s-y

— ITJ

C -u 0 c

•H OJ

•u S ctj !

- ^ I

S I

ItJ JJ IT3

a -a IT3 f^

U >

cy5

o a a

cy:

G O

•H

cn •H o 0

Q OJ

o •0

;3 -p o :3 ;-i

-p

Ul

7i

-p

a 0 rj G O O

0

•H

'^

H

s r H I

a < r < H 2 : < 2 C n < w r - - < C Z

44

Organization Environment

Figure 8. Model of Organizations and Their Environments m CI

I

73

Table 2

Characteristics of Decision Making Process

45

^^\^^^ Problem ^ ' v. Var i e ty

Solution ^ v,, ^ Process ^ v ^

Unanalyzable (nonprogrammable)

Analyzable (programmable)

High Variety of Problems

Construct (Box 4)

Program (Box 3)

Low Variety of Problems

Judgment (Box 2)

Routine (Box 1)

H

'A

H

r

I r

CHAPTER III

AREAS OF CONCERN

Introduction

The research framework presented in Fidure 6 (Chapter

I) indicates four characteristics important in influencind

the use of a decision support system* To summarize? they

are:


2* characteristics of the decision makind environment



This research framework is further developed in Fidure 9 of

this chapter to include the factors makind UP each of the

characteristics* These factors were developed after a

literature search and discussion with system desidners?

users? and MIS-related professionals* It is the purpose of

this chapter to present these factors as areas of concern*

Additionally? the deneral measurement techniaue for these

factors will be provided*

H

I 5:1

Characteristics Analyzed in this Study

The three characteristics shown with solid lines in the

model in Fidure 9 (pa^e 59) were used in this study:


46

47



The characteristics of the decision makind environment?

represented by the broken line in Fidure 9? were excluded

from this study for the followind reasons*

The measurement of environmental characteristics

reQuires complex analysis* Downey and Slocum C19753?

recodnizind the complexity of measurement? ardue that an

ordanization's environmental characteristics are not well

represented by a simple summation of individual perceptions

of them* Individuals within an ordanization do not work

within a sindle environment? analysis needs to be directed

at individuals existind in several environments? which

complicates the analysis* Thus? the difficulty in measurind

environmental characteristics lies in the extensive number

of factors to be measured* Also? it is more difficult to

isolate factors in the environment* If measurement of the

«ii

environmental characteristics were included? the emphasis of

this study would shift from a study concernind manadement

information systems to a consideration of the environment*

Thus? characteristics of the decision makind environment

were not included in this research effort* However? a

discussion of the environmental characteristics of the

ordanizations from which data was collected for analysis in

this study will be included in Chapter IV*

48

Areas of Concern

The model presented in Fidure 9 includes the

characteristics and factors deemed most important in

affectind DSS usaGe* Each factor can be stated as an area

of concern for this study* In this section? these areas of

concern will be presented* Also? other research studies

which have used the same or similar factors will be

presented to provide support for includind the factors in

this research*

Characteristics of the decision maker

With the current emphasis on the user in the

development of computer-based information systems? many

researchers have included characteristics of the decision

maker as part of their studies* Most notable from the

standpoint of the development of this writer's study are

Lucas C19753? Gindras C1975:? and Schewe C1976D? who have

used all of the decision maker factors included in this

study *

*1* To what dedree does a^e affect the extent of

use of the decision support system?

*2* To what dedree does educational level affect the

extent of use of the decision support system?

*3* To what decree does educational backdround affect

extent of use of the decision support system?

The three areas of concern listed above relate to the

m.

49

factors of aê and education* Redardind aêr it is

Generally believed that younGer decision makers are more

receptive to new ideas and techniQues to aid them in

decision makinG* Thus? it is necessary to analyze any

differences in usaGe rates based upon the aê of the user*

ReGardinG education? two factors of the decision maker's

educational experience need to be analyzed: number of years

and type of education* If the decision maker has formal

education beyond hidh school? the type of educational

backdround may have an effect upon DSS usade CGuthrie? 1971?

Kyoman 1976? Vasarhelyi? 19773*

*4* To what dedree do the years of experience of

the decision maker affect the extent of use

of the decision support system?

*5* To what dedree do the years of experience in

his present position affect the extent of


As the lendth of time an individual spends with a

company increases? his familiarity with the formal and

informal information flow within that company increases*

The same is true for the lendth of time spent in a

particular position* Based upon experience? a decision

maker may choose to use either a formal approach (for

example? a decision support system)? or an informal approach

to receive information*

•6* To what dedree does the codnitive style of the

•A

50

decision maker affect the extent of use of the

decision support system?

Different people use different problem solvind

techniQues? randind from analytical to heuristical?

trial-and-error approaches* And Just as different people

have different problem solvind techniQues? different

researchers have obtained different results redardind the

effect of codnitive style on use of an information system*

For example? Benbasat and Schroeder C1974I1 analyzed

codnitive style in their experiment concernind certain

characteristics of decision makers* They concluded that

codnitive style did not affect the cost or time performance

as a main effect* On the other hand? Lucas C1975II

determined that codnitive style appeared to affect the use

of an information system? and he ardued for more supportind

research* Likewise? Doktor and Hamilton C19733? in a study

involvind codnitive style and its effect in implementind

J)

H

manadement information system projects? concluded that:

* • * while codnitive style is clearly not the only contributind factor? there is drowind evidence to suddest that differential thoudht processes may account for certain implementation obstacles*' Thus? codnitive style factors should be considered in future studies of system implementation and use Cpade 8933*

There have been several other authors who have used

codnitive style as a research variable CBarkin? 1974?

Vasarhelyi? 1977? Huysman? 1970? Bariff and Lusk? 1977?

Mock? 1973? and Dermer? 19733* Thoudh codnitive style has

51

been used often? there is still inconclusive support

redardinG its effect on use of an information system? the

stronGest conclusion Generally drawn is that coGnitive style

may affect usaGe* Since most researchers a^ree that more

research is needed redardinG its effect? coGnitive style was

included in this study*

Characteristics of the implementation process

In the implementation process? there are three factors

that are very important: user involvement? user trainind?

and top manaGement support* There are probably more

conceptual and research reports reGardinG implementation

than the other two areas of this research* This is

primarily due to the similarities of operations

research/manadement science implementations and MIS

implementations* Redardind both kinds of implementations?

individuals can readily believe in the intuitively appealind

idea that system implementations are likely to be successful

with hidh levels of user involvement? user trainind? and top

manadement support*

The followind areas of concern of the implementation

process were used in this study:

*7* To what dedree does user involvement in the

~implementation process affect the extent of


In terms of system development? user involvement has

n

11

52

been strondly advocated* In the last decade? the concept of

participative manadement has been emphasized as an excellent

way to Get employees involved in decision makinG? employees

will work harder for the successful implementation of

decisions in which^they participated* This? of course? has

a direct bearinG on MIS implementation as well? for it is

believed by many CMann and Williams? I960? Lawrence? 1954?

Kind and Cleland? 19753? and empirically studied by others

CHuse? 1967? Dickson and Simmons? 1970? Swanson? 1974?

Schewe? 19763 that user involvement is important*

*8* To what dedree does user trainind in the use !

< of the decision support system affect the ^

extent of its use? .

•Hi

If implementation success is measured in terms of ^

system usade? as is often the case? then user trainind is " ':UI

7 perhaps the most appealind idea in terms of the 3 implementation of successful systems* Several authors have •*

included user trainind in their research studies? includind

Dickson C:i9693? Schewe C19763? Mann and Williams C19703? and

Dickson and Simmons C19703* Likewise? it was included in

this research to determine the effect of user trainind on

DSS usade*

•9* To what dedree does top manadement support

of the decision support system affect the

extent of its use?

Conceptually? top manadement support of an information

system is an admirable objective* However? there are

companies that do not have support from their top manaders*

For instance? Diebold reports that:

• • • a particularly sidnificant problem exists with reGard to top manaGement itself* From all indications? computer activity in most companies does not receive top manaGement attention which one would expect in view of the maGnitude of the investment and its potential benefits C1969? pa^e 163*

This conclusion is also consistent with Burck's findind

•<!1968? pade 1463 that too many companies are still leavind

the application of computer systems to technicians rather

than manaders: only when the top manaders pitch-in and

support the systems will the machine realize its

potentialities*

In terms of research efforts? Dickson C19693? Schewe

C19763? Huse C19673? and Robey and Zeller C19783 have

included top manadement support as a variable in their

studies* Althoudh conceptually top manadement support of

systems is appealind? the results of these studies have

varied in their effect upon information system usade* It

was? therefore? included in this study*

Characteristics of the decision support system

Several recent studies have included the information

system factors of this writer's study* For example? Lucas

II19753 developed a descriptive model that included the

user's perceptions about the Quality of the information

ystem* The factors he included as a measure of the Quality

of the system are the same factors that are included in this

study* Additionally? Schewe [119763? Swanson C19743? Cheney

C19773? Bostrom C19783? and the researchers involved in many

of the Minnesota experiments CDickson? et al*? 19773 have

included the same kinds of factors for Quality of the

system* Usind these research efforts for deneral support of

the factors concernind the characteristics of a decision

support system? the followind areas of concern are

presented*

*10* To what dedree does the lendth of time the

decision support system has been installed

affect the extent of its use?

