Minnesota State University, Mankato Minnesota State University, Mankato

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and Creative Works for Minnesota and Creative Works for Minnesota

State University, Mankato State University, Mankato

All Graduate Theses, Dissertations, and Other Capstone Projects

Graduate Theses, Dissertations, and Other Capstone Projects

2016

IT Centralization and the Innovation Value Chain in Higher IT Centralization and the Innovation Value Chain in Higher

Education: A Study for Promoting Key Innovations Through Education: A Study for Promoting Key Innovations Through

Innovation Management and Organizational Design Innovation Management and Organizational Design

Edmund Udaya Clark Minnesota State University Mankato

Follow this and additional works at: https://cornerstone.lib.mnsu.edu/etds

Part of the Computer and Systems Architecture Commons, Higher Education Commons, and the

Organizational Behavior and Theory Commons

Recommended Citation Recommended Citation Clark, E. U. (2016). IT Centralization and the Innovation Value Chain in Higher Education: A Study for Promoting Key Innovations Through Innovation Management and Organizational Design [Doctoral dissertation, Minnesota State University, Mankato]. Cornerstone: A Collection of Scholarly and Creative Works for Minnesota State University, Mankato. https://cornerstone.lib.mnsu.edu/etds/652/

This Dissertation is brought to you for free and open access by the Graduate Theses, Dissertations, and Other Capstone Projects at Cornerstone: A Collection of Scholarly and Creative Works for Minnesota State University, Mankato. It has been accepted for inclusion in All Graduate Theses, Dissertations, and Other Capstone Projects by an authorized administrator of Cornerstone: A Collection of Scholarly and Creative Works for Minnesota State University, Mankato.

ITCentralizationandtheInnovationValueChaininHigherEducation:AStudy

forPromotingKeyInnovationsThroughInnovationManagementand

OrganizationalDesign

EdmundUdayaClark

ThisDissertationisSubmittedinPartialFulfillment

oftheRequirementsfor

theEducationalDoctorateDegree

inEducationalLeadership

MinnesotaStateUniversity,Mankato

Mankato,MN

(ApprovedMay,2016)

ii

Date:May2,2016

Thisdissertationhasbeenexaminedandapproved.

ExaminingCommittee:

__________________________________________________Dr.CandaceRaskin,Advisor

__________________________________________________Dr.JasonKaufman,CommitteeMember

__________________________________________________Dr.ScottWurdinger,CommitteeMember

iii

Abstract

Thepurposeofthepresentstudywastoinvestigatetheimpactof

organizationalcentralizationinhighereducationtechnologysupportunitson

institutionalinnovativeness.Thecentralizationtoolsusedforthepresentstudy

includedmeasuresdevelopedbyHage&Aiken(1971),Kaluzny,etal.(1974),and

Ferrell&Skinner(1988).TheinnovativenessmeasureswereestablishedbyHansen

&Birkinshaw’s(2007)toolforevaluatinginnovationvaluechainactivitiesin

organizations.Dataweregatheredfromanation-widesample(n=303)ofIT

workersat38researchoneinstitutionsintheUnitedStates.Theresultsindicated

thatinnovationvaluechainactivities(ideageneration,conversion,anddiffusion)

werenegativelyimpactedascentralizationincreased.However,thesefindings

variedsignificantlybythetypeofinstitutionbeingmeasured,thephaseofthe

innovationvaluechainbeingstudied,andthetypeofreportinglineforeach

participant.

iv

Acknowledgements

“Darknesscannotdriveoutdarkness:onlylightcandothat”(MartinLuther

King).Thankstomycommittee,CandaceRaskin,JasonKaufman,andScott

Wurdinger,andtheentirefacultyoftheEducationalLeadershipprogramfor

teachingmetoshinethelightofknowledgeonthemostimportantissuesin

education.

“Comingtogetherisabeginning;keepingtogetherisprogress;working

togetherissuccess”(HenryFord).ThankstomyveryspecialEducational

Leadershipdoctoralcohort,RobbieBurnett,KellyKillorn,JayMeiners,Kenneth

Turner,BeVang,MeganWeerts,KaylaWestra,andWayneWhitmoreforcoming

together,keepingtogether,andworkingtogether;teachingmesomuchandfor

inspiringmealongtheway.

“Doyoureallywanttolookbackonyourlifeandseehowwonderfulitcould

havebeenhadyounotbeenafraidtoliveit?”(CarolineMyss).Thankstomy

parents,Edmund&ChouwaneeClark,andmychildren,Adam,Audrey,Jackson,and

John,foralwaysbelievingthatIcandoanything.

“Ourchiefwantissomeonewhowillinspireustobewhatweknowwecould

be”(RalphWaldoEmerson).Thanksfinallytomywife,DonaClark,foralways

inspiringmetofindandbecomethebestversionofme.

v

TableofContents

Abstract………………………………………………………………………………….iii Acknowledgements……………………………………………………………………...iv List of Figures…………………………………………………………………………...vi Chapter I - Introduction…………………………………………………………….…..1

Background of the Problem……………………………………………….…….1

Purpose Statement….……………………………...…………………………….6

Delimitations and Limitations…………………………………………………..7

Definition of Key Terms…………………………………………………………7 Chapter II - Review of the Literature…………………………………………………..9 Chapter III - Method…………………………………………………………………...35 Chapter IV - Results……………………………………………………….…………...41 Chapter V - Discussion…………………………………………………….…………...51 References……………………………………………………………………………….61 Appendix A - Centralization Assessment Combination Instrument………………...79 Appendix B - InnovationValueChainSurvey………………………...……………81

vi

List of Figures Figure 1 - A Model of Five Stages of the Innovation-Decision Process………..…….22 Figure 2 – Innovation Value Chain Models…………………………………………...25 Figure 3 – R1 University Locations…………………...……………………………….37 Figure 4 – Respondent Demographics…………………...………………………...….42 Figure 5 – Distribution of Participation in Decision-Making scores …………….….43 Figure 6 – Distribution of Hierarchy of Authority scores ………………..………….45 Figure 7 – Distribution of Centralization scores ………………….………………….45 Figure 8 – Innovation generation, conversion, and diffusion as a function of centralization……………………………………………………………………………46 Figure 9 – Correlation plots for centralization to generation, conversion, and diffusion …………………...………………………………………………………….……………52

1

ChapterI

Introduction

BackgroundoftheProblem

Theimportanceofinnovationmanagementforhighereducation

organizationshasneverbeenmorecritical.Avarietyoffactorshavecombinedto

presentnewchallengesforAmericanuniversities,particularlypublicuniversities.

Thesechallengesconsistofaseaofdemographicchanges,combinedwitha

correspondingchangeinstudentneedsanddesires(Snyder&Dillow,2015;

Desrochers,etal.,2010).Thereisatrendofdecreasingfundingfromstatesfor

publiceducationthathaspersistedsince1980(Mortenson,2012).Thesefunding

changeshavebeenaccompaniedwithaccountabilitydemandsforincreased

efficiencyandgreaterstudentoutcomes,fromgraduationratestoemploymentat

graduation(Huisman&Currie2004;King,2007;McLendon,Hearn,&Deaton,

2006).Theentriesofnewprivateandfor-profitinstitutionshavecreatedanintense

levelofcompetitionforstudentsaroundtheglobe(Hemsley-Brown&Oplatka,

2006;Dill,2003).Finally,rapidchangesintechnologyhaveaffordednew

opportunities,butmanyinstitutionshavestruggledtokeeppace(Boezerooij2006;

Kassens-Noor,2012;Al-Qahtani&Higgins,2013;Merchant,etal.2014).

Manyscholarshavestudiedthesefactors—fromaccountabilityto

demographicsandtechnologicalprogress—andmeasuredtheirimpactsonhigher

education.However,asresearchersprobethesetrends,newgapsintheliterature

haveemerged.Forexample,haveaccountabilitydemandsandfundingshortfalls

madeuniversitiesmoreorlessinnovative?Someuniversitieshavedecidedto

2

decentralizeacademicunitsintoself-sustainingspin-offs,whileothershavedecided

tocentralizecontrolasmuchaspossible.Havecutsinstudentandfacultysupport

impactedtheabilityofschoolstoadaptswiftlytoemergingchallenges?Which

modelsworkbesttopreservetheabilitytogenerate,adopt,anddiffusenewideas?

Theissuespresentedbythesequestionsarecompoundedwhennational

demographicchangesarealsotakenintoaccount.Theblendofwhiteandnon-

whitestudentshaschangeddrasticallyoverthepast20years,withanincreasingly

highpercentageofincomingstudentsrepresenting“at-risk”populations(Gavigan,

2010;Klemencic&Fried,2015).Thesestudentssufferfromagreaterrateof

attritionthantraditionalstudents,andrequireincreasedattentionand

interventionsinorderforthemtosucceed(Jones&Watson,1990).Whiletheterm

“at-risk”broadlyencompassesalargepopulationthatincludesfirst-generation

students,studentsfromlowersocio-economicbackgrounds,immigrantstudents,

andstudentsofcolor,thereisevidencethatagreatmanystrategiesmustbe

employedandtailoredtopromoteretentionineachofthesesegments(Dumbrigue,

Moxley,&Durack,2013).

Furthermore,incomingstudentshavedifferentneedsandwantsinregardto

technologythantheyhaveinpastgenerations.Thesestudentshavebeen

collaboratingelectronicallysinceaveryyoungage,usingcloud-basedservices

providedbyGoogleandMicrosoft.Theyhaveturnedinassignmentsonlinesince

the3rdgrade,andaccessedtheirgradesandassignmentsviatheweb.Theaverage

childhashadacellphonesinceage10andmorethanhalfofthesechildrenusea

smartphonetoaccesssocialmediaandinteractwiththeirpeers(Boerma,2014).

3

Accompanyingthischangeinstudentsisadynamicrateofchangeinthe

technologiesavailabletoconsumers.Bandwidthavailabilityandusagehas

quadrupledin10years.ThelastdecadehasseentherapidconversionofDVDsto

Blu-Raydiscstopurelystreamingmedia.Cableandsatelliteprovidersconfronta

newgenerationofcustomersthathavenointerestintheirofferings,otherthanthe

bandwidththattheycanprovidetoaccessonlinesitesandservices(Steel&Marsh,

2015).Highdefinitionvideohasmorethanquadrupledinresolutionandvirtual

realityispoisedtobecomeanewstandardforinteractingwithdigitalmedia(Sydell,

2016;Kuusisto,2015).

Asnewtechnologieshaveemerged,sohavenewplayersinthehigher

educationspace.For-profit,fullyonlineuniversitiesliketheUniversityofPhoenix

andCapellamadehugesplashesinitially,butcurrentlyfacestiffchallengesinthe

formofpoorstudentoutcomes,highdebt,andacriticalfederalgovernmentstance

(Lam,2015).However,otherplayerslikeEdXandCourserahavepartneredwith

large,prestigiousuniversitieslikeStanfordandMITtodeliverinstructioninnew

formatslikeMOOCs(massivelyopenonlinecourses),self-pacedmodules,and

adaptivelearningapproaches.Whiletheseofferingsaddprestigeandserveas

valuablemarketingtoolsforthemosteliteinstitutions,thevastmajorityofschools

havenotbeenparticipantsinthesenewpartnerships(Hampson,2012).

Institutionalresponsestothesechallengeshavebeenvariedandconsistofa

widerangeofapproaches,successes,andfailures.Responsestobudgetreductions

haveincludedcentralizationeffortsandspin-offsofprofessionalschools.Data

analyticsandlearneranalyticshavebeenmadepossiblebynewsoftwareplatforms

4

andhavebeenadoptedbymostinstitutionstomeettheneedsofchangingstudent

demographics.Thesetoolshavebeenusedtoimproverecruitmenteffortsaswellas

theretentionofexistingstudentsateachcollege(Creasey,2008).Manyschools

havelaunchedonlinecoursesandprogramstomatchtheconvenienceofferedby

for-profitonlineinstitutions.Mosthaveadoptedsomeamountofblendedor

technology-enhancedlearningapproaches,whichutilizetechnologicalaffordances

toprovidebetterlearningexperiences.Finally,agrowingnumberofinstitutions

haveestablishedinstructionalinnovationcenterstosupportfacultyinadoptingnew

approachestoteachingandlearning,fromonlinecoursestoflippedclassrooms,

wherelecturesarepre-recordedandpresentedonlinewhileclasstimeisusedfor

in-depthdiscussions(Graham,Woodfield,&Harrison,2012).However,despite

theseattemptstoinnovate,manycollegeshavefailedtosurvivethiscombinationof

criticalstresses.AMoody’spredictionforecaststhattheclosureofsmallcolleges

anduniversitieswilltripleto15peryearby2017(Woodhouse,2015).

ProblemStatement

Alargebodyofevidencehasdemonstratedthecriticalimportanceof

innovationtoorganizations(Borins,1998,2001;Andrewsetal.,2006;Christensen

etal.,2004;Damanpouretal.,2009;Tiddetal.,2001).Furthermore,scholarshave

alsoidentifiedmanyproblemsinvolvedinsuccessfullyimplementingthese

innovations(Ensminger,2005;Griffith,Zammuto,&Aiman-Smith,1999;Meyer&

Goes,1988;Surry&Ely,2002;Polley,etal.,1999),includingtheculturaland

resourcebarrierstoimplementationwithinorganizations(Aubert&Hamel2001;

Denis,etal.,2002;Heide,etal.,2002;Fennell&Warnecke1988;Rogers2003).

5

However,thereisverylittleresearchthatprovidesguidanceonhoworganizational

structurescaninfluencethelikelihoodofimplementationofkeytechnological

innovations(Damanpour&Wischnevsky2006;Tidd,2001).WhileDamanpour’s

(1996)researchmappedthebroadimpactofcentralizationoninnovativenessin

largeandsmallfirms,DamanpourandWischnevsky’s(2006)papersuggeststhat

unitswithinanorganizationcanalsohavelargeimpactsontheinnovationcycle:

“Futureresearchonthegenerationofinnovationshouldcompareand

contrastindependententrepreneurialorganizationswiththeautonomous

unitsofestablished,largeorganizationsengagedinthegenerationof

innovation—notwiththoseorganizationsintheirentirety”(p.279).

Giventhatinstitutionsofhighereducationareorganizeddifferently,andthat

technologysupportorganizationsinsideeachinstitutionarealsoorganized

differently,thereisaneedtofurtherunderstandhowthesestructuraldifferences

mayimpactinnovationgenerationanddiffusionrates.Currentliteratureon

innovationhasfocusedonmanyfactorsthatmaypromoteadoptionanddiffusionin

organizations.However,verylittleresearchhasbeendoneinunderstandingthe

impactofthesenewchallengesinpublichighereducationonorganizational

innovativeness,specifically:accountability,fundingchanges,demographicchanges,

increasingcompetition,andrapidtechnologychanges.Furthermore,scarce

researchhasbeenconductedinmeasuringthevalueofcommoninstitutional

responsesandtheirpositive(ornegative)impactsonorganizationalinnovativeness.

Moreover,literatureoncentralizationhasgenerallyunderestimated(ornot

considered)theroleofsubunitswithinagivenorganization,andhasnottypically

6

includedhighereducationasanareaofstudy.Itisimportanttoisolateaspectsof

centralizationthatcanbecontrolledbyhighereducationinstitutionsandthatalso

havelargerimpactsontheinnovationprocess.Finally,theinnovationvaluechain,

whichdescribesinnovationasaprocessprogressingfromideagenerationto

conversiontodiffusion,islikelytobegreatlyimpactedbythelevelofcentralization

oftechnologysubunitswithinhighereducationinstitutions.Thisconnectionhas

notbeenexploredinpreviousresearch.

PurposeoftheResearch

Thepurposeofthisresearchistomeasuretheimpactofcentralizationin

publichighereducationtechnologysupportunitsontheirrespectiveinstitutions’

abilitiestogenerate,convert,anddiffusenewinnovations.Understandingwhat

organizationalapproacheswouldenhanceeachphaseoftheinnovationprocess

couldincreasethecapabilitiesofdeeplystressedinstitutionstosurviveinarapidly

changingenvironment.

Hypotheses

Hypothesis1.Thisstudyhypothesizesthatmoredecentralizedtechnology

structureswillshowgreatereffectivenessduringtheideagenerationphasethan

morecentralizedstructures.

Hypothesis2.Thisstudyhypothesizesthatmoredecentralizedtechnology

unitswillshowgreatereffectivenessduringtheideaconversionphasethanmore

centralizedstructures.

