Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2016. / The aim of this research is to identify and explore the factors affecting information security compliance of information security policies and regulations, in a financial services organisation. The organisation has to comply with information security regulations and legislations by righteousness of its operations in light of the fact that any wrong doing together with misuse of data, are continually expanding. Corporate embarrassments comes about due to rupture of security, results in expanded thoughtfulness regarding corporate consistency. Legislature and policies have been set up to counter information security issues. This legislature and policies are not adequately addressing the compliance issues that arise, but are needed within organisations. Compliance targets are not met due to inconsistent guidelines that turns out to be significant in diminishing the financial position, reputation and security of information. This research further aims to explore whether employees comply with laws and regulations regarding information in an organisation. This is done in order to confirm whether governance and human factors play any significant part in compliance. The research is an exploratory study and specifically analyses the governance function and which stakeholders influence its operations in information compliance. The research investigates certain questions on organisational culture and the human factor, do influence employee’s compliance to laws and regulations. The objectives of the research are to investigate which factors, and how such factors influence compliance of information security policies and compliance with the goal of designing an integrated framework to assist in counteracting these findings. The research is underpinned by the Neo-institutional theory, Agency Theory and Rational choice theory. The Denison organisational cultural model and a framework proposed by von Solms are used as lenses to interpret the data of the research.

Research linking marketing to financial outputs has been gaining significance in the marketing discipline. The pertinent questions are, therefore: how can marketing improve measures of firm performance and draw potential investors to the company, and where is the quantitative proof to back up these assertions? This research investigates the role of marketing expenditures in the context of initial public offerings (IPOs). The proposed theoretical framework comes from marketing and finance literature, and uses econometric models to test the hypotheses. First, we replicate the results of a previous study by Luo (2008) showing a relationship between the firm's pre-IPO marketing spending and IPO underpricing. Next, we extend the previous study by looking at the IPO's long-run returns, types of risk, analyst coverage, and market/industry characteristics. The results of this study, based on a sample of 2,103 IPOs from 1996 to 2008, suggest that increased marketing spending positively impac ts firm performance. We examine different measures of firm performance, such as risk and long-run performance, whose results are important to the firm, its shareholders, and potential investors. This study analyzes the impact marketing spending has on IPO characteristics (IPO underpricing in the short-run and cumulative abnormal returns in the long run); risk characteristics (systematic, unsystematic, bankruptcy risk, and total risk); analyst coverage characteristics (the number of analysts, optimistic coverage, and forecast error) and market characteristics (market volatility and industry type). We control for variables such as firm size, profitability, and IPO characteristics. In this paper, the results show that increased marketing spending lowers underpricing, lowers bankruptcy risk, lowers total risk, leads to greater analyst coverage, leads to more favorable analyst coverage, and lowers analyst forecast error. For theory, this paper advances the literature on the / marketing-financ e interface by extending the market-based assets and signaling theories. For practice, the results indicate that spending more money on marketing before the IPO and disclosing this information produces positive bottom-line results for the firm. KEYWORDS: Marketing-Finance, Risk, Financial Analysts, Marketing Spending, Firm Performance, Marketing Strategy Meets Wall Street, Long-Run Firm Performance, Underpricing, Stock Recommendations, Initial Public Offering, Marketing Strategy, Econometric Model. / by Monica B. Fine. / Thesis (Ph.D.)--Florida Atlantic University, 2012. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2012. Mode of access: World Wide Web.

The principal objective of this study was to investigate process simulation and optimization of an existing offshore natural gas process which needed profitability improvements. Optimization was done using two alternative approaches: a global approach (response surface methodology) or a local approach (successive quadratic programming). The global approach was characterized by process performance at selected case study points throughout the feasible operating region and made use of global information, while the local approach was characterized by numerical iterative computation driven by local information in the neighborhood of a single point in the design space. A Box-Behnken design was used as a second-order response surface design for the estimation of correlation between process simulator design variables and an economic objective function, and the estimation model was then optimized. In the local approach, a process simulator (ASPEN PLUS) with optimization capabilities was used. From the investigation, three major design variables were identified that had significant effects on the objective function of maximum product sales value. The three variables were: the compression ratio of the Production Compressor, the heat duty of the Gas/Gas Exchanger, and the compression ratio of the Expander. The results indicated that profitability of the offshore natural gas process could be improved by greatly (about 60%) increasing the production of raw condensate, even though this meant slightly lower (about 4%) sales of natural gas as a main product. The improvement found, however, was only 7% when the design variables were limited by currently installed equipment. The global approach was found to converge more consistently because once the global quadratic model was calculated, convergence to its unique optimum was simple. On the other hand the local approach had non-unique termination points due to the small effects of some design variables. The global approach provided better engineering insight since the effects of each design variable could be easily calculated from the quadratic model. However, the global approach was less efficient in terms of engineering manpower because of the time required to identify the quadratic model. / Graduation date: 1995

Thesis (M.B.A.)--University of Hong Kong, 1996. / Includes bibliographical references (leaf 140-142).

