Hotel Revenue Convergence: Evidence Across Star Hotels in Chinese Provinces.
Ontology highlight
ABSTRACT: Supplementary information
The online version contains supplementary material available at 10.1007/s11293-022-09745-6.
SUBMITTER: Apergis N
PROVIDER: S-EPMC9185133 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description: Not available
| S-EPMC10866484 | biostudies-literature
Project description:Although haze pollution with PM2.5 as the chief pollutant has become a critical threat worldwide, little research has examined the effects of PM2.5 concentrations on subjective well-being. Based on a longitudinal aggregated panel dataset from Chinese provinces, this study investigates the effects of PM2.5 concentrations on levels of happiness and the inequality of happiness. The results showed that high ground-level PM2.5 concentrations decreased the average level of happiness and high PM2.5 concentrations had stronger negative effects on the happiness of persons with high income than those with low income. In addition, PM2.5 concentrations were also significantly negatively related to inequality of happiness in Chinese provinces. Further empirical tests showed that the negative effects of PM2.5 concentrations on the inequality of happiness could be explained by the stronger influence of PM2.5 concentrations on the subjective well-being of individuals with a higher initial level of happiness than those with a lower initial level of happiness. This confirms that PM2.5 pollution can do harm to subjective well-being and reduce variations in the subjective well-being of individuals. The policy implications of controlling haze pollution and improving well-being are discussed.
| S-EPMC6480587 | biostudies-literature
Project description:The spatial correlation pattern of economic resilience is an important proposition for China's sustainable economic development. This paper measures the economic resilience of 31 provinces in China from 2012 to 2020, and explores the spatial correlation of economic resilience from the overall, group and individual perspectives and its influencing factors. The results show that first, a tightly ordered hierarchy of economic resilience formed in each province of China after 2016. Among them, Jiangsu, Shandong, Guangdong, Hubei, and Shaanxi are the most important clustering points and radiation centers in the spatial correlation framework of economic resilience. Second, being adjacent to marginal and core provinces will maintain the province's centrality index category to the greatest extent, while being adjacent to sub-core and general provinces leads the province to gain more opportunities for upward transfer. Third, the essence of the interprovincial economic resilience subordination linkage in China is manifested in the aggregation of city clusters or economic circles. The northern economic resilience linkage system with the Bohai Rim as the core contains more provinces but is less stable. Provinces located in the Yangtze River Delta region are the opposite. Fourth, the proximity of geographical location and the difference in human capital level drive the formation of spatial association networks, while the difference in external openness and the difference in physical capital inhibit the formation of networks.
| S-EPMC10243094 | biostudies-literature
Project description:Financial inclusion has generally been considered an effective mechanism to support economic growth and reduce Vietnam's poverty for the last decade. While the importance of financial inclusion to economic growth or macroeconomic stability has been widely examined, it appears that the degree of financial inclusion across Vietnam has not attracted attention from academics and policymakers. In particular, a convergence of financial inclusion across provinces in Vietnam has never been examined. This paper is conducted to examine the static and dynamic distributions of financial inclusion across provinces in Vietnam. The latest three biennial surveys from 2014 to 2018 and a novel approach known as the dynamic kernel density function are used in this study. Our results indicate that Vietnam's economic growth and development over the 2014-2018 period is relatively inclusive. The evidence also demonstrates that households provided with access to multiple sources of finance depend significantly on the provincial level of income. We also find that provinces located in the national key economic regions, including (i) the Northern region and (ii) the Southern region, appear to achieve a higher degree of financial inclusiveness. Our findings also confirm the catching-up from the financially disadvantaged provinces to financially advantaged provinces locating within the key economic regions. We argue that understanding the asymmetric effect of economic growth on financial inclusion will be helpful for the Vietnamese government in formulating and implementing economic policies promptly to secure the sustainable and inclusive goals of economic growth and development in the future.
| S-EPMC8389425 | biostudies-literature
Project description:Understanding trends in regional house prices and whether they converge to a single steady state or form clusters are important issues. These trends have been studied at length in respect to advanced and emerging market economies (EMEs). However, the trends are not understood well in the context of a major and populous EME such as India, which can offer vital policy insights for other countries. Using residential house price data for fifty cities, this study showed that house prices do not converge to a single steady state in India. Rather these prices form three clusters wherein they converged to their respective steady-state paths and displayed conditional convergence. Higher initial house price, home loan, rent, population density and literacy were associated with an increased probability of higher house price club. City inflation, on the contrary, increased the chances of association with lower-price clubs. Similar dynamics of housing clusters can enable policymakers to probe the common driving factors and accordingly devise cluster-specific policy measures. There is no study, so far, on club convergence of house prices for India; so this study contributes to this gap in the literature. Supplementary Information The online version contains supplementary material available at 10.1007/s41685-023-00285-8.
| S-EPMC10089830 | biostudies-literature
Project description:Leaf microorganism communities play significant roles in the process of plant growth, but the microbiome profiling of crop leaves is still a relatively new research area. Here, we used 16S rDNA sequencing to profile the microbiomes of 78 primary dried tobacco leaf samples from 26 locations in eight Chinese provinces. Our analyses revealed that the national leaf microbial communities contain 4473 operational taxonomic units (OTU) representing 1234 species, but there is a small, national core microbiome with only 14 OTU representing nine species. The function of this core microbiome is related to processes including nitrogen fixation, detoxification of diverse pollutants, and heavy-metal reduction. The leaf microorganism communities are obviously affected by local environments but did not exhibit obvious relationships to single ecological factors (e.g., temperature, precipitation). Our findings enhance the understanding of microbial diversity of tobacco leaves, which could be utilized for a variety of bioprocess, agricultural, and environmental detoxification applications.
