A Path to Successful IT Outsourcing: Interaction Between ...Goo et al. 2008].pdf · A Path to...

Decision Sciences C© 2008, The AuthorVolume 39 Number 3August 2008

Journal compilation C© 2008, Decision Sciences Institute

A Path to Successful IT Outsourcing:Interaction Between Service-LevelAgreements and Commitment

Jahyun Goo,† C. Derrick Huang, and Paul HartInformation Technology and Operations Management Department, Barry Kaye College ofBusiness, Florida Atlantic University, 777 Glades Road, Boca Raton, FL 33431-0991,e-mail: [email protected], [email protected], [email protected]

ABSTRACT

Although service-level agreements (SLAs) are important for IT outsourcing manage-ment, appropriate mechanisms for constructing effective SLAs are still poorly under-stood, leading to inadequate or overcomplicated contracts that are ineffective. This studyexamines the associations among three distinct sets of SLA characteristics and outsourc-ing success, as well as the role of commitment in these relationships. Analyzing surveydata based on a model theorizing the alignment of SLA characteristics with intendedoutsourcing objectives, we find that different types of benefits attained through IT out-sourcing arrangements are associated with the use of specific contractual dimensions.We also find that commitment, in general, moderates the impact of SLAs on outsourc-ing success, although the nature of the moderation varies with the different benefits IToutsourcing engagement is intended to achieve. Interestingly, in certain cases—changecharacteristics for achieving technology benefits, in particular—commitment can bea barrier to the effective use of SLAs in achieving intended outsourcing benefits. Assuch, our study extends the literature on IT outsourcing, contracting and commitment,as well as provides a general guideline for practitioners to structure effective SLAs andto properly use commitment for managing IT outsourcing engagements to successfullyachieve intended benefits.

Subject Areas: Commitment, Hierarchical Moderated Regression Analy-sis, IT Outsourcing, Outsourcing Success, and Service-Level Agreements(SLAs).

INTRODUCTION

With the increasingly sophisticated forms of outsourcing arrangements, suchas business process outsourcing (Mani, Barua, & Whinston, 2006), offshoring(Rottman & Lacity, 2004), and capability sourcing (Gottfredson, Puryear, &Phillips, 2005), the tasks of managing IT outsourcing engagements becomemore challenging. Given the inherent complexities, companies strive to developa good start in outsourcing engagements with well-crafted contracts. This in-creases the pressure on information systems (IS) professionals to understand the

†Corresponding author.

469

470 A Path to Successful IT Outsourcing

issues involved in IT outsourcing contracts (Ang & Beath, 1993; Wang, Barron,& Seidmann, 1997; Anderson & Dekker, 2005; Argyres & Mayer, 2007). At thesame time, management increasingly uses commitment, or partnership, to com-plement the adaptive limit of contracts for managing the uncertainties embeddedin these arrangements (Kern & Willcocks, 2002; Koh, Ang, & Straub, 2004; Sull& Spinosa, 2007). Given that the level of balance between contractual manage-ment and social enforcements may result in either a “virtuous cycle” or “viciouscycle” of outsourcing for better performance (Sabherwal, 1999; Poppo & Zenger,2002), it is important to understand how contractual provisions and commitmentwork together in an IT outsourcing engagement in order to enhance the designand management of contracts that improve the performance of IT outsourcingengagement.

This article examines the association between different contract characteris-tics and IT outsourcing success, and also investigates how commitment moderatessuch relationships, using hierarchical moderated regression analysis of survey data.We use SLAs, a proven effective tool for managing IT outsourcing performance(Singleton, McLean, & Altman, 1988; Mingay & Govekar, 2002; Yadav, Bharad-waj, & Saxena, 2006), as the proxy for outsourcing contracts and adopt a structurethat classifies SLAs provisions into three categories and 11 items (Goo, 2008;Goo, Kishore, Rao, & Nam, 2008). Few, if any, SLAs contain all the identifieditems, because doing so would inevitably make the SLAs too complicated to man-age (Karten, 2004) and/or increase contracting costs (Anderson & Dekker, 2005).When designing contracts, the main issue is to select the right items to enhance out-sourcing success so that the written contract is aligned with the strategic intent andoperations requirements of the intended outsourcing arrangement. Thus, we test amodel to see if the three characteristics of SLAs have differentiated relationshipswith different measurements of outsourcing success, and if and how commitmentmoderates such relationships. It is important to note that we do not develop ahypothesis about whether the contracts and commitment are complements or sub-stitutes for one another; the intention is to understand possible intricate interactionbetween the two.

The rest of the article is organized as follows. First, we provide a literaturereview and theoretical discussion for the three variables—SLAs, the independentvariable; commitment, the moderating variable; and outsourcing success, the de-pendent variable—of this study. Next, the research model and hypotheses arepresented. We then describe in detail the research methodology, data collection,and statistical analysis, followed by the results and a discussion of the findings ofthis study and their implications. The article concludes with the contributions andlimitations of this study, as well as suggestions for future research directions.

RESEACH BACKGROUND

IT outsourcing literature has investigated various aspects of contracting issuesincluding legal (Walden, 2005), structural (Whang, 1992; Ang & Beath, 1993),economic (Wang et al., 1997), and performance issues (Singleton et al., 1988;Gopal, Sivaramakrishnan, Krishnan, & Mukhopadhyay, 2003; Anderson & Dekker,2005 ). Practitioners, however, tend to focus on those contractual issues that directly

Goo, Huang, and Hart 471

impact the performance of outsourcing arrangements. SLAs are an addendumto the main contract describing the products or services to be delivered by theoutsourcing provider. They establish the parties’ expectations, identify contacts ifend-user problems should arise, and specify the metrics by which the effectivenessof various contracted services and processes will be measured and controlled. Assuch, SLAs are an important tool for managing IT outsourcing relationships andensuring optimum performance (Singleton et al., 1988; Fitzgerald & Willcocks,1994; Currie, 1996 ). However, the existence of SLAs by no means guaranteesthe success of outsourcing. SLAs, in particular the earlier ones, often containclauses and metrics dealing with only the most rudimentary service elementswhile ignoring such important issues as governance and changes in relationships,resulting in uncertainty in anticipating desired outcomes (Fitzgerald & Willcocks,1994). On the other hand, in striving to capture all potential benefits, companiessometimes structure SLAs so comprehensively that their complexity makes themvirtually unmanageable (Marcolin, 2002; Karten, 2004). Indeed, prior research hasshown that poor outcomes of IT outsourcing are often attributed to failure in clearlydefining specific goals, aligning contracts with strategic objectives, and makingcontracts flexible enough to adjust to changes in the business or the technology(Ang & Beath, 1993; Anderson & Dekker, 2005). Thus, it is critical to understandthe underlying structure of SLAs, and recent literature has started to focus on thisissue (Stone, 2001; Deloitte, 2005).

Structure of SLAs in IT Outsourcing

For this study, both deductive and inductive approaches are used to frame the struc-ture of SLAs. First, we adopt a priori theoretical framework incorporating Ang andBeath’s (1993) hierarchical elements and Macneil’s (1978) relational dimensionsto identify 11 contractual issues that are important in IT outsourcing relationships.While such a framework and the deduced issues may lead to “boilerplate” tem-plates for outsourcing engagements, there remains, as commonly observed (e.g.,Whang, 1992; Wang et al., 1997), diversity in any SLA where emphasis is placedon different characteristics. Thus, as the second step, we map out the provisions inseveral actual SLAs to the 11 elements identified in the first step in order to findthose different characteristics. We employ the axial coding technique (Strauss &Corbin, 1990) for developing a parsimonious number of categories or dimensions.(Appendix B describes the inductive coding process in detail.) In doing so, wefind three sets of theoretically distinct SLA characteristics. They are foundation,change, and governance characteristics, reflecting common underlying themesof management control often used by firms to manage outsourcing relationships(Choudhury & Sabherwal, 2003). It is noted that we use the term SLA charac-teristics to refer to the content of formal contract clauses, because the exact formof actual clauses may differ in different SLAs. As derived, these characteristicsare consistent with and appear grounded in existing theoretical frameworks. Forexample, Ang and Beath (1993) note the importance of behavior-based controland propose to include “standard operating procedures” as hierarchical elementsin SLAs, while the axial coding process reveals change characteristics stipulatedthrough a future demand management plan and an anticipated change plan that


encourage the service provider (SP) to deliver input to the service recipient (SR)for the relationship to remain close even when precise specification of servicesand service levels may not be possible in situations of high uncertainty. Thesethree characteristics (and their associated elements) and their relevance to spe-cific types or goals of outsourcing relationships are briefly discussed below. Adetailed description can be found in Table 1 (for a fuller discussion of the de-velopment efforts and statistical validation of the SLA structure, refer to Goo,2008).

Foundation characteristics (FCs)

FCs specify common objectives and set clear standards of conduct by defining rolesand responsibilities of the parties involved in the outsourcing arrangement. Service-level objectives and service-level content elements explicitly state the requirementsand intent of the arrangement and form the basis for operating philosophy ofthe outsourcing relationship. The third element, process ownership plan, spellsout the roles and responsibilities of key process owners and codifies a sharedunderstanding among key decision makers and staff members who develop thedetailed mechanisms for implementing the contract. These FC elements clearlyspecify “who is to deliver which services at what level,” a critical agreementthat facilitates the operations of outsourcing relationships. FCs are also importantfor outsourcing arrangements that involve the transfer of significant portions of aclient’s in-house operations to external service providers, because the contract canbe long term (Kishore, Rao, Nam, Rajagopalan, & Chaudhury, 2003) and involvea group of decision makers and staff members who might inherit the relationshipover time (Choudhury & Sabherwal, 2003).

