scholarly journals Study on the Temporal and Spatial Differentiation of Provincial Tourism Efficiency in Eastern China and Influencing Factors

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Huadi Wang ◽  
Shaogui Xu ◽  
Qiuyi Xie ◽  
Jianying Fan ◽  
Nianxing Zhou
Keyword(s):  
Economic Development ◽  
Influencing Factors ◽  
Labour Force ◽  
Eastern China ◽  
Regional Distribution ◽  
Malmquist Index ◽  
Spatial Differentiation ◽  
Scale Efficiency ◽  
Resource Endowment ◽  
Temporal And Spatial

Tourism efficiency can be used to effectively measure the utilization of regional tourism resources and the state of tourism economic development. Based on the super efficiency DEA model, Malmquist index, and spatial econometric model, this article measures the static and dynamic tourism efficiency of 11 provinces and cities in eastern China for 2010 to 2019. In combining ArcGIS 10.0 and MATLAB 2016b software, this article studies the temporal and spatial differentiation of tourism efficiency in eastern provinces and cities and influencing factors. The results show that (1) the overall tourism efficiency of eastern provinces is at a high level and relatively stable, but the regional distribution is quite varied, and problems of spatial imbalance are prominent; (2) the overall tourism efficiency of eastern provinces is increasing, and the change index of technical efficiency contributes the most, followed by the change index of scale efficiency; and (3) industrial status, traffic conditions, tourism resource endowment, and the labour force are the main factors affecting the temporal and spatial differentiation of tourism efficiency in eastern provinces and cities, while the level of economic development and information technology have no significant impact.

scholarly journals Temporal and Spatial Differentiations in Environmental Governance

2018 ◽  
Vol 15 (10) ◽  
pp. 2242 ◽  
Author(s):  
Benhong Peng ◽  
Yue Li ◽  
Guo Wei ◽  
Ehsan Elahi
Keyword(s):  
Economic Development ◽  
Technological Progress ◽  
Environmental Governance ◽  
Industrial Structure ◽  
Efficiency Index ◽  
Tobit Model ◽  
Scale Efficiency ◽  
Spatial Efficiency ◽  
Urban Construction ◽  
Temporal And Spatial

With the general degradation of environmental carrying capacity in recent years, many developing countries are facing with the dual task of economic development and environmental protection. To explore the issue of urban environmental governance, in this research, we establish a Data Envelopment Analysis (DEA) model to investigate the environmental governance regarding temporal and spatial efficiency. Further, we deconstruct environmental governance efficiency into comprehensive efficiency, pure technical efficiency, and scale efficiency and develop a Tobit model to analyze the influencing factors affecting urban environmental governance efficiency. In addition, the above DEA, Tobit model, and deconstruction of efficiency have been applied to study environmental governance efficiency for the Yangtze River urban agglomeration. Findings include: (1) The gap in environmental governance efficiency between cities is highly noticeable, as the highest efficiency index is 0.934, the lowest is only 0.246, and the comprehensive efficiency index has fallen sharply from 0.708 to 0.493 in the past 10 years; (2) Environmental governance efficiency is basically driven by technological progress, while the scale efficiency change index is the main driver of the technological progress change index; (3) For environmental governance efficiency, urbanization and capital openness are irrelevant factors, economic level and urban construction are unfavorable factors, and industrial structure and population density are favorable factors. These findings will help urban agglomerations to effectively avoid the adverse effects of environmental governance efficiency in economic development, and achieve a coordinated development of urban construction and environmental governance.

scholarly journals Analysis of Main Influencing Factors of Global Electrification Development

2020 ◽  
Vol 165 ◽  
pp. 06025
Author(s):  
Junshu Feng ◽  
Peng Wang
Keyword(s):  
Economic Development ◽  
Influencing Factors ◽  
Development Process ◽  
Industrial Structure ◽  
Urbanization Level ◽  
Resource Endowment ◽  
The World ◽  
Development Paths ◽  
Policy Guidance

Based on the analysis of electrification development process in major countries, this paper systematically studied and judged 5 important influencing factors of electrification development in the world, including resource endowment, economic development, improvement of people’s livelihood, infrastructure and policy guidance, among economic development includes industrial structure and urbanization level. The opinions of this paper can support different regions or countries to choose proper electrification development paths.

scholarly journals Spatial Differentiation and Influencing Factors of Water Pollution-Intensive Industries in the Yellow River Basin, China

2022 ◽  
Vol 19 (1) ◽  
pp. 497
Author(s):  
Haibo Du ◽  
Xuepeng Ji ◽  
Xiaowei Chuai
Keyword(s):  
Water Pollution ◽  
Influencing Factors ◽  
River Basin ◽  
Yellow River ◽  
Spatial Differentiation ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Resource Endowment ◽  
The Yellow River Basin ◽  
Concentration Of Industries

