标准普尔500公司人工智能扩散监测：实证结果和方法学进展

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2022

AIDiffusionMonitoringamongS&P500Companies:EmpiricalResultsandMethodologicalAdvancements

TomaszMucha

TimoSeppala

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AIDiffusionMonitoringamongS&P500Companies

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AIDiffusionMonitoringamongS&P500

Companies:EmpiricalResultsandMethodologicalAdvancements

CompletedResearchPaper

TomaszMucha

AaltoUniversity

Otakaari24,02150Espoo,Finland

tomasz.mucha@aalto.fi

TimoSeppälä

AaltoUniversity

Otakaari24,02150Espoo,Finland

timo.seppala@aalto.fi

Abstract

Withtheincreasingpaceofdigitaltechnologyinnovationandcommercialization,monitoringcommercialdiffusionoftechnologiesbecomesmoreimportantfororganizations.TechnologymonitoringisfundamentaltoR&Dplanning,technologymanagement,andstrategicdecision-making.Despiteitsimportance,monitoringthediffusionoftechnologiesatthecommerciallifecyclestagereliesoncrudemethods,suchas“snapshot-in-time”surveysandkeywordcounts.Theseapproachesareinstarkcontrasttonovelandrapidlyadvancingmethodsformonitoringtechnologiesattheprecommerciallifecyclestages,suchasfundamentalscientificresearchandappliedR&D.Weaddressthisimbalancebyproposingaspecializedmethodformonitoringthecommercialdiffusionoftechnology.Themethodrecognizesphasesintechnologyadoptionbyorganizationsandcapturesthetemporalprogressionofthediffusionprocess.Oneofthecentralelementsoftheproposedmethodistheclassificationoftext,whichreliesonqualitativecontentcoding.Ourapproachtocodingleveragestheinsightsfrominnovationdiffusionresearchandissensitizedspecificallytodetectphasesintechnologyadoptionbyorganizations.Theapproachisillustratedwiththecaseofartificialintelligence(AI)diffusionamongS&P500companiesduringthe2004–2019period.Ourfirstcontributionisanewmethodformonitoringthecommercialdiffusionoftechnologies.Itprovidestransparent,replicable,updatable,andgranularresults,

whichcancomplementsurvey-basedtechnologymonitoring.ThesecondcontributionisempiricalevaluationofAIdiffusioninthecontextofleadingfirmsinNorthAmerica.

Keywords:Technologydiffusion,technologyadoption,technologystrategy,artificialintelligence(AI),machinelearning(ML)

AIDiffusionMonitoringamongS&P500Companies

ProceedingsoftheTwenty-seventhDIGITWorkshop,Copenhagen,DenmarkDecember2022

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AIDiffusionMonitoringamongS&P500

Companies:EmpiricalResultsand

MethodologicalAdvancements

CompletedResearchPaper

Introduction

Technologyadoptionisafundamentaldriverofproductivityandcompetitivenessforfirmsandnations(Brynjolfssonetal.2018;Hall2004).Hence,technologymonitoringunderliesthegenerationofstrategicforesightregardingchangesimpactingbusinesses,economies,andsocieties(Roperetal.2011,secs.1and4.2).Therefore,monitoringtechnologiesthroughouttheirlifecyclesishighlyrelevanttobothresearchandpractice.Themethodwiththelongesttrackrecordandcommonlyusedtodayissurvey-basedresearch(Roperetal.2011,pp.100–103).Survey-basedresearchisparticularlyprevalentinstudiesconcernedwithtechnologiesenteringcommercializationandlaterstagesinthetechnologylifecycle.Scholarsandpractitionerstaskedwithtechnologymonitoringrelyonsurveys(forexample,see:Balakrishnanetal.2020;MagoulasandSwoyer2020;MontagnierandEk2021;Oliveiraetal.2019;Zolasetal.2020).Anothergroupoftechnologymonitoringmethods,sometimesreferredtoas“techmining”(PorterandCunningham2004),emergedfromthecontentanalysis(Roperetal.2011,p.106)andiscurrentlyunderactivedevelopment(CunninghamandKwakkel2016,p.xx),particularlyformonitoringprecommercial-stagetechnologies.ThesenovelapproachesprovideanincreasingrangeofinsightsandinformR&Dandtechnologyplanningrelatedtoprecommercial-stagetechnologies.