Change characteristics (CCs)

CCs provide general processes for adjusting the terms of the agreement to alignthem with changing goals of the outsourcing relationship (DiRomualdo & Gur-baxani, 1998; Kishore et al., 2003). Many contracts in the IT industry are mod-ified reflecting learning over time (Mayer & Argyres, 2004). Through the futuredemand management plan and anticipated change plan, both parties agree to con-tinuous evaluation and improvement of the SLA in areas such as service activities,functions, processes, and their desired levels, so that the provider’s performancecontinues to meet the changing business needs of the recipient (Klepper & Jones,1998). To maintain agility and flexibility in the IT outsourcing relationship (Ang& Beath, 1993; Lacity, Willcocks, & Feeny, 1995), the innovation plan and feed-back plan identify the structure for motivating new innovations and the road mapfor efficient adjustments by identifying all affected areas and resources. CCs areespecially critical to the SR’s desire to gain access to cutting-edge technologies inareas such as IS planning and new product design. Because outsourced servicestend to be close to the core of the client’s business strategy, agreement alignmentand reorientation may be needed. CCs help both parties to agree on mechanismsfor managing unanticipated changes of highly uncertain or unstructured technicaltasks (Choudhury & Sabherwal, 2003).


Tab

le1:

The

cont

ract

uale

lem

ents

ofse

rvic

e-le

vela

gree

men

tsin

ITou

tsou

rcin

g.

Con

trac

tual

Con

trac

tual

Issu

esof

Cha

ract

eris

tics

Ele

men

tsof

SLA

SLA

inIT

Out

sour

cing

Cla

uses

inPr

actic

eSu

ppor

ting

Ref

eren

ces

Foun

datio

n:• P

ublic

izin

gco

mm

onva

lues

,be

lief,

philo

soph

yw

ithin

acl

an(K

irsc

h,19

97)

Serv

ice

Lev

elO

bjec

tives

Spir

itof

cont

ract

uals

olid

arity

and

publ

icity

ofco

mm

onva

lues

,bel

ief,

philo

soph

ybe

twee

nor

gani

zatio

nsto

ensu

repe

rfor

man

ce

• Ast

atem

ento

fbo

thSR

’san

dSP

’sbu

sine

ssob

ject

ives

from

the

enga

gem

ent

• Ast

atem

ento

fov

eral

lfro

mth

eco

ntra

ct• A

stat

emen

tof

expe

ctat

ions

and

capa

bilit

ies

ofth

eSP

(Fitz

gera

ld&

Will

cock

s,19

94;H

eide

,199

4;Si

mon

s,19

95;

Cho

udhu

ry&

Sabh

erw

al,

2003

;Koh

,eta

l.,20

04;

Rin

g&

Van

deV

en,

1994

)• R

esul

ting

insh

arin

ga

com

mon

ideo

logy

,in

tern

aliz

ing

ase

tof

valu

es,

and

com

miti

ngto

acl

an(C

houd

hury

&Sa

bher

wal

,20

03)

Proc

ess

Ow

ners

hip

Plan

Num

ber

ofco

mpa

nies

taki

ngpa

rtin

som

eas

pect

ofth

eIS

port

folio

sw

hen

outs

ourc

ed

• Sta

tem

ento

fpr

oces

ses

that

are

deliv

ered

via

the

agre

emen

ts• S

tate

men

tof

proc

esse

sdi

rect

lyaf

fect

edby

the

serv

ices

incl

uded

inth

eag

reem

ent

• Sta

tem

ento

fpr

oces

sth

atar

ere

quir

edto

man

age

the

agre

emen

tbet

wee

nth

eSR

and

SP• S

tate

men

tof

proc

ess

owne

rshi

pro

les,

auth

oriti

esan

dre

spon

sibi

litie

s

(Sca

rdin

o,20

01b;

Sing

leto

n,et

al.,

1988

;K

oh,e

tal.,

2004

;Rin

g&

Van

deV

en,1

994) C

ontin

ued


Tab

le1:

(Con

tinue

d)

Con

trac

tual

Con

trac

tual

Issu

esof

Cha

ract

eris

tics

Ele

men

tsof

SLA

SLA

inIT

Out

sour

cing

Cla

uses

inPr

actic

eSu

ppor

ting

Ref

eren

ces

• Pro

vidi

ngm

eans

tocr

eate

age

nera

lcom

mitm

ent

betw

een

part

ners

from

whi

chde

sira

ble

actio

nsev

olve

(Bri

ckle

y,19

99;

Will

iam

son,

1985

)

Serv

ice

Lev

elC

onte

nts

Spec

ifica

tion

ofob

ligat

ions

inte

rms

ofa

stat

emen

tof

wor

k,th

eas

soci

ated

and

requ

ired

serv

ice

leve

ls,a

ndth

epr

ice

tobe

paid

into

alls

ourc

ing

agre

emen

ts.

• Age

nera

ldes

crip

tion

ofth

ese

rvic

esre

quir

ed,m

ajor

cate

gori

esof

serv

ices

and

spec

ific

serv

ice

elem

ents

• Aco

mpi

latio

nof

the

mos

tco

mm

onse

rvic

ele

vels

com

plet

edfo

rea

chse

rvic

ele

vel

• Ser

vice

-lev

elta

rget

,tim

efr

ame

defin

ition

,qua

lity

stat

emen

t,et

c.

(And

erso

n&

Nar

us,1

990;

Moh

r&

Spek

man

,199

4;M

aure

r,et

al.,

2001

;Fi

tzge

rald

&W

illco

cks,

1994

;Ker

n&

Blo

is,

2002

)

Cha

nge:

• Spe

cific

rule

san

dpr

oced

ures

,w

hich

wou

ldle

adto

desi

red

outc

omes

iffo

llow

ed(K

irsc

h,19

97;C

houd

hury

&Sa

bher

wal

,200

3)

Futu

reD

eman

dM

anag

emen

tPl

an

Plan

ning

the

proc

ess

and

met

hodo

logi

esfo

rco

ping

with

chan

gean

dco

ntin

genc

ies

ina

long

term

enga

gem

ents

:agr

eein

gto

agre

e

• Joi

nt(S

R/S

P)de

man

dfo

reca

stin

gpr

oces

s• A

ssum

ptio

nsm

ade

and

proc

ess

for

upda

ting

the

key

assu

mpt

ions

that

affe

ctde

man

d• P

rior

itiza

tion

met

hodo

logy

for

curr

enta

ndfu

ture

dem

ands

• Pro

cess

for

sche

dulin

g,co

stin

gan

dm

odif

ying

agre

emen

ts

(Gro

ver,

etal

.,19

96;K

ern

&W

illco

cks,

2002

;H

eide

,199

4;Sc

ardi

no,

2001

)

Con

tinue

d


Tab

le1:

(Con

tinue

d)

Con

trac

tual

Con

trac

tual

Issu

esof

Cha

ract

eris

tics

Ele

men

tsof

SLA

SLA

inIT

Out

sour

cing

Cla

uses

inPr

actic

eSu

ppor

ting

Ref

eren

ces

• Mec

hani

sms

that

faci

litat

ejo

inta

dapt

atio

nto

prob

lem

sra

ised

from

unfo

rese

eabl

ech

ange

sin

toth

eco

ntra

ct(W

illia

mso

n,19

96)

Ant

icip

ated

Cha

nge

Plan

The

join

tdev

elop

men

tof

expe

ctat

ions

abou

tper

ceiv

edun

cert

aint

ies,

espe

cial

lyco

ncer

ned

with

antic

ipat

edco

nflic

tsof

inte

rest

and

pote

ntia

ltro

uble

• Cle

arde

finiti

ons

ofth

eke

yca

tego

ries

ofch

ange

• Rol

es,r

espo

nsib

ilitie

san

dde

cisi

on-m

akin

gpr

oced

ures

for

the

SRan

dSP

for

each

cate

gory

ofch

ange

• Top

driv

ers

for

chan

ge–

revi

ewed

regu

larl

y

(Ben

dor-

Sam

uel,

1999

;Fo

nten

ot&

Wils

on,

1997

;Lee

&K

im,1

999)

• Met

hodo

logy

alig

ned

tom

atch

know

nex

chan

geha

zard

s,pa

rtic

ular

lyth

ose

asso

ciat

edw

ithun

cert

aint

y(W

illia

mso

n,19

85;1

991)

Feed

back

Plan

Con

tinuo

uspr

oces

ses

for

chan

ging

inte

rfac

es,

appr

oach

esan

dat

titud

esto

war

dbe

tter

serv

ice

deliv

ery

stat

esw

ithin

ade

alba

sed

onle

arni

ngby

doin

g

• Sta

tem

ento

fho

wch

ange

sw

illbe

impl

emen

ted

base

don

mea

sure

men

tres

ults

• The

road

map

for

effic

ient

feed

back

onth

eid

entifi

eddr

awba

cks

• Pri

oriti

zatio

nm

etho

dolo

gyfo

rcu

rren

ttas

ksan

dfe

edba

cks

(Sin

glet

on,e

tal.,

1988

;K

ern

&W

illco

cks,

2002

;M

arco

lin,2

002)

Inno

vatio

nPl

anC

oope

rativ

ein

nova

tion,

espe

cial

lyjo

inte

ffor

tsat

cont

inuo

uspe

rfor

man

ceim

prov

emen

tand

plan

ning

• Pro

cess

for

inno

vatio

n,in

clud

ing

impl

emen

tatio

nan

dpr

iori

tizat

ion

• Pro

cess

for

tech

nolo

gyad

vanc

emen

ts(s

cope

impr

ovem

enta

ndte

chno

logy

refr

eshe

s/up

grad

es)

• Bus

ines

s-m

easu

red

inno

vatio

n(b

usin

ess

proc

ess

impr

ovem

ent)

(Mat

lus,

2002

;Kir

sch,

1997

;Cho

udhu

ry&

Sabh

erw

al,2

003)

Con

tinue

d

476 A Path to Successful IT OutsourcingT

ab

le1:

(Con

tinue

d)

Con

trac

tual

Con

trac

tual

Issu

esof

Cha

ract

eris

tics

Ele

men

tsof

SLA

SLA

inIT

Out

sour

cing

Cla

uses

inPr

actic

eSu

ppor

ting

Ref

eren

ces

Gov

erna

nce

:• M

echa

nism

sth

atm

itiga

tedi

srup

tions

(Will

iam

son,

1996

)

Mea

sure

men

tC

hart

erTa

ctic

alm

easu

rem

ents

for

calc

ulat

ing

and

reck

onin

gof

serv

ice

perf

orm

ance

asw

ell

assu

cces

sm

etri

csde

rive

dfr

omth

eSR

’sst

rate

gic

plan

.

