IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/75025.html
   My bibliography  Save this paper

A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making

Author

Listed:
  • Wulf, David
  • Bertsch, Valentin

Abstract

Multi-Criteria Decision Analysis (MCDA) enables decision makers (DM) and decision analysts (DA) to analyse and understand decision situations in a structured and formalised way. With the increasing complexity of decision support systems (DSSs), it becomes challenging for both expert and novice users to understand and interpret the model results. Natural language generation (NLG) techniques are used in various DSSs to cope with this challenge as they reduce the cognitive effort to achieve understanding of decision situations. However, NLG techniques in MCDA have so far mainly been developed for deterministic decision situations or one-dimensional sensitivity analyses. In this paper, a concept for the generation of textual explanations for a multi-dimensional preferential sensitivity analysis in MCDA is developed. The key contribution is a NLG approach that provides detailed explanations of the implications of preferential uncertainties in Multi-Attribute Value Theory (MAVT). It generates a report that assesses the influences of simultaneous or separate variations of inter-criteria and intra-criteria preferential parameters determined within the decision analysis. We explore the added value of the natural language report in an online survey. Our results show that the NLG approach is particularly beneficial for difficult interpretational tasks.

Suggested Citation

  • Wulf, David & Bertsch, Valentin, 2016. "A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making," MPRA Paper 75025, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:75025
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/75025/1/MPRA_paper_75025.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bertrand Mareschal & Jean Pierre Brans, 1994. "PROMCALC & GAIA: a new decision support system for multicriteria decision aid," ULB Institutional Repository 2013/9349, ULB -- Universite Libre de Bruxelles.
    2. Paul D Ellis, 2010. "Effect sizes and the interpretation of research results in international business," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 41(9), pages 1581-1588, December.
    3. Streimikiene, Dalia & Balezentis, Tomas & Krisciukaitienė, Irena & Balezentis, Alvydas, 2012. "Prioritizing sustainable electricity production technologies: MCDM approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3302-3311.
    4. Kowalski, Katharina & Stagl, Sigrid & Madlener, Reinhard & Omann, Ines, 2009. "Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1063-1074, September.
    5. JosÉ Figueira & Salvatore Greco & Matthias Ehrogott, 2005. "Multiple Criteria Decision Analysis: State of the Art Surveys," International Series in Operations Research and Management Science, Springer, number 978-0-387-23081-8, September.
    6. Hauke Jan & Kossowski Tomasz, 2011. "Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data," Quaestiones Geographicae, Sciendo, vol. 30(2), pages 87-93, June.
    7. Loomes, Graham & Sugden, Robert, 1982. "Regret Theory: An Alternative Theory of Rational Choice under Uncertainty," Economic Journal, Royal Economic Society, vol. 92(368), pages 805-824, December.
    8. Stewart, TJ, 1992. "A critical survey on the status of multiple criteria decision making theory and practice," Omega, Elsevier, vol. 20(5-6), pages 569-586.
    9. Ribeiro, Fernando & Ferreira, Paula & Araújo, Madalena, 2013. "Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: The Portuguese case," Energy, Elsevier, vol. 52(C), pages 126-136.
    10. Jessop, Alan, 2014. "IMP: A decision aid for multiattribute evaluation using imprecise weight estimates," Omega, Elsevier, vol. 49(C), pages 18-29.
    11. Browne, David & O'Regan, Bernadette & Moles, Richard, 2010. "Use of multi-criteria decision analysis to explore alternative domestic energy and electricity policy scenarios in an Irish city-region," Energy, Elsevier, vol. 35(2), pages 518-528.
    12. A Morton & B Fasolo, 2009. "Behavioural decision theory for multi-criteria decision analysis: a guided tour," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 268-275, February.
