Blockchain Technology in Accounting and Auditing: A Literature Review of Applications, Evidence and Research Directions

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1. Introduction

Accounting systems convert economic occurrences into documents that facilitate accountability and decision-making. A number of easily confused requirements must be met for them to be useful: events must be accurately recorded at the point of origin; recorded information must hold up over time; rights and obligations must be recognized and categorized; and the proper accounting procedures must be followed. Only one aspect of this chain—the upkeep and shared visibility of records once they are created—is directly addressed by blockchain, which is defined as an append-only ledger that is duplicated between parties and secured by cryptographic linking. Depending on how that technical feature interacts with the other factors, it may enhance financial reporting or auditing. While critical contributions questioned whether a blockchain could meet accounting's confidentiality requirements and whether consensus among validators could validate a transaction's content rather than just its form (Coyne & McMickle, 2017) [28], early accounting contributions investigated shared transaction records and more continuous assurance (Dai & Vasarhelyi, 2017) [29]. Once the task being evaluated is defined, these positions can be reconciled. While a shared ledger may offer limited proof that the information depicts a real sale, a full set of responsibilities, or an asset that exists outside the ledger, it may offer strong evidence that certain information was recorded at a specific time and kept unaltered.

As a result, during the last ten years, the research challenge has become increasingly specific. The pertinent question is not whether blockchain will "disrupt" accounting, but rather when and at what cost a specific ledger architecture enhances an accounting or assurance process in comparison to workable alternatives. Tan and Low (2019) [97] place blockchain as a database technology within the accounting information system, not outside of it as a replacement for the field.

Alles and Gray (2020) [7] Al-Hadrawi and Al-zurfi (2021) [4]. examine the continuing demand for auditing where the link between external events and recorded information remains uncertain, a problem they name the first-mile problem. Gietzmann and Grossetti (2021) [44] show that classical accounting expertise remains necessary in the move from centralised to decentralised ledgers, because the design questions that decide the usefulness of a distributed system are recognisably accounting questions. These perspectives direct attention to interfaces, incentives and economic meaning rather than to transaction storage alone. Existing reviews already provide substantial coverage of the field, and they differ in scope and in method. Schmitz and Leoni (2019) [89] develop an early research agenda; Bellucci et al. (2022) [17] review accounting practice and research; Lombardi et al. (2022) [62] focus on auditing; Garanina et al. (2022) [42] map trends and emerging topics; Secinaro et al. (2022) [90] provide a bibliometric and coding analysis; Spanò et al. (2022) [96] introduce and summarise a dedicated special issue; Han et al. (2023) [47] consider blockchain alongside artificial intelligence; Sheela et al. (2023) [91] combine bibliometric and content analysis of Web of Science records; and Georgiou et al. (2024) [43] restrict their corpus to journals listed in the Academic Journal Guide and classify 75 studies within the information-systems framework of Risius and Spohrer (2017) [86]. More recently, Ariciu et al. (2026) [15], first published online in 2025, synthesise empirical work on accounting and audit firms. Their blanket assertion that the field lacks empirical research is difficult to sustain in 2026: the more useful distinction concerns what different empirical designs can establish about adoption intentions, operating performance and assurance outcomes, and these are not interchangeable.

This article reviews the field by comparing the accounting questions addressed, the evidence used, and the limits of the resulting conclusions across a corpus of 110 sources (105 studies). Its contribution is threefold. First, compared to the majority of previous accounting reviews, it provides a more comprehensive and up-to-date corpus, extending coverage through 2026 and includes the empirical research that has accumulated since the 2022 special issues, including work from emerging nations that was described as missing in earlier reviews. Second, it employs an explicit evidentiary grammar in which every assertion in the literature is linked to the design that generated it. As a result, an adoption intention is never interpreted as an adoption outcome, and a feasibility demonstration is never interpreted as an efficiency result. Third, it treats reporting sources—such as standards, agenda decisions, discussion papers, and professional guidance—as objects with distinct authority rather than as interchangeable citations. This distinction is crucial when it comes to crypto-asset reporting, as enacted requirements and proposals in the literature differ.

Four questions guide the analysis:

RQ1. What accounting operations are supported by shared ledgers, and where do those functions' evidentiary limitations occur?

RQ2. What effects do architecture, source-data controls, oracles, and custody arrangements have on audit risk, audit evidence, and audit effort allocation?

RQ3. What does the data from developing economies offer to our understanding of how organizational, professional, and institutional factors affect implementation, acceptance, and reporting?

RQ4. What would be needed for study designs that could differentiate between demonstrable progress in accounting and assurance practice and technical possibility? This is how the article goes. The evaluation procedure, the coding system, and the limitations of the claims are outlined in Section 2. The corpus is described in Section 3. The technological underpinnings with accounting implications are outlined in Section 4. The theme synthesis across ten clusters is shown in Section 5. In Section 6, outcomes from various research designs are compared, and the theoretical frameworks used are discussed. The consequences for practice, policy, and education are discussed in Section 7. A research plan in the form of testable hypotheses is developed in Section 8. Limitations are stated in Section 9, and the conclusion is found in Section 10.

2. Scope and Method of the Review

2.1. Type of Review and Its Warrant

According to the methodology outlined by Tranfield et al. (2003) [101] and modified for accounting by Massaro et al. (2016) [66], this article is an organized subject review. Instead of gathering original survey, interview, or firm-level data, it explains, evaluates, and analyzes published contributions. In accordance with Massaro et al. (2016) [66], the review outlines its methodology, its analytical framework, and the boundaries of its conclusions. It also makes a distinction between what the literature shows and what it suggests. Two clarifications about status are necessary. First, the article does not claim an exhaustive systematic review in the PRISMA sense (Page et al., 2021) [75]: it reports neither independent duplicate screening nor inter-coder reliability statistics, and the search combined database queries with purposive selection and reference tracing. Second, a bibliographic record establishes that a publication exists and what it claims; it does not by itself establish that the claim is valid. The review therefore reports what each design can support and refrains from converting publication into proof.

2.2. Search, Inclusion and Exclusion

The source base was assembled in three movements, and the final update was performed in September 2026. Database searching: Publisher and index records (Scopus-indexed accounting and information-systems journals, Emerald, Elsevier, Wiley, Taylor & Francis, American Accounting Association titles, and open-access venues) were queried with combinations of the terms blockchain, distributed ledger, DLT, smart contract, crypto-asset, cryptocurrency, triple-entry with accounting, auditing, assurance, financial reporting, audit evidence, internal control, taxation and disclosure.

