Coupling Coordination and Spatiotemporal Dynamic Evolution Between Medical Services and Tourism Development in China

Analysis the status and spatio-temporal characteristics of the synergistic development of China's multi-level medical insurance system

Examined the synergistic development and spatio-temporal evolution of China's multi-level medical insurance system (MMIS) on a macroscopic level. We assess the comprehensive development of the MMIS across China's 31 provinces from 2011 to 2020 by constructing a comprehensive indicators evaluation model. Subsequently, a coupling coordination index (CCI) model is employed to provide precise insights into the coupling coordination effects among various medical insurance schemes comprising MMIS. Lastly, spatial autocorrelation analysis is conducted to evaluate both the global and local spatio-temporal evolutionary characteristics of MMIS. The CCI of MMIS at the national average level exhibited a fluctuating upward trend, progressing from the moderate disorder recession degree (0.287) in 2011 to the well-coordinated degree (0.887) in 2020. However, the majority of provinces (83.87%) still lingered within the realm of barely coordinated degree ([0.500-0.600]). Specifically, the CCI within the eastern coastal region surpassed that of the western and central regions, with the central region showing the most pronounced increase in CCI. Over the past decade, MMIS demonstrated significant spatial agglomeration, as evidenced by the global Moran's I ranging from [0.1668-0.3037]. Furthermore, findings from local spatial autocorrelation analysis suggest a gradual attenuation in the spatial clustering disparity of CCI across various provinces. Government ought to focus on the spatio-temporal evolution patterns of MMIS, and strengthen cooperation between the government and market in health governance, while utilizing information technology and data sharing to improve the overall quality of medical insurance benefits.

Research on the supply and demand of elderly care service resources in China

PURPOSE

This study aims to assess the current status and spatial distribution differences of elderly care service resources supply and demand in China.

METHODS

Semi-structured qualitative interviews were utilized to gather participants' insights into the current demands for elderly care services, the status of resource allocation, and related indicators. The entropy weight method was employed to determine indicator weights, yielding objective demand and allocation indices for elderly care service resources. Kernel density estimation was used to illustrate the distribution characteristics of the demand and allocation indices. The coupling coordination degree model was applied to measure the coupling coordination level of China's elderly care service resource supply and demand system in 2020.

RESULTS

The demand index ranks highest in Beijing (0.3291), Shanghai (0.2941), and Tianjin (0.2563), while the lowest are found in Tibet (0.1673), Guangxi (0.1727), and Guizhou (0.1737). Kernel density estimation shows that the demand index is concentrated in the range of 0.1800 to 0.2000. The top three regions for allocation index are Shanghai (184.0007), Qinghai (129.8177), and Beijing (109.5941), with the lowest in Liaoning (34.8558), Hainan (35.3168), and Yunnan (36.6366). Kernel density estimation indicates that the allocation index is concentrated in the range of 25-75. Calculations of coupling coordination degree show that Shanghai has high coordination quality (0.9368), Beijing has good coordination (0.8392), while Hainan and Yunnan experience severe imbalances (0.1990, 0.1831).

CONCLUSIONS

There is a significant lack of coordination between the demand for elderly care services and the allocation of resources in Hainan and Yunnan provinces in China. Most provinces, with the exception of Beijing and Shanghai, exhibit some degree of misalignment. The Chinese government should address the varying needs of the elderly population in different regions, pay timely attention to regional disparities, enhance regional cooperation, and dynamically allocate elderly care resources in a rational manner.

Assessment of low-carbon tourism development from multi-aspect analysis: a case study of the Yellow River Basin, China

Climate change has become an unavoidable problem in achieving sustainable development. As one of the major industries worldwide, tourism can make a significant contribution to mitigating climate change. The main objective of the paper is to assess the development level of low-carbon tourism from multi-aspect, using the Yellow River Basin as an example. Firstly, this study quantified tourism carbon dioxide emissions and tourism economy, and analyzed their evolution characteristics. The interaction and coordination degree between tourism carbon dioxide emissions and tourism economy were then analyzed using the improved coupling coordination degree model. Finally, this study analyzed the change in total factor productivity of low-carbon tourism by calculating the Malmquist-Luenberger productivity index. The results showed that: (1) the tourism industry in the Yellow River Basin has the characteristics of the initial environmental Kuznets curve. (2) There was a strong interaction between tourism carbon dioxide emissions and tourism economy, which was manifested as mutual promotion. (3) The total factor productivity of low-carbon tourism was increasing. Based on the above results, it could be concluded that the development level of low-carbon tourism in the Yellow River Basin has been continuously improved from 2000 to 2019, but it is still in the early development stage with the continuous growth of carbon dioxide emissions.

Big data-driven spatio-temporal heterogeneity analysis of Beijing's catering service industry during the COVID-19 pandemic

The Catering Service Industry (CSI) experienced profound impacts due to the COVID-19 pandemic. However, the long-term and multi-timepoint analysis using big data remained limited, influencing governmental decision-making. We applied Kernel Density Estimation, Shannon Diversity Index, and the Geographic detector to explore the spatial heterogeneity and determinants of the CSI in Beijing during the pandemic, with monthly granularity. The temporal-spatial dynamics of the CSI presented a "W"-shaped trend from 2018 to 2023, with pivotal shifts aligning with key pandemic stages. Spatial characteristics exhibited heterogeneity, with greater stability in the city center and more pronounced shifts in peripheral urban zones. Districts facing intricate outbreaks showed lower catering income, and Chinese eateries exhibited heightened resilience compared to others. The CSI displayed strong interconnections with living service sectors. Development in each district was influenced by economic level, population distribution, service facilities convenience, and the risk of the COVID-19 pandemic. Dominant factors included total retail sales of consumer goods, permanent population, average Baidu Heat Index, density of transportation and catering service facilities, infection cases and the consecutive days with confirmed cases existing. Consequently, we suggested seizing post-pandemic recovery as an avenue to unlock the CSI's substantial potential, ushering a fresh phase of growth.