7

Hypothesis3.Thisstudyhypothesizesthatmorecentralizedtechnology

structureswillshowgreatereffectivenessduringthediffusionphasethanmore

decentralizedstructures.

Hypothesis4.Thisstudyhypothesizesthatmorecentralizedtechnology

structureswillshowlowereffectivenessforallthreephasesoftheinnovationvalue

chainthanmoredecentralizedstructures.

Hypothesis5.Thisstudyhypothesizesthatparticipationindecisionmaking

measureswillshowmoresignificantcorrelationswithinnovationvaluechain

phasesthanhierarchyofauthoritymeasures.

SignificanceoftheResearch

Thisstudywillilluminatethestrengthsandweaknessesofspecificand

controllableaspectsofcentralizationforfaculty,staff,andadministratorshopingto

utilizenewtechnologiestoachievetheirrespectiveinstitutionalgoals.Theresults

fromthisstudywillhelpcollegesanduniversitiestochooseanddesign

organizationalstructuresandprocessestohelppromotekeyinnovations,while

providingthemwithabroaderunderstandingofthestrengthsandweaknessesof

theircurrentorganizationalmodels.Specificaudiencesthatwillbenefitmostfrom

thisresearchincludepresidentsandadministratorsatR1institutions.

Delimitations

Thisstudywillonlyincludedatafromresearchone(R1)institutionsinthe

UnitedStates,whichmaynotbegeneralizabletoschoolsthatfallintoother

categories(e.g.,private,Master’scomprehensive,etc.).

DefinitionofKeyTerms

8

Centralization.Forthepurposesofthisstudy,thistermisdefinedasameasureof

both1)participationindecisionmakingand2)hierarchyofauthorityinagiven

organization.

Innovation.Forthepurposesofthisstudy,thistermisdefinedas“anidea,practice,

orobjectthatisperceivedasnewbyanindividualorunit,”which“presentsanew

alternativeoralternatives,aswellasanewmeansofsolvingproblems”(Rogers,

2003).

InnovationValueChain.Forthepurposesofthisstudy,thistermisdefinedasa

viewofinnovationas“asequential,three-phaseprocessthatinvolvesidea

generation,ideadevelopment,andthediffusionofdevelopedconcepts”(Hansen&

Birkinshaw,2007).

9

ChapterII

LiteratureReview

Publichighereducationinstitutionsfaceavarietyofintensifyingpressures,

fromstateaccountabilityregimesandchangingstudentdemographicstonew

competitorsandpotentiallydisruptivetechnology-basedapproaches.These

pressureshaverequireduniversitiestoconsidernewwaysofdoingbusinessin

ordertoremaincompetitive.Asthesepressuresmount,differentinstitutionshave

optedtocentralizeordecentralizeoperationswhileattemptingtoincreasetheir

organizationalinnovativeness.Undertheseconditions,itisreasonabletoassume

thatpublichighereducationinstitutionswoulddesiretounderstandthepotential

impactsoftheircentralizationanddecentralizationdecisionsontheirabilitiesto

managetheinnovationprocess.

Thisstudywillfocusspecificallyontechnologyserviceunitcentralizationin

publichighereducation(asmeasuredbycentralizationsurveytoolscreatedby

Hage&Aiken(1971),Kaluzny,etal.(1974),andFerrell&Skinner(1988))andthe

relationshipofthisrelativecentralizationtoinnovationmanagementpractices

withintheseinstitutionsasdeterminedbyHansen&Birkinshaw’s(2007)

InnovationValueChain(IVC)tool.Consequently,thisreviewoftheliteraturewill

focusonthreeprimaryareasofinterest:1)accountability,funding,demographic,

andcompetitivepressuresinpublichighereducationthathaveledtocallsforrapid

changes,2)centralizationandtoolsforunderstandinglevelsofcentralization,the

importanceofsubunitsinorganizations,andthelinkageofsubunitswithimpactsin

technologyadoptionmodels,and3)studiesthathighlightthecurrent

10

understandingoffactorsthatleadtoinnovationgeneration,conversion,and

diffusion;alongwithananalysisoftheinnovationvaluechainframework.This

chapterwillthenconcludewitharationaleforthepresentstudy.

PressuresonPublicHigherEducationandInstitutionalResponses

Accountability.U.S.publichighereducationinstitutionsareunder

increasingpressurefromtheirrespectivestategovernmentstojustifytheirfunding

(Spellings,2006).Infact,approximately50%oftheUnitedStateshadimplemented

accountabilityprogramsforpublichighereducationinstitutionsby2013

(Dougherty,etal.,2013).Stateaccountabilityregimesgenerallyarecomposedof

twocategoriesofdemands:1)callsforincreasedefficiency,and2)callsforbetter

studentoutcomes.Inthefirstcategory,legislativeaccountabilitymeasuresoften

includedemandsfordecreasedadministrativecostsandincreasedoperational

efficiency(Leveille,2006).Oneresultofthesedemandsisatrendtoward

centralizationofoperationsandsupportunitsatmanyinstitutions(Geiger,2015).

Someinstitutions,liketheUniversityofMinnesota,havebeenpubliclyshamedfor

theiradministrativebloat(Belkin&Thurm,2012).Inresponse,theUniversityof

Minnesotapromisedtocentralizeoperationsandcutmillionsinadministrative

costs.Similarly,otherlargeinstitutions,fromArizonaStateUniversitytothe

UniversityofTexasatAustin,havefocusedonreducingadministrativecostsand

relatedpositions(Lindsay,2015).

Thesecondcategoryofaccountabilitydemandscallforbetterstudent

outcomes,includingretention,graduation,andemploymentrates(Huisman&

Currie2004;King,2007;McLendon,Hearn,&Deaton,2006).The2016report,

11

“AmplifyingHumanPotential:EducationandSkillsfortheFourthIndustrial

Revolution”,commissionedbyInfosyscorporation,foundthatformercollege

studentsaroundtheglobearequestioningwhethertheireducationsadequately

preparedthemfortheircareers(Infosys,2016).Thepressurecomesnotonlyfrom

studentconsumersandstatelegislators,butalsofromnationalbodies,includingthe

U.S.DepartmentofEducation(DOE).In2006,theDOE’sReport“ATestof

Leadership:ChartingtheFutureofU.S.HigherEducation”calledforincreased

accountability,access,andaffordabilityinhighereducation(Spellings,2006).

Creasey(2008)writesaboutthetrend:

Recentlyhighereducationadministratorshavebeenheldaccountableto

provide(a)measurements,(b)process,and(c)policy.Moreover,

administratorsareexpectedtorespondtochancellors,provosts,boards,and

committeesto(a)justifyexpenditures,(b)engageinstrategicplanning,(c)

managetheirorganizations,and(d)understandthevalueofITinvestments.

(p.1)

Thisheightenedoversightofuniversitiesandcollegesextendsfromensuring

thealignmentofbusinessprocesseswithITinvestments,to“demonstratingthe

impactoftechnologyonstudentlearningoutcomes”(Creasey,2008,p.1).These

pressures,bothfromnewgenerationsofstudentsandfaculty,aswellasfromstate

andnationalorganizations,callforincreasedintegrationoftechnological

innovationsatinstitutionsofhighereducation.

DemographicChangesandIncreasedCompetition.National

demographicshavealsobeenafactorinthecallsforchange.TheUSDepartmentof

12

EducationrecentlyfoundthatthepercentageofstudentsofcolorinAmerican

collegeshasrisendramaticallyfrom1976to2011,whilethepercentageofwhite

studentshasdeclinedfrom84%to61%(Snyder&Dillow,2015;Desrochers,etal.,

2010).

Manyofthesegrowingpopulationsfallunderthecategoryofat-risk

students,whichrequirenewandimprovedapproachestotheireducation(Gavigan,

2010).KlemencicandFried(2015)describeadecliningdomesticpopulationof18-

24yearoldsintheUnitedStatesalongwitharapidlyincreasingagingpopulation.

SiemensandMatheos(2012)writeoftheimplicationsofapopulationexplosionin

Asiaandafocusonskills-basededucationinaneverexpandingtechnological

environment.KlemencicandFriedconclude:

Competitionfor…studentsamonghighereducationinstitutionswillbecome

stronger,creatingincentivesfortherecruitmentofforeignstudentsandfor

supplementingthetraditionalstudentswithlifelonglearners.Thus,higher

educationinstitutionswillhavetoadjusttheiracademicprogramsand

organizationalstructuresandbecomemorepermeable,de-emphasizingtheir

socialselectivityandaccommodatingtheneedsofanincreasinglydiverse

studentpopulation.(p.13)

Intensecompetitionisanotherfactorthatisforcinguniversitiestoinnovate

andadoptnewbusinessmodels.Hemsley-BrownandOplatka(2006)describethe

intensifyingawarenessofuniversitiesfortheirneedtocompetethusly:“Inthe

contextofincreasingcompetitionforhome-basedandoverseasstudentshigher

educationalinstitutionsnowrecognizethattheyneedtomarketthemselvesina

13

climateofinternationalcompetition”(p.316).Similarly,Dill(2003)positsthat“US

highereducationisthemostmarket-orientedsystemintheworld”(p.137).This

market-orientedcompetitivenessisdrivenbylargeandgrowingnumbersofprivate

andfor-profitinstitutionscompetingforthesamepoolofstudents,alongwith

federalprogramsthatfundindividualstudentsandresearchers.Furthermore,

Hoxby(1997)concludesthatincreasingcompetitivenessispartiallyduetothe

erosionofgeographicmonopoliesinpublichighereducationovertime(i.e.,that

studentsusedtoattendin-statepublicschoolsatamuchhigherratethantheydo

today).

Itisthereforecriticalthatinstitutionsconsciouslyengageinthepracticeof

innovationmanagement,sothatnewopportunitiestoadvancestudentandfaculty

successareleveragedappropriatelyandmorequickly.

FundingPressures.Addingtothispressurefromaccountabilitydemands

anddemographicchangesisapersistentdeclineinallbuttwostates(Wyomingand

NorthDakota)instatefundingforpublicuniversitiessincetheearly1980s

(Mortenson,2012).AMoody’s(Moody’s,2013)financialoutlookreportconcluded:

For2013,Moody’srevisesitsoutlookfortheentireUShighereducation

sectortonegative,markingashifttonegativefromstableforeventhe

sector’smarketleadingdiversifiedcollegesanduniversities.Theoutlookfor

theremainingmajorityofthesectorremainsnegative,asithasbeensince

2009.Thenewsector-widenegativeoutlookreflectsmountingpressureon

allkeyuniversityrevenuesources,requiringbolderactionsbyuniversity

leaderstoreducecostsandincreaseoperatingefficiency.(p.1)

14

TechnologicalAdvances.Finally,manyscholars(Boezerooij2006;

Kassens-Noor,2012;Al-Qahtani&Higgins,2013;Merchant,etal.2014)have

pointedouttheglobalanddistance-amelioratingeffectsofe-learning,socialmedia,

andvirtualrealityofferings,whichhavefundamentallychangedthenatureand

potentialofeducationaldeliveryviatechnologicalmeans.Arecentreporton

technologyandeducation(Infosys,2016)foundthatrapidtechnologicalchangewas

promotinganemergingemphasisonskills-basedlearning,particularlyin

technology-relatedskills.Thereport,consistingofsurveysofthousandsof16-25

yearoldsfromcountrieswiththeninelargestglobaleconomies,discoveredthat

“youngpeopleagreeoverwhelminglythattechnologyhaspositivelyinfluencedtheir

development”(p.28).Alargemajorityofthesesurveyparticipantsagreedthat

technologyhadenablednewwaystoaccesseducationalresourcesandofferings.

Allofthesefactorsaddtothepressureonpublichighereducation

institutionstobecomemoreinnovative.

InstitutionalResponses.Institutionsofhighereducation,bothpublicand

private,haveraisedtuitionsignificantlyoverthepast25years,evenwhenadjusted

forinflation(Ehrenberg,2012;Baum&Ma,2012;Archibald&Feldman,2012).

Desrochers,etal,(2012)attributethesetuitionincreasesatpublicinstitutionsto

declinesinstatefunding,particularlyafterthe2001recession.Tuitionhasbeenthe

moststablesourceofrevenuefortheseinstitutions,consideringallsourcesof

funding,fromfederalgrantstodonorgifts.Desrochers,etal.(2012)foundthatas

increasingcostshavebecomelesssubsidizedbystates,tuitionhasrisen

accordingly.

15

Institutionshavealsoturnedtonewwaystodelivertheircoursestowider

audiences.Theserangefromcommonlocally-deliveredonlinecoursestoMassive

OpenOnlineCourses(MOOCs)deliveredthroughpartnershipswithlargenon-profit

organizations,likeEdXandCoursera.Typically,theselatterofferingsinvolvehigher

profileinstitutionslikeMIT,Harvard,andBerkeley,andareconsideredameasureof

institutionalprestige.Voss(2013)states:“Theparticipatingcollegesand

universitieshavestatedthattheybelievetheirinvolvementwiththeseinitialefforts

willextend,enhance,andpreservetheirinstitutionalreach,brand,andreputation”

(p.2).

Meanwhile,lesserprofileinstitutionshavebeenexpandingtheironline

offeringsinordertoattractnewstudentsandoffermoreconveniencefortheirlocal

students(Rosenberg,2001;Bates,2005).Alargenumberofscholars(Giannoni,et

al.,2003;Covington,etal.,2005;Maguire,2005)havehighlightedtheproblemof

facultyresistancetoonlineteachingmodalities.YetAllen&Seaman(2007)found

thatthedemandfromstudentsforonlinecourseshasgrownveryrapidlyandthat

mostuniversityleadersexpectthistrendtocontinue.Furthermore,thistrendhas

alsoemergedincorporateenvironments,whereemployeesareexpectedtoengage

inonlinelearningaspartoftheirrequiredtrainingsandprofessionaldevelopment

activities.(Yoon,2003;Smart&Cappel,2006).Thistensionbetweenstudent,

workforce,andfacultyexpectationshighlightstheimportanceofinnovationand

changemanagementinhighereducation.

Oneofthemostcommondemandsofaccountabilityregimesforpublic

highereducationisforincreasedefficiencyanddecreasedadministrativecosts

16

(Desrochers,2010).However,thecombinationoffundingcutsandaccountability

measuresthatcallforincreasedadministrativeefficiencyandcentralizationmaybe

workingagainstthedemandsforinstitutionstoinnovateinordertopromote

studentsuccessforarapidlychangingcollegestudentprofile(CurrieHuisman2004,

p.1).Paradoxically,thesepressureshaveresultedinconflictinginstitutional

responses.Zusman(2005)foundthatschoolscouldeitherrespondbycentralizing

ordecentralizingoperationsundertheseconditions.Forexample,someinstitutions

haveaskedtheirprofessionalschoolstobecomeself-supportingautonomousunits,

whichwouldequatetodecentralizationoftheseprograms.Ontheotherhand,

whenfacultypositionsareretrenchedtheremainingfacultyhavelessinputin

governanceandcurriculumdecisions(Slaughter&Rhoades2004).Some

researchershaveproposedthearrivalofa“centralizeddecentralization”modelin

highereducation(Watkins,1996;Boezerooij2006),wherestaffandservicesare

developedandpaidforbylocaldepartmentsandcollegeswhileunderthebroad

controlofinstitutionalpoliciesandobjectives.Inthemidstofsomanyconflicting

priorities,someinstitutionshavedecidedtotrytobuckagainsttheirstate

accountabilityregimesbyacceptinglessinappropriationsinreturnformorelocal

autonomyandcontrol.

Manyoftheattainableimprovementsavailabletothesecollegesand

universitieswillrequirenewandjudiciousimplementationsoftechnological

innovations,whethertheserelatetoadvancementsindataanalytics,improved

communicationsystems,orenhancedclassroomtechnologies(Creasey,2008).

Undertheseconditions,itisreasonabletoassumethatpublichighereducation

17

institutionswoulddesiretounderstandthepotentialimpactsoftheircentralization

anddecentralizationdecisionsontheirabilitiestomanagetheinnovationprocess.

InnovationConcepts

Researchininnovationisveryrichandconstantlyexpanding.Thisisinlarge

partduetotheassertionofmanyscholarsthatinnovationisthemostimportant

factorinthesuccessoforganizations(Crossan&Apaydin,2010;Kemp,etal.,2003;

Rosenbusch,etal.,2011).Crossan&Apaydin(2010)foundthenumberofresearch

articlesconcerninginnovationhasrisenexponentiallyinrecentyears,while

lamentingtheabsenceofunifyingdefinitions,variables,andframeworksforthe

field.

