📄 DAO Governance: Voting Power, Participation, and Controversy
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Priorities Extracted from This Source
#1
Reduce centralization and unequal voting power in DAO governance
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Increase member participation and engagement in governance
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Assess and manage controversy in DAO decision-making
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Develop and select more effective DAO governance models
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Enable transparent, repeatable, cross-model governance analysis
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Mitigate governance security risks such as flawed design and Sybil attacks
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Compare on-chain and off-chain voting mechanisms
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Reduce concentration of voting power in DAO governance
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Improve member participation in governance decisions
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Assess and manage proposal controversy and voting efficiency
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Increase data transparency and comparability for governance analysis
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Mitigate security risks from token-based governance concentration
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Protect minority rights in DAO governance
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Compare on-chain and off-chain voting systems
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Design governance mechanisms that limit transferable or accumulable voting power
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Increase voter participation in DAO governance
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Reduce centralization in voting power and decision-making
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Mitigate security risks caused by low participation and low quorum thresholds
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Protect minority representation and minority shareholder interests
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Improve the effectiveness of decentralization and democratic decision-making
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Reduce inefficiency, cost, and delay in voting on uncontroversial proposals
#22
Address voter fatigue from frequent low-stakes governance decisions
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Improve DAO governance design through better metrics, analysis, and future research
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26 March 2026
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Latest updates: hps://dl.acm.org/doi/10.1145/3777416 .
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Published: 18 November 2025
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. Accepted: 20 October 2025
RESEARCH-ARTICLE Revised: 24 September 2025
DAO Governance: Voting Power, Participation, and Controversy - A Received: 26 January 2025
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Review and an Empirical Analysis .
Citation in BibTeX format
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MARKUS JUNGNICKEL, Imperial College London, London, U.K.
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FERDA ÖZDEMIR SÖNMEZ, University of West London, London, U.K.
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CATHY MULLIGAN, Imperial College London, London, U.K.
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WILLIAM J. KNOTTENBELT, Imperial College London, London, U.K.
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Open Access Support provided by:
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Imperial College London
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University of West London
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Distributed Ledger Technologies: Research and Practice
hps://doi.org/10.1145/3777416
EISSN: 2769-6480
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DAO Governance: Voting Power, Participation, and Controversy - A
Review and an Empirical Analysis
MARKUSJUNGNICKEL,ImperialCollegeofLondon,DepartmentofComputing,UK
FERDAÖZDEMIRSÖNMEZ,ImperialCollegeofLondon,DepartmentofComputing,UKandUniversity
ofWestLondon,SchoolofComputingandEngineering,UK
CATHYMULLIGAN,ImperialCollegeofLondon,DepartmentofComputing,UK
WILLIAMJ.KNOTTENBELT,ImperialCollegeofLondon,DepartmentofComputing,UK
DAOshaveemergedasanovelorganizationalstructure,attractinggrowinginterestduetotheirdecentralized,transparent
governance,whichreplacestraditionalhierarchieswithstakeholder-managedrulescodifiedassmartcontracts.Althoughvar-
iousgovernancemodelsexist,comparativeresearchacrossdimensionsremainslimited,leavingtheliteraturefragmentedand
offeringlittlepracticalguidanceforselectingsuitablemodels.Thispapercriticallyanalysesexistinggovernancemechanisms
andtheirimplementationtosupportthedevelopmentofmoreeffectiveDAOmodels.Toaddresscurrentgaps,wereviewprior
quantitativestudiesandconductexploratorydataanalysisoncentralization,participation,anddecisioncontroversy.The
findingsshowthatreputationandshare-basedmodelscanmitigatethecentralizationseenintoken-basedsystems,thoughall
modelssufferfromlowmemberengagement,suggestinganoverrelianceondirectdemocracy.Ouranalysiscanbereplicated
acrossplatformsandtimeframestorefineandvalidatetheseinsights.
CCSConcepts:•Appliedcomputing→Electronicfundstransfer;•Computingmethodologies→Distributed
computingmethodologies;•Computersystemsorganization→Peer-to-peerarchitectures.
AdditionalKeyWordsandPhrases:smart-contract,blockchain,infrastructureprojects,governance,voting,dao,decentralized
autonomousorganization
1 INTRODUCTION
TheDAOecosystemhasexperiencedstronggrowthoverthelastthreeyears[8],andthereisanincreasing
interestinusingDAOstomanagenotjustblockchainsolutionsbutalsofinancialservices,sustainabilitygoals,
andnearlyeveryaspectofsocietyhashadaDAOproposedforthem.Atthesametime,DAOsarestilldeveloping
appropriategovernancemodelsthatsuitevermorecomplexusecases[8],whichcanbeaccommodatedbythe
decentralizedandimmutablenatureofblockchains[23].
Developingarobustgovernancemodelhasalwaysbeencriticaltothesuccessandlongevityoforganizations
andhasbeenstudiedforaverylongtime;infact,itshistorypredatesthatofblockchaintechnologyandallother
Authors’addresses:MarkusJungnickel,markusjungnickel@gmail.com,ImperialCollegeofLondon,DepartmentofComputing,South
KensingtonCampus,London,England,UK,SW72AZ;FerdaÖzdemirSönmez,f.ozdemir-sonmez@imperial.ac.uk,ImperialCollegeof
London,DepartmentofComputing,SouthKensingtonCampus,London,England,UK,SW72AZandUniversityofWestLondon,School
ofComputingandEngineering,StMary’sRoad,Ealing,London,England,UK,W55RF;CathyMulligan,c.mulligan@imperial.ac.uk,
ImperialCollegeofLondon,DepartmentofComputing,SouthKensingtonCampus,London,England,UK,SW72AZ;WilliamJ.Knottenbelt,
w.knottenbelt@imperial.ac.uk,ImperialCollegeofLondon,DepartmentofComputing,SouthKensingtonCampus,London,England,UK,
SW72AZ.
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ACM2769-6480/2025/11-ART
https://doi.org/10.1145/3777416
Distrib.LedgerTechnol.
2 • Jungnickeletal.
pertinenttechnologicaladvancements.Aristotle[49]wasanearlyadvocateforgovernancemodels.Theformation
ofthe”RuleofLaw”[30]isalsoasignificantaccomplishmentinthehistoryofgoverningparadigms,asitsupports
theequalityofallcitizensbeforethelaw,preventsthearbitraryuseofpower,andensuresanon-arbitraryform
ofgovernance.Significantamountsofliteraturehavebeendedicatedtostudyingorganizations,organizational
theoryandsimilartopicsthatoutlinegovernancemechanismsforthemanagementofsociety,companiesand
otherstructureswherehumansneedtocollaborateandcoordinateinvariousforms.
Similarideasapplytotoday’sentirelytechnology-dependentfuturisticorganizations,DAOs.However,although
theoreticallysettingupanewDAOorganizationisstraightforward,theimplicationsofincorrectgovernance
systemswouldbehigh,causingirreversiblesituationsandcausedamagebeyondrepair.Forinstance,in“The
DAO”case,anoverlookedpieceofcodeintendedtopromotedecentralizationandencouragethecreationof
“childDAOs”ultimatelyledtotheorganization’scollapse”[58].Suchholesingovernancemechanismsarecritical
issuesforDAOstoaddresstobeusedeffectivelywithinsociety.
Thispaperexaminesexistinggovernancemodels,focusingoncentralization,participation,controversyand
theeffectsoftheseongovernancesystems.Theresearchismotivatedbytheneedtoincreaseunderstandingof
andimproveexistingDAOgovernancemodels,aswellasenablecomparisonofthemalongseveralvariables.
1.1 ObjectivesandAim
ThisstudyaimstocriticallyevaluateexistingDAOgovernancemodelstosupportthedevelopmentandselection
ofmoreeffectivemechanisms.Thespecificobjectivesare:
• Analyzehowkeygovernancemetrics—participation,controversy,andvotingpower—differacrossmodels.
• ReviewandclassifyDAOvotingmechanismsbyweight,type,andmethodtoofferastructuredoverview.
• Performexploratorydataanalysistocomparevotingpowerdistribution,memberparticipation,anddecision
controversyacrossgovernancemodels.
• Providetransparent,repeatableanalysismethodstoaccommodatetheevolvingDAOecosystem.
1.2 Contributions
Themostsignificantcontribution,inlinewiththecorrespondingobjectivessetoutinSection1.1,istheliterature
reviewwhichidentifiedtheproblemswithexistinggovernancemodelsandhighlightscriticalareasthatremain
understudiedbyexistingresearch.
Thestudyalsoincludesanexploratorydataanalysisasasecondarycontributiontopresenttheidentified
problems and the gaps visually. For this project, the exploratory analysis does not form the basis of further
statisticalhypothesistesting.Withoutmorerobustempiricaldata,exploratorydataanalysiswasusedtodetermine
theadvantagesanddisadvantagesofvariousdesignapproachesfortheDAOs.Theoutputsoftheexploratory
dataanalysiscanbeusedtosetupcomprehensivelyandtesthypothesesforfuturework.
Thereviewshowsthatexistingresearchissomewhatpiecemealandfailstocomparedifferentgovernance
modelsacrossmultipledimensions.Thedifferencebetweenon-chainandoff-chainvotinghasalsoremained
understudied.Thesegapsareproblematicbecausesuchcomparisonsarenecessarytoformulatehypothesesabout
whichgovernancefeaturesarecausingissues.Theexploratorydataanalysisconductedforthisresearchattempts
tofillsomeofthesegaps.Thisaimstomakeinitialobservations,revealconnectionsanddevelophypothesesabout
thedata;theresultsarethentypicallytestedinaconfirmatorydataanalysis[61].Threeofthemostcommon
governancesystemsdifferintheirperformanceacrosskeydimensions:
• UnequalVotingPower:Theresultsrevealhowreputationandshare-basedgovernancesystemsmanageto
avoidthehighdegreesofcentralizationofthevotingpowerintoken-basedgovernance.
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 3
• LowEngagement:Theanalysisshowslowvoterparticipationacrossgovernancemodelsandsupportsthe
hypothesisthatthisisnotduetothecostandcomplexityofon-chainvotingbutanexcessiveuseofdirect
democracy.
• Absence of Controversy: The results demonstrate that both on and off-chain decision-making in DAOs is
mostlyuncontroversial;itisnotthecasethatafewpowerfulmembersareusingtheirvotingweighttooutvote
apowerlessmajority.However,thisispartiallytheresultofextremelylowparticipationamongthemajority.
Therestofthepaperisorganisedasfollows.Section2summarisesthestateoftheart.Section3definesthe
scopeofthereview.Section4describesthedata’slimitations,followedbyadetailedmethodologydescription.