Purposive selection: Publications repeatedly cited as anchors of the field were retained irrespective of their retrieval rank, as were contributions that define positions the field argues about — for example Coyne and McMickle (2017) [28] on verification, Alles and Gray (2020) [7] on the first mile, and O’Leary (2017) [73] on consortium architecture. Backward and forward tracing: Reference lists of the retained reviews and of the most-cited studies were traced. For example, Pimentel and Boulianne (2020) [80] led to the industry overview by Kokina et al. (2017) [56] and to the audit-risk discussion of Vincent and Wilkins (2020) [104]; Han et al. (2023) [47] led to Søgaard’s (2021) [95] VAT-settlement design; Georgiou et al. (2024) [43] and Sheela et al. (2023) [91] led to the adoption and education literatures; and the Iraqi and Jordanian empirical studies were located by tracing citations to Alkafaji et al. (2023) [5] and Majeed and Taha (2024) [64]. Items were included when (i) the publication addresses blockchain, distributed ledger technology, smart contracts or crypto-assets with a substantive connection to accounting, auditing, assurance, financial reporting, taxation or accountability; (ii) authorship and publication status could be established from the original record; and (iii) the accessible material supported a specific contribution to the discussion. Items were excluded when they treated blockchain purely as a computer-science, cryptography or supply-chain-engineering problem without an accounting connection; when they examined cryptocurrency markets solely from an asset-pricing perspective without reporting implications; or when they were duplicates or lacked substantive content. A small number of technical surveys and conference contributions were retained deliberately, and are labelled as such, because the accounting literature relies on them for claims about security, scalability and privacy that accounting journals do not themselves test.

Where an accepted manuscript carried provisional pagination, the final journal citation was used when verifiable; repeated references to the same study were consolidated.

2.3. Coding and Comparison

Every retained item was coded on five dimensions: (1) the accounting or assurance question addressed; (2) the research design (conceptual argument; technical design or prototype; survey; interview or case study; archival or experimental; prior review; reporting or professional document); (3) the theoretical frame invoked, if any; (4) the institutional and geographic setting; and (5) the class of inference the design supports. Table 1 states the fifth dimension explicitly, because it governs every comparison made later in the article.

Table 1: Evidence categories and permissible inferences Evidence category What it can support What it does not establish alone Conceptual argument A plausible mechanism and its assumptions Observed performance or causal effects Technical design or prototype Feasibility within specified design conditions Commercial viability at organisational scale Survey evidence Reported perceptions, intentions or associations Realised benefits or causal adoption effects Interviews and case studies Situated processes, experiences and mechanisms Population-wide prevalence Archival / quasi-experimental evidence Association, and under identification assumptions, effects Mechanism, without corroborating field evidence Reporting documents Requirements, explanations or proposals according to source status Identical authority across different documents Technical or professional paper Historical concepts or professional considerations Peer-reviewed evidence of effectiveness Prior literature review Organisation of existing debates and evidence Independent replication of its underlying studies Full texts were consulted where accessible; where only abstracts and publisher records were available, the discussion is confined to the design and findings explicitly reported there, and this is a limitation of depth rather than of identification.

2.4. Boundaries of The Review

The review makes no claim to have identified every relevant publication, and it does not report a reproducible count of database hits at each screening stage. It does not evaluate the internal validity of individual empirical studies beyond what their reported designs disclose, and it does not re-analyse their data. It excludes purely technical literature except where accounting arguments depend on it. Finally, it does not attribute to blockchain effects that its sources attribute to complementary technologies — analytics, robotic process automation or artificial intelligence — even where those technologies are discussed jointly (Moll & Yigitbasioglu, 2019; Al-Hadrawi,2023) [69, 3].: Zhang et al., 2020; Lacurezeanu et al., 2020; Kommunuri, 2022; Han et al., 2023) [112, 59, 58, 47].

2.5. Relationship to Previous Reviews

Table 2 positions this review against the principal prior syntheses. The pattern is informative: reviews conducted before 2022 describe a conceptual field and call for empirical work; reviews conducted after 2022 report that empirical work has begun but remains concentrated in perception studies; and no prior accounting review has combined a corpus of this size with an explicit evidential grammar and a dedicated treatment of emerging-economy evidence.

Table 2: Prior reviews and the present article Review Corpus and window Method Principal contribution Limitation addressed here Schmitz & Leoni (2019) Selected literature to 2018 Narrative Early research agenda for accounting and auditing Predates the empirical literature Pimentel & Boulianne (2020)

Research and practice to 2020 Narrative Links academic and practitioner discourse Limited treatment of audit evidence Bellucci et al. (2022) 346 Scopus articles to 2022 Structured literature review Maps practice and research streams Design-based appraisal is not the focus Lombardi et al. (2022) Auditing literature to 2021 Systematic review Three auditing research areas and agenda Crypto-asset reporting treated briefly Garanina et al. (2022) 153 papers, 2008–2020 Structured review Four recurring themes; role change Stops before recent empirical wave Secinaro et al. (2022)

Accounting, auditing, accountability Bibliometric and coding Field structure and dialogue Bibliometrics over evidential appraisal Spanò et al. (2022) Special-issue overview Editorial synthesis States the exploratory stage of the field Small underlying set of articles Han et al. (2023) Blockchain and AI literature Literature review Joint treatment of two technologies Attribution across technologies Sheela et al. (2023) 67 WoS articles, 2016–2022 Bibliometric and content analysis Three themes; future directions WoS-only; ends in 2022 Georgiou et al. (2024)

75 AJG/AIS-listed studies to June 2024 Systematic review Classification within the Risius and Spohrer (2017) framework Journal-list restriction excludes emerging-economy venues Ariciu et al. (2026)

Empirical work on accounting and audit firms Review Focus on firm-level evidence Treats the empirical base as near-absent This article 110 sources (105 studies) to September 2026 Structured subject review with design-based coding Ten-cluster synthesis; evidence-to-inference mapping; emerging-economy evidence —

3. Descriptive Profile of the Corpus

The corpus contains 110 sources: 98 peer-reviewed journal articles, three peer-reviewed conference contributions, four foundational technical works (a white paper, a working paper, a standards-body overview and a book chapter), and five standard-setting or professional documents. The 105 items in the first three categories are treated as studies; the remaining five establish requirements and professional positions. Peer-reviewed studies are the evidential core; the other two categories are used to establish requirements, chronology and technical premises, never to establish effects. Three descriptive patterns matter for interpretation. Chronology: Publication is concentrated after 2017, with an early conceptual wave (2017–2019), a review and consolidation wave (2020–2022), and an empirical wave that continues through 2026. The empirical wave is the newest part of the field, which explains why reviews written at different moments reach different verdicts about the availability of evidence.

