An empirical investigation of IT project success in developing countries

The high rate of unsuccessful IT projects has been examined by many researchers world-wide in order to identify IT project critical success factors (CSFs). Using a framework from previous literature, this research examines four organizational factors (Top management support, project team competencies, communication management, and project management) that affect IT projects success in Saudi Arabian public organizations and compares the outcomes with findings in Malaysian multinational companies. Furthermore, organizational culture as a moderator has been deployed in the model to examine its impact on the relationships between CSFs and IT project success. A quantitative approach using a survey questionnaire method was used to collect the data. The questionnaires were distributed to CIOs in Saudi Arabian public organizations. PLS-SEM was used to analyze the collected data and test the relevant hypotheses. The outcomes showed that there were some similarities and differences between Saudi Arabia and Malaysia. In both countries, IT project success was influenced by project management; however, it was not influenced by project team competency. Furthermore, the outcomes showed that IT project success in Saudi Arabia was influenced by top management support while it is influenced by communication management in Malaysia. Finally, it was found that organizational culture moderates the relationships between top management support and project management and IT project success in Saudi Arabia, while the organizational culture moderates the relationships between communication management and project management and IT project success in Malaysia

Three Dimensional Attitude Estimation Via The TRIAD Algorithm and A Time-Varying Complementary Filter

ABSTRACT An innovative implementation of attitude estimation in 3 degrees of freedom (3-DOF) combining the TRIAD algorithm [1] and a time-varying nonlinear complementary filter (TVCF) is derived. This work is inspired by the good performance of the TVCF in 1-DOF [2] developed for applications limited to small mobile platforms with low computational power. To demonstrate robust 3-DOF estimation, information from vector and rate-gyroscope measurements are fused. Simulation and experimental results demonstrate comparable performance to the extended Kalman filter (EKF) and improved performance over alternative methods such as sole gyroscope rate-integration and the TRIAD algorithm without the TVCF as a pre-filter