Section5isdedicatedtothereviewresultscontainingboththeliteraturesummarywithgapsandtheresultsof
theexploratorydataanalysis.Section6hasthediscussionpart,whichincludesadetaileddiscussionofselected
parametersandtheiridentifiedeffectsonthegovernancesystems.Finally,Section7concludes.
2 STATEOFTHEART
2.1 ConceptandDefinitionforDAOs
Adecentralizedautonomousorganization(DAO)employsalgorithmicgovernancethroughsmartcontractsona
blockchain,withthedegreeofautonomyvaryingamongdifferentDAOs[68][64].
ThedefinitionofDAOshasbeenfurtherrefinedbyButerin,whodistinguishesthemfromDistributedOrgani-
zations(DOs)[64].Whilethelatterisgovernedbythedecision-makingofhumanmembers,theformermakes
decisionsautonomously.Althoughthedistinctionisoftheoreticalinterest,thepreciseclassificationofaproject
asaDOorDAOhaslittlepracticalrelevance.Nonetheless,it’sworthnotingthatsomeDAOsconsideredinthis
paperaremeanttobegovernedbymajoritydecisions,whichwouldnotqualifyasfullyautonomousDAOssince
theydependonthemajoritywilloftheirmembers.
2.2 DAOGovernanceModels
2.2.1 DemocraticGovernance. Democraticgovernancereferstothedecision-makingprocesseswithinDAOs
thatuseavotingsysteminwhichmemberscanfreelyparticipate.Avotingsystemencapsulatesthreeconcepts:
VoterRegistration,VotingWeight,andVotingMethod.
VoterRegistration: DAOslimitparticipationingovernancevotesbyimplementingmembershipsystems(Voter
Registration).Theprimarypurposeofamembershipsystemistorecorddifferencesinvotingweight,ensureonly
individualsinterestedintheDAOscanparticipate,andguardagainstSybilattacks.Thethreemostcommonly
usedmembershipsystemsare[12]:
Token-basedmembership MembershipisgrantedviathepossessionoftheDAO’sfungiblegovernancetokens;
theextentofgovernancepowertypicallydependsonthenumberoftokensanaddressholds.Thegovernance
token can be freely transferred and purchased on public exchanges. Since the value of a governance token
istypicallydependentonthesuccessofitsDAO,ownershipofthetokentheoreticallyalignstheindividual’s
economicinterestswiththoseofthecollective.
Share-basedmembership Similartoacompany,membersholdsharesthatgrantthem(proportionate )own-
ershipoftheDAO’streasuryandvotingrightsinitsgovernance.Unliketoken-basedsystems,sharescannot
simplybeacquiredonanopenexchangebutareearnedorgrantedoncertainconditions.Differentsharetypes
arepossible,includingadistinctionbetweenpurelyeconomicandvotingshares.
Openmembership Inthismodel,anyonecanparticipateingovernance,butgovernancepowerdependson
certainattributes.Forexample,someDAOsusereputationsystems,wherebymemberswithahigherreputation
scorearefavoredinthegovernanceprocess.Reputationcanonlybeearned(i.e.grantedbyothermembers),not
Distrib.LedgerTechnol.
4 • Jungnickeletal.
purchasedortransferred.WhileanyonecanparticipateintheDAO,onlythosethathaveearnedareputationwill
haveanimpact.
DAOs grant membership to addresses, not individuals. Some share-based DAOs seek to vet new member
addressesandidentifytheindividualscontrollingthem(e.g.theLAO[60]),butmosttokenandopen-membership
DAOsdonot.Sincegovernancetokenscanbetransferredfreely,vettingeachnewholderwouldnotbeviable.
Openmembershipbydefinitionimposesnorestrictionsonparticipation;however,attributessuchasreputation
can be reserved for vetted members. Most DAOs also allow smart contracts to become members: it is not
uncommonthatmembersarethemselvesDAOs(e.g.ConvexDAOinCurveDAO[15]).
VoterWeight: AttributingequalweighttothevotesofallmemberswouldexposetheDAOtotheriskofSybil
attacks.Unlessnewmemberaddressesarevetted,oneindividualcancontrolmanymemberaddresses,meaning
attackerscouldsimplygeneratenewaddressesuntiltheycontrolamajority.SincemostDAOsprefernotto
imposerigorousmembershipcontrols,theyinsteaddistributevotingpowerunequally.Thisdecreasestheriskof
Sybilattacksbecausevotingpowerisnolongerproportionatetothenumberofaddressesindividualcontrol.Itis
alsoviewedasfairthatthosememberswhohaveinvestedorcontributedmosttotheDAOshouldberewarded
andtrustedwithalargershareofthevotingpower.Themostcommonapproachesforvote-weightingisdiscussed
below.
Token-BasedWeighting Intoken-basedvotingsystems,theweightofavotecastbyanaddressisdetermined
bythenumberofgovernancetokensitcontrols.Typicallyoneunitofweightisgrantedforeachtokensothat
powerisproportionatetotokenownership.Curve[18],Uniswap[63],Maker[37],andothermajorprotocol
DAOsusethismechanism.
Share-BasedWeighting Proposalsareapprovedbyasimplemajorityofshares;themoresharesamember
controls,thegreatertheirvotingweight.Thismeanstheapproachisverysimilartotoken-basedvoting.Itwas
famouslypioneeredbytheMolochDAO[55]andisnowusedbyDAOhaus,aDAOcreationwebsite.
Reputation-BasedWeighting Inreputation-basedweighting,amember’sreputationbalancedeterminesthe
weightofthevotestheycast.Thismeansvotingweightcannotbepurchasedortransferredbutmustbegranted
bytheDAO.SeveralmajorDAOtoolingprovidersofferreputation-basedgovernancemechanisms,including
Aragon[24],Colony[24],andDAOstack[24].Oneofthemostwell-knownreputation-basedDAOsisdxDAO[39].
QuadraticWeighting Quadraticvotingmechanismstypicallyusegovernancetokensbutimplementanon-
linearrelationshipbetweenthenumberoftokensownedandvotingpower[65].Unliketraditionaltoken-based
voting,amembercanchoosehowmanyoftheirgovernancetokenstouseonagivenproposal;theweightof
theirvoteWisthesquarerootofthenumberoftokensTusedEq.1:
√
𝑊 = 𝑇 (1)
Thismeansthecostofaunitofweightincreasesquadratically.Unliketheaboveapproaches,thetokensusedon
aproposalarenolongeravailableforvotingonotherproposals.Membersthusneedtochoosehowtoallocate
theirsupplyofgovernancetokensacrossdifferentproposals.Theusedtokensarethenre-distributedequally
amongvotersafterafixedperiodorburnedpermanently.
VotingMethod: AnotherelementofDAOgovernanceisthevotingmethodemployedtoselectawinningou tcome.
Although DAOs have access to a wide range of voting methods [43], most primarily adopt one of the three
approachesoutlinedbelow.Foramorecomprehensivereview,refertothetaxonomyofDAOvotingmethods
createdbyAragon[3],asupplierofDAOgovernanceinfrastructure.
PluralityVoting Pluralityvotingmeanstheoptionwiththemajorityofvotingweightwins;inDAOs,the
optionsareusuallyabinarychoicebetweentheapprovalorrejectionofagivengovernanceproposal.Sincethis
meansonlyasimplemajorityisrequiredtopassaproposal,quorumsareusedtoenforceaminimumamount
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 5
of participation. This voting method is very popular and is used by most major token-based DAOs, such as
Uniswap[63]andCompound[14].
ContinuousApprovalVoting Incontinuousapprovalvoting,competingproposalsaremutuallyexclusive
alternatives.Whateverproposalreceivesthemostvotesgetsimplemented.Onceaproposalhasbeenapproved,
thevotesinitsfavorremainrelevantsinceanewalternativeproposalisonlypassedifitreceivesmorevotes
thanthelastwinningproposal.Thismeansvotingisalwaysachoicebetweenkeepingthestatusquo(i.e.the
lastwinningproposal)orreplacingitwiththenewproposal.Votersseekingtoobjecttothenewproposaldo
notvoteagainstitbutsimplyvoteinfavorofthelastwinningproposal,expressingtheirsupportforkeeping
thestatusquo.Thisvotingmechanismisused,amongothers,byMakerDAO[37],whichgovernstheprotocol
responsiblefortheDaistablecoin[24].
HolographicConsensusVoting Holographic Consensus is a voting mechanism that seeks to resolve the
requirementofhighmemberengagement[19][26].Itallowsmemberstobetastakeonwhetherproposalswill
beacceptedorrejectedbythecommunity,therebyfilteringtheproposalsforthemostrelevantones[22].The
moretokenshavebeenstakedonthesuccessofaproposal,themorelikelyitistocometotheattentionof
additionalmembers.ParticipantsintheDAOcanthusbemorepassiveandonlyreviewhighly-backedproposals.
Whenenoughtokenshavebeenstakedonthesuccess,thevotingrulesfortheproposalareamendedtoallowfor
asimplemajoritywithoutaquorumbeingreached.Thismeansonlyasubsetofmembersneedtoparticipate
inthosevotes,forwhichthereisahighchancethattheywouldbevotedforbyalargemajorityanyway[26].
ThisvotingmechanismwaspioneeredbyDAOstack,aDAOcreationwebsite,andhasbeensuccessfullyusedby
dxDAO[27].
2.2.2 ExecutiveGovernance. Executivegovernanceconcernsdecision-makingprocessesinDAOsthatdonot
relyonmembervotes.Decisionsareeithermadebysmallgroupsorsingleindividuals.
SmallGroupDecisions Small group decision-making in DAOs is typically done through multi-signature
wallets, such as Gnosis Safes [53]. In their usage, these wallets are akin to standard wallets (public/private
keypairs),butarecontrolledbyseveralowners.Tousethewallet,apreviouslyspecifiedfractionoftheowners
mustsignthetransactionwiththeirownwallet.
Multi-signaturewalletsaremainlyusedinthreeways:1)astheonlymechanismgoverningtheDAOorasub-
sectionoftheDAO,2)asasafeguardthatcanoverrideorvetodemocraticdecisions,or3)implementnon-binding
off-chainvotes.Multi-signaturewalletstypicallyuseabasicapprovalsystem,whereanytransactionsignedby
MoutofNownersisexecuted.Moresophisticatedmechanismsforsmall-groupdecisionsmakinghavebeen
developed(e.g.Colony[13]),butarelesscommonlyused.
