Turnaround Strategies and Performance of State Owned Sugar Companies in Kenya

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dc.contributor.author Wandera, Joseph Ogwobo
dc.date.accessioned 2019-02-05T07:39:17Z
dc.date.available 2019-02-05T07:39:17Z
dc.date.issued 2019-02-05
dc.identifier.citation WanderaJO2019 en_US
dc.identifier.uri http://hdl.handle.net/123456789/4887
dc.description Doctor of Philosophy in Business Administration en_US
dc.description.abstract This was a study on the relationship between turnaround strategies and the performance of state owned Sugar Companies in Kenya. Four specific objectives formed the study and these were: to assess the relationship between cost reduction strategy, diversification strategy, re-organization strategy and modernization strategy respectively on the performance of state owned sugar companies in Kenya. The theories that guided the study were the contingency theory of structural adoption to regain fit theory, the generic strategy theory and the life cycle theory. The context of the study was all the five state owned sugar companies operating in Kenya which have also gone through the turnaround process. The total target population was 406 managers cutting across all the management levels in all the selected companies from which a sample of 197 respondents was selected using the stratified random sampling technique. Descriptive research design was employed for the study as it is usually the best method for collecting information that will demonstrate relationships and describe the world as it exists. Close ended questionnaires were used as data collection instruments and they were conveyed to the respondents through drop and pick technique. One questionnaire was administered to each sampled respondent. The strata earmarked for questionnaires were the strategic level, tactical level and the operational level management as they are all involved in organization turnaround process. Data analysis and interpretation was done quantitatively based on descriptive statistics such as measures of location (mean) and measures of dispersion (standard error mean) as well as inferential statistics mainly, the bivariate Pearson correlation, multi-linear regressions, Analysis of Variance and the stepwise multiple regression. The hypotheses was tested at 95 percent confidence level (level of significance, α = 0.05). Data processing and analysis was finally done by the help of the SPSS software Version 24 from which several findings were arrived at, key being that only the reorganization and realignment strategy demonstrated a significant positive relationship to the performance of state owned sugar companies in Kenya, this being a result of both the multiple and stepwise regression analysis. The retrenchment, diversification and modernization strategy presented insignificant results to organizational performance though the correlation studies showed moderate positive relationship to organizational performance for all the independent variables under study. The study concluded with an emphasis on the reorganization and realignment strategy as the key catalysts for successful turnaround process. Key recommendation was the adoption of reorganization strategy and that realignments should be done to cut on the costs and ensure efficiency as a cost reduction strategy. Diversification strategy did not prove worth going for during turnaround and it was recommended that they be applied differently from the approach used by the companies under study and also cautiously as the companies are barely trying to survive at this stage. Modernization strategy also proved not to be a good strategy during turnaround and as such should be applied cautiously. en_US
dc.description.sponsorship Prof. Maurice M. Sakwa, PhD JKUAT, Kenya Dr. Mugambi Fred Mwirigi, PhD KRA, Kenya en_US
dc.language.iso en en_US
dc.publisher JKUAT-COHRED en_US
dc.subject Turnaround Strategies en_US
dc.subject Performance en_US
dc.subject State Owned Sugar Companies in Kenya en_US
dc.title Turnaround Strategies and Performance of State Owned Sugar Companies in Kenya en_US
dc.type Thesis en_US

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