Evendefiningtheword“innovation”hasbecomeacontentiousissueinits

ownright.FromShumpeter’s(citation)definitionin(1942)(“industrialmutation

thatincessantlyrevolutionizestheeconomicstructurefromwithin,incessantly

destroyingtheoldone,incessantlycreatinganewone”(p.73),totheUnitedStates

SecretaryofCommerce’slengthydefinitionin2008(“thedesign,invention,

developmentand/orimplementationofneworalteredproducts,services,

processes,systems,organizationalstructures,orbusinessmodelsforthepurposeof

creatingnewvalueforcustomersandfinancialreturnsforthefirm”(p.v.),thereis

aplethoraofproposedmeaningsinbetween.

However,themostcitedpublicationoninnovationisRogers’(2003)work,

DiffusionofInnovations,astudyofhownewinnovationsaredisseminatedthrough

societies.Rogersdefinesinnovationas“anidea,practice,orobjectthatisperceived

18

asnewbyanindividualorunit,”onewhich“presentsanewalternativeor

alternatives,aswellasanewmeansofsolvingproblems”(p.12).Diffusionis

definedas“theprocessinwhichaninnovationiscommunicatedthroughcertain

channelsovertimeamongmembersofasocialsystem”(p.5).Thisdefinition

establishesaprocess,orsequence,inpromotingtheutilityandusageofnew

innovations,bothforindividualsandfororganizations.Indeed,Rogerssaysthat

thisinnovationdecisionisa“processthatoccursovertimeandconsistsofaseries

ofdifferentactions”(p.169).

Inhiswork,Rogersdefines5stagesforthisinnovationcommunication

processforindividuals,alongwithenablers(andinhibitors)ofeachstage.These

stagesbeginwithknowledge,progressingtopersuasion,andsubsequentlydecision,

implementation,andconfirmation.Rogersalsospecifiesaseriesof“prior

conditions”whichhelppredictsuccessfortheinnovationprocess.Theseinclude

previouspractices,thefeltneedsandproblemsoftheindividual,theinnovativeness

oftheindividual,andthenormsofher/hissocialsystems.Thisseminalworkledto

alargenumberofsubsequentstudieswhichanalyzedeachphase,fromknowledge

toconfirmation.Thefivestagesarenextdiscussedinturn:

Theknowledgestageisprecededbyapriorconditionofneed.Untilan

individualhasidentifiedaneedforimprovement,s/hemaypractice“selective

awareness”(Rogers,p.171)andnotrecognizethevalueofavailableinnovations

andtheirapplicationstotheirsituation.Theknowledgestageconsistsofthree

typesofawareness.First,anindividualmustbeawareoftheexistenceofa

particularinnovation;second,theindividualmustpossesstheknowledgetousethe

19

innovation;andthird,theindividualmustunderstandthebasicprinciplesforusing

theinnovationsothatitcanbeusedmosteffectively.Avarietyofscholarshave

focusedontheindividualandorganizationalcharacteristicsthatmighthelp

promotesuccessintheknowledgephase.WhileBaldrigeandBurnham(1975)

foundnosignificantcorrelationswithindividualcharacteristics,laterresearchers

(Glynn,1996;Stoker,etal.,2001)foundthatattributeslikefamiliaritywiththe

worksetting,creativity,self-efficacy,andlesserneedforworkdirectionresultedin

greaterinitialinnovationbehaviors.Others,likeGeorge,etal.(2006),haveused

HallandHord’s(1987)ConcernsBasedAdoptionModeltoidentifyindividual

feelingsaboutparticularinnovations,whichledtogreateradoptionandgreater

implementationasindividualsbecamemoreinterestedinusingtheinnovations.

Someotherscholarshavealsoinvestigatedtheorganizationalfactorsthat

mayenhancesuccessintheknowledgestage.Abrahamson&Rosenkopf(1997)and

FritschandMonz(2010)foundthatthequalityofthesocialnetworkiskeyto

advancingknowledgesharingwithinanorganization.Fitzgerald,etal.,(2002)

concludedthatstrongorganizationalsiloswereadetrimenttoRogers’innovation-

decisionprocess.

Thesecondstage,persuasion,concernstheattributesofinnovationsthat

makethemmoreorlessattractivethanthecurrentlyemployedalternatives.These

characteristicsincluderelativeadvantage,whichencompassesbothpriceand

effectiveness;compatibility,bothwithindividualandorganizationalneedsand

norms;relativecomplexity,whereeaseofusehelpsacceleratetheinnovation-

decisionprocess;andreinvention,whereuserscanreusetheinnovationinnew

20

waysthanitwasoriginallyintended.Allofthesecharacteristicsleadtheindividual

toforma“favorableorunfavorableattitudetowardtheinnovation”(Rogers,p.

174).KleinschmidtandCooper(1995)establishedthestrongsignificanceofthese

attributesintheinnovation-adoptiondecision,andreviewsoftheliterature

(Tornatzky&Klein,1982;VanderPanne,etal.,2003,Jeyaraj,etal.,2006)have

confirmedthispositivecorrelation.Themorethatthesepositivetraitsare

exhibited,themorelikelythattheindividualwillchoosetoadopttheinnovation.

Thethirdstage,adoption(orrejection),isthedecisionpointforthe

individual,whochooseswhethertouseorabandontheinnovation.Rogers(2003)

foundthatthedecisiontoadoptwasmadeeasieriftheinnovationcouldbeusedon

atrialbasis.Thisattributeoftrialability,wheretheinnovationistriedoutinlow

stakesenvironments,hasbeeninvestigatedbyLin&Chen(2012),Jeyeraj,etal.,

(2006),andDucharme,etal.,(2007),whofoundmediumstrengthcorrelations

amidstsomemixedresults.Intheadoptionstage,theTechnologyAcceptance

Model(TAM),developedbyDavis(1989)andexpandedbyVenkatesh(2000),has

becomethemostoftenusedtooltopredictindividualadoption(Jeyeraj,etal.,

2006).

Venkatesh,etal.(2003)subsequentlycreatedtheUnifiedTheoryof

AcceptanceandUseofTechnology(UTAUT),whichattemptstobringtogetherall

researchfindingsofindividualadoptionintoaunifiedtheory.Thevariables

identifiedinUTAUTinclude:performanceexpectancy,effortexpectancy,attitude

towardusingtechnology,socialinfluence,facilitatingconditions,self-efficacy,and

individualanxiety.Thesevariablesreflectthelatestthinkingonthemostimportant

21

variablesinindividualadoption,andintroducesomeorganization-relatedconcepts

whichwillbediscussedlaterinthissection.

Thefourthstage,implementation,isdescribedasthepoint“whenan

individualorotherdecision-makingunitputsaninnovationtouse”(Rogers,p.

179).Importantly,thisisthestagewhereinnovationsare“re-invented”tomatch

theuniqueneedsofindividualswithintheirparticularenvironments(Rogers,p.

180).KleinandKnight(2005)andHolahan,etal.(2004)areamongawiderangeof

scholarsthathavestudiedimplementationintopicsrangingfromcomputersin

manufacturingfirmstosciencecoursesinpublicschools.Klein&Knight(2005)

foundthatimplementationisaffectedby6mainfactors:1)theexistenceofpolicies

anorganizationhascreatedtoaddressimplementation,2)organizationalclimate,3)

managementsupportfortheinnovation,4)availablefinancialresourcestosupport

theimplementation,5)thelearningorientationoftheorganization,and6)long-

termorientation(or“managementpatience”(p.245)).Manyofthesevariables

againpointtoenvironmentalvariableswithinanorganization,andwillbediscussed

shortly.

ThefinalstageofRogerstheoryofdiffusionofinnovationsisconfirmation,

inwhichindividualslookforexternalfeedbackontheinnovationandseek

“reinforcementfortheinnovation-decisionalreadymade,andmayreversethis

decisionifexposedtoconflictingmessagesabouttheinnovation”(Rogers,p.189).

Here,thegoalistoavoiddissonance,astheindividualhasalreadybuiltupabodyof

knowledgeaboutaparticularinnovation,analyzeditsrelativeadvantages,andhas

implementedit.Negativefeedbackhasapowerfulaffectatthispointonthe

22

individual’sdesiretocontinueusingtheinnovation,whichmayleadto

discontinuationofimplementation.

Figure 1. A Model of Five Stages of the Innovation-Decision Process. Rogers (2003), page 170. Reprinted under Fair Use guidelines.

Importantly,Rogersdifferentiatesthestagesofinnovationwithin

organizationsfromthatofindividuals.Theseorganizationalstagesstartwithan

initiationphase,comprisingagenda-settingandmatching;andanimplementation

phase,composedofredefining/restructuring,clarifying,androutinizing.

Agenda-settingistheprocessofclarifyinganorganizationalvisionanda

problemthatmustbeaddressedforthefirmtobesuccessful.Thiscloselymatches

thepre-existingneedconditionintheindividualinnovation-decisionmodel.

Matchingistheprocessofselectinginnovationsthatwillbestaddresstheidentified

problem(s)intheagenda-settingstage.Oncethesetwostageshavecompleted,the

adoptiondecisionhasbeenmade,andtheorganizationmovestothe

implementationphase.

23

Duringtheimplementationphase,anorganizationgoesthroughtheprocess

ofredefining/restructuring,whichconsistsofre-inventingtheinnovationsothat

itcanworkwiththeorganization,whilealsoadaptingtheorganizationto

accommodatethenewinvention.AccordingtoVanDeVen(1986),“innovations

transformthestructureandpracticesof[theirorganizational]environments”(p.

605).Organizationaladaptationcouldincludethecreationofneworganizational

units,likeaskunkworks,orarestructuringofthecurrentorganization.

Next,theorganizationwillentertheclarifyingstage,inwhichthe

organizationgrowstounderstandthemeaningandpotentialscopeandscaleof

changethatwillbeassociatedwiththeinnovation.Rogerswarnsthatimplementing

aninnovationtoorapidlyatthisstagecan“leadtodisastrousresults”(p.427).If

theinnovationfeelsforcedquicklybytheorganizationonindividuals,rejectionis

morelikelytooccur.Thisconceptrelatestotheimportanceofaparticipative

environment(Stoker2001;Fitzgerald,etal.,2002),whichallowsindividualstofeel

lessdirectedandmoreself-efficacious.

Thefinalstepintheorganizationalimplementationphaseisroutinization,

wheretheinnovation“hasbecomeincorporatedintotheregularactivitiesofthe

organizationandhaslostitsseparateidentity”(Rogers,p.428-429).Atthispoint,

thesubjectinquestionisnolongerviewedasinnovativeandtheorganizationwill

eitherstartwithnewagenda-settingordiscovernewmatchesforitsidentified

problems.

Rogerspositsthatinterestininnovationinorganizationshasincreased

greatlybecauseoftheintroductionofnewcomputer-relatedtechnologies.Henotes

24

that“theimplementationofmanyofthesenewtechnological…innovationshas

failed”(p.418)andconcludesthatorganizationalinnovationhasbecomeacritical

areaoffocusformanagers.

Ferlie&Shortell(2001)focusonorganizationalpre-existingfactorsthathelp

advanceinnovationsinorganizations,includingorganizationalcultureandclimate.

Theyconcludethatsuccess“liesintheorganization'sabilitytoprovideanoverall

climateandcultureforchangethroughitsvariousdecision-makingsystems,

operatingsystems,andhumanresourcepractices"(p.287).Theseassertionsfound

validationinVenkateshetal.’s(2000,2003)TechnologyAcceptanceModel(TAM)

andsubsequentUnifiedTheoryofAdoptionandUseofTechnology(UTAUT),which

highlightstheimportanceofadequateorganizationalresourcesfortheinnovation,

compatibilitywithexistingsystemsinuse,andadequatetechnologysupportforthe

innovation.ThesefactorsfromTAMandUTAUTillustratetheimportanceofthe

informationtechnologysubunitsofagiveninstitution,andwillbediscussedmore

thoroughlyinthecentralizationsectionbelow.

InnovationValueChain

Theinnovationvaluechain(IVC),proposedinseparateformatsbyHansen&

Birkinshaw(2007)andRoper,Du,&Love(2008),isawaytomeasurethe

innovationmanagementactivitiesoforganizationsandlargeentities,including

entirecountries.VariousstudieshaveusedtheIVCtomeasuretheinnovation

supportingactivitiesofIrelandandSwitzerland(Roper&Avanitis,2012),Japan

(Kodama,2009),andChina(Guan&Chen,2010),amongothers.Initssimplest

format,theIVCdescribesasequentialprocessofideageneration,ideaconversion,

25

andideadiffusionunderHansen&Birksinshaw’s(2007)model,oralternately,as

knowledgesourcing,knowledgetransformation,andknowledgeexploitationunder

Roper,Du&Love’s(2008)model.

Figure 2. Innovation Value Chain Models. Adapted from Sheu & Lee (2009). AccordingtoHansenandBirkinshaw’s(2007)model,thesubcomponentsof

thisthreestageprocessincludesiximportantmanagementtasks:internalsourcing,

cross-unitsourcing,externalsourcing,selection,development,anddiffusionofthe

innovationwithinthefirm.Internalsourcingissimplythegenerationofinnovative

ideasfromwithinthefirm.Cross-unitsourcingtakestheinternalideageneration

processastepfurtherbyinvolvingthecollaborationofdifferentunitswithinthe

sameorganizationtogenerateideas.Externalsourcingistheprocessofintegrating

innovativeideasfromoutsidetheorganization.Thesesourcingprocessesgenerate

ideasthatmustthenbescreenedthroughaselectionprocessandfurtherdeveloped

sothattheresultinginnovationcanworkwithinthefirm.Finally,theinnovations

shouldbediffusedthroughouttheorganization.Thesetaskstakentogether

constitutetheorganizationalactivitiesoftheinnovationvaluechain.

26

Hansen&Birkinshaw’s(2007)paperproposesaquestionnairetoquickly

determineagivencompany’sIVCstrengthsandweaknessesinordertofocus

managementeffortsontherevealedweaknesses.Giventhemanypressures

previouslydescribedinthischapter,fromstateaccountabilitystandardsto

increasingcompetition,institutionshavemuchtogainthroughunderstandingthese

factorsintheirperformance.

Thequestionnairebeginswithseriesofquestionsthatprobethecreationof

newideaswithinaunit,viacollaborationwithotherunits,orviasourcesoutsideof

theorganization.Keyperformanceindicatorsareidentifiedtoshowmeasuresthat

canbeusedtovalidatethequalityofresponses.Thenextsectioncoversthe

conversionphaseoftheIVC,whereideasarescreenedandpotentiallyfunded,and

innovationsareturnedintoviableproductsandbusinesspracticesforthe

organization.Finally,thesurveyendswithaquestionabouttheeffectivenessof

innovationdiffusionwithinthefirm,wheretheinnovationisdisseminated

throughouttheorganization(seeAppendixBforthefullinstrument).

Roper,etal.(2008)useamoremathematicalapproachtoexploreIVC

activitieswithincorporations,particularlymanufacturingfirms.Forexample,the

formulaforknowledgesourcingwithinafirmis:KS∗ =ˇʹKSkit + ʹRIjit + ʹKUCjit + ʹGOVTjit + ʹMKTjit +εjit,

jit∗

0123(1) KSjit = 1 if KSjit > 0; (p.963).ThekeydifferenceinRoper’sapproachascomparedto

Hansen&Birkinshaw’sapproachisthattheendresultinRoper’smodelisan

innovationthatcanbe“exploited”(VanHorne,etal.,2006,p.757);inotherwords,

aproductthatcanbesoldtoacustomer.Forthisreason,Roper’sapproachhas

beenusedtosurveyinnovationdevelopmentactivitiesonanationalscale;the

27

concernsofnationaleconomiesusuallyfocusonGrossDomesticProduct(GDP)and

othermeasureswhichinvolvesalesofparticulargoodstoconsumers.

Incontrast,theHansen&Birkinshawmodelcanbeusedtoanalyzeactivities

withintheorganizationthathavenodirectcustomers.Therefore,theHansen&

Birkinshawtoolismoreapplicableforthepurposesofthisdissertation.

Lane(2007)declaresthat“inacademia,especiallyinscientificandmedical

fields,individualsappeartobestronglyindependentandconservativeinnature,

andgenerallyskepticalofeducationalchange”(p.86).PutinthelensesofHansen

andBirkinshaw’sIVC,whatpartofthechainisweakest?Isitthegenerationofnew

ideas,theirconversionintoactionableapproaches,ortheirdiffusion(orallthree)?

