Saudi Cultural Missions Theses & Dissertations

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    Corporate Governance mechanisms and Dividend Payout: An Empirical study of the UK listed firms.
    (Kingston University of London, 2023-12) Alzahrani, Amal; Elmarzouky, Mahmoud
    In this dissertation we explore the link of corporate governance mechanisms and dividends payout. The corporate governance mechanisms employed are board size, board independence, CEO duality, and managerial shareholding. In addition to the above we used control variables to ensure that the results are accurate. In order to investigate the link between corporate governance mechanisms and dividends payout. We used a sample of UK listed firms in the stock exchange for the years 2015 -2021. This research used an OLS regression to estimate the empirical model and to control the heteroskedasticity and employed a fixed effects of year and industry. Our results show a significant positive correlation between board size, CEO shareholdings percentage and dividends payout. Whiles it showed a negative relationship between board independence, CEO duality and dividends payout. This result is beneficial as it adds to the body of knowledge on how firms can use CG mechanisms to enhance dividends payout and can guide managers in formulating effective dividend policies by considering the factors influencing dividend payout as revealed in this study.
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    LOW SENSITIVITY DESIGN OF NONLINEAR SYSTEMS USING LINEARIZED MODELS
    (Wichita State University, 2024-05-17) Alotaibi, Jameelah Saad; Delillo, Thomas
    Low sensitivity linearized models ensure that the predictability and stability of nonlinearized models are achieved in a very assertive manner. The stability, which characterizes the trajectory in terms of equilibrium point, is of utmost importance. It should be noted that an equilibrium is considered asymptotically stable when there is a Lyapunov function present. One must not overlook the fact that the linear optimal state feedback for quadratic criteria, which do not include sensitivity, has the remarkable ability to automatically reduce sensitivity. It is an undeniable fact that the maximization of performance measures or the minimization of cost functions plays a crucial role in ensuring optimization. The primary focus of the research conducted was to significantly reduce the adverse impact of uncertainty on low sensitivity nonlinear models. To achieve this, a single perturbation technique was employed to convert the high-order system into a reduced model. This approach not only simplifies implementation but also effectively mitigates the impact of uncertainty. Additionally, the application of the KF estimator further enhances the reliability of the methodology. In this particular case, the static output feedback gain emerges as a more static and reliable output feedback control method that eliminates the need for an observer to estimate the states of system.
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