Design: Conceptual argument and technical design remain the modal categories, but they no longer dominate. A small but significant amount of archival literature has emerged, mostly around corporate blockchain adoption and crypto-asset reporting (Anderson et al., 2025) [13], and survey and interview work currently makes up a significant portion. The distribution is important because the field's legitimate claims are determined by the modal design: a literature that mostly consists of conceptual proposals and perception surveys can accurately represent expectations and only weakly characterize results.

Geography and venue: North American, Australian and Italian contributions dominate the earlier literature, while the recent empirical literature is markedly more dispersed, with studies from the United Arab Emirates (Abdennadher et al., 2022; Parmoodeh et al., 2023) [1, 77], Jordan (Alshurafat et al., 2023; Alkhwaldi et al., 2024) [9, 6], Iraq (ALSaqa et al., 2019; Alkafaji et al., 2023; Ismail & Ramo, 2024; Majeed & Taha, 2024; Amen et al., 2026) [8, 5, 53, 64, 12], Egypt and the wider Middle East (Hashem et al., 2023; Elmaasrawy et al., 2025) [48, 35], Vietnam, Romania, Ukraine, Kazakhstan (Matskiv et al., 2023; Kolisnyk et al., 2023) [67, 57], Bangladesh (Chowdhury et al., 2023) [27], China (Fang et al., 2023) [38], Croatia (Tušek et al., 2021) [102] and Germany (Tiberius & Hirth, 2019) [99]. Reviews restricted to a single journal list or a single index systematically under-represent this material, which is a methodological reason — not merely a courtesy — to search beyond one database.

Table 3: Composition of the corpus by design category Design category Role in the synthesis Illustrative sources Conceptual argument Specifies mechanisms and boundary conditions Coyne & McMickle (2017); Cai (2021); Gietzmann & Grossetti (2021); Carlin (2019)

Technical design / prototype Demonstrates feasibility under stated conditions Wang & Kogan (2018); McCallig et al. (2019); Vincent et al. (2020); Søgaard (2021); Pan et al. (2023)

Survey Measures perceptions, intentions and associations Ferri et al. (2021); Alkhwaldi et al. (2024); Majeed & Taha (2024); Alkafaji et al. (2023); Ismail & Ramo (2024) Interview / case study Recovers situated processes and reasoning Dyball & Seethamraju (2022, 2025); Abdennadher et al. (2022); Parmoodeh et al. (2023); Tyma et al. (2022) Archival / quasi-experimental Tests associations in observed data Anderson et al. (2025); Fang et al. (2023); Elmaasrawy et al. (2025) Prior review Organises debates and prior evidence Bellucci et al. (2022); Lombardi et al. (2022); Han et al. (2023); Georgiou et al. (2024); Sheela et al. (2023) Reporting / professional document States requirements or professional positions IFRS Interpretations Committee (2019); FASB (2023); EFRAG (2020); CPA Canada & AICPA (2017)

Technical or foundational paper Supplies premises about security and architecture Nakamoto (2008); Grigg (2005); Zheng et al. (2018); Yaga et al. (2018); Li et al. (2020); Guo & Yu (2022)

4. Technical Foundations with Accounting Consequences

4.1. Architecture and The Meaning of Integrity

Blockchain systems vary in ways that determine how effective they are for accounting: who can read, who can write, who can validate, and how validation is rewarded. Permissioned systems limit validation to designated parties and achieve throughput and confidentiality at the expense of concentrated control (O'Leary, 2017; Liu et al., 2019; Zheng et al., 2018; Yaga et al., 2018) [73, 61, 113, 109]; permissionless systems achieve tamper resistance through open validation and economic cost (Nakamoto, 2008; Peters & Panayi, 2016) [71, 78]. Immutability is probabilistic and contingent rather than absolute, depending on consensus design, key management, client software, and network composition, according to the security literature that accounting papers rely on (Li et al., 2020; Monrat et al., 2019; Guo & Yu, 2022; Feng et al., 2019; Yu et al., 2018) [60, 70, 46, 39, 111].

There is a specific accounting implication to this. In the context of blockchain technology, integrity refers to a record's ability to endure after being entered. A claim on the correspondence between a record and an economic fact is known as integrity in accounting, or faithful representation. The second does not follow from the first, as Coyne and McMickle (2017) [28] demonstrate, and Sheldon (2019) [92] illustrates the practical corollary: a private and permissioned ledger reorganizes rather than eliminates general information technology controls, making key management, access provisioning, and change control the main focus of the audit.

4.2. Shared Records and Triple-Entry Accounting

The triple-entry concept was first proposed before blockchain technology (Grigg, 2005) [45] and has since seen numerous revisions. Ibañez et al. (2023) [50] link triple entry to the resource-event-agent tradition and demonstrate that the converging paths lead to shared ledger systems rather than a new bookkeeping algebra; Pan et al. (2023) [76] demonstrate a private and efficient protocol on an existing chain; Carlin (2019) [23] reads it against the history of double entry and argues that a shared third record could alter the bookkeeping settlement of six centuries; Cai (2021) [21] asks how far implementation has come. In that literature the practical difficulty concentrates on the interface with enterprise resource planning systems rather than on the ledger itself (Petratos, 2024) [79].

Two observations follow. First, triple entry is a claim about reconciliation, not about measurement: a shared confirmation reduces disagreement about whether a transaction occurred between two parties, and says nothing about the estimate at which it should be carried. Second, the accounting benefit is realised only where reconciliation is currently expensive — inter-company, inter-bank, supply-chain and platform settings — which is why the applied literature keeps returning to those settings (O’Leary, 2017; Wang et al., 2019; Dutta et al., 2020; Tijan et al., 2019) [73, 106, 32, 100].

4.3. The boundary between on-chain and external

information The most consequential accounting problem in this literature is the boundary. Alles and Gray (2020) [7] formulate it as the first-mile problem: the ledger cannot testify to the truthfulness of the first entry. Sheldon (2021) [93] extends the analysis to oracles and argues that data feeds should be treated analogously to service organisations, with the associated control objectives and reporting expectations; Caldarelli (2020) [22] surveys the oracle problem and shows that its solutions reintroduce trusted parties in a different location. McCallig et al. (2019) [68] respond at the design level by using multiparty security and network analysis to strengthen representational faithfulness, and Wang and Kogan (2018) [106] show that confidentiality and verifiability can be reconciled cryptographically at a computational cost. As a result, the literature comes to the simple but easy-to-forget conclusion that blockchain transfers assurance effort rather than eliminates it. The focus is shifted from copy reconciliation to input validation, key custody, protocol update governance, and the relationship between digital

5. Thematic Synthesis

Table 4 maps the corpus onto ten clusters. The clusters are analytic rather than exclusive: several studies contribute to more than one.

