Antecedents of Information and System Quality

8/9/2019 Antecedents of Information and System Quality

1/38

Antecedents of Information and System Quality: An Empirical Examination within the

Context of Data WarehousingAuthor(s): R. Ryan Nelson, Peter A. Todd and Barbara H. WixomReviewed work(s):Source: Journal of Management Information Systems, Vol. 21, No. 4 (Spring, 2005), pp. 199-235Published by: M.E. Sharpe, Inc.Stable URL: http://www.jstor.org/stable/40398737.

Accessed: 04/09/2012 22:05

Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at.http://www.jstor.org/page/info/about/policies/terms.jsp

.JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of

content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms

of scholarship. For more information about JSTOR, please contact [email protected].

.

M.E. Sharpe, Inc.is collaborating with JSTOR to digitize, preserve and extend access toJournal of

Management Information Systems.

http://www.jstor.org
http://www.jstor.org/action/showPublisher?publisherCode=meshttp://www.jstor.org/stable/40398737?origin=JSTOR-pdfhttp://www.jstor.org/page/info/about/policies/terms.jsphttp://www.jstor.org/page/info/about/policies/terms.jsphttp://www.jstor.org/stable/40398737?origin=JSTOR-pdfhttp://www.jstor.org/action/showPublisher?publisherCode=mes


2/38

Antecedents

f

nformationnd

System

Quality:AnEmpiricalExamination

Within

heContext

fData

Warehousing

R. RYAN

NELSON,

PETER A.

TODD,

AND

BARBARAH.

WIXOM

R. Ryan

Nelson

is a

Professornd

heDirector

f heCenter or

he

Management

f

Information

echnology

t

theMclntire chool

of Commerce

t the

University

f

Virginia.

is research

nterests

re

n the reasof

technology

doption

nd

nnova-

tion,

nformation

echnology

uman

apital,

nd

project

management.

is research

hasbeenpublishedn suchournals s JournalfManagementnformationystems,

MIS

Quarterly,

nd

Communications

f

he

ACM.

Peter A.

Todd

is the

Chesapeake

nd

Potomac

rofessornd

AssociateDean

for

Graduate

rograms

t

theMclntire

chool

of

Commerce

t the

University

f

Vir-

ginia.

His research

nterests

re n the

reas

of

technologydoption

nd

nnovation,

the ole f

T

in

decision-making

nd

human-computer

nteraction.

e has

published

in a

variety

f

ournals

ncluding

IS

Quarterly

nd

nformation

ystems

esearch.

He

currently

erves s

a senior

ditor

orMIS

Quarterly.

Barbara

H.

Wixom

s an

Associate

rofessor

fCommerce

tthe

Mclntire

chool

f

CommercettheUniversityfVirginia.he is a Fellow oftheDataWarehousing

Institute

or

er

ata

warehousing

esearch,

ssociate

ditor

or heJournal

f

Busi-

ness

ntelligence,

nd

two-time

inner fthe

ociety

or

nformation

anagement

PaperCompetition.

rofessor

ixom

eaches

raduate

nd

undergraduate

lasses

n

data

warehousing,

ata

management,

nd

T

strategy,

nd

her esearch ocuses

n data

warehousing

enefits

nd

use.

She

has

published

n

ournals

hat

nclude

ournal

f

Management

nformation

ystems,

IS

Quarterly,

nd

nformation

ystems

esearch.

Abstract:

Understanding

he uccessful

doption

f nformation

echnology

s

argely

based

upon

understanding

he

inkages

mong uality,

atisfaction,

nd

usage.

Al-

though

he

atisfaction

nd

usage

constructs

avebeen

well

studied

n

the

nforma-

tion ystemsiterature,here asbeen nlyimitedttentiono nformationnd ystem

quality

ver

the

past

decade.

To address

his

hortcoming,

e

developed

model

consisting

f

nine undamental

eterminants

f

quality

n an nformation

echnology

context,

our

nder he

rubric

f nformation

uality

the

output

f an information

system)

nd

five hat

escribe

ystem

uality

the

nformation

rocessing

ystem

e-

quired

o

produce

he

utput).

Wethen

mpirically

xamined

he

ptness

four

model

using

sample

f465

data

warehouse

sers

rom even

different

rganizations

hat

employed

eport-based,

uery-based,

nd

analytical

usiness

ntelligence

ools.

The

results

uggest

hat ur

determinants

re

ndeed

redictive

f

overall

nformation

nd

system uality

n

data

warehouse

nvironments,

nd

hat ur

model

trikes

balance

between

omprehensiveness

nd

parsimony.

e

conclude

with discussion

f the

implicationsor oth heorynd he evelopmentnd mplementationf nformation

technology

pplications

n

practice.