IndividualDecisions Some DAOs allow certain individuals to make low-impact governance decisions by
themselves;inparticular,DAOscreatedusingColony’sgovernancemodelemploythismechanism[2].Such
decision-makingistypicallyimplementedviaapermissionregistrythatrecordswhichmemberaddressesare
allowedtocallwhichfunctionsintheDAO.Beforeexecutingthefunctioncode,theDAOsmartcontractconsults
thepermissionregistry,todeterminewhetherthememberisentitled.
2.3 DAOLandscape
TheDAOlandscapecanbroadlybeseparatedintothreesegments:1)DAOsusedforthecollectionanddistribution
offunds,2)ProtocolDAOsthatenablecommunitycontrolovertokenprotocols,and3)ServiceDAOs,suchas
thoseusedforsocialmediaDApps[20][16].Thisreviewwillpresentacross-sectionofDAOsspanningthese
segments.TheDAOswereselectedsothateachofthemaingovernancemodelsdescribedaboveisrepresented.
Distrib.LedgerTechnol.
6 • Jungnickeletal.
3 SCOPE
3.1 GovernanceModelsAcrossSelectedDimensions
TheanalysisfocusedonunderstandinggovernancebehaviorwithinthemostprominentDAOvotingsystems
acrossselecteddimensions.Itshouldbenotedthattheterm’governancemodels’inthiscontextspecifically
referstotheaspectsofvotingpower,controversy,andparticipation.Weacknowledgethatgovernancemodels
canencompassbroaderintrinsicdetails,suchaschosenvotingmechanisms,hierarchies,ortheabsencethereof.
However,ouranalysisislimitedtotheselecteddimensionsmentionedabove,focusingprimarilyonmembership,
proposalcreation,andvotingdata.Thislimitationarisesfromthechallengeofcomparingalargenumberof
DAOsacrossvariousdetailedparametersthatmaynotbeuniformlyavailable.
Inthisstudy,wecategorizeDAOsintothreeprominentgovernancemodels:”share,””reputation,”and”token”-
based models, which are identified as the most common approaches. While all these models use tokens for
representation,thenatureanduseofthesetokensdiffersignificantly.”Share”DAOsinvolvetokensthatoften
representstakedbalances,whichmaynotbeactivelytradable.”Reputation”DAOsusenon-transferabletokens
earnedthroughcontributionsandactivitieswithintheDAO.Ontheotherhand,”token”DAOsuseactively
tradabletokens,whicharetypicallyliquid(i.e.,transferabletokenswithhighmarketliquidity)andcanbeused
fortransactionsoutsidetheDAO.Thisdistinctionhelpstobetteranalyzeandcomparethedifferentgovernance
structuresandtheirimplicationsonvotingpowerandparticipationwithinDAOs.
EachofthemodelswasrepresentedbyanumberofDAOs;alloftheselectedDAOsaredeployedtoEthereum
Mainnetoroneofitssidechains.
• Share:DAOhausisanapplicationthroughwhichcreatorscanconfigureanddeploypre-madeDAOtemplates1
, which implements the Moloch DAO’s share-based governance model. DAOhause was used to represent
share-basedgovernancebecauseallDAOscreatedthroughthiswebsiteareverysimilar,meaningtheycanbe
analyzedintheaggregate.Intotal,503DAOswereincluded;thethreelargestbyAuMwereselectedfordeeper
analysis.
• Reputation:DAOstackisalsoanapplicationforcreatingandconfiguringDAOs.Itoffersareputation-based
governancemodeldescribedinthecasestudyofdxDAO.LikeDAOhaus,DAOstackwasselectedbecauseit
hasproducedalargenumberofverysimilarreputation-basedDAOs.Atotalof211DAOswereincluded,and
dxDAOwasselectedfordeeperanalysis.
• Token:AnumberofprotocolDAOswereselectedtorepresenttoken-basedvoting.TheseDAOsgoverntoken
protocols, such as those used for decentralised borrowing and lending [20] [17]. Unfortunately, no DAO
creationtoolcouldbeidentifiedthathasproducedalargenumberofsimilartokenDAOsforwhichgovernance
dataisavailable2;forthisreason,foursimilarbutindividuallycreatedDAOshadtobeused.
Additionally,votingdatafrom9725DAOsonSnapshot[54],apopularoff-chainvotingapp,wasexamined.
ArecentstudybyWangetal.[67]providesalarge-scaledescriptiveanalysisofDAOsusingSnapshotdata,
focusingonclassificationofDAOtypes,votingmechanisms,andtokenusage.Ourworkiscomplementaryin
thatweemployDAO-specifictechnicalmetrics(e.g.,Gini,Lorenz,andNakamotocoefficients)andcontroversy
measures,therebyofferingamorefine-grainedperspectiveoncentralizationdynamicsandparticipationtrends
thatarenotaddressedinWangetal.’sstudy.TheresultsofvotesonSnapshotarenotimplementedautomatically
1Whiletherearemanycustom-madeDAOswithuniquegovernancemodels,theemergenceofDAOtemplatesandlibrarieshaveledtoa
convergenceofgovernancemodels.ThemajorityofDAOsarecreatedviawebsitesthatallowuserstoconfigureanddeployDAOswithout
requiringanytechnicalunderstanding.Thesewebsitesdifferentiatethemselvesbythegovernancemodelstheyoffer;acomparisonofthe
DAOscreatedfromdifferentwebsitesthusallowsforacomparisonofdifferentgovernancemodels.Themostpopularcreationwebsitesare
Aragon,Colony,DAOhausandDAOstack[26][48].
2WhileAragonisapopularapplicationofferingtoken-basedtemplateDAOs,itwasnotusedbecausegovernancedatacouldnotbeaccessed,
andtheDAOsitproducesvarymoreintheirgovernancesystems.
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 7
on-chain.DAOsusuallyeitheruseSnapshotasapollingtoolpriortoon-chainvotingtotestmembersentiment
(e.g.Uniswap)orimplementsomemechanismtotranslateoff-chaindataintoon-chainexecution(e.g.Sushi
DAO).DAOsonSnapshotuseawiderangeofvotingsystems,includingthethreeselectedforanalysishere.This
allowsalike-for-likecomparisonofonandoff-chaindecision-making.
3.2 GovernanceDimensions
InSection2.2,weintroducedvariouscategorizationsrelatedtogovernancemodels,suchasdifferentmembership
methodsandvotingweightmechanisms.Thiscomprehensiveoverviewaimedtoprovidereaderswithafounda-
tionalunderstandingofthediverseapproachesinDAOgovernance.However,thecategorizationinthissection
focusesspecificallyonthedataandanalysesconductedinthisstudy,includingvotingpower,controversy,and
participation.Whileouranalysisincludesmembershipdataandvotingpower,itdoesnotdelveintothespecifics
of how membership is determined or the detailed calculations of voting weighting for each vote. Therefore,
thesimplificationisalignedwithourstudy’sscopeanddata,allowingforastructuredanalysisofgovernance
behavioracrossthemostprominentvotingsystemsusedinDAOs.
• VotingPower:Theanalysissoughttoshedlightonthedistributionofpowerandhowitdiffersacrossgovernance
models.Thisisakeygovernancedimensionsincehighlyunequaldistributionscanleadtoacentralizationof
power,introducingconcernsaboutsecurity,minorityprotection,andtheextenttowhichdecision-makingis
democratic.
• Participation:Participationconcernstherateatwhichmembersentitledtovoteongovernanceproposals
actuallypartakeindecision-making.Thisisakeydimensionofgovernanceasitrevealswhoismakingthe
decisionsintheDAO,andhowthisdependsonotherfactors,suchasvotingpower.
• Controversy:ThecontroversyofDAOdecision-makingconcernstheextentofdisagreementaboutgovernance
proposalsamongmembers.Itisakeydimensionofgovernancesinceitshedslightontheefficiencyofthe
consensusmechanismsusedandtheextenttowhichmemberinterestsarealigned.
ThesemetricsareofparticularimportanceastheyprovidevaluableinsightsintothehealthofDAOsandhelp
identifyareasforenhancingtheirgovernancestructures.Byanalyzingandcomparingthesemetricsacrossa
selectedgroupofDAOmodels,weaimtoprovideacomprehensiveevaluationoftheirgovernancehealth.Other
potentialgovernancemetricsmayalsoberelevant,butforthepurposeofthisstudy,weprioritizetheanalysisof
participation,controversy,andvotingpowermetrics.Thereareseveralreasonsforthis.First,thedistribution
ofvotingpowerwithinaDAOcansignificantlyimpactitsgovernanceprocessesandoutcomes.Second,ahigh
levelofparticipationfrommembersiscrucialforthesuccessofDAOs.Third,measuringthelevelofcontroversy
withinaDAOcanhelpidentifyareasofpotentialconflictandfacilitatetheresolutionofdisputes.
WhileourstudypresentsanempiricalanalysisofdecentralizationtrendsacrossleadingDAOs,recenttheoretical
worksshouldbeacknowledged.Forinstance,Hanetal.[32]developamodelthatexploreshowtokenlocking
mayalleviateconflictsofinterestamongstakeholders,offeringagovernancedesignrationale.Laturnus[36]
highlightspersistentlylowparticipationratesinDAOs,complementingourfindingsonfluctuatingmember
engagement.Additionally,recentreviewstudiessuchasHanetal.[31]andJiangandLi[34]providebroader
theoreticalperspectives.Comparedtothese,ourcontributionisdistinctinofferingplatform-specifictemporal
metricsandvisualanalysestodissectevolvinggovernancebehaviorsempirically.
4 DATAANDMETHODOLOGY
4.1 Dataset
DataaboutgovernancebehaviorisemittedandstoredbythesmartcontractsconstitutingtheDAO.Theoretically,
thisdatacanberetrievedbyqueryingablockchainnodeforpastsmartcontracteventsorcallingmethodsonthe
Distrib.LedgerTechnol.
8 • Jungnickeletal.