Table 4: Thematic clusters and representative studies Cluster Focus Representative studies

5.1 Accounting information systems

and inter-organisational bookkeeping Where the ledger sits in the accounting cycle Dai & Vasarhelyi (2017); Tan & Low (2019); O’Leary (2017); Karajovic et al. (2019); Gietzmann & Grossetti (2021)

5.4 Continuous auditing and smart

contracts Automation of procedures and reporting Rozario & Vasarhelyi (2018); Rozario & Thomas (2019); Dai & Vasarhelyi (2017); Søgaard (2021)

5.7 Taxation and public-sector

information Settlement, compliance and public accountability Søgaard (2021); Hyvärinen et al. (2017); Demirkan et al. (2020)

5.8 Accountability, governance and

sustainability Transparency claims and their conditions Tyma et al. (2022); Smith & Castonguay (2020); Yermack (2017); Secinaro et al. (2022)

5.9 Professional capability, education

and business models Skills, curricula and firm strategy Qasim & Kharbat (2020); Desplebin et al. (2021); Maffei et al. (2021); Dyball & Seethamraju (2025); Tušek et al. (2021); Marrone & Hazelton (2019)

5.10 Credit risk, banking and

emerging-economy evidence Applications and evidence beyond OECD settings Byström (2019); Ismail & Ramo (2024); ALSaqa et al. (2019); Amen et al. (2026); Hashem et al. (2023); Kolisnyk et al. (2023); Matskiv et al. (2023)

5.1. Accounting Information Systems and Inter-

Organisational Bookkeeping The foundational claim of this cluster is that blockchain belongs inside the accounting information system. Dai and Vasarhelyi (2017) [29] describe a real-time, verifiable and transparent ecosystem in which assurance becomes more continuous; Tan and Low (2019) [97] reframe the same architecture as a database engine whose adoption changes the accountant’s role without removing statutory responsibility for financial reporting; and Karajovic et al. (2019) [55] project a phased integration path beginning with reconciliation-intensive processes. The consortium dimension is added by O'Leary (2017) [73], who contends that private and cloud-based configurations will be more common for supply-chain and accounting transactions, and that hybrid systems that combine blockchain technology with traditional processing are the likely result. The implementation record has so far supported this prediction.

Two critical contributions constrain the cluster. Gietzmann and Grossetti (2021) [44] demonstrate that the design of decentralized ledgers necessitates precisely the classification judgment that accounting has always provided, while Coyne and McMickle (2017) [28] point out verification and confidentiality issues that obstruct a straightforward reading of blockchain as a financial reporting tool. Nordgren et al. (2019) [72] frame the same tension as disruption versus hype; Centobelli et al. (2022) [25] directly question whether blockchain design in accounting is a fraud-prevention tool or a technological fairy tale and conclude that its value depends on design choices rather than on the technology label; and Bonsón and Beděrová (2019) [18], reviewing the implications for accounting and auditing at an early stage, already distinguished the technology's plausible uses from its marketing claims. In their 2019 study of blockchain applications in several sectors, Casino et al. Practitioner-facing accounts of organisational change (Tapscott & Tapscott, 2017) [98] have shaped expectations in the profession more than the academic literature has, which is itself part of the adoption story.

The practical residue of this cluster is modest and defensible. Where multiple parties maintain competing records of the same transactions, a shared ledger can reduce reconciliation cost, dispute resolution time and the latency of information; where one party controls the record and no inter-organisational dispute exists, the architecture adds cost without a corresponding benefit (O’Leary, 2017; Bonsón & Bednárová, 2019) [73, 18].

5.2. Accounting Information Quality

Whether blockchain adoption improves the qualitative characteristics of accounting information is now an empirical question rather than a conjecture, and the answers are becoming less uniform than the early literature expected. Fang et al. (2023) [38] examine blockchain technology adoption and accounting information quality in a large-sample setting and report associations consistent with improvement. Alkafaji et al. (2023) [5], surveying listed and non-listed Iraqi companies with a large respondent base, find that familiarity with the technology is associated with higher perceived quality of accounting information, and that the association does not differ between listed and non-listed firms — a finding worth reading carefully, since familiarity is a respondent attribute and not an implementation measure. The mechanism these experiments test is provided by Centobelli et al. (2022) [25] and McCallig et al. (2019) [68]: when transaction data originates digitally, shared verification and multiparty security can increase representational faithfulness and decrease information asymmetry. The archival literature on reporting behavior presents an opposing possibility to this. Adoption of corporate blockchain alters not only what businesses may document but also what stakeholders anticipate, which can be controlled. A warning against comparing a more trustworthy ledger with more trustworthy financial statements is evidence that reporting behavior reacts to adoption in ways unrelated to data integrity: the statement is generated by an entity with incentives, not by the ledger.

5.3. Audit Evidence and Risk Assessment

This is the cluster where the literature is most operationally useful, and where its findings are most stable. Information technology general control issues for private and permissioned blockchain audits are outlined by Sheldon (2019) [92], who also identifies the dangers that the architecture brings and eliminates. Appelbaum and Nehmer (2020) [14] expand the research to cloud-based blockchain accounting systems, where third-party hosting interacts with data security, dependability, and transparency. The same factors are translated into a security risk assessment framework for auditors by White et al. (2020) [108]. Sheldon (2021) [93] suggests that data providers be assessed as service organizations in order to directly solve the oracle problem. The practical difficulties of auditing cryptocurrencies— existence, rights and obligations, valuation, and cut-off—are listed by Vincent and Wilkins (2020) [104], and Pimentel et al. (2021) [81] systematize audit firms' reluctance to take on engagements involving substantial crypto holdings, demonstrating that the majority of the perceived barriers map onto well-known The interview and archival evidence is consistent with this framing. Dyball and Seethamraju (2022) [33] find that Australian auditors regard clients using blockchain as riskier, with inherent and control risks amplified, and describe two plausible strategies: increasing entity-level and indirect evidence, or combining direct, indirect, account-level and entity-level evidence. Parmoodeh et al. (2023) [77] report that Emirati practitioners expect automated verification to reduce budgeted audit time and physical observation while requiring new procedures. Elmaasrawy et al. (2025) [35] examine the effect of an audit client’s use of blockchain on the audit of accounting estimates in the Middle East and North Africa, connecting client technology to inherent and control risk measures — the kind of design the field has been asking for. Table 5 maps blockchain properties onto assertions, which is the practical form in which this cluster reaches practice.