Coupling coordination of the provision of medical services and high-quality economic development in the Yangtze River Economic Belt

Background

Promoting high-level coupling coordination between the provision of medical services (PMS) and high-quality economic development (HED) has emerged as a critical issue in China's pursuit of high-quality development and is now a significant subject of concern in the area of welfare economics.

Materials and methods

Based on panel data from 11 provinces and municipalities in the Yangtze River Economic Belt, covering the period from 2010 to 2020, this study conducted an empirical analysis of the coupling coordination between PMS and HED and its influencing factors. Methods combined a comprehensive evaluation model, a coupling coordination model, and a panel Tobit model.

Results

The study found that: (1) Regarding the overall situation in the Yangtze River Economic Belt, the overall PMS demonstrates a fluctuating upward trend, while HED fluctuates within the lower range of 0.3 to 0.4. The coupling coordination degree between PMS and HED fluctuates within the moderate range of 0.5 to 0.6. (2) In terms of the spatiotemporal evolution trends, there still exists substantial spatial disparity among provinces and municipalities within the Yangtze River Economic Belt regarding PMS; nonetheless, this gap is gradually narrowing. Significant regional disparities are also observed in HED, with Shanghai, Jiangsu, and Zhejiang leading among the provinces and municipalities in the Yangtze River Economic Belt. The coupling coordination degree between PMS and HED displays notable spatial discrepancies, where downstream areas of the Yangtze River Economic Belt such as Shanghai, Jiangsu, and Zhejiang exhibit a higher coupling coordination degree compared to other provinces and municipalities. However, most provinces and municipalities outside this group remain at a moderately coordinated stage concerning the degree of coupling coordination between PMS and HED. (3) Economic development level and local government competition had a significant negative impact on coupling coordination between PMS and HED, whereas there was a significantly positive impact on the degree of fiscal autonomy and urbanization.

Discussion

This study contributes to comprehensively understanding the coupling and coordination relationship between the PMS and HED across provinces and municipalities in the Yangtze River Economic Belt. It provides empirical evidence for the collaborative evolution of PMS and HED.

The coupling coordination between rural public services and rural tourism and its causative factors: The case study of southwestern China

Rural public services and rural tourism are interdependent, and their coordinated development is crucial for promoting rural revitalization and overall growth in China. So far, the existing studies mainly focus on the mutual influence, mutual promotion, and coordination paths of rural public services and rural tourism but fail to conduct an empirical analysis on the coupling coordination of rural public services and rural tourism or summarize the spatial and temporal differences of the coupling coordination. Therefore, we adopt an evaluation index system for rural public services and rural tourism. To measure the development level and the coupling coordination degree of rural public services and rural tourism in southwestern China from 2012 to 2019, we used a comprehensive evaluation model and a coupling coordination degree model. Additionally, geographic detectors were utilised to detect the causative factors of their coupling coordination development. Based on the analysis of research results, we made the following observations. In southwestern China, the comprehensive development of rural public services and rural tourism indicated an upward trend. An additional interactive coupling relationship between the two systems is observed, and its coupling coordination degree increases, with the increment varying from slow to rapid. The type of coupling coordination changes from rural tourism lagging type to rural public service lagging type, and there are spatial differences in the degree of coupling coordination between the two. The coupling coordination development of the two systems is affected by multiple causative forces, such as economic, industrial, resource attraction, and service guarantee forces, and some differences distinguish the driving strengths of both single and interaction factors. The main contribution of this article is to reveal the coupling and coordination relationship between rural public services and rural tourism, to explore the driving factors affecting the degree of coupling and coordination between them, and to make relevant policy recommendations.

Dynamic evolution characteristics and driving factors of tourism ecosystem health in China

Tourism ecosystem health is key to high-quality tourism development. China is now promoting sustainable development and high-quality transformation and upgrading of regional tourism; thus, the research on tourism ecosystem health is of practical significance. Based on the DPSIR model, an evaluation index system of tourism ecosystem health in China was constructed. Then the entropy weight method, spatial autocorrelation analysis, Markov chain analysis, and quantile regression were used to explore the dynamic evolution characteristics and driving factors of tourism ecosystem health in China from 2011 to 2020. The following conclusions were drawn: (1) The tourism ecosystem health in China showed an M-shaped fluctuation process as a whole, with significant spatial correlation and spatial difference. (2) There was a "path-dependent" and "self-locking" effect on the type transfer of tourism ecosystem health, and the type transfer was mainly between adjacent types in successive transfers, with the probability of downward transfer higher than upward transfer, and the geospatial background played a significant role in its dynamic evolution process. (3) In provinces with low tourism ecosystem health type, the negative effect of technological innovation capacity was more significant, and the influence coefficient of the positive effect of tourism environmental regulation and information technology level was larger, while in provinces with high tourism ecosystem health type, the negative effect of tourism industry agglomeration was more significant, and the influence coefficient of the positive effect of tourism industry structure and tourism land-use scale was larger.