IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v317y2024i1p156-170.html
   My bibliography  Save this article

Trust exploration- and leadership incubation- based opinion dynamics model for social network group decision-making: A quantum theory perspective

Author

Listed:
  • Wang, Peng
  • Liu, Peide
  • Li, Yueyuan
  • Teng, Fei
  • Pedrycz, Witold

Abstract

Social network (SN) holds significant sway over the consciousness and behavior of involved individuals, serving as an evolutionary medium for opinion dynamics models. Consensus is a fundamental concept in group decision-making (GDM). How to effectively explore the opinion evolution during the consensus-reaching process through SN is of paramount significance for decision-making science. Therefore, a dual-mechanism containing trust exploration and leadership incubation is developed for modeling opinion dynamics, creating a favorable condition for achieving consensus. First, a novel mechanism for analyzing the completeness of SN is proposed, encompassing a trust propagation process that considers trust discount and stability, as well as a trust aggregation method grounded by quantum theory. Second, a trust screening rule is discussed to retain the valid indirect trust relationships (TRs), and then a leadership incubation mechanism is developed to promote the effective achievement of consensus opinions in group decision-making. Finally, a numerical study is presented to elucidate the superiority and rationality of the proposed methods, and some simulation experiments and comparative analyses demonstrating the effectiveness and advantages of which are covered.

