Regional Differences In China Research Articles

Regional Comparisons of Contemporary Construction Industry Sustainable Concepts in the Chinese Context

Emerging construction practices such as building information modelling (BIM), prefabrication construction, green building, and integrated project delivery methods are gaining momentum in China, with great potential due to the size of its construction market. Through this, the sustainability level of China’s construction industry is expected to be enhanced from the economic, social and environmental perspectives. So far, there has been limited understanding of how BIM, as a digital technology, would affect other contemporary sustainable construction practices from the industry professionals’ point of view. Limited studies have been carried out to study the regional differences of these contemporary sustainable practices in China. This study adopted a questionnaire-based approach targeting industry professionals from three different metropolitan cities (Shanghai, Guangzhou, and Wenzhou).The follow-up comprehensive statistical analysis revealed that with regards to these contemporary sustainable construction practices, survey participants held much varied views on the growth of renovation projects, traditional Design–Bid–Build delivery, and conventional on-site construction methods. These three types were also generally perceived to have weak correlation with BIM application. Regional comparison further conveyed information on differences in perceptions among survey respondents from these three cities. For example, respondents from Wenzhou perceived more positive effects of BIM use in conventional construction projects. This research addressed the inter-correlation among these emerging sustainable construction practices, as well as the regional differences in China’s construction market. The findings provide insights and the big picture for both governmental authorities and industry practitioners on the latest sustainable practices of China’s construction industry. Recommendations are also offered towards improved economic, social and environmental sustainability performance for construction projects in the country.

Study on Gasoline Vehicle Emission Inventory Considering Regional Differences in China

Rapid growth of China’s urban road vehicles, in particular, the increase in the number of gasoline vehicles, leads to an increase in the traffic congestion and problems pertaining to air pollution. The establishment of the emission inventory of gasoline vehicles is influenced by several factors, like environmental characteristics, vehicle conditions, road conditions, and so on. In order to obtain gasoline vehicle emission inventory in accordance with the actual situation in different regions, this study proposed a method of establishing a list of gasoline vehicles with regional differences. Comprehensive consideration and evaluation of various factors that affect the vehicle emissions were carried out and the corresponding correction factors were obtained. According to the formula of comprehensive emission factor for Zibo city, the emission inventory of gasoline vehicle was established. This method can be effectively utilized to obtain the emission inventory of gasoline vehicles in different cities more accurately and provide theoretical support for control strategies of gasoline vehicle emissions.

Bi-level allocation of carbon emission permits based on clustering analysis and weighted voting: A case study in China

A rational regional allocation scheme of carbon emission permits is important for establishing the nationwide carbon emission trading system (ETS) of China. Considering the vast area and great regional differences in China, a novel bi-level allocation scheme based on clustering analysis and a weighted voting model is proposed in this research. At the first level, 30 regions in China are clustered into four classes according to their characteristics of carbon emissions, which include emission reduction pressure, capacity, responsibility and potential. Then the total carbon emission permits are allocated to each class of regions. At the second level, carbon emission permits are allocated to each province (municipality) within a class. The weighted voting models are developed for both the two levels, where the allocation schemes based on historical emissions, population and GDP are selected by each region according to the different voting rights of each region. The voting rights of each region for choosing its inclined scheme are quantified through a multi-index comprehensive evaluation, which employs the entropy method at the first level due to the lack of prior knowledge and the analytic hierarchy process (AHP) at the second level to increase policy flexibility. The combination of subjective weighting evaluation method (AHP) and objective weighting evaluation method (the entropy method) increases the flexibility of the abatement policy while guaranteeing the objectivity of decision-making process. Case studies of the allocation for carbon emission permits in China by 2020 and 2030 are carried out under the proposed allocation scheme. The derived allocation results show that the proposed allocation scheme can provide a balanced consideration to equality and efficiency, which are compared with those in reported literatures. The proposed allocation scheme can not only encourage all regions to reduce carbon emission intensity, but also achieve in meeting the carbon emission demand of the population in each region.

Influence factor analysis of migrants' settlement intention: Considering the characteristic of city

The settlement intention of migrants is an important factor for urban development. Through examination of existing research we found that the influencing factors on settlement intention differed by region; however, little attention was paid to the factors affecting settlement intention based on regional differences in China. Using data from the National Health and Family Planning Commission of the People's Republic of China, this study chose 282 cities as study areas, First, this was performed through the statistic and spatial analysis of GIS, which explains the effect of the city level variable on settlement intention; then, it introduced a hierarchical linear regression model, combining macro statistics with micro-survey data to explain the factors influencing settlement intention as well as the relationship between the city-level variable and the individual-level variable. The results showed three things: First, the characteristic of city had an impact on the settlement intention. Second, the regional difference of settlement intention was significant, it was interesting insofar as Eastern China attracted the most migrants but the settlement willingness of migrants in the east was the most insignificant. Thirdly considering the characteristic of city, education, age, income, employment status and occupation type had a significant effect on urban settlement intention.