CentralizationConcepts

Whilemanystudiesprovideaframeworkforunderstandinginnovation

adoptionfromaculturalandsocialcontext,relativelyfewstudieshavefocusedon

theimportanceoforganizationalstructuresasanelementininnovationadoption

andimplementation(Gupta,Smith,&Shalley,2006,Siggelkow&Levinthal,2003;

Westerman,McFarlan,&Iansiti,2006),andevenlesssoinhighereducation

settings.Twoadditionalfactorsthatcanbeinvestigatedunderthislensincludethe

structuresofsubunitswithinaninstitutionandtheircorrespondinglevelsof

centralization.

Thereareawidevarietyofmethodstomeasurethecentralizationof

organizations.Centralizationcanbedescribedmathematically,asameasureof

centralityandtherelationshipofanodetoothernodes.Thisapproachwasfirst

proposedbyAlexBavelasin1948tostudycommunicationwithinagroup,

28

researchedandrefinedbymanyscholars,andrefinedstillfurtherbyFreemanto

providecomparativedataaboutnodesin1978.Thismeasureiswidelyusedinthe

socialsciencestodescribecentralityinsocialnetworks.

Usingadifferentapproach,Treisman(2002)proposedapoliticalmodelof

centralizationwhichcouldbeusedfordescribingtherelativecentralizationofstates

andnations.Hismodelcomprisessixcomponents:1)verticaldecentralization,2)

decisionmakingdecentralization,3)appointmentdecentralization,4)electoral

decentralization,5)fiscaldecentralization,and6)personneldecentralization.

InTreisman’smodel,verticaldecentralizationissimplyameasureofthe

numberoftiersinanorganization,fromitshighestleveltothelowestlevel.

Decision-makingdecentralizationreferstotheauthoritytomakedecisionsateach

ofthetiers,andappointmentdecentralizationconcernswherehiringdecisionscan

bemade.Electoraldecentralizationdescribesthenumberoftiersthathavedirect

elections.Forexample,intheU.S.government,thePresidentandCongressare

elected,butsomepositionsareappointedratherthanelected.Finally,fiscal

decentralizationconcernsthepercentageofrevenuesthataredistributedto

subunitswithinthegovernment,andpersonneldecentralizationisameasureofthe

percentageofadministrationthatcanbefoundatthesubunitlevel.

HageandAiken(1967)createdatooltomeasurethelevelofcentralizationin

non-profitorganizationsthathassincebeenutilized,validated,andmodifiedmany

times(Dewar,Whetton,Boje,1980).TheHage&Aikentoolhasbeenusedtostudy

avarietyoforganizationalfactorsandperformanceindicators,fromcomplexityand

formalization(Hage&Aiken1967)topatientoutcomes(Aiken,etal.,2000)and

29

organizationaldesign(Agranoff1976).Thesurveyconsistsoftwoparts:1)a

measureofparticipationindecisionmaking,and2)ameasureofthehierarchyof

authorityintheorganization.Laterscholars,likeKaluzny,etal.(1974),alsochoose

tomeasurecentralizationasadegreeofparticipationindecisionmaking,asdoes

Ferrell&Skinner(1988).

Notably,HageandAiken(1971)usedtheirmeasureofcentralizationtofind

itsimpactoninnovationinastudyofhealthcarefirms.Thefindingsfromthisstudy

wereinconclusiveonthistopicbecausefulldatawasnotavailableatthetimeof

publication.Otherscholars,likeDamanpour(1996)havesoughttomeasurethe

impactofcentralizationandformalizationoninnovationwithinfor-profitandnon-

profitfirms.Damanpourfoundthatcentralizationwasmorenegativelyrelatedto

innovationinfor-profitorganizationsthaninnot-for-profitorganizations.In

Damanpour’s(1996)model,centralizationleadstolowerrisk-takingwithnew

innovations.Alowerrateofrisk-takingismoreharmfulinfor-profitfirms,dueto

thefactthatnon-profitfirmshavegreateraccountabilitytoexternalcontrolsthan

for-profitfirms(e.g.,legislativefunding,stateandfederalrequirements,etc.).This

addedaccountabilityfornon-profitsmakesthemmorestaticingeneralthanfor-

profitfirms,andsolesswillingtotakeriskswithnewinnovations.

AndersonandKing(1993)describearelated“innovationdilemma”(p.11)

thatwasidentifiedinpreviousstudiesofcentralizationandinnovation:namelythat

earlystagesofinnovationarefacilitatedbydecentralization,whilelaterstagesare

facilitatedbycentralization.Additionally,Kim(1980)foundthatcentralization’s

impactoninnovationinorganizationsdependedonthetypeoforganization.

30

Resourceallocationdecision-making(definedbyKimasparticipationindecision-

making)was“significantlyrelatedtoprogramchangesinserviceorganizations,

whiledecision-makingaboutwork(definedbyKimashierarchyofauthority)

was…significantlyrelatedtomorefrequentproductchangesinmanufacturing

organizations”(p.241).

Importantly,theHage&Aiken(1971),Damanpour(1996),Andersonand

King(1993),andKim(1980)studiesdidnotestablishtherelativecentralizationof

subunitswithinthefirmstheystudied,andthepotentialimpactofsubunit

structuresonorganizationalinnovativeness.

Subunits.Somescholarshaveassertedthatsubunitswithinagivenfirmcan

haveanequallylargeroleontheadoptionandimplementationprocess(Tushman,

etal.,2010;Pennings,etal.,2014;Abrunhosa,A.,&Sá,P.M.,2008).Kim(1980)

statesthata“plausiblewaytoinvestigatethecontingencyrelationshipbetween

organizationalstructureandthedifferentphasesoftheinnovationprocessmaybe

toassumethattheorganizationhasdifferentsubunitstodealwithdifferentstages”

(p.228).However,Kim(1980)didnotpursuethislineofresearchinhispaper.In

highereducation,subunitsmayconsistofdivisions,colleges,departments,and

administrativeserviceunits.Thesesubunitscanbehighlycentralizedor

decentralized,dependingonbudgetaryconstraintsandinstitutionalculturalnorms.

Tushman,etal.(2010)identifyfourdistincttypesoforganizational

structuresbasedonareviewoftheliterature.Thefirstmodel,thefunctional

structure,describesanorganizationbasedonoperationalunitsthatoperateas

discretebusinessfunctions.Innovationscholars(Audia,Locke,andSmith,2000;

31

CampbellandPark,2005;CarrollandTeo,1996;ChristensenandBower,1996;Hill

andRothaermel,2003)havefocusedontheinertialaspectofthisorganizational

model,claimingthatpartnershipsandacquisitionsareessentialpathwaysto

innovationbecausetheyarenecessarytoovercometheinternalinertiaofcultural

normsandseniorleadershipbiases.

Thesecondmodel,thecross-functionalteamstructure,highlightsthe

importanceofstrategicdirectivesandtechnologicalchanges,whichrequire

coordinatedcollaborationsbetweenunitswithinafunctionalstructureinorderto

accomplishadesiredgoal(Donaldson&Preston,1995;Gresov,1989;Miles,etal.,

1978;NadlerandTushman,1997).Thesecross-functionalteamsfocusoncreating

newideasby“innovatingviastructuraloverlays”withinanorganization(Tushman,

etal.,2010,p.6).

Thethirdandfourthmodels,asdescribedbyChristensen(1997),

WheelwrightandClark(1992),andO’ReillyandTushman(1997),arethespin-out

structureandtheambidextrousstructure,respectively.Spin-outsaredefinedas

“distinctinnovationunit[s]withoutgeneralmanagercontroland/orseniorteam

support,”whileambidextrousunitsaredescribedas“distinctinnovationunit[s]

withgeneralmanagercontrolandseniorteamsupport”(Tushman,etal.,2010,p.

11).Spin-outsareemployedtoencouragenew-to-the-firminnovations,while

ambidextrousstructuresseektopromotebothnewideasandexpandonexisting

innovations.

Whilehighereducationhasbeenorganizedverytraditionallyintofunctional

units,alloftheseorganizationalmodelscanbefoundinthesubunitsofpublic

32

highereducationinstitutions.DespitethefactthattheHage&Aikenmeasureof

centralizationhasbeenusedtomeasurefirmsattheorganizationallevel,the

importanceofsubunitsandtheirownvaryingstructuresandlevelsofcentralization

hasbeenneglected.Furthermore,asinnovationstudieshaveadvancedtoinclude

theprocessaspectsofinnovationmanagement,broadmeasuresofinnovationas

describedintheDamanpour(1996)studyappeartobeinsufficientfortheanalysis

oftheimpactofsubunitcentralizationaspartofinnovationmanagementpractices.

Damanpour’sresearchfocusesontherelativeinnovativenessoffirms,ratherthan

thestrengthsandweaknessesoftheirinnovationmanagementpractices(as

determinedvis-à-vistheIVC).

Inanextensivereviewofinnovationscholarship,Crossan&Apaydin(2010)

delineatebetweeninnovationasoutcomeandinnovationasprocess.Theformeris

ameasureofnewproducts,services,andactivitiesatagivenfirm,whilethelatteris

areflectionofparticularmanagementpracticesthatpromote(ordemote)

innovativeness.Thisdissertationfocusesoninnovationasprocessinaneffortto

helpinstitutionsunderstandtheirrespectivestrengthsandweaknessesinthat

process.Giventhefinancialandlegislativepressuresonpublichighereducationto

becomemoreefficient(andthereforemorecentralized)whilesimultaneously

becomingmoreinnovative,itisimportanttoknowtherelationshipofcentralization

andefficiencystrengthsandweaknessesininnovationmanagement.

Rationale

Inconclusion,theroleofhighereducationserviceunitsintheinnovation

processhasnotbeenadequatelyresearched,andthequestionofwhichserviceunits

33

tostudyhasnotbeenfullyansweredintheseenvironments.Technologyunitsin

publichighereducationseemparticularlyripeforstudy,giventheirpotential

impactinawidevarietyoffactorsthatpromoteinnovationgeneration,conversion,

anddiffusion.WhilescholarslikeFullerandSwanson(1992)investigatedtheroles

ofinformationtechnologysubunitsonorganizationalinnovativeness,theydidnot

factorintherelativecentralizationofthesesubunitsorincludeeducational

institutions.Perhapsmostimportantly,theyfocusedonorganizational

innovativenessasanoutcome,ratherthaninnovationasaprocess.Recently

developedandvalidatedmeasures,suchasVenkatesh’s(2000,2003)TAMand

UTAUTmodels,includeanumberoffactorsthatcouldbeimpactedbythe

functionalityandagilityoflocaltechnologysupportunits.Specificfactorsthataffect

innovationadoption,fromindividualapprehensiontofacilitatingconditionslikethe

availabilityoftrainingandsupport,givefurtherevidencethattechnologyservice

unitsareverylikelyanimportantconsiderationintechnologyadoptionand

diffusion.

Althoughstudieshavedemonstrated1)thecriticalimportanceofinnovation

(Borins,1998;Andrewsetal.,2006;Christensenetal.,2004;Damanpouretal.,

2009;Tiddetal.,2001),2)themanyproblemsinvolvedinsuccessfullymanaging

innovation(Ensminger,2005;Griffith,Zammuto,&Aiman-Smith,1999;Meyer&

Goes,1988;Surry&Ely,2002;VandeVen,1999),and3)theculturalandresource

barrierstochangewithinorganizations(Aubert&Hamel2001;Denisetal.2002;

Fennell&Warnecke1988;Ferlieetal.2001;andRogers2003),thereisinadequate

researchonhowsubunitorganizationalstructurecaninfluencethesuccessof

34

innovationmanagementforkeytechnologicalinnovations.Giventhatinstitutionsof

highereducationareorganizeddifferently,andthattechnologysupport

organizationsinsideeachinstitutionarealsoorganizeddifferently,thereisaneed

tofurtherunderstandhowthesestructuraldifferencesmayimpacttheinnovation

managementprocess.ThisstudywillapplyHansen&Birkinshaw’s(2007)

innovationvaluechaintodeterminehowrelativecentralizationoftechnologyunits

promotesordemoteseachphaseoftheinnovationvaluechainacrosstheinstitution

anduseHage&Aiken’s(1967),Kaluzny,etal.’s(1974)andFerrellandSkinner’s

(1988)surveyinstrumentstoidentifytherespectivecentralizationoftechnology

organizationsinpublicResearchOneLeveluniversities.

Manyinternalandexternaldrivers—rangingfromstudentsuccessand

institutionalrankingstofinancialandoutcome-basedaccountabilitymeasures—

incentivizeinstitutionsofhighereducation.Yeteachinstitutionemploysoneof

manyorganizationalmodelsduetoavarietyoffactorsspecifictotheinstitution.

Studieshaveshowntheimportanceofimplementingnewinnovationsinorderto

addressthesedrivers.Docertainorganizationalmodelsyieldbetterresultsto

promotevariousphasesofthegeneration,conversionanddiffusionofthese

innovations?Thisstudywillilluminatethestrengthsandweaknessesofspecific

organizationalmodelsforfaculty,staff,andadministratorshopingtoutilizenew

technologiestoachievetheirrespectiveandinstitutionalgoals.Thelarger

communitywillbenefitbybeingabletoidentifypotentialactionstoaddress

shortcomingsintheirinnovationmanagementprocesses,andtheinnovation

researchcommunitywillbenefitfromnewdatainanunder-researchedtopicarea.

35

ChapterIII

Method

ThepurposeofthisquantitativestudywastoapplyHageandAiken’s(1971),

Kaluzny,etal.’s(1974),andFerrellandSkinner’s(1988)centralizationtoolsto

HansenandBirkinshaw’s(2007)innovationvaluechaintoolinordertoexplore

whetherthereexistedarelationshipbetweencentralizationandtheinnovation

process.Morespecifically,thepresentstudyhopedtofindadifferenceinthe

relativestrengthsandweaknessesinideageneration,conversion,anddiffusionof

technologicalinnovationsamongResearchOne(R1)DoctoralUniversitiesbased

upontherelativecentralizationlevelsoftechnologyunits.TheResearchOne

classificationisasubcategoryofclassificationsofhighereducationinstitutions

developedbytheCarnegieFoundationfortheAdvancementofTeaching(“The

CarnegieClassificationofInstitutionsofHigherEducation,”n.d.).Itwasexpected

thatthenumberofinstitutionsinthiscategorywouldprovidegreatdepthand

varietytotheoverallstudy,andthatstronginferencesaboutITorganizational

structuresandtheirrelationshiptoinnovationmanagementactivitieswouldbe

derivedfromtheresultingdata.Towardthispurpose,fivehypothesesweretested:

Hypothesis1.Thisstudyhypothesizedthatmoredecentralizedtechnology

structureswouldshowgreatereffectivenessduringtheideagenerationphasethan

morecentralizedstructures.

Hypothesis2.Thisstudyhypothesizedthatmoredecentralizedtechnology

unitswouldshowgreatereffectivenessduringtheideaconversionphasethanmore

centralizedstructures.

36

Hypothesis3.Thisstudyhypothesizedthatmorecentralizedtechnology

structureswouldshowgreatereffectivenessduringthediffusionphasethanmore

decentralizedstructures.

Hypothesis4.Thisstudyhypothesizedthatmorecentralizedtechnology

structureswouldshowlowereffectivenessforallthreephasesoftheinnovation

valuechainthanmoredecentralizedstructures.

Hypothesis5.Thisstudyhypothesizedthatparticipationindecisionmaking

measureswouldshowmoresignificantcorrelationswithinnovationvaluechain

phasesthanhierarchyofauthoritymeasures.

Subjects

Surveyparticipantsconsistedofsubunit(college,school,subdivision)ITstaff

andmanagersworkingatR1universitiesacrosstheUnitedStates,aCarnegie

classificationthatconsistsof115institutions.TheR1universitiescategorywas

chosenbecauseitencompassesaconsiderablenumberofinstitutionsdistributedin

roughproportiontopopulationcentersthroughouttheUnitedStates(Figure1),and

alsocomprisesinstitutionswithavarietyororganizationalmodels,andsizes.

Importantly,theseinstitutionshaveresourcelevelsthatallowthemtomakechoices

regardingthecentralizationanddecentralizationoftheirsubunits.Also,therange

ofpotentialdecentralizationismuchhigherattheseinstitutions,giventhesizeand

scopeoftheirmissionsandcampuspopulations.TheCarnegieFoundation

identifiesR1schoolsasinstitutionswiththehighestresearchactivitythatawarded

atleast20research/scholarshipdoctoratedegreesin2015.

