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Record W4385444142 · doi:10.1111/1911-3846.12891

How does depletion interact with auditors' skeptical dispositions to affect auditors' challenging of managers in negotiations?

2023· article· en· W4385444142 on OpenAlexaffvenue
Lori Shefchik Bhaskar, Tracie M. Majors, Adam Vitalis

Bibliographic record

VenueContemporary Accounting Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSkepticismAuditNegotiationPsychologyAccountingAffect (linguistics)BusinessService (business)Social psychologyPolitical scienceMarketingEpistemologyCommunicationLaw

Abstract

fetched live from OpenAlex

Abstract We use multiple methods to examine how depletion and auditors' skeptical dispositions interact to affect auditors' challenging of managers in negotiations over financial statement amounts. We expect auditors are likely depleted from effortfully exercising self‐regulation during the busy times when these negotiations occur. Individuals in a depleted state tilt toward natural, less effortful behaviors. Thus, we posit that the effects of depletion will diverge depending on the auditor's skeptical disposition—a determinant of how natural or effortful they will find the skeptical behaviors (e.g., challenging) versus client service behaviors (e.g., maintaining the client relationship and audit efficiency) required for negotiations. We predict that client service auditors (i.e., low skeptics) will challenge managers less in negotiations when depleted versus non‐depleted, while high skeptic auditors will challenge more when depleted. We test this interactive prediction in an abstract experiment where we manipulate depletion and measure auditors' skeptical dispositions using trait skepticism. Findings support our predictions. We also develop a new measure of auditors' client service–skeptic disposition based on the skepticism literature that adds nuance to the traditional lower versus higher skeptic labels. In a second study, interviews with audit partners validate the realism of our depletion and client service–skeptic constructs and corroborate our experimental findings. Our study sheds light on depletion effects in auditors' negotiations with their clients and how the effects differ based on auditor personalities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.064
GPT teacher head0.395
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2023
Admission routes2
Has abstractyes

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