The structure adjustment and layout optimization of water pollution-intensive industries (WPIIs) are crucial to the health and sustainable development of the watershed life community. Based on micro-detailed data of Chinese industrial enterprises from 2003 to 2013, we analyzed and revealed the spatial differentiation characteristics and influencing factors of WPIIs in the Yellow River Basin (YRB) from 2003 to 2013 by constructing a water pollution-intensive index and integrating kernel density estimation and geographically weighted regression models from a watershed perspective. The results show that: (1) the scale of WPIIs in the YRB showed a growth trend from 2003 to 2013, and the output value increased from 442.5 billion yuan in 2003 to 6192.4 billion yuan in 2013, an increase of 13 times. (2) WPIIs are generally distributed in an east-west direction, and their spatial distribution is river-side, with intensive distribution in the downstream areas and important tributaries such as Fen River and Wei River. (3) WPIIs are generally clustered in high density downstream, but the spatial clustering characteristics of different industries varied significantly. The chemical industries, paper industries, etc. were mainly concentrated in downstream areas. Processing of food from agricultural products was distributed in the upper, middle and downstream areas. Resource-intensive industries such as coal and oil were concentrated in energy-rich midstream areas. (4) Natural resource endowment was the main factor affecting the distribution of WPIIs in the midstream and upstream areas of the basin, and technological innovation played a significant role in the distribution of downstream industries. The level of economic development and industrial historical foundation promoted the geographical concentration of industries. The scale of wastewater discharge and the proximity of rivers influenced the concentration of industries in the midstream and downstream.

A note on the stabilities of work trip travel demands in Toronto

1986 ◽  
Vol 13 (3) ◽  
pp. 389-395 ◽  
Author(s):  
B. G. Hutchinson
Keyword(s):  
Labour Force ◽  
Spatial Differentiation ◽  
Labour Force Participation ◽  
Careful Consideration ◽  
Trip Generation ◽  
Home Based ◽  
Temporal And Spatial ◽  
Work Trip ◽  
Census Metropolitan Area ◽  
Over Time

The 1971 and 1981 census journey-to-work data are used to examine the temporal and spatial stabilities of home-based work trip travel demands in the Toronto census metropolitan area (CMA). Regression analysis is used to establish consistent trip generation equations at the census tract level using population, household, and dwelling unit data; the stabilities of alternative equations over time are examined. All of the partial regression coefficients shifted over time, reflecting the substantial changes that have occurred in household structure, female labour force participation, and the characteristics of the housing market. The spatial distributions of the residuals are examined in terms of the spatial differentiation that exists in the household sector in the Toronto CMA in terms of variables such as household size, population age, and occupation status. The use of traditional trip generation techniques is difficult to sustain given the temporal and spatial variations in the trip generation rate. It is concluded that travel demands can only be estimated from a careful consideration of the residential dynamics of the major subareas in a region.

scholarly journals Spatial–Temporal Heterogeneity and the Related Influencing Factors of Tourism Efficiency in China

2021 ◽  
Vol 13 (11) ◽  
pp. 5825
Author(s):  
Zhiliang Liu ◽  
Chengpeng Lu ◽  
Jinhuang Mao ◽  
Dongqi Sun ◽  
Hengji Li ◽  
...  
Keyword(s):  
Spatial Pattern ◽  
Influencing Factors ◽  
High Efficiency ◽  
Southern China ◽  
Malmquist Index ◽  
Northern China ◽  
Tourism Industry ◽  
Environmental Cost ◽  
Resource Endowment ◽  
Low Efficiency

Tourism efficiency is an effective index of measuring the development quality of the tourism industry. In this study, the tourism efficiency of 30 provinces in China during the period from 2006 to 2018 was measured with the SBM model and Malmquist index. On the basis of ESDA and GWR models, we explored the spatial pattern of China’s tourism efficiency and the spatial heterogeneity of the influencing factors in depth. The results revealed that China’s tourism efficiency has been constantly enhanced with an increasingly balanced pattern. Meanwhile, the utilization degrees of various input factors have constantly been improving. Both technological efficiency and technological progress jointly promote rapid growth of total-factor productivity. Accompanied with constant enhancement of the spatial agglomeration effect, the local spatial pattern also showed obvious differentiation. In general, low-efficiency regions were mainly concentrated in northern China, while high-efficiency regions were concentrated in southern China. The distinct spatial–temporal differentiation characteristics of tourist economic efficiency can be attributed to different influencing strengths of various factors in various regions and different action tendencies. The level of economic development, traffic conditions, the professional level of tourism, and openness degree can significantly promote tourism efficiency. Tourism resource endowment and environmental cost impose slight effects and differ in action direction, thereby inhibiting the tourism efficiency of many regions.

