The risk assessment of construction project investment based on prospect theory with linguistic preference orderings Gou, Xunjie Xu, Zeshui Zhou, Wei Herrera Viedma, Enrique Risk assessment Construction project Investments Prospect theory linguistic preference orderings Consensus Multiple experts decision-making (MEDM) can be regarded as a situation where a group of experts are invited to provide their opinions by evaluating the given alternatives, and then select the optimal alternative(s). As a useful linguistic expression model, linguistic preference orderings (LPOs) were established in which the order of alternatives and the relationships between two adjacent alternatives are fused well. Considering that prospect theory has the superiority in depicting risk attitudes (risk seeking for losses and risk aversion for gains) during the uncertain decision-making process, this paper develops a consensus model based on prospect theory to deal with MEDM problems with LPOs. Firstly, each LPO provided by expert is transformed into the responding DHLPR with complete consistency. Then, the reference point of expert is determined and the prospect preference matrix is established. Moreover, we can obtain the overall prospect consensus degree for a MEDM problem by calculating the similarity degree between individual and collective prospect preference matrix. Furthermore, a consensus improvement method is developed to complete the consensus reaching process. Finally, we apply the proposed method to deal with a practical MEDM problem involving the construction project investment, and make some comparative analyses with existing methods. 2021-02-18T10:37:06Z 2021-02-18T10:37:06Z 2021-01-17 info:eu-repo/semantics/article Xunjie Gou , Zeshui Xu , Wei Zhou & Enrique Herrera-Viedma (2021): The risk assessment of construction project investment based on prospect theory with linguistic preference orderings, Economic Research-Ekonomska Istraživanja, [DOI: 10.1080/1331677X.2020.1868324] http://hdl.handle.net/10481/66650 10.1080/1331677X.2020.1868324 eng http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess Atribución 3.0 España Routledge Journals, Taylor y Francis LTD