The life span of a typical decision support system is

five to six years? at which time either maJor renovations

are performed or the system is eliminated* By dividind the

life span into shorter time periods? it is possible to

determine if usade rates vary throudhout the life span of

the decision support system*

•11* To what dedree does the response time of the

decision support system affect the extent of

its use?

*12* To what decree does the distance between the

user's work area and the place where he inter

acts with the decision support system affect

the extent of its use?

There are some mechanics of the decision support system

:"j

55

that need to be evaluated* If a user has to wait a

considerable lendth of time before receivinG his output? or

if he has to travel a considerable distance to interact with

the system? the extent of utilization of the decision

support system may be affected* It is necessary to

determine if? indeed? there is any effect*

•13* To what deGree does the accuracy of the output

from the decision support system affect the

extent of its use?

•14* To what dedree does the timeliness of the

output from the decision support system affect

the extent of its use?

•15* To what dedree does the relevancy of the output


extent of its use?

Inaccurate? untimely? and/or irrelevant information may

affect the amount of usade of the decision support system?

and these factors must be evaluated*

•16* To what dedree does the format of the output


extent of its use?

•17* To what dedree does the mode of input/outPut

affect the extent of use of the decision

support system?

The format of output can either be denerallly

structured to fit all users of the system? or personally

•1 n <

H

structured by each individual user* Mode of input/outPut

can be either batch or on-line* In each case? these factors

may have an effect on the usade of the DSS*

Response Measurement

System usade has been used in several studies as

response measurement (dependent variable)* For example?

Schewe C19763 distinGuished between system usade in terms of

routinely denerated reports and in terms of special reports

Generated individually by the decision maker? usind the

latter as the response measure in his study* Lucas C19753

in the descriptive model analyzed system usaGe as the 1

dependent variable* Swanson C19743 determined several

different measures of the use of a system in his

behaviorally oriented research* In comparinG desidner

characteristics with user characteristics? Gindras C19753

used system usade as a measure of the Quality of the

information system* Several others? includind Schroeder and

Benbasat C19773? Senn C19783? and Vasarhelyi C19773? have

also used system usade as the dependent variable*

Therefore? usind the above studies as support? this study

used the decision maker's perceived use of the decision

•il

I! •t

'3

support system as the response measurement *

me

Redardind the studies diven above? it is appropriate to

ntion that in most cases system usade was used as an

indication of system success This appears to be an

57

appropriate indication of the success of systems? althoudh

there are obviously varyind dedrees of success based on the

characteristics of the system* Also? as Ein-Dor and SeGev

C19783 point out? one must be careful in discussind success?

for success of an MIS project is not the same as success of

a manadement information? or decision support? system*

A clear distinction should be made between the success of an MIS project? defined as completion on time and within buddet? and the success of the MIS? which is the end product of the project* A project may be successful and yet result in an unused and therefore unsuccessful system* A project may be pladued by cost overruns and schedule slippades? and still result in a widely used system Cpade 10663*

Measurement TechniQues

The precise data datherind techniQues will be presented

in Chapter IV* However? at this point it is appropriate to

discuss the deneral measurement techniQues used in this

study* There were basically two different methods* A few

items on the Questionnaire reQuired objective responses*

For example? a^e was measured accordind to a classification

from 20 to 29? 30 to 39? etc* The other factors that were

objectively measured were education level? type of

education? experience? and lendth of time the user has used

the system* All of the remainind factors were measured

accordind to a response alond a diven scale* For example?

codnitive style was measured usind a 17-item instrument

developed and validated by Barkin C19743* The respondents

,1

•iJ

could circle numbers which randed throudh adree strondly?

58

adree slidhtly? disadree slidhtly? or disadree stronGly* An

instrument developed and validated by Lucas C19753 was used

to measure the characteristics of the implementation process

and the decision support system* Several other researchers

CSchewe? 1976? Swanson? 1974? Cheney? 1977? Bostrom? 19783

have used the same or similar instruments for measurind

these characteristics* It is important to note that in

redard to the characteristics of the implementation process

and the decision support system? the decision maker's

perceptions were soudht* There was no attempt to

differentiate between "actual" and "perceived?" for

individuals will behave accordind to their perceptions? and

it is? therefore? perceptions of characteristics which

affect DSS utilization*

•3 -.3

59

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•4

CHAPTER IV

METHODOLOGY OF THE STUDY

Van Horn C19743 indicated four possible methods for

study in MIS:

1* case studies?

2* field studies? includind experimental desidn? but

no experimental controls?

3* field tests? includind both experimental desidn

and controls? and

4* laboratory studies* 1

1 He further indicated that of these four methods? the two <

'J that are most promisind are field studies focusind

\ '-fi

on desiGn considerations? and laboratory studies which can ^ use data and strTjctures from actual situations*

Given these alternative methods? it was determined to

conduct a field study to dather data for this

research* However? before data could be dathered in the

field? a pretest of the instruments was necessary*

Pretest of Instruments

A pretest was conducted in Lubbock? Texas? durind

March? 1979? to determine the validity of the data datherind

instruments* Supervisory manaders from two Lubbock

corporations were asked to complete the instrument* Two

60

A;

•.31

)

'i'i \ \

61

methods were used in administerind the pretest in each of

the corporations: (1) Participants were diven the

instrument and asked to complete it at that time? after

completion? this researcher conducted follow-up interviews

to determine if the responses indicated were the

respondents' valid perceptions and to identify any ambiduous

Questions* (2) Participants were diven the instrument and

were allowed several hours to complete it* This researcher

then collected the instruments? conductind the same

follow-up interview as outlined above* Althoudh both

methods yielded valid responses? the latter method was used

for this study because manaders were more receptive to

completind the instrument at their convenience* As a result

of the pretest? a few minor chandes were made to some of the

Questions in the instruments* These minor chandes did not

alter the essence of the instruments? instead? the

Questions were stated more clearly or concisely*

1

n

3

Measurement TechniQues

The data datherind instruments are presented in

Appendix A* Generally? factors in this study were measured

usind an objective response or a response based on a

Likert-type scale* Sections I and II of the data GatherinG

instruments concern the characteristics of the decision

m aker? as follows:

62

Factor Analyzed Question Number(s)

Ade

Years of education

Educational backGround

reGardinG computer systems

Years of experience with

I - 1

1 - 2

the company 5

Years of experience in

present position 1 - 6

Codnitive style II-l throudh 11-17

Sections I pertains to the decision maker's demodraphic

characteristics? which were determined usind objective

Questions* Question 4 concernind manaderial level in the

company was used to make sure that only lower level manaders

responded to the instrument* Question 7 was included to

measure the respondent's overall attitude when workind with

computer-based systems*

Section II is a 17-item instrument which measures

codnitive style* From the responses? which randed throudh

a^ree strondly? adree slidhtly? disadree slidhtly? and

disadree strondly? a measure of the participant's codnitive

style was obtained* This instrument was developed and

validated by Barkin C19743? and is referred to as the

1

3

Analytic-Heuristic Questionnaire (AHQ)*

In Section III? the characteristics of the

implementation process and the decision support system were

63

measured? as follows:

Factor Analyzed

Participation

Trainind

TOP manadement support

Response time

Accuracy

Timeliness

Relevancy

Format

Distance traveled

Question Number

1

2

3

4

5 -

5

6

9

a

b

c

Time the system has

been in use III - 11

Questions 1-6? 9? and 11 reQuired responses alonG a diven

e 7-Point scale? and pertain to the user's perceptions of th

characteristics of the implementation process and the

decision support system* Question 10 was included to make

sure that only on-line system users responded* Question 12

measured the respondent's overall reaction to completind the

data datherind instruments*

The response measurements for this study were: (1) use

of routinely denerated reports by the decision support

system? and (2) use of special reports denerated by the

individual decision maker* These response measurements were

J

3

m easured by Questions 7 and 8 in Section III*

64

Project Selection

Letters seekinG participation in the study were mailed

to 24 oil companies in selected cities* These letters

(Appendix B) emphasized that companies are spendind a dreat

deal of money in desidninG systems? many of which have

failed or are not livinG UP to initial expectations? and

this study will provide them an opportunity to be involved

with research in the desiGn of systems* The criteria

reGardinG the decision support systems to be analyzed were

included in the letters? and were as follows:

1* A decision support system had been in use within

the past six months to three years*

2* The decision support system reQuired at least six

months to develop*

3* The decision support system serves a minimum of

five decision makers*

4* The decision support system is on-line*

Enclosed with the letter was a brief Questionnaire (see r

Appendix B) reGardinG the system the company identified as a

candidate system for the study* These Questionnaires were

used to determine if the systems met the criteria outlined

above and to determine some General characteristics of the

systems *

After the candidate system Questionnaires were returned

by mail to the researcher? the individuals who completed

them were contacted by telephone to answer any Questions and

1

1

\ 1

i

3

to establish a timetable for an initial meetinG* After the

screenind process? eiGht oil companies were chosen to

participate in the study*

Description of the Decision MakinG Environment

Before proceedind to the next section redardind the

data collection procedures? it is useful to denerally

describe the environment? the decision support systems? and

the decision makers of the participatind oil companies* The

economic importance of the oil industry needs little

elaboration* In 1974? the refinind companies had sales

within the United States in excess of $117 billion and ^

accounted for 25 per cent of the net income of all ^ 1

manufacturind companies in the U*S*? 15 per cent of all . a

manufacturind assets were m the oil industry CFederal Trade 1

Commission? 19743* Five of the ten lardest companies and 16 ^ .J

of the top 50 were oil companies* Althoudh there were only

34 oil companies amond the lardest 500? they accounted for

24 per cent of the entire droup's sales? 25 per-cent of the

assets? and 34 per cent of the profits CU*S* Department of

Labor? 19783*

The eidht companies which participated in the study

were larde? international oil companies* The yearly sales

fidures ranged from $441 million to $27 billion? and the

number of people employed by these companies randed from

3210 to 70?646*

66

Within the oil industry? there are three maJor

divisions: (1) exploration and production? (2) refinind?

