PMID- 36570042
OWN - NLM
STAT- Publisher
LR  - 20240216
IS  - 2198-6053 (Electronic)
IS  - 2199-4536 (Print)
IS  - 2199-4536 (Linking)
DP  - 2022 Dec 19
TI  - Assessment of regional economic restorability under the stress of COVID-19 using 
      the new interval type-2 fuzzy ORESTE method.
PG  - 1-36
LID - 10.1007/s40747-022-00928-x [doi]
AB  - The economic implications from the COVID-19 crisis are not like anything people 
      have ever experienced. As predictions indicated, it is not until the year 2025 
      may the global economy recover to the ideal situation as it was in 2020. Regions 
      lacked of developing category is among the mostly affected regions, because the 
      category includes weakly and averagely potential power. For supporting the 
      decision of economic system recovery scientifically and accurately under the 
      stress of COVID-19, one feasible solution is to assess the regional economic 
      restorability by taking into account a variety of indicators, such as development 
      foundation, industrial structure, labor forces, financial support and 
      government's ability. This is a typical multi-criteria decision-making (MCDM) 
      problem with quantitative and qualitative criteria/indicator. To solve this 
      problem, in this paper, an investigation is conducted to obtain 14 indicators 
      affecting regional economic restorability, which form an indicator system. The 
      interval type-2 fuzzy set (IT2FS) is an effective tool to express experts' 
      subjective preference values (PVs) in the process of decision-making. First, some 
      formulas are developed to convert quantitative PVs to IT2FSs. Second, an improved 
      interval type-2 fuzzy ORESTE (IT2F-ORESTE) method based on distance and 
      likelihood are developed to assess the regional economic restorability. Third, a 
      case study is given to illustrate the method. Then, robust ranking results are 
      acquired by performing a sensitivity analysis. Finally, some comparative analyses 
      with other methods are conducted to demonstrate that the developed IT2F-ORESTE 
      method can supporting the decision of economic system recovery scientifically and 
      accurately.
CI  - (c) The Author(s) 2022.
FAU - Zhang, Hui
AU  - Zhang H
AD  - School of Business, Heze University, Heze, Shandong China. GRID: grid.440746.5. 
      ISNI: 0000 0004 1769 3114
FAU - Gao, Hui
AU  - Gao H
AUID- ORCID: 0000-0001-6394-0217
AD  - School of Business, Heze University, Heze, Shandong China. GRID: grid.440746.5. 
      ISNI: 0000 0004 1769 3114
FAU - Liu, Peide
AU  - Liu P
AD  - School of Management Science and Engineering, Shandong University of Finance and 
      Economics, Jinan, 250014 Shandong China. GRID: grid.443413.5. ISNI: 0000 0000 
      9074 5890
LA  - eng
PT  - Journal Article
DEP - 20221219
PL  - Germany
TA  - Complex Intell Systems
JT  - Complex & intelligent systems
JID - 9918284259706676
PMC - PMC9761058
OTO - NOTNLM
OT  - COVID-19
OT  - Interval type-2 fuzzy set
OT  - ORESTE method
OT  - Regional economic restorability
COIS- Conflict of interestThe authors declare that they have no known competing 
      financial interests or personal relationships that could have appeared to 
      influence the work reported in this paper.
EDAT- 2022/12/27 06:00
MHDA- 2022/12/27 06:00
PMCR- 2022/12/19
CRDT- 2022/12/26 04:28
PHST- 2022/07/03 00:00 [received]
PHST- 2022/11/14 00:00 [accepted]
PHST- 2022/12/26 04:28 [entrez]
PHST- 2022/12/27 06:00 [pubmed]
PHST- 2022/12/27 06:00 [medline]
PHST- 2022/12/19 00:00 [pmc-release]
AID - 928 [pii]
AID - 10.1007/s40747-022-00928-x [doi]
PST - aheadofprint
SO  - Complex Intell Systems. 2022 Dec 19:1-36. doi: 10.1007/s40747-022-00928-x.