Thesis (Ph. D.)--UCLA, 2008. / Vita. Includes bibliographical references (leaves 87-92).

Thesis (Ph. D.)--George Washington University, 2002. / Includes bibliographical references (leaves 311-336).

Thesis (J.S.D.)--Stanford University, 1991. / Includes bibliographical references (leaves 170-182).

Thesis (M.Eng.(Control Engineering)--University of Pretoria, 2003. / Abstract in English. Includes bibliographical references.

The purpose of this study was to investigate the efficiency, effectiveness, and impact of learner control when using interactive video as a training tool. Food service managers (H=60) were randomly assigned to two groups, experimental and control. Each group was trained on the subject matter of food service sanitation following the program developed by the National Restaurant Association's Educational Foundation entitled, Applied Foodservice Sanitation: A Coursebook. Students of the control group were trained by the traditional, lecture-pupil technique (LPl. students of the experimental group were trained via interactive video (IV). The students of the experimental group were further randomly assigned to subgroups; limited interactive (L-I) and fully-interactive (F-I). Immediately following training, all students were given a review of the subject matter and then took the certification exam. Using t-tests to analyze scores between groups and multiple regressions to analyze the effect of time on score fc,r the experimental groups, effectiveness, efficiency, and predictability of score based on time-to-train were measured. The findings indicated that the IV program was as effective as the traditional technique and was significantly more efficient. The multiple regression analysis revealed that time was not a predictor of score; however, when students increased their interactivity while using IV programs, learning (effectiveness) increased. Interactive video programs that are designed to be limited-interactive are as effective and can be as efficient as fully-interactive programs. students who trained in small groups tended to score equally with students trained individually. / Ed. D.

Thesis (MBA)--Stellenbosch University, 1999. / ENGLISH ABSTRACT: Neural networks are computer systems that attempt to mimic the operation of the human brain. In contrast to traditional systems these systems can learn and will change their behaviour over time. In the highly competitive business environment of today, neural networks is one of many technologies that can assist organisations in gaining a competitive advantage. Neural networks also find application in the financial services industry. Applications range from corporate distress or failure models to forecasting of stock prices and many others. Generally speaking, neural networks often offer an exciting alternative to traditional methods of forecasting and classification in this industry. Neural networks must be implemented with care and judgement, as their performance is sensitive with respect to their construction and architecture. Neural networks, as with other technologies, rarely operate in isolation. Neural networks can be integrated with expert systems, genetic algorithms, data mining and even traditional statistical and operational research techniques. Integration produces systems in which the whole is greater than the sum of the parts. Neural networks are also researched and applied in the South African financial services industry, both at an academic and commercial level. Indications are that South Africa is not far behind the international community in exploring the benefits of neural networks. / AFRIKAANSE OPSOMMING: Neurale netwerke is rekenaarstelsels wat poog om die werking van die menslike brein na te boots. In kontras met tradisionele stelsels, leer neurale netwerke en verander dus hul gedrag met verloop van tyd. In vandag se hoogs kompeterende besigheids omgewing, is neural netwerke een van vele tegnologieë wat organisasies kan gebruik om ‘n mededingende voordeel te bekom. Neurale netwerke het ook toepassing in die finansiële dienste industrie. Toepassings wissel van korporatiewe mislukkings modelle tot die vooruitskatting van aandele pryse en vele ander. Neurale netwerke bied ‘n opwindende alternatief tot tradisionele modelle vir vooruitskatting en klassifikasie. Toepassings van neurale netwerke moet egter met oorleg plaasvind, aangesien hul prestasie sterk afhanklik is van hul konstruksie en argitektuur. Soos met ander tegnologie, word neurale netwerke selde in isolasie geïmplementeer. Neurale netwerke kan met sukses geïntegreer word met ekspert stelsels, genetiese algoritmes, data ontginnings metodes sowel as tradisionele statistiese of operasionele navorsings metodes. Integrasie bied stelsels wat meer bied as die som van die onafhanklike komponente. Neurale netwerke word ook in die Suid-Afrikaanse finansiële industrie nagevors en toegepas. Alle indikasies dui daarop dat, met betrekking tot die navorsing van voordele van neurale netwerke, Suid Afrika nie ver agter die internasionale gemeenskap is nie.