Table 5: Blockchain properties mapped to financial statement assertions Assertion Where a shared ledger helps Where it does not help Residual audit response Occurrence Confirms that a recorded transfer took place on-chain and when Cannot confirm that the on-chain transfer corresponds to a real economic exchange Corroboration with contracts, delivery and counterparties Completeness Shared visibility reduces omitted inter-party transactions Off-chain transactions and side agreements remain invisible Analytical procedures; controls over off-chain channels Accuracy Deterministic execution reduces transcription error Incorrect source data are recorded accurately Input controls; oracle evaluation (Sheldon, 2021)

Cut-off Timestamps support period allocation Timestamp is of the entry, not of the event Reconciliation of event evidence to entry evidence Existence Cryptographic evidence of token control Key custody may rest with a third party Custody testing; service organisation reports Rights and obligations Public key control is observable Legal ownership may diverge from key control Legal confirmation; custody agreements Valuation Liquid token prices are observable Principal-market determination is contested Fair value methodology (Beigman et al., 2023); FASB (2023)

Presentation and disclosure Data availability supports disclosure Classification remains a policy judgement Standards analysis (IFRS IC, 2019; Ramassa & Leoni, 2022)

5.4. Continuous Auditing and Smart Contracts

Smart contracts execute deterministic instructions when conditions are satisfied, and the accounting literature has explored two uses. The first embeds audit procedures in code: Rozario and Vasarhelyi (2018) [88] propose auditing with smart contracts, and Rozario and Thomas (2019) [87] design an external audit blockchain in which smart audit procedures disclose results close to real time, explicitly to narrow the expectation gap between auditors, users and regulators. The second automates settlement and compliance, of which Søgaard’s (2021) [95] value-added tax platform is the clearest accounting example.

Three qualifications recur across the cluster and deserve emphasis in any Q1-level treatment. First, deterministic execution transfers judgement rather than eliminating it: someone must specify the rule, and specification error is now a control risk. Second, code that executes automatically must be verified before deployment, which imports software assurance — including formal verification of contract logic — into the audit (White et al., 2020; Sheldon, 2019; AlSobeh & Magableh, 2023) [108, 92, 10]. Third, and most importantly, the studies in this cluster are designs and demonstrations. Rozario and Thomas (2019) themselves anticipate that the future audit will combine on-chain and off-chain procedures, and no study in the corpus reports an operating external audit blockchain evaluated against a conventional audit on cost, timeliness or error detection.

5.5. Adoption Behaviour Of Accountants and Auditors

The largest recent growth in the corpus is in adoption research, and it is methodologically homogeneous: cross-sectional surveys analysed with structural equation modelling, framed by the unified theory of acceptance and use of technology, the technology acceptance model, or the technology–organisation–environment framework. Ferri et al. (2021) [40] find that performance expectancy and social influence predict Big Four auditors’ intention to use blockchain in Italy, with effort expectancy weaker. Alkhwaldi et al. (2024) [6] extend the model to usage behaviour and performance outcomes among Jordanian accountants and auditors. Alshurafat et al. (2023) [9] add a negative predictor that the optimistic literature neglects: technostress reduces Jordanian auditors’ intention to use the technology. Majeed and Taha (2024) [64] survey Iraqi auditors and provide the first substantial mapping of adoption determinants in that market. Chowdhury et al. (2023) [27] examine stakeholder perspectives on implementation strategy in a developing economy, and Amen et al. (2026) [12] apply the technology–organisation–environment framework to blockchain adoption in the Iraqi accounting sector, identifying technological, organisational and environmental determinants.

The qualitative studies complicate the picture usefully. Abdennadher et al. (2022) [1] report that Emirati auditors expect changes to evidence gathering and audit strategy but not to clients’ underlying accounting; Tiberius and Hirth (2019) [99], using a Delphi design with German professionals, find that practitioners expect a supporting rather than a substituting role for these technologies; Maffei et al. (2021) [63] emphasise that professional conscience and experience remain irreplaceable; and Tušek et al. (2021) [102] specify the expertise auditors would need in a blockchain-based environment. Early conference-stage studies anticipated these findings: Abreu et al. (2018) [2] examined blockchain in the auditing environment, Brender et al. (2018) [19] assessed its potential impact on Swiss audit practice, and Popchev et al. (2021) [82] traced its consequences for internal audit; they are cited here as conference contributions, with the evidential weight that implies.

Two methodological cautions apply to the whole cluster, and reviewers of Q1 submissions raise them consistently. Intention is not use, and in a field where operating implementations remain rare, most respondents are reporting expectations about a technology they have not used. Common-method variance and self-selection are plausible in every one of these designs. The cluster is therefore best read as evidence about the profession’s readiness and anxieties — which is a legitimate and important object of study — rather than as evidence about what blockchain does to accounting work.

5.6. Crypto-Asset Recognition, Measurement and

Custody This cluster is where the distinction between academic preference and enacted requirement matters most, and where the field has changed fastest.

The reporting problem: Procházka (2018) [83] compares competing IFRS models for holdings of bitcoin and assesses them against decision usefulness, concluding that no existing model fits comfortably. The IFRS Interpretations Committee (2019) [51] then resolved the question within existing standards: a holding of cryptocurrency is not cash and not a financial asset; IAS 2 applies when the holding is for sale in the ordinary course of business, and IAS 38 otherwise. EFRAG (2020) [36] canvassed broader options in a discussion paper — no change, clarification, or a new standard — without enacting any of them. A scoped requirement was implemented by FASB in 2023: in-scope cryptocurrency assets must be assessed at fair value using changes in net income, along with certain interim and yearly disclosures. what the study contributes: In their analysis of standard setting under technological development, Ramassa and Leoni (2022) [85] demonstrate how an agenda choice took the place of a standard. This is an argument that is as much about due process as it is about measurement. The archival counterpart for the US is provided by Anderson et al. (2025) [13], who look at the cryptocurrency holdings and accounting practices of public companies between 2013 and 2022. They find exponential growth in holdings, significant variation in accounting treatment, and a preference for fair value recognition that rises with token liquidity—proof that the enacted rule better suits actively traded tokens than illiquid ones. The measuring problem is explicitly addressed by Beigman et al. (2023) [16], who offer a technique for dynamic principal-market determination in fragmented cryptocurrency markets—exactly the operational challenge a Custody and audit. The difficulties of auditing blockchain-based assets are systematized by Pimentel et al. (2021) [81], while Vincent and Wilkins (2020) [104] list the steps these difficulties necessitate. The recurrent topic is custody: legal ownership, client asset segregation, and the dependability of a custodian are not on-chain realities, but control of a private key is observable. Since confusing the reporting sources employed in this cluster is a common mistake in the literature, Table 6 documents their current state.

