4.3 Article

Group Decision Algorithm for Aged Healthcare Product Purchase Under q-Rung Picture Normal Fuzzy Environment Using Heronian Mean Operator

Journal

Publisher

SPRINGERNATURE
DOI: 10.2991/ijcis.d.200803.001

Keywords

Aged healthcare product purchase; Group decision-making; q rung picture normal fuzzy sets; Heronian mean operators

Funding

  1. National Social Science Foundation of China [17ZDA119]
  2. Natural Science Foundation of China [71704007]
  3. Beijing Social Science Foundation of China [18GLC082]
  4. University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province [2017103]
  5. ESRC [ES/L011859/1] Funding Source: UKRI

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With the intensification of the aging, the health issue of the elderly is amusing public concern increasingly Various healthcare products for the elderly are emerging from the market, this how to select suitable aged healthcare product is critical to the wellbeing of the elderly. In the literature, nonetheless, a comprehensive and standardized evaluation framework to support healthcare product purchase decision for the aged is currently lacking. This paper proposes a novel group decision-making method to aid the decision-making of aged healthcare product purchase based on q-rung picture normal fuzzy Heronian mean (q-RPtNoFHM) operators. In it, firstly, a new fuzzy variable called the q-rung picture normal fuzzy set (q-RPtNoFS) is defined to reasonably describe different responses to healthcare product evaluation, for which, some definitions including operational laws, a score function, and an accuracy function of q-RPtNoFSs are introduced. Then, two q-RPtNoFIIM operators are presented to aggregate group decision information. In addition, some properties of q-RPtNoFHM operators, such as monotonicity, commutativity, and idempotency, are discussed. Finally, an example on antihypertensive drugs purchase is gave to illustrate the practicality of the proposed method, and conduct sensitivity analysis to analyze the effectiveness and flexibility of proposed methods. (C) 2020 The Authors. Published by Atlantis Press B.V.

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