Journal

fManagement

nformation

ystemsSpring

005,

Vol.

21,

No.

4,

pp.

199-235.

2005 M.E.

Sharpe,

nc.

0742-1222

/

2005

$9.50

+

0.00.


3/38

200

NELSON, TODD,

AND

WIXOM

Key

words

and

phrases: business

ntelligence

oftware,

ata

warehousing,

nfor-

mation

uality,

nformation

ystems

uccess,

ystem uality.

Quality

has evolved

into

a core

business concept with

multidisciplinaryp-

plications

nd

dramatic

mplications

or usiness alue.When

manufacturing

irms

were

orced o cometo terms ith

he

uality hallenge

fthe

arly

980s,

he otal

qualitymanagement

TQM)

movement ad a

profound

ffect n

product

evelop-

ment

23,

25,

38].

Since that

ime,

ther

isciplines,

uch

s

marketing

nd human

resource

management,

ave

engaged

n

quality ursuits;

he

former

iting

vidence

thathe ualityf ustomerervice s often s importants the ualityf he roduct

[87],

nd he

atter

ecognizinguality

fwork ife s a

key

river

f

mployee

eten-

tion

61].

In

addition,

verallmeasures

f

quality,

uch as those

aptured

n the

Baldridge

wards nd BalancedScorecard

ractices,

ave

proliferated1

57].

Some

researchersssert hat

uality

f

products

nd services s

the

ingle

most

mportant

determinantf

business'

ong-term

uccess

3,

15].

Despite

ncreasing

ttention

o

the

uality

onstruct

n

thebroader

usiness itera-

ture,

ttention

o nformationnd

system uality

as

become

ess centraln recent

years.

nstead,

n

an efforto

understandsers' eactionso nformation

echnology

(IT),

researchersavefocused n

perceptions

elated o T

use,predominantly

ase

ofuseand

usefulness,

long

with therelated actors

e.g.,

21,77]).

Although

uch

perceptions

avebeen

mportant

n

explaining

T

usage,

hey

re

relatively

bstract

and,

s a

result,

rovide

imited

uidance

or

ystem esigners

31, 75].

Orlikowski

and

acono

59]

have

noted

hat

uch T

research,

hich

mploys "proxy

iew"

of

technology,

as ost ts

connectiono the

field's ore

ubject

matter the

T

artifact

itself.We

believe hat

dentifying

he imensions

f

the

T artifacthat

hape

uality

can

provide

his

onnection.

Thus,

he

primary

urpose

f

this esearch

s to

dentify

set of

antecedentshat

simultaneously

efine he

nature f

the

T

artifactnd

drive nformationnd

system

quality. uilding nthefindingseportednWixom ndTodd 84],wewillempiri-

cally

test he

uitability

f

these

determinantss aids in

the

prediction

nd under-

standing

f

quality

within

n T

context.

second

esearch

bjective

s

to

explore

he

area

of

data

warehousing,

pecifically

hree

opular

usiness

ntelligence

pplica-

tions

predefined

eports,

d hoc

queries,

nd

nalytical

ools.We

hope

o

provide

T

managers

ith

better

nderstanding

f hese

ontemporary

ools o

help

hem reate

IT

infrastructureshat

ffectively

upport

rganizational

ecision-making.

The

Quality

onstruct

There are

multiple

perspectives

on

quality

n

the

business

iterature.n

a com-

prehensive

eview,

eeves nd

Bednar

65]

dentify

our

ominant

iews f

quality:


4/38

ANTECEDENTS OF INFORMATION

AND

SYSTEM

QUALITY

20

1

quality

s

excellence,

uality

s

value,

uality

s

conformance ith

pecifications,

and

quality

s

meeting xpectations.

he excellence iew

suggests

hat

uality

s

assessed

n some bsolute

tandard.

he

value

perspective

efines

hat otion

o

ug-

gest

hathe tandardsf xcellence eed obe assessed elativeo he osts f chieving

them.

he conformance

iewfurther

ystematizes

hese

deas to

suggest

hat

uality

be

assessed

n terms f

a

consistent

nd

quantifiable

elivery

f

value relative o a

specific

esign

deal.

Finally,

henotion f

quality

s

meetingxpectationsuggests

that

uality

s defined

y

conformance

o customer

xpectations

hat

may

relate o

excellence, alue,

nd other ttributes

hat re salient o consumers

n

shaping

heir

perceptions

f

quality.