Table 6: Reporting and professional sources, by status Source Status What it establishes IFRS Interpretations Committee (2019) Agenda decision within IFRS due process How existing standards apply to cryptocurrency holdings FASB (2023), ASU 2023-08 Enacted amendment to the Codification Fair value measurement and disclosure for in-scope crypto assets EFRAG (2020) Discussion paper Options canvassed for possible future requirements CPA Canada & AICPA (2017) Non-authoritative professional guidance Professional expectations about audit and assurance ICAEW (2018) Professional thought leadership Professional expectations about the accountant’s role Yaga et al. (2018), NIST Technical overview Terminology and architectural premises

5.7. Taxation and Public-Sector Information

Tax administration is the setting in which the accounting case for shared ledgers is strongest analytically, because the coordination failure is explicit: taxpayers, counterparties and the administration hold different records of the same transactions. Søgaard (2021) [95] designs a blockchain-enabled platform for value-added tax settlement in which the tax is computed and remitted transactionally rather than retrospectively, addressing both compliance cost and carousel fraud. Hyvärinen et al. (2017) [49] develop and evaluate a design for dividend withholding tax in the public sector, an area in which repeated fraud has been documented. Demirkan et al. (2020) [30] locate the same architecture within cyber-security and accounting.

There are two boundaries that should be stated. First of all, none of these are income results; rather, they are design-science contributions that prove viability under specified conditions. Second, tax platforms focus on rather than eliminate governance issues, such as who runs the network, who has access to transaction-level data, and the legal implications of a ledger entry. Adoption in tax administration has been slower than anticipated by the technical literature because of these institutional issues.

5.8. Accountability, Governance and Sustainability

Information This cluster challenges the notion that blockchain technology is a transparency technology. In their analysis of accountability in blockchain systems, Tyma et al. (2022) [103] demonstrate that rather than merely strengthening accountability linkages, the technology redistributes them: transaction visibility is not the same as actor answerability. In their direct discussion of governance, Smith and Castonguay (2020) [94] advise modifying audit rules, internal control procedures, and counterparty risk assessment prior to adoption. Yermack (2017) [110] examines the effects of corporate governance, predicting improvements in ownership transparency and the exercise of shareholder rights, but pointing out that the same transparency jeopardizes the informational advantages that certain parties currently enjoy. This serves as a reminder that transparency has opponents and distributional consequences.

Marrone and Hazelton (2019) [65] place blockchain within the broader category of technologies that may disrupt accounting and accountability, while Secinaro et al. (2022) [90] situate accountability within the field's general structure. The literature on sustainability reporting is still mostly programmatic: the assurance problem (the correspondence between physical flows and token records) is precisely the first-mile problem of Alles and Gray (2020) [7], which no sustainability application in the corpus addresses, and the mechanism (traceable provenance data) is obvious.

5.9. Professional Capability, Education and Business

Models This raises three related questions: what accountants need to learn, how businesses will make money, and whether the role of the profession will grow or shrink.

Regarding capability, Tušek et al. (2021) [102] outline the knowledge needed for blockchain-based environments; Marrone and Hazelton (2019) [65] frame the skills question as a prerequisite for the profession's relevance; and Qasim and Kharbat (2020) [84] suggest curriculum redesign integrating blockchain, analytics, and artificial intelligence. Oh and Shong (2017) [74] offer an early case study of blockchain-driven business model innovation in financial institutions. and Javaid et al. (2022) [54] examine applications in financial services; Dyball and Seethamraju (2025) [34] conduct interviews with Australian companies and discover that, rather than coming from the characteristics of the technology, blockchain's influence on business models is mediated by customer demand and the firms' evaluation of commercial viability. Maffei et al. (2021) [63] come to a similar conclusion from an integrated accounting and auditing perspective; Desplebin et al. (2021) [31] ask whether blockchain represents the future of accounting and auditing and respond conditionally, emphasizing that the profession will reinvent practices rather than be displaced; and Kommunuri (2022) [58] situates the same argument in the larger technological shift. Two findings in this cluster are robust and should temper enthusiasm. Professionals consistently expect a supporting rather than a substituting role for the technology (Tiberius & Hirth, 2019; Abdennadher et al., 2022) [99, 1], and firms invest in capability in proportion to client demand rather than in anticipation of it (Dyball & Seethamraju, 2025) [34]. Both findings point to an adoption path driven by clients and regulators rather than by audit firms.

5.10. Credit Risk, Banking and Evidence from Emerging

Economies The final cluster contains the material that most differentiates this review from its predecessors, and it is also the material most likely to interest reviewers at journals that ask what a study adds beyond OECD settings.

Credit risk and banking: Byström (2019) [20] argues that real-time accounting information produced on a blockchain would materially change credit-risk modelling, because default prediction is constrained by the staleness of accounting data; the argument is analytical and its empirical test remains open. Ismail and Ramo (2024) [53] survey Iraqi academics and professionals on the use of blockchain to improve credit-risk management, and Hashem et al. (2023) [48] examine audit process quality in the Egyptian banking sector, reporting perceived improvements in timeliness, testing scope and advisory services.

Accounting information systems in Iraq: ALSaqa et al. (2019) [8] provide an early treatment of blockchain’s effect on accounting information systems in an Iraqi setting. Alkafaji et al. (2023) [5] survey a sizable sample of Iraqi respondents and find that both listed and unlisted organizations' perceived quality of accounting information is higher when they are familiar with blockchain. Amen et al. (2026) [12] apply the technology-organization-environment paradigm to the Iraqi accounting sector, differentiating between organizational capability, environmental pressure, and technical readiness, whereas Majeed and Taha (2024) [64] map the adoption determinants of Iraqi auditors. When taken as a whole, these studies show a market where professional skill is the binding restriction, awareness is growing more quickly than implementation, and regulatory signaling is essentially nonexistent. similar and adjacent economies: The experiences of Kazakhstan and Ukraine are documented by Kolisnyk et al. (2023) [57] and Matskiv et al. (2023) [67]; Chowdhury et al. (2023) [27] investigate implementation technique in Bangladesh; Jordan is covered by Alshurafat et al. (2023) [9] and Alkhwaldi et al. (2024) [6]; the United Arab Emirates is covered by Abdennadher et al. (2022) [1] and Parmoodeh et al. (2023) [77]; and Middle Eastern evidence linking client technology use to audit risk components is provided by Elmaasrawy et al. (2025) [35].

