To enhance preparedness for diverse pandemic situations we aim to predict the performance of various pharmaceutical intervention strategies. We gathered domain experts and ran a series of decision conferences where a scenario-based multi-criteria decision analysis (MCDA) model was interactively defined and implemented. Assuming an influenza pandemic, a micro simulation model was used to estimate societal health impact, a health-economic model was used to estimate economic losses, and expert preferences were elicited to define trade-offs between multiple criteria and synthesize various estimates. Sensitivity analysis to address various forms of uncertainty was also conducted. Nine intervention strategies, including the baseline “no interventions” strategy, were evaluated and ranked under five pandemic scenarios for Sweden's population. We conclude that a scenario-based MCDA approach relying on multiple models for assessment of consequences is instrumental in defining robust interventions and support decision-making at the pre-pandemic and pandemic situations. 

Objectives: To enhance preparedness for diverse pandemic situations by predicting the performance of alternative pharmaceutical intervention strategies.

Methods: We gathered domain experts and ran a series of decision conferences where a scenario-based MCDA model was interactively defined and implemented. Assuming an influenza pandemic, a microsimulation model was used to estimate societal health impact, a health-economic model was used to estimate economic losses, and expert preferences were elicited to define trade-offs between multiple criteria and synthesize various estimates. Sensitivity analysis to address various forms of uncertainty, along with exploration of inter-scenario robustness of strategies, were also conducted.

Results: Nine intervention strategies, including the baseline "no interventions" strategy, were evaluated and ranked under five pandemic scenarios for Sweden’s population. The strategy prioritising vaccination of children and people in medical risk groups performed most robust across the scenarios.

Conclusions: Scenario-based MCDA approach relying on multiple models for consequences assessment is instrumental in defining robust intervention strategies under deep uncertainty and support decision-making at the pre-pandemic and pandemic situations.

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.

The long-term success or failure of a development project is largely shaped by the external context. Therefore, assessment of factors influencing fulfilment of long-term development outcomes is vital for better project planning. In recent decades, the logical framework (logframe) has de facto become a standard tool for planning and managing development interventions. While the logframe requires identification of assumptions and risks regarding the external context, it does not suggest ways to analyse them in a conventional risk assessment manner. Also, the log-frame has been criticised for ignoring uncertainty in project environment along with neglecting external opportunities. Therefore, in this paper we suggest a method for project context analysis that extends the log-frame with scenarios analysis and address aforementioned shortcomings. We implement and demonstrate the application of the method on an international aid development project, discuss the method's potential use-cases, specific limitations and future development.

Studying the case of the subsidy for electric vehicles in Great Britain (“plug-in car grant”), this research suggests an integrated impact assessment approach by coupling policy issue system modeling with stakeholder preference elicitation.

In particular, we utilize fuzzy cognitive mapping to model the policy issue as a dynamic and complex system. We further simulate the subsidy policy in the model to estimate the changes in select policy aspects. The simulation outcomes are assessed through perspectives of stakeholder groups. For the latter task, nine stakeholder groups were identified and profiled by conducting content analysis and applying the novel CAR method.

While the simulation-based impact assessment of public policy proposals allows policy makers to identify the feasible policy options and verify their economic, social and environmental impacts, it does not provide the explicit evaluation of policy options. Multi-criteria decision analysis (MCDA) techniques can support an in-depth performance evaluation of policy options taking into account the preferences of decision makers and stakeholders. These preferences reflect acceptable trade-offs of performance among objectives. This study reviews multi-attribute decision-making (MADM) technique and presents a common policy appraisal format using main evaluation criteria linked to a set of measurable, context dependent attributes. We argue for a rank-based approach for eliciting preferences, select a novel method for attribute weight elicitation, and show how it can be integrated within a public policy multi-criteria evaluation framework. A use case for policymaking, ‘Ultra-Low Emission Vehicles (ULEV) Uptake in UK’, is used for demonstration of the proposed approach for policy decision analysis. This approach seeks to couple systems modelling and simulation of policy scenarios with MCDA, stakeholder analysis and preference elicitation. The outputs can further provide analytical insights in controversy/acceptability of policy options, and consequently guide further policy formulation and the design of better options.

Most research in research areas like e-government, e-participation and open government assumes a democratic norm. The open government (OG) concept is commonly based on a general liberal and deliberative ideology emphasising transparency, access, participation and collaboration, but were also innovation and accountability are promoted. In this paper, we outline a terminology and suggest a method for how to investigate the concept more systematically in different policy documents, with a special emphasis on post-soviet countries. The result shows that the main focus in this regions OG policy documents is on freedom of information and accountability, and to a lesser extent on collaboration, while other aspects, such as diversity and innovation, are more rarely mentioned, if at all.

Corporate reputations are intangible assets that provide organizations with significant market advantages. Nevertheless, too often corporate decisions and actions, being strategically sound within the traditional management paradigm, meet unexpected backlash by key stakeholders, loss of reputation, and inevitable dire consequences for business. Drawing conclusions from the reputation measurement literature, this study further conceptualizes and operationalizes the notion of reputation risk. Having adopted multiple stakeholder view on corporate reputation, this paper presents a format for stakeholder profile, which guides systematic reputation risk identification. Furthermore, we utilize a multi-criteria approach for aggregating reputation risk assessments and prioritizing identified risks. Finally, we demonstrate application of the approach on a state-owned company.

The success of a development intervention is primarily defined by its longer-term results. Information and Communication Technology for Development (ICT4D) projects are no exception. In particular, the external context in which such projects are to be deployed plays a crucial role for achieving better development results. Thus, an analysis of contextual factors is essential for decision-makers at the project proposal screening and evaluation. Guided by the results-based management framework, a tool for influence assessment of contextual factors is designed and presented in this paper. The tool comprises a suggested model for common ICT4D contextual factors and a complementing method for their assessment. The method employs a scenario- based judgments elicitation process for data extraction together with Monte- Carlo simulation for data processing and aggregation. While the tool is not intended for comprehensive and deep analysis, the underlying streamlined process along with the easy to interpret assessment results arguably ensure further wide adoption.

Strategic fit is a crucial criterion for screening strategically important projects. However, this aspect is vague and unquantifiable to employ with conventional quantitative analysis. This study suggests a method to assess strategic fit as relevance of a project to a set of organisation strategic goals in the context of multi-criteria project evaluation. The assessment is done subjectively by means of linguistic values, which are translated into numerical ones by employing a fuzzy logic.