Reeves nd

Bednar

65]

note

hat

uality

ssessments

elative o

expectationsep-

resent he

most

pervasive

erspective

n

quality,

ith he

critical

xemplar

eing

service uality. eithamlt al. [88]define ervice uality s thedegree o which

service

xceeds

customer

xpectations.

urther,

hey mpiricallydentify

set of

service

ttributes

hat

ollectively

etermineustomer

xpectations

bout ervice

quality;

hese

ervice

ttributes

nclude

esponsiveness,

eliability,

ssurance,

angi-

bility,

nd

empathy.

onsistent

ith he

notion hat

alient eliefs bout

bjects

nd

behaviors

hape

roader

ttitudes

26],

hese

ive actors

avebeen

mpirically

ested

across

variety

f

ettings

oestablish

heir verall

tility

n

shaping

ervice

uality.

In the

nformation

ystems

IS)

literature,

uality

as been

frequently

eferenced,

but

relatively

ll-defined,

onstruct

e.g.,

4,

8, 41, 51,

71]).

Furthermore,

ith he

exception

f

T service

uality

e.g.,

37,

40,

63]),

the

tudy

f

quality

s a

key epen-

dent ariable as been argelyupplantedyusage nthe S literature.hefollowing

section

rovides

review

frelevant

iterature

hile

eveloping

he heoreticalon-

text

or he

uality

f

S.

The

Theoretical

ontext

or

Quality

Some

IT

frameworks

ave

been

created

o

place

quality

nto broader

heoretical

context.

uilding

n

concepts

rom

hannon

ndWeaver

69]

andMason

52],

DeLone

and

McLean

22]

identify

nformation

nd

system uality

s the

key

nitial nteced-

entsfor S success.Extendinghesenotions,eddon 67] developed respecified

model f S

success,

which hows

hat

nformation

uality

nd

ystem uality

ointly

influence

erceptual

measures

f

system

enefit,

epresented

y

perceived

seful-

ness

nd

user atisfaction

which

eddon

67]

definess

satisfaction

ith

se).

These,

in

turn,

nfluence

xpectations

bout

hebenefits

f future

se,

and

subsequently,

actual

usage

of

IT,

which

an have

a series

f

positive

r

negative

rganizational

consequences

46,

50].

Related

fforts

ave focused

n

empirically

ssessing

he

oleof nformation

nd

system

uality

s antecedents

f

atisfaction

nd

usage

na

variety

f

ettings

64,

68,

70, 84,

85].

n

general,

uch

tudies

reat

uality

t holistic

evel.

However,

t s clear

that ualityonstructsremultidimensional42,64,67].Moregenerally,oodhue

[31]

notes

hat

ser valuations

f S attributes

an

provide

basisfor he etermina-

tion f S

value.


5/38

202

NELSON, TODD,

AND WIXOM

One

criticalssue s

determining

hat onstitutes

"good"

set of S

dimensions.

We offerour

ey oals

for he et fdeterminants

hat

hape uality.

ollectively,

he

dimensionshould:

1 be

complete

in

the ense

f

xplaining

verall

nformationnd

ystemuality);

2. be

relativelyarsimonious;

3. enhance

nderstanding

f themultifaceted

ature f

nformation

nd

system

quality;

nd

4. be

actionable,

n the

ense

hat

he imensions

an be influenced

hrough

ys-

tem

esign

r

managerial

ntervention.

Using

hese our

oals

as a

guide,

we willturn o

a

derivation

f

thedimensions

f

informationnd

ystemuality

nd o

the

ntegration

f

hose nto

model f

quality.

Information

uality

Researchersave ntroduced

variety

fdefinitions

or nformation

or

data)

uality.

In

general,

he efinitions

ake ither n ntrinsicr

contextual

iewof

nformation

quality.

he

ntrinsiciew

onsidershe

roperties

f nformation

argely

n solation

from

specific

ser,

ask,

r

pplication.

hus,

he

ntrinsiciew eflects

measure

f

agreement

etween

he

datavalues

presented

y

n

S and

the ctual

alues he

data

represents

n

the ealworld

47,60],

the

degree

o which atavalues

renot

naccu-

rate, utdated,

nd

nconsistent

48],

nd he

ccuracy

f nformation

enerated

y

n

IS [31,67, 82]. Althoughhis s an importanterspective,t s somewhatimited

because t treats nformations

an

object

hat an be

assessed n isolation

f the

context

o

which t s

applied.

hus,

ntrinsic

uality

s

a

necessary,

utnot

ufficient,

conditiono determine

nformation

uality.

A

context-basediew

extends henotion f

nformation

uality,uggesting

hat

t

needs obe

defined elative o the

user

f

the

nformation,

he ask

eing ompleted,

and he

pplication

eing mployed

47,

0].