Despitethecontributionofthesemethods,limitationsprevailinmonitoringthecommercialdiffusionoftechnologies.First,sincesignificanthurdlesseparatetechnologicalinventionsandappliedR&Dfromcommercialization(Roperetal.2011,p.8),methodsfocusedonearlystagesofthetechnologylifecycle,suchaspatentanalysis,arenotsufficienttounderstandthesubsequentcommercialdiffusionoftechnology.Second,methodsfocusedonlaterstagesinthetechnologylifecyclealsofacelimitations(Rogers1983,p.117).Thus,thedevelopmentofmonitoringmethodssuitableforcommercial-stagetechnologies,whicharelongitudinalandrecognizethecomplexityofthetechnologyadoptionprocessbyorganizations,hasbeenmissing.Therefore,weproposeamethodspecificallydesignedtorecognizephasesintechnologyadoptionbyorganizationsandcapturethediffusionprocessovertime.Theproposedmethodleveragesthequalitativecontentanalysisapproach.Ourapproachtocodingissensitizedtostudyingtheorganizationaladoptionoftechnologies.Itbuildsoninsightsfrominnovationdiffusionresearchconcernedwiththeprocessoftechnologyadoptionwithinorganizations(CooperandZmud1990;Greenhalghetal.2008,sec.5.3;MeyerandGoes1988;Rogers2010).Themethodisillustratedwiththecaseofartificialintelligence(AI)diffusionamongS&P500companiesduringtheJanuary2004–May2019period.AIisa“frontierofcomputationaladvancementsthatreferenceshumanintelligenceinaddressingevermorecomplexdecision-makingproblems”(Berenteetal.2021,p.1435).TopexecutivesinternationallyrecognizeAIashavingthepotentialtosignificantlyimpactthestrategicpositionoftheirorganizationsandthecompetitivedynamicsofindustries(Ransbothametal.2020).Therefore,businessleaders,scholars,andpolicy-makersarekeentomonitorthecommercialdiffusionofAI.

Thisstudybringsseveralcontributions.First,ourmethodaddressestheissueoftechnologymonitoringfortechnologiesinthelatterpartoftheirlifecycle,namely,thoseenteringintocommercializationorlaterstages.Second,theproposedmethodisversatileintermsofitsapplicabilitytoawiderangeoftechnologies.Thisversatilitystemsfromitsrelianceonqualitativecontentanalysis,whichisnotlimitedtoanyspecifictypeoftextordocument,anditssensitizationtobroadlydefinedphasesoftechnologyadoption.Next,practitionerscanreadilyadopttheproposedmethodintouseandcomplementtheirexistingtechnologymonitoringapproaches.Theirprojectswillbenefitfromtransparent,replicable,updatable,andgranularresultsgeneratedbyourmethod.Thus,theproposedmethodpresentsavaluableadditiontoasurvey-basedapproachtomonitoringthecommercialdiffusionoftechnology.Finally,giventhattheproposedmethodfollowsastructuredprocedureforcontentcoding,itmayserveinthefutureasafoundationforanautomatedtechnologymonitoringalgorithm.

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Theoreticalbackground

Ourapproachdrawsontheexistingresearchontechnologymonitoringandinnovationdiffusion.Therefore,inthissection,weprovideabriefoverviewoftherelevanttheoryandmethodsfromthesetwopartiallyoverlappingstreamsofliterature.Weseparatelyidentifythedevelopmentofmethodsformonitoringtheprecommercialandcommercialdiffusionoftechnologiesinbothstreamsofliterature.Technologymonitoringistheprocessofobservingandkeepingupwithdevelopmentsinaspecifictechnology(Roperetal.2011,p.72).Itiswidelyusedandprovidesessentialinputsforbothbusinessandpolicydecision-makersand,thus,contributestoR&Dmanagement,technologymanagement,andcorporateandnationalstrategies(Burgelmanetal.2004,pp.8–9;ChenandSmall1994;PorterandDetampel1995;TeichertandMittermayer2002).Inthispaper,welimitthescopeoftechnologymonitoringtoincludepastdevelopments.