Table1. DataCollectionCodeandCommandSamples
(a) (c)
{ curl −X POST −H ”Content−Type: application/json”
avatarContracts(first:5) −d ’{”query”: ”{ proposals(first: 5)
{ { id proposer description status
id votes { id voter support } } }”}’
address https://api.thegraph.com/subgraphs/name/daosubgraph/moloch
name
Ifauthenticationisrequired,includeanAPIkeyintheheaders:
nativeToken
} curl −X POST −H ”Content−Type: application/json”
−H ”Authorization: Bearer YOUR_API_KEY”
} −d ’{”query”: ”{ proposals(first: 5)
{ id proposer description status
votes { id voter support } } }”}’
https://api.thegraph.com/subgraphs/name/daosubgraph/moloch
(b)
(d)
{
proposals(
first: 1000, {”data”: { ”avatarContracts”: [{
skip: 0, ”address”: ”0x006087d6ac20840c23ba298512db454a05c19b10”,
where: { ”id”: ”0x006087d6ac20840c23ba298512db454a05c19b10”,
space: ”sushigov.eth” ”name”: ”FitTogether”,
}, ”nativeToken”:”0xa3820e0f6be1c306c0a76746af80b60c228d99c2”
orderBy: ”created”, }, {
orderDirection: desc ”address”: ”0x00e1b6de09e01d5b178ecf68966a34bd1dcd4064”,
) { ”id”: ”0x00e1b6de09e01d5b178ecf68966a34bd1dcd4064”,
id ”name”: ”YoyoDAO”,
title ”nativeToken”:”0xb9697151c7af8f8a4d2702c8291e3d649525b1d9”
choices }]}}
state
end (e)
snapshot
scores_total
import Web3 from ”web3”;
scores
import { AbiItem } from ”web3−utils”;
state
import { LAO_ABI } from ”./ABIs”;
author
import fs from ”fs”;
created
space {
const provider = ”https://mainnet.infura.io/v3/
id
YOUR_INFURA_PROJECT_ID”;
name
const web3 = new Web3(
}
new Web3.providers.HttpProvider(provider));
votes
const adr = ”0x8F56682a50BECB1df2Fb8136954f2062871bc7fc”;
}
const contract = new
}
web3.eth.Contract(LAO_ABI as AbiItem[], adr);
async function getPastVotes() { fs.writeFileSync(
”./votes.csv”, ”memberAddress,proposalId ,vote\n”);
const events = await contract.getPastEvents(”SubmitVote”,{
fromBlock: 9000000, toBlock: ’latest ’
});
events.forEach(event => {
const memberId = event.returnValues.memberAddress;
const propId = event.returnValues.proposalId;
const vote = event.returnValues.uintVote;
fs.appendFileSync(”./votes.csv”, ‘${memberId},${propId},
${vote}\n‘);
});
}
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 9
contracttoextractthedataitcontains.SeveralDAOsusesubgraphstomakedataabouttheirgovernancemore
readilyaccessible.Subgraphsaremaintainedbyindexers,wholistentoeventsontheblockchain,storetheevent
data,andofferaGraphQLinterfacetorunqueries[59].
Theprimarysourceofdatafortheanalysiswassuchsubgraphs,buttheydidnotalwayscontainalltherequired
information.Insuchcases,datapublishedontheDAOwebsitewereusedtofillinthegaps.Table2containsa
completelistofthesourcesusedfortheanalysis3.
4.1.1 DataCollectionUsingTheGraph. TheGraphisadecentralizedprotocolforindexingandqueryingdata
fromblockchains.ItallowsdeveloperstobuildandpublishopenAPIs,calledsubgraphs,thatapplicationscan
queryusingGraphQL.Subgraphsarebuiltbydefiningaschemathatspecifiesthedatastructureandthesources
ofthedata.Oncedeployed,indexersonTheGraphnetworkcontinuouslyupdatethesubgraphsasnewdatais
addedtotheblockchain.
TheGraphQueries:QueriestosubgraphsonTheGrapharemadeusingGraphQL,whichallowsyouto
requestspecificdatainastructuredformat.InTable1athereisabasicexampleofaGraphQLquerytoretrieve
thefirstfiveofthemaincontracts(avatarcontracts)fortheDAOsthatarepartofDAOstackDAOs.
RunningTheQueries:Torunthesequeries,youcanuseTheGraph’shostedserviceoradecentralizedGraph
node.Table1cshowsacommandtorunaqueryusingthehostedservice.
EachsubgraphhasauniqueURL.Forexample,theMolochDAOsubgraphURLmightbe:
https :// api . thegraph .com/subgraphs/name/daosubgraph/moloch
SomeGraphQLendpointsrequireanAPIkey.YoucanobtainthisbysigninguponTheGraph’shostedservice
platform.YoucanthenusethesamecommandwiththeinclusionofAPIkey,Table1c.
QueryResultsWhenthequerydescribedinSection4.1.1isexecuted,theresultissimilartothesample
showninTable1a.Dependingonthequeryandcorrespondingdatastructure,TheGraphprovidesaJSONformat
file.ThisJSONfileincludeskey-valuepairsrepresentingdifferentaspectsofthequerieddata,suchasaddresses,
IDs,names,andnativetokens.ThesamplefromTable1dillustratesthetypicalstructureofsucharesultforthe
firsttwoDAOsfromDAOstack.
4.1.2 DataCollectionUsingSnapshotAPI. SnapshotisadecentralizedvotingsystemwidelyusedbyDAOsfor
off-chaingovernance.SnapshotallowsDAOstocreateproposalsandvotingsystemsthatdonotincurgascosts,
makingitapopularchoiceformanydecentralizedorganizations.SnapshotAPIcanbequeriedtogatherproposal
andvotingdata.Table1blistsaquerycompatiblewithSnapshotAPIbasedbyGraphQLfortheSushiDAO.
Torunthisquery,youcanuseaJavaScriptcodewithAxios,apromise-basedHTTPClientfornode.jsandthe
browser.ThiswayyoucanfetchtheproposaldataandsaveittoaCSVfileoranyothersuitableformat.
Snapshot data can also be queried using the snapshot.js node package. However, in this study, using the
GraphQL-basedqueriesprovidedbytheSnapshothubservicefordatacollectionispreferred.
4.1.3 DataCollectionviaDAOContracts. DAOcontractscanbedirectlyqueriedtocollectgovernancedatasuch
asvotingrecords,proposals,andmemberinformation.Byinteractingwiththesmartcontractdirectlythrougha
blockchainnode,historicaleventdataemittedbythecontractcanbeextracted.Thismethodwasappliedfor
severalDAOstoretrievespecificgovernancedata.
Table1ehasasimplifiedexampleofqueryingTheLAODAOcontracttoretrievepastvotingevents.This
exampleusesWeb3.jstointeractwiththeblockchain.
Usingthesemethods,thestudycollectedcomprehensivedataonDAOgovernancebehavior,ensuringarobust
datasetforanalysis.
3Datauptothe4thweekofJune2025wasincludedinthegovernanceanalysis.
Distrib.LedgerTechnol.
Chunk 1
10 • Jungnickeletal.
Table2. SummaryofTheExploratoryAnalysis
CrossRefer- AnalysisName DAOs #of DataUsed DataOrigin
ence DAOs
Figure1a,Figure GiniDistributionAcross AllActiveDAOhaus 503 MembersDataforAllDAOshavingDAOID,member On-chain
1b DAOs,GiniDistribution DAOs ID,MemberShareConvertedtoaGiniDataHaving
AcrossDAOMemberSize DAOID,MemberSize,GiniCoefficient
Figure2a,Figure GiniDistributionAcross AllActiveDAOstack 211 MembersDataforAllDAOshavingDAOID,member On-chain
2b DAOs,GiniDistribution DAOs ID,MemberShareConvertedtoaGiniDataHaving
AcrossDAOMemberSize DAOID,MemberSize,GiniCoefficient
Figure3a LorenzCurves DxDao,Lao,Meta, 7 HoldersData* On-chain
Moloch,Maker,
Uniswap,Curve
Figure3b,Figure ChangeofGiniCoeffi- DxDao,Lao,Meta, 6 HistoricalBalances(Shares)Data On-chain
3c cientinTime,Changeof Moloch,Uniswap,
NakamotoCoefficientin Curve
Time
Figure3d VotingPowerPieCharts DxDao,Lao,Meta, 7 HoldersDatawhichisMemberswithShares/Balances> On-chain
Moloch,Uniswap, 0
Curve,Maker
Figure4a On-chainVotingFrequency DxDao,Curve, 6 MembersData,VotingData On-chain
Uniswap,Lao,
MetaCartel,Moloch
Figure4b On-chainvsOff-Chain Curve,Uniswap, 3 MembersData,VotingData On-chainand
VotingFrequency MetaCartel Off-Chain
Figure5a,Figure MajorityvsTurnout,Major- AllSnapshotDAOs 9725 ProposalDataHavingProposalID,VoteCounts,Pro- Off-chain
5b,Figure5d ityvsSize,MajoritySize posalResults
Figure5c,Figure MajorityvsTurnout(Sushi), Sushi 1 ProposalDataHavingProposalID,VoteCounts,Pro- Off-chain
5e MajoritySize(Sushi) posalResults
Figure6 StakeMajorityvsShare AllActiveDAOstack 211 ProposalDataHavingProposalID,VoteCounts,Pro- On-chain
Majority(DAOstack) DAOs posalResults
Figure7a,Figure ControversyAnalysisVote AllActiveDAOhaus 503 ProposalDataHavingProposalID,VoteCounts,Pro- On-chain
7d,Figure7g vsMajorityforDAOhaus DAOs posalResults
Proposals,Controversy
AnalysisTurnOutvs
MajorityforDAOhaus
Proposals,Controversy
Analysis%ofProposals
vsMajorityforDAOhaus
Proposals
Figure7c,Figure ControversyAnalysisVote Aave,Uniswap 2 ProposalDataHavingProposalID,VoteCounts,Pro- On-chain
7f,Figure7i vsMajorityforSelected posalResults
ProtocolDAOs,Contro-
versyAnalysisTurnOutvs
MajorityforSelectedPro-
tocolDAOs,Controversy
Analysis%ofProposals
vsMajorityforSelected
ProtocolDAOs
Figure7b,Figure ControversyAnalysisVote AllActiveDAOstack 211 ProposalDataHavingProposalID,VoteCounts,Pro- On-chain
7e,Figure7h vsMajorityforDAOstack DAOs posalResults
Proposals,Controversy
AnalysisTurnOutvs
MajorityforDAOstack
Proposals,Controversy
Analysis%ofProposals
vsMajorityforDAOstack
Proposals
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 11
4.1.4 DataLimitations. Theexploratoryanalysisfacedseveraldata-relatedchallenges:
• Heterogeneity:Governancedatastructuresvaryacrosscontractsandsubgraphs,complicatingretrievaland
limitingdirectcomparability.
• Availability:Onlyon-chaindatastoredoremittedbycontractswasaccessible.Duetogascostconcerns,this
dataisoftenminimalandinconsistentacrossDAOs.
• SelectionBias:DataavailabilityinfluencedDAOselection,potentiallyskewingthesampletowardDAOs
withmoretransparentdata.
