Trust remains the foundation of the financial system, whether digital or physical. Financial trust structures and governance are fundamental to the stability and perception of money in both traditional and digital environments. Financial systems are thus built on two interconnected forms of trust: public trust in societal institutions and inter-organisational trust among financial actors such as banks, businesses, and state agencies. At the core of many hybrid operations lies the objective of weakening public trust in state institutions and social cohesion. Everyday infrastructures such as digital payment systems become plausible targets in a hybrid threat campaign. This study therefore investigates the following research question, ‘How do different hybrid threat scenarios impact key value dimensions of consumer trust in digital payment systems?’, through a scenario-based multi-criteria threat evaluation survey conducted in Sweden, Finland, and Germany. The study suggests that hybrid threat preparedness must include psychosocial dimensions of technical diagnostics. Financial trust is simultaneously procedural and emotional, and hybrid actors are increasingly adept at targeting both. The evidence affirms the need for a re-conceptualisation of digital financial infrastructure as a domain of national security.

Evaluating innovation and optimising its role in the inventions is fundamental for applied research, that requires planning the use of available resources. Traditional assessment approaches often miss to capture how innovation stagnates between the ideation and prototyping phases (the Valley of Death), and to learn how innovation emerges from intermediate-steps contributed by individuals. This paper focuses on tracing innovation as an approach enabling mapping of pathways of intermediate-steps and opportunities for valorising unplanned outcomes. We adopt a qualitative case study to explore how innovation pathways can be conceptualised through technological readiness levels. The operational settings of an EU-funded project defined the boundaries of the study. A network analysis explored relationships among themes that emerged from respondents involved in the activities, following an inductive approach to derive themes from data. Findings indicate that intermediate innovation steps, including failures, are viewed as cumulative contributions to novelty. Their documentation is seen as an investment for unlocking latent value embedded in distributed knowledge. Within this scope, we outline a blockchain-based knowledge graph as a proof-of-concept for tracing cumulative contributions, identifying breakthroughs leading to technological maturity and supporting generation of hypothesis grounded on experimental trials. As a result, we suggest that paths recombining prior knowledge into novelty encode latent value that can be interpreted as a function of the network topology, and propose a conceptual framework for analysing value by means of information theory metrics applicable to innovation graphs.

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.