Abstract
References
- Rosenberger, P., & Gritsch, C. (2024). Data-based analysis of experience as an influence on focus in project execution phases. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM), 27, 187-193.
Abstract
Project management models and guidelines focus on standardizing and describing which kind of tasks project managers need to perform and how to perform these tasks. While these frameworks detail such activities, they do not cover how much project managers should perform different tasks depending on their particular project phase and other factors like project size and experience of the team. This article is based on the concept of multivariate regression and optimization being used to improve Project Process Relevance Factors as described in the Ph.D. thesis "Optimized Tailoring of Agile Project Management Frameworks - From Combining Scrum and PMI towards Multivariate Optimization" by Philipp Rosenberger (Rosenberger, 2022). The doctoral dissertation provided the data and scientific approach that was utilized as well in this article. The purpose of the research is to examine how project experience affects the project management activities that must be completed throughout the execution phase in order to optimize the health and success of a project. The data analysis indicated significant similarities in the distribution of emphasize between novice and skilled project management practitioners. After optimizing the distributions of relevance, the results indicate that experienced project managers need to concentrate more on supporting the project process as such. This involves conducting risk responses and overseeing stakeholder participation. In contrast, novice project managers should to focus on managing specific outcome-related project tasks.
References
- Rosenberger, P., & Gritsch, C. (2024). Data-based analysis of experience as an influence on focus in project execution phases. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM), 27, 187-193.
Details
| Primary Language | English |
|---|---|
| Subjects | Software Engineering (Other) |
| Journal Section | Articles |
| Authors | |
| Early Pub Date | July 19, 2024 |
| Publication Date | July 1, 2024 |
| Submission Date | January 16, 2024 |
| Acceptance Date | April 11, 2024 |
| Published in Issue | Year 2024Volume: 27 |
