Collaborative Decision-Making Analysis and Applications

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Fuzzy Sets, Systems and Decision Making".

Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 6306

Special Issue Editors

School of Business, Anhui University, Hefei 230601, China
Interests: large-scale fuzzy multi-attribute decision-making; fuzzy group decision-making; large scale group collaborative decision-making; data envelopment analysis; aggregation theory; decision support systems; bounded rationality theory; applied mathematics
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Guest Editor
School of Business, Anhui University, Hefei 230601, China
Interests: decision analysis; data envelopment analysis; management science; multicriteria analysis; mathematical programming optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recently, with the development of network technology, collaborative decision making and evaluation has become the focus of sustainable development assessments of the environment, renewable energy, emergency response, medicine, manufacturing, and so on. Collaborative decision making and evaluation requires experts from different fields to participate in decision-making processes and obtain the most effective outcome within a short period of time.

As a key factor in the process of collaborative group decision making, the effective communication and collaborative cooperation among decision-making experts will greatly help to rapidly achieve collaborative group decision-making outcomes. Firstly, the traditional consensus level measurement model ignores that the group consensus level in the decision-making process is dynamic and needs to be constantly updated. Secondly, the existing research on the adjustment process of group consensus usually ignores the internal correlation of preference information and makes unnecessary adjustments to the number and range of original preference information elements. Finally, as the main body of decision making, the incomplete rational behaviour characteristics of experts cannot be ignored. These factors will greatly reduce the satisfaction of decision-making experts with the results of group decision making.

Therefore, it is important to study collaborative decision-making methods and their applications in the sustainable management of health emergencies and disaster risks. This would be a promising research line, which could lead to an exciting breakthrough for this field.

You are cordially invited to submit papers related to all aspects of collaborative decision making, both theoretical and applicational. This involves (but is not limited to) collaborative group decision making, fuzzy group decision making, large-scale group decision making, data envelopment analysis, data aggregation theory, collaborative decision support systems, collaborative stochastic decision making,  collaborative multi-objective decision making, graph theory-driven collaborative decision making, collaborative game theory, and collaborative evolutionary algorithms and their applications for the environment, renewable energy, emergency responses, medicine, manufacturing, etc.

Dr. Feifei Jin
Prof. Dr. Jinpei Liu
Guest Editors

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Keywords

  • collaborative decision making
  • swarm intelligence algorithm in collaborative decision making
  • information aggregation operators in collaborative decision making
  • collaborative stochastic decision making
  • collaborative decision support systems
  • collaborative multi-objective decision making
  • fuzzy graph theory in decision making
  • social network-driven collaborative decision making
  • fuzzy group decision making
  • fuzzy sets
  • fuzzy multi-criteria method
  • large-scale group decision making
  • consistency adjustment algorithms
  • consensus researching models
  • big data analysis for large-scale collaborative decision making
  • data-driven multiple criteria decision making
  • collaborative game theory
  • collaborative evolutionary algorithms
  • consensus and cooperation evaluation for emergency sustainable management issues
  • big data analysis for large-scale collaborative decision making
  • designing effective sustainable assessment system
  • data-driven, large-scale, collaborative decision making in emergency medical health management
  • data-driven, large-scale, collaborative decision making in risk measures

Published Papers (4 papers)