From his

erspective,

nformation

uality

is

assessed

y

he

egree

o which

t

s

helpful

n

completing

particular

ask

27,

45,

62, 72,

74, 81,

82].

For

example,

his

might

e

assessed

bstractly

n

terms f the

usefulnessf

the nformationn

aiding ecision-making.

he

context

iew

xpandsthedimensionsf nformation

uality eyond

ccuracy

o nclude imensionsuch

as

relevance,

ompleteness,

nd

urrency

f

he

nformation

hat

hape erceptions

f

quality

n

the ontext

fuse

[82].

In

addition

o

ntrinsicnd

context-based

imensionsf

nformation

uality,

Wang

and

Strong

82]

also

suggest

hat

heres a

representational

imension.

he

roleof

format

n

nformation

rocessing

nd

decision-making

as

ong

been

topic

f

tudy

in

S research

e.g.,

1

1,36,

76, 79,

83]).

The

representational

imension

eflects

he

degree

o

which

nformation

resentation

ffectively

acilitates

nterpretation

nd

understanding;

herefore,

he

ormatf

the

nformations an

mportant

imension

f

informationuality64].

Collectively,

here

re

myriad

imensions

hat an be

considered nder

he abel

of

intrinsic,

ontextual,

nd

representational

nformation

uality,

nd

there

s

little on-


6/38

ANTECEDENTS OF INFORMATION AND

SYSTEM

QUALITY

203

sensus

n what

onstitutes

complete

nd

yet arsimonious

etof

nformation

ual-

ity

imensions

80].

Building

n the

ategorization

f

ntrinsic,ontextual,

nd

rep-

resentational

imensions

rovided yWang

nd

Strong

82],

we havedistilled

core

setof nformation

uality

imensionss follows:

ccuracyreflecting

ntrinsic

ual-

ity), ompleteness

nd

currency

reflecting

ontextual

uality),

nd

format

reflect-

ing

epresentationaluality).

he

dimensions,

heir

erivation,

nd reatmentn

prior

literature

re shown

n

Appendix

.

Accuracy

s most

ommonly

efined s the orrectnessn the

mapping

f

stored

informationo the

ppropriate

tate n the ealworld hat he nformation

epresents

[5,

27,

43].

Wand

nd

Wang

80]

further

efine

henotion f

accuracy

o

nclude he

idea

that he nformation

ot

only

s

correct,

nambiguous,

nd

objective,

ut lso

meaningful

nd

believable.

he

key

lement

f his efinements thenotion hat here

isan mportanterceptualomponentoaccuracy.nformationot nlymust e ac-

curate ut

must lso be

perceived

o be accurate

82].

A

furtherxtension

o

the

no-

tion

of

accuracy

s

consistency

5,

27, 34,

41],

referring

o thecorrectnessf the

relationship

etween

r

mong

multiple

tems

f

nformation

ndof

nformationver

time.

n

udging

ccuracy,

e would ssert

hat sers ssess

perceptions

f correct-

nessof

nformation

xtracted

rom

ystems

ver

protractederiod

f time.

heir

overall

ense

of

accuracymay

be

shaped

y

the

underlying

orrectness

f the nfor-

mation,

erceptions

f the

believability

f the

nformation,

nd

the

onsistency

f

longitudinalxperiences.

Beyond

ccuracy,

he

uality

f nformation

lso can be

shaped

y completeness.

Completenessefers o thedegree owhich ll possible tates elevanto theuser

population

re

represented

n

the tored

nformation

5,

27, 34,

80].

t s

important

o

recognize

hat he ssessment

f

completeness

nly

an be made

relative o the on-

textual emands

f he ser

nd hat he

ystem

may

be

complete

s

far

s one user s

concerned,

ut

ncomplete

n the

yes

of

another.

While

completeness

s a

design

objective,

ts ssessment

s

basedon

the

ollective

xperience

nd

perceptions

fthe

system

sers.

In addition o

completeness,

urrency

as been dentified

s an

mportant

actor

n

contextual

nformation

uality

4,

8,

16, 35,

54].

Currency

efers o the

degree

o

which nformation

s

up

to

date,

r

the

degree

o

which he nformation

recisely

reflects

he

current

tate f the

world hat

t

represents.2

urrency

s a contextual

attribute

f

system

uality

o the xtent

hat

ts

ssessment

s

dependent

n

task

nd

user

erceptions

6].

Users

may

havedifferent

emands

or

urrency

nd,

s a conse-

quence,

nformation

hats viewed

s current

or netask

may

e

viewed

s

toodated

for nother.

gain,

user

perceptions

f

currency

elative o

the askdemands ver

time

willbe an

mportant

eterminant

f nformation

uality.

