Firms and governance factors affecting the adoption of web-based corporate reporting: Evidence from the USA
Bibliographic record
Abstract
This paper examines the potential determinants associated with a firm’s decision to use a corporate website. The probability of web-based corporate reporting adoption was measured by using a dichotomous variable, where one is given if the firm has a website and zero otherwise. Based on a sample of 1217 US listed firms, it was found that 950 firms have a website and 267 do not. Those firms with a website are larger, more profitable and have a larger board size with more female directors when compared with firms without websites. In addition, the results of the regression analysis revealed that firm size, profitability, leverage, board size and the percentage of female directors in the boardroom have a significant positive impact on the probability of a firm having a website. However, firm age has a significant negative impact on the probability of web-based corporate reporting adoption. A weakness in the previous literature has been the neglect of firms without an online presence, which implies a potential selection bias. Consequently, this research contributes to the international accounting literature by expanding our understanding in relation to the probability of firms adopting web-based corporate reporting and the economic consequences of them doing so through reducing asymmetric information, which acts as an incentive to encourage investment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".