The society in the digital transformation era demands new decision schemes such as e-democracy or based on social media. Such novel decision schemes require the participation of many experts/decision makers/stakeholders in the decision processes. As a result, large-scale group decision making (LSGDM) has attracted the attention of many researchers in the last decade and many studies have been conducted in order to face the challenges associated with the topic. Therefore, this paper aims at reviewing the most relevant studies about LSGDM, identifying the most profitable research trends and analyzing them from a critical point of view. To do so, the Web of Science database has been consulted by using different searches. From these results a total of 241 contributions were found and a selection process regarding language, type of contribution and actual relation with the studied topic was then carried out. The 87 contributions finally selected for this review have been analyzed from four points of view that have been highly remarked in the topic, such as the preference structure in which decision-makers&#x0027; opinions are modeled, the group decision rules used to define the decision making process, the techniques applied to verify the quality of these models and their applications to real world problems solving. Afterwards, a critical analysis of the main limitations of the existing proposals is developed. Finally, taking into account these limitations, new research lines for LSGDM are proposed and the main challenges are stressed out. 

Large-Scale Group Decision Making: A Systematic Review and a Critical Analysis

• It develops the user satisfaction criteria of peer-to-peer accommodation. • The individual opinions are aggregated by group consensus decision. • A minimal variance weights based feedback model is proposed for consensus. To promote the development of the peer-to-peer (P2P) accommodation in sharing economy, it is important to understand and ensure the determinants of high-level user satisfaction. Focusing on factors that affect the travel experience of P2P accommodation users, this article proposes a large-scale group decision making (LSGDM) based method with online reviews to evaluate user satisfaction of sharing accommodation. Firstly, the user demands (UDs) reflecting the actual concerns of users are extracted by combining negative and positive reviews from P2P accommodation platform Airbnb, where negative reviews are classified by sentiment analysis, TF-IDF and Word2Vec technology are used for extraction and the further verification of UDs from all online reviews is performed. Secondly, the level of satisfaction is evaluated through online responses from P2P accommodation users in a large-scale group of decision makers. Thirdly, the final degrees of satisfaction are ascertained by the proposed LSGDM approach, which includes subgroup clustering and a minimal variance weights based feedback mechanism for fair weights allocation under the condition of reaching consensus. Finally, the conclusions further serve as references for improving the performance of P2P sharing accommodation. 

An online reviews-driven large-scale group decision making approach for evaluating user satisfaction of sharing accommodation

Optimized decision support for BIM maturity assessment

Fuzzy DEMATEL method is diffusely employed to analyze the interrelationship among factors in various fields under uncertain and fuzzy environment. In the extant fuzzy DEMATEL studies, fuzzy assessments are converted into related crisp values by means of different defuzzification ways. Such conversion may result in not only the loss of information, but also the discount of consideration of fuzzy information. Therefore, it seems reasonable and necessary to keep as much information as possible during the analysis process, instead of converting it into crisp values at the very beginning. An appropriate way to keep as much information as possible is to employ alpha level sets to handle fuzzy information instead of simple defuzzification. In addition, it is quite common that experts may hesitate under uncertain and fuzzy environment in the real-world situation, when providing their assessments on the interrelationship among factors. However, such practical issue is neglected in the extant fuzzy DEMATEL methods. With respect to aforementioned limitations, this study proposes a novel alpha level sets based fuzzy DEMATEL method to handle the fuzzy information, together with considering experts’ hesitation from qualitative context under uncertain and fuzzy environment. Additionally, two different options are provided to analyze the interrelationship among factors in the proposed method. The proposed method not only improves the extant fuzzy DEMATEL studies, but also enriches the theoretical studies of fuzzy DEMATEL, its novelty and superiority is demonstrated through illustrative example and related comparisons. • A novel way for handling fuzzy assessments in fuzzy DEMATEL methods is proposed. • Two options for analyzing the interrelationship among factors are provided. • Expert’s hesitant information in fuzzy DEMATEL method is considered. 

