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COVID-19 Pandemic and Financial Performance

2023· article· en· W4381679939 on OpenAlexaboutno aff
Abdullah Mohammad Al-Zoubi

Bibliographic record

VenueInternational Journal of Professional Business Review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsOriginalityQuarter (Canadian coin)Profitability indexMarket liquidityPandemicCoronavirus disease 2019 (COVID-19)Stock exchangeBusinessDebtValue (mathematics)AccountingEconomicsFinanceGeographyStatisticsMathematicsSociologyQualitative researchInfectious disease (medical specialty)Social science

Abstract

fetched live from OpenAlex

Purpose: This study aims to illustrate the impact of the corona pandemic (COVID-19) on the financial performance in industrial companies in Jordan. Theoretical framework: This study depend on review of literature review to determine variables of study and its relationship, has been determined all variables: corona pandemic (COVID-19) is independent variable, dependent variables was divide into three axes: profitability, liquidity and debts each of them was measure by some financial ratios that its will show later in hypotheses. Design/Methodology/Approach: The study was applied on 16 industrial companies in Jordan, their quarterly financial statements were collected from Amman’s stock exchange from the first quarter of the year 2017 to the end of the third quarter of the year 2021. Finding: It concluded to the fact that there is a negative impact on profitability reflected by the corona pandemic (COVID-19), and another positive impact on debts, and has no impact on the liquidity. Research, Practical & Social implications: The implication drawn from this study is that it show to researchers and interested of investment, that causes it corona pandemic (COVID-19) impact on performance of companies listed on important sector in Jordan is industrial Sector, which is represented 60% from all investments. Originality/value: The value of the study's originality in the past two years is the world was invaded by a new disease called Corona (COVID-19), and the disease enforced some changes on companies activities and performances it due to the closure works of companies.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.112
GPT teacher head0.370
Teacher spread0.258 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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