marketind? and distribution? and (3) petrochemicals* All

of the participatinG companies were involved with all three

areas* However? the systems identified for analysis were

only from the refininG? marketinG? and distribution area*

This emphasis on only one area resulted in more consistency

amonG systems? althouGh there were some differences*

Of the eidht systems used in this study? five were

similar:

1* marketind analysis system: developed to provide

rapid access to operational and financial data

2* refinery blue book system: developed to collect

and validate all monthly refinery cost and yield

data

3* economic analysis system: desidned to provide

rapid and complete economic analysis of capital

investment expenditure opportunities? includind

sensitivity and incremental analysis

4* inventory manadement systems: desidned to provide

current information concernind the status of a

variety of inventories

5* distribution network system: developed to provide

cost analysis of alternate distribution networks*

All of the systems met the established criteria? in

that they had been in use within the past six months to

1

67

three years? reQuired at least six months to develop? serve

3 minimum of five users, and are on-line* The computer

systems suPPortind these decision suPPort systems were all

larde mainframe systems located in-house* The number of

users served by each decision supPort system ranGed from 5

to approximately 100 users at all manaGement levels of the

orGanization*

ReGardinG the characteristics of the 64 participatinG

system users? they were all lower level manaders? with an

averaGe aê of 31* The averaGe number of years of education

was sliGhtly over 16 years? with 72% havind a collede ^

dedree* Most of the users had some experience with computer )

systems as part of their formal education* Also? the \ 1

*avevaê respondent" had a rather positive attitude when \ •m

workind with computer systems* The averaGe number of years 1

the respondent had been with the company was 6*375? and the '

averaGe number of years of experience in the present

position was 3*03* Since these were lower level manaders?

the decisions they make are relatively short-randed? but not

necessarily prodrammed and routine* Additionally? althoudh

a business firm's environment consists of many components

(see Fidure 10? paê 72)? the decisions of the manaders in

this study are not directly affected by external

environmental factors* In terms of the types of positions

held by these manaders? the followind list is

representative:

68

!• inventory section supervisor

2* Plannind advisor

3* facilities evaluation coordinator

4* refininG supervisor

5* truckinG supervisor

6* supervisor in wholesale sales

7* supervisor in distributor sales

8* PurchasinG aGent

9* raw materials supervisor

10* warehouse supervisor

11* economics and evaluation manader ^

Data Collection Procedures

The data collection procedures for each corporation

were as follows:

1* An initial meetind , was held with the

appropriate manader to clarify any details of the

study with the intent of obtainind formal approval?

in some cases? formal approval was received later* In

each case? this individual was a manader in the

information systems department who was familiar with

the decision support system to be analyzed and its

users* A copy of the data datherind instrument was

presented to the individual for his consideration? as

well as the consideration of his superiors* Once final

approval was dranted? a timetable for collectind the

1

i

•

IB

i 3

69

data was established*

2* On the arranded date? as early in the mornind as

possible? the researcher individually distributed the

data datherind instruments to the decision makers/users

of the decision support systems* These users were

told to complete the instruments sometime durind the

day* At the end of the day? the researcher

individually collected the instrument from each

respondent* At the time of collection? the

respondents were asked if they had any Questions

concernind the instrument? and a check was made to

insure that all items had been answered*

collected? it was coded for analysis*

Data was analyzed two ways: (1) usind descriptive

statistics? and (2) analysis usind a deneral linear model*

Since this was a field study? primary data analysis involved

the use of descriptive statistics to identify the

characteristics that affected decision support system usade*

Additionally? since data was drawn from an apparently

random sample? F-ratios were calculated usind linear model

procedures* Usind these ratios as a measure of the effect

of each factor upon DSS utilization? inferences were drawn

about the relationship between the factors and the use of

)

3* Once the data from the eidht companies had been 4 1 "S

Data Analysis Procedures ^ 3

• 0

xp^'^- 70

2* On the arranded date? as early in the mornind as /

possible? the researcher individually distributed the

data datherind instruments to the decision makers/users

of the decision support systems* These users were

told to complete the instruments sometime durind the

day* At the end of th( day the researcher

individually collected the instrument from each

respondent* At the time of collection? the

respondents were asked if they had any Questions

concerninG the instrument? and a check was made to

insure that all items had been answered*

3* Once the data from the eidht companies had been

collected? it was coded for analysis*

Data Analysis Procedures

Data was analyzed two ways: (1) usind descriptive

statistics? and (2) analysis usind a deneral linear model*

i

3

.1

Since this was a field study? primary data analysis involved

the use of descriptive statistics to identify the

characteristics that affected decision support system usade*

Additionally? if it is believed that the data is drawn

from a random sample? F-ratios can be calculated usind

deneral linear model procedures* Usind these ratios as a

m easure of the effect of each factor upon DSS utilization?

inferences can be drawn about the relationship between the

factors and the use of the decision support system*

71

instrument were repeated? and the respondent's answers were

checked adainst the oriGinal responses* In two of the

cases? errors were detected reGardinG the responses for

General and specific use of the DSS* These errors were

corrected? and the observations were included in the

analysis* In another situation? the respondent indicated

that he was opposed to completinG the instrument initially?

he had completed it haphazardly? and strondly preferred not

to be bothered adain* Upon examination of his

Questionnaire? it was noted that most of the responses were

at either extreme? and it? therefore? was decided to

eliminate that observation from the study*

\

11

• 1

3

,1

72

d) e c o u

•H > c w CO CO

c • H CO 3

CO

CJ

C • H

CO 

0)

3

•H

4 i

if

• »

CHAPTER V

RESULTS OF THE STUDY

Introduction

Data collected from the decision makers was analyzed

two ways: (1) usinG descriptive statistics? includind

conditional probabilities and mean response freQuency

distribution? and (2) usind a deneral linear model to

calculate F-ratios* Usind the results of these analyses?

the factors of the model (Fidure 9? pa^e 59) that affect

the dedree of use of a decision support system were

identified* Before presentind these factors? the reader is

reminded that the response measurements for this study were

perceived decision support system usade? measured in terms

of: (1) deneral? routinely denerated reports? and (2)

specific? personally initiated reports* Throudhout this

chapter? the terms "deneral use" and "specific use" refer to •]

the two different types of usade* Both deneral and specific

use were measured alond a 7-Point scale? with 1 representind

very little use? and 7 representind a dreat deal of use* If

4 is considered average usade? the responses above and below

this average can be analyzed descriptively*

Conditional probabilities and F-values were calculated

for all factors in the study* There were several factors in

the analysis that were not supported in terms of their

73

74

effect on DSS usaGe* These factors' conditional

probabilities and F-values are presented in Tables 15-17*

AlthouGh the purpose of this chapter is to provide evidence

of those factors affectinG DSS usade? the factors not

supported by the analysis also will be discussed in Chapter

VI*

Factors Affectind General Use

Two factors were sidnificant in affectind deneral use

of the decision support system: (1) accuracy of the output

provided? and (2) user trainind of the DSS durind the

implementation process* Of the 64 lower level manaders that

participated in the study? 26 indicated they had above j

average deneral use of the decision support system? i*e*? 26 •

responded with a 5? 6? or 7 for deneral use* Output

accuracy? also measured on a 7-Point scale? was indicated

above average by 35 manaders* Twenty respondents marked

both deneral use and accuracy above average* In terms of

conditional probabilities? this means that diven above

average accurac^y the probability that there will be above

average deneral use is 0*57* Table 3 shows the precise

breakdown of the responses for deneral use and accuracy*

(Note: All tables and fidures are found at the end of this

chapter bedinnind on pa^e 83*) Additionally? there were 25

responses of below average deneral use and 13 responses of

below averade accuracy* Ten manaders indicated below

75

averade measures for both General use and accuracy (see

Table 3)* Given below averaGe accuracy? there is a 0*77

probability that General use will be below averaGe* A 0*57

probability of above averaGe General use Given above average

accuracy? and a 0*77 probability of below average deneral

use diven below averade accurac^f supports the conclusion

that accuracy affects deneral use*

The importance of accuracy is further supported by a

draph of the mean responses and by calculatind an F-value

concernind the effect of accuracy on deneral DSS usade* The

^raph of the mean responses for accuracy and deneral use

(see Fidure 11) indicates a deneral , trend in which deneral

use increases as the perceived accuracy of output increases*

As indicated in Table 4? the computed F-value is 25*14?

with a probability of 0*0001 that the critical F is dreater

than the computed F* (The reader is reminded that a hidh

value of F means there is a hidh probability of difference?

not that the difference is hidh)*

The second factor which affected deneral DSS use was

user trainind durind the implementation process* Table 5

shows the responses of General use and user trainind* User

trainind was measured alond a 7-point scale? with 24

respondents indicatind above average trainind* Of those 24?

and the 26 users who responded with above averade deneral

use? 18 responded with above averade use on both measures*

That is? Given above average trainind? there is a 0*75

76

probability that there will be above averade deneral use*

Interestindly? only 2 people responded with above averade

trainind but below averade deneral use* Also? 16 users

indicated both below averade trainind and deneral use* In

other words? there is a 0*72 probability that deneral use

will be below averade Given below averaGe traininG* The

mean response Graph (FiGure 12) Generally shows a trend of

increasind deneral use as the amount of trainind increases*

The computed F ratio (Table 4) is 32*93? with a probabillity

of 0*0001 that the critical F value is dreater than the

computed F ratio* Given the relatively hidh conditional | r I

probabilities of 0*75 and 0*72? the mean response ]

distribution? and the larde F-value of 32*93? trainind was j

determined to have a strond effect upon deneral DSS use*

DSS use (see Table 6)* Nineteen indicated in the above

average rande for both accuracy and trainind? 13 also

indicated above average deneral use* This is a conditional

probability of 0*68 that above average DSS usade will

accompany above average trainind and accuracy* Conversely?

