基于三支冲突感知分析的群决策共识模型

doi:10.16381/j.cnki.issn1003-207x.2023.0901

Abstract

Abstract:

In complex group decision making， conflicts are an inevitable issue. Conflicts often arise due to divergence in background and knowledge among experts. While the experts may face the same conflict within a given context， their distinct backgrounds and knowledge lead to varying perceptions and cognitions regarding it. At present， there has been a growing focus on the analysis and resolution of conflicts. However， limited research has considered the influence of conflict perception on group decision making. Therefore， drawing on the idea of symbol-meaning-value （SMV） space， the perception-cognition-action （PCA） concept is integrated into conflict space to construct a three-way group consensus model. Guided by conflict perception， cognitive conflict identification， and conflict resolution strategies， this model is designed to address conflict issues and facilitate consensus reaching. For conflict perception， a method for measuring conflict perception based on the characteristics of group consensus is proposed. Based on the conflict perception among experts， conflict initiators and receivers are further identified. Regarding cognitive conflicts， the Three-Way Conflict Analysis （TCA） method is employed to address the issue of cognitive conflict identification between experts and the group. Finally， for conflict resolution strategies， direction rules are designed to eliminate cognitive conflicts and facilitate the group consensus based on perceived conflicts. Furthermore， numerical experiments and robustness tests are conducted to demonstrate the feasibility and effectiveness of the proposed model. Through the numerical experiments and robustness tests， the following results are drawn： firstly， when considering conflict perception， the proposed method can effectively reduce the overall adjustment while shortening the required time to reach the consensus. Secondly， the decision results remain stable under different situations with our proposed method. Finally， the robustness tests show the stability of our proposed model in facilitating the group consensus. Overall， it contributes to the field of group decision-making in this paper by providing a systematic approach integrating opinion dynamics and the three-way conflict analysis with conflict perception. The proposed method enhances group collaboration efficiency， facilitates consensus building， and mitigates conflict problems.

Key words: three-way conflict analysis, three-way decision, group decision making, opinion dynamics, conflict perception

CLC Number:

C934

Qiang Zheng,Decui Liang,Yuanyuan Fu, et al. Consensus Model of Group Decision Making Based on Three-way Conflict Analysis Considering Conflict Perception[J]. Chinese Journal of Management Science, 2026, 34(1): 85-93.

Figures/Tables 14

级别	$S C E A c , c $	$W C E A c , c $	$N C E A c , c $
$S C M A c ., c . → S C M A c ., c .$	—	—	—
$S C M A c ., c . → W C M A c ., c .$	—	—	—
$S C M A c ., c . → N C M A c ., c .$	策略 3.a	策略2.a	—
$W C M A c ., c . → S C M A c ., c .$	策略 3.a	—	—
$W C M A c ., c . → W C M A c ., c .$	—	—	—
$W C M A c ., c . → N C M A c ., c .$	策略 1	策略2.b	—
$N C M A c ., c . → S C M A c ., c .$	策略 3.b	策略2.a	—
$N C M A c ., c . → W C M A c ., c .$	策略 1	策略2.b	—
$N C M A c ., c . → N C M A c ., c .$	—	—	—

$I D = 0.85$	考虑冲突调整策略
结束条件触发时间	3	1
是否达成共识	是	否
意见整体调整度	170.5	13.5

$I D = 0.75$	考虑冲突调整策略
结束条件触发时间	3	6
是否达成共识	是	是
意见整体调整度	173.9	198.9

对象	$0.75 + C P$	0.75	$0.85 + C P$	0.85
$a 1$	-1	-1	-1	-1
$a 2$	-1	-1	-1	0
$a 3$	1	1	1	0
$a 4$	0	0	0	0
$a 5$	1	1	1	0
$a 6$	0	-1	0	0
$a 7$	-1	-1	-1	0
$a 8$	-1	-1	-1	0
$a 9$	1	1	1	1
$a 10$	0	0	0	0
$a 11$	1	1	1	1
$a 12$	1	1	1	1
$a 13$	1	1	1	1
$a 14$	1	1	1	1
$a 15$	-1	-1	-1	0
$a 16$	1	1	1	1
$a 17$	1	1	1	1
$a 18$	0	0	0	0
$a 19$	-1	-1	-1	-1
$a 20$	0	0	0	0

