@revista_internacional{944,
  keywords = {Large-scale group decision making, Mathematical optimization-based feedback mechanism, Non-cooperative behavior, ELICIT, DEA cross-efficiency},
  author = {Hui-Hui Song and Bapi Dutta and Diego García-Zamora and Ying-Ming Wang and Luis Martínez},
  title = {Managing non-cooperative behaviors in consensus reaching process: A novel multi-stage linguistic LSGDM framework},
  abstract = {Large-scale group decision-making (LSGDM) is a complex process involving numerous decision-makers (DMs). However, considering such a large number of DMs increases the complexity of the process. it seems necessary to pay much more attention to aspects such as a proper dimensionality reduction for scalability, consensus processes with automatic feedback, and effective management of non-cooperative DMs. To address such aspects, this paper presents a novel framework for LSGDM, based on Extended Comparative Linguistic Expressions With Symbolic Translation (ELICIT). We first extend the K-means clustering algorithm by incorporating individual assessments and trust relationships to classify DMs into subgroups, enhancing decision-making efficiency. We then develop a feedback mechanism based on two optimization consensus models for ELICIT information, that automatically provides optimal recommendations. An essential aspect of our proposal is the management of non-cooperative behaviors by utilizing the normal distribution to detect and penalize misbehaviors. Furthermore, we introduce a Data Envelopment Analysis (DEA) cross-efficiency method based on ELICIT values to rank all alternatives once an acceptable group consensus degree is reached. The framework’s effectiveness is demonstrated through a practical application case study, accompanied by a parametric analysis. Comparisons with existing LSGDM methods highlight the superiority of our proposal in terms of efficiency.},
  year = {2024},
  journal = {Expert Systems with Applications},
  volume = {240},
  pages = {122555},
  issn = {0957-4174},
  url = {https://www.sciencedirect.com/science/article/pii/S0957417423030579},
  doi = {https://doi.org/10.1016/j.eswa.2023.122555},
}