Modelling the Use of Z Score ratios in Predicting Bankruptcy likelihood of Sugar Companies in Kenya

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dc.contributor.author Range, Maurice Mwita
dc.date.accessioned 2019-06-12T09:20:49Z
dc.date.available 2019-06-12T09:20:49Z
dc.date.issued 2019-06-12
dc.identifier.uri http://hdl.handle.net/123456789/5045
dc.description Doctor of Philosophy in Business administration (Finance) en_US
dc.description.abstract The sugar companies in Kenya contributes significantly in the country’s economy by creating employment opportunities, production of sugar which is used for domestic, industrial consumption and for exports which enable the country to earn foreign income hence improving balance of trade. However, despite the important contributions that the sugar industry plays in the Kenyan economy, the bankruptcy likelihood of this sector is high. Research has hardly been done in predicting the bankruptcy likelihood of sugar companies. This study sought to bridge this gap by modelling the use of the Z score ratios in predicting the bankruptcy likelihood of sugar companies in Kenya. Specifically the study assessed the effects of working capital to total assets ratio, determined the influence of retained earnings to total assets ratio, established the effect of earnings before interest and tax to total assets ratio, examined the influence of book value of equity or market value of equity to total liabilities ratio and established the effect of sales to total assets ratios in predicting the bankruptcy likelihood of sugar companies in Kenya. This research was anchored on various theories including; liquidity preference, resource dependence, static trade off, pecking order and entropy theory. Descriptive research design was used in the study. The target population was the 12 sugar companies in Kenya as per Sugar Directorate year book 2016 which included both public owned and private owned sugar companies. The study adopted purposive sampling technique to collect primary data. An open and closed ended questionnaire was used to collect primary data from public owned sugar companies in Kenya. A data collection sheet was used to collect secondary data from public and private owned sugar companies in Kenya. Data was analyzed using SPSS and presented in form of figures and tables. The results of the study revealed that the following ratios are significant discriminators and predictors of the bankruptcy likelihood of sugar companies in Kenya; BVE or market value of equity to total liabilities, earnings before interest and tax to total assets, retained earnings to total assets and working capital to total assets. However, the study established that the ratio sales to total assets ratio was not a significant discriminator and predictor of the bankruptcy likelihood of sugar companies in Kenya. In addition, the results revealed that all the public owned sugar companies had high bankruptcy likelihood while on the other hand the private owned sugar companies’ had a low bankruptcy likelihood during the period of the study. Consequently, the Z score ratios model was found to be a robust model in predicting the bankruptcy likelihood of sugar companies in Kenya. The study recommends adoption of the Z score ratios model as a utility predictor of bankruptcy likelihood of sugar companies in Kenya. This study has implications to policy since it establishes a versatile model of predicting the bankruptcy likelihood of sugar companies whose sustainability is pertinent in achieving the countries sustainable development agenda and economic growth. The study also contributes to the existing body of knowledge of extending the discourse of the application of the Z score ratios model in predicting bankruptcy likelihood by applying discriminant analysis. Additionally the findings of this study has implications to methodology because it employed descriptive research design unlike the other previous studies which used case study design which is subjective and not conclusive hence their findings cannot be generalized to other sugar industries in the sector. en_US
dc.description.sponsorship Dr. Agnes Njeru, PhD JKUAT, Kenya Prof, Gichuhi Waititu, PhD JKUAT, Kenya en_US
dc.language.iso en en_US
dc.publisher JKUAT-COHRED en_US
dc.subject Sugar Companies in Kenya en_US
dc.subject Predicting Bankruptcy likelihood en_US
dc.subject Modelling the Use of Z Score ratios en_US
dc.title Modelling the Use of Z Score ratios in Predicting Bankruptcy likelihood of Sugar Companies in Kenya en_US
dc.type Thesis en_US


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