Mid Sweden University

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.

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. 

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. 

This paper provides an overview and mapping of needs and use of data related to formal risk analysis within the context of critical infrastructures, including activities of risk assessments and risk modelling as a part of preventive work against major accidents and crises. The aim is to contribute to a greater understanding of the type of data that is actually used in published sources where different risk assessment or risk analysis methods are applied for critical infrastructure protection. The study focuses specifically on the presentation of applications of quantitative or semi-quantitative risk analysis in the scientific literature within the domain of societally important services and critical infrastructures. The survey was delimited to peer reviewed research papers between the years 2010 and 2020 and resulted in a total number of 183 papers subject for evaluation. The results provide insights into the type of data that is used, missing or difficult to obtain for an application of the identified methods. To obtain a comprehensive critical infrastructure risk analysis data needs are related to three different data dimensions; geospatial topology data, socio-economic data, and infrastructure data. However, no databases are currently available with the explicit purpose to support critical infrastructure risk analysis. Even though this is not viewed as a problem in the examined papers, collecting that data is resource intensive which is a barrier for a more systematic use of formal risk analysis methods.

Various societal functions, such as healthcare, freight transports, water supplies and electricity, ensure the daily life, endurance and progress of modern societies. The protection of such critical functions requires comprehensive information processing. Based on evidence from documents on the Swedish planning process STYREL and interviews with entrusted decisionmakers at county administrative boards, municipalities and power grid operators, this study aims to crystallise information pathways and flaws to highlight information filtration and alteration. Analyses of the material reveal a set of information-flawing filters, such as information withholding or loss when sharing, information scarcity in criticality assessments and ad-hoc information creation due to scarcity. Because of these filters, the Swedish process causes an altering of information that affects the quality of decisions and the emergency response plan that relies on them. Thus, this study indicates deficiencies that relate to information sharing, information security and decision-making that pose risks to citizens and businesses.

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.