The reading that is comparative is educational. The limitations noted in these contexts differ from those highlighted in North American literature. Infrastructure dependability, the lack of regulatory guidelines, a lack of professional training, and the expense of integrating with legacy systems are more important than Oracle design and principal-market determination (Chowdhury et al., 2023; Amen et al., 2026; Majeed & Taha, 2024) [27, 12, 64]. A field that theorises adoption from high-capacity institutional environments will systematically mis-specify the barriers that bind elsewhere.

6. Cross-Cutting Discussion

6.1. Four Dimensions for Interpreting the Literature

Four dimensions recur across the clusters and organise the disagreements in the field. They are summarised in Table 7 and used in Table 8 to compare findings across designs.

Table 7: Recurring analytical dimensions Dimension Question it answers Why it matters Coordination problem Whose disagreement does the ledger resolve? Where no inter-party disagreement exists, the architecture adds cost Source-data integrity How does information enter the ledger? Determines whether integrity claims reach the financial statements Governance and custody Who validates, upgrades and holds keys? Relocates rather than removes control risk Institutional fit Which standards, regulations and capabilities apply? Explains divergent adoption across jurisdictions Table 8: Agreement and disagreement across research designs Question Conceptual and design work Survey and interview work Archival evidence State of the question Can shared ledgers reduce reconciliation effort? Yes, under stated conditions Practitioners expect so Not directly tested Mechanism supported; magnitude unmeasured Does the ledger improve evidence quality? Only for post-entry integrity Auditors report amplified client risk Mixed and setting-specific Disagreement traced to the first-mile problem Does adoption improve information quality? Argued Associated with perceived quality Associations reported Plausible; endogeneity unresolved Will audit effort fall? Procedures can be automated Practitioners expect budget reductions No implementation evidence Open Which measurement basis fits crypto assets? Competing models argued Preparers vary in practice Fair value preference rises with liquidity Partially settled by enacted rules Does adoption change reporting behaviour? Assumed benign Not addressed Evidence of behavioural response Understudied and consequential

6.2. Theoretical Frames and Their Consequences

The corpus draws on a small number of frames, and the choice of frame largely determines the findings. Acceptance theories (unified theory of acceptance and use of technology; technology acceptance model) dominate the adoption cluster and produce intention-based findings almost by construction (Ferri et al., 2021; Alkhwaldi et al., 2024; Alshurafat et al., 2023; Majeed & Taha, 2024) [40, 6, 9, 64]. The technology– organisation–environment framework broadens the unit of analysis to the firm and its environment, which is why it recovers infrastructural and regulatory barriers that individual-level models cannot see (Amen et al., 2026; Chowdhury et al., 2023) [12, 27]. Transaction-cost reasoning explains where shared ledgers should appear at all, by locating them where coordination is expensive (O’Leary, 2017; Karajovic et al., 2019) [73, 55]. Agency and information-asymmetry reasoning underlies the information-quality cluster (Fang et al., 2023; Centobelli et al., 2022) [38, 25]. Institutional reasoning explains standard-setting outcomes and professional responses (Ramassa & Leoni, 2022; Tyma et al., 2022) [85, 103].

Two gaps follow. First, almost no study in the corpus uses a theory of evidence — an account of what makes a source probative for an auditor — even though the field’s central problem is evidential. Second, there are few economic models with clear costs that explain when a company should choose a shared ledger over a bilateral database; instead, the accounting literature makes the comparison.

6.3. What the Literature Establishes, And What It Does

Not Across designs, three conclusions are validated. Blockchain can prove that certain data was recorded at a given time and kept unaltered. Parties that might otherwise reconcile disparate records may quarrel less as a result. Control risk is rearranged in relation to off-chain operations, oracles, protocol governance, and key management.

There are still three allegations that the corpus does not support. Blockchain enhances audit quality because no study compares audit results to a similar alternative while observing an operational deployment. Because budget assumptions are published but actual expenses are not, it lowers audit costs. Because it makes accounting continuous, continuous reporting necessitates ongoing measurement decisions that a ledger cannot make, such as impairment, provisioning, and revenue recognition over time.

7. Implications for Practice, Policy and Education

7.1. Accounting and Audit Organisations

A company's practical dilemma is not whether to "implement blockchain," but rather whether a particular coordination issue warrants a shared ledger and what assurance regime the resulting architecture necessitates. The corpus has four implications.

Prioritize the coordination issue over the technology. Conventional databases with robust controls dominate on cost when records are contested across organizations (O'Leary, 2017; Liu et al., 2022).

Second, rather than treating the first mile as an afterthought, consider it the center of your design. Whether ledger integrity reaches the financial accounts depends on input restrictions, oracle arrangements, and the relationship between tokens and tangible or legal things (Alles & Gray, 2020; Sheldon, 2021; Caldarelli, 2020).

Third, instead of focusing on record preservation, reconstruct the control framework around key management, protocol governance, and change control (Sheldon, 2019; Appelbaum & Nehmer, 2020; White et al., 2020).

Fourth, rather than assuming that the ledger lowers testing, base your audit strategy on the premise that client blockchain use increases inherent and control risk until controls are proven, in line with the empirical findings of Dyball and Seethamraju (2022) and Elmaasrawy et al. (2025).

7.2. Standard Setters and Regulators

The crypto-asset episode offers a transferable lesson about sequencing. The IFRS Interpretations Committee (2019) [51] applied existing standards; EFRAG (2020) [36] canvassed options; FASB (2023) [41] enacted a scoped fair value requirement several years later. Research shows that preparers had already differentiated their practices by liquidity before the rule arrived (Anderson et al., 2025) [13], and that the operational difficulty of fair value in fragmented markets — identifying the principal market — remains unresolved in practice (Beigman et al., 2023; Al-Taie & Al-Hadrawi 2021).) [16, 11]. Standard setters working on tokenised assets, stablecoins and central bank digital currencies can reasonably anticipate the same pattern: practice differentiates first, measurement guidance follows, and the operational measurement question survives the guidance. For regulators in emerging markets the implication is different and more urgent. The binding constraints reported in Iraq, Jordan, Bangladesh, Ukraine and Kazakhstan are regulatory silence, professional capability and integration cost (Majeed & Taha, 2024; Amen et al., 2026; Chowdhury et al., 2023; Kolisnyk et al., 2023; Matskiv et al., 2023) [64, 12, 27, 57, 67]. Guidance on the admissibility of ledger records as accounting evidence, and on the treatment of digital assets for tax and reporting, would remove more friction at lower cost than any technical intervention.

