Background The inequity of healthcare utilization in rural China is serious, and the urban-rural segmentation of the medical insurance system intensifies this problem. To guarantee that the rural population enjoys the same medical insurance benefits, China began to establish Urban and Rural Resident Basic Medical Insurance (URRBMI) nationwide in 2016. Against this backdrop, this paper aims to compare the healthcare utilization inequity between URRBMI and New Cooperative Medical Schemes (NCMS) and to analyze whether the inequity is reduced under URRBMI in rural China. Methods Using the data from a national representative survey, the China Health and Retirement Longitudinal Study (CHARLS), which was conducted in 2015, a binary logistic regression model was applied to analyze the influence of income on healthcare utilization, and the decomposition of the concentration index was adopted to compare the Horizontal inequity index (HI index) of healthcare utilization among the individuals insured by URRBMI and NCMS. Results There is no statistically significant difference in healthcare utilization between URRBMI and NCMS, but in outpatient utilization, there are significant differences among different income groups in NCMS; high-income groups utilize more outpatient care. The Horizontal inequity indexes (HI indexes) in outpatient utilization for individuals insured by URRBMI and NCMS are 0.024 and 0.012, respectively, indicating a pro-rich inequity. Meanwhile, the HI indexes in inpatient utilization under the two groups are − 0.043 and − 0.028, respectively, meaning a pro-poor inequity. For both the outpatient and inpatient care, the inequity degree of URRBMI is larger than that of NCMS. Conclusions This paper shows that inequity still exists in rural areas after the integration of urban-rural medical insurance schemes, and there is still a certain gap between the actual and the expected goal of URRBMI. Specifically, compared to NCMS, the pro-rich inequity in outpatient care and the pro-poor inequity in inpatient care are more serious in URRBMI. More chronic diseases should be covered and moral hazard should be avoided in URRBMI. For the vulnerable groups, special policies such as reducing the deductible and covering these groups with catastrophic medical insurance could be considered.

Decision-makers (DMs) will face severe challenges when selecting an optimal alternative for an emergency response over multiple time periods. The aim of this paper is to develop a novel dynamic emergency decision-making method with probabilistic hesitant fuzzy information for handling emergencies. First, an approach based on the GM(1,1) model for predicting the decision-making information at the next stage is proposed. Second, a new probabilistic hesitant fuzzy distance measure based on the hesitant degree of the probabilistic hesitant fuzzy element is put forward, and a mathematical programming model to determine the stage weights is established. What is more, the closeness degree between each alternative and the ideal alternative is calculated, and the emergency alternatives are ranked on the strength of the technique for order preference by similarity to an ideal solution method. Moreover, a practical example is used to verify the feasibility and rationality of the proposed method. INDEX TERMSDynamic emergency decision-making, probabilistic hesitant fuzzy set (PHFS), GM(1,1) model, TOPSIS method. degree in pure mathematics from Wuhan University, and management science from College of Economics and Management at Nanjing University of Aeronautics and Astronautics, China, respectively. He is an Associate Professor in the school of mathematics and Physics at Anhui University of Technology. His research areas are multiple attribute decision making, clustering analysis, and aggregation operators. His articles are published in the Technological and Economic

Once an emergency event occurs, effective emergency measures should be taken. It is known that the emergency event possesses characteristics of limited time and information, harmfulness, and uncertainty, and the decision makers are often bounded rational under uncertainty and risk. This paper presents a novel approach to emergency decision making with hesitant fuzzy information, which takes regret aversion of the decision makers into account. Firstly, based on the idea of the water-filling theory in the field of wireless communications, a mathematical programming model that can convert the attribute values into a compatible scale and eliminate the influence of different physical dimensions is constructed to determine the attribute weights. Then, a group satisfaction degree function is introduced into the regret theory to depict the psychological behaviors of the decision makers, based on which the perceived utility value function of alternative is constructed. The total perceived utility values of alternatives can be computed, and the ranking order of alternatives is obtained. Finally, a case study on a fire and explosion accident is given to illustrate the application of the proposed method. Besides that, the comparisons show the feasibility and superiority of the proposed method.

The selection of venture capital investment projects is one of the most important decision-making activities for venture capitalists. Due to the complexity of investment market and the limited cognition of people, most of the venture capital investment decision problems are highly uncertain and the venture capitalists are often bounded rational under uncertainty. To address such problems, this article presents an approach based on regret theory to probabilistic hesitant fuzzy multiple attribute decision-making. Firstly, when the information on the occurrence probabilities of all the elements in the probabilistic hesitant fuzzy element (P.H.F.E.) is unknown or partially known, two different mathematical programming models based on water-filling theory and the maximum entropy principle are provided to handle these complex situations. Secondly, to capture the psychological behaviours of venture capitalists, the regret theory is utilised to solve the problem of selection of venture capital investment projects. Finally, comparative analysis with the existing approaches is conducted to demonstrate the feasibility and applicability of the proposed method.

Inclusive growth, which encompasses different aspects of life, is a growth pattern that allows all people to participate in and contribute to growth process. In this paper, a novel hesitant fuzzy multiple attribute decision making (HFMADM) approach based on the nondimensionalization of decision making attributes is presented and then applied to the evaluation of inclusive growth in China. Firstly, a novel generalized hesitant fuzzy distance measure is proposed to calculate the difference and deviation between two hesitant fuzzy elements (hfes) without adding any values into the shorter hesitant fuzzy element. Secondly, the coefficient of variation and efficacy coefficient method are extended to accommodate hesitant fuzzy environment and then used to cope with HFMADM. In the analysis process, non-dimensional treatment for hesitant fuzzy decision data is produced. Lastly, the method proposed in this paper is applied to an example of inclusive growth evaluation problem under hesitant fuzzy environment and the case study illustrates the practicality of the proposed method. Beyond that, a comparative analysis with some other approaches is also conducted to demonstrate the superiority and feasibility of the proposed method.