A novel alpha-level sets based fuzzy DEMATEL method considering experts' hesitant information

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Classical dynamic consensus and opinion dynamics models: A survey of recent trends and methodologies

The society in the digital transformation era demands new decision schemes such as e-democracy or based on social media. Such novel decision schemes require the participation of many experts/decision makers/stakeholders in the decision processes. As a result, large-scale group decision making (LSGDM) has attracted the attention of many researchers in the last decade and many studies have been conducted in order to face the challenges associated with the topic. Therefore, this paper aims at reviewing the most relevant studies about LSGDM, identifying the most profitable research trends and analyzing them from a critical point of view. To do so, the Web of Science database has been consulted by using different searches. From these results a total of 241 contributions were found and a selection process regarding language, type of contribution and actual relation with the studied topic was then carried out. The 87 contributions finally selected for this review have been analyzed from four points of view that have been highly remarked in the topic, such as the preference structure in which decision-makers' opinions are modeled, the group decision rules used to define the decision making process, the techniques applied to verify the quality of these models and their applications to real world problems solving. Afterwards, a critical analysis of the main limitations of the existing proposals is developed. Finally, taking into account these limitations, new research lines for LSGDM are proposed and the main challenges are stressed out.

Consensus Reaching Processes (CRPs) deal with those group decision‐making situations in which conflicts among experts' opinions make difficult the reaching of an agreed solution. This situation, worsens in large‐scale group decision situations, in which opinions tend to be more polarized, because in problems with extreme opinions it is harder to reach an agreement. Several studies have shown that experts' preferences may not always follow a linear scale, as it has commonly been assumed in previous CRP. Therefore, the main aim of this paper is to study the effect of modeling this nonlinear behavior of experts' preferences (expressed by fuzzy preference relations) in CRPs. To do that, the experts' preferences will be remapped by using nonlinear deformations which amplify or reduce the distance between the extreme values. We introduce such automorphisms to remap the preferences as Extreme Values Amplifications (EVAs) and Extreme Values Reductions (EVRs), study their main properties and propose several families of these EVA and EVR functions. An analysis about the behavior of EVAs and EVRs when are implemented in a generic consensus model is then developed. Finally, an illustrative experiment to study the performance of different families of EVAs in CRPs is provided.

Nonlinear preferences in group decision-making. Extreme values amplifications and extreme values reductions

Symmetric weights for OWA operators prioritizing intermediate values. The EVR-OWA operator

Relationship between the distance consensus and the consensus degree in comprehensive minimum cost consensus models: A polytope-based analysis

The development of New Energy Vehicles (NEVs) has contributed to the alleviation of environmental pollution in the transportation sector. Although NEVs have some advantages, such as energy saving, being environmentally friendly, and low noise, they are restricted by their cruising range or recharging-related problems. To minimize such disadvantages, an optimal plan for the charging station site is necessary. This paper proposes a Large-Scale Group Decision-Making (LSGDM) method to select the best location for such charging stations. This method involves a large group of experts providing their preferences according to their knowledge and background. To facilitate the elicitation, our method uses Hesitant Fuzzy Linguistic Term Sets (HFLTS) and Extended Comparative Linguistic Expressions with Symbolic Translation (ELICIT) model to improve the elicitation process, guarantee precise computing processes and obtain interpretable results. A social network is then constructed based on experts’ preference similarity and trust relationships, which reflects both their relationship and its strength simultaneously. Afterwards, a social analysis-based clustering process groups the experts, and a Three-Way Decision (TWD)-based Consensus Reaching Process (CRP) is introduced to improve the group’s agreement. Finally, a selection of charging station site case studies is conducted, and a comparative analysis is carried out to illustrate the quality of the proposal. 

Diego García-Zamora

Papers

Large-Scale Group Decision Making: A Systematic Review and a Critical Analysis

Nonlinear preferences in group decision-making. Extreme values amplifications and extreme values reductions

Symmetric weights for OWA operators prioritizing intermediate values. The EVR-OWA operator

Relationship between the distance consensus and the consensus degree in comprehensive minimum cost consensus models: A polytope-based analysis

A Large Scale Group Three-Way Decision-based consensus model for site selection of New Energy Vehicle charging stations