• Sta

tem

ento

fm

easu

rem

ent

met

hodo

logy

• Defi

nitio

nof

wha

tis

tobe

mea

sure

d• D

efini

tion

ofpr

oces

ses

tope

riod

ical

lym

easu

reth

ede

fined

cate

gori

es• I

nter

face

sw

ithth

efe

edba

ckpl

an

(Mau

rer,

2001

;Sin

glet

on,

etal

.,19

88;O

uchi

,197

9;Su

sarl

a,et

al.,

2003

;Kir

sch,

1997

;Cho

udhu

ry&

Sabh

erw

al,2

003)

• Set

ting

and

chec

king

perf

orm

ance

targ

ets,

inte

rim

mile

ston

esto

ensu

reth

atth

ere

latio

nshi

pre

mai

nson

cour

se(O

uchi

,197

9;Su

sarl

a,et

al.,

2003

;Kir

sch,

1997

;Cho

udhu

ry&

Sabh

erw

al,2

003)

Con

flict

Arb

itrat

ion

Bal

ance

ofpo

wer

that

impo

ses

one’

sw

illon

othe

rs• A

stat

emen

tof

the

para

met

ers

for

invo

lvin

gth

eth

ird

part

yin

disc

ussi

ons

betw

een

the

SRan

dSP

• Pro

cess

desc

ript

ions

tode

term

ine

how

the

part

ies

inte

ract

• Asc

hedu

lefo

rre

gula

rin

tera

ctio

nsbe

twee

nth

epa

rtie

s,an

dtim

etab

les

for

reso

lvin

gis

sues

betw

een

the

SRan

dSP

• Ast

atem

ento

fth

epr

actic

esan

dco

nduc

trul

esre

quir

edto

pres

erve

the

inde

pend

ence

ofth

ein

depe

nden

tadv

isor

(Moh

r&

Spek

man

,199

4;D

wye

r,et

al.,

1987

;A

nder

son

&N

arus

,199

0;Fo

nten

ot&

Wils

on,1

997;

Lew

icki

&B

unke

r,19

96)

Con

tinue

d


Tab

le1:

(Con

tinue

d)

Con

trac

tual

Con

trac

tual

Issu

esof

Cha

ract

eris

tics

Ele

men

tsof

SLA

SLA

inIT

Out

sour

cing

Cla

uses

inPr

actic

eSu

ppor

ting

Ref

eren

ces

• Rew

ards

orsa

nctio

nsfo

rm

eetin

gor

mis

sing

the

targ

ets

(Kle

in,e

tal.,

1978

)

Com

mun

icat

ion

Plan

The

appr

oach

for

diss

emin

atin

gco

ntra

ct-r

elat

edin

form

atio

nto

allo

fth

epa

rtie

sin

volv

edin

the

rela

tions

hip

thro

ugh

sche

dule

din

tera

ctio

nan

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Governance characteristics (GCs)

GCs provide key interorganizational management mechanisms such as commu-nication protocols, reporting policies, and administrative procedures for disputeresolution, outcome assessment, information disclosure, incentives and penalties,and even termination options. They provide a structure for continually assessingthe value that the relationship generates to ensure that it remains on course (Ouchi,1979; Susarla, Barua, & Whinston, 2003). The four elements under this category—communication plan, measure charter, conflict arbitration plan, and enforcementplan—specify measures of service performance as well as tactical mechanismsand responses to enable the IT unit to manage components necessary to ensurethe goals of outsourcing relationships. As such, GCs not only allow the SR tocontinually verify that the services it receives match best practices in quality andcost, but also help resolve conflict through the processes specified in the contract.Because the emphasis is on procedures and measurements, contractual elementsunder GCs tend to be more relevant to bringing in IT skills and capabilities thanto elements related to linking IT to business results.

Commitment

However well structured, SLAs can have varying degrees of effectiveness acrossthe outsourcing engagements. This is because, although a well-designed SLAcan align contractual terms with outsourcing objectives, it does not necessarilycommit the participant firms to actual action. The need for commitment is furtherexacerbated in more complex relationships, where sophisticated SLAs are requiredto address multiple outsourcing objectives. Research has shown that as simpleoutsourcing arrangements evolve in complexity, the role of commitment increasesin helping to overcome the adaptive limits of the formal contracts (Hart, 1988;Kern & Willcocks, 2002; Poppo & Zenger, 2002; Sull & Spinosa, 2007).

Drawing on relational exchange literature (Dwyer, Schurr, & Oh, 1987;Morgan & Hunt, 1994), we define commitment as a party’s belief that an ongoingrelationship with another is so important as to warrant maximum effort at main-taining it. Research has found that commitment is important for the success of IToutsourcing (Grover, Cheon, & Teng, 1996; Lee & Kim, 1999; Koh et al., 2004).Commitment can guide the use of contracts to align actions in outsourcing relation-ships as well as provide the self-enforcing range of a contractual relationship bycoaching outsourcing partners to be proactive beyond what the contract suggests(Klein, 1996; Kern & Willcocks, 2002). Also, commitment encourages proceduralcoordination such as active communication, conflict resolution, and open exchangeof relevant ideas and feelings among participating firms. Commitment generateswillingness to make contractual adjustments in current services and the deliveryof new services by the SP when unforeseen circumstances justify modifications(Gundlach & Cadotte, 1994). In an environment fostered by commitment, con-tracts are modified over time, and, thus, ongoing learning by outsourcing partnerscan be sustained (Mayer & Argyres, 2004).

Although commitment is an important factor to IT outsourcing success, com-panies sometimes can be too committed in IT outsourcing relationships (Newman& Sabherwal, 1996; Sull, 2003). When an outsourcing relationship works well,


parties often commit to investing additional resources based on the expectationthat they will help attain the goal and the subjective expected value of goal at-tainment (Brockner, 1992). But such commitment and additional investment canmake it difficult to adjust to changing conditions and needs beyond the originalagreements (Williamson, 1983). For example, commitment increases the expec-tation of relationship longevity and reduces the desire for precise performancemeasurement in the short run. As a result, parties can lose sight of outdated pat-terns of operation. These situations are more likely to arise when the informationon past performance is ambiguous (Ross & Staw, 1986). Further, high level ofcommitment can put outsourcing arrangements into “reinforcement traps” (Ross& Staw, 1993), in which actions intended for near-term benefits impose lastingconstraints on IT operations and the organization. Therefore, it is important tounderstand the dynamics of commitment in IT outsourcing relationships and itsinteraction with other control mechanisms, such as SLAs, on outsourcing success(Sabherwal, 1999; Choudhury & Sabherwal, 2003).

Outsourcing Benefits and Success

Outsourcing success as a dependent variable is widely used in the literature. Fol-lowing Chandler’s (1962) conceptualization of intended strategy and Grover et al.’sdefinition (1996), the success of outsourcing is defined as the satisfaction with theintended benefits gained by an SR as a result of outsourcing activity. In practice,IT outsourcing success is, for the most part, operationalized as items of overallsatisfaction with promises stipulated in the contract (e.g., Saunders, Gebelt, &Hu, 1997; Susaria et al., 2003; Koh et al., 2004). Based on these findings, thesuccess measure is predicated on the intended benefits and outcome, which candiffer from one outsourcing engagement to another. Previous studies have placeda heavy emphasis on cost drivers in measuring outsourcing success (e.g., Loh &Venkatraman, 1992; Clemons, Reddi, & Row, 1993). More recent literature hasincorporated other types of outsourcing benefits, including business impact, usersatisfaction, economic benefits, IS improvement, technological capabilities, andcommercial options, to provide a more complete picture of outsourcing success(Saunders et al., 1997; DiRomualdo & Gurbaxani, 1998; Lee & Kim, 1999, 2005).This shift in focus on outsourcing benefits is expected, because, as the practice ofIT outsourcing becomes mature and more sophisticated, companies try to achieveperformance objectives and cost effectiveness at the same time in addressing broadstrategic concerns (e.g., Cross, 1995; McFarlan & Nolan, 1995; Grover et al., 1996;Clark, Zmud, & McCray, 1998; DiRomualdo & Gurbaxani, 1998; Quinn, 1999;Gottfredson et al., 2005 ). In other words, cost reduction or economics is no longer astand-alone driver since it underlies all benefit categories. Researchers have calledfor quality operationalization of outsourcing success via organizational benefits(e.g., Lee, Miranda, & Kim, 2004).