Monitoringprecommercialdiffusionoftechnology

Companiescannotuseprecommercial-stagetechnologiesintheirdailyoperationsbutmightengagewiththesetechnologiesthrough,forexample,R&Dwork.Nevertheless,understandingthedevelopmentpathsforprecommercialtechnologiesmightbestrategicallyimportant(TeichertandMittermayer2002).Sincetechnologicalprogressattheprecommercialstagemanifestsitself,atleastpartially,inscientificpublicationsandpatents(PorterandCunningham2004,p.7),technologymonitoringprimarilyleveragesthesedocuments(Martino2003;Roperetal.2011,pp.81–82).Itisoftenreferredtoas“techmining”(PorterandCunningham2004,sec.2.3;Roperetal.2011,sec.5.2).PorterandCunningham(2004,p.19)definetechminingas“theapplicationoftextminingtoolstoscienceandtechnologyinformation,informedbyunderstandingoftechnologicalinnovationprocesses.”Particularlyintheareaofpatentanalysis,therehavebeenmanyrecentadvances,suchasanalysisofinnovationtopics(Choietal.2018);identificationofinterindustrytechnologies(Fredströmetal.2021);andscreeningideasintheearlystagesoftechnologydevelopment(Hongetal.2021).

Despitetheseadvances,monitoringtheprecommercialdiffusionoftechnologyisinsufficienttounderstandthesubsequentcommercialdiffusion.First,notallinventions“findaviablecommercialapplication”(Grant2016,p.243).Next,thereisasignificanttimelagbetweenmakinganinventionanditscommercialization(Roperetal.2011,sec.1.2),whichresultsfromaninnovationneedingtoovercome,inmanycases,significantdifficultiesbeforetheadopterstakeitintouse(Rogers2010,p.1).Consequently,themethodsformonitoringcommercialdiffusionoftechnologypresentadistinctareaofresearchandpractice.

Monitoringcommercialdiffusionoftechnology

Monitoringthecommercialdiffusionoftechnologydevelopsanunderstandingoftheextenttowhichthetargetpopulationofadoptershastakenafocaltechnologyintouse.Itpresentsauniquesetofchallenges.Unlikeinthecaseofprecommercialdiffusion,therearenocommonlyusedandstandardizedpublicationstomeasureprogression.Instead,technologiesdiffusinginatargetmarketspreadthroughvariouschannels,suchasindustryconferences,press,word-of-mouth,businessintelligence,andmanymore(Rogers2010,pp.18–20).Consequently,manytypesofactorsengageinmonitoringthecommercialdiffusionofvarioustechnologies.Theyincludenationalstatisticaloffices,not-for-profitorganizations,andotherserviceproviders,suchasmarketresearchfirmsandconsultingcompanies.

Therearetwomaincategoriesofmethodsusedinmonitoringthecommercialdiffusionoftechnology:(1)surveyresearchand(2)analysisofvarioustypesofcontent.Weprovideabriefbackgroundonthetwocategoriesanddiscusstheirlimitations.Theuseofsurveystocollectdataforresearchandanalysisofcommercialdiffusionoftechnologyhasbeenandcontinuestobeveryprominent.AseminalstudyofhybridcorndiffusioninIowa(RyanandGross1943),whichreliedoninterview-basedsurveys,formedthefoundationofthediffusionresearchparadigminthe1940s(ValenteandRogers1995).Giventhesuccessfulexpansionofdiffusionresearchinthefollowingdecadesbeyondthedisciplineofruralsociology(Rogers2010),thepreviouslyestablishedmethodologicalapproachcontinuedtothriveandevolve.Recentstudiesinvestigatingthediffusionofdigitaltechnologiescontinuetorelyonsurveysasasourceofdata(Oliveiraetal.2014,2019).Nationalstatisticalofficesalsousethisapproachtogaugethecommercialdiffusionoftechnology.ArecentpublicationofU.S.enterprisetechnologyadoptionbytheU.S.CensusBureauisagoodillustration(Zolasetal.2020).Additionally,majorconsultingcompaniesandotherorganizations