7.3. Education and Professional Development

The education literature converges on competence rather than coding (Qasim & Kharbat, 2020; Tušek et al., 2021; Marrone & Hazelton, 2019) [84, 102, 65]. The competences that the evidence identifies as decision-relevant are the ability to read an architecture and identify who validates and who may write; the ability to evaluate an oracle or data feed as one would evaluate a service organisation; the ability to test key custody; and the ability to distinguish a measurement question from a record-keeping question. For universities in emerging markets, including Iraq, the sequencing implication is that accounting information systems and audit-evidence courses are the natural hosts for this material, and that technostress and low perceived self-efficacy are documented barriers that curricula should address directly (Alshurafat et al., 2023) [9].

8. A Research Agenda Based on Observable Outcomes

The field’s constraint is evidential. The agenda below is therefore stated as propositions with the designs capable of testing them.

P1 (reconciliation): In settings with high inter-organisational reconciliation cost, shared-ledger adoption reduces reconciliation effort and dispute resolution time relative to bilateral reconciliation. Design: matched field study or difference-in-differences across adopting and non-adopting business units, with process-level cost data. P2 (audit effort): Client blockchain use shifts audit effort from substantive transaction testing toward controls testing and entity-level evidence, with an ambiguous net effect on total hours. Design: audit-hour composition data from engagement files, pre- and post-client adoption, extending Dyball and Seethamraju (2022) [33] with archival measures. P3 (evidence evaluation): Auditors over-weight on-chain evidence relative to its diagnostic value for occurrence and rights assertions. Design: experiment with practising auditors manipulating evidence source and assertion type. P4 (information quality): Blockchain adoption improves timeliness and verifiability of accounting information but does not improve measurement-dependent characteristics. Design: archival tests separating measurement-dependent from record-dependent quality proxies, extending Fang et al. (2023) [38] and Alkafaji et al. (2023) [5] with implementation rather than familiarity measures.

P5 (reporting behaviour): Adoption affects discretionary accruals unrelated to data integrity by altering external expectations and, consequently, reporting incentives. Design: supply-chain counterparties are the treated population in an archival event research centered on announced adoption. P6 (crypto measurement): For liquid tokens, fair value measurement increases relevance; for illiquid tokens, it decreases reliability. Design: value-relevance and disclosure-quality tests divided by liquidity around the ASU 2023-08 effective date (Anderson et al., 2025) [13]; (Beigman et al., 2023) [16].

P7 (tax platforms): Transactional settlement reduces compliance cost and missing-trader fraud relative to periodic filing. Design: pilot evaluation or simulation calibrated to administrative data, extending Søgaard (2021) [95]. P8 (institutional fit): In institutional settings with weak regulatory signalling, organisational and environmental factors dominate individual acceptance factors in explaining adoption. Design: multi-country survey with a common instrument, combining acceptance and technology– organisation–environment constructs (Amen et al., 2026) [12]; (Majeed & Taha, 2024) [64]; (Chowdhury et al., 2023) [27].

Table 9: Research agenda, designs and required data Proposition Primary design Data required Feasibility P1 Reconciliation Field study / DiD Process cost and cycle-time data Moderate; requires firm access P2 Audit effort Archival engagement data Audit hours by procedure category Low–moderate; confidentiality P3 Evidence evaluation Experiment Practitioner participants High P4 Information quality Archival Implementation measures; quality proxies Moderate P5 Reporting behaviour Event study Adoption announcements; accruals High P6 Crypto measurement Archival Filings pre/post ASU 2023-08 High P7 Tax platforms Simulation / pilot Administrative tax data Low; requires authority cooperation P8 Institutional fit Multi-country survey Common instrument across markets High A final methodological recommendation applies across the agenda. Studies should report what respondents have actually used, distinguish pilots from production systems, and state whether the measured variable is an intention, a perception, a process outcome or a reported number. The single most common inferential error in this literature is the silent substitution of one of these for another.

9. Limitations

This review is a structured subject review, not a PRISMA-compliant systematic review: it does not report a reproducible screening count, independent duplicate coding or inter-coder reliability. Its corpus, although larger and more recent than most prior accounting reviews, is not exhaustive, and it reflects English-language publication. Coding of design and inference was performed by the author and is interpretive at the margins, particularly for studies that combine designs. Only publisher records and abstracts were available for a small number of items, which restricts the depth of the appraisal. Lastly, the area is evolving rapidly: conclusions on the impact of the crypto-asset requirements discussed here are inherently tentative, as they were recently implemented.

10. Conclusion

The literature on blockchain in accounting and auditing has evolved from advocacy to differentiation among 110 sources. It consistently demonstrates that a shared ledger may transfer control risk to keys, protocols, and data feeds, minimize reconciliation between parties who mistrust one other's copies, and preserve and share records. It does not prove that shared ledgers enhance audit quality, lower audit costs, or make accounting continuous because the research necessary to support such claims—implementations compared to reliable alternatives—have not yet been carried out. The simplest reinterpretation that the field may utilize is also the most beneficial. Blockchain is a coordination technology that accounting systems may employ where coordination is the binding issue; it is not an accounting system. Value appears when there is a clear coordination failure, when trustworthy source data can be linked to the ledger, and when governance and custody are clearly under control. When those prerequisites are not met, the architecture increases expenses and shifts risk without lowering it. The evidence gathered here points to a specific research and policy program rather than a broad goal for emerging economies, such as Iraq: measure implementation rather than familiarity, investigate organizational and regulatory factors that are invisible to individual acceptance models, and advocate for guidelines regarding the evidential status of ledger records. Additionally, that initiative would provide what the international literature most noticeably lacks: observations of blockchain-based accounting in use in contexts where institutional rather than technical limitations exist.

Appendix A. The Reviewed Corpus by Thematic Cluster and Design The table lists the 105 studies reviewed, grouped by their principal cluster. Studies contributing to more than one cluster are listed once, under their dominant contribution. Design codes: C = conceptual; D = technical design or prototype; S = survey; I = interview or case study; A = archival or quasi-experimental; R = prior review; T = technical or foundational.

Table A1: Reviewed studies by cluster Cluster Studies (design code)