The

final imension

f

nformation

uality aptured

n

Table

1 s

format.

ormats

tiedto the

notion

f

representationaluality

4,

47, 53,

82].

Format efers

o

the

degree

o

which nformation

s

presented

n

a mannerhat

s

understandable

nd n-

terpretableotheuser, ndthus ids n the ompletionf a task. here s significant

research

n information

resentation,

nd theone consistent

onclusion rom his

line f

research

s

that

he

uitability

f

particularresentation

s

highly ontingent


7/38

204

NELSON, TODD,

AND WIXOM

Table

1

Information

uality

imensions

Information

Dimension Definition qualityategory

Accuracy

The

degree

to which nformation

s

correct,

Intrinsic

unambiguous,

meaningful,

elievable,

and

consistent.

Completeness

The

degree

to

which all

possible

states

Extrinsic;

relevant

o

the user

population

are

represented

contextual

in the stored information.

Currency

The

degree

to

which nformation

s

up-to-date,

or

the

degree

to

which the

information

recisely

reflects he current

tate of

the world

that

t

represents.

Format The

degree

towhich nformations presented in Extrinsic;

a manner that s understandable

and

representational

interpretable

o the

user and

thus aids

in

the

completion

of

a task.

Note: The

dimensions,

heir

erivation,

nd treatment

n

prior

iterature

re shown

n

Appendix

A.

__

on

themanner

n which he

presentation

atches

he

demands

f the

ask nd

the

mentalmodel

mployed

y

theuser

78].

Thus,

he ssessment

f format

ill be

shaped y he erceptionsf he ser ompletingifferentaskswithhe ystemver

time.

To

summarize,

number

f

factors ave

been dentified

nd

abeled

s dimensions

of nformation

data)

quality

s illustrated

n

Appendix

;

however,

n

ntegration

f

the iteratureased on

Wang

nd

Strong's

82]

organizing

ramework

uggests

hat

these actorsanbe reduced

o

a

relatively

oncise

et fdeterminants

f nformation

quality

see

Table

1).

The

dimensions e

identify

re

accuracy,

ompleteness,

ur-

rency,

ndformat.

ollectively,

hese our imensions

ppear

o

capture

he

key

le-

ments f information

uality

by taking

nto account he

ntrinsic

roperties

f

information

uality

elated o

correctness,

he ontextual

actors

riving

ask

erfor-

mance,

s well s the

epresentational

haracteristicsf nformation

uality.

or

ach

dimension,

t s

important

o

recognize

hat

uality

s not ssessed

n

an absolute nd

objective

ense,

ut atherhat

he ssessmentf

quality

s tied

o the

perceptions

f

informationonsumers ho

re

working

n

specific

askswithin

pecific

ontexts.

Applying

ur

four-model

ssessment

riteria,

e conclude hat

hese

imensions

enhance

nderstanding

f

he

multifacetedature f

nformation

uality y

apturing

dimensionselated o the

ntrinsic,xtrinsic,

nd

representational

iewsof

nforma-

tion

uality

nd

by

emphasizing

he

mportance

f context nd

perception

n the

overall

uality

ssessment.

urther,

e

propose

hat hese imensionsre ctionable

in that hey anguide designero refinepecific acets f a systemnanefforto

enhance

uality,

nd the

dimensionsre

relativelyarsimonious,istilling

ver30

dimensions

epresented

n

the

iteraturentofour

ey

constructselated

o

quality.


8/38


9/38

206

NELSON,

TODD,

AND WIXOM

Table2.

System uality

imensions

System uality

Dimension Definition category

Accessibility

The

degree

to

which a

system

and

the

System-related

information

t

contains

can be accessed

with

relatively

ow effort.

Reliability

The

degree

to which

a

system

is

dependable

(e.g.,

technically

vailable)

over

time.

Response

time

The

degree

to

which a

system

offers

uick

Task-related

(or

timely)

responses

to

requests

for nformation

or action.

Flexibility

The

degree

to

which

a

system

can

adapt

to

a

variety

f user needs

and to

changing

conditions.

Integration

The

degree

to whicha

system

facilitates he

combination

of information

rom arious

sources

to

support

business decisions.

Note: The

dimensions,

heir

erivation,

nd treatment

n

prior

iteraturere

shown

n

Appendix

B.

the xtenthat he

ystem

tself

s

either

ccessible

o user

rnot

ccessible,

egard-

less

of

the ask hat heuser

s

trying

o

accomplish.

Reliability

eferso the

dependability

f

a

system

ver

ime

10,

71,

73].

