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Record W2775793269 · doi:10.1080/15256480.2017.1397583

Key managerial and financial accounting skills for private club managers: Comparison to lodging managers

2017· article· en· W2775793269 on OpenAlexaboutno aff
Mi‐Ran Kim, Raymond S. Schmidgall

Bibliographic record

VenueInternational Journal of Hospitality & Tourism Administration · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHospitality and Tourism Education
Canadian institutionsnot available
Fundersnot available
KeywordsClubBusinessAccountingHospitality industryEmpirical researchHospitalityManagement accountingMarketingFinancial accountingSkills managementAccounting information systemTourismPolitical science

Abstract

fetched live from OpenAlex

This study provides empirical evidence of the comprehensive accounting skills by financial executives across the United States, and Canada believed important to private club general managers. This study’s purview extends to identify any significant differences or similarities in the accounting skills between the private club and lodging managers. Four hundred and one responses (211 from clubs and 190 from hotels) were received. The most critical accounting skills for club and lodging managers are understanding operating budgets, capital budgets, income statements, and analyses of variances. When comparing the accounting skills to managers between clubs and hotels, the ranks of importance are similar. The findings provide theoretical and practical implication for hospitality researchers, managers, and educators.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0030.004
Open science0.0010.000
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 head0.014
GPT teacher head0.300
Teacher spread0.286 · 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.

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

Citations2
Published2017
Admission routes1
Has abstractyes

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