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    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.

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    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.

  • 8/9/2019 Antecedents of Information and System Quality

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    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:

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    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.

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    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-

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    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

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    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.

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    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

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    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

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    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

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    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,

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    as

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    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

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    rder.3ach

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    as measured n a seven-

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    ikert-type

    cale,

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    rom

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    stronglyisagree

    o

    7)

    strongly

    gree.

    Before

    mplementing

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    urvey,

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    as further

    eviewed

    y

    cademics

    and

    practitioners

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    urvey

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    pleted

    he nstruments

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    nd

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    wo ofthe

    articipants

    ere nterviewedo

    gain

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    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

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    tems. he

    specified

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    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

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    tudy

    o assess the success

    of their

    organization's

    ata

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    even

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    tries

    e.g.,

    health

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    oods,

    inancial

    ervices,

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    to

    participate.

    ach

    organization

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