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publishinginsightsontechnologydiffusioncontinuetorelyonsurveys,(forexample,see:Balakrishnanetal.2020;MagoulasandSwoyer2020;Ransbothametal.2020).Despitethislonglineage,surveyresearchfacesmanylimitationsforprovidinginsightsintotechnologymonitoring.Rogers(2010,pp.126–130)highlightssomeofthecriticismofsurvey-basedmethods.Oneofthelimitationsofsurveys,whichhepointsout,isprovidinga“snapshot-in-time”perspectiveratherthana“movingpictures”perspective.Thislowtemporalgranularityisadrawback,especiallyforrapidlyadvancinganddiffusingtechnologies.Evenremedyingthisbyrunningsurveysatmultiplepointsintimeintroducesnewchallenges–distortionoftheperceptionofinnovationbytherespondents(Rogers1983,p.117)andaggravationofnonresponsebias(Roperetal.2011,p.103).Inaddition,surveyresearchintechnologymonitoringcansufferfromlongtimelags,problemswithdefinitionsoftechnicalterminology,andinthecaseofcommerciallyrunstudies,limitedtransparencyregardingspecificmethodsandsampling(MontagnierandEk2021).Consequently,survey-basedmethodsalonearenotsufficientformonitoringthecommercialdiffusionoftechnology.

Thesecondcategoryofmethodsusedinmonitoringcommercialdiffusionoftechnologyoriginatesfromcontentanalysis.Astudyofthediffusionofmultidivisionaladministrativestructureamonglargeindustrialfirms(Teece1980)reliedonqualitativecontentanalysis.Teeceanalyzed,amongothers,annualreports,10-KformsfiledwiththeSecuritiesandExchangeCommission,prospectuses,businessperiodicalarticles,recruitingliterature,andpubliclyavailabletextsofspeechesbycorporateofficials.Theresultingclassificationoforganizationalformsdidnotallowformultiplephasesininnovationadoptionbutratherwasbinaryinnature(ArmourandTeece1978).Similarly,amorerecentanalysis(DanielZhangetal.2021,p.106)disregardedphasesintechnologyadoptionbyemployingcountsoftechnology-relatedkeywordsinexecutivepresentationsasanindicatoroftechnologydiffusion.Twootherstudies(MikovaandSokolova2019;Segevetal.2015)analyzingthecommercialdiffusionoftechnologyandemployingcontentanalysisalsofacedlimitations,whichresultedfromthelackofcontroloverthesampleofcompaniesincludedinthedataanalysis.Overall,weconcludethatthecurrentstateofmethodsformonitoringthecommercialdiffusionoftechnologyhasbeeninsufficientandstagnant.Itispossibletoaddressthisgapbydrawingoninsightsfrominnovationdiffusionresearchontheprocessoftechnologyadoptioninfirms(Greenhalghetal.2008,sec.5.3;Rogers2010,pp.126–130).

Proposedmethod

Ourproposedapproachtomonitoring

commercialdiffusionoftechnology

consistsoffoursteps(Figure1):(1)

scopingandsituatingtechnology

diffusionmonitoringproject,(2)

samplingandcontentretrieval,(3)

analyzingandclassifyingcontent,and

(4)presenting,exploring,and

exploitingtheresults.Wedescribe

thesestepsingreaterdetailinthe

followingsubsections.

Step1:Scopingandsituating

technologydiffusion

monitoringproject

Figure1.Overviewofstepsintheproposedmethod.

Thefirsttaskofresearchersemploying

theproposedmethodistodefinethescopeofthemonitoringprojectbyidentifyingcategories,names,orkeywordsrepresentingthetargettechnology.Thesekeywordsguidethecontentsearchandretrieval(instep2).Theterminologyfordescribingandreferringto(early)commercial-stagetechnologiesiseitherestablishedoremerging(SantosandEisenhardt2009).Thetrade-offbetweenspecificityandbreadthofthesekeywordsdrivesthescopeofthemonitoringproject.Forexample,somekeywordsmightrepresentabroadertechnologicaltrajectoryorfrontier,suchas“solarenergy.”Othersmightencompassonlyanarrowersetoftechnologies,suchas“towerconcentratingsolarplants.”Furthermore,thelevelofprojectscopingdifficultymightdependonthefamiliarityoftheresearchteamemployingtheproposedmethod

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withthetargettechnology.Ifresearchersareunfamiliarwiththefocaltechnology,theyshouldfirstconductabroaderexploratoryanalysis(Roperetal.2011,pp.76–77).

