{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:09:47Z","timestamp":1760148587439,"version":"build-2065373602"},"reference-count":28,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,5,24]],"date-time":"2023-05-24T00:00:00Z","timestamp":1684886400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Xi\u2019an University of Posts and Telecommunications 2022 Key Project of Postgraduate Innovation Foundation","award":["CXJJZW2022005"],"award-info":[{"award-number":["CXJJZW2022005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Axioms"],"abstract":"<jats:p>With the development of the cloud computing era, the decision-making environment and algorithm models have become increasingly complex, and traditional decision-making methods have been unable to meet the needs of large group decision-making (LGDM) problems. Firstly, in order to solve this problem, the concept of double hierarchy interval hesitant fuzzy language (DHIHFL) is proposed. Compared with the traditional double hierarchy hesitant fuzzy language (DHHFL), it contains all elements from the lower limit to the upper limit and more comprehensively characterizes the hesitation of language information. Secondly, for LGDM problems, a self-confident double hierarchy interval hesitant fuzzy language (SC-DHIHFL) is developed, and the integration of self-confident degree can better enrich the evaluation information and promote the achievement of group consensus. Thirdly, a new two-stage LGDM method is proposed. The first stage is clustering and grouping and reaching consensus within the group, and the second stage is the integration of LGDM information. The two-stage method contains novel methods such as expert clustering algorithm, subjective and objective comprehensive weight, consensus degree, and deviation weight considering minority opinions. Finally, the proposed LGDM consensus method is applied to a practical LGDM problem, and the effectiveness is verified by comparative analysis with existing methods.<\/jats:p>","DOI":"10.3390\/axioms12060511","type":"journal-article","created":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T02:30:06Z","timestamp":1684981806000},"page":"511","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Two-Stage Large Group Decision-Making Method Based on a Self-Confident Double Hierarchy Interval Hesitant Fuzzy Language"],"prefix":"10.3390","volume":"12","author":[{"given":"Wenyu","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Economics and Management, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710061, China"},{"name":"China Research Institute of Aerospace Systems Science and Engineering, Beijing 100048, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0262-4895","authenticated-orcid":false,"given":"Mengyao","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Modern Posts, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710061, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1904-7071","authenticated-orcid":false,"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Economics and Management, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710061, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,24]]},"reference":[{"key":"ref_1","first-page":"140","article-title":"Dynamic Evolution Research on Emergency Decision Quality of Large Group Based on the Public Preferences Big Data","volume":"30","author":"Xu","year":"2022","journal-title":"Chin. 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