Living on a low income as a systemic impediment to socio-economic development of Ukraine

2020 ◽  
pp. 99-109
Author(s):  
NATALIIA TOLSTYKH
Keyword(s):  
Economic Development ◽  
Social Welfare ◽  
Low Income ◽  
Labour Force ◽  
Well Being ◽  
Social Consequences ◽  
Human Potential ◽  
Subsistence Level ◽  
Socio Economic Development ◽  
The Government

The article sheds light on various approaches that seek to determine how widespread poverty and life on a low income are in Ukraine nowadays. As a social phenomenon, poverty has traditionally been associated with destitution and living below the subsistence level set by the government. However, the author holds the view that life on a low income not only means living near or below the poverty line. There is another part of Ukraine’s population that should also be considered needy — those whose income is less than twice as the subsistence level, and most of them are also subject to socio-economic deprivation. Drawing upon the findings of a social survey conducted by the Institute of Sociology of the NAS of Ukraine in 2019, the paper analyses the standard of living among different income groups. Particular attention is given to consumption patterns and social well-being of respondents in the lower income brackets. From the data, it can be inferred that living conditions of many Ukrainians are inadequate to sustain and develop human potential; furthermore, the low-income households have literally to struggle every day to make ends meet. The author brings into focus the main macroeconomic factors contributing to this situation and its adverse effect on the nation’s social potential. Some of the most common social consequences of living on a low income have been identified, such as limited consumption, a person’s dissatisfaction with life and his/her position in society. The above-mentioned survey also provides the estimates of how much the current subsistence level (with regard to Ukraine) should be. Having been made by different socio-demographic and occupational groups of Ukraine’s population, these estimates are a useful source of information — given that subsistence level is considered the basic social standard. According to the survey, all these figures are at variance with the official subsistence level, which is noticeably lower, and this indicates that the current subsistence level needs an upward revision. Today, the overall socio-economic situation in Ukraine is unfavourable for neoliberal economic reforms initiated by the government. Since these policies are primarily designed to reduce the role of state in managing the economy and implementing social welfare programmes, following this path will inevitably result in the entrenchment of mass poverty and in a major loss of Ukraine’s human potential, as well as labour force. The author argues that tackling the country’s chronic low income problem is only possible if a new strategy for socio-economic development is adopted, where social welfare is prioritised.

scholarly journals Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors

2020 ◽  
Vol 12 (4) ◽  
pp. 1502 ◽  
Author(s):  
Xia Wang ◽  
Lijun Zhang ◽  
Yaochen Qin ◽  
Jingfei Zhang
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Manufacturing Industry ◽  
Ferrous Metal ◽  
Bohai Bay ◽  
High Carbon ◽  
Intergovernmental Panel ◽  
Resource Endowment ◽  
Regional Factors ◽  
Lock In

There are industry lock-in and regional lock-in phenomena in China’s manufacturing industry carbon emissions. However, the existing researches often focus on global carbon emissions, which is not adverse to finding the main problems of manufacturing industry carbon emissions. The biggest contributions of this study are the identification of the industry lock-in and regional lock-in of China’s manufacturing industry and the finding of the regional factors that affect the carbon lock-in of the manufacturing industry, which points out the direction for the low-carbon transformation of the local manufacturing industry. This paper is based on the IPCC (Intergovernmental Panel on Climate Change) carbon emissions coefficient method and energy consumption data from 2000 to 2016 to count the manufacturing industry carbon emissions of 30 provinces in China (except Hong Kong, Macao, Taiwan and Tibet). On this basis, the paper uses a spatial–temporal geographical weighted regression (GTWR) model to analysis the regional influencing factors of the high-carbon manufacturing industry. Results demonstrate that China’s high-carbon manufacturing industry mainly concentrates on the ferrous metal processing industry, non-metallic mineral manufacturing industry and other sectors. In addition, the carbon emissions of high-carbon manufacturing industries are mainly concentrated in Bohai Bay and the North China Plain. The industrial structure and economic scale are the main reasons for the regional carbon lock-in of the high-carbon manufacturing industry, and the strength of the lock-in has continued to increase. Resource endowment is a stable factor of carbon lock-in in high-carbon regions. Technological progress helps to unlock carbon, while foreign direct investment results in the enhancement of carbon regional lock-in. This study focuses on the regional factors of carbon lock-in in the manufacturing industry, hoping to provide decision support for the green development of China’s manufacturing industry.

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