374 research outputs found
An optimal feedback model to prevent manipulation behaviours in consensus under social network group decision making
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.A novel framework to prevent manipulation behaviour
in consensus reaching process under social network
group decision making is proposed, which is based on a theoretically
sound optimal feedback model. The manipulation
behaviour classification is twofold: (1) âindividual manipulationâ
where each expert manipulates his/her own behaviour to achieve
higher importance degree (weight); and (2) âgroup manipulationâ
where a group of experts force inconsistent experts to adopt
specific recommendation advices obtained via the use of fixed
feedback parameter. To counteract âindividual manipulationâ, a
behavioural weights assignment method modelling sequential
attitude ranging from âdictatorshipâ to âdemocracyâ is developed,
and then a reasonable policy for group minimum adjustment cost
is established to assign appropriate weights to experts. To prevent
âgroup manipulationâ, an optimal feedback model with objective
function the individual adjustments cost and constraints related
to the threshold of group consensus is investigated. This approach
allows the inconsistent experts to balance group consensus and
adjustment cost, which enhances their willingness to adopt the
recommendation advices and consequently the group reaching
consensus on the decision making problem at hand. A numerical
example is presented to illustrate and verify the proposed optimal
feedback model
Multiple Attribute Strategic Weight Manipulation With Minimum Cost in a Group Decision Making Context With Interval Attribute Weights Information
AbstractâIn multiple attribute decision making (MADM),
strategic weight manipulation is understood as a deliberate
manipulation of attribute weight setting to achieve a desired
ranking of alternatives. In this paper, we study the strategic
weight manipulation in a group decision making (GDM) context
with interval attribute weight information. In GDM, the
revision of the decision makersâ original attribute weight information
implies a cost. Driven by a desire to minimize the cost,
we propose the minimum cost strategic weight manipulation
model, which is achieved via optimization approach, with the
mixed 0-1 linear programming model being proved appropriate
in this context. Meanwhile, some desired properties to manipulate
a strategic attribute weight based on the ranking range
under interval attribute weight information are proposed. Finally,
numerical analysis and simulation experiments are provided with
a twofold aim: 1) to verify the validity of the proposed models
and 2) to show the effects of interval attribute weights information
and the unit cost, respectively, on the cost to manipulate
strategic weights in the MADM in a group decision context.This work was supported in part by National
Science Foundation of China under Grant 71571124, Grant 71871149, and
Grant 71601133; in part by Sichuan University under Grant sksyl201705
and Grant 2018hhs-58; and in part by FEDER Funds under Grant TIN2016-
75850-R
Integrating expertsâ weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors
This work was supported in part by the NSF of China under grants 71171160 and 71571124, in part by the SSEM Key Research Center at Sichuan Province under grant xq15b01, in part by the FEDER funds under grant TIN2013-40658-P, and in part by Andalusian Excellence Project under grant TIC-5991.The consensus reaching process (CRP) is a dynamic and iterative process for improving the consensus level among experts in group decision making. A large number of non-cooperative behaviors exist in the CRP. For example, some experts will express their opinions dishonestly or refuse to change their opinions to further their own interests. In this study, we propose a novel consensus framework for managing non-cooperative behaviors. In the proposed framework, a self-management mechanism to generate experts' weights dynamically is presented and then integrated into the CRP. This self-management mechanism is based on multi-attribute mutual evaluation matrices (MMEMs). During the CRP, the experts can provide and update their MMEMs regarding the experts' performances (e.g., professional skill, cooperation, and fairness), and the experts' weights are dynamically derived from the MMEMs. Detailed simulation experiments and comparison analysis are presented to justify the validity of the proposed consensus framework in managing the non-cooperative behaviors.National Natural Science Foundation of China
71171160
71571124SSEM Key Research Center at Sichuan Province
xq15b01European Union (EU)
TIN2013-40658-PAndalusian Excellence Project
TIC-599
Task and relationship conflict in subordinates and supervisors relations: interaction effects of justice perceptions and emotion management
This dissertation investigates the antecedents and outcomes of task and relationship conflict in subordinates and supervisors relations. Based on abusive supervision studies and the justice framework, I proposed that the relationship between abusive supervision and task conflict is mediated by procedural justice, and that the relationship between abusive supervision and relationship conflict is mediated by interactional justice. Based on emotional intelligence theory, I also proposed that these mediation processes are moderated by an individualâs emotion management ability (EMA). Finally, I anticipated that relationship conflict elicits more detrimental effect on employeesâ organizational citizenship and workplace deviance behaviors. A total of 310 employees and their supervisors in a large hospital participated in this study. The results demonstrated that procedural justice fully mediates the relationship between abusive supervision and task conflict. Interactional justice fully mediates the relationship between abusive supervision and relationship conflict. An employeeâs EMA moderates these relationships, such that individuals with higher EMA are more sensitive to repaying the favors that they have received. Lastly, relationship conflict is more damaging to organizational functioning than task conflict, such that the impact of relationship conflict on organizational citizenship and workplace deviance behaviors is significantly stronger. Implications and future directions are discussed