37

Figure 3. R1 University Locations. By Edmund Clark (2016). Source data retrieved from http://classifications.carnegiefoundation.org/.

SubunitITworkerswerechosenbecausetheywerewell-positionedto

respondtothetaskindependenceandhierarchyofauthorityquestionsposedinthe

threecentralizationmeasuresandbecausetheycouldalsoprovidemore

representativeanswerstotheinnovationvaluechainquestions.Thecentralization

questionsweregearedtowardworkersunderneathtoporganizationalpositions,

andtheinnovationvaluechaincouldprovideamorecompletepictureofagiven

institutionwhenmultiplesubunitmeasuresofideageneration,conversion,and

diffusionweretakenintoaccount.

Measures

Surveyparticipantsfromeachinstitutionwereaskedtoidentifytheir

position,subunit,andrelationoftheirsubunitstothecentralITunitateach

institution.Eachparticipantwasthenaskedtocompleteasinglesurveythat

combinedmultipleinstrumentscreatedbyHage&Aiken(1971),Kaluzny,etal.

(1974),Ferrell&Skinner(1988),andHansen&Birkinshaw(2007).Thefirstthree

instrumentsmeasureparticipationindecision-makingandhierarchyofauthority

38

(seeAppendixA).TheHageandAikentoolhasbeenpreviouslyvalidatedbyDewar,

Whetton&Boje(1980)inareviewoffourpreviousstudies,witharangefrom.81to

.95fortheparticipationindecisionmakingmeasuresand.70to.96inthehierarchy

ofauthoritymeasures.(SeeFigureXDewarWhettonBoje1980below).

Additionally,Kim(1980)validatedtheHageandAikenvariablesat.90for

participationindecisionmakingand.68forhierarchyofauthorityitems.The

presentstudyadaptedtheHageandAikentooltospecificallymeasurethese

variablesinITsubunits.

TheKaluzny(1974)toolhasbeencitedinover100studiesandbuildson

Hage&Aiken’sparticipationindecisionmakingtoolbyincludingadditional

organizationalfactorslikefundingandaffiliation.ThisstudyadaptedtheKaluzny

tooltofocusontechnologysubunitorganizationsandtheirparticipationin

decision-makinginrelationshiptocentraltechnologyorganizations.Similarly,the

FerrellandSkinner(1988)toolhasbeencitedinover400studiesandwasadapted

todemonstratetheparticipationindecisionmakingfordecentralizedtechnology

subunitsinrelationshiptocentralizedtechnologysubunitsinhighereducation.One

goalofthisdissertationwastoestablishafirmcorrelationbetweenallthreeofthese

centralizationtools,therebyprovidingfurthervalidityforanysubsequentlinkages

withtheinnovationvaluechainmeasures.

TheHansen&Birkinshaw(2007)innovationvaluechaintool(seeAppendix

B)madeupthelastportionofthissinglecombinedinstrument.Thistoolhasbeen

citedinover600researchpapersandreflectedthefocusoninnovation-as-process

utilizedinthepresentstudy.AsdescribedinChapter2,theHansenandBirkinshaw

39

(2007)tooldividestheinnovationprocessintothreemainphasesandsixsub-

phasesandthisdissertationattemptedtofindlinkagesbetweentheaforementioned

centralizationmeasuresandtheirimpactsineachinnovationvaluechainphaseand

sub-phase.

ProcedureforDataCollection

SubjectswereidentifiedviaparticipationintheMORLeadershipprogram,a

nationalleadershipdevelopmentprogramwithcohortsfromover30R1

institutions.Datawascollectedfromasingle-stageQualtrixsurvey(seeAppendixA

&Bforthecompletequestionlist)thatwasdistributedtosubunitITstaffateach

institutionwithincurrentandpreviousMORcohortgroups.Thesesubjectswere

thenrecruitedviae-mailthroughMORleadershiprepresentatives.Theeconomyof

designandrapidturnaroundfordatacollectionviaInternetsurveyjustifiedtheuse

ofthisinstrumentforthepresentstudy.

ProcedureforDataAnalysis

DatafromthesurveywasaggregatedandthenevaluatedthroughJASP,an

open-sourcesoftwareprogramforadvancedstatisticalanalysis.Theidentifying

informationofparticipantswasredacted.Thethreecentralizationmeasureswere

normalizedandcombinedandthencorrelatedwiththethreeinnovationvaluechain

sub-measuresandevaluatedforcross-dimensionalcorrelationsbyspecific

participantcharacteristics.First,thecentralizationmeasuresweretestedto

determinewhethertheywereinagreement.Then,thecentralizationmeasures

weretestedforthestrengthsoftheirrelationshipsineachphaseoftheinnovation

valuechain.Datawasscrubbedandcheckedforoutliers,usingstatisticalmethods

40

anddistributioncharts.Finally,correlationsweremeasuredbykeyparticipant

characteristics,includinginstitutiontype,organizationaltype,andreportingtype.

41

ChapterIV

Results

DemographicCharacteristics Thesurveyforthepresentstudyreceived525responses.Participant

responseswereexcludedifanyofthemeasurementitems(participation,hierarchy,

generation,conversion,anddiffusion)wereleftblank,iftherespondentdidnot

workatanR1institution,oriftherespondentwasnotpartofanITunit.These

exclusionseliminated222responses.

303centralizedanddecentralizedITstaffat38R1institutions(100%ofthe

R1institutionsservedbytheMORleadershipprogram)fullycompletedthesurvey

forthestudy.Ofthe38institutions,22werepublic,and16wereprivate.The

institutionsweregeographicallydistributedthroughouttheUnitedStateswith

locationsincludingpartsoftheNorthern,Southern,EasternandWesternregionsof

thecountry.Takentogether,these38institutionsconstituteapproximatelyone

thirdofthe115R1institutionsintheUnitedStates.

Thesubjectsweremadeupof168centralized(55.4%ofthetotal)and111

decentralized(36.6%)technologystaff,alongwith24additionaltechnologystaff

(7.9%)thatheldjointreportstobothcentralandnon-centralunits.Positions

rangedfromsystemadministratorstoCIOs,withgreatvarietyinbetween,including

academictechnologystaffanddesktopsupportspecialists.

Privateuniversityrespondentsincluded91surveyresponses,or30%ofthe

totalresponses,whilepublicuniversityrespondentsmadeuptheremaining212

responses(70%).Oftheprivateinstitutionresponses,54(59.3%)camefrom

42

centralizedITpositions,32(35.1%)fromdecentralizedpositions,and5(5.5%)

fromjoint-reportingpositions.Ofthepublicinstitutionrespondents,114(51.6%)

werecentralizedITpositions,79(37.3)weredecentralized,and19(9%)werejoint

reports.

Figure 4. Respondent Demographics. Edmund Clark (2016). Source data from survey results.

ParticipationinDecision-Making

Participantswereaskedtocompleteasinglesurveythatincludedtwo

separateinstrumentstomeasureparticipationindecisionmaking:1)fourquestions

withafive-pointscale(lowof0tohighof4,withamaximumscoreof16)adapted

fromHage&Aiken’s(1971)tool,and2)sixquestionswitha3-pointscale(0-2,with

amaximumscoreof12)adaptedfromKaluzny,etal.,(1974).Higherscoresfrom

theseinstrumentsindicatedlowerparticipation,andthereforemorecentralization.

Thesequestionswereintendedtoprobetowhatextenttherespondentwas

involvedwithorganization-widedecisionsinvolvingnewinitiatives,newhires,and

fundingfortechnology(seeAppendixA).

43

Thesemeasureswerethenscored;normalizedbyconvertingeachscoreinto

apercentageofthepossibletotal("#$%&'&(#%&)*++,

;"#$%&'&(#%&)*-+-

);andthenconverted

intoasingleparticipationscore("#$%&'&(#%&)*+."#$%&'&(#%&)*--

).Theresultingscores

rangedfromasinglescoreof0(or0%)—meaningthatthispersonparticipatedin

everyinstitutionalITdecision-makingprocess—tothreescoresof1(or100%),

meaningthattheseindividualsneverparticipatedininstitutionalITdecision-

making.Thecorrelationbetweenthetwoparticipationmeasureswaslarge(r=

.65),withameanscoreof.6159(outofamaximumscoreof1.0)forthefirsttest

andameanscoreof.5674forthesecondtest.Thecorrelationsreliablypredicted

eachother,bututilizingasimilarpointscalewouldhavelikelyresultedinacloser

correlationbetweenthetwomeasures.Thetotalparticipationscoredistribution

skewedhigh,whichindicateslowerparticipationinthedecision-makingprocess

(seeFigure5).

Figure 5. Distribution of Participation in Decision-Making scores. Edmund Clark (2016). Source

data from survey results.

44

HierarchyofAuthority

Thesurveyforthepresentstudyalsocontainedtwoinstrumentstomeasure

thehierarchyofauthorityexperiencedbyeachindividualattheirinstitutionwhenit

cametotechnologyactivities;orinotherwords,towhatextenttheindividualcould

actwithoutaskingforpermissionfromasuperiororcentralauthority.These

measuresweresimilarlyconstructed,andconsistedoffivequestionsadaptedfrom

Hage&Aiken(1971)ona4-pointscale(lowof0tohighof3foreachitem,

maximumscore15)alongwithfivequestionsadaptedfromFerrell&Skinner

(1988)onasimilar4-pointscale(0-3foreachitem,maximumscore15).Aswith

thepreviouslydiscussedparticipationmeasures,higherscoresindicateless

freedomtoact,andthereforemorecentralization.Thehierarchyscoresshoweda

largeandveryreliablecorrelation(r=.82)andrangedfromfourscoresof“0”

(meaningthatnopermissionwaseverneededtoact)to“1”(meaningthatnoaction

couldbetakenwithoutpermission).Notsurprisingly,threeofthefour“0”scores

camefromhighly-rankedstaffwithtitlesofCIOorDeputyCIO.

Theresultinghierarchymeasureswerethenscoredandnormalizedusinga

similarapproach(0&1$#$'23++4

; 0&1$#$'23-+4

),andsubsequentlyaveragedtocreatea

totalhierarchyscore(0&1$#$'23+.0&1$#$'23--

).Themeanscoreforthefirsthierarchy

measurewas.3328,whilethemeanscoreforsecondhierarchymeasurewas.3302.

Thehierarchyscoresskewedlowandwereabnormallydistributedtowards

independence,asseeninFigure6.Thisresultseemsconsistentwiththesizeand

relativedecentralizationoftheseresearchinstitutions.

45

Figure 6. Distribution of Hierarchy of Authority scores. Edmund Clark (2016). Source data from

survey results.

CentralizationScore

Thefinalderivedmeasurewasacentralizationscoreforeachresponse,

whichwascomposedoftheparticipationscore("#$%&'&(#%&)*+."#$%&'&(#%&)*--

)added

tothehierarchyscore(0&1$#$'23+.0&1$#$'23--

)tocreateatotal.Thesecentralization

scoresrangedfrom16.66to170.41andweredistributednormally,asseenin

Figure7.Thecentralizationmeasurewasusedastheindependentvariableto

Figure 7. Distribution of Centralization scores. Edmund Clark (2016). Source data from survey

results.

46

determinecorrelationswiththeinnovationgeneration,conversion,anddiffusion

measures.

InnovationValueChain

Thesurveyusedforthepresentstudyalsocontainedonefinalelement.The

innovationvaluechainquestionsdevelopedbyHansen&Birkinshaw(2007)

attempttomeasurethestrengthandweaknessofinnovationgeneration,

conversion,anddiffusionactivitiesinanorganization.Thesequestionsconsistedof

sixquestionsrelatingtoideagenerationona3-pointscale(lowof1tohighof3,

maximumscore18);fourquestionsrelatingtoideaconversionona3-pointscale

(1-3,maximumscore12);andthreequestionsrelatingtodiffusiononthesame3-

pointscale(1-3,maximumscore9).Higherscoresineachofthesecategories

indicatedpoorerperformance.

Findings

47

Figure 8. Innovation generation, conversion, and diffusion as a function of centralization.

Edmund Clark (2016). Source data from survey results.

Thecentralizationscoreforallinstitutionshadamoderateandpositive

correlationtothegenerationofideasscore(r=.33,DF=302,p<.0001).Thisresult

meansthatincreasedcentralizationresultedinmorenegativeeffectsforidea

generation.Therefore,thefirsthypothesiswassupported:thatmoredecentralized

technologystructureswouldshowgreatereffectivenessduringtheideageneration

phasethanmorecentralizedstructures.

Itwashypothesizedthatmoredecentralizedtechnologyunitswouldshow

greatereffectivenessduringtheideaconversionphasethanmorecentralized

structures.Thecentralizationscoreforallinstitutionshadaweakbutpositive

correlationtotheconversionscore(r=.29,DF=302,p<.0001).Thisresultmeans

thatmorecentralizationledtomorenegativeperformanceinideaconversion.

Therefore,thesecondhypothesiswassupportedbythestudy.

Thethirdhypothesis,thatmorecentralizedtechnologystructureswould

showgreatereffectivenessduringthediffusionphasethanmoredecentralized

structures,wasnotsupportedbythedata.Thecorrelationbetweenthe

centralizationscoreandthediffusionscorewasnonexistent(r=.08).Strangely,the

negativeimpactofcentralizationonthediffusionscoreinprivateschoolswas

significantandnegative(r=.33,DF=90,p=.0013).Thisfindingissurprising,in

thatitsuggeststhatcentralizationatpublicinstitutionshasalmostnoimpactonthe

diffusionprocess,whileithasamoderatelynegativeimpactatprivateinstitutions.

48

Thefourthhypothesis,thatmorecentralizedtechnologystructureswould

showlowereffectivenessforallthreephasesoftheinnovationvaluechainthan

moredecentralizedstructures,wassupportedbythedata.Intheall-institution

results,highercentralizationresultedinlowerinnovationprocessscoresin

generation,conversion,anddiffusion(r=.33,p<.0001;r=.29,p<.0001;andr=

.08,respectively).Whenreviewingcentralstaffresponsesontheirown,thesame

patternemerged(r=.35,p<.0001;r=.27,p<.0004;andr=.08,respectively).

Decentralizedstaffalsosawthispattern,withslightlymoresignificantnegative

impactsondiffusion(r=.31,r=.29,andr=.15,respectively).Interestingly,joint

reports(r=.29,.50,and.04,respectively)sawthelargestcorrelationonthe

conversionphase,butthesamplesizeforthisgroupincludedonly24responses.

Alsoofinterestwasthatprivateinstitutionssawmuchlargercorrelations(r=.40,

.33,and.33,respectively),thanpublicuniversities,whichyieldedtheonlyresults

thatwerepositive(butatanonsignificantlevel)fordiffusion(r=.30,.28,and-.05,

respectively).

Finally,itwashypothesizedthatparticipationindecision-makingmeasures

wouldshowmoresignificantcorrelationswithinnovationvaluechainphasesthan

hierarchyofauthoritymeasures.Suchafindingwouldechothevalidationstudies

conductedbyDewar,Whetton&Boje(1980),inwhichparticipationindecision

makingwasfoundtobeslightlymoreimpactfulinthefourstudiesreviewedthan

thehierarchyofauthoritymeasures(.95,.92,.93,and.81fortheparticipation

measurevs..79,.96,.93,and.70forthehierarchymeasure).Surprisingly,thestudy

didnotsupportthehypothesis.Participationscoresimpactedgeneration,

49

conversion,anddiffusionwithPearsoncoefficientsof.22,.18,and.18;while

hierarchyscoresshowedimpactsof.24,.23,and-.07respectively.Thismay

indicatethatthetypeoforganizationsstudied(e.g.,manufacturing,government,

education,etc.)haveimportanteffectsonthepowerofthesemeasures.

Institutiontypeandjointreportingstructuresasemergentfactors

Thetwostrongestresultsthatemergedthatwerenotanticipatedbythis

studywere:1)thattheinnovationvaluechainwasmuchmoreadverselyimpacted

bycentralizationinprivateinstitutionsthaninpublicinstitutions,and2)thatjoint

reportssawastrong(r=.50)adverseimpactofcentralizationonconversion.These

findingsmeritfurtherinvestigation.

Inordertovalidatethisfinding,aTietjen-Moorestatisticaltestwas

conductedtodeterminewhetherthereweresignificantoutliersinthe

centralization,generation,conversion,ordiffusionscoresforprivateinstitutions.

