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a b s t r a c tModel-based energy scenarios are a widely used tool for supporting economic and political decision makers. The results of energy modeling and the conclusions deduced therefrom, however, depend on the model input data derived from framework assumptions about future developments in the embedding society, which are deeply uncertain in the long term. The challenge to deal with this 'context uncertainty' in a systematic and comprehensive manner has only recently started to attract intensified attention in energy research; the search for appropriate methods is ongoing. This paper proposes a new concept for the construction of socio-technical energy scenarios, which combines familiar environmental modeling approaches with new developments in qualitative scenario methodology, and demonstrates the possible application of the concept in model-based energy scenario construction.

Energy conversion is a major source of greenhouse gas (GHG) emissions, and energy transition scenarios are a key tool for gaining a greater understanding of the possible pathways toward climate protection. There is consensus in energy research that political and societal framework conditions will play a pivotal role in shaping energy transitions. In energy scenario construction, this perspective is increasingly acknowledged through the approach of informing model-based energy analysis with storylines about societal futures, an exercise we call "socio-technical energy scenario construction" in this article. However, there is a dispute about how to construct the storylines in a traceable, consistent, comprehensive, and reproducible way. This study aims to support energy researchers considering the use of the concept of socio-technical scenarios in two ways: first, we provide a state-of-the-art analysis of socio-technical energy scenario construction by comparing 16 studies with respect to five categories. Second, we address the dispute regarding storyline construction in energy research and examine 13 reports using the Cross-Impact Balances method. We collated researcher statements on the strengths and challenges of this method and identified seven categories of promises and challenges each.

This paper proposes two criteria to assess and compare the quality of (integrated) scenarios, namely scenario traceability and scenario consistency. From a futures research perspective, both are identified as being central challenges to scenario quality. Traceability is a recognized standard of scenario communication but difficult to achieve in practice. Consistency, simultaneously a construction principle and a constitutive element of scenarios, is not easy to accomplish either. Integrated scenario methodologies, i.e., those approaches combining, e.g., 'story and simulation' (SAS), are especially challenged by both issues. In this paper, scenario traceability and scenario consistency are more precisely defined and operationalized to allow for qualitative measurement, assessment and comparisons of different (integrated) scenario methodologies and their resulting socioenvironmental scenarios. The criteria are applied empirically to new forms of integrated scenario methodologies. They serve to analyze two explorative case studies combining the systematic yet qualitative cross-impact balance analysis (CIB) with simulation. The criteria allow illuminating whether and on what dimensions and levels these new forms of integrated scenario methodologies do (or do not) support scenario consistency and scenario traceability. The empirical analysis shows that new integrated scenario methodologies combining CIB with numerical simulation present some new answers to the traceability and consistency challenges of classical SAS approaches. The application suggests that the two criteria are appropriate and useful for assessing scenario quality from an academic perspective. Still, further research is needed to understand the relation of traceability and consistency to additional quality criteria that influence the practical usefulness of scenarios from a policy advice-oriented perspective.

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The successful implementation of Pervasive Computing technologies in healthcare does not only depend on technical issues but also on acceptability and acceptance issues. In this paper we focus on factors that facilitate or inhibit user acceptance of Pervasive Computing in healthcare. We present selected findings of the research project 'PerCoMed -Pervasive Computing in Healthcare'. The project is based on two case studies in pre-and post-clinical healthcare. In the first study, the potential of Pervasive Computing technologies for the treatment of acute cardiovascular diseases is investigated, in the second case study, the potential for the treatment of multiple sclerosis (MS) is evaluated. A qualitative user acceptance analysis of the two case studies shows the following results: the main factor of user acceptance is the perceived medical usefulness. Furthermore, acceptance is strongly inhibited if data privacy or if subjective norms are violated. Usability only presents a decisive factor of acceptance if problems with usability reduce the perceived usefulness.