    13. Bell, Michelle L. & Hobbs, Benjamin F. & Ellis, Hugh, 2003. "The use of multi-criteria decision-making methods in the integrated assessment of climate change: implications for IA practitioners," Socio-Economic Planning Sciences, Elsevier, vol. 37(4), pages 289-316, December.
    14. Durbach, Ian N. & Stewart, Theodor J., 2012. "Modeling uncertainty in multi-criteria decision analysis," European Journal of Operational Research, Elsevier, vol. 223(1), pages 1-14.
    15. Durbach, Ian N. & Stewart, Theodor J., 2009. "Using expected values to simplify decision making under uncertainty," Omega, Elsevier, vol. 37(2), pages 312-330, April.
    16. Hämäläinen, Raimo P. & Alaja, Susanna, 2008. "The threat of weighting biases in environmental decision analysis," Ecological Economics, Elsevier, vol. 68(1-2), pages 556-569, December.
    17. Zimmermann, H. -J., 2000. "An application-oriented view of modeling uncertainty," European Journal of Operational Research, Elsevier, vol. 122(2), pages 190-198, April.
    18. Haim Levy, 1992. "Stochastic Dominance and Expected Utility: Survey and Analysis," Management Science, INFORMS, vol. 38(4), pages 555-593, April.
    19. Tommi Tervonen, 2014. "JSMAA: open source software for SMAA computations," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(1), pages 69-81.
    20. Greening, Lorna A. & Bernow, Steve, 2004. "Design of coordinated energy and environmental policies: use of multi-criteria decision-making," Energy Policy, Elsevier, vol. 32(6), pages 721-735, April.
    21. Henk Broekhuizen & Catharina Groothuis-Oudshoorn & Janine Til & J. Hummel & Maarten IJzerman, 2015. "A Review and Classification of Approaches for Dealing with Uncertainty in Multi-Criteria Decision Analysis for Healthcare Decisions," PharmacoEconomics, Springer, vol. 33(5), pages 445-455, May.
    22. Løken, Espen, 2007. "Use of multicriteria decision analysis methods for energy planning problems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(7), pages 1584-1595, September.
    23. Danae Diakoulaki & Carlos Henggeler Antunes & António Gomes Martins, 2005. "MCDA and Energy Planning," International Series in Operations Research & Management Science, in: Multiple Criteria Decision Analysis: State of the Art Surveys, chapter 0, pages 859-890, Springer.
    24. Theodor J Stewart, 2005. "Dealing with Uncertainties in MCDA," International Series in Operations Research & Management Science, in: Multiple Criteria Decision Analysis: State of the Art Surveys, chapter 0, pages 445-466, Springer.
    25. Hodgkin, Julie & Belton, Valerie & Koulouri, Anastasia, 2005. "Supporting the intelligent MCDA user: A case study in multi-person multi-criteria decision support," European Journal of Operational Research, Elsevier, vol. 160(1), pages 172-189, January.
    26. Pohekar, S. D. & Ramachandran, M., 2004. "Application of multi-criteria decision making to sustainable energy planning--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 8(4), pages 365-381, August.
    27. A Jessop, 2011. "Using imprecise estimates for weights," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1048-1055, June.
    28. Mateos, A. & Jimenez, A. & Rios-Insua, S., 2006. "Monte Carlo simulation techniques for group decision making with incomplete information," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1842-1864, November.
    29. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhao, Jun-Hong, 2009. "Review on multi-criteria decision analysis aid in sustainable energy decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2263-2278, December.
    30. Geldermann, Jutta & Bertsch, Valentin & Treitz, Martin & French, Simon & Papamichail, Konstantinia N. & Hämäläinen, Raimo P., 2009. "Multi-criteria decision support and evaluation of strategies for nuclear remediation management," Omega, Elsevier, vol. 37(1), pages 238-251, February.
    31. Valentin Bertsch & Wolf Fichtner, 2016. "A participatory multi-criteria approach for power generation and transmission planning," Annals of Operations Research, Springer, vol. 245(1), pages 177-207, October.
    32. Wassila Ouerdane & Nicolas Maudet & Alexis Tsoukiàs, 2010. "Argumentation Theory and Decision Aiding," International Series in Operations Research & Management Science, in: Matthias Ehrgott & José Rui Figueira & Salvatore Greco (ed.), Trends in Multiple Criteria Decision Analysis, chapter 0, pages 177-208, Springer.