Performance evaluation of China's high-tech innovation process: Analysis based on the innovation value chain

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.

Hazard regionalization of debris-flow disasters along highways in China

Regional differences in China’s natural landscape involve significant differences in the distributions of debris-flow disasters along highways (DFDHs), which makes it very difficult to forecast, identify, and provide early warnings for such disasters. Previous research mainly focused on single-gully debris-flow disasters or a number of debris-flow disasters with similar morphological characteristics, which could not reflect the inherent mechanisms leading to the occurrence of DFDHs. Hazard regionalization of DFDHs in China can clarify the priorities and protection standards for different areas in China, and provide a theoretical basis for macro-policy formulation. We identify the hazard sources of DFDHs, extract hazard assessment indicators, and calculate the weight of each indicator using a cloud model-improved analytic hierarchy process. We draw basic maps of assessment indicators and perform a spatial analysis of hazard of DFDHs using ArcGIS, and a hazard regionalization scheme for DFDHs in China is developed. The results show that the degree of hazard of DFDHs in China ranges from 1.000 to 7.900. China is divided into low, moderate, severe, and extremely severe hazard areas. The extremely severe hazard areas are the Loess Plateau (north part of the QinBa Mountain area), the Taiwan–Wuyi Mountain area, the Sichuan–Yunnan Mountain area, and the Tianshan–Kunlun Mountain area.

Regional differences of urbanization in China and its driving factors

After more than 30 years of rapid urbanization, the overall urbanization rate of China reached 56.1% in 2015. However, despite China’s rapid increase in its overall rate of urbanization, clear regional differences can be observed. Furthermore, inadequate research has been devoted to in-depth exploration of the regional differences in China’s urbanization from a national perspective, as well as the internal factors that drive these differences. Using prefecture-level administrative units in China as the main research subject, this study illustrates the regional differences in urbanization by categorizing the divisions into four types based on their urbanization ratio and speed (high level: low speed; high level: high speed; low level: high speed; and low level: low speed). Next, we selected seven economic and geographic indicators and applied an ordered logit model to explore the driving factors of the regional differences in urbanization. A multiple linear regression model was then adopted to analyze the different impacts of these driving factors on regions with different urbanization types. The results showed that the regional differences in urbanization were significantly correlated to per capita GDP, industry location quotients, urban-rural income ratio, and time distance to major centers. In addition, with each type of urbanization, these factors were found to have a different driving effect. Specifically, the driving effect of per capita GDP and industry location quotients presented a marginally decreasing trend, while main road density appeared to have a more significant impact on cities with lower urbanization rates.

Investigating the role of high-tech industry in reducing China's CO2 emissions: A regional perspective

China currently is the largest emitter of carbon dioxide (CO2) in the world. Moreover, total energy consumption and CO2 emissions in China will continue to increase due to the rapid advance of industrialization and urbanization. Therefore, vigorously developing the high–tech industry becomes an inevitable choice to reduce CO2 emissions at the moment or in the future. However, most of the existing literature analyzes the impact of the high–tech industry on emission mitigation from an aggregate perspective. Few studies have focused on regional differences in China. Based on 1999–2015 panel data of China's 30 provinces, this study uses the STIRPAT model to explore the influence of the high–tech industry on CO2 emission reduction in China from a regional perspective. The results show that the high–tech industry is beneficial to reduce CO2 emissions. Moreover, the impact intensity of the high–tech industry in the eastern region is higher than those in the central and western regions due to significant differences in R&D funding, R&D personnel investments and high–tech purchase expenditure. The study's findings not only contribute to the existing literature, but also worthy of adequate attention from China's policy makers.

Higher Education Development and Regional Differences in China

This paper analyzed the development of higher education and the regional differences in China, using the survey data and official statistics. Two indicators, the undergraduate students of per 100,000 population and higher education’s contribution to GDP growth, were applied respectively to study the regional differences. The results showed that higher education in China was enjoying great development, fundamentally constructed talent cultivation system and comprehensively reasonable resource distribution. However, some colleges and universities still had some problems, such as incorrect orientation, overheated scale expansion and insufficient capital investment. Besides, higher education in China was suffering from considerable regional differences, namely higher education in East China is developing rapidly and contributing more to the economic growth, while the West China has presented slower rate of higher education development and smaller contribution to economic growth. Based on the problems lying in present reality of higher education development, this paper proposed the suggestions to enhance the development of higher education in China and to dispel the regional differences in higher education performance.