In this study, to measure success, we classify organizational benefits gainedfrom IT outsourcing into three categories that reflect and are consistent withthe trend in the existing body of outsourcing research: functional, strategic, andtechnological. Although these categories are different in focus, they are not or-thogonal: many types of outsourcing have multiple intended benefits, and some


outsourcing outcomes, business improvement for instance, would inevitably ex-hibit two or more sets of benefits. Functional benefits derive from the improvementof IT or MIS as a corporate function and are closely aligned with IS improvement(DiRomualdo & Gurbaxani, 1998) and user satisfaction (Lee & Kim, 2005). Whenpursuing such outsourcing benefits, companies hope to use the expertise of serviceproviders to provide effective and efficient IT functions, such as systems operationsand end-user support to internal users (Grover et al., 1996), in order to facilitateand support company operations and produce quality information or knowledgenecessary for management decision making. The functional benefits can usuallybe measured in the quality of IT output. Strategic benefits refer to the ability of acompany to use outsourcing to achieve its business goals and/or execute its strate-gies (DiRomualdo & Gurbaxani, 1998; Dibbern, Goles, Hirschheim, & Jayatilaka,2004). Such benefits can be derived from allowing the company to focus on itscore business by outsourcing routine IT activities, to deploy IT to significantlyimprove critical aspects of business performance, or to enhance innovations withIT outsourcing (DiRomualdo & Gurbaxani, 1998; Quinn, 1999; Gottfredson et al.,2005). When companies outsource customer relationship management, for exam-ple, they usually expect strategic benefits. Technological benefits refer to the abilityof a company to acquire, secure, and control IT capabilities and resources via out-sourcing. Such benefits include gaining access to leading-edge IT, avoiding the riskof technological obsolescence that results from dynamic changes in IT (Groveret al., 1996), and acquiring IT capabilities for agility (Sambamurthy, Bharadwaj,& Grover, 2003).

In the next section, the three variables discussed in this section—SLA char-acteristics, the independent variable; commitment, the moderating variable; andoutsourcing success and benefits, the dependent variable—are used to build ourresearch model.

MODEL AND HYPOTHESES

The objective of this study is to examine the effect of SLAs on the success of IToutsourcing and the role of commitment in such relationships. While drafting anSLA that includes all three characteristics and 11 elements might be a safe wayto take full advantage of SLAs, the optimal approach is to stipulate contractualelements that map to the SR’s desired goals or intended benefits (DiRomualdo &Gurbaxani, 1998). Our base model assesses the relationship between three differentcharacteristics of SLAs and IT outsourcing success as measured by three categoriesof intended benefits. Next, we extend the model to examine the moderating effectof commitment on the nature of the relationships between the SLA characteristicsand components of IT outsourcing success using hierarchical moderated regressionanalysis. We intend to determine how outsourcing success guided by SLAs variesas a function of commitment, which governs the adoption of actions necessary forcarrying out the elements of SLAs (Newman & Sabherwal, 1996; Sull, 2003). Theresearch model is illustrated in Figure 1 and discussed below.

To achieve functional benefits of IT outsourcing, it is crucial for both sidesto be clear about who is to deliver which services at what level. Such explicitlydefined objectives, ownership of functions, and requirements of the relationship is


Figure 1: Research model.

even more important when multiple SPs are involved (Gottfredson et al., 2005).Fox (1974) further argues that when common goals are shared, participants arecapable of allocating roles among themselves in light of what they perceive asfunctional necessities. Because the elements of CCs are concerned with the pro-cess of modifying the SLA terms to align them with the ongoing changes of therelationship (DiRomualdo & Gurbaxani, 1998; Kishore et al., 2003), they are notdirectly related to the delivery of functional objectives of outsourcing. However,service-level objectives and service content provide an unambiguous statementof required functional performance. Process ownership plans formalize and doc-ument the critical roles and the boundaries of responsibility. Therefore, FCs setclear standards of conduct by defining the roles and responsibilities of variousparties involved in the outsourcing arrangement and can enhance the performanceof IT function over time, as the SR and the SP learn more about each other’s rolesand delegations to be able to match expected service level to process ownership(Susarla et al., 2001; Miranda & Saunders, 2003). GCs help the SR to accuratelymeasure the performance of the functions provided by the SP and encourage theSP to meet the requirements via “carrots and sticks” provided in the conflict arbi-tration plan and enforcement plan. Moreover, the measurement charter can alsoreduce outcome uncertainty by explicitly providing desired performance and the


methodology for its measurement. The communication plan plays an importantrole in sustaining mutual benefits by ensuring information sharing and fosteringconfidence in the continued enhancement of functional outcomes (Mohr & Nevin,1990). Therefore, SLAs intended to achieve functional benefits should focus onthe FC and GC.

H1a: There is a positive relationship between the extent of foundation char-acteristics and functional benefits of IT outsourcing success.

H1b: There is a positive relationship between the extent of governance char-acteristics and functional benefits of IT outsourcing success.

Commitment has generally been considered as a complement for contractualcontrols (Poppo & Zenger, 2002). By stating the partners’ mutual goals and sharedexpectations, FCs motivate commitment in the outsourcing relationship for bothparties (Jap & Ganesan, 2000). Commitment, in return, reinforces the intentionof the FCs to ensure desirable functional outcomes by motivating the parties tofollow the SLA terms by resisting possible aggressive ex post incentives (Newman& Sabherwal, 1996) or hold-ups (Klein, 1996) that occur because of the boundedrationality of contracts. Moreover, consistency and durability of commitment en-courage decision makers and other individuals who inherit the responsibility toshare the intention of the relationship stated in the FCs of SLAs (Ring & Van deVen, 1994; Koh et al., 2004), stabilizing the relationship over time, and leading todesirable functional outcomes. In addition, commitment can encourage a mindsetof continuous fair dealing based on the elements of the FCs of the SLAs (McK-night, Cummings, & Chervany, 1998). For example, the process ownership planprovides the “relational cohesion” (Lawler & Yoon, 1996) that motivates parties toappreciate the value of FC provisions in the dynamic negotiations that lead to func-tional performance (Beaudry & Poitevin, 1994), and a high level of commitmentengenders mutual confidence in the ownership of functions and their obligations(Koh et al., 2004).

Commitment encourages both parties to continue a relationship even underconditions of high uncertainty (Helper & Levine, 1992). It thus motivates them tofollow the GC terms that lead to functional success of outsourcing. For example,when parties commit to the terms for defining and measuring outcomes set forthin the measurement charter, it is more likely that the relationship remains oncourse (Susarla et al., 2003) and that the desired IT functional outcome is attained(Singleton et al., 1988). In addition, commitment to the continued relationshipcan make the enforcement plan more effective, because the parties would take thelegal and economic consequences seriously. Moreover, because commitment canmotivate a desire to preserve a state of fair dealing, the mutually agreed arbitrationcharter under GC would be viewed as a proper way of preserving and deepeningthe relationship. Therefore

H1c: Commitment positively moderates the relationship between the extentof foundation characteristics and functional benefits of IT outsourcingsuccess.


H1d: Commitment positively moderates the relationship between the extentof governance characteristics and functional benefits of IT outsourcingsuccess.

Outsourcing arrangements intended to lead to strategic benefits tend to belarge, complex, and ambitious projects with complicated requirements that aredifficult to measure and can vary dramatically from one to another. This oftendemands a partnership where management controls rely on social enforcementsgrounded on the legal terms of the contracts (Fitzgerald & Willcocks, 1994).To attain high level of such benefits in outsourcing relationships, both FCs andCCs of the SLAs should be carefully negotiated, while GCs, which emphasizemeasurements and procedures in managing the engagement, are likely to havean insignificant impact on strategic goals and outcomes. The FCs specify theservice level, content, and ownership, and help both parties set clear objectivesand role responsibilities in the relationship while explicating common beliefs instrategic goals. These joint expectations, and the resulting psychological bonds,can move both parties toward the state of “embeddedness” that promotes theefficient use of time and resources and the adaptation of their complex integrativeagreements (Uzzi, 1997). The CCs specify behavioral guidelines for “agreeingto agree” throughout their outsourcing engagement despite intrinsic uncertaintiesin a strategic partnership. For instance, the future demand management plan andthe anticipated change plan foster bilateral expectations of willingness to makeadaptations as circumstances change. Such SLA elements instill parties with a highlevel of flexibility to incorporate contingencies, resulting in a relationship moreattuned to strategic benefits. Therefore

H2a: There is a positive relationship between the extent of foundation char-acteristics and strategic benefits of IT outsourcing success.

H2b: There is a positive relationship between the extent of change charac-teristics and strategic benefits of IT outsourcing success.

While FCs lay out general requirements and expectations and CCs govern theparties ex post incentives, commitment aligns the actions of the parties with thoseSLA terms to lead to desirable strategic outcomes, particularly when the uncertaintyin the level of required investments and the underlying risk and potential payoffsare high. For example, the future demand management plan and the innovation planunder CCs might not work properly as intended, because the cost of contractingfor contingencies associated with transaction uncertainty may seem so high thatthe parties choose instead to face the consequences of ex post problems (Anderson& Dekker, 2005). When parties commit to the relationship, they believe thattheir partners will not act opportunistically and view complying with provisionsfavorably. Therefore, commitment complements these two characteristics to helpattain strategic benefits through IT outsourcing by encouraging parties to worktoward preserving mutually agreed contracts even in the presence of potentiallyhigh-risk actions.


H2c: Commitment positively moderates the relationship between the extentof foundation characteristics and strategic benefits of IT outsourcingsuccess.

H2d: Commitment positively moderates the relationship between the extentof change characteristics and strategic benefits of IT outsourcing suc-cess.

IT as a resource is increasingly important as companies move to become agileand responsive to a dynamically changing business environment (Sambamurthyet al., 2003). Outsourcing arrangements intended to achieve technological benefitsare often motivated by the SR’s interest in acquiring access to cutting-edge tech-nologies and, thus, require frequent rebalancing and reorientation. Both parties,therefore, need to agree, at the outset, on mechanisms of managing evolving speci-fications (Choudhury & Sabherwal, 2003). FCs, focusing on service level, content,and ownership at the time of contract signing, are not directly concerned with suchdynamic relationships. CCs of the SLAs, on the other hand, are critical for achiev-ing the intended benefits of these highly uncertain or unstructured technical tasks.Furthermore, such contract terms, necessarily ambiguous at times, often lead toconfusion or even dispute. The GCs, which aim at mitigating disruptions, maintain-ing performance, and facilitating management in the life of the contract, becomeimportant complements. Consistent with the findings of Anderson and Dekker(2005), greater efforts to stipulate terms of the enforcement plan and avenues forlegal recourse in the event of disruption are desirable as the SR intends to takeadvantage of its market power to pick the best-of-breed technology suppliers tocontrol technological uncertainties (Cross, 1995). As the case of British Petroleumoutsourcing shows (Cross, 1995), this approach of using multiple suppliers makesthe SR less vulnerable to escalating commitment and outdated technology than ifit were tied to a single vendor, with the side effects that the SR must sometimescoordinate and resolve problems in replacing vendors. Thus, IT outsourcing agree-ments intended for technological benefits, assuming market competition amongsuppliers, require both CCs and GCs because they complement each other. That is,CCs build flexibility in the relationships (Ang & Beath, 1993; Lacity et al., 1995)while GC facilitates the management of multiple vendors. Therefore,

H3a: There is a positive relationship between the extent of change charac-teristics and technological benefits of IT outsourcing success.