$I D = 0.85$	考虑冲突调整策略
结束条件触发时间	3	2
是否达成共识	是	否
意见整体调整度	187.1	13.6

$I D = 0.75$	考虑冲突调整策略
结束条件触发时间	3	7
是否达成共识	是	是
意见整体调整度	187.4	200.1

对象	$0.75 + C P$	0.75	$0.85 + C P$	0.85
$a 1$	-1	-1	-1	-1
$a 2$	-1	-1	-1	-1
$a 3$	0	0	0	0
$a 4$	-1	-1	-1	0
$a 5$	1	1	1	1
$a 6$	1	1	1	1
$a 7$	-1	-1	-1	-1
$a 8$	1	1	1	1
$a 9$	0	0	0	0
$a 10$	0	1	1	0
$a 11$	1	1	1	1
$a 12$	-1	-1	-1	0
$a 13$	-1	-1	-1	0
$a 14$	0	0	0	0
$a 15$	-1	-1	-1	-1
$a 16$	1	1	1	1
$a 17$	-1	-1	-1	-1
$a 18$	-1	-1	-1	0
$a 19$	1	1	1	1
$a 20$	0	0	0	0

References 30

[1]	Gou X J， Xu Z S， Liao H C. Hesitant fuzzy linguistic possibility degree-based linear assignment method for multiple criteria decision-making［J］. International Journal of Information Technology & Decision Making （IJITDM）， 2019， 18（1）： 35-63.
[2]	Liao H C， Gou X J， Xu Z S， et al. Hesitancy degree-based correlation measures for hesitant fuzzy linguistic term sets and their applications in multiple criteria decision making［J］. Information Sciences， 2020， 508： 275-292.
[3]	Ren Z L， Xu Z S， Wang H. Multi-criteria group decision-making based on quasi-order for dual hesitant fuzzy sets and professional degrees of decision makers［J］. Applied Soft Computing， 2018， 71： 20-35.
[4]	高俊山，谷冬元，徐章艳，等. 一个Pawlak粗糙集冲突分析模型的改进［J］. 中国管理科学， 2008， 16（2）： 150-156.
	Gao J S， Gu D Y， Xu Z Y， et al. New conflict analysis model based on rough set theory［J］. Chinese Journal of Management Science， 2008， 16（2）： 150-156.
[5]	朱建军，王翯华，胡宏宇，等. 群决策中指标冲突问题的证据推理决策模型［J］. 中国管理科学， 2012， 20（S1）： 101-107.
	Zhu J J， Wang H H， Hu H Y， et al. Evidence reasoning model of index conflict problem in group decision［J］. Chinese Journal of Management Science， 2012， 20（S1）： 101-107.
[6]	张慧敏，李小南. 基于冲突分析的犹豫模糊多属性决策［J］. 模式识别与人工智能， 2020， 33（7）： 610-618.
	Zhang H M， Li X N. Hesitant fuzzy multi-attribute decision making based on conflict analysis［J］. Pattern Recognition and Artificial Intelligence， 2020， 33（7）： 610-618.
[7]	Wu J， Dai L F， Chiclana F， et al. A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust［J］. Information Fusion， 2018， 41： 232-242.
[8]	Wang M W， Liang D C， Xu Z S. Sequential three-way multiple attribute group decisions with individual attributes and its consensus achievement based on social influence［J］. Information Sciences， 2020， 518： 286-308.
[9]	Gou X J， Xu Z S， Wang X X， et al. Managing consensus reaching process with self-confident double hierarchy linguistic preference relations in group decision making［J］. Fuzzy Optimization and Decision Making， 2021， 20（1）： 51-79.
[10]	Zhang Z， Gao Y， Li Z L. Consensus reaching for social network group decision making by considering leadership and bounded confidence［J］. Knowledge-Based Systems， 2020， 204： 106240.
[11]	熊国强，张婷，王海涛. 情绪影响下群体性冲突的RDEU博弈模型分析［J］. 中国管理科学， 2015， 23（9）： 162-170.
	Xiong G Q， Zhang T， Wang H T. The RDEU game model analysis of group conflict influenced by emotion［J］. Chinese Journal of Management Science， 2015， 23（9）： 162-170.
