Purpose: The purpose of this paper is to enhance the understanding of what project complexity is, what drivers and factors that influence complexity and how consequences for organizational performance can be assessed. Design/methodology/approach: The research is explanatory and based on literature review, model development, interviews and case studies. The model is validated through a case study. Findings: The findings are a model for identifying and analyzing complexity drivers and complexity factors. The model starts with generic complexity drivers such as ambiguity, uncertainty, unpredictability and pace. These drivers are in each project influenced by nature and by socio-political, economic and technological surroundings to result in complexity factors that are specific to the project analyzed. The model can be used to analyze project complexity and to define requirements for the organization of the project and guidelines for the execution. Research limitations/implications: The research is limited to large projects with a technical delivery of some kind of facilities. Practical implications: The model can be used to assess the required capability of the organization for successful project execution. Originality/value: The contribution of the research is a new model for understanding project complexity. The distinction between project complexity drivers and factors is essential as well as the taxonomy for the factors building on and adding to already published research.

The uncertainty management theory has become well established over the last 20–30 years. However, the authors suggest that it does not fully address why opportunities often remain unexploited. Empirical studies show a stronger focus on mitigating risks than exploiting opportunities. This paper therefore addresses why so few opportunities are explored in large projects. The theory claims that risks and opportunities should be equally managed in the same process. In two surveys, conducted in six (private and public) companies over a four-year period, project managers stated that uncertainty management is about managing risk and opportunities. However, two case studies from 12 projects from the same companies revealed that all of them had their main focus on risks, and most of the opportunities were left unexploited. We have developed a theoretical explanation model to shed light on this phenomena. The concept is a reflection based on findings from our empirical data up against current project management, uncertainty, risk and stakeholder literature. Our model shows that the threshold for pursuing a potential opportunity is high. If a potential opportunity should be considered, it must be extremely interesting, since it may require contract changes, and the project must abandon an earlier-accepted best solution.

To add value to project performance and help obtain project success, a new framework for decision making in projects is defined. It introduces the project decision chain inspired by the supply chain thinking in the manufacturing sector and uses three types of decisions: authorization, selection, and plan decision. A primitive decision element is defined where all the three decision types can be accommodated. Each task in the primitive element can in itself contain subtasks that in turn will comprise new primitive elements. The primitive elements are nested together in a project decision chain.

One-of-a-kind production is project business. In any project, the decision process is of importance for a successful outcome. However, there is a need for a more formal approach to decision-making in projects. We have therefore, developed a model of the decision process. It uses three types of decisions: selection, authorisation and plan decisions. Enterprise models together with the project life cycle form a platform for developing a decision model. The life cycle enables a decision chain, whereas the enterprise models allow decisions at different levels. The horizontal decision chain is linked to physical flow of documents and materials. Vertically, decision-making is hierarchically decomposed into levels of different planning horizons and time periods.

An e-learning approach for project management using the hybrid model has been developed, tested and improved. Two Norwegian universities have developed a continuing education programme at two levels. The client has been three industrial companies in the oil and gas sector. For delivery another two universities outside Norway has participated. The hybrid model contains two plenary sessions using traditional teaching methods. In addition there are a number of virtual sessions using technology enhanced learning including multimedia technology. In addition there is a project assignment to be solved by groups of three course participants. Experience has shown that training based on a combination of on-campus and Web-based is an effective approach. This concept may be significantly more effective than traditional programs with plenary sessions only or with virtual content only.

Projects are today widely used as a business model for private and public sectors and they constitute the preferred model for developing changes in construction, oil and gas, chemical processes, aerospace, defence, etc