Mid Sweden University

In interval decision analysis, where input information is provided in terms of intervals or similar formats to represent imprecise input statements instead of using precise numbers for probabilities and consequence values, a vast array of techniques to conduct robustness and sensitivity analysis has emerged. At the same time, it is not straightforward how to relate these techniques to one another in a decision-analytic process and how they, in combination, serve as a source for obtaining insights into how imprecision affects decision evaluations. Therefore, this chapter aims to reflect upon a group of methods for robustness and sensitivity analyses that are compatible with a common framework for analysing decisions under risk, provide a systematic presentation of these, and discuss guidelines for their usage in decision analysis practice.

Implementing electronic health services with a patient-centric focus while adapting to the know-how of local contexts is a challenge. This paper addresses this challenge by establishing a template of modular requirements for designing a viable Electronic Health Record (EHR) system that enables transmission and sharing of patient data across primary, secondary, and specialized care, ensuring versatility in diverse healthcare environments and across varying socio-economic landscapes. The research is anchored in design science and employs an action research strategy, using northern Brazil as empirical case. The approach builds on generic requirements from standards established by the European Union, Fast Healthcare Interoperability Resources (FHIR), and the Swedish ePrescription journal system. These requirements are refined and adapted to the Brazilian context through a participatory method, considering development disparities across municipalities and aligning with national policy. A key feature is the integration of knowledge graphs, which, when combined with fieldwork iterations involving healthcare professionals and patient association representatives, facilitated the extraction of patient-centric requirements. Strategies from Brazilian healthcare policies targeting chronic kidney disease, selected as a significant challenge for specialized healthcare in emergent areas, were incorporated to generalize the design of EHR modules aimed at prevention and monitoring of population at risk. Results support that harmonization towards legacy system is strongly advised and discourage the introduction of systems designed from scratch.

Emerging technologies are often accompanied by optimistic “tech narratives” that emphasize their potential benefits to society. These narratives appear in various sources, including public policy documents, media coverage, and academic literature. However, identifying their origins and underlying rationale can be challenging. This paper addresses the research question (RQ): How can government tech narratives be traced and unveiled? To answer this question, we draw on the theoretical frameworks of “performativity” and “uncertainty assessment” to develop a two-step approach for investigating tech narratives. We apply this methodology to trace a narrative promoting the benefits of artificial intelligence (AI) in the Swedish public sector back to its source, an emerging government AI policy program. Our analysis reveals a hybridization of economic and political interests, as well as a recognized ignorance reflected in the lack of scrutiny of highly uncertain calculations. By presenting this two-step methodology for tracing and critically examining tech narratives, this paper makes a methodological contribution. In applying this approach, we also provide empirical insights into how tech narratives facilitate the materialization of technological infrastructures.

The paper aims to develop a set of key variables that can be used to model accessibility for informed and sustainable regional planning for sparsely populated remote areas. Based on a thematic analysis of empirical data from a Swedish case, the study extracts regional peculiarities related to the concept of regional accessibility. These peculiarities formulate a set of key variables that can be used to develop new accessibility models or expand existing ones to support decision-making at the policy design stage through a knowledge-based approach. The findings of the paper pinpoint characteristics of destinations that unpack the regional accessibility concept. The paper contributes with a fresh perspective on regional planning, addressing the often-overlooked distinct features of sparsely populated remote areas. Based on these insights, the suggested set of key variables reflects the regional peculiarities without neglecting the uniqueness of these areas. The extracted variables may be incorporated in modeling to simulate accessibility dynamics to offer contextually informed perspectives for policymakers. As a result, the findings from this paper strengthen informed decision-making concerning accessibility in planning for sustainable regional development.

The challenges regarding harmonised interoperable e-health services are enormous due to the complexity of the domain, comparatively high demands of privacy and security, implications of storing, sharing, and managing health data as well as unclear definitions and standards for patient's electronic health records. Therefore, the advantages of digitalisation are yet to reach the end user-patient, especially in the emergent regions where digital infrastructure is limited. The focus is on the north and northeast regions of Brazil, where a holistic understanding of the requirements for a digital transformation of the health care system is explored through the lens of an expert panel using a Delphi methodology, complemented by a comparison with related innovations in the digital health domain.