12 manaders responded in both the below average randes? with

9 also respondind below averade in deneral use? with a

conditional probability of 0*75 that below average deneral

use will accompany below averade trainind and accuracy*

Fidure 13 indicates a positively sloped trend in which

)

• Concludind that accuracy and trainind are important? it •

is useful also to analyze their combined effect upon deneral i

11

77

General use increases as the combined effect of accuvac^i and

traininG increases* A computed F-value of 38*86 (Table 4)

offers evidence of the combined effect of accuvac\i and

trainind on deneral DSS use*

Factors Affectind Specific Use

Four factors had an important effect upon specific

decision support system use: (1) experience in the decision

maker's present position? (2) user trainind durind the

implementation process? (3) accuracy of the output provided?

and (4) relevancy of the output provided* Of the 63

respondents? 29 indicated above average specific use? with

26 indicatind below average specific use*

Experience in the decision maker's present position?

which will be vefevved to as experience throudhout the

remainder of this chapter? averaded 3*03 years* Usind this

averade as a cut-off between above and below averade

experience? 18 manaders indicated above averade experience?

with 12 manaders respondind in the above averade randes for

both specific use and experience (see Table 7)* This

results in a probability of 0*67 that? diven above averade

experience? specific use will also be above averade* In the

below averade randes? there were 20 decision makers with

both below averade specific use and experience? resultind in

a conditional probability of 0*54 that specific use will be

below averade diven below averade experience* Althoudh the

78

Graph of the mean responses is somewhat erratic? there

appears to be a positive relationship between specific use

and experience* UsinG the General linear model procedure?

an F-value of 9*49 (see Table 4) was computed? with a

probability of 0*0031 that the critical F value is Greater

than the computed F value* While lower than desired? the

conditional probability of below averade use and experience

coupled with the hidh levels of the other probabilities

leads to the conclusion that experience affects specific DSS

use*

The second factor important in its effect upon DSS

specific use was user trainind (see Table 8)* Twenty-four

respondents indicated above average trainind durind the

implementation process* Of these? 18 also indicated above

averade specific use of the DSS? divind a conditional

probability of 0*76 that? diven above averade trainind?

there will be above averade specific use* Redardind the

below average randes? the probability was 0*72 that below

average specific use will occur diven below average

trainind? 18 of the 25 respondents indicated both below

average specific use and trainind* From Fidure 15? the mean

responses of trainind and specific use indicate that as the

amount of trainind increases? specific use increases* The

calculation of the F ratio (see Table 4)? results in a

computed F-value of 26*58? and a probability of only 0*0001

that the critical F-value is dreater than the computed

79

F-value* As a result of the hidh F-value? the mean response

distribution? and the hidh conditional probabilities?

trainind was determined to have a hidh dedree of effect upon

the extent of specific DSS usade*

Accuracy of output? the third factor? also was

determined to be important in affectind DSS specific use*

Thirty-five respondents indicated above averade randes for

accuracy? with 20 of them also indicatind above averade

specific use (see Table 9)* That results in a conditional

probability of 0*75 that specific use will be above average

Given above averaGe accuracy of output from the DSS*

Similarly? a conditional probability of 0*72 is obtained

from the 13 of 25 users with both below average use and

perceived accuracy* From the F-test? with a computed

F-value of 9*59? there is a 0*003 probability that the

critical F-value will be Greater than the computed F-value

(Table 4)* Given the hidh probabilities indicated? and the

trend of increasind specific use as accuracy increases (see

Fidure 16)? it was determined that accuracy has an important

effect upon DSS specific usade*

Relevancy of output is the fourth important factor in

affectind DSS specific use* Of the 41 respondents

indicatind above average relevancy of output? 26 indicated

above average for both above average relevancy and specific

use (see Table 10)* For the below averade responses? of the

15 users with below average relevancy 14 responded with

80

below averade on both measures* For both above and below

averade relevancy of output? the probabilities are 0*63 and

0*93? respectively? that above and below averaGe specific

DSS use will occur* Additionally? the Graph of the mean

responses (Fidure 17) shows a denerally increasind

relationship between specific use and relevancy* The

indication is that relevancy of output affects the dedree of

specific use of a decision support system* With these hidh

conditional probabilities and the mean responses ^raphf and

with the computed F value of 31*69 resultind m

probability of 0*0001 that the critical F-value exceeds the

computed F-value? it was determined that relevancy of output

affects specific DSS use*

Finally? three of these factors—trainind? accuracsif

and relevancy—were analyzed to determine their combined

effect* The fourth factor? experience? was not included in

this part of the analysis? for the system desidner has no

control over this factor* (This lack of control will be

discussed adain in Chapter VI*) Recall that there were 29

and 26 respondents indicatind above averade and below

averade specific use? respectively* Of the 16 users that

indicated above average on all three factors of trainind?

accuracy? and relevancy? 10 of them also indicated above

averade specific DSS use (see Table ID* This results in a

probability of 0*63 that there will be above averade

speci fie use Given above averade trainind? accuracy and

81

relevancy* Also? of the 9 manaders respondind in the below

averade rande for trainind? accuracy? and relevancy? all 9

indicated below averade decision support system specific

use? divind a 100% probability* These results imply that

below average trainind? accuracy? and relevancy will result

in below averade specific use? the interaction of the three

factors appears Quite strond* When the mean responses of

specific use and the combined effect of trainind? accuracy?

and relevancy are draphed (Fidure 18)? there is additional

evidence of the effect of these factors on specific use*

Further support for this strond interaction comes from a

computed F-value of 27*92? the probability measure is an

extremely low 0*0001 (see Table 4)* The conclusion drawn

from the hidh F-value? the ^raph of the mean responses? and

the hidh conditional probabilities is that the combined

effect of the three factors—trainind? accurac^r and

relevancy—is very important in terms of their effect upon

specific DSS usade*

The combined effect of the factors of trainind?

accuracy? and relevancy also can be evaluated in droups of

two? i*e*? trainind and accuracy? trainind and relevancy?

and accuracy and relevancy* Fidures 19-21 show the draphs

of the mean responses? which offer support for the effect of

the pairs of factors on specific use* From the information

contained in Tables 12-14? the conditional probabilities

were calculated as follows:

82

1* TraininG and accuracy: 0*68 for above average?

0*75 for below averager

2* Trainind af»d relevancy: 0*76 for above averager

1*00 for below averager

3* Accuracy and relevancy: 0*63 for above averager

1*00 for below averade*

The F-values (Table 4) also are very hidh: 22*52 for

trainind and accuracy? 40*31 for trainind and relevancy? and

18*17 for accuracy and relevancy* Thus? there is further

evidence that these factors are important in their combined

effect on specific DSS usade*

This chapter presented the analysis of the data

obtained from this field study? in which accuracy and

trainind were determined to have an effect upon DSS deneral

use? while experience? trainind? accuracy? and relevancy of

output affected specific DSS use* In Chapter VI? some

deneral conclusions will be drawn concernind these results?

and some suddestions for future research will be presented*

83

T3ble 3

FrGGuenc':::! of Accuracy and General Urie

A c c IJ r a c y

General

Use

~x

4

I.

0

0

0

0

0

0

0

0

0

'J

0

0

n

0

0

4

n 0

A ! 1 I

n

0

0

0

Ji 0

J

4

1.1.

8

11

T o t a 1 13 •I -7 5

94

G e n e r a 1

U s e 4

3 c>

H c: c IJ rac •::>•

F id I . . I r e 1 J. •> Mean FvesPGriso?-^s o f A c e i j r a c y a f i d G e r i G r a 1 IJse

85

Table 4

Factors Affectind DSS Us e

Factor

Trainind

Accuracy

Trainind % Accuracy

Expo?r ience

Trainind

Accuracy

Relevancy

T r B i n i n d S Ace u r 3cy

T r a i n i n i^ S Fs'elevancy

fi^CCUVBC'r.i S

Relevancd

Trainind S Accur-acy x Relevanc'j

Type of Use

General

General

General

Specific

Specific

bpeciric

Specific

Specific

Specific

Specific

Specific

F-value

32*93

25*14

38*86

9*49

26*58

9*59

31.69

40*31

1 a * 17

O "7 O*^ A" / * .• A*..

Prob*

0*0001

0*0001

0*0001

0*0031

0*0001

0*0030

0*0001

0*0001

0*0001

0*0001

0*0001

86

Table 5

FreQuency of Trainin?^ ai"id Gene ra 1 Use

Trainind

General

use

4

5

6

7

1

4

AV.