H3b: There is a positive relationship between the extent of governance char-acteristics and technological benefits of IT outsourcing success.

Even though commitment has generally been considered a complement tocontractual controls (Poppo & Zenger, 2002), this may not be always the case.When seeking technological benefits, companies often continually verify that theservices it receives match best practices in quality and cost. However, becausedurability and consistency of commitment could reduce the incentive for execut-ing performance measurement underlying GCs in the short run, the outsourcingrelationship can lose sight of the outdated patterns of operation and miss out onthe best of breeds. Moreover, such best-of-breed approach favors renegotiating theterms with and switching among multiple suppliers. A high level of commitment


in a relationship with a certain SP is likely to make the process of renegotiatingwith or switching vendors unpleasant, time-consuming, and resource intensive. Asa result, commitment may limit the ability of CCs to recalibrate an outsourcingrelationship in order to seize emerging opportunities (Sull & Spinosa, 2007), mak-ing SRs vulnerable to outdated technology and less likely to attain technologicalbenefits (Sambamurthy et al., 2003). In addition, the “reinforcement traps” (Ross& Staw, 1993) that commitment may induce to stay in the existing form of rela-tionship may reduce the effectiveness of GCs and CCs for exploring leading-edgetechnologies among suppliers. Therefore

H3c: Commitment negatively moderates the relationship between the extentof change characteristics and technological benefits of IT outsourcingsuccess.

H3d: Commitment negatively moderates the relationship between the extentof governance characteristics and technological benefits of IT out-sourcing success.

RESEARCH METHODOLOGY

Data Collection

The study utilizes a “key informants” methodology for data collection (e.g., Pin-sonneault & Kraemer, 1993; Segars & Grover, 1998). In survey research, targetedrespondents assume the role of a key informant and provide information on aparticular unit of analysis (a single outsourcing contract in this study) by re-porting on group or organizational properties rather than personal attitudes andperception. This method relies on select members to provide information aboutan outsourcing setting. Informants were not chosen at random; rather, they areselected because they possess specific qualifications such as status, experience, orspecialized knowledge on SLAs (Venkatraman, 1989).

A potential problem in utilizing key informant methodology is the possiblelack of knowledge of the respondents regarding a particular issue, leading toconfounding results and erroneous conclusions (Huber & Power, 1985; Hufnagel &Conca, 1994). Therefore, in this study, we identified SRs that were actively engagedin IT outsourcing and implementing SLAs as well as individuals within those SRorganizations who were intimately involved with, and most knowledgeable about,the outsourcing activity. To do so, prerecruiting calls were made to IT professionalsusing contact information on the attendee list of a national outsourcing conferencein South Korea. We identified (i) organizations that undertook IT outsourcing usingSLAs within the last 5 years in Korea, (ii) the level in the organizational hierarchywhere most of the SLA management was concentrated, and (iii) the organizationalmember most knowledgeable about and with the highest amount of vested interestin outsourcing engagements. We found the IS executives (vice president, CIO,director, contract officer, the head of IT sourcing management team) to be the mostaccurate source of organizational information regarding IT sourcing decisions andthe implementation of SLAs. One hundred fifty professionals agreed to eitherparticipate in the survey or direct us to key informants involved in IT outsourcingarrangements using SLAs within the firm. E-mails containing the URL linked


to the Web-based online survey instrument were sent to them. To increase theresponse rate, the respondents were offered financial incentives as well as a reportthat summarized the results of the study. Of the 150 participants who agreed, 92(61.3%) completed responses (Table 3).

We first checked for respondent bias to ensure that respondents did notsystematically differ from nonrespondents. Based on the guideline suggested byBabbie (1990), the respondents and nonrespondents were compared with respect totwo key organization features: annual sales volume and number of employees. Forthis test, we randomly selected 50 firms each from nonrespondent and respondentfirms. The results of the t-tests for an analysis of respondent bias showed no sig-nificant differences between respondents and nonrespondents at the p < .05 level(King & Sabherwal, 1992), suggesting a lack of nonresponse bias. Further, theresponses were from a wide variety of industries, with the manufacturing sectorslightly overrepresented and the public/government sector slightly underrepre-sented ( Table 2). Forty-seven percent of the respondents were senior IT executivesand 41% were IT managers. Although preliminary steps were taken to ensureappropriate selection of key informants, a formal check was administered as partof the questionnaire (Kumar, Stern, & Anderson, 1993). Specifically, two itemsregarding key informant quality were used to assess the informant’s knowledgeabout the SLAs chosen and his or her involvement with IT outsourcing arrange-ments. The mean score for informant quality for each item was 5.60 and 5.80 outof 7, respectively, indicating that respondents were appropriate. As a result, allresponses were retained.

Operationalization of Constructs

All constructs in the survey were measured using multi-item scales with seven-point Likert rating systems. A conscientious effort was made to adapt existingmeasures validated from prior studies for the latent constructs in this research.Appendix A shows the measurement items used for the research variables in thisstudy.

We used the concept of perceived benefit to capture outsourcing success,the dependent variable in this research. Items were adopted from existing stud-ies (e.g., Grover et al., 1996; Lee & Kim, 1999) assessing the degree to whichSRs are satisfied with respect to three categories of benefits: functional benefitsmeasured (Cronbach’s alpha = .88) by the extent to which the quality of outputinformation was enhanced through the outsourcing of IT systems, strategic benefits(Cronbach’s alpha = .89) measured by the extent to which the business strategyof the SR was enhanced through outsourcing practices, and technological benefits(Cronbach’s alpha = .80) measured by the extent to which the SR gained accessto and control of world-class IT and hedged the risk of technological obsolescencethrough outsourcing practices.

Thirty-three items were directly adopted from earlier studies (Goo, 2008;Goo et al, 2008) measuring 11 elements of SLAs. They were then aggregatedto form three latent variables representing three characteristics, the predictors orindependent variables in this study. Commitment measures were based on Kumar,Scheer, and Steenkamps’ (1995) commitment criteria including inputs, durability,


Table 2: Demographic characteristics of respondents (N = 92).

Std.Characteristics Frequency Percentage Mean Dev.

Titles of RespondentsPresident 2 2.2%CIO/Vice President 11 12.0%Director/Asst. Vice President 30 32.6%IT Manager 38 41.3%Others 7 7.6%Not Mentioned 4 4.3%

Respondents’ Knowledge Regarding Current SLAs – – 5.60 1.04

Respondents’ Involvement in Outsourcing – – 5.80 1.08

Types of IndustryManufacturing 23 25.0%Banking/Finance/Insurance 17 18.5%Wholesale/Retail 4 4.3%Public/Government 1 1.1%Construction/Real estate 4 4.3%Transportation 4 4.3%Medical/Health Care 14 15.2%IT/Communication/Software 18 19.6%Undecided 7 7.6%

Sales Amount (Million)0–10 18 19.6%10–30 9 9.8%30–50 9 9.8%50–100 4 4.3%100–250 12 13.0%250–500 4 4.3%500–1,000 5 5.4%1,000–2,500 4 4.3%2,500–5,000 7 7.6%5,000–10,000 6 6.5%10,000 & above 3 4.3%Not Mentioned 10 10.9%

Number of Employees1–100 20 21.7%101–200 15 16.3%201–500 10 10.9%501–1,000 15 16.3%1,001–3,000 15 16.3%3,001–5,000 4 4.3%5,001–10,000 7 7.6%Above 10,000 5 5.4%Not Mentioned 1 1.1%


Table 3: The assessment of the measurement models: Evidence of convergent validity.

No Averageof Composite Variance

Constructs Items Reliabilitya Extracted Loadings (t-Statistics)b

Service-Level Objectives 3 .87 .69 .83 (19.01), .84 (17.33), .81 (12.47)Process Ownership Plan 3 .92 .80 .94 (62.93), .89 (32.61), .85 (22.68)Service-Level Contents 3 .91 .77 .90 (50.49), .89 (35.26), .83 (20.31)Future Demand Mgmt Plan 3 .93 .81 .89 (35.81), .90 (37.28), .91 (39.86)Anticipated Change Plan 3 .92 .80 .90 (42.75), .89 (29.37), .90 (35.02)Innovation Plan 3 .90 .75 .75 (8.94), .90 (37.87), .92 (52.41)Feedback Plan 3 .94 .84 .90 (43.50), .91 (19.15), .93 (52.56)Communication Plan 3 .93 .81 .88 (29.53), .91 (29.34), .91 (43.10)Measurement Charter 3 .93 .82 .90 (37.49), .89 (33.16), .92 (35.83)Conflict Arbitration Charter 3 .89 .73 .82 (14.18), .84 (28.00), .90 (28.37)Enforcement Plan 3 .91 .76 .87 (28.70), .91 (36.34), .84 (14.77)Commitment 7 .93 .64 .81 (18.75), .84 (21.51), .81 (18.78),

.78 (18.45), .74 (13.27), .82 (22.31), .81(22.04)

Functional Benefits 4 .93 .76 .87 (31.63), .87 (30.18), .86 (21.58), .89(33.87)

Strategic Benefits 3 .93 .81 .87 (29.12), .92 (43.57), .91 (47.63)Technological Benefits 3 .88 .72 .80 (15.29), .90 (48.18), .83 (22.07)

aThe composite reliability scores were calculated with the formula prescribed by Fornell and Larcker(1981).bp < .001.

and consistency. Seven items were used to assess the extent to which the partiesintended to become more deeply involved in the outsourcing relationship throughthe investment of capital and effort, the parties’ desire to continue an outsourcingrelationship because of positive regard toward the partner, and the parties’ intentionto remain in the relationship, which reflects the relationship’s stability. The itemsloaded on a single factor with a high internal consistency (Cronbach’s alpha = .89).

