PurposeHow to identify the critical success factors (CSFs) of public health emergencies (PHEs) is of great practical significance to carry out a scientific and effective risk assessment. The purpose of this paper is to address this issue.Design/methodology/approachIn this paper, the authors propose a new approach to identify the CSFs by hesitant fuzzy linguistic set and a Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach. First, a larger group of experts are clustered into three groups according to similarity degree. Then, the weight of each cluster is determined by the maximum consensus method, and the overall direct influence matrix is obtained by clustering with hesitant fuzzy linguistic weighted geometric (HFLWG) operators. Finally, the overall direct influence matrix is transformed into the crisp direct impact matrix by the score function, and 11 CSFs of PHEs are identified by using the extended DEMATEL method.FindingsIn addition, an example of PHEs shows that the approach has good identification applicability. The approach can be used to solve the problems of fuzziness and subjectivity in linguistic assessments, and it can be applied to identify the customer service framework with the linguistic assessments process in emergency management.Originality/valueThis paper extends the above DEMATEL method to study in the hesitant fuzzy linguistic context. This proposed hybrid approach has a wider application in the high-risk area where disasters frequently occur.

Two aspects of problems including selection of aggregation operator for extreme fuzzy evaluation value and risk attitude of decision makers cannot be well solved in Pythagorean fuzzy (PF) multiattribute group decision making (MAGDM). This paper extends the evidential reasoning aggregation method in the intuitionistic fuzzy environment, expands the dictionary ranking method by constructing interval‐valued numbers through the proposed credibility functions of PF values and the concept of closeness degree, widens the continuous generalized ordered weighted average ( normalC ‐ GOWA ) operator to establish a risk attitude ranking measure, and puts forward a PF MAGDM approach based on risk attitude and evidence reasoning methodology (ERM). First, the proposed method utilizes the ERM to aggregate each decision maker's decision matrix and the weights of the attributes to get his/her aggregated decision matrix. Then, it incorporates the obtained aggregated decision matrices of the experts, the weights of the experts and the ERM to accomplish the aggregated PF value of each alternative. Finally, the ranking measure value of risk attitude on each alternative's PF value is calculated, and the sensitivity analysis on the ranking measure function is carried out. The proposed method has overcome the drawbacks of the existing methods for fuzzy MAGDM in PF environments.

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Massive power batteries (PBs) are crucial to new energy vehicle enterprises. Due to Extended Producer Responsibility (EPR), the third-party reverse logistics provider selection(3PRLPs) process has become an important decision to save cost. This paper uses an innovative combination of qualitative analysis and quantitative data integration to address the PB 3PRLPs problem by using Failure Modes and Effects Analysis (FMEA) and fuzzy evidential reasoning (FER). Firstly, the possible failures and potential effects in the PB 3PRLPs are identified by the FMEA to determine criteria and importance grades. Subsequently, AHP is utilized to calculate the criteria weight based on the importance of grades. FER is creatively applied to address the intersection of assessment grades and allocate the belief degree (BD) of the interaction to fuse heterogeneous data. Additionally, sensitivity analysis is done to look into the stability of the sequencing. Compared with other methods, the proposed method not only solves the subjectivity of AHP weighting but also manipulates probabilistic and fuzzy uncertainties for multi-criteria decision-making (MCDM). This method is useful in quantitatively analyzing the 3PRLPs problem and in providing auxiliary decision support for enterprises.

In view of the current status of government regulation (GR) failure and corporate social responsibility (CSR) deficiency of medicines in China, studies on the influence mechanism of drug safety are needed. In the paper, we design a questionnaire to survey the GR and CSR of drug safety in China. Structural equation model (SEM) based on the questionnaire outcomes is performed to evaluate the multivariate relationships among GR, CSR, and drug safety. The role of extrinsic and intrinsic factors influencing the level of drug safety is elaborated. The results illustrate that GR has a direct impact on drug safety. 1 | INTRODUCTION Drugs have always been recognized as an indispensable commodity in maintaining human life and health. Along with the improvement of life standards, drug safety has attracted consumers' attention (Yan & Tang, 2021). Drug safety management and strengthening drug safety supervision have been valued worldwide as a significant issue. According to the National Bureau of Statistics and the China Medical Products Administration, the number of drug retail chains, wholesalers, and pharmacies with licenses has reached 544,000 in China by the end of 2019. There are also 4529 active pharmaceutical ingredient (API) and preparation manufacturers. With the booming of the drug industries, the Chinese relevant regulatory authorities have increasingly strengthened the supervision of drug safety, setting up the National Medical Products Administration, and so on.