1

1

0

0

3

4

1

1

0

1

0 « M * • • • f » KM* . — •

3

1

0

A H

1

0

1

0 . . « » * . . . « M —

4

9

0

3

4

0

3 ».. „ . « «« » .

5

1

1

0

3

4

3

3 .» .^ ». «. ...

6

0

0

0

1

A H

1

0

-7

0

0

0

0

1

3

1 __ __ „ —

11

•7

7

1'

3

11

Total 10 10 5 14 15 5 a .ji

q-7

(j e n e r a il

Use

6

3

3

1 T a i i"i J. i"i si

F i i S u r e 12 •> Mean F^esponaes of T ra in in : : ; ^ and G e n e r a l Use

Table 6

Distribution of General Use and Trainind S Accuracy Responses

88

Below Averade Averade

Above Averade

Gen(?ral

Use ii*

u

6

0

3

0

0

0

0

0

0

0

0

4

4

0 5

0 4

Totals 12 p

89

G e n e r a 1

Uae

IJ

4

B e 1 o w Averade A V e r.'? i e

H D o V e M' V

Fi'^ure 13* Mean Responsea oP Training ?x Accurac-and General Use

90

Table 7

FreQuency of Experience and Specific Use

Experience

0*5 1 1 * 5 3 4

S p e c i f i c

Use 4

nr

6

"7 /

3

•T

0

0

0

0

0 0

0

0

0

3

0

0

0

0

0

5

0

0

0

0

0

0

0

12

3

6

8

10

10

9

Total 10 S -J o •••> 63

91

T a b :i. e 7 (C o ri t i n u e d)

FreQuency of Experience and Specific Use

Experience

vJ • ,J 6 6 • U 7 7 '^t

3

Specific

Use

5

6

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

o

V

0

0

0

0

0

0

V

0

0

3

1

0

0

0

0

0 !

O 1 A H

. . H H H . H * . H . H H

9 * 5

f 0

0

0

0

0

0

1

12

.:i

10

10

9

Total 3 1 3 63

Qr*

o

^J

S p e c i f :i.c

Use

•7

3 4 10

E x p e r i e n c e

;i. S i i j r e 1 -4 * r iear' l F^e<:JP 1:5naea o f E>cPer i e i " i ce a r id S p e c i f :i.c: LJs s

Table 3

F reQuency of Trainii"id a n d S p e c :i. f i c U s e

Trainind

93

5

Spec It ic

Use

T

4

5

6

0

0

5

0

O

2 ! 0

0 !

1 !

I o

0 ! 2

1 ! 1

0 ! .j

0

0

0

0

0

0

0

4* A H

8

6

8

10

10

Total 10 10 14 1 '=; vJ 63

•J

bpecific

Use

94

5

T r a i n i n :•'.

FiN^ure 15* Mean Responses of Trainin:^ and Specific Use

Table 9

F"reQI..Iencw of Aceu racy and Specific Use

^ccuraca

95

4

Specific

Use

3

4

5

6

0

0

0

0

0

0

0

0

0

0

0

5

0

0

0

0

4

3

0

6

•7

b

4

•~)

0

0

0

o

0

3

-1

8

B

10

0

o

T o t a l 15 13 17 •7 sJ 6 3

96

o

Spec1 lie

Use 4

3

3 5 ~7 /

Accuracy

Fidure 16* Mean Responses of Accuracy and Specific Use

Table 10

FreQuency of Relevancy and Specific Use

Relevancy

97

3

Specific

Use

5

7

1 2 3 4 5 6 7

4 ! 2 ! 3 ! 0 ! 0 ! 2 ! 1

2 ! 1 ! 0 ! 1 ! 0 ! 2 ! 2

0 ! 0 ! 2 ! 1 ! 3 ! 0 ! 0

0 ! 0 ! 0 ! 3 ! 1 ! 3 ! 1

0 ! 0 ! 1 ! 1 ! 6 ! 2 ! 0

0 ! 0 ! 0 ! 1 ! 1 ! 6 ! 2

0 ! 0 ! 0 ! 0 ! 2 ! 2 ! 5

1 ' •!• A H

3

10

Total 6 3 a 7 13 17 11 63

s p e c i f i c

U s

A

98

R 0? 1. e V a f i c ••.{

F i : d I J r e 1 7 * M e a r i R e s p o n s e s o f Re 1 ev;:;r- ic 'J and S P I - ^ c i r i c Ua^^

Table 11

Distribution of Specific Use and Trainind ^ Accuracy f^ Relevancy Responses

99


Above Avera.de

Specific

Use

5

-7

7 ! 0 ! 2

2 ! 0 ! 1

0 ! 0 ! 0

0 ! 1 ! 3

0 ! 0 ! 2

0 ! 0 ! 5

0 ! 0 ! 3

Totals 16

http://Avera.de

"7

S p e c i f i c

Use

cr

4

-.r

100

B e 1 o w {^vevasie H V e T\

H D o V e

A V e T' a si e

Tr 'a: i .ninSA % A c ; c i j r a c y % F;e 1 evaric•::::

F" i £21J r e 1 3 * Mean R e s p o n s e s o f T r s i n i n : ^ S A c c u r a c : : : % F e I e V a n c y a n d S F e c :i. f i. c i.i a e

Table 12

Distribution of Specific Use and Trainind ?x Accuracy Responses

101

Below Averade AverasL e

Above Averade

Spec n. tie

Use

7

6

3

0

3

0

0

0

0

0

0

0

0

0 3

Totals 19

spec: i f L

Use

102

B e 1 o w Avera?.?,e A v e r a s}, e

i"i b o V e

Averss ie

T r s i ri :i. i"i a % A c c u r a c a

F i si u r e 19 ^ Mean R e s p o n s e s o f T r a i n i n : ^ % Accurac:b a fi d 3 p e c i f i e IJ a e

Table 13

Distribution of Specific Use and Trainind % Relevancy Responses

103


Above Averade

Specific

Use

6

"7

9

0

0

0

0

0

0

0

0

0

6

Totals 13 91 AH J.

104

Specific

Use

7

6

5

"X


Above Averade

Trainind S Relevancy

Fidure 20 * Meari ResPOnses of Tra inii"id ?J. Re 1 evancy a ri d S p e c i f i c U s e

Table 14

Distribution of Specific Use and Accuracy S Relevancy Responses

105


Above Averade

Q '."• /.•a •-< i j p e c i T i c

Use

3

4

5

6

•~i

0

0

A

0

0

0

0

0

0

3

4

-y

3

T o t a l s 9 l A

• e c i f • 1 c

4

106

Belcjw A V e r;;? 3 e A V e r ii? d e

A b o V e Aver ' a <;i e

I't c e IJ r a c a Z. R. e 1 e v;:; n c a

F i :r;! ij T' e 2 1 * Me a n R e a P o ri a e s o f A c: c i..i r a c a n d S p e c i f i a U ;i -a

& R e ]. e V a i"i c:

107

Table 15

C o n d i t :i. o n a 1 F" r o b a b i 1 i t i e s o f 01 her F a c t o v s

Factor

Yea rs of Edi..ication

E d u c ' 1 B a c k d r o u !"i d

L o lYi p a n y L x P e r i e n c e

F' o s i t i o n E x p e r i e n e e

C o d i"i i t i V e S Iv ».:< 1 e

F' a r t i c i p a t i o n

T o p M n d t * S u P P O r t

Response Time

Timeliness

F< e 1 e V a n c y

F o r m a t

Distance

Time in Use

General Use

Below Averade

0.31

0*36

0.46

0*41

0*45

0*46

0*45

0*47

0*42

A f^t"^

0*35

0*44

0.36

Above Averade

0 •> 5 0

0*33

0 * 4 :l.

0*33

0*59

0*47

0*46

0*43

0*40

0*46

A ' <"'

0*45

A -7 -7

Specific Use

Below Averade

0*: ••?. a

.i w

0*40

0*43

0*20

0 * 43

0*50

0*52

A " "

*

0 . *•-;• '•"1

Above A v e r a d e

0 * 5 0

0 * 3 3

0 * 5 4

•

0 * 4 7

0.>33

0 * 5 4

! 0 > 52

0 . 3 4

0 * 5 0

0>22 ! 0*51

0 * 3 2 ! 0>3-

•i; "denotes factor included as havin^^ an important effect

Table 16

108

Factors with Low F-values for General Us e

Factor !

Ade ._.— __.__ _.._, __ __ .„ ..„._ „ — _ .—_

Years of Education

Educ ' 1 Backd rourid

C o m p a n y E x p e r i e i"i c e —

F' o s i t i o r-i E x P e r i e n c e

C o d n i t i v e S t y 1 a

Participation - ~

T o p M ft d t * S u p p o r t

Response Time —

Timeliness —

Format

Distance

Time in Use _

F"

..H ~ H ™ — H

-value !

0*63 ! !

0*36 !

0*33 !

0*54 —

0 * 00

1 0 30

1*91

1 * 15

O -7 •.

0*31

1 * 44 — -

0 * 14

0*52 .._ _ _ ...

