Eric John Ward, University College, London (UCL)


Aron Larsson, DSV


David Sundgren, DSV



Anton Talantsev
Anton Talantsev

The long-term success or failure of a strategic project is largely shaped by its context. Therefore, the assessment of the external factors influencing the fulfilment of project long-term goals is vital for the effective project appraisal and planning.

However, many projects are embedded in a complex, dynamic, and multi-stakeholder environment creating a condition of severe uncertainty. These aspects make both the assessment of a project context and the prediction of the outcomes challenging. In the face of these challenges, the overall aim of this thesis is to propose both conceptual thinking and practical approaches for the project context analysis.

To this end, the presented work has adopted a design science research and formal approaches from the fields of systems analysis, risk assessment and decision sciences, to systematically understand the problems of the context analysis, and to develop and evaluate the solutions. This thesis presents novel methods for assessing project context, which have been implemented in the following decision support tools:

• a tool for strategic fit assessment,

• a tool for context factor analysis,

• a tool for corporate reputation risk assessment,

• a toolkit for stakeholder-based impact assessment of a policy,

• a toolkit for assessing intervention strategies in pandemics.

The proposed methods have been applied and evaluated in case-studies within various domains, such as business strategy, development aid, energy policy, and public healthcare. These studies have demonstrated the adequacy and usefulness of the proposed methods for supporting decision making in situations with varying levels of uncertainty. This indicates the potential of the methods to improve the effectiveness of the project appraisal practice.

This research has concluded that a project context is a multi-faceted concept, and, thus, no single method is capable of the comprehensive assessment. Instead, an assembly of specialised but complementary approaches is required to adequately model and assess both the various aspects of the context and the uncertainties of different types.

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