Blockchain Technology: Changes and Challenges for Accounting and Accountants
Bibliographic record
Abstract
This dissertation reports three essays relating to changes and challenges for accounting and accountants with regard to the nascent blockchain technology. These essays all focus on different phases of blockchain development and explore the impact the technology is having on the accounting profession. Blockchain emerged with Bitcoin in 2008 and since then, various applications are possible, such as finance, supply chain, health, and insurance, to name a few. In the first study, I explore the case study of impak Finance, the first Initial Coin Offering (ICO) based on cryptocurrency accepted by the regulator in Canada. I conducted 8 interviews from the key stakeholders to understand the benefit and the risk of this ICO. In this context, I find that audit firms didn’t have the tools to support emergent companies that use cryptocurrency and cannot meet the requirements of the regulator in terms of financial information. This situation has rarely occurred in the history of auditing and it remains a current difficulty in the market to find an audit firm to give an opinion on financial statements. My second study is based on the Bitcoin story. Drawing on a netnography of the early Bitcoin community from the technology’s formation in 2008 through to the disappearance of its founder in 2011, this paper aims to explore the role of accounting in the development of a new financial system. We propose that Bitcoin is more than a form of digital currency, but rather a new accounting regime (Jones & Dugdale, 2001) that effectively takes accounting expertise away from accountants. The theoretical root of the accounting regime is from Giddens’ modernity theory. It is urgent that accountants take an interest and educate themselves on the blockchain issue to seize this opportunity before becoming redundant or absent, as the Bitcoin story demonstrates, the ledger is an accounting regime without accountants. In the third and last study, I conducted 28 interviews about blockchain applications and implementation into business and explore how triple-entry accounting evolves with blockchain technology. Ultimately, I illustrate how triple-entry accounting, which is intrinsic to blockchains, modifies and simplifies the processing of accounting operations. Additionally, participants in the blockchain network operate with a single ledger, driving a single version of reality that creates a consensus and generating real-time information. My findings raise questions regarding the future role of accountants as internal control experts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.025 |
| Scholarly communication | 0.026 | 0.035 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".