Prob*

0*4321

0*5529

0*3645

0*4636

0*9772

0*1346

(\ 1 -7 0 0 W f J* / AH AU

0*2334

0*1017

0*5794

0*2356

1 0.7144 . ._...»._ .>- — — ~—•— - —

! 0*4726 ! .„ — — -

Table 17

109

Factors with Low F-values for Specific U se

Factor

Ade

Y e a r s o i E d u c a t .i. o n

E d u c ' 1 B a c k d r o u n d

C o m p a n y E v. p e r i e n c e

Codnitive Style

Participation

TOP Mndt* Support

R" e s p o n s e T i m e

F-value

0*64

0 * 05

0*45

Timeliness

F'ormat

Distance

Time in Use

2*43

1*93

0*61

i 0-7 J. * A:. .•

2*93

0*06

0,51

1*3;

1*7.£

Prob •

0*4286

0*3226

0*5061

0*1256

0*1643

0*4369

0*2639

0*0392

0.3144

A .'* "7 7 -T

0,1823

0.1993

CHAPTER VI

GENERAL CONCLUSIONS AND SUGGESTIONS

FOR FUTURE RESEARCH

The research discussed in this dissertation was

desidned to analyze certain characteristics of the decision

maker? the implementation process? and the decision support

system that affect the extent of use of the decision support

system^ To do this? a research framework was developed? the

relevant literature was reviewed? and specific areas of

concern were identified* These areas of concern were

examined by collectinG data from lower level manaders in

eidht oil companies* The data was then analyzed usind

descriptive statistics and deneral linear models to

determine the important factors affectind DSS deneral and

specific use* The results of the data analysis were

presented in Chapter V* In this chapter? the deneral

implications for the system desidner will be discussed and

some areas for future research will be suddested*

Limitations of the Study

Before proceedind to the deneral implications? it is

important to reiterate that the results indicated are based

solely upon the data dathered in this study* Since the

systems analyzed had to meet the established criteria

110

Ill

redardinG lenGth of time in use? development time? and

number of users served? the results obtained have

limitations* These criteria narrowed the population in an

attempt to increase the similarities amond the systems

studied? and therefore? may have limited the

Generalizability of the results* Thus? even thoudh some of

the factors did not appear to be important in this study? it

does not mean that those factors are unimportant in all

cases* Because of the attempt to use similar systems within

the same industry? certain factors may not have varied as

much as if a wider variety of situations were analyzed*

There are a few additional points needind reiteration*

First? as in all cases where individual's perceptions are

measured? the assumption is that the individual knows his

true perceptions and is willind to experess them accurately*

Second? the eidht oil companies that participated in the

study were primarily treated as a population? for they

technically do not constitute a random sample* Finally?

efforts were made to Question a representation of all users

of the systems? even thoudh it was an individual in the

company who determined which users would participate*

General Implications

From the data Gathered in this study? it appears that

certain factors were important in their effect upon DSS

usaGe* In terms of General use? the factors of user

112

traininG durinG the implementation Process and the accuracy

of output appeared to be important* For specific use, the

apparently important factors were experience in the

manaGer's Present Position? user trainind? accuracy of

output? and relevancy of output* What does this imply for

the system desidner?

First? from the results of the analysis? it would be

difficult to conclude that as a broad classification?

characteristics of the decision maker are any more important

than characteristics of the implementation process or of the

decision support system* That is? in terms of both deneral

and specific DSS use? there was only one factor (experience)

from the characteristics of the decision maker? only one

factor (user trainind) from the characteristics of the

implementation process? and only two factors (accuracy and

relevancy) from the characteristics of the decision support

system that were determined to be important* Given that

only selected factors were found to be important in any one

characteristic? it would be Quite inappropriate to conclude

that system desiGn emphasis should be placed on any one of

them in its entirety* On the other hand? it is possible to

identify factors which deserve emphasis*

For instance? the only factor that appeared to be

important from the characteristics of the decision maker was

the number of years of experience in the present position?

in which it was only important for specific DSS use* Thus?

113

the implication is that manaders will use the DSS more for

specific? personally initiated reports the dreater the years

of experience in their Present Position* Since experience

is somethinG over which the system desiGner has no control?

he should? instead? emphasize the important factors in the

other characteristics*

That user traininG durinG the implementation process

appeared to be important in both deneral and specific use

indicates the apparent impact of trainind on usade* The

factors in the characteristic of the decision support system

that appeared to be important were accuracy and relevancy of

output* These are factors over which the system desidner

has some control* Since a system is successful with dreater

usade? the implication is that increased trainind? accuracy?

and relevancy of output will increase the system's success*

Therefore? they merit attention from the system desidner*

To this point? the discussion has primarily considered

the important factors in the study* However? the factors

that were not determined to be important from the analysis

also can provide added insidht* For example? in terms of

characteristics of the decision maker? many people adree

that a^e has an effect upon how an individual perceives

computer-based systems: younGer manaGers are beind broudht

UP in the "computer a^er' and? therefore? they are more

receptive to workind with computer-based systems* From the

data collected in this study? however? such a claim cannot

114

be supported* The same is true for an individual's

coGnitive style and formal educational trainind with

computers and comPuter-based systems* It is believed that

individuals with Greater analytic tendencies and dreater

experience with computers in their formal education would be

more receptive to their use as an employee* Adain? these

assumptions are not supported by this research*

In terms of the characteristics of the implementation

process? user involvement in the desidn of systems and top

manaGement support in the desidn and use of systems are

believed important* However? neither claim is supported by

the analysis of the data in this research* Likewise? the

importance of the decision support system characteristics of

timeliness of output? format? response time? lendth of time

the DSS has been in use? and distance traveled to interact

with the system were not found to be important in affectind

General or specific use* This doesn't suddest that the

system desidner need not be concerned with the factors

listed above which didn't appear to be important? rather?

the desidner should focus Greater attention on those factors

rated important*

It is useful to take a closer look at some of these

factors that didn't appear to be important? usinG Table 15

(paGel07)* For example? years of education didn't appear

to be important* However? the^conditional probabilities are

0*31 and 0*38 that there will be below averade deneral use

115

and specific use? respectively? diven below average years of

education* This implies that althoudh education didn't

appear to have overall importance? it does have an effect if

it is below averade* That is? a dreat deal of education

didn't contribute to hidh levels of DSS use? whereas lower

levels of education did appear to decrease DSS usade*

The conditional probability is 0*20 that? diven below

averade coGnitive style? there will be below averade

specific DSS use* This implies that althoudh codnitive

style didn't appear to have an overall effect? it did appear

to decrease usade if codnitive style was below averade*

Similarly? the conditional probability is 0*22 that there

will be below average specific DSS use diven below averade

distance traveled to interact with the system* The

implication is that a user may not necessarily use the

system more if there is a convenient distance to be traveled

to interact with the system? but that if the distance is

inconvenient? there will be a decrease in use* Thus?

further refinements are provided from the data analysis

concerninG the effect of education? codnitive style? and

distance traveled*

In conclusion? from the results of this study? it

appears that trainind and accuracy are important in

affectinG General DSS use? and experience in the present

position? user traininG? accuracy of output? and relevancy

of output are important in affectind specific DSS use*

116

Thus? the system desidner should stress these factors*

RememberinG that experience? over which the system desiGner

has no control? is the only factor from the characteristics

of the decision maker? the reader may conclude that the

results of this study imply that the decision maker (user)

is not important in the desiGn of manaGement information

systems? and that emphasis should be returned to the

technical aspects of the systems* This is not, the case*

One of the initial premises of this study was the importance

of the user? for the data datherind technioues were based

upon the user and his perceptions* Since the user is

unQuestionably important in systems desidn today? in a

behavioral context? it is important also to determine which

specific factors need to be emphasized* Therein lies the

sidnificance of this study? for it has determined factors

which affect the use of manadement information systems*

Suddestions for Future Research

This study has determined certain factors which are

important in the desidn of successful manadement information

systems* Still? the need for further investidation in other

areas is needed if researchers? practitioners? and users are

to fully understand what makes one information system a

success and another a failure* Amond the Questions

reQuirind future research are:

1* How is the use of a decision support system

117

affected by a chande in the decision makinG

environment? Do these chanGes affect all

users of the system alike? or is the effect

dependent upon the precise factors in the

environment?

2* Do the factors of importance determined by

this research have the same dedree of impor

tance in industries besides the oil industry?

and at other manadement levels besides the

supervisory level? The investidation of the

factors in different ordanizational and

manaderial settinds may provide some inter

estind results*

3* What differences exist between users' percep

tions and system desidners' perceptions of

the characteristics of the implementation

process and the decision support system?

What contributes to these differences? and

how does one close the ^ap between these

differences?

4* What differences exist between a user's percep

tion of an implementation process or decision

support system and the actual situation? That

is? if perceptions are measured usind Question

naires? and actual situations are measured

usind observations and computer monitorind

118

devices? are there differences between the

actual and perceptions? What types of

manadement practices caused these differ

ences? if they exist?

Answers to these Questions will continue to provide

insidht into the desidn and development of successful

manaGement information systems*

LIST OF REFERENCES

Ackoff? R*A* ManaGement misinformation systems* Manadement

Science? 1967? lA_f 147-158*

Adams? C* R* How manaGement users view information systems*

Decision Sciences? 1975? 6? 337-345*

Aldrich? H*E* OrGanizational boundaries and inter-

ordanizational conflict* Human Relations? 1971? 24?

279-293*

Alter? S* L* How effective menders use information systems*

Harvard Business Review? November-December 1976f PP*

97-104*

Alter? S* L* Why is man-comPuter interaction important for

decision support systems* Interfaces? 1977? 7j 109-115*

Anthony? R*N* Plannind and control systems: a framework for

analysis* Cambridde? MA: Harvard University Press?

