Remote Work in Audit Firms: A Systematic Literature Review and Theoretical Framework
Bibliographic record
Abstract
The mass adoption of remote working technologies, facilitated by the COVID-19 pandemic, has permitted a transformation in the work of professional auditors. Where auditors previously worked long hours at the office or on the road near colleagues, remote work has created new work routines that are conducted alone at home. While home-based remote work may be a relatively new phenomenon for auditors, it is not a new phenomenon for knowledge workers in general. In this paper, we perform a systematic literature review across fields such as sociology, psychology, and management information systems to develop an organizing framework for the literature on remote work according to four primary dimensions: organizational factors, employee factors, job-level outcomes and the work-family boundary. From this organizing framework, we propose a theoretical model for how remote work can impact auditors in audit firms bringing in insights from the literature on the audit profession. Our theoretical model proposes that remote work will lead to changes in audit practices that will have implications at the client, employee and firm level. This theoretical model allows us to propose future avenues for research in this rapidly evolving area.
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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 | 0.019 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.047 | 0.034 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".