The impact of corporate social responsibility on customer loyalty: A case for two global corporations in China

AbstractCorporate social responsibility (CSR) initiatives have differential impact on developing customer loyalty in the context of two leading international sportswear companies operating in China. Academic interest in CSR in China has grown over the years. The findings suggest a relatively strong impact of CSR dimensions (e.g., workplace, marketplace, and environment support) and other related attributes (e.g., price, product quality, and uniqueness) on developing customer loyalty in China. There are regional differences in China in relation to customers’ CSR perceptions and the likelihood of being influenced by a company’s CSR initiatives.

Regional disparities in China's marine economy

Understanding the performance of each coastal area as it develops is the primary task of policy-makers in a marine economy; however, quantitative regional differences in China's marine economy have not been empirically examined. This paper offers a methodological contribution by applying a series of techniques, including the variation coefficient, Gini coefficient, and Theil index decomposition, to illustrate the relative differences among coastal areas. Additionally, the coastal areas of China were divided into two categories to reveal the provincial differences and regional disparities in China's marine economy. The results show that although the numerical economic differences in Gross Ocean Product (GOP) among coastal areas have increased significantly during the 21st century, the gaps among coastal regions have gradually decreased. In addition, China's marine economy presents three levels of regional development (developed, medium-developed, and developing). The results of the Theil index decomposition show that the overall difference in China's marine economy is derived mainly from differences within the three macro marine economic regions; these differences account for more than 95% of the overall difference. Furthermore, the underlying reasons for and driving mechanism of regional differences in China's marine economy can be illuminated in terms of differences in natural resource endowments and geographic locations; industrial agglomeration and diffusion; changes in regional development policy; and foreign investment. These findings offer basic data support and policy recommendations for marine economy management at the national and regional levels.

Does the high–tech industry consistently reduce CO2 emissions? Results from nonparametric additive regression model

China is currently the world's largest carbon dioxide (CO2) emitter. Moreover, total energy consumption and CO2 emissions in China will continue to increase due to the rapid growth of industrialization and urbanization. Therefore, vigorously developing the high–tech industry becomes an inevitable choice to reduce CO2 emissions at the moment or in the future. However, ignoring the existing nonlinear links between economic variables, most scholars use traditional linear models to explore the impact of the high–tech industry on CO2 emissions from an aggregate perspective. Few studies have focused on nonlinear relationships and regional differences in China. Based on panel data of 1998–2014, this study uses the nonparametric additive regression model to explore the nonlinear effect of the high–tech industry from a regional perspective. The estimated results show that the residual sum of squares (SSR) of the nonparametric additive regression model in the eastern, central and western regions are 0.693, 0.054 and 0.085 respectively, which are much less those that of the traditional linear regression model (3.158, 4.227 and 7.196). This verifies that the nonparametric additive regression model has a better fitting effect. Specifically, the high–tech industry produces an inverted “U–shaped” nonlinear impact on CO2 emissions in the eastern region, but a positive “U–shaped” nonlinear effect in the central and western regions. Therefore, the nonlinear impact of the high–tech industry on CO2 emissions in the three regions should be given adequate attention in developing effective abatement policies.

Impact of urbanization on energy related CO2 emission at different development levels: Regional difference in China based on panel estimation

We examined the influence of urbanization on CO2 emission at different development levels employing the stochastic impacts by regression on population, affluence and technology (STIRPAT) model on provincial panel data from 1995 to 2013 for China. To investigate regional differences based on development levels in the effects of urbanization on CO2 emission, we divided the 29 provinces of China into three regions according to their per capita real GDP at constant value (1990 = 100). The panel estimation for the whole dataset and the three regions showed an inverted U relationship between urbanization and CO2 emission in the major regions of China. Specifically, the effects of urbanization vary significantly across the regions. In region 2 and region 3, a threshold level was identified, beyond which the emission urbanization elasticity was negative, and further increases in the urbanization rate did not contribute to higher emissions. However, in region 1, only population and affluence, rather than urbanization, were significant factors affecting CO2 emissions. In addition, the results did not confirm the environmental Kuznets Curve relationship between income and CO2 emission, where CO2 emission increases monotonically with income. We propose a series of policy implications based on these outcomes to help realize emission reduction targets better.