Situatingthetechnologydiffusionmonitoringprojectinvolvestheidentificationofearlierfindingsontechnologydiffusion,whichhavebeengeneratedbyotherresearchersorfromcommercialsources.Suchreportsandresultsoncommercialdiffusionoftechnologymightbeavailable,forexample,fromtradeassociations,marketresearchfirms,consultingfirms,nationalstatisticaloffices,orpress.Thepurposeofsituatingtechnologydiffusionmonitoringistwofold.First,ituncoverstheleveloftechnologydiffusionreportedbyothers.Theseinsightsenablethecomparisonoftheresultsfromothersourcesagainsttheoutputsfromourmethod(instep4).Second,situatingtheprojectcontextualizestheunderstandingofthediffusionprocessforthetargettechnology.Thisunderstandingincludespreviouslyuseddefinitionsandscopeoftechnology,samplesofcompanies,methods(particularlytheirshortcomings),andtimeframes.

Step2:Samplingandcontentretrieval

Oncetheprojectscopehasbeendefinedandsituatedwithinthecontextofthetargettechnology,thenextstepistonarrowitdownandfocus.Thisinvolvestheselectionoftargetcompanies,aswellasasuitabletimeframeandtextcontent.Thisstepconcludeswiththesearchandretrievalofunstructuredtextcontentfortheanalysisinthenextstep.

Theselectionofcompaniesincludedinthemonitoredsampleisvitalbecausecompanysizeandindustryarestronglyassociatedwiththerateandleveloftechnologydiffusion(Fichman2000;Greenhalghetal.2008,p.139;OliveiraandMartins2011).Furthermore,thetypeofcompaniestobemonitoredwillalsodeterminetherangeofunstructuredtextsourcespotentiallyavailablefortheanalysis.Sometypesofcontent,suchaswebsitesorpressarticles,mightbeavailableacrossawiderangeofcompanies,whilelargercompaniesmightalsogeneratecontentintheformof,forexample,pressreleases,annualreports,ortranscriptsofexecutivepresentations.Anotheraspectofcontentselectionisitsalignmentbetweenthescopeoftechnologymonitoringandtheroleofthetechnologyfortargetcompanies.Forexample,strategicallyimportanttechnologiesforcompaniesinthelogisticsindustryarelikelytobediscussedbythesecompaniesinpressreleasesorannualreports,butlesssointhesametypesofcontentcomingfromthehealthcareindustry,wherethesametechnologiesmightstillbeapplicable,butarenotasimportant.

Determinationoftherelevanttimeframeisalsoanintegralpartofthisstep.Attheinitiationofthemonitoringproject,itisnecessarytodecidehowfarbackintimetogo.Identifyinglandmarkeventsindicatingtechnologycommercializationservesthatpurposewell.Forexample,aneventindicatingthecommercializationofwindturbinesisthefirstinstallationofautility-scalewindturbinefarmbyanenergycompany.Alternatively,patentanalysiscanprovideinsightsintowhenafocaltechnologybeginstoenterthecommercializationstage(PorterandCunningham2004,pp.284–285).If,however,themonitoringprojectisarerunorupdateofpreviousresearch,onlyrecentinformationneedstobeanalyzed.

Thisstepconcludeswithcontentsearchandretrieval.Thesetasksleveragetechnology-relatedkeywordsidentifiedinthepreviousstep.Thecontentsearchinvolvestheidentificationofdocumentswithunstructuredtextcontentwheretherearereferencestothetargettechnologyandcompanies.Theexecutionofthecontentsearchcaneitherrelyonexistingcommercialandopendatabasesorcustom-builtapproachesforcontentidentificationandretrieval.Potentiallysuitablecontenttypesincludeannualreportsoflistedcompanies,pressarticles,socialmediapostings,technicalreports,“gray”literature,companywebsites,andtranscriptsofexecutivepresentations.Amorein-depthdiscussionofthedatasources,search,andcontentretrievalgoesbeyondthescopeofthispaper.Otherauthorshavecoveredthesetopicsinthepast(forexample,seeMartino2003;MikovaandSokolova2019;PorterandCunningham2004,secs.6–8;Roperetal.2011,sec.5.2).