Two control variables that may influence IT outsourcing success are incor-porated into the analysis. First, the type of outsourced IT activity may affect thelevel and measurement of outsourcing success because of the different levels ofuncertainties and required investments associated with different IT activities. Sec-ond, the length of association with the outsourcing partner is included as a controlvariable to help minimize the potential effects of relationship duration that mayotherwise confound the results. As a relationship develops, a deeper level of un-derstanding of the nature of the services is expected. In addition, the longer theduration of association, the greater the probability of a higher quality relationship(Levinthal & Fichman, 1988) and, thus, the more likely outsourcing success.

Each of the constructs in the model exhibits convergent validity and discrim-inant validity. Convergent validity is adequate when constructs have an averagevariance extracted (AVE) of at least .5 and when items load highly (loading > .7)on their associated factors as well. Table 3 shows that the measures have signif-icant loadings that are much higher than the suggested threshold. For satisfac-tory discriminant validity, the square root of the AVE should be greater than thevariance shared among the target construct and other constructs in the model (Chin,


Table 4: Correlations of latent variables and evidence for discriminant validity.

SLO POP SLC FDMP ACP IP FP CP MC CAC EP C FB SB TB

SLO .83

POP .51 .89

SLC .60 .68 .88

FDMP −.39 −.61 −.56 .90

ACP −.35 −.56 −.40 .75 .90

IP −.36 −.41 −.37 .66 .75 .86

FP −.45 −.48 −.47 .69 .55 .60 .91

CP .48 .58 .56 −.56 −.47 −.46 −.68 .90

MC .54 .56 .68 −.61 −.38 −.49 −.67 .68 .91

CAC .40 .37 .35 −.57 −.53 −.61 −.67 .53 .55 .85

EP .31 .45 .45 −.34 −.23 −.26 −.15 .37 .28 .28 .87

C .54 .54 .56 −.37 −.24 −.31 −.43 .54 .60 .40 .39 .80

FB .58 .55 .50 −.41 −.32 −.28 −.48 .58 .53 .38 .25 .65 .87

SB .54 .46 .43 −.31 −.23 −.29 −.40 .43 .47 .27 .18 .51 .68 .90

TB .50 .50 .43 −.28 −.27 −.28 −.36 .47 .51 .41 .37 .49 .61 .65 .85

Note: Bolded diagonal elements are the square root of average variance extracted (AVE). Thesevalues should exceed the interconstruct correlations (off-diagonal elements) for adequate discriminantvalidity.Index: SLO = service-level objectives; PO = process ownership plan; SL = service-level contents;FDMP = future demand mgmt plan; AC = anticipated change plan; IP = innovation plan; FP =feedback plan; CP = communication plan; MC = measurement charter; CAC = conflict arbitrationcharter; EP = enforcement plan; C = commitment; FB = functional benefits; SB = strategic benefits;TB = technological benefits.

1998). The items demonstrate satisfactory convergent and discriminant validity(Table 4).

Data Analysis

We use hierarchical moderated regression analysis (MRA) as the methodologyfor testing both direct and moderating effects of the multiplicative model (e.g.,Sharma, Durand, & Gur-Arie, 1981; Carte & Russell, 2003). MRA with cross-product terms was our choice over ANOVA, because the latter, by forcing the datato be split into subgroups, would have wasted information and been inferior to themultiplicative model (McKeen, Guimaraes, & Wetherbe, 1994). In order to avoidthe risk of multicollinearity due to the use of cross-product terms, all independentvariables were “centered” (by subtracting their means) as suggested by Cronbach(1987).

As suggested by Carte and Russell (2003), to avoid the error of misinterpret-ing the result in MRA, commitment is modeled as a “pure” moderator as opposedto a “quasi” moderator. In other words, our cross-product terms take the form Y =X + X ∗ Z (i.e., pure-moderated model) and not the form Y = X + Z + X ∗ Z (i.e.,quasi-moderated model), where Y is one of three categories of benefits gainedfrom IT outsourcing, X is one of the three SLAs characteristics (FC, CC, andGC), and Z is commitment. This modeling approach is consistent with the prac-tice recommended by the literature that investigators must avoid quasi-moderatedmodel when interval scales are used, as is the case of this study (e.g., McKeenet al., 1994; Carte & Russell, 2003). The focus of this study is to test the intricateinteraction of commitment with SLAs in association with outsourcing success, not


the complement versus substitution between commitment and SLAs or whetherone dominates the effect of the other. Thus, commitment is not hypothesized todirectly impact success of IT outsourcing, and we can adopt the pure moderatedmodel consistent with the literature. We adopt “differential prediction,” where thenature of the X→Y relationship varies as a function of Z, as opposed to “differen-tial validity,” where the strength of the X→Y relationship varies as a function ofZ (Arnold, 1982; Baron & Kenny, 1986). MRA has been suggested as appropriatefor testing the moderation of differential prediction (Sharma et al., 1981; McKeenet al., 1994).

Prior to discussing the results, it is important to note that the decision to usethe subjective and retrospective self-report measures raises a legitimate concern ofcommon method bias (e.g., Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Self-reported data collected from the same source at one time may yield correlationsthat systematically contaminate data obtained from that source. However, relianceon key informants is the only realistic and feasible way to obtain data for this study,and thus the practical utility of same-source self-reported measures is inevitable inthe present context (Parkhe, 1993). We would merely observe that it would havebeen difficult to collect the data about perceptions of commitment through meansother than surveys. Also, because we chose to base the study on the nature of SLAsclauses, the success of outsourcing engagements must be viewed in the contextof their promise for achieving the goals of each organization. From a statisticalviewpoint, the common source data problem might not be as damaging so longas tests for interaction effects are included in the analysis (Evans, 1985). Thus,although we cannot totally rule out common method concerns, the reported resultsshould be considered in light of these concerns as well as the practical difficultiesinvolved in obtaining data from multiple methods.

The potential impact of common method variance was assessed by incorpo-rating two additional statistical analyses. Harman’s (1967) single-factor test wasperformed by loading all of the items in the study into an exploratory factor analy-sis. The results generated a large number of factors with the first factor accountingfor 18% of the covariance, indicating that there is not a substantial amount ofcommon method variance present. Furthermore, as suggested by Podsakoff et al.(2003), we reanalyzed the relationships between SLAs characteristic variables andoutsourcing success variables after adding the first factor, “partialing out” the vari-ance accounted for in the first factor. After conducting this procedure, we foundthat both the nature and significance of the results remained unchanged. Our resultsare with the first factor as a general variable explicitly added to the hierarchicalmoderated regression model.

Results

Having validated the measurement model, the next step was testing the hypothe-sized relationships among three SLA characteristics and three categories of out-sourcing success. Under each category of outsourcing success (i.e., three benefits),we tested both base and moderated model using the hierarchical MRA. The resultsare shown in Table 5. First, the base model examines the main effect of three SLAcharacteristics by assessing sign, statistical significance of the path coefficients,


Tab

le5:

Res

ults

.

Succ

ess

ofIT

Out

sour

cing

Func

tiona

lBen

efits

Stra

tegi

cB

enefi

tsTe

chno

logi

calB

enefi

ts

Hie

rarc

hica

lH

iera

rchi

cal

Hie

rarc

hica

lB

ase

Mod

erat

edB

ase

Mod

erat

edB

ase

Mod

erat

edM

odel

Mod

elM

odel

Mod

elM

odel

Mod

el

(Con

stan

t)1.

062

2.75

81.

173

2.42

31.

018

1.52

0Fo

unda

tion

Cha

ract

eris

tics

(FC

).5

31∗∗

∗.5

93∗∗

.668

∗∗∗

.634

∗∗SL

As

Cha

nge

Cha

ract

eris

tics

(CC

)−.

415

−.67

0.1

60∗

.262

Gov

erna

nce

Cha

ract

eris

tics

(GC

).2

23∗∗

−.54

1.7

21∗∗

∗1.

031∗∗

∗In

tera

ctio

nTe

rms

FC∗

Com

mitm

ent(

C)

−.03

5−.

038

CC

∗C

.086

∗∗∗

−.10

4∗∗G

C∗

C.1

13∗∗

−.08

1∗∗∗

Con

trol

Var

iabl

esTy

peof

ITA

ctiv

ity−.

051

−.05

3.0

59.0

52−.

010

−.01

3L

engt

hof

Ass

ocia

tion

.105

∗∗.0

87.0

55.0

35−.

004

−.00

9G

ener

alV

aria

ble

.081

.003

.431

.237

−.02

5−.

113

R2

.462

.522

.583

.624

.352

.407

�R

2.0

60.0

41.0

54F

Cha

nge

14.7

68∗∗

∗5.

314∗∗

∗8.

854∗∗

∗3.

412∗∗

9.35

8∗∗∗

3.85

6∗∗

Not

e:C

omm

itmen

t(C

)is

trea

ted

asa

pure

mod

erat

orin

the

mod

els

follo

win

gth

esu

gges

tion

byC

arte

and

Rus

sell

(200

3).

