Background: Effort estimation is one of the cornerstones in project management with the purpose of creating efficient planning and the ability to keep budgets. Despite the extensive research done within this area, one of the biggest and most complex problems in project management within software development is still considered to be the estimation process. Objectives: The main objectives of this thesis were threefold: i) firstly to define the characteristics for a large project, ii) secondly to identify factors causing inaccurate effort estimates and iii) lastly to understand how the identified factors impact the effort estimation process, all of this within the context of large-scale agile software development and from the perspective of a project team.Methods: To fulfill the purpose of this thesis, an exploratory case study was executed. The data collection consisted of archival research, questionnaire, and interviews. The data analysis was partly conducted using the statistical software toolStata.Results: The definition of a large project is from a project team’s perspective based on high complexity and a large scope of requirements. The following identified factors were identified to affect the estimation process in large projects: deficient requirements, changes in scope, complexity, impact in multiple areas, coordination, and required expertise, and the findings indicate that these are affecting estimation accuracy negatively. Conclusions: The conclusion of this study is that besides the identified factors affecting the estimation process there are many different aspects that can directly or indirectly contribute to inaccurate effort estimates, categorized as requirements, complexity, coordination, input and estimation process, management, and usage of estimates.

There are several critical success factors suggested for why agile software development projects succeed, including organisational and process factors. Although there are an increasing number of identified critical success factors, IT professionals lack the modelling techniques and the theoretical framework to help them meaningfully understand their influences. To solve this problem, this study developed a model by employing the following theories: Theory of Reasoned Action (TRA), Theory of Planned Behaviour (TPB), and Unified Theory of Acceptance and Use of Technology (UTAUT) to create a fit model for agile software development projects. The research sought to answer the question: What are the critical success factors that influence the success of agile software development projects? The literature review considers the continued failure of agile and traditional software development projects which have led to the consideration of, and dispute over, critical success factors — the aspects most vital to a methodology’s success. Though TRA, TPB and UTAUT have previously been applied to agile methodologies, empirical models have not been completely integrated to develop a fit model. This research sought to fill this gap. Data was collected in South Africa through a web-based survey using structured questionnaires and an interview guide. Face-to-face interviews were done to identify the critical success factors in agile projects. The data was captured and analysed for descriptive statistics, convergent and discriminant validity, composite and internal reliability, and correlation in order to inform the structural equation modelling (SEM). SEM was used to test the research model and hypotheses to answer the research questions. The results informed development of a comprehensive model that could provide guidelines to the agile community. The study contributes towards understanding the critical success factors for agile projects. It examined direct, indirect and moderating effects, and the findings contribute towards developing a framework to be used by agile professionals. These key result shows that organisational factors have a great influence on performance expectancy characteristics. To ensure success of agile projects, managers are advised to focus on the effect of the organisation’s environment, culture and policies on performance and effort expectancy. / School of Computing / Ph. D. (Computer Science)