Step3:Analyzingandclassifyingcontent

Thisstepreliesonqualitativecontentcoding(Saldaña2015).Inthequalitativecontentanalysistradition,acodeis“awordorshortphrasethatsymbolicallyassignsasummative,salient,essence-capturing,and/orevocativeattribute”tothesectionoftextbeinganalyzed(Saldaña2015,p.3).Inourmethod,researchersgeneratethecodes.Thisapproachtoqualitativecontentcodingisinlinewiththeprovisionalcodingmethod,whichutilizesaresearcher-generatedandpredeterminedlistofcodesusedintheanalysis(Saldaña2015,pp.120–123).Thus,thecreationofthecodingscheme(seeAppendix1)mustprecedethecontent

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analysis.Theintentionbehindthisschemeistoalignitwiththeobjectiveofthecommercialtechnologydiffusionmonitoringproject.Hence,thecodesrepresentphasesinthecommercialadoptionoftechnologybythetargetcompanies.Pastresearchcanprovideastartingpointforcodingschemedevelopment.Forexample,Rogers(2010)proposedagenericmodeldescribingtheprocessoftechnologyadoptionbyorganizations.Appendix2presentsanon-exhaustivelistofmodelsdefiningphasesininnovationortechnologyadoptionbyorganizations.Researchersemployingtheproposedmethodshouldselecttheinitialcodingschemebasedonitssuitabilityinthecontextofthetechnologymonitoringproject.

Theanalysiscomprisesfourelements:(1)selectionofthecodingunit;(2)testingoftheinitialcodingschemeonasubsampleofthecontent;(3)potentialrearrangementoftheschemeandanotherroundoftesting;and(4)codingoftheentiresampleofavailablecontent.Thecodingorrecordingunitisthe“unitoftexttobeclassified”(Weber1990,p.22).Sincethesourcedocumentsusuallylinktoonlyasinglecompany,itissufficienttoassignasinglecodetothewholedocument.However,ifasingledocumentrelatestomorethanonecompany,itisnecessarytonarrowdownthecodingunittoensureanunambiguouslinkbetweencodesandindividualcompanies.Furthermore,smallercodingunits,suchasparagraphs,alsofacilitatepostprocessingandposthocanalysis.Forexample,technologyusecaseanalysisisconductedfasterwhenleveragingparagraph-levelratherthandocument-levelcoding.Aftertheselectionofthecodingunit,itispossibletotestthecodingscheme.Sincethecodesarepredeterminedbytheresearchersbeforeanalyzingthecontent,“[t]estingnotonlyrevealsambiguitiesintherulesbutalsooftenleadstoinsightssuggestingrevisionsoftheclassificationscheme”(Weber1990,p.24).Wesuggestcodingrandomlyselecteddocumentsrepresentingapproximately5%–10%oftheoverallsampletotestthecodingscheme.Testingshouldallowresearcherstoevaluatewhetherthecodingschemegranularitylevelissuitable.Anotherrecommendationistoinitializetheschemewithahighnumberoftechnologyadoptionphases.Suchgranularitycapturesfinerdetailfromthecontent,ifavailable,andthusismoreinformative.Researchersfollowingthisproceduremustalsoconsiderreliability.Therearemanyapproachestoensurethereliabilityofqualitativecontentcoding,someofwhichinvolvequantitativemeasuresofreliability,whileothersrestoretoconsensusbetweenratersandgroupdiscussions(Saldaña2015,pp.27–28).Irrespectiveoftheselectedmethodforestablishingreliability,theresearchersinvolvedintheprojectshouldtransparentlyreportitintheirstudy.

Step4:Presenting,exploring,andexploitingtheresults

Theresultsfromthepreviousstepneedtobefurtherprocessedtoderiveinsightsfromtechnologydiffusion.Aftercodingtheentiresample,theresultsneedtobeaggregatedonacompanyandcodelevelbecauseitislikelythatasinglecompanywillbeassociatedwithmultipledocumentsandcodes.Theprocedureforaggregationincludestwosteps:(1)sortingthedocumentsbythecompanyandbydatefromoldesttothemostrecent;and(2)foreachcompany-codecombination,recordingtheearliestdateinatable.Theresultingtableshouldincludecompanynames(inrows)andphasesoftechnologyadoptionincludedinthecodingscheme(incolumns).Thevaluesinthetableshouldshowdateswhenindividualcompaniesreachedspecificphasesoftechnologyadoption.Someofthecellsintheresultingtablearelikelytobeblankduetonoavailableinformation.Thisprocedureassumesthatifasinglecompanyisassociatedwithagivenphaseoftechnologyadoptiononaparticulardate,thenitcannotbe“degraded”toanearlierphase,evenifthereisacoderepresentingalowerphaseoftechnologyadoptionassignedtoitonalaterdate.Forexample,researchersmaycodecompanyAasreach