3 research outputs found
An optimization model of the acceptable consensus and its economic significance
Purpose
â The purpose of this paper is to construct an optimal resource reallocation model of the limited resource by a moderator for reaching the greatest consensus, and show how to reallocate the limited resources by using optimization methodology once the consensus opinion is reached. Moreover, this paper also devotes to theoretically exploring when or what is the condition that the group decision-making (GDM) system is stable; and when new opinions enter into the GDM, how the level of consensus changes.
Design/methodology/approach
â By minimizing the differences between the individualsâ opinions and the collective consensus opinion, this paper constructs a consensus optimization model and shows that the objective weights of the individuals are actually the optimal solution to this model.
Findings
â If all individual deviations of the decision makers (DMs) from the consensus balance each other out, the information entropy theorem shows this GDM is most stable, and economically each individual DM gets the same optimal unit of compensation. Once the consensus opinion is determined and each individual opinion of the DMs is under an acceptable consensus level, the consensus is still acceptable even if additional DMs are added, and the moderatorâs cost is still no more than a fixed upper limitation.
Originality/value
â The optimization model based on acceptable consensus is constructed in this paper, and its economic significance, including the theoretical and practical significance, is emphatically analyzed: it is shown that the weight information of the optimization model carries important economic significance. Besides, some properties of the proposed model are discussed by analyzing its particular solutions: the stability of the consensus system is explored by introducing information entropy theory and variance distribution; in addition, the effect of adding new DMs on the stability of the acceptable consensus system is discussed by analyzing the convergence of consensus level: it is also built up the condition that once the consensus opinion is determined, the consensus degree will not decrease even when additional DMs are added to the GDM
Proposal for a Fuzzy Model to Assess Cost Overrun in Healthcare Due to Delays in Treatment
Apart from the effects of treating those infected with COVIDâ19, the pandemic has also
affected treatment for other diseases, which has been either interrupted or canceled. The aim of this
paper is to provide a financial model for obtaining the cost overrun resulting from the worsening of
illnesses and deaths for each of the causes considered. To achieve this, first deaths have been
classified into causes of death and for each of these causes, an estimation has been made of the
worsening condition of patients due to delay in treatment. Through these data, a fuzzy relation
between deaths and the worsening condition of patients can be obtained. Next, the expertise process
has been used to estimate cost overrun in relation to patientsâ pathologies. The expertsâ opinions
have been aggregated using ordered weighted average (OWA). Lastly, using fuzzy logic again, a
correction coefficient has been determined, which optimizes the future implementation of the
proposed model without the need for a new estimation of inputs. The paper concludes with a
numerical example for a better comprehension of the proposed theoretical model. Ultimately, it
provides the scientific community in general and in particular managers of public administration
entities with a novel tool for improving the efficiency of the healthcare system