Search

Haze pollution not only affects the quality of economic growth and the image of the government, but also seriously affects public health. With the improvement of climate risk perception, the public is actively seeking all kinds of risk management measures to combat the hazards of haze pollution. The study of the relationship between haze pollution, climate risk perception and the development of commercial health insurance is of great significance to the formulation of haze control policies and the improvement of social security system. This paper attempts to explore the relationship between haze pollution, climate risk perception and commercial health insurance demand by establishing static and dynamic models based on panel data from 31 provinces in China from 2005 to 2022. Also, the spatial spillover effects of haze pollution in different regions on the development of commercial health insurance in other regions are investigated by establishing a spatial Durbin model. It is found that (1) haze pollution has a lagged positive effect on the demand for commercial health insurance; (2) haze pollution has a significant spatial spillover effect on the development of commercial health insurance; (3) this study used Python technology to construct a climate risk perception index, and found that the moderating effect of the residents' perception of climate risk existed significantly, and that the residents might take other measures to manage the risk in the short term, but in the long term, the climate risk perception showed a positive correlation with the level of education. This paper provides implications for government departments and social media to strengthen education and publicity, improve residents' awareness of risk diversification, and deepen the concept of commercial health protection. [ABSTRACT FROM AUTHOR]

This paper summarizes emerging practice and research issues in the health insurance industry. We provide an industry overview, epitomize business analytics applications, and outline current and emerging problems of interest to key stakeholders and researchers in information systems, operations management, and healthcare management. Specifically, we focus on three areas of research that are of importance to the health insurance industry as well as the healthcare system: (i) management and evaluation of intervention programs, (ii) creation of effective provider networks, and (iii) emerging issues such as the impact of a pandemic, patient communication and steering, and technological innovations in health care. We lay out brief details of how each of these problems can be formulated, where the data can be acquired (public and/or proprietary data sets), and provide guidance for solving them. For several of these problems, we provide models that span causal modeling, predictive modeling, and prescriptive modeling. [ABSTRACT FROM AUTHOR]