4.2 Methodology
Thevotingpowerofanaddressreferstotheweightattributedtoavotecastfromthataddress.TheGinicoefficient
wastheprimarymetricusedtomeasurethedegreeofinequalityinvotingpower.Lorenzcurveswereusedto
displaythefractionofthetotalvotingpower(y-axis)heldbyagivenfractionoftheDAO’smembers(x-axis).
Sinceneitherofthesemetricsrevealstheimpactofinequalityondecision-making,theNakamotocoefficient
wasalsocalculated.Thiscoefficientistheminimalnumberofmembersrequiredforanabsolutevotingmajority
withintheDAO.Onlyon-chaindatawasusedsincemembers’off-chainvotingweightistypicallythesame.
(cid:40)
• VotingPower:𝑉𝑃(𝑚) =
share𝑚 ifDAOusesshares
balance𝑚 otherwise
• GiniCoefficient:𝐺 =1− (cid:205)𝑛 𝑖=1 ( 𝑛 𝑥 − 𝑖+ 1 𝑥𝑖−1 ) ,where𝑥 𝑖 isthecumulativevotingpowerofthe𝑖𝑡ℎ member(sorted),
and𝑛isthenumberofmembers.
• LorenzCurve:𝐿(𝑝) =
∫
0
𝑝𝑥(𝐹−1(𝑢))𝑑𝑢
,representingthecumulativevotingpowerheldbythebottom𝑝%of
∫1𝑥(𝐹−1(𝑢))𝑑𝑢
0
members.
(cid:16) (cid:17)
• NakamotoCoefficient:𝑁 =min𝑘 (cid:205)𝑘 𝑖=1 𝑆 𝑖 ≥ 51% ,where𝑆 𝑖 isthevotingshareofmember𝑖;𝑁 denotesthe
smallestnumberofmemberscontrolling51%ofvotingpower.
SeveralDAOsacrossallthreegovernancemodelswereselectedforatemporalanalysis;temporaldatawasnot
availableforallDAOsanalyzed.SincetheDAOshaveexistedfordifferentamountsoftime,thetimeintervals
werenormalized.Asaresult,therateofchangeofthecoefficientsisnotcomparableacrossDAOs.Theearliest
measurementsforeachDAOaretakenapproximatelyonemonthaftercreationandthelatestmeasurements
are fromthe 30th of July 2022. Measurementswere taken at quarterly intervals, meaning not all temporary
fluctuationsaredisplayed.
TwometricswereusedtomeasureparticipationinDAOgovernance;thefrequencywithwhichmembersvote
andvoterturnout.DuetothelimitedavailabilityofdataonlyasubsetoftheDAOsiscompared.Bothonand
off-chainvoteswereconsideredtoofferadirectcomparison.
• VotingFrequency:votingFrequency(𝑚𝑒𝑚𝑏𝑒𝑟 𝑖) =NumberofVotesbymember𝑖
• NormalizedFrequency:normalizedFrequency(𝑚𝑒𝑚𝑏𝑒𝑟 𝑖) = votingFrequency(𝑚𝑒𝑚𝑏𝑒𝑟𝑖)
TotalNumberofProposals
• ParticipationDistribution(StackedBar):Normalizedvotingfrequenciesaregroupedintointervals(e.g.,
0–20%,20–40%,etc.).Foreachbin𝑏,theproportionofmembersis:weight(𝑏) = #MembersinBin𝑏
TotalMembers
Theseproportionsarevisualizedasstackedbars,whereeachsegmentreflectsonebin.
• VoterTurnout:Foreachproposal𝑝,voterTurnout(𝑝) = #VotedMembers
TotalMembers
Controversyisdeterminedbytwofactors:thedivergenceofvoteropinionsandtheimportanceattributedtothe
decision.Majoritysize(i.e.percentageofvotesforthewinningoption)capturesdivergence,whilevoterturnout
reflectsimportance.Highlycontroversialdecisionsareexpectedtoshowlowmajorities(highdisagreement)and
highturnout(highimportance).Bothon-andoff-chainvoteswereanalysedforcomparison.
Distrib.LedgerTechnol.
12 • Jungnickeletal.
• MajoritySize:MajoritySize(𝑝) = #VotesforWinningOption
TotalVotes
• VoterTurnout:Ratioofvotingmemberstototalmembers:VoterTurnout(𝑝) = #MembersWhoVoted
TotalMembers
• Controversy Score: Defined as ControversyScore(𝑝) = (1−MajoritySize(𝑝)) ×VoterTurnout(𝑝); higher
valuesindicatemorecontroversialproposals.
• Controversy Hexbin Plot: Shows vote density based on turnout (x-axis) and majority size (y-axis):
HexbinDensity=Density(Turnout,MajoritySize)
• NumberofProposalsHistogram:ShowshowfrequentlydifferentproposalcountsoccuracrossDAOs:
Histogram(𝑥) =Frequency(NumberofProposals)
• Turnout vs Majority: Relationship between turnout and majority size: TurnoutvsMajority =
(Turnout,MajoritySize)
• TurnoutbyDAOSize:EachpointshowsaDAO’ssizeanditscorrespondingturnout:(DAOSize,Turnout)
• ControversybyDAOSize:Plots(DAOSize,MajoritySize)toassesscorrelation.
• Turnout by DAO Proposals: Relationship between number of proposals and turnout:
TurnoutbyDAOProposals= (NumberofProposals,Turnout)
• Controversy by DAO Proposals: Relation between number of proposals and majority size:
ControversybyDAOProposals= (NumberofProposals,MajoritySize)
5 REVIEWRESULTS
5.1 SummaryoftheReviewResults
SeveralquantitativeanalysesofDAOgovernancebehavioralreadyexist,butmuchoftheresearchispiecemeal,
andlackscomparativeanalysesacrossmultiplegovernancemodels,andgenerallyfailstoconsideroff-chain
voting.Table3providesanoverviewofthemainacademicpapersthateithercontainquantitativeanalysesof
DAOgovernance,proposemethodsforconductingsuchanalyses,orhighlightothergovernanceissues.The
subsectionsbelowdescribehowthispaperseekstobuilduponandextendtheexistingresearchacrossthethree
governancedimensionsbeinginvestigated.
5.1.1 VotingPower. WhilemuchresearchhasexploredcentralizationinDAOgovernance,ithaslargelyfocused
on token-based models. There is broad consensus that such models exhibit high inequality and centralized
decision-making[56,35,33,6],thoughthepreciseextentremainsdebated[41].Thisstudyexpandsonexisting
workbyincludingDAOstack[22]andDAOhaus[21]models,aimingnottoresolvedisputesovertokengovernance
buttorankinequalityacrossmodelsandexamineitsdrivers.Rikkenetal.[47]analyzevotingweightbasedon
6000DAOprojects,findinghigherviabilityinthoseusingweightedvoting.Axelsenetal.[5]proposeabroader
framework,TIGER,toassesscentralizationthroughfactorsliketoken-weighting,infrastructure,governance,
escalation,andreputation.
5.1.2 Participation. Voterparticipationhasalsobeenexaminedseveraltimes,includingtwocomparativeanalyses
ofgovernancemodelsbyRikkenetal.[48]andFaqir-Rhazouietal.[26].Theirresearchshowsdisparitiesin
thedegreeofparticipationacrossvotersandamongDAOs.Themajorityofoverallactivityhappensinasmall
minorityofDAOsbyasmallminorityofmembers.Typically,memberswithmorevotingpowerparticipatemore
actively.ThisstudyseekstoreplicatetheseresultsacrossaslightlydifferentselectionofDAOsandextendsthe
researchbyincludingacomparativeanalysisofonandoff-chainvoting.Amongothergovernanceproblems,lack
ofparticipationismentionedbyPereiraandGarcia[45]butnoevaluationmethodispresented.
5.1.3 Controversy. Controversyhasbeenstudiedtheleastamongthegovernancedimensionsexaminedinthis
research.Whileseveralstudieshavefoundlargemajoritysizes,especiallyintoken-basedprotocolDAOs(e.g.
Fritschetal[29]),moreanalysisisneededontherelationshipsbetweenmajoritysizeandotherindicatorsof
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 13
controversy,suchasvoterturnoutandthevotermajority4.Theexistingresearchalsodoesnotfocusenoughon
comparingdifferentgovernancemodelsandoffvson-chainvoting.Thisstudyseekstoaddressthesegaps.
Governanceissuesthatdirectlyorindirectlyimpactvotingpowerdistribution,participation,andcontroversy
includelegalambiguities,rigidity,andvotingmisconduct,asnotedbyPereiraandGarcia[45].Similartothis
Bellavitisetal.[7]alsomentionedregulatoryuncertaintyasoneoftheshortcomingsofDAOSbygivingsamples
frombothinandoutsideofUSA.Beyondoperationalconcerns,thelong-termsustainabilityandadoptionofthese
governancemodelsremainpersistentchallenges[46].Bellavitisetal.[7]alsoempiricallystudytheeconomy
andevolutionofDAOs,bothofwhicharedirectlytiedtotheirsustainability.Whileempiricalstudieshelpto
understandthecurrentsituationandtoplanforthefuture,benefitingfromlong-knownmanagementtheorems
suchasagencyandstewardshiptheoremsisalsoveryusefulasusedbyAlawadietal.[1].Someotheruseful
theoremsincludetransactionalcosttheory[69],sociomaterialitytheory[50].
5.2 ExploratoryDataAnalysisResults
5.2.1 VotingPower. Theresultsshowthattoken-basedprotocolDAOsexhibitsignificantlyhigherinequalityin
votingpowerdistributioncomparedtoDAOhausandDAOstack.ThemedianGinicoefficientsforthesethree
groupsare0.98,0.75,and0.46,respectively.TheGinicoefficientdistributionsforDAOhausandDAOstackare
showninFigures1aand1b,andFigures2aand2b,respectively.ThesefiguresillustratethattheDAOhausmodel
isassociatedwithgenerallyhighlevelsofinequalityinvotingpower,asnearlyhalfoftheDAOsexhibitaGini
coefficientexceeding0.8.Incontrast,theDAOstackmodeldemonstratesamuchbroaderdistribution,withthe
majorityofDAOsmaintainingGinivaluesbelow0.6.
Several DAOs were selected for a more detailed comparative analysis. Figure 3a presents Lorenz Curves
comparingvotingpowerinequalityacrossrepresentativeDAOsfromeachgovernancemodel.Thecurvefor
protocolDAOs(dashed-dotted)deviatesmostfromtheequalityline,indicatingthemostunequaldistributionof
votingrights.DAOhaus(dashed)andDAOstack(dotted)DAOsfollowbehind,respectively.