It

can

be

defined

bjectively

s the echnical

vailability

fthe

ystem

nd

can

be

concretely

measured

y

metricsuch s

uptime,

owntime,

rmean ime etween ailures. e-

spite

he act

hat

eliability

an be measured

bjectively,

t

lso s true hat

ndividu-

als

may

have

perceptions

f

reliability

hat re

ndependent

f measured

eliability.

Consider

user

who

only

workswith

system

nce

week or short

eriod

f ime.

A

momentfdowntime

uring

hat ime

may

have

significant

etrimental

ffectn

reliability.

hus,

ser

erceptions

f

reliability

re

key

o

determiningystemuality.

Response

ime efers o the

degree

o which

system

ffers

uick

or

timely)

e-

sponses

o

requests

or nformationr action

4,

20, 24,

35].

Different

inds f

sys-

tems

e.g.,

transaction

rocessing,

ecision

upport)

ften re

designed

r

optimized

toprovide ertain esponse imes, nd usersmayperceive heresponse ime f a

system

asedon thekind

f ask hat

hey

re

performing.

or

xample,

sers

may

e

very

olerant

f

ong

response

imes or

n

Internet

pplication,

ut

hey

wouldbe

much ess

tolerant

f a

similar

esponse

ime n a

desktop pplication.

o the

xtent

that

his s the

ase,

we

argue

hat

esponse

ime s a

task-related

roperty

f

system,

andone n which

ser

erceptions

ayvary

rom

bjective

measures.

While he wo

shouldbe related n

most

ases,

ultimately

t s the

perceptions,

otthe

objective

measures,

hatwill

guide

perceptions

f

quality

nd

usage

behavior.

Flexibility

elates o the

degree

o

which

system

an

adapt

o a

variety

f user

needs

nd o

hanging

onditions

4,

33,

54,

82].

The

definitionf

flexibility

uggests

theneedtoadapt ochangingonditionsnddifferentserneeds,makingt a task

property

f

system

uality.

o the

xtent hat

system

ill

be used over ime nd

must

rovide

nformations

input

o a

wide

variety

f

decision

asks,

lexibility

an


10/38

ANTECEDENTS OF INFORMATION

AND

SYSTEM

QUALITY

207

be

expected

obe a

key

determinantf

quality.

he

relative

mportance

f

flexibility

in

determininguality

may

epend

n the

egree

owhich ask emands

hange

ver

time.

n

a

data

warehouse

ontext,

or

xample,

e

mightxpect

hat

lexibility

s

ess

important

n the ontextf

predefined

eports

which

rovide

nformationor tatic

tasks)

nd

more

mportant

or

uerying

nd

analysis,

which

re ess structurednd

more

ikely

o

change

ver

ime.

Finally,

ntegration

eferso the

degree

o

which

system

acilitateshe

ombina-

tion

f nformation

rom arious ources o

support

usiness ecisions

4,

53,

82].

The need

for

ntegration

ill

vary

cross

tasks nd

contexts,

nd

thus,

ntegration

represents

task-related

roperty.

asks

that

re

more

nterdependent

ill

require

systems

hat

acilitate

ntegration

o

greateregree

han

ystems

hat

upportargely

independent

asks

32].

Determinants

f

nformation

nd

System uality

When

onsidering

nformation

nd

system uality

ogether,

t s

useful

o think f

information

s

the

product

f

system

ndthe

ystem

s the nformation

rocessing

system

hat

roduces

he

nformation

22].

As noted

bove,

he

key

dimensions

f

information

uality

re

ccuracy, ompleteness,

urrency,

nd

ormat.

he

key

deter-

minants

f

system

uality

re

ccessibility,

eliability,esponse

ime,

lexibility,

nd

integration.

ollectively,

hese eterminants

hould

xplain

nformation

nd

system

quality,

nd

they

ndirectly

hould

nfluence

ser

perceptions

bout atisfaction

ith

the nformationnd

system

see

Figure

).

As

explained

arlier,

he

iterature

uggests

hat

ystem

actors

ay

nfluenceuser's

perception

f,

r atisfaction

ith,

he nformation

rovided

y

he

ystem

12].

More-

over,

ast

onfusion

n

differentiatingystem

uality

romnformation

uality

actors

(see

Appendices

and

B)

suggests

hat rossover

r interaction

ffects

may

exist

between

he

woconstructs.

herefore,

heresearch

model

ncludes rossover

ela-

tionships

rom

uality

information

nd

ystem)

o satisfaction

system

nd

nforma-

tion)

s well

s an

nteraction

ffectf

nformation

nd

ystemuality

n nformation

satisfaction

nd

system

atisfaction

see

Figure

1).