    33. Lahdelma, Risto & Hokkanen, Joonas & Salminen, Pekka, 1998. "SMAA - Stochastic multiobjective acceptability analysis," European Journal of Operational Research, Elsevier, vol. 106(1), pages 137-143, April.
    34. Kahneman, Daniel & Knetsch, Jack L., 1992. "Valuing public goods: The purchase of moral satisfaction," Journal of Environmental Economics and Management, Elsevier, vol. 22(1), pages 57-70, January.
    35. Antonio Jiménez & Alfonso Mateos & Sixto Ríos-Insua, 2005. "Monte Carlo Simulation Techniques in a Decision Support System for Group Decision Making," Group Decision and Negotiation, Springer, vol. 14(2), pages 109-130, March.
    36. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Decision analysis in energy and environmental modeling: An update," Energy, Elsevier, vol. 31(14), pages 2604-2622.
    37. Butler, John & Jia, Jianmin & Dyer, James, 1997. "Simulation techniques for the sensitivity analysis of multi-criteria decision models," European Journal of Operational Research, Elsevier, vol. 103(3), pages 531-546, December.
    38. Editors, 2014. "International Journal of Systems Science," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 1-1, December.
    39. David E. Bell, 1982. "Regret in Decision Making under Uncertainty," Operations Research, INFORMS, vol. 30(5), pages 961-981, October.
    40. Scholten, Lisa & Schuwirth, Nele & Reichert, Peter & Lienert, Judit, 2015. "Tackling uncertainty in multi-criteria decision analysis – An application to water supply infrastructure planning," European Journal of Operational Research, Elsevier, vol. 242(1), pages 243-260.
    41. Graves, Samuel B. & Ringuest, Jeffrey L., 2009. "Probabilistic dominance criteria for comparing uncertain alternatives: A tutorial," Omega, Elsevier, vol. 37(2), pages 346-357, April.
    42. Scott, James A. & Ho, William & Dey, Prasanta K., 2012. "A review of multi-criteria decision-making methods for bioenergy systems," Energy, Elsevier, vol. 42(1), pages 146-156.
    43. Mareschal, Bertrand & Brans, Jean-Pierre, 1988. "Geometrical representations for MCDA," European Journal of Operational Research, Elsevier, vol. 34(1), pages 69-77, February.
    44. Heo, Eunnyeong & Kim, Jinsoo & Boo, Kyung-Jin, 2010. "Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(8), pages 2214-2220, October.
    45. Risto Lahdelma & Pekka Salminen, 2001. "SMAA-2: Stochastic Multicriteria Acceptability Analysis for Group Decision Making," Operations Research, INFORMS, vol. 49(3), pages 444-454, June.
    46. Insua, David Rios & French, Simon, 1991. "A framework for sensitivity analysis in discrete multi-objective decision-making," European Journal of Operational Research, Elsevier, vol. 54(2), pages 176-190, September.
    47. Jasbir S. Dhaliwal & Izak Benbasat, 1996. "The Use and Effects of Knowledge-Based System Explanations: Theoretical Foundations and a Framework for Empirical Evaluation," Information Systems Research, INFORMS, vol. 7(3), pages 342-362, September.
    48. Matsatsinis, Nikolaos F. & Samaras, Andreas P., 2001. "MCDA and preference disaggregation in group decision support systems," European Journal of Operational Research, Elsevier, vol. 130(2), pages 414-429, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. McKenna, R. & Bertsch, V. & Mainzer, K. & Fichtner, W., 2018. "Combining local preferences with multi-criteria decision analysis and linear optimization to develop feasible energy concepts in small communities," European Journal of Operational Research, Elsevier, vol. 268(3), pages 1092-1110.
    2. Valentin Bertsch & Wolf Fichtner, 2016. "A participatory multi-criteria approach for power generation and transmission planning," Annals of Operations Research, Springer, vol. 245(1), pages 177-207, October.
    3. Strantzali, Eleni & Aravossis, Konstantinos, 2016. "Decision making in renewable energy investments: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 885-898.
    4. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Khalifah, Zainab & Zakuan, Norhayati & Jusoh, Ahmad & Nor, Khalil Md & Khoshnoudi, Masoumeh, 2017. "A review of multi-criteria decision-making applications to solve energy management problems: Two decades from 1995 to 2015," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 216-256.
