I intervallbeslutsanalys, där ingångsinformation tillhandahålls i termer av intervall eller liknande format för att representera oprecisa indatasatser istället för att använda exakta siffror för sannolikheter och konsekvensvärden, har ett stort utbud av tekniker för att utföra robusthets- och känslighetsanalyser dykt upp. Samtidigt är det inte okomplicerat hur man relaterar dessa tekniker till varandra i en beslutsanalytisk process och hur de i kombination fungerar som en källa för att få insikter om hur oprecision påverkar beslutsutvärderingar. Därför syftar detta kapitel till att reflektera över en grupp metoder för robusthets- och känslighetsanalyser som är kompatibla med ett gemensamt ramverk för analysera beslut under risk, och ge en systematisk presentation av dessa och diskutera riktlinjer för deras användning i beslutsanalyspraxis.

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, and to 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.

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.

Syftet med denna forskning var att utveckla ett metodiskt ramverk som skulle kunna tillämpas för policybildning i situationer med en hög nivå av osäkerhet och heterogenitet av befintliga åsikter bland involverade intressenter om riskreducering och hantering såsom covid-19 pandemisk risk. I detta dokument presenterar vi ett sådant ramverk och dess tillämpning för beslutsfattande i Botswana för att mildra covid-19-pandemin. Syftet med den föreslagna modellen är dubbelt: för det första att förse beslutsfattare med tillförlitlig och användbar epidemiologisk modellering eftersom åtgärder för att begränsa spridningen av covid-19-viruset till en början till stor del baserades på olika epidemiologiska riskbedömningar. För det andra, med tanke på att vissa uppsättningar åtgärder som antagits i andra delar av världen successivt medför höga eller till och med mycket höga sociala och ekonomiska kostnader för de länder som antog dessa åtgärder, tillhandahöll vi en beslutsstödsmodell med flera kriterier som kunde användas för att att väga olika politiska tillvägagångssätt för att bekämpa virusspridningen med hänsyn till lokala konsekvensbedömningar inom en mängd olika samhällsområden. Vi beskriver hur utformningen av en nationell covid-19-strategi och policy i Botswana 2020 hjälptes till genom att använda IKT-beslutsstödsmodeller som en viktig informationskälla. Därefter presenterar vi simuleringsmodellen för virusspridning och dess resultat som är kopplade till en multikriteriebeslutsstödsmodell. Slutligen diskuterar vi hur ramverket kan vidareutvecklas för Botswanas behov för att optimera riskhanteringsalternativ vid hantering av covid-19 och andra pandemiscenarier. Det betydande forskningsbidraget är att flytta fram forskningsfronten när det gäller en metodik för att inkludera heterogenitet i åsikter och identifiering av kompromisslösningar i policyrelevanta diskurser under en hög grad av osäkerhet.

The purpose of this research was to develop a methodological framework that could be applied for policy formation in situations having a high level of uncertainty and heterogeneity of existing opinions among involved stakeholders about risk mitigation and management such as COVID-19 pandemic risk. In this paper, we present such a framework and its application for policy decision-making in Botswana for mitigating the COVID-19 pandemic. The purpose of the proposed model is twofold: firstly, to supply decision-makers with reliable and usable epidemiologic modelling since measures to contain the spread of the COVID-19 virus were initially to a large extent based on various epidemiologic risk assessments. Secondly, given that some sets of measures adopted in other parts of the world were progressively imposing high or even very high social and economic costs on the countries which adopted these measures, we provided a multi-criteria decision support model which could be used in order to weigh different policy approaches to combat the virus spread taking into consideration local impact assessments across a variety of societal areas. We describe how the formulation of a national COVID-19 strategy and policy in Botswana in 2020 was aided by using ICT decision support models as a vital information source. Then we present the virus spread simulation model and its results which are connected to a multi-criteria decision support model. Finally, we discuss how the framework can be further developed for the needs of Botswana to optimise hazard management options in the case of handling COVID-19 and other pandemic scenarios. The significant research contribution is on advancing the research frontier regarding a methodology of including the heterogeneity of views and identification of compromise solutions in policy-relevant discourses under a high degree of uncertainty.

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.

The concept of “GovTech” has emerged as a business-oriented model and practice for enabling the public sector to take advantage of digital solutions as service towards the citizen, while the private for-profit sector is responsible for innovation, development, and profitable maintenance of the GovTech services, hence making the whole area of solutions seemingly desirable to invest in.

However, the current literature on stakeholder views of the GovTech market remains rather generic, less connected to concrete examples of GovTech solutions as these are perceived within a given and delimited GovTech domain. The objective of this paper is to apply exploratory quantitative data analysis for phenomena detection and evaluation. We explore to what extent the constructs of the area actually are disparate and ill-suited to use for quantitative GovTech research, and find five factors showing a degree of mistrust between the public and private sector and prescribe further research into developing constructs that can cut across the research area, enabling for a build-up of a stronger theoretical base for tech business in the public-private markets.