[12]	Pessoa L， Medina L， Desfilis E. Refocusing neuroscience： Moving away from mental categories and towards complex behaviours［J］. Philosophical Transactions of the Royal Society B： Biological Sciences， 2022， 377（1844）： 20200534.
[13]	Holley R A， Liggett T M. Ergodic theorems for weakly interacting infinite systems and the voter model［J］. The Annals of Probability， 1975，3（4）： 643-663.
[14]	Berger R L. A necessary and sufficient condition for reaching a consensus using DeGroot’s method［J］. Journal of the American Statistical Association， 1981， 76（374）： 415-418.
[15]	DeGroot M H. Reaching a consensus［J］. Journal of the American Statistical Association， 1974， 69（345）： 118-121.
[16]	Friedkin N E， Johnsen E C. Social influence and opinions［J］. The Journal of Mathematical Sociology， 1990， 15（3-4）： 193-206.
[17]	Friedkin N E， Proskurnikov A V， Tempo R， et al. Network science on belief system dynamics under logic constraints［J］. Science， 2016， 354（6310）： 321-326.
[18]	Hegselmann R， Krause U. Opinion dynamics and bounded confidence： Models， analysis and simulation［J］. Journal of Artificial Societies and Social Simulation， 2002， 5： 8130429.
[19]	Hegselmann R， König S， Kurz S， et al. Optimal opinion control： The campaign problem［J］. Journal of Artificial Societies and Social Simulation， 2015， 18（3）： 18.
[20]	Weisbuch G， Deffuant G， Amblard F， et al. Meet， discuss， and segregate！［J］. Complexity， 2002， 7（3）： 55-63.
[21]	Pawlak Z. An inquiry into anatomy of conflicts［J］. Information Sciences， 1998， 109（1-4）： 65-78.
[22]	Yao Y Y. Three-way conflict analysis： Reformulations and extensions of the Pawlak model［J］. Knowledge-Based Systems， 2019， 180： 26-37.
[23]	Lang G M， Miao D Q， Cai M J. Three-way decision approaches to conflict analysis using decision-theoretic rough set theory［J］. Information Sciences， 2017， 406： 185-207.
[24]	Lang G M， Miao D Q， Fujita H. Three-way group conflict analysis based on Pythagorean fuzzy set theory［J］. IEEE Transactions on Fuzzy Systems， 2020， 28（3）： 447-461.
[25]	Sun B Z， Chen X T， Zhang L Y， et al. Three-way decision making approach to conflict analysis and resolution using probabilistic rough set over two universes［J］. Information Sciences， 2020， 507： 809-822.
[26]	Yao Y Y. Symbols-Meaning-Value （SMV） space as a basis for a conceptual model of data science［J］. International Journal of Approximate Reasoning， 2022， 144： 113-128.
[27]	Nanay B. Perception， cognition， action［J］.Oxford Bibliographies，2016，DOI：10.1093/OBO/9780195396577-0326 .
[28]	Liang D C， Yi B C， Xu Z S. Opinion dynamics based on infectious disease transmission model in the non-connected context of Pythagorean fuzzy trust relationship［J］. Journal of the Operational Research Society， 2021， 72（12）： 2783-2803.
[29]	Yao Y Y. Three-way decisions with probabilistic rough sets［J］. Information Sciences， 2010， 180（3）： 341-353.
[30]	Yao Y Y. Three-way decision and granular computing［J］. International Journal of Approximate Reasoning， 2018， 103： 107-123.