Onecentralizationscorewaseliminatedfromthedataandthreevalueswere

eliminatedfromthegenerationscores;however,correlationsdidnotchange

significantly(r=.39.,.34,and.35vs.r=.40,.33,and.33,respectively).

Privateuniversitiesdidnothavesignificantlyhighercentralizationscores

thanpublicuniversities(meanscoresof93and92,respectively).However,

decentralizedstaffreportedmuchhigherandmorenegativeimpactsfrom

centralization(r=.51,.39,.30)thancentralizedstaff(.30,.29.,.40).Bothsetsof

numbersclearlyindicatethatprivateinstitutionsexperiencenegativeinnovation

processissuesascentralizationincreases,andthisproblemisseenbothby

centralizedanddecentralizedstaff.Thatthispatternemergedinprivateinstitutions

50

ratherthaninpublicinstitutionsmayreflectanumberofmoderatingfactors,

includingbudget(15ofthe20highest-endowedR1universitiesareprivate

institutions,perhapslargebudgetsproducemorestaticenvironments),

organizationalstructures(centralizationmaybemorereflectiveofhierarchicaland

bureaucraticstructuresutilizedinpublicschools)andculture(perhapsprivate

schoolsaremoreculturallyentwinedwithtradition,potentiallyslowingthe

generation,conversion,anddiffusionofnewideas).

Jointreportsoccupiedasmallbutinterestingportionofthedataforthe

presentstudy.Staffwithjointreportsstronglyindicatedanegativeeffectof

centralizationontheconversionprocess.Itispossiblethatthenatureofthese

positions—bridginglocalandcentralunits—couldplacethematthefrontlines

wherenewideasareconvertedintoservicestobediffusedthroughouttherestof

theinstitution.Suchstrikingresultsareworthyofalargerinvestigation.

51

ChapterV

Discussion

HighereducationintheUnitedStatesfacesanunprecedentedcollectionof

simultaneouschallengesaftermanydecadesofrelativestasis.Thesechallenges

comeintheformofnewbusinessmodels,newstudentpopulations,new

competition,andnewtechnologies.Asfinancialpressuresmount,manyinstitutions

haveturnedtoorganizationalcentralizationasawaytoincreaseefficiencyand

maximizeoperationalinvestments.However,thecaseforcentralizationhasarisen

concurrentlywithanequallystrongcaseforinnovation.Callsforreformin

Americanhighereducationhavereachedanewcrescendoastuitionhasspiraled

upward,studentdebthasincreased,andsmallerschoolshavebeguntofailatever-

growingrates.

Inrecognizingthesechallenges,thisresearchstudysoughttoisolate

commonlyknownattributesofcentralizationandfocusonvariablesthatcouldbe

moreeasilycontrolledbyinstitutionsregardlessoforganizationalstructure.Two

factorswithahighlevelofvalidationinpreviousstudies,participationindecision-

makingandhierarchyofauthority,wereselectedasmeasuresofcentralizationthat

couldbemoreeasilychangedataninstitutionallevelthanothermeasures(e.g.,

politicalstructures,budgetmodels,etc.).

Thesevariableswerethencombinedtocreateacentralizationscoreinorder

todeterminehowimpactfulthistypeofcentralizationwasontheinnovation

process.Giventheincreasingimportanceoftechnologyforinnovationinallfields,

includingeducation,thisstudyfocusedonITsupportunitsandtheirstaffatR1

52

universities,whichrepresenttheflagshipinstitutionsforAmericanhigher

education.

Datawasgatheredfrom303ITworkersat38R1institutionsrepresenting

statesincludingCalifornia,Connecticut,Georgia,Illinois,Indiana,Iowa,Kentucky,

Maryland,Massachusetts,Michigan,Minnesota,Missouri,Nebraska,NewJersey,

NewYork,NorthCarolina,Ohio,Oregon,Pennsylvania,SouthCarolina,Texas,

Washington,andWisconsin.Theresultswerecompiledandanalyzedforpopulation

segments,institutionaltype,scoredistributions,andscorecorrelationsviaJASPand

MicrosoftExcel.

SummaryofFindings

Participantsinthepresentstudyfoundthatcentralizationhadnegative

impactsonideagenerationandconversion(seeFigure8).Thescaleofthese

impactsrangedfromweaktostrong,dependingontheinstitutiontype,theposition

type,andthepositionreportingmodel.Surprisingly,theimpactofcentralizationon

thediffusionprocessseemedtoshowextremelymixedresultsandvariedgreatly

dependingonwhethertheinstitutionwaspublicorprivate.

Figure 9. Correlation plots for centralization to generation, conversion, and diffusion. Edmund

Clark (2016). Source data from survey results.

53

Thehypothesisthatcentralizationwouldadverselyimpacttheidea

generationprocesswassupported,aswasthehypothesisthatcentralizationwould

alsohavenegativeimpactsforconversion.Thesefindingsaresignificantinthat

presentstudyhascontrolledforthetypesofinstitutionsstudied(R1institutions)as

wellasthesubtypeoforganization(ITsupportunits),andsohastherefore

establishedsomemeasureofcontrolforpotentiallymoderatingvariablessuchas

size,slackresources,specialization,andfunctionaldifferentiation(Greenhalgh,et

al.,2004).Thesecorrelationswerefoundregardlessofinstitutiontype(publicor

private),organizationtype(centralizedordecentralized)orstaffreportingtype

(centralized,decentralized,orjoint).However,thevariableofinstitutiontypewas

showntobeimportant,asthereweresignificantdifferencesinresultsfrompublic

vs.privateinstitutions.

Perhapsthemoststrikingexampleofthisdifferenceisthefindingthat

centralizationhadwidelydifferentimpactsoninnovationdiffusionatthesetwo

typesofinstitutions.Theoverallimpactforpublicswasnonsignificant(r=-.05,

range=-.07-.04),whiletheimpactforprivateswasnegativeandmuchmore

powerful(r=.33).Thefactthatbothcentralizedanddecentralizedstaffatprivate

schoolsagreedonthisfinding(rangeofr=.30-.40)callsforafocusedinvestigation

onthisissue.

Onepossibleexplanationisthatpublicschoolsexhibitmorebureaucratic

structuresthanprivateschools,andthereforearelessimpactedbyincreased

centralization.Thishypothesiswouldrequireacomparisonandevaluationof

organizationalstructuresattheseinstitutions.However,onewouldalsohaveto

54

explainwhythisincreasedcentralizationonlyhadasignificantlydifferentimpacton

innovationdiffusion.Itispossiblethatbureaucraticcontrolsonthediffusionofa

newinnovationaremoreacceptableatpublicuniversitiesthanatprivate

universities.

Budgetsizeisanotherpossibleexplanation.Itispossiblethatextremely

wealthyinstitutionsarelesspronetodiffusenewinnovationsbecausetheyare

underfewerpressurestodoso.Therefore,intentionaldiffusionthrough

centralizationwouldhaveanegativeeffectontheprocess,andwouldbeculturally

incompatible.

Anotherpotentiallysignificantfindingwasthatjointreportssawmuch

differentpatternsintherelationshipbetweencentralizationandtheinnovation

process.Fortheseindividuals,ideaconversionwasthemostnegativelyimpacted

fromcentralization.Theseresultsarenotasreliableastheotherfindings,giventhe

smallsamplesizeofthispopulation(n=24).However,themeanoftheconversion

scoreswasnotsignificantlydifferentfromthatofthetotalpopulation(µ=7.79vs.

7.77,respectively).Onepotentialexplanationisthatthesestaffoccupyaspace

whereideaconversionismorelikelytooccur.Inordertoinvestigatethis,onecould

conductastudytoexaminewhattypesofinnovationsaremorelikelytobeseenby

thispopulationaswellashowtheyfunctionwithintheinnovationprocess

continuum.

Implications

Theimplicationsofthesefindingsaresignificant,inthatthecentralization

factorsusedforthepresentstudyaretheoreticallyunderofthecontrolofmanagers

55

andsupervisors,regardlessoforganizationalstructureorinstitutiontype.

Irrespectiveofbudgetfactorsorreportingmodels,alargenumberofpotential

interventionscouldbeemployedtoincreaseparticipationindecision-makingwhile

allowingindividualstomakemorelocaldecisionstotrynewtechnologiesand

processes.Fortheformer,greateremploymentofcommunicationandfeedback

mechanismscouldincreaseparticipationwhilesimultaneouslyimprovingworking

relationshipswithdecentralizedunits.Inordertocontrolforthepotentialnegative

effectsofthelatter,anorganizationcouldspecifylengthsoftimefornewpilots

whileensuringthatpilotsareactivelyencouragedandthatresultsareshared

widely(whetherpositiveornegative).

Thepresentstudysoughttoestablishaconnectionbetweenmore

controllableaspectsofcentralizationandtheirimpactsontheinnovationprocess.

Giventhemanychallengesfacinghighereducation,anintensifiedfocuson

innovationwillbenecessarytoensurethatinstitutionssurviveandthriveasthey

moveintonewandunchartedwaters.Whileincreasingcentralizationandefficiency

maybemandatedbyexecutiveboardsandstatelegislatures,thereishopethatitis

possibletoaccomplishsuchgoalswhileprotectingandfortifyingtheinnovation

process.Theresultsofthisstudysuggestthatthereareindeedwaystoprevent

certainaspectsofcentralizationfromdisruptingthegenerationandconversionof

newideas.

StrengthsandLimitations

Thestrengthsofthepresentstudyincludefourprimaryitems:1)anew

operationalizationofpreviouslyvalidatedcentralizationinstrumentsonthe

56

innovationvaluechain,2)adiscoveryofimportantfactorsthatimpactthe

innovationprocessatR1institutions,3)adiscoverythatthetypeofinstitutionhas

animportanteffectoninnovationdiffusion,and4)acontributiontonewknowledge

inthestudyofhighereducationintheUnitedStates.

ThepresentstudywasthefirsttoemployHage&Aiken’s(1971)measuresof

participationindecision-makingandhierarchyofauthoritytodetermineimpactson

theinnovationprocessasmeasuredbyHansen&Birkinshaw’s(2007)innovation

valuechaintool.Thisoperationalizationhelpedtofurtherisolatehow

centralizationadverselyimpactstheinnovationprocess,therebycontributingtothe

ever-expandingbodyofinnovationresearch.

Byutilizingthetooldevelopedforthepresentstudy,intriguingcorrelations

werediscoveredbetweenthecentralizationmeasureandeachphaseofthe

innovationvaluechain.Thesecorrelationssuggestthatinstitutionsshouldcarefully

evaluatehowwelltheyenableparticipationandlocaldecision-makingastheywork

throughtheinnovationprocess.

Thediscoverythatprivateuniversitiessufferfromcentralizationindifferent

andmorepowerfulwaysthanpublicuniversitiesisanimportantfinding.This

suggeststhattherearesignificantmoderatingcircumstancesthatmustbe

accountedforwhencomparingpublicandprivateR1institutions,andthattheyare

notashomogenousassometimesbelieved.

Finally,thepresentstudycontributedtothebodyofknowledgeofhigher

educationintheUnitedStatesbyexpandingunderstandingoftheimportanceofIT

57

subunitsintheinnovationprocessaswellasthehighlightingkeyvariablesthat

affecttheinnovationprocessattheseinstitutions.

Thepresentstudyalsohadsomenotablelimitations.First,theinstitutions

thatrespondedmaynotadequatelyrepresenttheentirebodyofAmericanR1

institutions.Certaingeographicalregionsofthecountry,includingtheSoutheast

andSouthwest,wereeitherinadequatelyrepresentedornotrepresentedatall.

Furthermore,itisunknownhowwellfindingsatthese38R1institutionswould

translateforthevastmajorityofinstitutionsthatoccupyothertiersintheCarnegie

classificationsystem.

Second,theuseofanationalITleadershipdevelopmentprogramto

determineparticipantshaslimitationsinthatthepopulationreflectsatop-heavy

population(i.e.,moreoften,higherrankingmanagers).Itispossiblethatincluding

morestaffattheoperationallevel(e.g.,programmers,systemadministrators,

desktoptechnicians,etc.)wouldchangetheseresultssignificantly.Moreover,entry

intotheMORLeadershipProgramrequiressponsorshipfromthecentralIToffice

(usuallyfromtheCIOoftheinstitution),sotherelationshipsbetweenthese

populationsofdecentralizedandcentralizedstaffmaynottypifystandard

relationshipsatthesetypesofinstitutions.

Finally,asinanystudyofthisscope,thepotentialimportanceofmoderating

variablesloomslarge.InGreenhalgh,etal.’s(2004)reviewofinnovationdiffusion

literature,organizationalfactorssuchassize,maturity,functionaldifferentiation,

specialization,slackresources,anddecentralizationtakentogetherhada.39

correlationwithinnovationadoptionanddiffusion.Inthisrespect,thefindingsof

58

thepresentstudyareextremelysignificant,inthatdecision-makingandhierarchyof

authoritymadeupanextremelylargeportion(.33,.29)ofthistotal.

However,onecouldtheorizethatmoderatingvariables,likeorganizational

size,shouldbeaccountedformorespecificallyinthesecorrelations.Because

Damanpour’s(1996)studydefinedlargeorganizationsasanyorganizationswith

morethan500employees,allinstitutionsinthisstudyqualifiedaslarge.Therefore,

sizewouldbeahiddenvariablewithaneffectthatmustbeaccountedfor.(Infact,

allR1institutionswouldqualifyas“large”underthisdefinition,sonewwaysof

discoveringtheimpactoforganizationalsizemustbedevelopedandinvestigatedin

thissector.)Alargemetastudyof53relatedstudiesconductedbyCamison-Zornoza

etal.,(2004)foundacorrelationbetweensizeandinnovationat(r=.15).However,

thisstudydidnotincludeeducationalinstitutions.Illustratingthemixedresults

foundinthisareaofresearch,Damanpour’s(1996)studyoncentralizationand

innovationfoundthat“theeffectofsizeoncentralization-innovationwas

nonsignificant”(p.11).

WhileitispossiblethatothervariablesdiscussedbyGreenhalgh,etal.

(2004)(namely,functionaldifferentiation,specialization,andslackresources)

beyondthosepreviouslydiscussedinthepresentstudy(participationindecision-

making,hierarchyofauthority,andorganizationalsize)haveextremelysmall

impactsoninnovativeness,itisunlikely.Therefore,eachofthesevariablesshould

alsobeisolated,measured,andcorrelatedtofindtowhatextenttheyserveas

moderatingvariablesforthisstudyandotherslikeit.Whilethefocusofthepresent

studyonITsubunitsandR1institutionshassubstantiallycontrolledforthese

59

variables,thereisnearlyalwaysroomforimprovement,especiallyincreatingan

operationalcontinuumforeachofthesevariables.Theselimitationshavethe

potentialtolimitthegeneralizabilityofthefindingsinthepresentstudy.

Recommendationsforfurtherresearch

Theresultsfromthepresentstudy,alongwithitsconcomitantstrengthsand

weaknesses,yieldseveralrecommendationsforfurtherinvestigation.First,the

studycouldbeexpandedtoincludeagreaterrepresentationofallITworkers,

includingworkersthatdonotparticipateintheMORprogram,aswellasincluding

moretypesofinstitutions.Suchastudycouldbeconductedwithamore

encompassingdistributionlist,likethatofEducause.Includingthisexpanded

populationcouldrevealnewpatternsandcorrelationsbetweencentralizationand

theinnovationprocess.

Second,thefindingofdifferencesinthecentralization-innovationprocess

betweenpublicandprivateR1shasthepotentialtobeafruitfulareaofresearch.

Thesemoderatingfactorsshouldbeidentifiedandmeasuredsothatfutureresearch

inhighereducationinnovationcanaccountforthesedifferences.Itispossiblethat

identifiedmoderatorscouldalsoapplytoothertypesofinstitutionsandsituations.

Finally,theimpactofthejointreportingstructureinITsubunitsshouldbe

investigatedmorethoroughly.Itispossiblethatincreasingcentralizationdemands

willresultinpopulationgrowthforthistypeofposition,andthereforeitis

importanttounderstandtheuniquechallengesandopportunitiesconfrontedbythis

groupofindividuals.Theideathatspecifictypesofreportingarrangementscan

60

haveimportantimpactsontheinnovationprocessmayuncoverafertileareaofnew

research.

61

References

Abrahamson,E.,&Rosenkopf,L.(1997).Socialnetworkeffectsontheextentof

innovationdiffusion:Acomputersimulation.Organizationscience,8(3),289-

309.