Tounderstandhowinequalityevolvesovertime,Figure3btracksthechangeinGinicoefficientsoverthe
normalized lifetime of selected DAOs. For most DAOs, the Gini value remains relatively stable, with minor
fluctuationsobservedintheearlyphasesofactivity.Thepatternconfirmsthatinequalitytendstobepersistent
ratherthantransient.
Figure3cdisplaystheNakamotocoefficientsovertimeforthesameselectionofDAOs.Althoughnoneofthe
DAOsreachaNakamotocoefficientabove16,themetricdoesfluctuate,reflectingchangesinconcentrationlevels
amongthemostpowerfulmembers.
Inotherwords,asmallbutchangingminorityofmembersisinfullcontroloftheseDAOs.Figure3dprovides
abreakdownofvotingpowerbyaddressinselectedDAOs.Thechartshighlightthatevenwithinthesubsetof
dominantvoters,powerishighlyconcentrated.Itshouldbenotedthatthisanalysisconsidersvotingaddresses
ratherthanindividuals.Asingleindividualmaycontrolmultipleaddresses,oroneaddressmayrepresentasmart
contractoperatedcollectively.Forinstance,theCurveDAO’sprimaryvotingaddressbelongstoConvexFinance,
meaningtheactualdecision-makingpowerlieswiththemultisigsignersbehindthatprotocol5.
time.
4Thevotermajorityreferstothefractionofmemberswhovotedinfavorofaproposal.SinceDAOsgenerallydonotgiveeachmemberthe
samevotingweight,alargemajorityofvotingweightcastinfavorofadecisiondoesnotnecessarilymeanamajorityofvotersarealsoin
favor.
5WhileConvexholdsvotesonwhethertosupportCurveFinanceproposals,thesevotesarenonbindingandoff-chain.Theyareimplemented
atthediscretionofthesignatoriesoftheDAO’smultisigwallet.ThismeansthemajorityofvotingpowerinCurveisnotheldbyone
individual,butasmallgroupofindividuals.Theexampledemonstratesthatthedistributionofvotingpoweracrossindividualscanonlybe
determinedbyanalyzingeachaddressandreviewingthegovernancesystemcontrollingit;thedifficultyofsuchananalysismeansthatthe
precisedistributionremainsunknowninmostmid-to-largesizedDAOs.
Distrib.LedgerTechnol.
14 • Jungnickeletal.
(a)GiniAcrossDAOs (b)GinibyDAOSize
Fig.1. DAOhausPowerDistribution
(a)GiniAcrossDAOs (b)GinibyDAOSize
Fig.2. DAOstackPowerDistribution
5.2.2 Participation. Figures4aand4billustratememberparticipationdistributionsforaselectionofDAOs,
showingthefractionofmembersfallingintofivevotingactivitybrackets.Inthecaseofon-chainparticipation
(Figure4a),theoverwhelmingmajorityofmembersinallDAOsparticipatedinfewerthan20%ofproposals.Only
asmallfractionofmembersreachedhigherparticipationlevels,andparticipationabove60%israreacrossall
cases.
Three of the DAOsalso use Snapshot for off-chain voting, which allowsfor a direct comparison between
thetwomechanisms.AsshowninFigure4b,off-chainparticipationfollowsasimilarpattern:mostmembers
engageinlessthan20%ofproposals,withonlyafewexhibitingconsistentvotingbehavior.However,some
Snapshotplatforms,suchasMetaCartelSnap,showslightlymoreactivevotersubsetscomparedtotheiron-chain
counterparts.
VoterturnoutperproposalisdiscussedseparatelyinSection5.2.3.
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 15
(a)LorenzCurves (b)GiniCoefficient
(c)NakamotoCoefficient (d)SharesofVotingPower
Fig.3. InequalityinselectedDAOs
5.2.3 Controversy. ThissubsectionpresentstheupdatedanalysisofproposalcontroversyinDAOgovernance
votes,basedonthenewlyrefinedvisualizationinFigure5.Thefigurecapturesthedistributionofgovernance
proposalsfromSnapshot-basedoff-chainvotingsystems,acrossseveralDAOs.
InFigure5a,theconcentrationofproposalsinthetop-leftcornerhighlightsacommonpattern:mostproposals
receivelowvoterturnoutyetexhibitoverwhelmingmajorities.ThisindicatesthatinmanyDAOs,asmallportion
ofmembersdeterminetheoutcomewithlittleopposition.Theincludedtrendlineconfirmsanegativecorrelation
between turnout and majority size—higher participation levels are generally associated with closer results.
Figure5dfurtherreinforcesthisobservationbydisplayingthedistributionofmajoritysizesacrossallSnapshot
proposals,withamedianmajorityof90.49%,suggestinglimitedcontroversyinmostcases.
ToexaminetheroleofDAOsizeinthesedynamics,Figure5bmapsmajoritysizeagainstDAOsize.Themajority
ofdatapointsareagainclusteredtowardlowparticipationandhighconsensus.Thetrendlineremainsrel atively
flatacrossDAOsizes,indicatingthatevenasDAOsgrow,thepatternoflowturnoutandstrongagreement
persists—suggestingthatscalealonedoesnotsubstantiallyincreasedisagreementorcontroversy.
SushiDAOwasanalyzedseparatelyasitisoneofthefewlargeDAOsthatrelyexclusivelyonoff-chainvoting.
Theaimwastoassesswhethervotingbehaviorinpurelyoff-chainsystemsdeviatesfromDAOsthatuseahybrid
model.AsshowninFigure5e,thedistributionofproposalcontroversyinSushiDAOcloselyresemblestheoverall
Snapshotdistribution(Figure5d),indicatingnomajordeviationincontroversypatterns.
Distrib.LedgerTechnol.
16 • Jungnickeletal.
(a)On-ChainFrequency (b)On-ChainvsOff-Chain
Fig.4. ParticipationviaVotingFrequency
(a)Maj.vsTurnout (b)Maj.vsSize (c)Maj.vsTurnout(Sushi)
(d)MajoritySize (e)MajoritySize(Sushi)
Fig.5. ControversyinOff-ChainVoting
Thecontroversiesinon-chainvotingacrossDAOhaus,DAOstack,andtheselectedprotocolDAOsaredepicted
inFigure7.Theseresultssuggestthatcontroversyinon-chainvotingmaybeslightlylowerthaninoff-chainvoting,
withmedianmajoritysizesof98.28%,97.85%,and96.74%respectively.Inallthreecategories,mostproposals
receiveaconsistentlylargemajorityevenwithvaryingparticipationlevels.AlthoughtheprotocolDAOshave
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 17
Fig.6. StakeMajorityvsShareMajority(DAOstack)
thelowestmedianmajorityamongthethreegroups,proposalsonDAOhausandDAOstackdemonstrateawider
spreadinmajoritysizes,indicatingmorevariabilityinvotingoutcomes.
Sincetheaboveresultsconsidermajoritysizeintermsofvotingpower(i.e.,weightedvotes),theymayobscure
thepresenceofcontroversyamongindividualvoters.Membersoftenholddifferentvotingweights,meaninga
majorityofthevotingpowermaysupportthewinningoutcomeevenifmostvotersopposeit.Toassessthis
potentialdiscrepancy,Figures7ato7eplotthesharemajority(fractionoftotalvotingpower)againstthevote
majority(fractionofindividualvoters).Inallthreediagrams,alargeproportionofobservationsareclustered
nearthetop-rightcorner,reflectingnear-unanimousoutcomeswherebothvoteandsharemajoritiesareclose
to100%.Asaresult,thedegreeofdivergenceislesspronouncedthanitmightinitiallyappear.Thetrendlines
confirmthatvoteandsharemajoritiesgenerallyincreasetogetherinproportion.Themeanvotemajoritiesfor
DAOhaus,DAOstack,andtheprotocolDAOsare98.09%,97.38%,and96.74%,respectively.Thepercentageof
proposalswheretheoutcomewouldhavedifferedifbasedonvotemajorityratherthansharemajorityis0.91%
forDAOhaus,11.01%forDAOstack,and1.58%fortheprotocolDAOs.
The results for DAOstack additionally include an analysis of the staking majority relevant for the used
exclusivelyinDAOstackproposals.In77.3%ofproposals,thereisastakemajorityinfavourofthewinning
outcome;however,Figure6showsthatthesizeofthestakemajoritydoesnottendtoincreaseproportionately
withthesharemajority.Thisgraphhelpsassesstheeffectivenessoftheholographicconsensusmechanismin
DAOstack.Thelackofahighcorrelationbetweenstakemajorityandsharemajorityindicatesthattheboosting
mechanismmaynotbeeffectivelypredictingandinfluencingproposaloutcomes.
6 DISCUSSION
TheresultsoftheexploratorydataanalysisleadtothreemainconclusionsaboutDAOgovernance:
• Centralization:Traditionaltokengovernanceshouldbeavoidedduetoitstendencytofavourhighlycentral-
izationvotingpowerdistributions.
• LowParticipation:Participationingovernancedecisionsislow,somembersshouldinsteadelectdecision-
makerstoconductgovernanceforthem.
• LackingControversy:Governanceproposalsareoftenuncontroversial,somakingthemsubjecttovotingis
inefficient;instead,governanceshouldfocusonfewer,morecontroversialdecisions.
Thefollowingsubsectionswilladdressthesepointsinturn;eachsubsectioncontainsadiscussionoftheproblem
andanevaluationofitsimpact.
Distrib.LedgerTechnol.
18 • Jungnickeletal.
