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

Family Group Decision Making Utilization

In 2002, Greater Minnesota Family Services (GMFS) began providing Family Group Decision Making (FGDM) services funded by a grant and Three Counties for Kids and is still provided today in five counties. These counties are Blue Earth, Brown, Nicollet, Sibley, and Watonwan all located in Southern Minnesota. A survey was conducted to determine why the FGDM program is or is not utilized by county employees in the service area. Of county employee’s surveyed (N=25), 92% have used FGDM and 82% of those who identified their level of satisfaction (N=22) were satisfied to very satisfied with the services

Strengthening group decision making within shared governance: a case study

Shared governance is an approach to empowering nurses and other health care workers to have authority for decisions concerning their practice. Commonly, visible definers of shared governance are groups of workers known as ‘councils’ whose membership works collectively to realise a shared goal. The literature is replete with rhetoric as to the benefits of shared governance yet the evidence base concerning shared governance and especially decision-making within shared governance is scant. This paper presents a case study of group decision-making within a UK shared governance council model. The evidence which informs the case study is drawn from a doctoral action-research study to strengthen decision-making within the model. Eight key factors affecting decision-making and four supportive conditions are presented and incorporated into a conceptual model. Within the case study, presence of these factors was found to be necessary but not sufficient to enhance decision-making. Factors included having a clear issue, clear aim, fitting issue, manageable issue, size, lead person allocated, level of authority, background information, key informant/s, a mechanism for evaluation, adequately skilled members, support/guidance and sufficient/appropriate membership. Aspects of group decision-making processes are highlighted and compared with established management, shared governance and group dynamics theory

Group Decision-Making in Ultimatum Bargaining: An Experimental Study

Many rent-sharing decisions in a society are result from a bargaining process between groups of individuals (such as between the executive and the legislative branches of government, between legislative factions, between corporate management and shareholders, etc.). The purpose of this work is to conduct a laboratory study of the effect of different voting procedures on group decision-making in the context of ultimatum bargaining. An earlier study (Bornstein and Yaniv, [2]) has suggested that when the bargaining game is played by unstructured groups of agents, rather than by individuals, the division of the payoff is substantially affected in favor of the ultimatum-proposers. Our theoretical arguments suggest that one explanation for this could be implicit voting rules within groups. We propose to explicitly structure the group decision-making as voting and study the impact of different voting rules on the bargaining outcome.Bargaining games, group decision making and experimental design

Positive Affect and Group Decision Making

This paper presents a research model and empirical findings on the relationship between positive affect and group decision making. In the research model positive affect is posited to influence an individual’s willingness to communicate which in turn improves group decision making. Group cohesion is posited as moderating the relationship between positive affect and willingness to communicate. Results from an experiment involving teams in a group systems support (GSS) environment support the hypothesized relationships

Multicriteria Support for Group Decision Making

This chapter presents the support method for group decision making. A group decision is when a group of people has to make one joint decision. Each member of the group has his own assessment of a joint decision. The decision making of a group decision is modeled as a multicriteria optimization problem where the respective evaluation functions are the assessment of a joint decision by each member. The interactive analysis that is based on the reference point method applied to the multicriteria problems allows to find effective solutions matching the group’s preferences. Each member of the group is able to verify results of every decision. The chapter presents an example of an application of the support method in the selection of the group decision

Risk Sharing and Group Decision Making

In a decision-making problem where a group will receive an uncertain payoff which must be divided among the members of the group, the ultimate payoff of interest is the vector of individual payoffs received by the members of the group. In this paper, preferences are quantified in terms of cardinal utility functions for such vectors of payoffs. These utility functions can represent preferences concerning “equitable” and “inequitable” vectors of payoffs as well as attitudes toward risk. The individual utility functions are aggregated to form a group utility function for the vector of payoffs, and this latter function is, in turn, used to generate a group utility function for the overall group payoff and a sharing rule for dividing the group payoff into individual payoffs. The resulting group decisions are Pareto optimal in utility space. Properties of the sharing rule and the group utility function are investigated for additive and multilinear group utility functions