An Empirical Study on the Indirect Empowerment of Economic Development by the Digital Economy-Based on the Perspective of China’s Domestic Economic Cycle

Wang, Xinyi; Chen, Jun

doi:10.1007/s13132-023-01445-z

Cited by 5 publications

(3 citation statements)

References 33 publications

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“…The Theil index can be decomposed into intra-regional and inter-regional variation to better analyze the regional variability 34 . Moreover, the size of the Thiel index has a positive relationship with the variability of health tourism development, i.e., the larger the numerical value, the greater the variability, and the smaller the numerical value, the smaller the variability, and its numerical value range are [0,1] 35 . The equation for calculating the Thiel index is as follows 36 : …”

Section: Methodsmentioning

confidence: 99%

Analysis of spatial-temporal pattern, dynamic evolution and influencing factors of health tourism development in China

Wang,

Feng,

et al. 2023

Sci Rep

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The evaluation index system is constructed based on the connotation and characteristics of health tourism. Using the entropy method, Thiel index, exploratory spatial data analysis method, spatial Markov chain and spatial econometric model, research is carried out around the development index, difference status, spatial-temporal pattern, dynamic evolution and influencing factors of health tourism. The following results were drawn: (1) The development index of health tourism in China is low, but the development speed is fast. The inter-regional development index shows an eastern China > central China > western China pattern, and the development speed exhibits a western China > central China > eastern China situation. (2) In the overall difference in China’s health tourism development, the intra-regional difference is consistently higher than the inter-regional difference. Among the three major regions, the overall difference between eastern China and western China is always higher than that of central China. (3) The development of health tourism in China is positively correlated in the global space, with some local spatial clustering. (4) The dynamic evolution of health tourism development in China shows part of the “Matthew effect” characteristics, with an obvious spatial spillover effect. (5) Various influencing factors produced widely varying direct, indirect and total effects on health tourism development in China, eastern China, central China and western China. Finally, based on the results of the above empirical analysis, policy recommendations to promote the development of health tourism in China are proposed.

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Section: Methodsmentioning

confidence: 99%

Analysis of spatial-temporal pattern, dynamic evolution and influencing factors of health tourism development in China

Wang,

Feng,

et al. 2023

Sci Rep

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“…According to the meanings of the indicators, digital infrastructure, digital technology and digital talent are selected as the input indicators, while digital industrialization and industrial digitization are selected as the output indicators. At the same time, in view of previous research [8,[47][48][49][50] and the principles of data availability, strong discrimination and accuracy, the indicator system is quantified as shown in Table 1.…”

Section: Indicator Selectionmentioning

confidence: 99%

Efficiency Evaluation of China’s Provincial Digital Economy Based on a DEA Cross-Efficiency Model

2023

Mathematics

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The Chinese government clearly put forward a strategy to speed up the development of the digital economy in “the 14th Five-Year” Plan, which will become the booster of China’s development. China has a vast territory and the state of development of the digital economy varies greatly across different regions. It is crucial to clarify the reasons for these differences and take measures to narrow them. Therefore, the evaluation and analysis of the current situation are conducive to the further development of the digital economy. Taking 30 provinces (excluding Tibet, Hong Kong, Macao and Taiwan) of China as the research objects, this paper constructs an index system taking digital infrastructure, digital technology and digital talent as input variables and taking digital industrialization and industrial digitization as output variables. The data envelopment analysis (DEA) cross-efficiency model is constructed to calculate and compare the cross-efficiency of the digital economies in each province. The results show the following: (1) The development efficiency of China’s digital economy has generally been low, and there is a large “digital divide” between provinces. (2) The input of digital talents is crucial for the digital economy in order to achieve high output and high efficiency, and high output is often accompanied by high efficiency. Based on the above conclusions, this paper puts forward some suggestions to promote the development of China’s digital economy.

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“…In the "double-cycle" development pattern, high-quality economic growth puts forward higher requirements for the optimization of industrial structure. Traditional industries can ride on the "De", smooth the motion of production elements, improve the industrial digitalization system, and develop the consumer market [57]. Emerging cultural businesses, the digital derivation of traditional cultural products, the sharing economy and cost dynamic monitoring system, and a series of business links prompt cultural enterprises to upgrade and transform their business, business model, and management.…”

Section: De and Structural Upgrading Of The Cultural Industrymentioning

confidence: 99%

How the Digital Economy Empowers the Structural Upgrading of Cultural Industries—An Analysis Based on the Spatial Durbin Model

Yao,

Song,

Wang

2023

Sustainability

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The digital economy (De) is a major driving force in pushing structural improvements in the cultural industry. Theoretically, the De can empower the structural upgrading of the cultural industry by promoting technological innovation. Empirically, based on the provincial panel data of 31 regions in China from 2013 to 2020, this research utilizes the spatial Durbin model (SDM) to reveal the impact of the De on the structural upgrading of cultural industries. It also utilizes the mediation effect to test the path of the De on the structural upgrading of cultural industries through regional technological innovation. It is found that (1) the structural upgrading of the cultural industry shows significant spatial autocorrelation, and the eastern region is where the high–high cluster pattern predominates. (2) The De could successfully encourage the restructuring of the local cultural industry, and the spillover effect in space also promotes improving the organization of the cultural industry in neighboring regions. (3) A mechanism analysis shows that the De realizes the upgrading of cultural industry structure by enhancing regional technological innovation ability. Based on this, relevant policy recommendations are made to promote the upgrading of cultural industry structure in three dimensions: improving the level of the De, strengthening the ability of inter-regional cooperation, and promoting technological innovation. The study provides an important reference for the upgrading of China’s cultural industry structure from the De’s perspective.

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An Empirical Study on the Indirect Empowerment of Economic Development by the Digital Economy-Based on the Perspective of China’s Domestic Economic Cycle

Cited by 5 publications

References 33 publications

Analysis of spatial-temporal pattern, dynamic evolution and influencing factors of health tourism development in China

Analysis of spatial-temporal pattern, dynamic evolution and influencing factors of health tourism development in China

Efficiency Evaluation of China’s Provincial Digital Economy Based on a DEA Cross-Efficiency Model

How the Digital Economy Empowers the Structural Upgrading of Cultural Industries—An Analysis Based on the Spatial Durbin Model

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