1965*

Ardyris? C* On the effectiveness of research and develop

ment ordanizations* American Scientist? 1968? 56_?

344-355*

Ardyris? C* ManaGement information systems: the challende

to rationality and emotionality* Manadement Science?

1971? 17? B275-B291*

Bariff? M*L*? S Lusk? E*J* Codnitive and Personality tests

for the desidn of manadement information systems*

119

120

Manadement Science? 1977? 23? 820-827*

Barkin? S* An investidation into some factors affectinG

information system utilization* Unpublished doctoral

dissertation. University of Minnesota? 1974*

Benbasat? I*, & Schroeder, R.G* An experimental investida

tion of some MIS desidn variables* MIS Quarterly?

1977? 1, 21-28*

Bennis? W*G* ChanGinG orGanizations* New York: McGraw-Hill,

1966*

Bostrom? R*P*? g Heinen? J*S* MIS problems and failures:

a socio-technical perspective (MIS Research Center

WorkinG Paper 76-07)* Unpublished manuscript? Univer

sity of Minnesota? 1976*

Burns, T*? S Stalker? G*M* The manadement of innovation*

Chicado: Quadrandle Books? 1961*

Cheney? P*H* OrGanizational characteristics and information

systems: an investiGation* Unpublished doctoral

dissertation? University of Minnesota? 1977*

Chervany? N*L*? Dickson? G*W*? & Kozar? K*A* An experimental

GaminG framework for investidatind the influence of

MIS's on decision effectiveness (MIS Research Center

WorkinG Paper 71-12)* Unpublished manuscript? Univei—

sity of Minnesota? 1972*

Chervany? N*L*? & Sauter? R*F* Analysis and desidn of

computer-based manadement information systems: an

evaluation of risk analysis decision aids (MIS

121

Research Center WorkinG Paper 76-05)* Unpublished

manuscript. University of Minnesota? 1976*

Chervany? N*L*? I Dickson? G*W* On the validity of the

analytic-heuristic instrument in the Minnesota

experiments* ManaGement Science? 1978? 24? 1091-1092*

Child? J* OrGanizational structure? environment and perfor

mance: the role of strateGic choice* Sociolody? 1972?

_6^ 2-21*

Daft? R*L*? X Macintosh? N*B* A new approach to the desidn

and use of MIS* California Manadement Review? 1978?

3? 82-92*

Davis? G*B* Manadement information systems: conceptual

foundations? structure and development* New York:

McGraw-Hill? 1974*

Dermer? J*D* Codnitive characteristics and the perceived

importance of information* The Accountind Review?

July 1973? pp* 511-519*

Dickson? G*W*? & Simmons? J*K* The behavioral side of MIS*

Business Horizons? 1970? 3 ? 59-71*

Dickson, G*W*, S Wynne? B*E* Manaders and man-machine

systems (MIS Research Center Workind Paper 72-04)*

Unpublished manuscript? University of Minnesota?

1973*

Dickson? G*W*? Senn, J*A*? S Chervany? N*L* Research in

manadement information systems: the Minnesota experi

ments* Manadement Science? 1977? ^ ? 913-923*

122

Doktor? R*H*? % Hamilton? W*F* Codnitive style and the

acceptance of manaGement science recommendations*

ManaGement Science? 1973? 19? 884-894*

Duncan? R*B* Characteristics of OrGanizational environments

and perceived environmental uncertainty* Administra

tive Science Quarterly? 1972? ^ ? 313-327*

Ein-Dor? P*? % SeGev? E* OrGanizational context and the

success of manaGement information systems* Manade

ment Science? 1978? £4? 1064-1076*

Emery? F*E*? & Trist? E*L* The causal texture of ordaniza

tional environments* Human Relations? 1965? 18?

21-32*

Emery? F*E* The next thirty years: concepts? methods? and

anticipation* Human Relations? 1967? 20_? 199-237*

Federal Trade Commission* Quarterly financial report*

Washindton? D*C*: U*S* Government Printind Office?

1974*

Gerrity? T*P* The d'esidn of man-machine decision systems*

Unpublished doctoral dissertation? Sloan School of

Manadement? 1970*

Gershefski? G*W*? 8 Harvey? A* Corporate models—the state

of the art* Manadement Science? 1970? 16^ B303-B321*

Ghyman? K*? S Kind? W*R* Desidn of a stratedic Plannind

m anadement information system* Qmeda? 1976? j4_?

595-607*

Gindras? L* The PsycholoGy of users and desidners of infor

123

mation systems: a field study (Information Systems

Workind Paper 15-75)* Unpublished manuscript? UCLA?

1975*

GinzberG, M*J. A detailed look at implementation research

(Sloan Workind Paper 753-4)* Unpublished manuscript?

Massachusetts Institute of Technolody? 1974*

GinzberG? M*J* Improvind MIS project selection (Research

WorkinG Paper 135A)* Unpublished manuscript?

Columbia University? 1978*

GinzberG? M*J* Steps towards more effective implementation

of MS and MIS* Interfaces? 1978? 8_? 57-63*

Glassman? R* Behavioral implications in procedures of

manaGement systems analysis* Data Manadement?

December 1972? PP* 21-24*

Grudnitski? G*M* A methodolody for the desidn of decision

maker oriented information systems* Unpublished

doctoral dissertation? University of Massachusetts?

1975*

Guthrie? A* Attitudes of middle manaders towards manadement

information systems* Unpublished doctoral disserta

tion? University of Washindton? 1971*

Hedberd? B*? S Jonsson? S* Desidnind semi-confusind

systems for orGanizations in chandind environments*

Paper presented at the 8th Annual Conference of the

American Institute for Decision Sciences? San

Francisco, November 1976*

124

Huysmans, J*H* The effectiveness of the codnitive style

constraint in implementind operations research Pro

posals* Manadement Science? 1970? 17? 92-104*

Huysmans, J*H* The implementation of operations research*

New York: John Wiley? 1970*

Jenkins? A*M* An investidation of some MIS desidn variables

and decision makind performance: a simulation experi

ment* Unpublished doctoral dissertation? University

of Minnesota? 1977*

Katz? D*? % Kahn? R*L* The social psycholody of ordaniza

tions* New York: John Wiley? 1966*

Keen? P*G*W* Interactive computer systems for manaders: a

modest proposal* Sloan Manadement Review? Fall 1976?

pp* 1-17*

Kind? W*R*? S Cleland? D*I* The desidn of manadement infor

mation systems: an information analysis approach*

Manadement Science? 1975? 22? 286-297*

Knidht, K*E*, S McDaniel, R*R* Ordanizations: an informa

tion systems perspective* Belmont, CA: Wadsworth?

1979*

Kyoman, J* Behavioral considerations in MIS chande*

Unpublished doctoral dissertaion? Georde Washindton

University? 1976*

Lawrence? P*R* How to deal with resistance to chande*

Harvard Business Review? 1954? 32? 55-69*

Lawrence? P*R*? S Lorsch? J*W*? Ordanizations and environ-

12:

ment: manadinG differentiation and intedration*

Homewood? IL: Irwin? 1967*

Lucas? H*C* Performance and the use of an information

system^ Manadement Science? 1975? 21? 908-919*

Lucas? H*C* Why information systems fail* New York:

Columbia University Press? 1975^

Mason? R*0*? % Mitroff? I*I» A prodram for research in

manadement information systems* Manadement Science?

1973? £9_? 475-487*

McGhee? W*? Shields? M*D*? X Birnberd? J*G* The effects of

personality on a subject's information processind*

The Accountind Review? 1978? 53? 681-697*

McKinsey and Company* Unlockind the computer's profit

potential: a research report to manadement* The

McKinsey Quarterly? Fall 1968? PP* 12-25*

McLean? E*R*, S Soden, J*V* Stratedic plannind for MIS—

a conceptual framework* 1976 National Computer

Conference Proceedinds? 1976? 45? 425-432*

Meador? C*L*? S Ness? D*N* Decision support systems: an

application to corporate plannind* Sloan Manade-

ment Review? Winter 1974? PP* 51-68*

Meldman? J*A* A new technieue for modelind the behavior of

man-machine information sytems* Sloan Manadement

Review? Sprind 1977? PP* 29-46*

Powers? R*F*? & Dickson? G*W* MIS project manadement:

myths? opinions and reality* California Manadement

126

Review? 1973? 1^, 147-156*

Roberts, E*B* Stratedies for effective implementation

of complex corporate models* Interfaces? 1977?

J^ 26-33*

Robey? D*, % Zeller, R*L* Factors affectind the success

and failure of an information system product Quality*

Interfaces? 1978? 8? 70-75*

San MiGuel? J*G* Information processind in manaderial

decision makind: a preliminary study* Omeda? 1976?

_4_? 577-582*

Sayles? L*R* Manaderial behavior: administration in

complex ordanizations* New York: McGraw-Hill? 1964*

Schewe? C*D* The manadement information system user: an

exploratory behavioral analysis* Academy of Manade

ment Journal? 1976? 19_? 577-590*

Schultz? R*L*? & Slevin? D*P* Implementind operations

research/manadement science* New York: American

Elsevier Publishind? 1975*

Scott-Morton, M*S* Computer driven visual display devices:

their impact on the manadement decision process*

Unpublished doctoral dissertation. Harvard University?