Table3. SummaryofRelatedWork
Authors Topic Findings DAOs
Fritschetal.[29] Governancebehavior,inequality, Unequalvotingpower,lowdelegation,infrequent ENS,Uniswap,
votedelegation participation Compound
Rikkenetal.[48] Governancesystempopularityand Aragonmostpopular,DAOhausandDAOstackfollow; Aragon,DAOhaus,
activity mostDAOsinactive,fewhighlyactive DAOstack
ElFaqiretal.[24] Viabilityofholographicconsensus BoostingpredictsproposalsuccessinlargeDAOs DAOstack
FaqirRhazouiet EffectofgaspricesonDAOactiv- Nosignificantimpactonvotingbehavior DAOhaus,DAOstack
al.[28] ity
FaqirRhazouietal. PopularityandactivityinDAO Aragonmostpopular,DAOhausandDAOstackfollow; Aragon,DAOhaus,
[26] governancesystems lowactivity DAOstack
Sunetal.[56] Centralizationandvotingactivity Highinequality,lowparticipation,largeholdersdomi- Maker
inMaker nate
Stroponiatietal.[35] Centralizationintokengover- Highinequality,decisionsbysmallminority;security Maker,Curve,IDEX,
nance risks Compound,Uniswap
Jensenetal.[33] Inequalityintoken-basedgover- Highinequality,powerfulminoritydominance Yearn,Compound,
nance Uniswap,Balancer
NadlerandSchar Wrappedownershipofvoting Lesscentralizationthanappears;largetoken-holders Maker,Compound,
[41] power oftencontractscontrolledbysmallerowners Sushi
Barbereauetal.[6] Inequalityintoken-basedgover- Highinequalityduetoinitialdistributionandunlimited Uniswap,Aave,
nance votingpowerpurchase Maker,Compound
Rikkenetal.[47] ParametersaffectingDAOviability DAOswithoutweighteddecision-makingorincentives 6000initialDAO
aremoreviable projects
Axelsenetal.[5] DAOcentralizationmeasurement Proposesaframeworktomeasurecentralizationin UsesCompoundto
DAOgovernance evaluateframework
PereiraandGarcia DAOgovernanceissuesandfuture Proposesfuturestudytopics,e.g.,adoptingdecentral- -
[45] topics izedgovernance,communityretention
Peña-Calvinetal. FrameworktocategorizeDAOs CategorizesDAOsbydomain,purpose,votingprocess, 40DAOsusing
[44] crypto-tokenuse;identifiesarchetypesinAragon Aragon
Pinioetal.[46] ComparativeanalysisofDAO ProvideskeyinsightsintoDAOgovernancebutfocuses 10leadingDAOs
governancemetrics onalimitedsetofmetrics,which,whilevaluable,may (unnamed)
notfullycapturethecomprehensivelandscapeofDAO
governancedynamics
Bellavitisetal.[7] DAOs’challenges,opportunities, HighlightsDAOs’marketpotential,providesempirical 2300activeDAOs
empiricalanalysis governanceanalysis fromDAOAnalyzer
AAlawadietal.[1] SurveyonDAOgovernancesys- DAOsalignedwithstewardship,butoperationslean Participantsfrom20
tems towardagencyperspectives DAOs
6.1 CentralizationinTokenGovernance
AllgovernancemodelsinvestigatedproducedDAOswithhighlyunequalvotingweightdistributions,leadingto
centraliseddecision-making,consistentwithexistingresearch[56][35][33][6].Thisanalysisexploresdifferences
incentralizationlevelsacrossmodelsandunderlyingcauses.Token-basedprotocolDAOsconsistentlyshowed
thehighestGinicoefficients,followedbyDAOhausandDAOstack.Itisarguedthattoken-basedsystemsare
morepronetoinequalityduetothetradability,rewardfunction,andunequalinitialallocationoftokens.The
relativelylowercentralizationinDAOhausandDAOstackhighlightsgovernancefeaturesthatmayreducepower
imbalances.
Amajordriverofinequalityintoken-basedgovernanceistheabsenceoflimitsonpurchasingvotingrights.
Here,votingpowerderivesfromfreelytradeabletokens,enablingindividualstobuyorborrowlargeamounts
foroutsizedinfluence.Incontrast,DAOhausandDAOstackimplementstructuralsafeguards:DAOhausrequires
memberapprovaltoissuevotingshares,whileDAOstackgrantsnon-transferable,earnedreputationscores.
Thesemechanismsshowhowlimitingtransferabilityandaccumulationcanreducecentralization.
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 19
(a)VotevsShare(DAOhaus) (b)VotevsShare(DAOstack) (c)VotevsShare(ProtocolDAOs)
(f)MajorityvsTurnout(Protocol
(d)MajorityvsTurnout(DAOhaus) (e)MajorityvsTurnout(DAOstack) DAOs)
(g)MajoritySize(DAOhaus) (h)MajoritySize(DAOstack) (i)MajoritySize(ProtocolDAOs)
Fig.7. ControversyinOn-ChainVoting
Intoken-basedDAOs,thetreatmentofgovernancetokensasfinancialassetscreatesstrongeconomicincentives
formemberstoaccumulatevotingpower,therebyamplifyingtheriskofcentralization.Governancetokensof
majorprotocolDAOs—suchasMKR,CRV,andUNI—havedeliveredsubstantialinvestmentreturns,makingthem
attractiveevenbeyondtheirutilityingovernance.AsStroponiatietal.[35]highlight,suchtokensareoften
acquirednotonlytoexertinfluencewithintheDAO,butalsoasspeculativeassets.Thesedynamicsareless
pronouncedinDAOhausandDAOstack.DAOhausdistinguishesbetweenvotingsharesandeconomicshares,
Distrib.LedgerTechnol.
20 • Jungnickeletal.
partiallydecouplinggovernanceinfluencefromfinancialinvestment.Thismeansthatindividualsinvestingfor
financialgaindonotnecessarilygainequivalentvotingrights.DAOstackfurthermitigatesthisissuebyassigning
votingpowerthroughnon-transferablereputationscores,whichcarrynomonetaryvalueandcannotbetraded,
therebyavoidingdirectalignmentbetweenfinancialincentivesandgovernanceinfluence.
Manytoken-basedDAOsusetheirgovernancetokenstorewardcontributors;theinitialallocationofthe
governancetokennormallyincludessignificantgrantstofounders,employeesandventurecapitalinvestors,
grantingthemadisproportionatelylargeandpersistentshareofgovernancepower[35][33]Forexample,40%of
theinitialsupplyoftheUniswapgovernancetokenwasdistributedinthismanner[62].TypicallyDAOcreators
arguethatthecentralizationtheyintroducedthroughtheinitialallocationwillnaturallydeclineovertimeasmore
membersjointhecommunity[62],buttheresultsofthedataanalysissuggestthattheGinicoefficientremains
stable throughout the DAO’s lifecycle. This is consistent with existing studies on inequality in token-based
governance[35][29].ThetemporalanalysisoftheNakamotocoefficientsrevealsnoconsistenttrendtowards
decentralizationacrosstoken-basedDAOs.WhileUniswap’scoefficientincreasesmodestlyfrom9to10,this
changeisnegligiblegiventheDAO’slargememberbase.Curve,ontheotherhand,initiallyrisesfrom13to
16butsubsequentlydropssharplyto1,indicatingamovetowardsgreatercentralization.dxDAOpresentsa
morestructuredpattern,withagradualstepwiseincreaseinitscoefficient,suggestingthatdecentralizationmay
beachievableundercertaingovernanceconditions.Thesefindingsimplythatdecentralizationdoesnotoccur
naturallyovertimeandmayevendeteriorateinsomecases.Jensenetal.[33]comparethecentralizationof
severaltoken-basedDAOs,someofwhichemployedafair-launchstrategyintendedtopreventanunequalinitial
distribution[33].Theyobservethatdespitesuchefforts,inequalitylevelsintheseDAOsrapidlyconvergedwith
thoseofmoretraditionallylaunchedprojects.Thissuggeststhatalthoughafairinitialallocationmaynotbe
sufficientforachievinglong-termdecentralization,itcouldstillbeanecessaryfoundation.
SinceDAOhausandDAOstackdonotusegovernancetokens,theyarelessvulnerable—butnotimmune—to
unequalinitialdistribution.DAOhausseparateseconomicandvotingshares,allowingfoundersandinvestors
toreceivefinancialrewardswithoutgainingexcessivegovernancepower.However,applyingthisseparation
dependsonthecommunity.Similarly,DAOstack’sreputationisintendedtobeearnedovertime,yetthisisnot
alwayspracticed.Forinstance,dxDAOgrantedinitialreputationbasedontokenholdings,possiblyexplainingits
notablyhigh
6.2 ImpactofCentralizationinTokenGovernance
ConsideringthatthehighlycentralisedprotocolDAOsincludedintheanalysisareverysuccessful–moreso
thananyDAOstackandDAOhausproject–thequestionarises,whydoesdecentralizationmatter?Itwillbe
arguedinthissectionthatthecentralizationofvotingpowerintokengovernanceraisesconcernsaboutsecurity
andminorityrights.TheseconcernsareespeciallypertinentfornewandsmallerDAOprojectsmeaningthey
deserveattentionirrespectiveofthesuccessofmajorprotocolDAOs.
6.2.1 SecurityRisks. Theabsenceofstrongprotectionsagainstcentralizationintoken-basedgovernancesystems
resultsinconsiderablesecurityrisks,whichhaveonlybeenpartiallymitigated.Token-basedgovernanceallows
individualswithsufficientresourcestopurchasevotingmajorities.Stroponiatietal.notethatthecostofacq uiring
amajoritysharemaysometimesbelowerthanthevalueoftokenstowhichthegovernancecontracthasaccess.
Atthetimeoftheirwriting,thecostofacquiringavotingmajorityinMakerDAOstoodat$44MandtheDAO
treasurywasvaluedat$2B[35].
Thecostofsuchanattackcanbefurtherreducedifgovernancetokensareborrowedinsteadofbought(e.g.
theBeanstalkHack[52]).Centralizationalsoincreasestheriskofbriberyandcollusion.Sincefewermembersare
requiredtoattainatokenmajority,fewerneedtobeconvincedtoparticipateinthescheme.
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 21
DAOshavetriedtomitigatetheseproblems,byincreasingthehurdlesformaliciousactorstoacquiresignificant
votingpower.Twomechanismshaveprovenparticularlypopular,butnoneareentirelysatisfactory:
TokenLocking Thisapproachrequiresmemberstolocktheirgovernancetokensintoanescrowaccountin
ordertoparticipateinvoting;whiletokensarelocked,thememberdoesnothaveaccesstothem.Forexample,
inCurveDAOmemberscancommittolockingtheirtokensforuptofouryearsandthelongertheperiod,the
largerthevotingpowertheyreceiveinreturn.Thismeansamalicioususerwouldhavetolockthegovernance
tokenforapotentiallylongperiodoftime,preventingtheuseofshort-termloans,suchasflashloans[66].While
thismechanismcertainlymakesitmoredifficulttoacquireamajority,itdidn’tpreventoneCurveDAOmember
fromtemporarilyholding71%ofvotingpower[10].Therearealsosmartcontractsthatcanhelpbypassthese
locks,allowingtheiruserstostilleffectivelytransferthelockedtokens[42].
ExecutionDelays TimedelaysafteraproposalhasbeenapprovedallowDAOmemberstoenactemergency
procedurestosecurethefundscontainedinthetreasuryifamaliciousactormanagestoacquireamajority.Maker
DAO,forexample,implementedthismechanismafterdiscoveringthesecurityriskdescribedabove[38].While
thepossibilityofashutdowncandeterattackers,aDAOshouldnotrelyonthethreatofitsowndestructionas
aprimarydefencemechanism;forexample,itmaynotwanttounwinditsentireoperationsduetoasmallor
medium-sizedattack.
