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Record W4383534905 · doi:10.3390/jrfm16070323

A Literature Review on the Financial Determinants of Hotel Default

2023· review· en· W4383534905 on OpenAlexvenueno aff
Theodore Metaxas, Αθανάσιος Ρωμανόπουλος

Bibliographic record

VenueJournal of risk and financial management · 2023
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Distress and Bankruptcy Prediction
Canadian institutionsnot available
FundersEuropean Social FundState Scholarships FoundationEuropean Commission
KeywordsStylized factBusinessProfitability indexDebtDimension (graph theory)Variety (cybernetics)LiabilityFinanceAccountingActuarial scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

Empirical corporate failure studies focusing on specific economic activities are increasing in number, as this path can be a more precise investigation of default, although still there is a gap in the literature reviews at the sector level. The purpose of this study is to focus on the hotel sector and isolate the financial determinants linked to hotel default, as the approach of accounting-based models is the most frequent practice. To arrange the variety of outputs, a thorough design is applied based on specific inclusion and exclusion criteria, leading to 29 studies, which are further narrated, focusing mainly on the financial dimension. In addition, information on the study design is recorded in an aggregated table. The most frequent stylized results show that debt and liability measures increase the default risk, while measures of profitability and size in terms of total assets reduce the risk. This review addresses the calls for a sectoral focus and provides an up-to-date financial overview of hotel default assessments. It further aims to benefit academia, as it can act as a base for further development, as well as stakeholders involved in the financial sustainability of the hotel sector.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.268
Teacher spread0.242 · 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 designOther design
Domainnot available
GenreReview

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

Citations4
Published2023
Admission routes1
Has abstractyes

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