This study explains the main corporate governance models used in the United States of America, United Kingdom, Germany and Japan by analyzing their similarities, differences, strengths and weaknesses. In addition, the possibility of future convergence between these models is discussed. Two types of corporate governance models are used in the world: Shareholder and Stakeholder models. In this study, USA, and UK will be analyzed as an example of the shareholder model, whereas Germany and Japan will be discussed as an example of the stakeholder model. The shareholder model emphasizes the benefits of shareholders and the management dominates the decision-making procedure of the companies. The stakeholder model, on the other hand, puts more emphasis on the interests of stakeholders or capital market players such as the workers, suppliers and the public. On the convergence debate, four different arguments are identified: The first and the main one is against convergence seeing it as a distant dream because of the differences between the countries. The second argument supports and expects convergence in the near future. The third argument supports the argument of functional convergence rather than formal convergence. The fourth argument supports the combination of both shareholder and stakeholder models to get effective corporate governance practices.This research supports the first argument which is against convergence, because looking at the differences between the countries in their economic, legal and political frameworks, it is still impossible to suggest convergence. Each country will continue to adopt its style according to its culture and also according to its differing needs.

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Purpose-The purpose of this quantitative study is to investigate and define project success according to software project participants in the Turkish Information Techology sector. In this study, the effect of different project management methodologies and education levels were also considered. Methodology-The study employs a quantitative hypothesis-testing method. The survey instrument of Procaccino, Verner, Shelfer and Gefen (2005) was used in this analysis. In collecting the responses, a 5-point Likert-type scale was used to specify the degree of agreement with each written statement (Procaccino, Verner, Shelfer, & Gefen, 2005). Findings-A total of 211 responses were collected. The demografic analysis shows that 31% (66) of the participants were female and 69% (145) were male. The average age of the survey participants was 33.9 years. The average number of years working in the IT sector was 9.7. Additionally, the analysis showed that 2 responses were missing, and 1 response only included the Kanban method. Interestingly 66 responses (31%) were only Scrum, which is one of the Agile methods. Moreover, 11 responses (5%) were only Waterfall, and 41 responses (19%) included both Waterfall and Scrum. 48.3% (102) of the participants used mixed methods, and 40.8 % (86) used at least one Agile method. Conclusion-During the analysis of survey results, factor analysis, The Kruskal-Wallis test, correlation analysis, regression analysis were used. Factor analysis was applied and nine factors were found and explained 63.526% of the measurement. These factors were: personal growth, customer requirements, rewards, interpersonal relations, team factors, management, project output, and personal factors. Difference analysis was applied to the demographic variables. As a result, it was found that gender, age group, job position, and education level did not cause a difference in the definition of project success. Work experience created a significant difference in the project output factors and project management methodology created a significant difference in the team factors. As a result of the correlation analysis, in the first correlation, the project output factors and professional growth factors were highly correlated with each other (0.600). The other correlations were as follows: the second correlation is identified between interpersonal relations factors and professional growth factors (0.544), the third correlation was identified between reward and professional growth factors (0.541), the fourth correlation was identified between customers and professional growth factors (0.489), the fifth correlation was identified between team factors and professional growth factors (0.481), and the sixth correlation was identified between personal factors and professional growth factors (0.349). The least correlated variables were the personal and professional growth factors (0.349). According to the regression analysis, the significance was very high (p = 0.008). This meant that the model was statistically significant and a regression...