Abrunhosa,A.,&Sá,P.M.(2008).OrganisationalEnablersofProcessInnovationin

thePortugueseFootwearIndustry:DoSubunits’DifferencesMatter?.Centro

deEstudosSociais,September.

Agranoff,R.(1976).Themanagementofelectioncampaigns.HolbrookPress.

Aiken,L.H.,Clarke,S.P.,&Sloane,D.M.(2000).Hospitalrestructuring:doesit

adverselyaffectcareandoutcomes?.JournalofNursing

Administration,30(10),457-465.

Aiken,M.,&Hage,J.(1971).Theorganicorganizationandinnovation.

Sociology,5(1),63-82.

Allen,I.E.,&Seaman,J.(2007).Onlinenation:Fiveyearsofgrowthinonline

learning.

SloanConsortium.POBox1238,Newburyport,MA01950.

Al-Qahtani,A.A.,&Higgins,S.E.(2013).Effectsoftraditional,blendedande-

learningonstudents'achievementinhighereducation.JournalofComputer

AssistedLearning,29(3),220-234.

Anderson,N.,&King,N.(1993).InnovationinOrganizations.InternationalReview

of

IndustrialandOrganizationalPsychology,8,1-34.

Andrews,R.,Boyne,G.A.,&Walker,R.M.(2006).Strategycontentand

62

organizationalperformance:Anempiricalanalysis.PublicAdministration

Review,66(1),52-63.

Archibald,R.B.,&Feldman,D.H.(2012).Theanatomyofcollegetuition.The

AmericanCouncilonEducation,1.

Aubert,B.A.,&Hamel,G.(2001).Adoptionofsmartcardsinthemedicalsector:

the

Canadianexperience.SocialScience&Medicine,53(7),879-894.

Audia,P.G.,Locke,E.A.,&Smith,K.G.(2000).Theparadoxofsuccess:Anarchival

andalaboratorystudyofstrategicpersistencefollowingradical

environmentalchange.AcademyofManagementjournal,43(5),837-853.

Baldridge,J.V.,&Burnham,R.A.(1975).Organizationalinnovation:Individual,

organizational,andenvironmentalimpacts.Administrativesciencequarterly,

165-176.

Bates,A.T.(2005).Technology,e-learninganddistanceeducation.Routledge.

Baum,S.&Ma,J.(2012).TrendsinCollegePricing2012.TheCollegeBoard.

Bavelas,A.(1948).Amathematicalmodelforgroupstructures.Human

organization,7(3),16-30.

Belkin,D.,&Thurm,S.(2012).DeansList:HiringSpreeFattensCollege

Bureaucracy–andTuition.WallStreetJournal,28.

Boerma,L.(2014).Kidswithcellphones:Howyoungistooyoung?Retreivedfrom

http://www.cbsnews.com/news/kids-with-cell-phones-how-young-is-too-

young/

Boezerooij,P.(2006).E-learningstrategiesofhighereducationinstitutions:an

63

exploratorystudyintotheinfluenceofenvironmentalcontingencieson

strategicchoicesofhighereducationinstitutionswithrespecttointegratinge-

learningintheireducationdeliveryandsupportprocesses.Universityof

Twente,CHEPS.

Bogaty,E.(2013).Announcement:Moody's:2013outlookforentireUSHigher

Educationsectorchangedtonegative.Retrievedfrom

https://www.moodys.com/research/Moodys-2013-outlook-for-entire-US-

Higher-Education-sector-changed--PR_263866

Borins,S.(1998).InnovatingwithIntegrity:HowLocalHeroesAreTransforming

AmericanGovernment.Washington,DC:GeorgetownUniversityPress.

Borins,S.(2001).Encouraginginnovationinthepublicsector.Journalof

intellectual

capital,2(3),310-319.

Camisón-Zornoza,C.,Lapiedra-Alcamí,R.,Segarra-Ciprés,M.,&Boronat-Navarro,M.

(2004).Ameta-analysisofinnovationandorganizationalsize.Organization

Studies,25(3),331-361.

Campbell,A.,&Park,R.(2005).TheGrowthGamble.NicholasBrealey

International.

Carroll,G.R.,&Teo,A.C.(1996).Creativeself-destructionamongorganizations:

An

empiricalstudyoftechnicalinnovationandorganizationalfailureinthe

Americanautomobileindustry,1885–1981.IndustrialandCorporate

Change,5(2),619-644.

64

Christensen,C.M.(1997).TheInnovator'sDilemma:TheRevolutionaryBookthat

WillChangetheWayYouDoBusiness.CollinsBusinessEssentials.

Christensen,C.M.,&Bower,J.L.(1996).Customerpower,strategicinvestment,

and

thefailureofleadingfirms.Strategicmanagementjournal,17(3),197-218.

Christensen,J.F.,Olesen,M.H.&Kjær,J.S.(2004).Theindustrialdynamicsofopen

innovation–evidencefromthetransformationofconsumerelectronics.

Workingpaper,CopenhagenBusinessSchool,DepartmentofIndustrial

EconomicsandStrategy.

Covington,D.,Petherbridge,D.,&Warren,S.E.(2005).Bestpractices:A

triangulated

supportapproachintransitioningfacultytoonlineteaching.OnlineJournal

ofDistanceLearningAdministration,8(1).

Creasey,W.(2008).TheInfluencesofInformationTechnologyOrganizational

PerformanceinHigherEducation.

Crossan,M.M.,&Apaydin,M.(2010).Amulti-dimensionalframeworkof

organizationalinnovation:Asystematicreviewoftheliterature.Journalof

managementstudies,47(6),1154-1191.

Damanpour,F.(1996).Organizationalcomplexityandinnovation:developingand

testingmultiplecontingencymodels.Managementscience,42(5),693-716.

Damanpour,F.,&Wischnevsky,J.D.(2006).Researchoninnovationin

65

organizations:Distinguishinginnovation-generatingfrominnovation-

adoptingorganizations.Journalofengineeringandtechnology

management,23(4),269-291.

Damanpour,F.,Walker,R.M.,&Avellaneda,C.N.(2009).Combinativeeffectsof

innovationtypesandorganizationalperformance:Alongitudinalstudyof

serviceorganizations.Journalofmanagementstudies,46(4),650-675.

Davis,F.D.(1989).Perceivedusefulness,perceivedeaseofuse,anduser

acceptance

ofinformationtechnology.MISquarterly,319-340.

Denis,J.L.,Hébert,Y.,Langley,A.,Lozeau,D.,&Trottier,L.H.(2002).Explaining

diffusionpatternsforcomplexhealthcareinnovations.Healthcare

managementreview,27(3),60-73.

Desrochers,D.M.(2010).TrendsinCollegeSpending1998-2008:WhereDoesthe

MoneyComeFrom?WhereDoesitGo?WhatDoesitBuy?.DeltaCostProject.

Dewar,R.D.,Whetten,D.A.,&Boje,D.(1980).Anexaminationofthereliability

and

validityoftheAikenandHagescalesofcentralization,formalization,andtask

routineness.AdministrativeScienceQuarterly,120-128.

Dill,D.D.(2003).Allowingthemarkettorule:ThecaseoftheUnitedStates.

Higher

EducationQuarterly,57(2),136-157.

Donaldson,T.,&Preston,L.E.(1995).Thestakeholdertheoryofthecorporation:

66

Concepts,evidence,andimplications.Academyofmanagement

Review,20(1),65-91.

Dougherty,K.J.,Natow,R.S.,Bork,R.H.,Jones,S.M.,&Vega,B.E.(2013).

Accounting

forhighereducationaccountability:Politicaloriginsofstateperformance

fundingforhighereducation.TeachersCollegeRecord,115(1),1-50.

Ducharme,LoriJ.,HannahK.Knudsen,PaulM.Roman,andJ.AaronJohnson.

"Innovationadoptioninsubstanceabusetreatment:Exposure,trialability,

andtheClinicalTrialsNetwork."Journalofsubstanceabusetreatment32,no.

4(2007):321-329.

Dumbrigue,C.,Moxley,D.,&Najor-Durack,A.(2013).Keepingstudentsinhigher

education:Successfulpracticesandstrategiesforretention.Routledge.

Ehrenberg,R.G.(2012).Americanhighereducationintransition.TheJournalof

EconomicPerspectives,26(1),193-216.

Ensminger,D.C.(2005).Implementationprofileinventory:comparingK–12,

higher

educationandbusiness.BritishJournalofEducationalTechnology,36(6),

1059-1061.

Fennell,M.L.,&Warnecke,R.B.(1988).DefinitionandDiffusionoftheInnovation.

InTheDiffusionofMedicalInnovations(pp.171-192).SpringerUS.

Ferlie,E.B.,&Shortell,S.M.(2001).Improvingthequalityofhealthcareinthe

UnitedKingdomandtheUnitedStates:aframeworkforchange.Milbank

Quarterly,79(2),281-315.

67

Ferrell,O.C.,&Skinner,S.J.(1988).Ethicalbehaviorandbureaucraticstructure

in

marketingresearchorganizations.journalofMarketingResearch,103-109.

Fitzgerald,L.,Ferlie,E.,Wood,M.,&Hawkins,C.(2002).Interlockinginteractions,

thediffusionofinnovationsinhealthcare.Humanrelations,55(12),1429-

1449.

Freeman,L.C.(1978).Centralityinsocialnetworksconceptualclarification.Social

networks,1(3),215-239.

Fritsch,M.,&Kauffeld-Monz,M.(2010).Theimpactofnetworkstructureon

knowledgetransfer:anapplicationofsocialnetworkanalysisinthecontext

ofregionalinnovationnetworks.TheAnnalsofRegionalScience,44(1),21-

38.

Fuller,M.K.,&Swanson,E.B.(1992).Thediffusionofinformationcenters:

Patternsofinnovationadoptionbyprofessionalsubunits.InProceedingsof

the1992ACMSIGCPRconferenceonComputerpersonnelresearch(pp.370-

387).ACM.

Gavigan,K.,&Kurtts,S.(2010).Togetherwecan:Collaboratingtomeettheneeds

of

at-riskstudents.LibraryMediaConnection,29(3),10.

Geiger,R.(2015).ImpactofthefinancialcrisisonhighereducationintheUnited

States.InternationalHigherEducation,(59).

George,A.A.,Hall,G.E.,Stiegelbauer,S.M.,&Litke,B.(2008).Stagesofconcern

questionnaire.Austin,TX:SouthwestEducationalDevelopmentLaboratory.

68

Giannoni,D.L.,&Tesone,D.V.(2003).Whatacademicadministratorsshould

know

toattractseniorlevelfacultymemberstoonlinelearningenvironments.

OnlineJournalofDistanceLearningAdministration,6(1).

Glynn,M.A.(1996).Innovativegenius:Aframeworkforrelatingindividualand

organizationalintelligencestoinnovation.Academyofmanagement

review,21(4),1081-1111.

Graham,C.R.,Woodfield,W.,&Harrison,J.B.(2013).Aframeworkfor

institutional

adoptionandimplementationofblendedlearninginhighereducation.The

internetandhighereducation,18,4-14.

Greenhalgh,T.,Robert,G.,Macfarlane,F.,Bate,P.,&Kyriakidou,O.(2004).Diffusion

ofinnovationsinserviceorganizations:systematicreviewand

recommendations.MilbankQuarterly,82(4),581-629.

Gresov,C.(1989).Exploringfitandmisfitwithmultiplecontingencies.

AdministrativeScienceQuarterly,431-453.

Griffith,T.L.,Zammuto,R.F.,&Aiman-Smith,L.(1999).Whynewtechnologies

fail:

Overcomingtheinvisibilityofimplementation.Industrial

management,41(3),29-34.

Guan,J.,&Chen,K.(2010).Measuringtheinnovationproductionprocess:Across-

regionempiricalstudyofChina’shigh-techinnovations.Technovation,30(5),

348-358.

69

Gupta,A.K.,Smith,K.G.,&Shalley,C.E.(2006).Theinterplaybetween

exploration

andexploitation.Academyofmanagementjournal,49(4),693-706.

Hage,J.,&Aiken,M.(1967).Relationshipofcentralizationtootherstructural

properties.AdministrativeScienceQuarterly,72-92.

Hall,G.E.,&Hord,S.M.(1987).Changeinschools:Facilitatingtheprocess.SUNY

Press.

Hampson,K.(2012).MOOCs:ThePrestigeFactor.Retrievedfrom

http://higheredmanagement.net/2012/05/20/moocs-the-prestige-factor/

Hansen,M.T.,&Birkinshaw,J.(2007).Theinnovationvaluechain.Harvard

business

review,85(6),121.

Heide,M.,Grønhaug,K.,&Johannessen,S.(2002).Exploringbarrierstothe

successfulimplementationofaformulatedstrategy.ScandinavianJournalof

Management,18(2),217-231.

Hemsley-Brown,J.,&Oplatka,I.(2006).Universitiesinacompetitiveglobal

marketplace:Asystematicreviewoftheliteratureonhighereducation

marketing.InternationalJournalofPublicSectorManagement,19(4),316-

338.

Hill,C.W.,&Rothaermel,F.T.(2003).Theperformanceofincumbentfirmsinthe

faceofradicaltechnologicalinnovation.AcademyofManagement

Review,28(2),257-274.

70

Holahan,P.J.,Aronson,Z.H.,Jurkat,M.P.,&Schoorman,F.D.(2004).

Implementing

computertechnology:amultiorganizationaltestofKleinandSorra’smodel.

JournalofEngineeringandTechnologyManagement,21(1),31-50.

Hoxby,C.M.(1997).HowthechangingmarketstructureofUShighereducation

explainscollegetuition(No.w6323).NationalBureauofEconomicResearch.

Huisman,J.,&Currie,J.(2004).Accountabilityinhighereducation:Bridgeover

troubledwater?.HigherEducation,48(4),529-551.

Infosys(2016).AmplifyingHumanPotential:EducationandSkillsfortheFourth

IndustrialRevolution.Retrievedfrom

http://www.experienceinfosys.com/humanpotential

Jeyaraj,A.,Rottman,J.W.,&Lacity,M.C.(2006).Areviewofthepredictors,

linkages,

andbiasesinITinnovationadoptionresearch.JournalofInformation

Technology,21(1),1-23.

Jones,D.J.,&Watson,B.C.(1990).High-RiskStudentsandHigherEducation:

Future

Trends.ASHE-ERICHigherEducationReportNo.3.ASHE/ERICHigher

EducationReports,TheGeorgeWashingtonUniversity,OneDupontCircle,

Suite630,Washington,DC20036-1183.

Kaluzny,A.D.,Veney,J.E.,&Gentry,J.T.(1974).Innovationofhealthservices:A

comparativestudyofhospitalsandhealthdepartments.TheMilbank

MemorialFundQuarterly.HealthandSociety,51-82.

71

Kassens-Noor,E.(2012).Twitterasateachingpracticetoenhanceactiveand

informallearninginhighereducation:Thecaseofsustainabletweets.Active

LearninginHigherEducation,13(1),9-21.

Kemp,R.,Folkeringa,M.,DeJong,J.P.,&Wubben,E.F.(2003).Innovationandfirm

performance.Zoetermeer:EIMBusiness&PolicyResearch.

Kim,L.(1980).Organizationalinnovationandstructure.JournalofBusiness

Research,8(2),225-245.

King,R.P.(2007).Governanceandaccountabilityinthehighereducation

regulatory

state.HigherEducation,53(4),411-430.

Klein,K.J.,&Knight,A.P.(2005).Innovationimplementation:Overcomingthe

challenge.Currentdirectionsinpsychologicalscience,14(5),243-246.

Kleinschmidt,E.J.,&Cooper,R.G.(1995).Therelativeimportanceofnewproduct

successdeterminants—Perceptionversusreality.R&DManagement,25(3),

281-298.

Klemencic,M.,&Fried,J.(2015).Demographicchallengesandfutureofthehigher

education.InternationalHigherEducation,(47).

Kodama,M.(2009).Boundariesinnovationandknowledgeintegrationinthe

Japanesefirm.LongRangePlanning,42(4),463-494.

Kuusisto,F.(2015).VRhead-mounteddisplays.XRDS:Crossroads,TheACM

MagazineforStudents-VirtualReality,22(1),64-65.

