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Probabilistic double hierarchy linguistic alternative queuing method for real economy development evaluation under the perspective of economic financialization

Author

Listed:
  • Xunjie Gou
  • Pinxin Xiao
  • Deyue Huang
  • Fumin Deng

Abstract

With the development of science and technology, the new road of scientific economic and financial development has played a decisive role in supporting the financial undertaking. To accelerate the economic development, it is very important to increase the guiding role of financial undertaking in the real economy. Therefore, it is necessary to promote the development of the real economy under the perspective of economic financialization based on some actions. To judge the implementation effect of these actions, this paper develops a multiple criteria decision-making (MCDM) method to evaluate them. First, the decision-making matrices are established with the probabilistic double hierarchy linguistic term set in which the probabilities are added to all double hierarchy linguistic terms. Additionally, a weight-determining method is developed to obtain the weight vector of criteria, and we develop a MCDM method named the probabilistic double hierarchy linguistic alternative queuing method (PDHL-AQM), where the decision-making result is intuitive by a directed graph or a 0–1 precedence relationship matrix. Furthermore, we apply the PDHL-AQM to solve a practical MCDM problem involving the real economy development evaluation under the perspective of economic financialization. Finally, some comparative analyses are made to show the advantages and reasonableness of the PDHL-AQM.

Suggested Citation

  • Xunjie Gou & Pinxin Xiao & Deyue Huang & Fumin Deng, 2021. "Probabilistic double hierarchy linguistic alternative queuing method for real economy development evaluation under the perspective of economic financialization," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 34(1), pages 3225-3244, January.
  • Handle: RePEc:taf:reroxx:v:34:y:2021:i:1:p:3225-3244
    DOI: 10.1080/1331677X.2020.1870520
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