Simulation modeling is an effective tool that enables knowledge-based approaches to support decision-making for complex problems. Agent-based modeling (ABM) simulation is particularly powerful in the visualization of macro-outcomes of individual and group-specific behaviour, for example in urban and regional planning. However, the adoption of ABM in practice often overlooks its capabilities. Ineffective planning sets sparsely populated remote regions to risk of suffering from long-term consequences, such as population decline. In these settings, it is important to bring municipalities into a dialogue to share the advantages of common planning at a regional scale for their mutual advancement. This study aims to explore the potential of applying ABM and its visual capabilities to support regionwide planning. For this purpose, we develop a model of accessibility of a Swedish region to enhance awareness of common problems with regional accessibility and lift the planning focus from a local scale to a regional one. The model in this paper draws on empirical data from interactions with planners in a region of six municipalities with varying degrees of urbanization in a sparsely populated remote area in Sweden. The model visualizes the dynamic changes in accessibility and demonstrates how destination clustering outplays on a higher system level usually overlooked in planning. The simulation of the case shows that aggravated agglomeration effects will prevent municipalities from developing their centers if they do not consider the opportunities in neighbouring areas within the same region. The paper contributes insights that stimulate the adoption of simulation in complex domains, such as public planning that seeks to align local and regional perspectives.

To achieve the recommendation stated in the chapter title, we propose the following:

Stakeholders can be better engaged in energy efficiency decisions through the use of multicriteria models.

Decision-makers should present trade-offs, such as cost and emissions, and combinations of acceptable solutions to various stakeholders such as the public, housing associations, regulatory agencies, and financial institutions.

Decision-makers should adopt a user-centred approach to energy efficiency measures by encouraging stakeholder dialogues around decision-support tools (e.g. multicriteria modelling) to improve understanding of costs and benefits of measures.

Decision-makers should identify opportunities for consensus building and mindset shifts about the wider benefits of energy efficiency measures by emphasising their social considerations.

Using Social Sciences and Humanities (SSH) perspectives can strengthen Science, Technology, Engineering and Mathematics (STEM) led multicriteria models that visualise trade-offs as well as identify plausible conflicts among stakeholders.

The purpose of this paper is to define indicators and measures of accessibility that can support decision-makers in designing policies for sustainable regional development. The study identifies aspects of accessibility that may influence the attractiveness of certain areas for population and infrastructure investments, notably sparsely populated regions that lay outside urban environments. The paper’s findings identify which accessibility indicators are relevant to the peculiarities of sparsely populated areas thereby defining the specific system requirements for possible simulation models. Such models can generate outcomes of policy scenarios that may be used to evaluate the consequences of policy-making. To support this objective, the study identifies the theoretical basis of accessibility indicators and their modeling potentials that address the complexity of the investigated domain. This paper is an important step toward developing a feasible modeling tool capable of generating policy-based scenarios that support effective decision-making in the context of regional planning.

A fundamental element of participatory group decision processes is acknowledging the desires and concerns of the participating stakeholders. That involves reaching out to stakeholders and asking them to provide input, whereby their desires and concerns can be addressed in the decision process. In this paper, we elaborate on a case of a participatory decision process intending to form a municipal growth strategy in northern Sweden, where an increased understanding of stakeholder values was at the forefront of the project. We present the concept of value driver as a means for interpreting and structuring stakeholder value input in participatory processes for decision-makers to gain an increased understanding of the stakeholders’ desires and concerns. In particular, we discuss the aggregation of such value drivers when reaching out to a large set of stakeholders via surveys and how such an approach can inform a participatory decision analysis process. The aim is to provide a conceptual representation of stakeholder values that can inform participatory decision processes seeking compromise solutions, such as how municipal resources should be allocated effectively based on what residents and business representatives find important for living, working, and running businesses in a municipality.