A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making |
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| Affiliation: | 1. Chair of Energy Economics, Karlsruhe Institute of Technology (KIT), Hertzstr. 16, 76187 Karlsruhe, Germany;2. Economic and Social Research Institute & Trinity College Dublin, Whitaker Square, Sir John Rogerson''s Quay, Dublin 2, Ireland;1. Department of Systems and Energy, University of Campinas – UNICAMP, Campinas, São Paulo, Brazil;2. Department of Computer Science, Federal University of São Carlos – UFSCar, Sorocaba, São Paulo, Brazil;1. College of Computer Science and Technology, University South China, Hengyang 421001, China;2. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;1. Instituto Superior Politécnico José Antonio Echeverría, Calle 114 No. 11901, Marianao, La Habana C.P. 19390, Cuba;2. Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro No. 1, Sta. María Tonanzintla, Puebla C.P. 72840, México;3. Centro de Bioplantas, Universidad de Ciego de Ávila, Carretera a Morón km 9, Ciego de Ávila C.P. 69450, Cuba |
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| 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. |
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