01940nas a2200181   4500000000100000000000100001008004100002260001200043100002000055700001600075700001900091700002000110700002300130700002600153245011800179490000800297520145300305       2023                            d  c03/20231 aSheng-Hua Xiong1 aChen-Ye Zhu1 aZhen-Song Chen1 aMuhammet Deveci1 aFrancisco Chiclana1 aMirosław Skibniewski00aOn extended power geometric operator for proportional hesitant fuzzy linguistic large-scale group decision-making0 v6323 a<p>The unduly low or high data are commonly regarded as outliers in the classical power geometric operator. However, in many cases, these types of data may be significantly important to the aggregated results. This study aims at expanding the practical application scope of the power geometric operator and then utilizing it to develop a proportional hesitant fuzzy linguistic large-scale group decision-making (LSGDM) model. The extended power geometric (EPG) operator is first introduced, in which these outliers can be distinguished as sufficiently important or "false/biased" data in accordance with the decision-making context. Several useful properties and application characteristics of the EPG operator are highlighted. Subsequently, the proportional hesitant fuzzy linguistic normalized Manhattan distance is proposed, which is a basic concept for the construction of the proportional hesitant fuzzy linguistic extended power geometry (PHFLEPG) operator. Combined with the clustering model for decision-makers, a PHFLEPG-operator-based consensus-reaching approach is provided to simplify and rationalize the decision-making process. Furthermore, the comprehensive LSGDM result is derived by utilizing the PHFLEPG operator. Eventually, a case study on regulatory capacity evaluation for the Civil Aviation Safety Regulatory Authority of China is performed to validate the feasibility and effectiveness of the established LSGDM method.</p>