Financial Ratio Patterns in Retail and Manufacturing Organizations

Gombola, Michael; Ketz, J. Edward

doi:10.2307/3665210

Cited by 55 publications

(41 citation statements)

References 6 publications

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“…CFFOCL, also reported significant by Gilbert et al (1990), had the second largest effect. These large cash flow ratio effects tend to support the argument that cash flow-based ratios may contain more predictive information than most other ratios (Gombola and Ketz, 1983). Consequently, the disregard of cash flow ratios seems to us a clear weakness in previous GCC insolvency research: cash flow-based ratios should be included when insolvency prediction models are constructed in the GCC.…”

Section: Discussionmentioning

confidence: 93%

“…Ward (1994) posited that cash flow information was more useful in some industries (mining, oil and gas) than others. Gombola and Ketz (1983), in one of the earliest studies to incorporate incremental operating cash flow, suggested that operating cash flow provides more information than that which exists in most other ratios. Similarly, Gentry et al (1987) found that cash flow-based ratios can improve the scope and accuracy of prediction models; and Gilbert et al (1990) who suggested that cash flow information can provide a more reliable means for assessing the financial health.…”

Section: Literature Review and Research Questionsmentioning

confidence: 99%

“…ratios most commonly and successfully used in prior studies (Beaver, 1966, Altman, 1968, Deakin, 1972, Elam, 1975, Gombola and Ketz, 1983, Mensah, 1983, Dambolena and Khoury, 2012. The financial ratios, shown in table 2, cover six major categories:…”

Section: Sampling and Data Collectionmentioning

confidence: 99%

See 2 more Smart Citations

Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling

Khoja

Chipulu

Jayasekera

2014

Rev Quant Finan Acc

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Design/methodology/approach: Financial ratio data on 56 matched pairs of insolvent and solvent firms are analysed using logistic regression with best-subset selection criteria to identify significant ratios, and prediction accuracy is tested on an ex-ante sample. The main dimensions of ratios, and the weights that firms attach to them, are examined using 3-way Multidimensional Scaling (MDS).Findings: A parsimonious Logit model comprising one profitability, one leverage and two cash flow ratios has accuracy levels of 84.4% overall, 95.6% type I and 73.9% type II. Four financial-ratio dimensions are extracted from the MDS: (i) 'Non-strategic sales activities', (ii) 'Profitability and financial stability balance', (iii) 'Sales activities against capital conversion'; and (iv) 'Market value against cash generation'. Insolvent firms appear very specific and attach most salience to the 'Non-strategic sales activities' dimension; unlike solvent firms which attach more salience to the other three dimensions.Practical Implications: Results indicate profitability ratios should be included in GCC insolvency classification models. It is suggested that firms' managers should focus less on non-strategic sales activities to reduce susceptibility to insolvency. Originality/value:The study provides empirical evidence on insolvency in the GCC and introduces the application of 3-way MDS to insolvency research in the region.

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Section: Discussionmentioning

confidence: 93%

Section: Literature Review and Research Questionsmentioning

confidence: 99%

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Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling

Khoja

Chipulu

Jayasekera

2014

Rev Quant Finan Acc

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“…Since the research of Fitzpatrick [1], various bankruptcy prediction models have been performed by many researchers [2][3][4][5][6][7][8][9][10][11][12][13][14]. The models are summarized as follows (Table 1) To design the bankruptcy prediction model, we will collect data for training, testing, and verification using NeuroShell.…”

Section: Design Of Bankruptcy Prediction Modelmentioning

confidence: 99%

“…Since a study by Fitzpatrick [1], various bankruptcy prediction models have been performed by many researchers [2][3][4][5][6][7][8][9][10][11][12][13][14]. The list of models is as follows: Artificial Neural Network, Bayesian, Case Based Inference, Discriminant Analysis, Expert Systems, Financial Statement Analysis, Fuzzy, Genetic Algorithms, Hybrid Neural Network, Inductive Learning, Lambda Index, Logit Analysis, Multivariate Discriminant Analysis, Principal Component Analysis, Probit Analysis, Probabilistic Artificial Neural Network, Profile Analysis, and Rough Set Theory [22][23].…”

mentioning

confidence: 99%

A Development of Hotel Bankruptcy Prediction Model on Artificial Neural Network

Choi¹,

Lee²

2014

Journal of the Korea Society of Computer and Information

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This paper develops a bankruptcy prediction model on an Artificial Neural Network for hotel management. A bankruptcy prediction model has a specific feature to predict a bankruptcy of the whole hotel business after evaluate bankruptcy possibility on the basis of business performance data of each branch. here are many traditional statistical models for bankruptcy prediction such as Multivariate Discriminant Analysis or Logit Analysis. However, we chose Artificial Neural Network because the method has accuracy rates of prediction better than those of other methods. We first selected 100 good enterprises and 100 bankrupt enterprises as experimental data and set up a bankruptcy prediction model by use of a tool for Artificial Neural Network, NeuroShell. The model and its experiments, which

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Impact of climate change mitigation policies on corporate financial performance: Evidence‐based on European publicly listed firms

Secinaro

Brescia

Calandra

et al. 2020

Corp Soc Responsibility Env

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This study examines the relationship between climate change and firm performance in the context of European publicly listed companies. We conduct a multivariate regression analysis using Corporate Environmental Performance and Corporate Financial Performance as independent and dependent variables, respectively. A financial statement analysis of European publicly traded firms with high environmental performance shows that they register high corporate financial performance. Environmental performance positively impacts financial performance (β = .013, p-value < .01). Return on equity (ROE) is positively related to firm size and CE1 (carbon emissions) intensity but negatively linked to CE2, CE1 & 2, and capital intensities. However, return on investment (ROI) is positively correlated with all the control variables, including capital intensity, firm size, and growth. The results confirm that the firm-wide adoption of environmental practices reduces environmental risks, and thereby lowers production costs and increases profits. These findings can guide policymakers and organizations pursuing climate change mitigation and sustainable business solutions.

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Financial Ratio Patterns in Retail and Manufacturing Organizations

Cited by 55 publications

References 6 publications

Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling

Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling

A Development of Hotel Bankruptcy Prediction Model on Artificial Neural Network

Impact of climate change mitigation policies on corporate financial performance: Evidence‐based on European publicly listed firms

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