Accounting

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https://hdl.handle.net/20.500.11888/14850

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Browsing Accounting by Author "Rabaia, Duha"

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    THE IMPACT OF CORPORATE GOVERNANCE AND BOARD OF DIRECTORS CHARACTERISTICS ON CORPORATE FAILURE: SURVIVAL STATISTICAL PREDICTION BY R
    (جامعة النجاح الوطنية, 2022-08-01) Rabaia, Duha
    This study aims to predict corporate failure (CF) of the companies listed on the Palestine Exchange (PEX) and the Amman Stock Exchange (ASE) by means of a statistical method, using R. In addition, the study intends to examine the impact of corporate governance (CG) and board characteristics (BC) on CF. The statistical method used in this study was survival analysis. RStudio was used to analyze the study data by applying the Cox hazard regression technique. The annual reports of a total of 96 companies from the industrial and service sectors were analyzed for the period between 2015 and 2019. More than 7200 observations were made in this study. Agency theory and upper echelons theory were the main theories used to explain the association among the study variables. The study found a significant negative association of board size, board independence, board age, board education, firm size, liquidity and profitability, considered together, and CF. In contrast, for companies in the PEX – except for board age, which showed significant negative association with CF – there existed a significant positive association of CF with ownership concentration, board education and board activity. For ASE, there was a significant positive association between profitability and CF but a significant negative association of board size, board independence, board age, board education, firm size, liquidity and profitability with CF. In general, the log-likelihood test result indicated that the CG and BC models are significant for the PEX and ASE. However, there was a significant difference between PEX and ASE regarding the impact of CG and BC on CF. Moreover, the statistical learning test suggested that liquidity, firm size, ownership structure, board age, board independence and profitability are the most important subset variables, in that order, to predict CF. Finally, receiver operating characteristic (ROC) curve illustrated that the survival models as classifiers are ideal and have an accuracy equal to 0.84. This study is expected to contribute to the literature in the field of accounting by providing an understanding of the association between CG and BC on one hand and CF on the other. Moreover, this study statistically predicts CF without relying on commonly used quantitative models for the purpose, such as Altman, Kida and Sherrod models. In addition, this study is one of the first ones to use RStudio in the field of accounting. Finally, it links behavioural science and accounting theories. Findings assist investors to evaluate financially distressed firms on the basis of CG and BC. In addition, it will help decision-makers to improve the firm and avoiding risks that may lead CF. Also, be essential for regulatory authorities in formulating new policies regarding CG and BC. Moreover, this study is considered a model that encourages researchers to use the RStudio program in their research. The study limitations are the difference between the size of PEX and ASE. As the size of the ASE is three times larger than the PEX. Thus, this leads to differences in the accuracy of the results, as the larger sample leads to results that are more accurate. In addition, the absence of an agreed index for evaluating CG practice compliance. Future studies are encouraged to study more factors that may be an effect on the CF especially under the influence of the Covid-19 pandemic. Another important suggestion is to use artificial intelligence in the prediction of CF in PEX and ASE.