Multi-stakeholder Preference Analysis in Ex-ante Evaluation of Policy Options - Use Case: Ultra Low Emission Vehicles in UK

  • Anton Talantsev
  • Osama IbrahimEmail author
  • Aron Larsson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9821)


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.


Public policy analysis Multi-criteria decision analysis Stakeholders Preference elicitation Decision support tools Ultra low emission vehicles 


  1. Belton, V., Stewart, T.J.: Multiple Criteria Decision Analysis: An Integrated Approach. Kluwer Academic Publishers, Berlin (2002)CrossRefGoogle Scholar
  2. Comes, T., Hiete, M., Wijngaards, N., Schultmann, F.: Decision maps: a frame-work for multi-criteria decision support under severe uncertainty. Decis. Support Syst. 52, 108–118 (2011)CrossRefGoogle Scholar
  3. Crain, W.F.: Multiattribute weight determination: elicitation & approximation. George Mason University (2003).
  4. Danielson, M., Ekenberg, L., Idefeldt, J., Larsson, A.: Using a software tool for public decision analysis: the case of Nacka municipality. Decis. Anal. 4(2), 76–90 (2007)CrossRefGoogle Scholar
  5. Danielson, M., Ekenberg, L.: The CAR method for using preference strength in multi-criteria decision making. Group Decis. Negot. 25(4), 775–797 (2015a)CrossRefGoogle Scholar
  6. Danielson, M., Ekenberg, L.: Using surrogate weights for handling preference strength in multi-criteria decisions. In: Kamiński, B., Kersten, G.E., Szapiro, T. (eds.) GDN 2015. LNBIP, vol. 218, pp. 107–118. Springer, Heidelberg (2015b)CrossRefGoogle Scholar
  7. Drake, J.M., Kulkarni, A.V., Kestle, J.: Endoscopic third ventriculostomy versus ventriculoperitoneal shunt in pediatric patients: a decision analysis. Child’s Nerv. Syst. 25, 467–472 (2009)CrossRefGoogle Scholar
  8. Franco, L.A., Montibeller, G.: Facilitated modelling in operational research. Eur. J. Oper. Res. 205, 489–500 (2010)CrossRefzbMATHGoogle Scholar
  9. Gou, H.C., Liu, L., Huang, G.H., Fuller, G.A., Zou, R., Yin, Y.Y.: A system dynamics approach for regional environmental planning and management: a study for the Lake Erhai Basin. J. Environ. Manage. 61, 93–111 (2001)CrossRefGoogle Scholar
  10. Hansson, K., Danielson, M., Ekenberg, L.: A framework for evaluation of flood management strategies. J. Environ. Manage. 86(3), 465–480 (2008)CrossRefGoogle Scholar
  11. Hülle, J., Kaspar, R., Möller, K.: Multiple criteria decision-making in management accounting and control – state of the art and research perspectives based on a bibliometric study. J. Multi Criteria Decis. Anal. 18(5–6), 253–265 (2011)CrossRefGoogle Scholar
  12. Kivunike, F.N., Ekenberg, E., Danielson, M., Tusubira, F.F.: Towards an ICT4D evaluation model based on the capability approach. Int. J. Adv. ICT Emerg. Reg. 7(1), 1–7 (2014)Google Scholar
  13. Larsson, A., Ibrahim, O.: Modeling for policy formulation: causal mapping, scenario generation, and decision evaluation. In: Tambouris, E., Panagiotopoulos, P., Sæbø, Ø., Tarabanis, K., Wimmer, M.A., Milano, M., Pardo, T. (eds.) ePart 2015. LNCS, vol. 9249, pp. 135–146. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  14. Miettinen, K., Hämäläinen, R.P.: How to benefit from decision analysis in environmental life cycle assessment (LCA). Eur. J. Oper. Res. 102, 279–294 (1997)CrossRefzbMATHGoogle Scholar
  15. Montibeller, G., Gummer, H., Tumidei, D.: Combining scenario planning and multi-criteria decision analysis in practice. J. Multi-Criteria Dec. Anal. 14(1–3), 5–20 (2006)CrossRefGoogle Scholar
  16. Quade, E.S.: Analysis for Public Decisions. Elsevier, New York (1982)Google Scholar
  17. Riabacke, A., Larsson, A., Danielson, M.: Conceptualisation of the gap between managerial decision-making and the use of decision analytic tools. Int. J. Inf. Technol. Bus. Manage. 21(1), 30–46 (2014)Google Scholar
  18. Riabacke, M., Danielson, M., Ekenberg, L.: State-of-the-art prescriptive criteria weight elicitation. Adv. Dec. Sci. 2012, 24 p. (2012)Google Scholar
  19. Sarabando, P., Dias, L.C.: Simple procedures of choice in multicriteria problems without precise information about the alternatives’ values. Comput. Oper. Res. 37(12), 2239–2247 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  20. Schroeder, M.J., Lambert, J.H.: Scenario‐based multiple criteria analysis for infrastructure policy impacts and planning. J. Risk Res. 14(2), 191–214 (2011)Google Scholar
  21. Stewart, T.J.: A critical survey on the status of multiple criteria decision making theory and practice. Omega 20(5–6), 569–586 (1992)CrossRefGoogle Scholar
  22. Wang, J., Zionts, S.: Using ordinal data to estimate cardinal values. J. Multi-Criteria Dec. Anal. 22, 185–196 (2015)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  1. 1.Department of Computer and Systems SciencesStockholm UniversityStockholmSweden
  2. 2.Department of Information and Communications SystemsMid Sweden UniversitySundsvallSweden

Personalised recommendations