    5. Scholten, Lisa & Schuwirth, Nele & Reichert, Peter & Lienert, Judit, 2015. "Tackling uncertainty in multi-criteria decision analysis – An application to water supply infrastructure planning," European Journal of Operational Research, Elsevier, vol. 242(1), pages 243-260.
    6. Simone Steinhilber & Jutta Geldermann & Martin Wietschel, 2016. "Renewables in the EU after 2020: a multi-criteria decision analysis in the context of the policy formation process," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 4(1), pages 119-155, June.
    7. Wang, Q. & Poh, K.L., 2014. "A survey of integrated decision analysis in energy and environmental modeling," Energy, Elsevier, vol. 77(C), pages 691-702.
    8. Ishizaka, Alessio & Siraj, Sajid & Nemery, Philippe, 2016. "Which energy mix for the UK (United Kingdom)? An evolutive descriptive mapping with the integrated GAIA (graphical analysis for interactive aid)–AHP (analytic hierarchy process) visualization tool," Energy, Elsevier, vol. 95(C), pages 602-611.
    9. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
    10. Govindan, Kannan & Jepsen, Martin Brandt, 2016. "ELECTRE: A comprehensive literature review on methodologies and applications," European Journal of Operational Research, Elsevier, vol. 250(1), pages 1-29.
    11. R. Pelissari & M. C. Oliveira & S. Ben Amor & A. Kandakoglu & A. L. Helleno, 2020. "SMAA methods and their applications: a literature review and future research directions," Annals of Operations Research, Springer, vol. 293(2), pages 433-493, October.
    12. Manley, Dawn K. & Hines, Valerie A. & Jordan, Matthew W. & Stoltz, Ronald E., 2013. "A survey of energy policy priorities in the United States: Energy supply security, economics, and the environment," Energy Policy, Elsevier, vol. 60(C), pages 687-696.
    13. Jamal, Taskin & Urmee, Tania & Shafiullah, G.M., 2020. "Planning of off-grid power supply systems in remote areas using multi-criteria decision analysis," Energy, Elsevier, vol. 201(C).
    14. Baudry, Gino & Macharis, Cathy & Vallée, Thomas, 2018. "Range-based Multi-Actor Multi-Criteria Analysis: A combined method of Multi-Actor Multi-Criteria Analysis and Monte Carlo simulation to support participatory decision making under uncertainty," European Journal of Operational Research, Elsevier, vol. 264(1), pages 257-269.
    15. Sola, Antonio Vanderley Herrero & Mota, Caroline Maria de Miranda & Kovaleski, João Luiz, 2011. "A model for improving energy efficiency in industrial motor system using multicriteria analysis," Energy Policy, Elsevier, vol. 39(6), pages 3645-3654, June.
    16. Tylock, Steven M. & Seager, Thomas P. & Snell, Jeff & Bennett, Erin R. & Sweet, Don, 2012. "Energy management under policy and technology uncertainty," Energy Policy, Elsevier, vol. 47(C), pages 156-163.
    17. Mario Martín-Gamboa & Luis C. Dias & Paula Quinteiro & Fausto Freire & Luís Arroja & Ana Cláudia Dias, 2019. "Multi-Criteria and Life Cycle Assessment of Wood-Based Bioenergy Alternatives for Residential Heating: A Sustainability Analysis," Energies, MDPI, vol. 12(22), pages 1-17, November.
    18. Marttunen, Mika & Haag, Fridolin & Belton, Valerie & Mustajoki, Jyri & Lienert, Judit, 2019. "Methods to inform the development of concise objectives hierarchies in multi-criteria decision analysis," European Journal of Operational Research, Elsevier, vol. 277(2), pages 604-620.
    19. Khishtandar, Soheila & Zandieh, Mostafa & Dorri, Behrouz, 2017. "A multi criteria decision making framework for sustainability assessment of bioenergy production technologies with hesitant fuzzy linguistic term sets: The case of Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1130-1145.
    20. Olivier Cailloux & Tommi Tervonen & Boris Verhaegen & François Picalausa, 2014. "A data model for algorithmic multiple criteria decision analysis," Annals of Operations Research, Springer, vol. 217(1), pages 77-94, June.

    More about this item

    Keywords

    Decision support systems; Multiple criteria analysis; Preferential uncertainty modelling; Natural language generation; Multi-dimensional preferential sensitivity analysis;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:75025. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.