Lam,B.(2015).For-ProfitColleges:Heretostayandthatmaynotbesuchabad

72

thingafterall.Retrievedfrom

http://www.theatlantic.com/business/archive/2015/04/for-profit-colleges-

here-to-stay/389045/

Lane,J.E.(2007).Thespiderwebofoversight:Ananalysisofexternaloversightof

highereducation.TheJournalofHigherEducation,78(6),615-644.

Leveille,D.E.(2006).Accountabilityinhighereducation:Apublicagendafortrust

andculturalchange.CenterforStudiesinHigherEducation.

Lin,A.,&Chen,N.C.(2012).Cloudcomputingasaninnovation:Perception,

attitude,

andadoption.InternationalJournalofInformationManagement,32(6),533-

540.

Lindsay,T.(2015).UniversityofTexasLookstoLimitAdministrativeBloat.

Retrievedfrom

http://www.forbes.com/sites/tomlindsay/2015/01/24/university-of-texas-

looks-to-limit-metastasizing-administrative-bloat/#40c9175b458a

Maguire,L.L.(2005).Literaturereview–facultyparticipationinonlinedistance

education:Barriersandmotivators.OnlineJournalofDistanceLearning

Administration,8(1).

McLendon,M.K.,Hearn,J.C.,&Deaton,R.(2006).Calledtoaccount:Analyzingthe

originsandspreadofstateperformance-accountabilitypoliciesforhigher

education.EducationalEvaluationandPolicyAnalysis,28(1),1-24.

Merchant,Z.,Goetz,E.T.,Cifuentes,L.,Keeney-Kennicutt,W.,&Davis,T.J.(2014).

73

Effectivenessofvirtualreality-basedinstructiononstudents'learning

outcomesinK-12andhighereducation:Ameta-analysis.Computers&

Education,70,29-40.

Meyer,A.D.,&Goes,J.B.(1988).Organizationalassimilationofinnovations:A

multilevelcontextualanalysis.Academyofmanagementjournal,31(4),897-

923.

Miles,R.E.,Snow,C.C.,Meyer,A.D.,&Coleman,H.J.(1978).Organizational

strategy,

structure,andprocess.Academyofmanagementreview,3(3),546-562.

Mortenson,T.G.(2012).Statefunding:Aracetothebottom.ThePresidency,15(1),

26-29.

Nadler,D.,&Tushman,M.(1997).Competingbydesign:Thepoweroforganizational

architecture.OxfordUniversityPress.

O’Reilly,C.A.,&Tushman,M.L.(1997).Usingcultureforstrategicadvantage:

promotinginnovationthroughsocialcontrol.Managingstrategicinnovation

andchange:Acollectionofreadings,200-216.

Pennings,J.M.,Hickson,D.J.,Hinings,C.R.,Lee,C.A.,&Schneck,R.E.(2014).

UncertaintyandPowerinOrganizations.AStrategicContingencies'Modelof

Sub-UnitFunctioning.Mensenmaatschappij,44(5),418-433.

Polley,D.E.,Garud,R.,&Venkataraman,S.(1999).Theinnovationjourney.

Rhoades,G.,&Slaughter,S.(2004).Academiccapitalismintheneweconomy:

Challengesandchoices.AmericanAcademic,1(1),37-59.

Rogers,E.M.(2003).Diffusionofinnovation.5thed.

74

Roper,S.,&Arvanitis,S.(2012).Fromknowledgetoaddedvalue:Acomparative,

panel-dataanalysisoftheinnovationvaluechaininIrishandSwiss

manufacturingfirms.ResearchPolicy,41(6),1093-1106.

Roper,S.,Du,J.,&Love,J.H.(2008).Modellingtheinnovationvaluechain.Research

Policy,37(6),961-977.

Rosenberg,M.J.(2001).E-learning:Strategiesfordeliveringknowledgeinthe

digital

age(Vol.3).NewYork:McGraw-Hill.

Rosenbusch,N.,Brinckmann,J.,&Bausch,A.(2011).Isinnovationalways

beneficial?

Ameta-analysisoftherelationshipbetweeninnovationandperformancein

SMEs.JournalofbusinessVenturing,26(4),441-457.

Schumpeter,J.(1942).Creativedestruction.Capitalism,socialismanddemocracy.

Siemens,G.,&Matheos,K.(2012).Systemicchangesinhighereducation.

Education,16(1).

Siggelkow,N.,&Levinthal,D.A.(2003).Temporarilydividetoconquer:

Centralized,

decentralized,andreintegratedorganizationalapproachestoexploration

andadaptation.OrganizationScience,14(6),650-669.

Smart,K.L.,&Cappel,J.J.(2006).Students'perceptionsofonlinelearning:A

comparativestudy.JournalofInformationTechnologyEducation,5(1),

20119.

75

Snyder,T.D.,&Dillow,S.A.(2015).DigestofEducationStatistics2013.NCES

2015-

011.NationalCenterforEducationStatistics.

Spellings,M.(2006).Atestofleadership:ChartingthefutureofUShighereducation.

USDepartmentofEducation.

Steel,E.&Marsh,B.(2015).MillennialsandCuttingtheCord:Mediaconsumption

habitsarechangingfast,especiallyamongyoungadultsages18to34.

Retrievedfrom

http://www.nytimes.com/interactive/2015/10/03/business/media/changi

ng-media-consumption-millenials-cord-cutters.html

Stoker,J.I.,Looise,J.C.,Fisscher,O.A.M.,&Jong,R.D.(2001).Leadershipand

innovation:relationsbetweenleadership,individualcharacteristicsandthe

functioningofR&Dteams.InternationalJournalofHumanResource

Management,12(7),1141-1151.

Surry,D.,&Ely,D.(2002).Adoption,diffusion,implementation,and

institutionalizationofinstructionaldesignandtechnology.Trendsand

issuesininstructionaldesignandtechnology.

Sydell,L.(2016).Is2016TheYearVirtualRealityFinallyGoesMainstream?

Retrievedfrom

http://www.npr.org/sections/alltechconsidered/2015/12/30/461432244/i

s-2016-the-year-virtual-reality-finally-goes-mainstream

Tidd,J.(2001).Innovationmanagementincontext:environment,organizationand

performance.InternationalJournalofManagementReviews,3(3),169-183.

76

Tidd,J.,Pavitt,K.,&Bessant,J.(2001).Managinginnovation(Vol.3).Chichester:

Wiley.

U.S.SecretaryofCommerceAdvisoryCommittee(2008).Innovation

Measurement:

TrackingtheStateofInnovationintheAmericanEconomy.Retrievedfrom

http://users.nber.org/~sewp/SEWPdigestFeb08/InnovationMeasurement2

001_08.pdf

Tornatzky,L.G.,&Klein,K.J.(1982).Innovationcharacteristicsandinnovation

adoption-implementation:Ameta-analysisoffindings.Engineering

Management,IEEETransactionson,(1),28-45.

Treisman,D.(2002).Definingandmeasuringdecentralization:aglobal

perspective.Unpublishedmanuscript.

Tushman,M.,Smith,W.K.,Wood,R.C.,Westerman,G.,&O’Reilly,C.(2010).

Organizationaldesignsandinnovationstreams.IndustrialandCorporate

Change,19(5),1331-1366.

VandeVen,A.H.(1986).Centralproblemsinthemanagementof

innovation.Managementscience,32(5),590-607.

VanderPanne,G.,VanBeers,C.,&Kleinknecht,A.(2003).Successandfailureof

innovation:aliteraturereview.InternationalJournalofInnovation

Management,7(03),309-338.

VanHorne,C.,Frayret,J.M.,&Poulin,D.(2006).Creatingvaluewithinnovation:

Fromcentreofexpertisetotheforestproductsindustry.ForestPolicyand

Economics,8(7),751-761.

77

Venkatesh,V.(2000).Determinantsofperceivedeaseofuse:Integratingcontrol,

intrinsicmotivation,andemotionintothetechnologyacceptancemodel.

Informationsystemsresearch,11(4),342-365.

Venkatesh,V.,Morris,M.G.,Davis,G.B.,&Davis,F.D.(2003).Useracceptanceof

informationtechnology:Towardaunifiedview.MISquarterly,425-478.

Voss,B.D.(2013).Massiveopenonlinecourses(MOOCs):Aprimerforuniversity

andcollegeboardmembers.AGBAssociationofGoverningBoardsof

UniversitiesandColleges.

Watkins,P.(1996).DecentralisingEducationtothePointofProduction:Sloanism,

themarketandSchoolsoftheFuture.Discourse:Studiesinthecultural

politicsofeducation,17(1),85-99.

Westerman,G.,McFarlan,F.W.,&Iansiti,M.(2006).Organizationdesignand

effectivenessovertheinnovationlifecycle.OrganizationScience,17(2),230-

238.

Wheelwright,S.C.,&Clark,K.B.(1992).Revolutionizingproductdevelopment:

quantumleapsinspeed,efficiency,andquality.SimonandSchuster.

Woodhouse,K.(2015).Closurestotriple.Retrievedfrom

https://www.insidehighered.com/news/2015/09/28/moodys-predicts-

college-closures-triple-2017

Yoon,S.W.(2003).Insearchofmeaningfulonlinelearningexperiences.New

DirectionsforAdultandContinuingEducation,2003(100),19-30.

Zusman,A.(2005).Challengesfacinghighereducationinthetwenty-first

78

century.Americanhighereducationinthetwenty-firstcentury:Social,

political,andeconomicchallenges,2,115-160.

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AppendixA

CentralizationAssessmentCombinationInstrument(Adaptedquestionswithoriginalversionsofthesequestionsinbracketsandboldtext)Instrument1:Hage&Aiken(1971).Centralization(measuredin2parts).(Part1)Participationindecision-making1.Howfrequentlydoyouusuallyparticipateinthedecisionontheadoptionofnewprograms?[Originalversion:same]2.Howfrequentlydoyouusuallyparticipateindecisionsontheadoptionofnewpolicies?[Originalversion:same]3.Howfrequentlydoyouusuallyparticipateinthedecisiontohirenewstaff?[Originalversion:same]4.Howfrequentlydoyouusuallyparticipateinthedecisionsonthepromotionsofanyoftheprofessionalstaff?[Originalversion:same](Responseset:1,alwaysthrough5,never)(Part2)Hierarchyofauthority1.AnytechnologydecisionImakehastohaveapprovalfromthecentralITunit.[Originalversion:AnydecisionImakehastohavemyboss’approval.]2.TherecanbelittleactiontakenhereuntilacentralITsupervisorapprovesadecision.[Originalversion:Therecanbelittleactiontakenhereuntilasupervisorapprovesadecision.]3.Apersonwhowantstomaketheirowntechnologydecisionswouldbequicklydiscouraged.[Originalversion:Apersonwhowantstomakehisowndecisionswouldbequicklydiscouraged.]4.Evensmallmattershavetobereferredtosomeonehigherupforafinalanswer.[Originalversion:Evensmalltechnologymattershavetobereferredtosomeonehigherupforafinalanswer.]5.IhavetoaskthecentralITunitbeforeIdoalmostanything.[Originalversion:IhavetoaskmybossbeforeIdoalmostanything.](Responseset:4,definitelytrue;3,moretruethanfalse;2,morefalsethantrue;1,definitelyfalse.)Instrument2:Kaluzny,etal.,(1974).Participationindecision-making.Theindexofparticipationindecisionmakingwasbasedontheextenttowhichindividualsindicatedparticipationindecisionsconcerningthefollowingitems:(1)allocationofoverallorganizationtechnologyfunds,[Originalversion:(a)allocationoftotalorganizationalincome]

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(2)adoptionandimplementationofneworganization-widetechnologyprogramsandservices,[Originalversion:(b)adoptionandimplementationofneworganization-wideprogramsandservices](3)developmentofformalaffiliationwithothertechnologyorganizations,[Originalversion:(c)developmentofformalaffiliationwithotherorganizations](4)appointmentandpromotionofadministrativetechnologypersonnel,[Originalversion:(d)appointmentandpromotionofadministrativepersonnel](5)appointmentoftechnologystaffmembers,and[Originalversion:(e)appointmentofmedicalstaffmembers,and](6)long-rangeplanningforneworganization-widetechnologyprogramsandservices.[Originalversion:(f)long-rangeplanningfornewhospital-wideprogramsandservices](Responseset:(1)considerableparticipation,(2)someparticipation,and(3)noparticipation.)Instrument3:Ferrell&Skinner(1988).Hierarchyofauthority.1.AnymajortechnologydecisionthatImakehastohaveapprovalfromthecentralITunit.[Originalversion:AnymajordecisionthatImakehastohavethiscompany’sapproval.]2.InmydealingswiththecentralITunit,evenquitesmallmattershavetobereferredtosomeonehigherupforafinalanswer[Originalversion:Inmydealingswiththiscompany,evenquitesmallmattershavetobereferredtosomeonehigherupforafinalanswer.]3.MydealingswiththecentralITunitaresubjecttoalotofrulesandproceduresstatinghowvariousaspectsofmyjobaretobedone.[Originalversion:Mydealingswiththiscompanyaresubjecttoalotofrulesandproceduresstatinghowvariousaspectsofmyjobaretobedone.]4.IhavetoaskcentralITunitrepresentativesbeforeIdoalmostanythinginmylocalITunit.[Originalversion:IhavetoaskmycompanyrepsbeforeIdoalmostanythinginmybusiness.]5.IcantakeverylittleactiononmyownuntilthecentralITunitoritsrepresentativesapproveit[Originalversion:Icantakeverylittleactiononmyownuntilthiscompanyoritsrepsapproveit.](Responseset:4,definitelytrue;3,moretruethanfalse;2,morefalsethantrue;1,definitelyfalse.)

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AppendixB

InnovationValueChainSurvey

(Hansen&Birkinshaw,2007)

Activity Phase

Ourculturemakesithardforpeopletoputforwardnovelideas Inhouseidea

generation

Highscoresindicatethatyourcompanymaybeanidea-poorcompany

PeopleinourunitcomeupwithveryfewgoodideasontheirownFewofourinnovationprojectsinvolveteammembersfromdifferentunitsorsubsidiaries Cross-pollination

amongbusinessesOurpeopletypicallydon'tcollaborateonprojectsacrossunits,businesses,orsubsidiariesFewgoodideasfornewproductsandbusinessescomefromoutsidethecompany

Externalsourcingofideas

Ourpeopleoftenexhibita"notinventedhere"attitude--ideasfromtheoutsidearen'tconsideredasvaluableasthoseinventedwithinWehavetoughrulesforinvestmentinnewprojects--it'softentoohardtogetideasfunded Selection Highscores

indicatethatyourcompanymaybeanconversion-poorcompany

Wehavearisk-averseattitudetowardinvestinginnovelideasNew-product-developmentprojectsoftendon'tfinishontime DevelopmentManagershaveahardtimegettingtractiondevelopingnewbusinessesWe'reslowtorolloutnewproductsandbusinesses

Diffusion

Highscoresindicatethatyourcompanymaybeandiffusion-poorcompany

Competitorsquicklycopyourproductintroductionsandoftenmakepre-emptivelaunchesinothercountriesWedon'tpenetrateallpossiblechannels,customergroups,andregionswithnewproductsandservices(ResponseSet:1,DoNotAgree;2,PartiallyAgree;3,Agree)

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AdaptedHansen&Birkinshawquestionsusedforthepresentstudy:(a)Ourinstitutionalculturemakesithardforpeopletoputforwardnovelideas.(b)Peopleinmyunit/division/collegecomeupwithveryfewgoodideasontheirown.(c)Ourinnovationprojectsrarelyinvolveteammembersfromunitsoutsideofmydivision/college.(d)Ourpeopletypicallydon'tcollaborateonprojectsacrossunits,divisions,andcolleges.(e)Goodideasfornewservicesandeducationalofferingsrarelycomefromoutsidetheinstitution.(f)Ourpeopleoftenexhibita"notinventedhere"attitude--ideasfromtheoutsidearen'tconsideredasvaluableasthoseinventedwithin.(g)Wehavetoughrulesforinvestmentinnewprojects--it'softentoohardtogetideasfunded.(h)Wehavearisk-averseattitudetowardinvestinginnovelideas.(i)Newinnovationprojectsoftendon'tfinishontime.(j)Academicleadershaveahardtimegettingtractiondevelopingneweducationalofferings.(k)Ourinstitutionisslowtorolloutnewservicesandeducationalofferings.(l)Ourservicesandeducationalofferingsarequicklycopiedatotherinstitutions.(m)Wedon'tpenetrateallpossiblechannels,customergroups,andregionswithnewservicesandeducationalofferings.(ResponseSet:1,DoNotAgree;2,PartiallyAgree;3,Agree)