These

relationshipsxplore

he

possibilityhatmore omplex uality/satisfactionelationshipsay xist.

Empirical

tudy

A cross-sectional

survey

was conducted

to

test hemodel

n

Figure

The

con-

text f

the

urvey

as user

xperiences

ith data

warehouse.

pecifically,

urvey

participants

ere sked

to

report

n their

xperiences

ith hree

ypes

f

business

intelligence

ools

most

ommonlymployed

o

access and

analyze

data warehouse

information:

1)

predefined

eporting

oftware,

2)

query

ools,

nd

3)

analysis

ools.

Predefinedeporting

s

software

hats set

upby

he ata

warehouse

roject

eam nd

is run

y

users

n a

regular

asis to

provide redetermined

nformation.

uery

ools

allow

users

o

extract

nformation

or hemselves

o

satisfy nplanned,

onroutine

n-

formation

eeds.

Analytical

ools

llow he

manipulation

nd

modeling

f nformation


11/38

208

NELSON, TODD,

AND WIXOM

IcOMPLETENESsl

(

ACCURACY

V^

'

^

^/information] /information^

i

quality

t

^satisfaction/*

( FORMAT

^

/ '

I

'

(currency)^

' /

N,

^

-

*/

' /

/infosaA

'SYSTEMSAy

(reliability

/ ' /

FLEXIBILITY

k,^^

'

/ ' /

^-

'

^7

SYSTEM

y

SYSTEM

^

J

QUALITY

I

^SATISFACTION/

( ACCESSIBILITY

^ /

f

(RESPONSE y /

I TIME

I

/

I

INTEGRATION

I

Figure

. Determinantsf

nformation

nd

System uality


12/38

ANTECEDENTS OF

INFORMATION AND

SYSTEM

QUALITY

209

extracted

rom

data

warehouse. he

following

ections

escribe

he

tudy,

ncluding

the nstrument

evelopmentrocess

nd

he

ample

hatwas used.

Instrumentevelopment

Development

fthe

urvey

nstrument

ollowed he

rocess

roposed y

Moore nd

Benbasat

55].

A

literatureeview

was

conductedo ocate

ast perational

easures

of the onstructs

nder

nvestigation,

roups

f

questions

were

ompiled

rom ali-

dated

nstruments

o

represent

ach

construct,

nd

wording

as

modifiedo

fit

he

data

warehouse ontext

o be

studied.

Next,

en

professors

nd

graduate

tudents

sorted

he tems

nto

eparate ategories,

dentifyingmbiguous

r

poorly

worded

items. tems

were

emoved ndminor

ording

hanges

weremade

prior

o

a second

round

f

orting,

hich idnotuncover urther

roblems.

he three

tems hatwere

categorized

most

ccurately

ere elected or ach

quality

imensionnd ncluded

onthe

urvey

nstrument

n

random

rder.3ach

question

as measured n a seven-

point

ikert-type

cale,

ranging

rom

1)

stronglyisagree

o

7)

strongly

gree.

Before

mplementing

he

urvey,

he nstrument

as further

eviewed

y

cademics

and

practitioners

ith

nowledge

f

urvey

esign,

S

quality,

nd

data

warehousing.

Minor

hanges

weremadebased

on their

uggestions.

he

resultingurvey

as

then

pilot-tested

sing espondents

rom

largepublic

university

o

identifyroblems

with he

nstrument's

ording,

ontent,ormat,

nd

procedures.

or this

pilot

est,

surveys

ere istributed

o 250 active

sers f a

large ublic niversity's

ata

ware-

house; 3 responded,esultingn a 29percentesponse ate. ilotparticipantsom-

pleted

he nstruments

nd

provided

writtenommentsbout

ength, ording,

nd

instructions.

wo ofthe

articipants

ere nterviewedo

gain

richer

nderstanding

of

he eedback.

hedata

were

nalyzed egarding

he

nternal

onsistencyeliability

of

he onstructs

sing

ronbach's

lpha,

nd ach xceeded

he

ccepted

.7 evel

of

reliability

58].

Based on

theresults

f the

pilot ample,

minormodifications

eremade to the

survey

esign.

he

final

urvey

ncludedtems

measuring

he onstructsrom

igure

1

as

well as

a series

f

demographic

nd

self-reportedsage

tems. he

specified

items nd

descriptive

tatistics,

rganized y

construct,

re

hown nTable

3.

