Multi-attribute Group Decision Making of Internet Public Opinion Emergency with Interval Intuitionistic Fuzzy Number

In this paper, an emergency group decision method is presented to cope with internet public opinion emergency with interval intuitionistic fuzzy linguistic values. First, we adjust the initial weight of each emergency expert by the deviation degree between each expert\u27s decision matrix and group average decision matrix with interval intuitionistic fuzzy numbers. Then we can compute the weighted collective decision matrix of all the emergencies based on the optimal weight of emergency expert. By utilizing the interval intuitionistic fuzzy weighted arithmetic average operator one can obtain the comprehensive alarm value of each internet public opinion emergency. According to the ranking of score value and accuracy value of each emergency, the most critical internet public emergency can be easily determined to facilitate government taking related emergency operations. Finally, a numerical example is given to illustrate the effectiveness of the proposed emergency group decision method

Team situation awareness using web-based fuzzy group decision Support systems

Situation awareness (SA) is an important element to support responses and decision making to crisis problems. Decision making for a complex situation often needs a team to work cooperatively to get consensus awareness for the situation. Team SA is characterized including information sharing, opinion integration and consensus SA generation. In the meantime, various uncertainties are involved in team SA during information collection and awareness generation. Also, the collaboration between team members may be across distances and need web-based technology to facilitate. This paper presents a web-based fuzzy group decision support system (WFGDSS) and demonstrates how this system can provide a means of support for generating team SA in a distributed team work contextwith the ability of handling uncertain information. © Atlantis Press

Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence

Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.National Natural Science Foundation of China (NSFC) 71971039 71421001,71910107002,71771037,71874023 71871149Sichuan University sksyl201705 2018hhs-5

A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme

Interest in group decision-making (GDM) has been increasing prominently over the last decade. Access to global databases, sophisticated sensors which can obtain multiple inputs or complex problems requiring opinions from several experts have driven interest in data aggregation. Consequently, the field has been widely studied from several viewpoints and multiple approaches have been proposed. Nevertheless, there is a lack of general framework. Moreover, this problem is exacerbated in the case of experts’ weighting methods, one of the most widely-used techniques to deal with multiple source aggregation. This lack of general classification scheme, or a guide to assist expert knowledge, leads to ambiguity or misreading for readers, who may be overwhelmed by the large amount of unclassified information currently available. To invert this situation, a general GDM framework is presented which divides and classifies all data aggregation techniques, focusing on and expanding the classification of experts’ weighting methods in terms of analysis type by carrying out an in-depth literature review. Results are not only classified but analysed and discussed regarding multiple characteristics, such as MCDMs in which they are applied, type of data used, ideal solutions considered or when they are applied. Furthermore, general requirements supplement this analysis such as initial influence, or component division considerations. As a result, this paper provides not only a general classification scheme and a detailed analysis of experts’ weighting methods but also a road map for researchers working on GDM topics or a guide for experts who use these methods. Furthermore, six significant contributions for future research pathways are provided in the conclusions.The first author acknowledges support from the Spanish Ministry of Universities [grant number FPU18/01471]. The second and third author wish to recognize their support from the Serra Hunter program. Finally, this work was supported by the Catalan agency AGAUR through its research group support program (2017SGR00227). This research is part of the R&D project IAQ4EDU, reference no. PID2020-117366RB-I00, funded by MCIN/AEI/10.13039/ 501100011033.Peer ReviewedPostprint (published version

A Seat at the Table: Including the Poor in Decisions for Development and Environment

Presents case studies of the access to information, public participation, and justice for the poor in environmental decision-making processes and barriers, including issues of literacy, costs, risk, and cultural context. Makes policy recommendations

Using Law to Fight a Silent Epidemic: The Role of Healthy Literacy in Health Care Access, Quality & Cost

The dominant rhetoric in the health care policy debate about cost has assumed an inherent tension between access and quality on the one hand, and cost effectiveness on the other; but an emerging discourse has challenged this narrative by presenting a more nuanced relationship between access, quality, and cost. This is reflected in the discourse surrounding health literacy, which is viewed as an important tool for achieving all three goals. Health literacy refers to one\u27s ability to obtain, understand and use health information to make appropriate health decisions. Research shows that improving patients\u27 health literacy can help overcome access barriers and empower patients to be better health care partners, which should lead to better health outcomes. Promoting health literacy can also reduce expenditures for unnecessary or inappropriate treatment. This explains why, as a policy matter, improving health literacy is an objective that has been embraced by almost every sector of the health care system. As a legal matter, however, the role of health literacy in ensuring quality and access is not as prominent. Although the health literacy movement is relatively young, it has roots in longstanding bioethical principles of patient autonomy, beneficence, and justice as well as the corresponding legal principles of informed consent, the right to quality care, and antidiscrimination. Assumptions and concerns about health literacy seem to do important, yet subtle work in these legal doctrines - influencing conclusions about patient understanding in informed consent cases, animating decisions about patient responsibility in malpractice cases, and underlying regulatory guidance concerning the quality of language assistance services that are necessary for meaningful access to care. Nonetheless, health literacy is not explicitly treated as a legally relevant factor in these doctrines. Moreover, there is no coherent legal framework for incorporating health literacy research that challenges traditional assumptions about patient comprehension and decision-making, and that emphasizes the need for providers to improve communication and take affirmative steps to assess patient understanding. The absence of a clear and robust consideration of health literacy in these doctrines undermines core access and quality aims, and it means that such laws are of limited efficacy in promoting health literacy. Returning to the theme that the health literacy problem reflects a complementary view of access, quality and cost, it is likely that the cost implications of this problem (and not concerns about quality and access) will motivate the kind of health literacy reform that may ultimately strengthen existing quality and access standards. One recent example of this can be seen in reforms linked to government, insurer and provider attempts to reduce costly medication errors