Consensus Model of Group Decision Making Based on Three-way Conflict Analysis Considering Conflict Perception

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 14

References 30

Related Articles 15

Metrics

Comments

Recommended 0

[1]	Faming Zhang, Jiangtao Han, Linqian Zhang, Shuqi Zhu. Multi-Attribute Large Group Decision Making Method Based on T₂PLD Operator in Social Trust Network [J]. Chinese Journal of Management Science, 2025, 33(9): 177-188.
[2]	Ren Mu, Lining Hao, Ankang Li, Shuyi Zhang, Wei Cui. Group Ranking Data Envelopment Analysis Model [J]. Chinese Journal of Management Science, 2025, 33(7): 24-32.
[3]	Chengwei Zhao, Xuanhua Xu, Ruihuan Liu, Jishan He. Multi-attribute Group Decision-making and Its Application Considering Dual Interaction and Incomplete Rational Psychology in Fuzzy Heterogeneous Environment [J]. Chinese Journal of Management Science, 2025, 33(6): 182-195.
[4]	Yang Jiao,Gang Li,Jianping Li,Bin Wang,Zhipeng Zhang. Research on the Weighting Method for Group Decision Considering Effective Information of Experts [J]. Chinese Journal of Management Science, 2024, 32(8): 107-116.
[5]	Haolun Wang. Spent Power Battery Recycling Technology Selection Based on Integrated CoCoSo and Heronian Mean with Intuitionistic Linguistic Rough Number [J]. Chinese Journal of Management Science, 2024, 32(5): 24-37.
[6]	Lisheng Jiang,Huchang Liao. Risk-efficiency Mixed Consensus Model Considering Consensus Efficiency and Misjudgment Risk [J]. Chinese Journal of Management Science, 2024, 32(2): 23-30.
[7]	Mengqi Li, Gaofeng Liu, Yejun Xu, Xia Liu, Huimin Wang. Research on Consensus of Social Network Group Decision Making Considering Experts' Trust Risk Behaviors Mining and Dynamic Management [J]. Chinese Journal of Management Science, 2024, 32(11): 144-156.
[8]	XU Xuan-hua, MA Zhi-peng, CHEN Xiao-hong. Dynamic Evolution Research on Emergency Decision Quality of Large Group Based on the Public Preferences Big Data [J]. Chinese Journal of Management Science, 2022, 30(7): 140-149.
[9]	PENG You, LIU Xiao-he, SUN Jian-bo. Interval-Valued Intuitionistic Fuzzy Multi-attribute Group Decision Making Approach Based on the Hesitancy Degrees and Correlation Coefficient [J]. Chinese Journal of Management Science, 2021, 29(8): 229-240.
[10]	LI Lei, ZHANG Shu-yang. Aggregation Method of Intuitionistic Fuzzy Numbers with Minimized Maximal Compromise under Consensus Condition [J]. Chinese Journal of Management Science, 2021, 29(2): 168-176.
[11]	YAO Sheng-bao, GU Miao. A Consensus Model for Group Decision Making under the Influence of Empathy [J]. Chinese Journal of Management Science, 2021, 29(11): 203-214.
[12]	LIU Jin-pei, YANG Hong-wei, CHEN Hua-you, ZHOU Li-gang. Group Decision Making with Interval Multiplicative Linguistic Preference Relations based on Cross-efficiency DEA and Group Consensus [J]. Chinese Journal of Management Science, 2020, 28(2): 190-198.
[13]	ZHAO Meng, ZHANG Chen-xi, HU Yi-qi, LI Gang. Multi-attribute Group Decision Making Method based on Aspiration Satisfaction Function [J]. Chinese Journal of Management Science, 2020, 28(2): 220-230.
[14]	LIU Pei-de, TENG Fei. Multiple Attribute Group Decision-Making Method Based on Evidential Reasoning and Generalized Shapley for Extended Probabilistic Linguistic Term Set [J]. Chinese Journal of Management Science, 2020, 28(11): 206-218.
[15]	DU Yuan-wei, WANG Su-su, YANG Ning, ZHOU Wen. Multiple Attribute Large-group Decision-making Method with Incomplete Information by Considering Expert's Knowledge Structure [J]. Chinese Journal of Management Science, 2017, 25(12): 167-178.