∗ p<

.1;∗∗

p<

.05;

∗∗∗ p

<.0

1.


and R2 in each model. Then the hierarchical moderated model tests the relativecontribution of moderating variables (cross-product terms) in explaining variationin outsourcing success, which was determined through both the increment in R2

and the significance of F statistics. In all analyses, unstandardized regression co-efficients were used, as recommended by Allison (1977). The results show that R2

for both base and moderated models ranges from 35% to 62%, indicating goodpredicting power of the models. All hierarchical models show increases in R2 andsignificant changes in F statistics, indicating that a significant moderating effectof commitment (C) exists on the nature of the relationships between SLAs andoutsourcing success. Specifically, R2 of each hierarchical moderated model incor-porating the interaction terms (i.e., FC∗C and GC∗C under functional benefits,CC∗C and GC∗C under strategic benefits, and CC∗C and GC∗C under technologi-cal benefits) is significantly greater than that of the base model (significance of Fchange = 5.314, p < .01; 3.412, p < .05; and 3.856, p < .05, respectively), indicat-ing commitment has significant moderation effect on the success of IT outsourcingwith respect to the three categories of benefits.

As hypothesized, both FC and GC contribute positively and significantlyto the functional benefits gained from IT outsourcing engagement (β = .531,p < .01; and β = .223, p < .05, respectively), supporting H1a and H1b. Forty-sixpercent of the variance in functional benefits of outsourcing success is explained bygovernance and FC of the SLAs. Table 5 shows that GC∗C contributes positivelyand significantly to functional benefits of IT outsourcing (β = .078, p < .01),supporting H1d: as modeled, commitment plays a role as a pure moderator uponwhich the relationship between GC and functional benefits of IT outsourcingis contingent. FC∗C turns out to be insignificant in the hierarchical MRA forfunctional benefits, rejecting H1c, while FC maintains its strong and significantimpact on functional benefits in the hierarchical moderated model (β = .593, p <

.05). Similarly, FC contributes positively and significantly to strategic benefits of IToutsourcing success in both base and hierarchical moderated models, supportingH2a (β = .668, p < .01). In contrast, relationships between CC and strategicbenefits are insignificant in both models, rejecting H2b. It appears that FC aloneexplains a fairly large portion of variance (34%) in strategic benefits of outsourcingsuccess in the base model. In the hierarchical MRA for strategic benefits, however,CC∗C contributes positively and significantly to strategic benefits of IT outsourcing(β = .086, p < .01), supporting H2d, whereas FC∗C turns out to be insignificant,rejecting H1c. In addition, the results show that after adding commitment as apure moderator, the nature of the relationship between CC and strategic benefitschanges. Contrary to our expectation, CC turns out to be negatively correlated(although statistically insignificant) to strategic benefits in the models. However,with the commitment interaction, CC positively contributes to strategic benefits ofIT outsourcing. Under technological benefits, both CC and GC contribute positivelyand significantly to IT outsourcing success in the base model, supporting H3a andH3b (β = .160, p < .1; β = .721, p < .01, respectively). Thirty-five percent ofthe variance in technological benefits gained from IT outsourcing was explainedby the direct effects of both CC and GC. The hypothesized negative interactionof commitment with both CC and GC of SLAs received strong support in thehierarchical moderated model (β = −.104, p < .05 and β = −.081, p < .01 forH3c and H3d, respectively).


DISCUSSION AND IMPLICATIONS

The objective of this study was to examine the effect of SLAs on the success of IToutsourcing and the influence commitment might have on such relationships usingcross-sectional survey data. Our study identifies three theoretically distinct setsof characteristics of SLAs for aligning the contractual elements with the intendedoutsourcing objectives. While the three characteristics can be complementary toone another, selective use of different contract terms relevant to the desired benefitswill more likely result in IT outsourcing success, as indicated by the differentialassociations between the three SLA characteristics and different types of outsourc-ing benefits. For example, when the objective of IT outsourcing is to enhance thequality of IT functions, contract terms related to FC and GC could be the moreeffective tool to achieve this goal. Such associations between contract terms andoutsourcing benefits provide a guideline for the future design of SLAs for outsourc-ing rearrangement. In so doing, this finding addresses a management dilemma inIT outsourcing: when negotiating an outsourcing relationship, the SLAs are of-ten kept short and basic—focusing on service elements and metrics—to maintainmanageability, limiting its many intangible benefits (Karten, 2004); or the partiesmay try to negotiate a comprehensive and full-featured SLA to take advantage ofits grand potential, running the risk of overcomplexity (Poppo & Zenger, 2002;Karten, 2004). Neither appears to be optimal. Our results show that managementcan take an approach that focuses on those key SLAs provisions that would benefitthe specific outsourcing objectives the most.

The study also aims to investigate the intricate interaction of commitmentwith the three sets of SLA characteristics to fill a gap in the existing literature, wherethe interaction of commitment with structural controls is commonly adopted in gen-eral (e.g., Beaudry & Poitevin, 1994; Kern & Willcocks, 2002; Lee & Kim, 2005),but no interactions with specific contract terms are studied. This investigationproduces a few results with significant theoretical implications and managementinsights. First, the nature of moderation effects varies with the different intendedbenefits of an IT outsourcing engagement. While commitment positively mod-erates the relationships between SLAs and both functional and strategic benefitsof outsourcing, the association between the SLAs and the technological benefitsof outsourcing is negatively moderated by commitment. Specifically, althoughcommitment enhances the use of CC and GC in attaining functional and strategicbenefits, respectively, it deteriorates the effect in achieving the technological ben-efits of IT outsourcing. This result suggests careful use of commitment in differentcontexts of IT outsourcing. In general, IT outsourcing, as compared to the tradi-tional, non-IT outsourcing, can use commitment to help overcome the adaptivelimits of the formal contract (Hart, 1988; Poppo & Zenger, 2002) because of thenature of such arrangements where two organizations cooperate toward ambigu-ous outcomes over the exchange of invisible assets (Itami, 1987). However, whenIT outsourcing is intended to provide fast-changing and highly uncertain tech-nological resources, it pays for the companies to stay agile by exploiting marketcompetition among providers (Sambamurthy et al., 2003), and a high level ofcommitment between two organizations in this context might become an obstacleto that end.


Figure 2: Mean response by groups (low commitment vs. high commitment).

The nature of moderation effects also varies with the different characteristicsof SLAs. First, we note that, contrary to our hypotheses, the associations of FCwith outsourcing benefits are not moderated by commitment. This finding can beexplained by the direct, clear-cut nature of the FC, where the service content, level,and ownership are specified. Similar to non-IT outsourcing, such contract termsare easy to follow and execute, and commitment becomes less of a factor in makingsuch a contract work.

Interestingly, CC behaves quite differently from the other two. We firstobserve that CC needs commitment to make it effective, as exemplified by one ofour results, where significant association between CC and strategic benefits onlyexists when commitment is present. This may be because, unlike the other two, CCcan be quite difficult to execute due to its complexity and future orientation and,thus, require all of the parties’ commitment to execution to actually make it work.We further examine the nature of CC by plotting the interactions between SLAscharacteristics and commitment in the case of technological success. We groupthe samples by dichotomizing commitment into two levels (high commitmentvs. low commitment) and graph the group means of technological benefits withextensiveness level (high and low) of both CC and GC. Our result is shown inFigure 2.

Figure 2 shows that, although commitment weakens the effects of both CCand GC on the attainment of technological benefits, the interactions are quitedifferent. In the case of GC, the mean score of technological benefits increases(albeit with small magnitude) in both levels of the commitment group, but thelines cross each other as the level of extensiveness of GC changes from lowto high. This finding indicates that, although GC clauses in the SLAs promotethe technological success of outsourcing, the marginal impact is reduced by theirinteraction with commitment. In the case of CC, in the low-commitment group, themean score of technological benefits increases (from 4.17 to 4.91) as the level ofextensiveness goes from low to high, indicating the positive role of CC in achievingthe technological success. However, in the high-commitment group, the mean scoreof technological benefits significantly decreases (from 4.73 to 3.51) as the levelof extensiveness of CC changes from low to high. That is, in a highly committed


outsourcing relationship, stipulating CC in SLAs actually negatively impact theattainment of technological benefits. One possible explanation of this nonintuitiveresult is that, clouded by the agility of obtaining leading-edge technology whilehighly committed to the service providers, outsourcing managers may be likely toview uncertainties and changes as external factors (e.g., due to regulation changessuch as Sarbanes–Oxley requirements), dampening the effect and quality of CC.Nevertheless, this anomalous finding deserves further theorizing and investigationin future studies.

CONCLUSION

The results of this study support the proposition that SLAs are positively associatedwith outsourcing success and that commitment moderates the effect of SLAs. Moreimportant, a well-structured SLA plays an important role in achieving the desiredoutcome of outsourcing, consistent with recent studies conducted by practitioners(Johnson & Rollins, 2004; Rodriguez, 2007). Our study implies an effective wayof structuring SLAs to achieve the desired outcomes in IT outsourcing. Based onthe three sets of SLA characteristics identified as theoretically distinct, our resultsshow the differential effects of these characteristics on the different componentsof IT outsourcing success classified as functional, strategic, and technologicalbenefits. We also confirm the important role of commitment in executing the SLAsby gearing the actions to achieve those ends. Moreover, we find that the natureof moderation effects of commitment varies with the different characteristics ofSLAs as well as the different benefits IT outsourcing engagement is to achieve. Inparticular, the interaction between change characteristics and commitment can beintricate and nonintuitive in effecting desired outsourcing benefits.