Suggested Citation

  • Wang, Peng & Liu, Peide & Li, Yueyuan & Teng, Fei & Pedrycz, Witold, 2024. "Trust exploration- and leadership incubation- based opinion dynamics model for social network group decision-making: A quantum theory perspective," European Journal of Operational Research, Elsevier, vol. 317(1), pages 156-170.
    • Handle: RePEc:eee:ejores:v:317:y:2024:i:1:p:156-170
    DOI: 10.1016/j.ejor.2024.03.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221724002236
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2024.03.025?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tong, Huagang & Zhu, Jianjun, 2023. "A parallel approach with the strategy-proof mechanism for large-scale group decision making: An application in industrial internet," European Journal of Operational Research, Elsevier, vol. 311(1), pages 173-195.
    2. Sumin Yu & Zhijiao Du & Xuanhua Xu, 2021. "Hierarchical Punishment-Driven Consensus Model for Probabilistic Linguistic Large-Group Decision Making with Application to Global Supplier Selection," Group Decision and Negotiation, Springer, vol. 30(6), pages 1343-1372, December.
    3. García-Zamora, Diego & Dutta, Bapi & Massanet, Sebastia & Riera, Juan Vicente & Martínez, Luis, 2023. "Relationship between the distance consensus and the consensus degree in comprehensive minimum cost consensus models: A polytope-based analysis," European Journal of Operational Research, Elsevier, vol. 306(2), pages 764-776.
    4. Decui Liang & Fangshun Li & Zeshui Xu, 2023. "A group-based FMEA approach with dynamic heterogeneous social network consensus reaching model for uncertain reliability assessment," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(1), pages 33-47, January.
    5. Li, Yanhong & Kou, Gang & Li, Guangxu & Peng, Yi, 2022. "Consensus reaching process in large-scale group decision making based on bounded confidence and social network," European Journal of Operational Research, Elsevier, vol. 303(2), pages 790-802.
    6. Meng, Fan-Yong & Gong, Zai-Wu & Pedrycz, Witold & Chu, Jun-Fei, 2023. "Selfish-dilemma consensus analysis for group decision making in the perspective of cooperative game theory," European Journal of Operational Research, Elsevier, vol. 308(1), pages 290-305.
    7. Chao, Xiangrui & Kou, Gang & Peng, Yi & Viedma, Enrique Herrera, 2021. "Large-scale group decision-making with non-cooperative behaviors and heterogeneous preferences: An application in financial inclusion," European Journal of Operational Research, Elsevier, vol. 288(1), pages 271-293.
    8. Guo, Weiwei & Gong, Zaiwu & Zhang, Wei-Guo & Xu, Yanxin, 2023. "Minimum cost consensus modeling under dynamic feedback regulation mechanism considering consensus principle and tolerance level," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1279-1295.
    9. Liu, Bingsheng & Zhou, Qi & Ding, Ru-Xi & Palomares, Iván & Herrera, Francisco, 2019. "Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination," European Journal of Operational Research, Elsevier, vol. 275(2), pages 737-754.
    10. Zhen Zhang & Zhuolin Li, 2023. "Consensus-based TOPSIS-Sort-B for multi-criteria sorting in the context of group decision-making," Annals of Operations Research, Springer, vol. 325(2), pages 911-938, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meng, Fan-Yong & Zhao, Deng-Yu & Gong, Zai-Wu & Chu, Jun-Fei & Pedrycz, Witold & Yuan, Zhe, 2024. "Consensus adjustment for multi-attribute group decision making based on cross-allocation," European Journal of Operational Research, Elsevier, vol. 318(1), pages 200-216.
    2. Jana Goers & Graham Horton, 2024. "On the Combinatorial Acceptability Entropy Consensus Metric for Multi-Criteria Group Decisions," Group Decision and Negotiation, Springer, vol. 33(5), pages 1247-1268, October.
    3. Xiangrui Chao & Yucheng Dong & Gang Kou & Yi Peng, 2022. "How to determine the consensus threshold in group decision making: a method based on efficiency benchmark using benefit and cost insight," Annals of Operations Research, Springer, vol. 316(1), pages 143-177, September.
    4. Dombi, József & Jónás, Tamás, 2024. "Consensus measures based on a fuzzy concept," European Journal of Operational Research, Elsevier, vol. 315(2), pages 642-653.
    5. Li, Yanhong & Kou, Gang & Li, Guangxu & Peng, Yi, 2022. "Consensus reaching process in large-scale group decision making based on bounded confidence and social network," European Journal of Operational Research, Elsevier, vol. 303(2), pages 790-802.
    6. Bisht, Garima & Pal, A.K., 2024. "Three-way decisions based multi-attribute decision-making with utility and loss functions," European Journal of Operational Research, Elsevier, vol. 316(1), pages 268-281.
    7. Tiantian Gai & Mingshuo Cao & Francisco Chiclana & Zhen Zhang & Yucheng Dong & Enrique Herrera-Viedma & Jian Wu, 2023. "Consensus-trust Driven Bidirectional Feedback Mechanism for Improving Consensus in Social Network Large-group Decision Making," Group Decision and Negotiation, Springer, vol. 32(1), pages 45-74, February.
    8. Li, Huanhuan & Ji, Ying & Ding, Jieyu & Qu, Shaojian & Zhang, Huijie & Li, Yuanming & Liu, Yubing, 2024. "Robust two-stage optimization consensus models with uncertain costs," European Journal of Operational Research, Elsevier, vol. 317(3), pages 977-1002.
    9. Wenfeng Zhu & Hengjie Zhang & Jing Xiao, 2023. "Coming to Consensus on Classification in Flexible Linguistic Preference Relations: The Role of Personalized Individual Semantics," Group Decision and Negotiation, Springer, vol. 32(5), pages 1237-1271, October.
    10. Monica Martinez-Blasco & Vanessa Serrano & Francesc Prior & Jordi Cuadros, 2023. "Analysis of an event study using the Fama–French five-factor model: teaching approaches including spreadsheets and the R programming language," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-34, December.
    11. Gallego-Losada, María-Jesús & Montero-Navarro, Antonio & García-Abajo, Elisa & Gallego-Losada, Rocío, 2023. "Digital financial inclusion. Visualizing the academic literature," Research in International Business and Finance, Elsevier, vol. 64(C).
    12. Chao Fu & Wenjun Chang, 2024. "A Markov Chain-Based Group Consensus Method with Unknown Parameters," Group Decision and Negotiation, Springer, vol. 33(5), pages 1019-1048, October.
    13. Gong, Zaiwu & Guo, Weiwei & Słowiński, Roman, 2021. "Transaction and interaction behavior-based consensus model and its application to optimal carbon emission reduction," Omega, Elsevier, vol. 104(C).
    14. Zhang, Lifeng & Chao, Xiangrui & Qian, Qian & Jing, Fuying, 2022. "Credit evaluation solutions for social groups with poor services in financial inclusion: A technical forecasting method," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    15. Yadgar Taha M. Hamakhan, 2020. "The effect of individual factors on user behaviour and the moderating role of trust: an empirical investigation of consumers’ acceptance of electronic banking in the Kurdistan Region of Iraq," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-29, December.
    16. József Dombi & Jenő Fáró & Tamás Jónás, 2023. "A Fuzzy Entropy-Based Group Consensus Measure for Financial Investments," Mathematics, MDPI, vol. 12(1), pages 1-18, December.
    17. Gao, Jianwei & Wang, Yaping & Guo, Fengjia & Chen, Jiayi, 2024. "A two-stage decision framework for GIS-based site selection of wind-photovoltaic-hybrid energy storage project using LSGDM method," Renewable Energy, Elsevier, vol. 222(C).
    18. Luis Lorenzo & Javier Arroyo, 2022. "Analysis of the cryptocurrency market using different prototype-based clustering techniques," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-46, December.
    19. Weerasinghe, Kasuni & Scahill, Shane L. & Pauleen, David J. & Taskin, Nazim, 2022. "Big data analytics for clinical decision-making: Understanding health sector perceptions of policy and practice," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    20. Dariush Akbarian & Ali Akbar Bani & Mohsen Rostamy-Malkhalifeh & Farhad Hosseinzadeh Lotfi, 2022. "An algorithm for the anchor points of the PPS of the BCC model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-14, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:317:y:2024:i:1:p:156-170. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.