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Research

21 pages, 2085 KiB  
Article
Distributionally Robust Optimization Model for a Minimum Cost Consensus with Asymmetric Adjustment Costs Based on the Wasserstein Metric
by Ziqi Wu, Kai Zhu and Shaojian Qu
Mathematics 2022, 10(22), 4312; https://doi.org/10.3390/math10224312 - 17 Nov 2022
Cited by 1 | Viewed by 1038
Abstract
When solving the problem of the minimum cost consensus with asymmetric adjustment costs, decision makers need to face various uncertain situations (such as individual opinions and unit adjustment costs for opinion modifications in the up and down directions). However, in the existing methods [...] Read more.
When solving the problem of the minimum cost consensus with asymmetric adjustment costs, decision makers need to face various uncertain situations (such as individual opinions and unit adjustment costs for opinion modifications in the up and down directions). However, in the existing methods for dealing with this problem, robust optimization will lead to overly conservative results, and stochastic programming needs to know the exact probability distribution. In order to overcome these shortcomings, it is essential to develop a novelty consensus model. Thus, we propose three new minimum-cost consensus models with a distributionally robust method. Uncertain parameters (individual opinions, unit adjustment costs for opinion modifications in the up and down directions, the degree of tolerance, and the range of thresholds) were investigated by modeling the three new models, respectively. In the distributionally robust method, the construction of an ambiguous set is very important. Based on the historical data information, we chose the Wasserstein ambiguous set with the Wasserstein distance in this study. Then, three new models were transformed into a second-order cone programming problem to simplify the calculations. Further, a case from the EU Trade and Animal Welfare (TAW) program policy consultation was used to verify the practicability of the proposed models. Through comparison and sensitivity analysis, the numerical results showed that the three new models fit the complex decision environment better. Full article
(This article belongs to the Special Issue Collaborative Decision-Making Analysis and Applications)
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22 pages, 2134 KiB  
Article
A Calibrated Individual Semantic Based Failure Mode and Effect Analysis and Its Application in Industrial Internet Platform
by Jian Wu, Jun Chen, Wei Liu, Yujia Liu, Changyong Liang and Mingshuo Cao
Mathematics 2022, 10(14), 2492; https://doi.org/10.3390/math10142492 - 18 Jul 2022
Cited by 23 | Viewed by 1449
Abstract
This article proposes a calibrated individual semantic (CIS)-based failure mode and effect analysis (FMEA) to deal with the risk evaluation of industrial internet platforms (IIP) from four perspectives: network security, data processing capability, equipment performance, and openness. The novelty of the CIS model [...] Read more.
This article proposes a calibrated individual semantic (CIS)-based failure mode and effect analysis (FMEA) to deal with the risk evaluation of industrial internet platforms (IIP) from four perspectives: network security, data processing capability, equipment performance, and openness. The novelty of the CIS model is based on the deviation between linguistic terms and numerical values to calibrate linguistic scales of decision-makers (DMs). Not only can it handle situations in which different DMs have different understandings of the same term, but it is also suitable for multiple attributes decision-making with uncertainty. In addition, this new FMEA framework considers the consensus-reaching process as a way to eliminate the disagreement among DMs from different departments. Finally, a comparison between the proposed and traditional method is presented to illustrate the advantages of new method. Full article
(This article belongs to the Special Issue Collaborative Decision-Making Analysis and Applications)
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25 pages, 8369 KiB  
Article
Data-Driven Coupling Coordination Development of Regional Innovation EROB Composite System: An Integrated Model Perspective
by Yaliu Yang, Yuan Wang, Yingyan Zhang and Conghu Liu
Mathematics 2022, 10(13), 2246; https://doi.org/10.3390/math10132246 - 27 Jun 2022
Cited by 8 | Viewed by 1502
Abstract
To promote coupling coordination development for regional innovation environment-resource-output-benefit (EROB) composite systems, we propose a data-driven integrated model method for measurement, evaluation, and identification. First, we construct an evaluation indicator system of coupling coordination development of regional innovation EROB composite systems. Second, we [...] Read more.
To promote coupling coordination development for regional innovation environment-resource-output-benefit (EROB) composite systems, we propose a data-driven integrated model method for measurement, evaluation, and identification. First, we construct an evaluation indicator system of coupling coordination development of regional innovation EROB composite systems. Second, we apply the entropy method to measure indicator weights and comprehensive development indices of regional innovation composite systems. The coupling coordination degree model is used to calculate and evaluate four subsystems’ coupling coordination development levels. The obstacle degree model is used to identify the main obstacle factors affecting coupling coordination development. Finally, using panel data of the Yangtze River Delta region (three provinces and one city) between 2014–2019 as a case study, we test the integrated model method. The results show that the comprehensive development level of the regional innovation EROB composite system in the Yangtze River Delta region maintained a stable growth trend; the coupling coordination development level among four subsystems continuously improved, with the main obstacle being the innovation resource subsystem. Accordingly, targeted policy suggestions are put forward. This study not only provides theoretical and methodological support for evaluating and optimizing regional innovation composite systems but also provides decision-making support for sustainable and high-quality development of regional economies. Full article
(This article belongs to the Special Issue Collaborative Decision-Making Analysis and Applications)
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23 pages, 5751 KiB  
Article
A VIKOR-Based Linguistic Multi-Attribute Group Decision-Making Model in a Quantum Decision Scenario
by Jingmei Xiao, Mei Cai and Yu Gao
Mathematics 2022, 10(13), 2236; https://doi.org/10.3390/math10132236 - 26 Jun 2022
Cited by 3 | Viewed by 1397
Abstract
Quantum decision theory has been successfully applied to multi-attribute group decision-making (MAGDM) to model decision-makers’ interference and superposition effects in recent years. Existing quantum models assume that interference effects among decision-makers are symmetric. However, asymmetric interference effects have been ignored. We propose a [...] Read more.
Quantum decision theory has been successfully applied to multi-attribute group decision-making (MAGDM) to model decision-makers’ interference and superposition effects in recent years. Existing quantum models assume that interference effects among decision-makers are symmetric. However, asymmetric interference effects have been ignored. We propose a VIKOR-based linguistic distribution assessments (LDAs) model considering asymmetric interference effects in a quantum decision scenario. Firstly, we combine VIKOR with LDAs to obtain a compromise solution in a fuzzy multi-attribute decision scenario with conflicting attributes. Secondly, an aggregation framework based on quantum probability theory is constructed to explore group preferences considering asymmetric interference effects among decision-makers. Finally, the model is compared with other methods to confirm its validity and stability. Full article
(This article belongs to the Special Issue Collaborative Decision-Making Analysis and Applications)
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