Themainreasonmajortoken-basedDAOshavenotexperiencedmoresecuritybreachesislikelytheirsize
and popularity. Their size means the investment needed to acquire a majority is large, and their popularity
meansthatanyattackerwouldlikelyfaceconsiderablecountermeasuresandretribution.Theproblemsdescribed
are thus most pertinent for new and smaller DAOs in which the cost of acquiring a voting majority can be
significantlylower.Althoughthesolutionsadoptedbysometoken-basedDAOscertainlymitigatethesecurity
risks,agovernancemodelinwhichtheydonotariseinthefirstplacewouldbepreferable.
6.2.2 Minority Rights. Token-based DAOs exhibit similar degrees of voting inequality as traditional public
companies, yet offer none of the protections afforded to minority shareholders under corporate law. DAOs
have often been described as decentralized alternatives to traditional organizations, that avoid hierarchical
andundemocraticdecision-making[4][11][40][57].However,theNakamotocoefficientsofthethreelargest
companiesintheS&ParehigherthanthoseofallprotocolDAOsthatwereanalysedhere,meaningtheyaremore
decentralised.Whileafairlike-for-likecomparisonbetweenDAOsandtraditionalcompanieswouldrequirea
muchlargerdatasetandmoredetailedanalysis,theresultsindicatethattheprevalentassumptionthatDAOs
aredecentralisedalternativestotraditionalcompaniesisnotnecessarilytrue.Minorityshareholderrightswere
introducedasanantidotetothecentraliseddistributionofvotingpowerinmanypubliccompanies;unlessthey
becomemoredecentralised,DAOsshouldbeexpectedtodothesame.Minorityrightsareimportantbecausethe
interestsofgovernancetokenholdersarenotnecessarilyaligned[9];thereareclearexampleswithinexisting
DAOs,wherelargeshareholdersusedtheirvotingpowertoinfluencedecisionsthatservetheirowninterests[35].
6.3 LowParticipation
6.3.1 ProblemofLowParticipation. Theresultsoftheexploratorydataanalysisreveallowvoterengagement
across all governance models, including in off-chain voting. A minority of members participate actively in
decision-making,whilethevastmajorityrarelycastsavote.Severalpotentialreasonsforlowparticipationwill
beexploredinthissubsection,resultingintheconclusionthatDAOsshouldmovetowardsmorerepresentative
andlessdirectdemocracy.
Centralizedvotingpowerreducesengagementamonglessinfluentialmembers.Whilethisstudyfoundno
stronglinkbetweendecentralizationandparticipationlevels,priorresearchshowsthatmemberswithhigher
votingpowervotemorefrequently[29,56,6].Formemberswithlittleinfluence,thecostandeffortofparticipation
mayoutweighthebenefitsofafavourableoutcome.If𝑝 isthechanceavoteisdecisiveand𝐵isthebenefitfrom
Distrib.LedgerTechnol.
Chunk 2
22 • Jungnickeletal.
apositiveresult,theexpectedbenefitis𝑝×𝐵[9].Forsmallstakeholders,both𝑝 and𝐵arelow.Sincethecost𝑐
(e.g.,time,gasfees)isconstant,onlythoseforwhom𝑝×𝐵 >𝑐 willbemotivatedtoparticipate,regardlessofthe
collectivebenefit.On-chainvotinginvolvesgasfeesandmaybeburdensomedependingontheinterface,butthere
isnostrongevidencethatthisalonereducesvoterengagement.ToolslikeSnapshotwereintroducedtoeliminate
gascostsandsimplifyparticipation;however,theanalysisshowsthatSnapshotvotingalsosuffersfromlow
turnoutintheDAOsstudied.Thischallengestheassumptionthatcostisthemainbarrier.Supportingstudies[28,
26]foundnoclearlinkbetweengasfeesandparticipation,evenonlow-costchainslikexDAI.Thesefindings
shouldbeinterpretedcautiously:Snapshotvotesarenon-binding,possiblylimitingmotivationtovote;gasprice
studiesdidn’taccountforfiatexchangerates;andDAOsonmainnet—generallylargerandmoreactive—tendto
showhigherparticipationthansmallerxDAI-basedDAOs[48].
While the causes of low voter participation remain somewhat unclear, the data tentatively supports the
hypothesis that a combination of centralization and direct democracy—rather than cost—is the main driver.
Centralizationcanmakemembersfeeltheirvotehaslittleimpact,whilefrequentproposalsindirectdemocracy
increasetheeffortrequiredtostayengagedbeyondtheperceivedbenefit.Thenextsectiondiscussestheimpact
oflowvoterengagement.
6.3.2 ImpactofLowParticipation. LowvoterparticipationincreasessecurityrisksinDAOs,underminesminority
representation,andchallengesthecorerationalefordecentralization.TheNakamotocoefficientwasusedto
illustratehowfewmembersareneededforabsolutemajoritycontrol;however,duetolowquorumthresholdsand
relianceonsimplemajorities,farfewerparticipantscandetermineoutcomes.Forexample,inUniswap,just7.5%
ofgovernancetokenscoulddecideallproposals[29].Whileexplicitattacksmightmobilisevoters,aconcealedor
self-interestedactoroftenneedsfarlessthananabsolutemajority—makinglowparticipationakeyenablerof
centralizationrisks.
Sincelowparticipationisnotequallydistributedacrossusersbutmoreprevalentinlesspowerfulmembers
[29],itdecreasestheextenttowhichtheinterestsofminorityshareholdersarerepresented.Buterinnotesthat
alargenumberofsmallshareholderswillfindithardertoorganizethemselvestoadequatelyrepresenttheir
interestingovernancethanasmallnumberoflargeshareholders[9].Lowparticipationreducestheprotectionof
minorityinterests,whicharealreadylargelyunprotected.
Finally, decentralization is intended to democratize decision-making, but if participation is very low, the
benefitsofdemocratisationarenotfullyrealised.However,thedisadvantagesofdemocraticdecision-making,
suchasthedelayintroducedbyvotingperiodsarepresentirrespectiveofthedegreeofparticipation.
6.4 Controversy
6.4.1 ProblemofLowControversy. Theanalysisshowedthatmostproposalshadlargemajoritiesandlowturnout
acrossallgovernancemodels,indicatinglowcontroversy.Snapshotexhibitedslightlyhighercontroversy,possibly
becausemajorDAOsuseittogaugesentimentbeforeon-chainvoting.Ifamajorityisclearoff-chain,opponents
maychoosenottovoteon-chaintoavoidgascosts.However,thisremainsspeculativeandwarrantsfurther
investigation.
Theanalysisalsorevealedthatthemajorityofvotesarealmostalwayscastinfavourofthesameou tcome
asthemajorityofvotingweight;inotherwords,ifeachvoterhadbeenweightedequallytheoutcomewould
haverarelydiffered.Whilethisprimafaciesupportsthehypothesisthatvotingisgenerallyuncontroversial,the
existenceofcontroversymaybeconcealedduetothehighdegreeofcentralizationinvotingpower.Ifalarge
majorityofvotingweightiscastinfavourofanoutcome,memberswithlittlevotingpowermaynotvoteagainst
it,asitwouldhavelittleimpact.Thiscangivethefalseimpressionthatnotjustthemajorityofweightbutalso
themajorityofvotersfavouranoutcome.Theextenttowhichtheseconcernsarevalidrequiresfurtheranalysis.
Distrib.LedgerTechnol.
DAOGovernance:VotingPower,Participation,andControversy-AReviewandanEmpiricalAnalysis • 23
6.4.2 ImpactofLowControversy. Votingonuncontroversialproposalsiscostlyandinefficientbecauseeachvoter
paysgasfeesandthefullvotingperiodneedstoelapseuntiltheproposalcanbeexecuted.Thecostanddelay
ofcollectivedecision-makingcanreducethescalabilityandisparticularlyproblematicfornewDAOsintheir
growthphase,wheredecisionfrequencycanbehigh.Moreover,frequentuncontroversialdecision-makingcan
causevoterfatigueandfacilitatelowparticipation;ifvotersareconstantlyconfrontedwithsmall,uncontroversial
decisions,theymayhavelesstimeandpatiencewhenmoreimportantproposalsarise.
7 CONCLUSION
7.1 SummaryofAchievements
ThispaperaimedtoanalyseDAOgovernancebehaviorsthroughareviewofexistingliteratureandexploratory
dataanalysis.Bycomparingdifferentgovernancemodels—bothonandoff-chain—thestudyhighlightedkey
issuessuchascentralization,lowengagement,andlimitedcontroversy.Theseinsightsareintendedtoinformthe
developmentofimprovedDAOgovernancedesigns.
7.2 Limitations
Thischapterpresentsanexploratoryquantitativeanalysiswithoutformalstatisticalvalidation,anditsconclusions
shouldbeinterpretedcautiously.Thefindingsofferhypothesesratherthandefinitiveclaimsaboutgovernance
behavior.Thescopewaslimitedbydataavailability,andonlyasubsetofmetricsandDAOs—particularlyfor
token-basedgovernance—couldbeincluded.Insomecases,onlyafewDAOswereanalyzedpergovernance
dimension.Despitetheselimitations,theresultsprovidevaluableinsightstoinformthedesignoffutureDAO
prototypes.
7.3 FutureWork
Future work should seek to validate the results of the exploratory data analysis through formal statistical
hypothesistesting.ItshouldalsoconsideradditionaldimensionsofDAOgovernancethatwereleftunexplored,
suchassmall-groupgovernancebehavior.Finally,thedatausedwaslimitedbothinsamplesizeandquality;
moreDAOsandvariationsongovernancemodelsneedtobereviewed.
Inaddition,complementaryapproachesbeyondtoken-distributionmetricscouldbeconsidered.Forinstance,
recent work by Fábrega et al. [25] introduces Voting-Bloc Entropy (VBE), a framework that assesses DAO
decentralizationbymodelingvotingblocsandalignedparticipantbehaviors.Likewise,Sharmaetal.[51]illustrate
howadvancedvisualizationandclusteringtechniquesappliedtoselectedDAOscanrevealfurtherdynamicsof
decentralization.Extendingourworktoincorporatesuchbehavior-orientedmetricsandvisualizationmethods
remainsanimportantavenueforfutureresearch.
ACKNOWLEDGEMENTS
ResearchsupportedbyBrevanHowardCentreforFinancialAnalysis.
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Received26January2025;revised24September2025;accepted20October2025
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