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Record W4397014659 · doi:10.1111/1911-3846.12948

Managers' career preferences and corporate culture

2024· article· en· W4397014659 on OpenAlexvenueno aff
Margaret A. Abernethy, Chung‐Yu Hung, Like Jiang

Bibliographic record

VenueContemporary Accounting Research · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
FundersUniversità BocconiNational Taiwan UniversityAccounting and Finance Association of Australia and New ZealandNational University of SingaporeCopenhagen Business School
KeywordsOrganizational cultureIncentiveBusinessValue (mathematics)Public relationsMarketingHofstede's cultural dimensions theoryWork (physics)Quality (philosophy)Labour economicsEconomicsPsychologyMicroeconomicsPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Abstract Building effective corporate culture is challenging as it requires senior managers to embed shared values within the firm. Yet some firms can do so, and some cannot. This study examines whether managers' career preferences influence manager‐employee value misalignment and weaken corporate culture. Career preferences for job‐hopping provide incentives for managers to signal their leadership quality in the labor market. We capture managers' and employees' attention allocation across different cultural values using data from conference calls and Glassdoor. We predict and find that job‐hopping managers direct their attention away from soft cultural values (e.g., respect and integrity) that are less observable by the external labor market. Furthermore, job‐hopping managers who pay insufficient attention to soft cultural values fail to address the concerns that employees have in their everyday work, resulting in lower overall employee culture ratings. Our study highlights the significance of managers' career preferences in shaping different cultural values and offers implications for firms selecting senior managers.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.117
GPT teacher head0.320
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2024
Admission routes1
Has abstractyes

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