Our study contributes to the growing field of IT outsourcing research invarious ways. Theoretically, we identify distinct sets of SLA characteristics anddevelop a model to study their differentiated association with different types ofoutsourcing success, extending the existing literature of contracting in IT outsourc-ing (Wang et al., 1997; Gopal et al., 2003; Anderson & Dekker, 2005; Mani et al.,2006; Goo et al., 2008 ). We also present varied moderated effect of commitment,filling a gap in this stream of research. For practitioners, we show that focuseduse of contractual elements aligned with the intended benefits can be effective inattaining the desired benefits. Our findings provide a guideline for designing effec-tive SLAs for managing the inherent complexity and uncertainty of IT outsourcing.We also show that, although in general commitment would aid the effect of SLAs,caution must be exercised in certain cases (e.g., including change characteristicsin the hope of attaining technological benefits) where a high level of commitmentto the outsourcing relationship may actually hamper the odds of success.

As with all research, this study has limitations. First, the survey in this studywas aimed at organizations that implemented IT outsourcing through SLAs andsenior executives with vested interest in SLA outcomes. Although the samplingframe has been widely used in IS research, no claim of external validity forthis study’s findings can be made, and our findings can only be generalized tofirms within the sampling frame. In addition, the sample was composed of Koreandomestic organizations selected from the attendee list of an outsourcing conference.


We anticipate that there could be systematic differences among countries in draftingcontracts or SLAs. Therefore, generalizing the observed structure of SLAs toorganizations of other nations or beyond the sampling frame requires caution.

Although procedural and statistical remedies were incorporated to minimizethe possible illusory or halo correlation as discussed in the data collection, it is ap-propriate to note that perceptual data about SLAs and outsourcing projects used bythe respondents in their response could limit the generalizability of our study. Wedo not know the extent to which respondent opinions about their SLAs are valid.That is, respondent perceptions of their SLAs may be colored by their other per-ceptions about their relationships with their service providers. And other variables,such as the frequency of cooperation between the SR and the SP, may affect theresults. For future studies, therefore, we recommend inclusion of additional vari-ables as well as verification of respondent perceptions by comparing respondentscores on SLAs questions with scores given by an independent panel of expertsfor the presence of specific SLAs elements in a subsample of actual SLAs.

Another limitation of this study comes from our survey of only the SRside of the SR–SP dyad, including the use of SR’s perceptions about the SP’scommitment. However, such an approach has at least some degree of accuracy,as perceptions of one partner’s commitment are influenced by the other partner’sactual commitment. Both presumably reveal their true perceptions, intentions,and actions to each other during interactions over time (Anderson & Weitz, 1992).Nonetheless, we recommend that future studies investigate the perspectives of boththe SR and SP to improve our understanding of IT outsourcing arrangements.

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APPENDIX A: RESEARCH VARIABLES AND MEASURES

Constructs Items

Service-Level Objectives A statement of the SR’s management and organizationalstructure expectations at the end of the contract, once therelationship is fully operational (.673)

A statement of innovation expectations and capabilities of theservice provider (.733∗)

A statement of the service recipient’s (SR) business objectivesfrom the service (.803∗)

Process Ownership Plan Statement of process ownership roles and responsibilities(.695)

Inventory of processes that are required to manage theagreements between the SR and SP (.880∗)

Inventory of processes directly affected by the servicesincluded in the agreements (.913∗)

Service-Level Contents A statement of the key business measurements required by theSR (.591)

Established service-level/quality targets (.779∗)

A general description of the service required, major categoriesof services, and specific service elements (.849∗)

Future DemandManagement Plan

Processes for scheduling, costing, and modifying agreementswith new demand (.847)

The processes used to obtain end-user feedback on the SP’sdelivery of services that are provisioned to meet newdemand (.863∗)

The processes that the SR and SP will use to prioritize changesand modify the volume, type, or level of service to matchevolving user requirements (.845∗)

Continued


APPENDIX A: Continued

Constructs Items

Anticipated ChangeManagement Plan

Relevant technology, business, and industry drivers for change(.832)

Roles, responsibilities, and decision-making procedures of theSR and SP for each category of change (.792∗)

Clear definitions of the key categories of change (i.e.,predetermined change—e.g., charges for volume changes,computer updates, etc.) (.862∗)

Innovation Plan Process for innovation, including implementation andprioritization (.845)

Process for business improvement and technologyadvancements (e.g., scope, improvement, and technologyrefreshes/upgrades) (.931∗)

Innovation incentive (reward) programs (.683∗)

Feedback Plan Statement of how changes will be implemented based onmeasurement results (.875)

The road map for an efficient feedback on the identifieddrawbacks (.870∗)

Prioritization methodology for current tasks and feedbacks(.880∗)

Communication Statement of the communication policy (.816)

Plan Organizational reporting structure (.866∗)

Identified communication initiatives/initiative owners andrecipients for various communication initiatives (.908∗)

Measurement Statement of measurement methodology (.858)

Charter Definition of what is to be measured (e.g., price and servicebenchmarking clause, customer satisfaction, contract andrelationship alignment and vision, etc.) (.859∗)

Definition of processes to periodically measure the definedcategories (.813∗)

Conflict ArbitrationCharter

A statement of the parameters for involving the third party indiscussions between the SR and SP (.814)

A schedule for regular interactions between the parties, andtime tables for resolving issues between the SR and SP(.680∗)

A statement of the practices and conduct rules required topreserve the independence of the independent advisor(.852∗)

Enforcement Plan Penalty definitions and formula (.705)

Conditions under which termination may occur (.956∗)

Statement of exit responsibilities (.788∗)

Functional Benefits The SP has helped in increasing accuracy of outputinformation.

The SP has helped in increasing timeliness of outputinformation.

Continued


APPENDIX A: Continued

Constructs Items

The SP has helped in increasing relevancy of outputinformation.

The SP has helped in increasing reliability of outputinformation.

Strategic Benefits We have been able to refocus on core business.We have been able to enhance customer satisfaction and

loyalty.We have been able to introduce new ways to compete.

Technological Benefits We have been able to gain access to world-class keyinformation technologies.

We have been able to reduce the risk of technologicalobsolescence.

We have been able to enhance operating efficiency oftechnological resources.

Commitment Both parties are willing to commit resources to sustain therelationship.

If we requested it, SP would be willing to make furtherinvestment to support our needs.

We are willing to put more effort and investment in buildingour business relationship with SP.

Even if they could, SP would not drop our organization as aservice recipient (client) because they like being associatedwith us.

We want to remain a customer to SP because we genuinelyenjoy our relationship with them.

The continuation of a relationship with this SP is veryimportant to us.

SP expects the relationship with us to continue for a long time.Please provide a brief description of the IT services the SP

currently provides your organization

1. Application services 5. Network ManagementType of IT Activity 2. Systems integration 6. Disaster recovery

3. Data center management 7. PC management and maintenance4. Training and consulting 8. Company-specific application

developmentLength of Association How long is the contract term with the SP in years?

When did you start contracting IT services from the SP?

Notes: The numbers in parenthesis are standardized parameter estimates of SLA items forthe measurement validation. ∗p < .001.The first item loading in each latent construct is fixed at 1.00 and does not have a t-value.


APPENDIX B: A SUMMARY OF INDUCTIVE

CODING APPROACH

Axial coding is a set of procedures whereby data are put back together by makingconnections between categories in new ways after open coding (Strauss & Corbin,1990). This is done by using a coding paradigm that involves context, actionstrategies, and consequences (Figure B). Through the open coding, we first fracturethe SLA provisions or clauses into categories by grouping the similar contract itemsin actual SLAs, allowing us to identify different categories and their properties. Wethen map these categories to the 11 contractual issues identified through a prioritheoretical frameworks such as Ang and Beath (1993) and Macneil (1978). Axialcoding puts the data back together by making connections between the categories(i.e., SLA characteristics) and subcategories (i.e., 11 SLA elements), focusing onthe motivation that gives rise to a category, the context (or specific set of properties)in which it is embedded, the action strategies by which the provisions or processesare carried out, and the consequences of such strategies. In addition, each of thesefeatures is systematically examined with the hope of developing few overarchingcategories beyond properties and dimensions. In this process, common underlyingthemes are revealed in three categories, which we named as foundation, changemanagement, and governance characteristics of an SLA.

It is important to point out that we constantly move between inductive anddeductive thinking in the coding process. Specifically, we deductively proposecontractual issues in IT outsourcing and their dimensions. When working withactual SLA provisions, we attempt to verify what we have deduced against data.Such constant interplay between proposing and checking makes our SLA structureof characteristics and elements grounded.

Figure B: Axial coding for SLAs.


Jahyun Goo is an assistant professor of MIS in the Barry Kaye College of Businessat Florida Atlantic University. He received his PhD and MBA degrees in MIS fromthe School of Management at the State University of New York at Buffalo. Hisactive research areas are information systems (IS) sourcing, IT management andstrategy, interorganizational relationships, and IS Security. His papers have beenpublished or accepted for publication in MIS Quarterly, Decision Support Systems,Information Systems Journal, and Information Systems Frontier, among others.He has presented his research at ICIS, HICSS, AMCIS, ECIS, INFORS, etc. Hereceived a best paper award at HICSS 2007 and was nominated for a best paperaward at ECIS 2006. He is a guest associate editor of MIS Quarterly special issueon Cyber security.

C. Derrick Huang is an assistant professor in the Department of InformationTechnology & Operations Management in the Barry Kaye College of Business atFlorida Atlantic University. Previously, as a practitioner, he held executive-levelpositions in the area of marketing and strategic planning in a number of high-techcompanies. His research interest lies in the business value and strategic impact ofinformation technology in organizations, and his current focus is on the economicsof information security investments and the strategic management of informationsystems outsourcing. He holds a PhD from Harvard University.

Paul Hart is a professor and an associate dean in the Barry Kaye College of Busi-ness at Florida Atlantic University in Boca Raton, FL. He received his PhD fromthe University of Southern California. His research interests include informationtechnology and interorganizational relationships, and information privacy and se-curity. He has published in a number of journals including Information SystemsResearch and Organization Science. He is currently the division chair-elect of theOrganizational Communications and Information Systems (OCIS) Division for the2008 Annual Meeting of the Academy of Management.

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