1967*

Senn, J*A* Enhancind the user interface: a research problem

in computer-based information systems* TIMS/QRSA

Bulletin, May 1978? 14-25*

Simon? H*A* The new science of manadement decision* New

127

York: Harper S Row? 1960*

Simon? H*A* Motivational and emotional controls of codni-

tion* Psycholodical Review? 1967? 74? 29-39*

Snider, J*G*? S OsGood? C*E* The semantic differential

techniQue* ChicaGo: Aldine Publishind? 1969*

SpraGue, R*H*, S Watson, H*J* MIS concepts—part I*

Journal of Systems Manadement, January 1975? PP* 34-37,

SpraGue? R*H*, & Watson? H*J* A decision support system for

banks* Omeda? 1976? 4? 657-671*

Srinivasan? C*A*? % Dascher? P*E* Information system's

desidn* user psycholodical considerations* MSU

Business Topics? Winter 1976? PP* 51-57*

Srinivasan? C*A*? S Schoenfield? H*M* Some problems and

prospects in desidn and development of corporate-

wide information systems* Manadement International

Review? 1978? 1 ? 15-31*

Stabell, C*B* Intedrative complexity of information

environmental perception and information use: an

empirical investidation* Ordanizational Behavior and

Human Performance, 1978? 22_? 116-142*

Swanson? E*B* Manadement information systems: appreciation

and involvement* Manadement Science? 1974? 2£? 178-

188*

Thompson? J*D* Ordanizations in action* New York: McGraw-

Hill? 1967*

U*S* Department of Labor* Bureau of Labor Statistics*

128

Employment and earninds* Washindton? D*C*: U*S*

Government Printind Office? 1978*

Van Horn, R*L* Empirical studies of manadement information

systems* Data Base? 1973? 5? 172-180*

Vasarhelyi, M*A* Man-machine plannind systems: a codnitive

style examination of interactive decision makind*

Journal of Accountind Research? Sprind 1977? PP* 138-

153*

Wynne? B*E*? % Dickson? G*W* Experienced manader's perfor

mance in experimental man-machine decision system

simulation* Academy of Manadement Journal? 1975? 18?

25-40*

129

APPENDIX A

DATA GATHERING INSTRUMENT

130

This Questionnaire is part of a research project beind

conducted at Texas Tech University redardind the use of

information systems*

Your responses will be strictly confidential* No one

in your company will see your individual responses*

Please answer all Questions* There are no "trick"

Questions? and there are no ridht or wrond answers*

Thank you in advance for your time and cooperation*

131

2*

Section I

1* AGe: (check one) under 20 20 - 29

30 40

39 49

50 - 59 60 and over

Education: (check the hiGhest level applicable and • enter number of years and specialization)

3*

4*

xJ *

6*

7*

.hiGh school diploma

.some professional? vocational or technical traininG .some colleGe experience .professional? vocational or technical dedree .collede dedree .some draduate work .Masters or hidher dedree

No* of Yrs* Subject

Specialization

To what extent did your educational trainind provide you with knowledde about computers? computer-based information systems and/or electronic data processind?

not at all to a very small extent to a moderate extent to a d©reat extent to a very dreat extent

How would you classify your level in the ordanization? top manadement middle manadement supervisor other

How lond have you been workind in your present company? years

How lond have you years

been workind in your present position?

My overall attitude when workind with computer-based systems is:

very nedative somewhat nedative indifferent somewhat positive very positive

132

Section II

The followind are some Questions desidned to show how you approach work-related Problems* The ar wer you choose for any item is neither ridht nor wrond* A simPly helPs to point out the way you study problems*

Listed below are a number of statements* Each represents a Personal opinion about various activities or events* You will Probably adree with some and disadree with others*

Read each item carefully* Then indicate the extent to which you a^ree or disadree by circlind the appropriate response as follows:

If you strondly adree? circle 1* If you slidhtly a^reer circle 2* If you slidhtly disadree? circle 3* If you strondly disadree? circle 4*

If you find that the responses do not adeauately indicate your personal opinion? use the one which come closest to the way you feel*

Please Give your opinion on every statement*

AGree Adree Disadree Disadree strondly sliGhtly slidhtly strondly

3 4 I am at my best when followind a plan*

3 4 When writind a report? I Just sit down a start

/ writind*

3 4 "Scheduled" has more appeal to me than "unplanned*"

3 4 Where I live? I seldom keep my letters and other personal thinds neatly arranded & filed*

^rf

133

AGree AGree DisaGree DisaGree StronGly SliGhtly SliGhtly StronGly

\ I am at my best when dealind with the unexpected*

\ The idea of makind a list of what I should det done over the weekend depresses me*

\ When there is an unfamiliar special Job to be done? I like to find out what is necessary as I do alond rather than attemptind to ordanize it carefully before startind*

4 If asked a few days before a holiday what you were doind to do that day? you would be able to tell pretty well*

4 In my daily work I usually plan so that I am not pressured for time in meetind a deadline*

4 If asked a few days before a holiday what you were doind to do that day? you would have to wait and see*

4 Followind a schedule cramps me*

4 The idea of makind a list of what I should det done over the weekend appeals to me *

4 I am more a "planner' than a "doer*"

134

Adree AGree DisaGree DisaGree StronGly SliGhtly sliGhtly stronGly

2 3 4 1 like to arrande my appointments and parties some distance ahead*

2 3 4 When startind a bid project that is due in a week? I like to list the thinds to be done and the order of doind them*

2 3 4 1 can more easily cope with set routine thatn constant chande*

2 3 ' 4 I am a spontaneous person*

135

Section III

^'l^^se answer the followind Questions about the systems listed* Remember? there are no ridht or wrond answers--this^is not a test* We are interested in your opinions

On the Questions below? Please circle the answer which best corresponds to your opinion* For example? if the Question was:

How hot is it here today?

' very cold 1 2 3 4 5 6 7 very hot

Then if you thoudht it was: very cold? you should circle 1* cold? you should circle 2* cool? you should circle 3* indifferent? you should circle 4* warm? you should circle 5* hot? you should circle 6* very hot? you should circle 7*

The followind Questions refer to the system*

1* What was the deGree of your own personal active partici pation throuGhout the development of this system?

Very little A dreat deal of participation 1 2 3 4 5 6 7 participation

2* The Quality of the trainind you received when this system was installed was:

Very poor 1 2 3 4 5 6 7 Very dood

3* In implementind this system? top manaGement was:

Not supportive ^ery

at all 1 2 3 4 5 6 7 supportive

4* When I interact with this system? the reponse time is:

Very slow 1 2 3 4 5 6 7 Very fast

5* My impression is that the output of this system is:

Inaccurate 1 2 3 4 5 6 7 Very accurate

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Not timely

Irrelevant to the user

3 4 6 7

1 2 3 4 5 6 7

6* The output of this system has been:

Generally formatted for 1 2 3 4 5 6 7 all users

Very timely

Very relevant to the user

Personally formatted by each user

7* To obtain routinely denerated reports? I use the system:

Very little 1 2 3 4 6 7 A dreat deal

8* To obtain special reports initiated Just by me? I use the system:

Very little 1 2 3 4 5 6 7 A dreat deal

9* To interact with this system? I have to travel:

An inconvenient distance 1 2 3 4 5 6 7

A convenient distance

Please explain how and where you interact with this system*

10* To interact with this system? I use: (check one)

punched cards a terminal

11* How lond have you used this system?

less than 6 months

12 months

1 - 1 1/2 years

1 1/2 - 2 years

2 1/2 years

2 1/2 - 3 years

more than 3 years

12* My overall reaction to completind this Questionnaire is:

Very nedative 1 2 3 4 5 6 7 Very Positive

i^d

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APPENDIX B

LETTER REQUESTING PARTICIPATION IN THE STUDY

138

Dear

The Collede of Business Administration at Texas Tech University is conductind research in the use of computer-based information systems in the oil industry* We would like your company to participate*

Briefly? we are interested in systems that have been in use within the past six months to three years? and that provide information from the computer to at least five operative manaders* Typical systems midht include inventory control systems? marketind intellidence systems? or production control systems*

To collect data from these manaders? we will ask them to complete a 5-10 minute Questionnaire* To minimize the inconvenience to your operations? Bill Fuerst will personally administer the Questionnaire at your convenience* Once the data has been dathered and analyzed? you will receive the results indicatind some of the important system desidn characteristics affectind usade of an information system*

If you would be willind to participate in this research or in learnind more about it? and have a system or systems that meet the above description? please complete the enclosed one-pade Questionnaire and return it to us in the stamped? addressed envelope* We will then contact you by telephone*

Thank you for your cooperation*

Sincerely?

Carl H* Stem Dean

Paul H* Cheney Assistant Professor Information systems/ Quantitative Sciences

William L* Fuerst Information Systems/ Quantitative sciences

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Candidate Systems

1* Briefly describe the system*

^^ system!^ "" '"''' ' °^ "• '"'' reeuired to develop the

3* How lond has the system been in use?

4* Was a Project team approach used in develoPind the system?

5* Estimate the number of "primary users' (i*e*? People who receive reports from the system)*

6* At what level of manadement is the system directed?

TOP manadement Middle manadement Supervisory manadement

7* Please indicate your name and address below*

Copyright by UILLIAM LEE FUERST 1979

Documents

Transcript of Copyright by UILLIAM LEE FUERST 1979