| S-EPMC8878116 | biostudies-literature
Project description:It is important for China to break the "low-end lock" of the manufacturing value chain worldwide by revealing how digital trade promotes and reallocates the export technology complexity of the manufacturing industry. Panel data for 30 provinces in China from 2011 to 2020 were employed to measure the digital trade development and export technology complexity of the manufacturing industry. Benchmark regression, intermediary effect regression, panel threshold and other models were used to test the promotion and reallocation of digital trade on the export technology complexity of the manufacturing industry. The findings are as follows: (1) Digital trade promotes the export technology complexity of the manufacturing industry, with significant regional heterogeneity (eastern, central and western regions), and the most obvious promotion in technology-intensive manufacturing. (2) Technological innovation and human capital play a reallocation role in the process of digital trade, affecting the technological complexity of manufacturing exports, with mediating effects of 14.19% and 8.61%, respectively. (3) Digital trade promotes and reallocates the export technology complexity of the manufacturing industry through industrial structure upgrading, and a nonlinear relationship was found. These results provide empirical support and a decision-making basis for digital trade in promoting the export technology complexity of the manufacturing industry. The development of digital trade should be encouraged; the differential development of digital trade in the eastern, central, and western regions should be boosted; importance should be attached to the intermediary incentive role of technological innovation and human capital; and the upgrading of the industrial structure should be promoted scientifically.
| S-EPMC10513322 | biostudies-literature
Project description:Economic development and ongoing urbanization are usually accompanied by severe haze pollution. Revealing the spatial and temporal evolution of haze pollution can provide a powerful tool for formulating sustainable development policies. Previous studies mostly discuss the differences in the level of PM2.5 among regions, but have paid little attention to the change rules of such differences and their clustering patterns over long periods. Therefore, from the perspective of club convergence, this study employs the log t regression test and club clustering algorithm proposed by Phillips and Sul (Econometrica 75(6):1771-1855, 2007. 10.1111/j.1468-0262.2007.00811.x) to empirically examine the convergence characteristics of PM2.5 concentrations in Chinese cities from 1998 to 2016. This study found that there was no evidence of full panel convergence, but supported one divergent group and eleven convergence clubs with large differences in mean PM2.5 concentrations and growth rates. The geographical distribution of these clubs showed significant spatial dependence. In addition, certain meteorological and socio-economic factors predominantly determined the convergence club for each city.
| S-EPMC8723917 | biostudies-literature
Project description:This paper uses the exogenous shock generated by the COVID-19 pandemic and the relative government response as an informative case in investigating the factors able to affect policy efficacy. Lockdown measures have been widely adopted to limit the diffusion of COVID-19, indirectly supporting the capacity of the hospital system to face the pandemic. Lockdown obliges people to change their social behaviour significantly, and consequently is a matter of serious concern amongst the population. For this reason, how people react to lockdown is of the utmost importance, since failure to observe it properly will be of little benefit in reducing contagion. In this rationale, factors correlated with individuals' behaviour could affect the efficacy of such measures. The aim of this paper is to investigate whether differences in institutional quality and social capital are correlated with the efficacy of lockdown measures, taking the Italian provinces as a case study. Using a quantitative analysis employing F-GLS estimators, our results suggest that both local social capital and institutional quality have affected the efficiency of lockdown measures in Italian provinces. In general terms these factors contribute to forming the set of incentives able to promote individual behaviour that is in closer compliance with government choices. In this perspective, institutional quality and social capital can be considered factors able to influence the efficacy of policies.
| S-EPMC8651260 | biostudies-literature
Project description:Closely connected to human carbon emissions, global climate change is affecting regional economic and social development, natural ecological environment, food security, water supply, and many other social aspects. In a word, climate change has become a vital issue of general concern in the current society. In this study, the carbon emission data of Chinese provinces in 1999-2019 are collected and analyzed, so as to identify the carbon emission of direct consumption per 10,000 residents in each province (including each municipal city and autonomous region) and the entire nation based on population data. The Arc Geographic Information Science Engine (ArcGIS Engine) and C#.NET platform are employed to call the MATLAB neural network toolbox. A model is selected and embedded in the prediction system to develop the entire system. This study demonstrates that the carbon emissions per resident in Northern China are significantly higher than those in Southern China, with the rate of carbon emissions continuing to increase over time. Compared with other models, the Elman neural network has a higher carbon emission prediction accuracy, but with more minor errors. For instance, its accuracy and prediction performance are improved by 55.93% and 19.48%, respectively, compared with the Backpropagation Neural Network (BPNN). The prediction results show that China is expected to reach its peak carbon emission in around 2025-2030. The above results are acquired based on the concept of carbon emissions and neural network model theories, supported by GIS component technology and intelligent methods. The feasibility of BPNN, Radial Basis Function (RBF) and Elman neural network models for predicting residential carbon emissions is analyzed. This study also designs a comprehensive, integrated and extensible visual intelligent platform, which is easy to implement and stable in operation. The trend and characteristics of carbon emission changes from 2027 to 2032 are explored and predicted based on the data about direct carbon emissions of Chinese provincial residents from 1999 to 2019, purposed to provide a scientific basis for the control and planning of carbon emissions.
| S-EPMC8118316 | biostudies-literature