Reviewer Acknowledgements for Asian Social Science, Vol. 21, No. 1
In: Asian social science, Band 21, Heft 1, S. 120
ISSN: 1911-2025
Reviewer Acknowledgements for Asian Social Science, Vol. 21, No. 1 2025.
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In: Asian social science, Band 21, Heft 1, S. 120
ISSN: 1911-2025
Reviewer Acknowledgements for Asian Social Science, Vol. 21, No. 1 2025.
In: Asian social science, Band 20, Heft 6, S. 109
ISSN: 1911-2025
Reviewer Acknowledgements for Asian Social Science, Vol. 20, No. 6 2024.
In: Asian social science, Band 20, Heft 5, S. 65
ISSN: 1911-2025
Reviewer Acknowledgements for Asian Social Science, Vol. 20, No. 5 2024.
In: Asian social science, Band 20, Heft 4, S. 67
ISSN: 1911-2025
Reviewer Acknowledgements for Asian Social Science, Vol. 20, No. 4 2024.
In: Asian social science, Band 20, Heft 3, S. 126
ISSN: 1911-2025
Reviewer Acknowledgements for Asian Social Science, Vol. 20, No. 3 2024.
In: Global Clinical Trials, S. 159-168
In: International journal of development and conflict: (IJDC), Band 1, Heft 3, S. 435-455
ISSN: 2010-2704
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In: Financial Management, Forthcoming
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Working paper
In: Review of Pacific Basin Financial Markets and Policies, Band 9, Heft 2, S. 317-336
ISSN: 1793-6705
We use four alternative prediction models to examine the usefulness of financial ratios in predicting business failure in China. China has unique legislation regarding business failure so it is an interesting laboratory for such a study. Earnings Before Interest and Tax to Total Assets (EBITTA), Earning Per Share (EPS), Total Debt to Total Assets (TDTA), Price to Book (PB), and the Current Ratio (CR), are shown to be significant predictors. Prediction accuracy achieves a range from 78% to 93%. Logit and Neural Network models are shown to be the optimal prediction models.