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Multi-stakeholder Preference Analysis in Ex-ante Evaluation of Policy Options - Use Case: Ultra Low Emission Vehicles in UK
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Mid Sweden University, Sweden.
2016 (English)In: Electronic Participation: 8th IFIP WG 8.5 International Conference, ePart 2016, Guimarães, Portugal, September 5-8, 2016, Proceedings / [ed] Efthimios Tambouris, Panos Panagiotopoulos, Øystein Sæbø, Maria A. Wimmer, Theresa A. Pardo, Yannis Charalabidis, Delfina Sá Soares, Tomasz Janowski, Springer, 2016, p. 176-188Conference paper, Published paper (Refereed)
Abstract [en]

While the simulation-based impact assessment of public policy proposals allows policy makers to identify the feasible policy options and verify their economic, social and environmental impacts, it does not provide the explicit evaluation of policy options. Multi-criteria decision analysis (MCDA) techniques can support an in-depth performance evaluation of policy options taking into account the preferences of decision makers and stakeholders. These preferences reflect acceptable trade-offs of performance among objectives. This study reviews multi-attribute decision-making (MADM) technique and presents a common policy appraisal format using main evaluation criteria linked to a set of measurable, context dependent attributes. We argue for a rank-based approach for eliciting preferences, select a novel method for attribute weight elicitation, and show how it can be integrated within a public policy multi-criteria evaluation framework. A use case for policymaking, ‘Ultra-Low Emission Vehicles (ULEV) Uptake in UK’, is used for demonstration of the proposed approach for policy decision analysis. This approach seeks to couple systems modelling and simulation of policy scenarios with MCDA, stakeholder analysis and preference elicitation. The outputs can further provide analytical insights in controversy/acceptability of policy options, and consequently guide further policy formulation and the design of better options.

Place, publisher, year, edition, pages
Springer, 2016. p. 176-188
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9821
Keywords [en]
Public policy analysis, multi-criteria decision analysis, stakeholders, preference elicitation, decision support tools, ultra low emission vehicles
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-135435DOI: 10.1007/978-3-319-45074-2_14ISBN: 978-3-319-45073-5 (print)ISBN: 978-3-319-45074-2 (print)OAI: oai:DiVA.org:su-135435DiVA, id: diva2:1045219
Conference
8th IFIP WG 8.5 International Conference, ePart 2016, Guimarães, Portugal, September 5-8, 2016
Available from: 2016-11-08 Created: 2016-11-08 Last updated: 2018-08-29Bibliographically approved
In thesis
1. Design and Investigation of a Decision Support System for Public Policy Formulation
Open this publication in new window or tab >>Design and Investigation of a Decision Support System for Public Policy Formulation
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The ultimate aim of support for public policy decision making is to develop ways of facilitating policymaking that can create policies that are consistent with the preferences of policymakers and stakeholders (such as an increase in economic growth, the reduction of social inequalities, and improvements to the environment), and that are at the same time based on the available knowledge and evidential information.

Using the design science research methodology, an iterative design process was followed to build and evaluate a research artefact in the form of an analytical method that is also operationalised as a decision support system (DSS) – in order to facilitate the problem analysis, the impact assessment and the decision evaluation activities carried out at the policy formulation stage of the policymaking process. The DSS provides a web-based, user-friendly interface for two main software modules: (i) a tool for modelling and simulation of policy scenarios; and (ii) a tool for multi-criteria evaluation of policy decisions. The target end-users of the DSS tools are policymakers, the support staff of politicians, policy analysts and researchers within governmental departments and parliaments at the various institutional levels of the European Union.

The proposed model-based decision support approach integrates systems thinking, problem structuring methods and multi-criteria decision analysis, in what can be described as a ‘sense-making’ approach. A new policy-oriented quantitative problem structuring method is introduced in this research, the ‘labelled causal mapping’ method, which aims to reduce the cognitive overload involved in representing complex mental models using system dynamics simulation modelling in order to facilitate knowledge representation and system analysis. One contribution of this work is an object-oriented implementation of a prototype tool for systems modelling and simulation of policy decision situations based on the labelled causal mapping method. The method provides a basis for further computational decision analysis. We proposed criteria models and data formats for common (generic) policy appraisal, and a preference elicitation method for in-depth decision evaluation based on the results of scenario simulation and the preferences of decision makers and stakeholder groups.

The artefact evaluation clarifies how well the proposed approach and the DSS tool prototype support a solution to the problem and the extent to which the outcomes in two policy analysis use cases are useful in terms of output analysis and knowledge synthesis.

The contributions of this research to theory and practice were articulated based on the design knowledge obtained through an iterative design process, notably the emergence of the concepts of transparency and intelligibility in policymodelling, (i.e., the need for explicit and interpretable models that can provide justification of a specific decision).

Place, publisher, year, edition, pages
Stockholm: Computer and Systems Sciences, Stockholm University, 2018. p. 258
Series
Report Series / Department of Computer & Systems Sciences, ISSN 1101-8526 ; 18-010
Keywords
Systems Thinking, Prescriptive Policy Analysis, Policy modelling and Simulation, ICT for governane, Sense4us, Policy Impact Assessment, Scenario Planning, Knowledge synthesis
National Category
Computer Sciences Public Administration Studies
Research subject
Computer and Systems Sciences
Identifiers
urn:nbn:se:su:diva-159437 (URN)978-91-7797-426-0 (ISBN)978-91-7797-427-7 (ISBN)
Public defence
2018-10-12, Lilla hörsalen, NOD-huset, Borgarfjordsgatan 12, Kista, Sweden, 13:00 (English)
Opponent
Supervisors
Note

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 8: Submitted.

Available from: 2018-09-19 Created: 2018-08-29 Last updated: 2018-09-19Bibliographically approved

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