Sample

Study articipants

ere olicited

ia an

e-mail

nnouncement

ent omembersf he

Data

Warehousing

nstitute

ffering

free

tudy

o assess the success

of their

organization's

ata

warehouseoftware.

even

rganizations

rom

variety

f ndus-

tries

e.g.,

health

are,

onsumer

oods,

inancial

ervices,

nd

government)greed

to

participate.

ach

organization

as asked o distribute

aper-based

urveys

ia n-

teroffice

ail o

all ofthe ctive

sers f tsdata

warehouse. ll

surveys

ere onfi-

dential;

o

dentifyingersonal

nformationas collected.

ompleted

urveys

ere

collected

y

a contact

erson

teach

organization

nd returnedo theresearchers.

Response

ates

aried cross

organizations

see

Table

4),

with n

overall

tudy

e-

sponse

ate f

21

percent,

ielding

65

completed

urveys.


13/38

210

O

-a

-aS

CO

>

i

&

1

O

co

I

t

M

Si S Si li

S

"

"05

il

"

h

"55

il

a)

h-oh-

o

co co

coiaio

b:

P

>

g

^

h-oh-

k^cq

corico

co

io io

oqrv.rN.

OJ

CO

O)

O)

O)

O>

1

i

i

li

Im

II

"(D

II

"

II

H

O

T3 g ^OD00li) bTili)^ ^COO CO ^ IO (D T-

S

in co

t-

^1^.0

o?T

CN

9?^

CL(5

^ ^

^

IO "t

IO ^tlOlO

lO^-^-

S

e

ci-

I

i=

?

^

.

g

'-3

-ri

i=

^

"5

.

CO

'-3

le li

J3S

I

gf

o ' o -H ii S Z ? o.

IS

S

8

^S"5

g|S

o.

fil

II

11

f

|

"

Ht

Sfl HI

f

1|1

11

III

1^1

1

||

s

M HI

si

^co-od-o

?

-o

'>

-OcdE

SEE ">

"2 i

.2

c

c

2E2

-o

2S0 000.

22o

2

5

aaa

>

Q.

7 "E cecero

00.

clq.^

p-Q.

2

0cod)2g:

o,

o

'

i

i

$

fi li

..i

i

I

1

i

t

;s

HE

5

I 5

1 i $

S I 2 i 5 & -- i S

fi

S

S

ti

p

=

p

5 S

a

Po

c

^m

cocco

I

c

8.

S5

S

S

5

ooe

~

cw

"co^3

^*C

C3)

"O

FO3

(OCtf)

iifM

II

il,

li

i ||

f

ili

i

1

6

us

i

i

fit

t lli

---.Eoo

il

=

1

cr >*

III Illc

.2o

lilil

ajQ-coto----.Eoo == cr >* oQ.Q->, .2o ajQ-coto

1

OO2-EO_==

lf &1 111 I III

g

| M |l|i||

Q.

OO2-EO_==

Hg

OQ.

^

S

O

OC

LL

^


15/38

212

T3

u

"

u

o

A

QUALITY

)

Pl-WI*-

^^SATISFACTION/

(

ACCESSIBILITY

W

/ /[Jj31

[1^536

V / &W* /

^'743

PI'486

x

/

$Jf

w-750

Pi-511

/responseX/^

I TIME I

^sQ*

(integrationV

Figure

. ResearchModel

Results.

Notes: 1

=

Predefined

eporting

oftware;

=

query

ools;

3

=

analysis

ools;

*

p

O)C0

cq

s

C3)

000500

o>o)d>

oqa>ci>

O)O)

T'

Sj

o

odd

odd

odd

odd

odd

00

.SS

T-1-1-

t-COt-

OCvllO

O>C3)

0)1^0)

GO

O) CO

O) O)

O)

O>

O)

O>

^i

^Ph

odd

odd

odd

odd

odo

00

CT

C/)

S

c

1

O

co

to

'+=

I

I

S

f

^1 1-

ES

c

T

o

2

S

n

>,?*>>

O.2

3

3

ip^

*

?

S

g'8

^c

*

5

f

lifi

g

?

I

8

"55t5

co

$^o

Sg^

-i=Q-.g

g

Ili II I HI p | fi

collo

.E

^ ^^^

^

| ?

1

|1

gel

'%'%'%

"5

S5|"

go

Seo-

Q-Q-Q-

g^

))cl:cj'

.Isi

i

III

Ilitl

IH

Ititeli.

Jii.ttli-Iif

tS o < o s s


38/38

235

i i

S5 5 fei 888 SfcS

ooo

85|

oo

o

d

do

odd odo ooo ooo ooo oo

111

11

111

111

ill

us

ill

111

sis

ill

ill

si ii

CO

Q.

i

(/)

. 8

&

p p

g

.g

Antecedents of Information and System Quality

Documents

Transcript of Antecedents of Information and System Quality