The Effects of Information Acquisition Effort, Psychological Ownership, and Reporting Context on Opportunistic Managerial Reporting*
Bibliographic record
Abstract
ABSTRACT Within the context of managerial reporting, the tasks of acquiring and reporting information are logically connected. Although the accounting literature acknowledges their importance, it often treats these tasks as distinct processes. I investigate how the effort exerted to acquire information influences managers' reporting. Managers' information acquisition effort can induce psychological ownership that can lead to a sense of deservingness that increases opportunistic reporting or to a sense of responsibility that reduces opportunism. I predict that the reporting context determines the ultimate effect of information acquisition effort on reporting behavior. I test this prediction with a 2×2 budget reporting experiment. Managers are either endowed with information to report or required to exert effort to earn it, with the latter expected to generate more psychological ownership. In addition, I manipulate the saliency of honesty in the reporting context by framing reporting in terms of a business dilemma (less salient honesty) or an ethical dilemma (more salient honesty). I find that when honesty is less salient, managers build more slack into their report under earned information than endowed information. In contrast, more salient honesty alleviates the effect of earned information on slack. In a supplemental experiment, I find similar results when all managers are endowed with information to report but psychological ownership is manipulated via different firm messaging. These results have important implications for theory and practice. For example, in a less salient honesty context, technological investments that reduce managers' effort needed to acquire information can also help decrease opportunistic reporting.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Accounting experiment on opportunistic managerial reporting; 'reporting' is budget reporting by managers, not research reporting.
The experiment studies managerial reporting behavior, not research practice.
Accounting experiment on managerial budget reporting and honesty; reporting here is business reporting, not research reporting.
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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".