Alternative Ranking-Based Clustering and Reliability Index-Based Consensus Reaching Process for Hesitant Fuzzy Large Scale Group Decision Making
The paper addresses the growing importance of Large Scale Group Decision Making (LSGDM) problems, focusing on hesitant fuzzy LSGDM. It introduces a Reliability Index-based Consensus Reaching Process (RI-CRP) to enhance efficiency. The proposed method assesses the ordinal consistency of decision makers' (DMs) information, measures deviation, and assigns a reliability index to DMs' opinions. An unreliable DMs management method is presented to filter out unreliable information. Additionally, an Alternative Ranking-based Clustering (ARC) method with hesitant fuzzy reciprocal preference relations is proposed to improve the efficiency of RI-CRP. The numerical example demonstrates the feasibility and effectiveness of the ARC method and RI-CRP for hesitant fuzzy LSGDM problems.Este artĂculo aborda la creciente importancia de los problemas de Toma de Decisiones en Grupo a Gran Escala (LSGDM), centrĂĄndose en el LSGDM difuso vacilante. Introduce un Proceso de Consenso Basado en Ăndices de Fiabilidad (RI-CRP) para mejorar la eficiencia. El mĂ©todo propuesto evalĂșa la consistencia ordinal de la informaciĂłn de los decisores, mide la desviaciĂłn y asigna un Ăndice de fiabilidad a las opiniones de los decisores. Se presenta un mĂ©todo de gestiĂłn de los decisores poco fiables para filtrar la informaciĂłn poco fiable. AdemĂĄs, se propone un mĂ©todo de agrupamiento alternativo basado en la clasificaciĂłn (ARC) con relaciones de preferencia recĂproca difusas vacilantes para mejorar la eficacia de RI-CRP. El ejemplo numĂ©rico demuestra la viabilidad y eficacia del mĂ©todo ARC y del RI-CRP para problemas LSGDM difusos vacilantes.Instituto Interuniversitario de InvestigaciĂłn en Data Science and Computational Intelligence (DaSCI
A Group Decision Making Approach Considering Self-Confidence Behaviors and Its Application in Environmental Pollution Emergency Management
Self-confidence as one of the human psychological behaviors has important influence on
emergency management decision making, which has been ignored in existing methods. To fill this
gap, we dedicate to design a group decision making approach considering self-confidence behaviors
and apply it to the environmental pollution emergency management. In the proposed method, the
self-confident fuzzy preference relations are utilized to express expertsâ evaluations. This new type of
preference relations allow experts to express multiple self-confidence levels when providing their
evaluations, which can deal with the self-confidence of them well. To apply the proposed group
decision making method to environmental pollution emergency management, a novel determination
of the decision weights of experts is given combining the subjective and objective weights. The
subjective weight can be directly assigned by organizer, while the objective weight is determined
by the self-confidence degree of experts on their evaluations. Afterwards, by utilizing the weighted
averaging operator, the individualsâ evaluations can be aggregated into a collective one. To do
that, some operational laws for self-confident fuzzy preference relations are introduced. And then,
a self-confidence score function is designed to get the best solution for environmental pollution
emergency management. Finally, some analyses and discussions show that the proposed method is
feasible and effective.The work was supported by National Key R&D Program of China (Grant No.
2017YFC0404600), National Natural Science Foundation of China (NSFC) under Grants (71871085, 71471056),
Qing Lan Project of Jiangsu Province. Additionally, Xia Liu andWeike Zhang gratefully acknowledge the financial
support of the China Scholarship Council (Nos. 201706710084, 201806240231)
A self-management mechanism for non-cooperative behaviors in large-scale group consensus reaching processes
In large-scale group decision making (GDM), non-cooperative behavior in the consensus reaching process (CRP) is not unusual. For example, some individuals might form a small alliance with the aim to refuse attempts to modify their preferences or even to move them against consensus to foster the allianceâs own interests. In this paper, we propose a novel
framework based on a self-management mechanism for non-cooperative behaviors in large-scale consensus reaching processes (LCRPs). In the proposed consensus reaching framework, experts are classified into different subgroups using a clustering method, and experts provide their evaluation information, i.e., the multi-criteria mutual evaluation matrices (MCMEMs), regarding the subgroups based on subgroupsâ performance (e.g., professional skills, cooperation, and fairness). The subgroupsâ weights are dynamically generated from the MCMEMs, which are in turn employed to update the individual expertsâ weights. This self-management mechanism in the LCRP allows penalizing the weights of the experts with non-cooperative behaviors. Detailed simulation experiments and comparison analysis are presented to verify the validity of the proposed framework for managing non-cooperative behaviors in the LCRP
Large-Scale Green Supplier Selection Approach under a Q-Rung Interval-Valued Orthopair Fuzzy Environment
As enterprises pay more and more attention to environmental issues, the green supply chain management (GSCM) mode has been extensively utilized to guarantee proïŹt and sustainable development. Greensupplierselection(GSS),whichisakeysegmentofGSCM,hasbeeninvestigated to put forward plenty of GSS approaches
- âŠ