Regional differences in China's fossil energy consumption: an analysis for the period 1997–2013

Measuring regional differences in fossil energy consumption is the first step to the study of natural resource allocation and utilization. This paper employs annual and cumulative consumption Gini indexes as well as the deviation index to discuss regional differences in the per capita consumption of fossil energy and related products across 30 Chinese provinces from 1997 to 2013. The results show that Chinese inter-provincial Gini ratio of fossil energy consumption is below 0.3 in recent years, and change in per capita energy consumption is the key factor behind the decline in the overall Gini index. Unlike existing studies based only on annual flows of energy consumption, this paper also focuses on cumulative energy consumption. Moreover, decomposing annual and cumulative consumption Gini coefficients by type, group, and incremental variation is rarely seen in other studies. Based on the above positive analysis, the paper provides some policymaking suggestions.

Contextual Effect of Wealth on Independence: An Examination through Regional Differences in China.

The current study disentangled two different effects of wealth on psychological tendency toward independence: one is an effect exerted at the individual level (i.e., being rich) and the other one is a contextual effect (i.e., being surrounded by rich individuals). Past research has found a stronger tendency toward independence among people in economically developed societies. This association has often been explained as a result of a greater amount of choices, and thus more opportunities to express individuality that wealth affords individuals. In addition to this individual-level process, theories in cultural psychology imply that the wealth-independence link also reflects social processes—living in a rich society, regardless of one’s own wealth, promotes independence (contextual effect of wealth on independence). Through a large-scale survey in China, using multilevel analyses, we found that wealth had both the individual-level effect and contextual effect on independence as well as related psychological tendencies (influence orientation and generalized trust), suggesting that individuals are more likely to be independent with greater personal wealth and when surrounded by wealthy others. Possible processes through which independence is promoted by liing in a wealthy area are discussed.

Public health in China: An environmental and socio-economic perspective

Abstract Despite the large literature on public health, few studies have examined the associations between public health outcomes and environmental and socio-economic factors. This study bridges this gap by demonstrating the relationships between public health and 10 selected environmental and socio-economic factors from the spatial perspective. In particular, three public health outcomes in China are investigated, namely the number of centenarians per 100,000 people (termed the centenarian ratio), the proportion of nonagenarians of the 65 years and older population (termed the longevity index), and life expectancy at birth. We base our analysis on stepwise regression and geographically weighted regression models, with study areas of 31 provinces in China. Our results show that SO2 (sulfur dioxide) concentration decreases the centenarian ratio; PM10 (particles with diameters of 10 μm or less) concentration and coal consumption (CC) per capita decrease the longevity index, and GDP (Gross Domestic Product) per capita prolongs life expectancy at birth, while energy consumption (EC) per capita decreases life expectancy at birth. Further, our findings demonstrate that public health outcomes show clear regional differences in China.

Housing prices, rural–urban migrants' settlement decisions and their regional differences in China

Rural–urban migrants are the major group who will boost the transformation of China's urbanization and reform of the household registration system. Their aspirations of living in the immigration area are an important premise of institutional change. The housing prices within the immigration areas are an important factor that can influence the rural–urban migrants' settlement decision. To what degree does the housing price influence the settlement decision? Do regional differences exist in the influence of house price? These issues need to be analyzed and verified in a theoretical and empirical ways. By introducing the variables of the housing price into the life-cycle theory function, we found that housing price influences the settlement decision through the welfare dissipation effect and the expected wealth effect. On the basis of welfare dissipation effect, hypothesis 1, we can come to the conclusion that high housing price will play a negative role in the process of settlement decision formation. Through expected wealth effect, hypothesis 2, we estimate that a housing price rise will promote the aspiration of living in the immigration area to some extent inversely. On this hypothesis basis, using the panel data model of China's 31 provinces and cities for the period 1995–2012, we found that, at the national level, the influence of housing price to the settlement decision is not significant. From the view of regional differences, the influence is negative in the eastern area, indicating that the welfare dissipation effect is greater than the expected wealth effect, in line with the hypothesis 1. The increase of housing prices will promote the settlement decision in the central area, this phenomena explains that the expected wealth effect is greater than the welfare dissipation effect, in line with the hypothesis 2. In the western area, the influence is non-significant.

Impacts of economic growth and urbanization on CO2 emissions: regional differences in China based on panel estimation

This study analyzed the impact of urbanization and the level of economic development on CO2 emissions using the STIRPAT model and provincial panel data for China. This study classified the 29 provinces of China into three groups (eastern, central, and western regions) and examined regional differences in the environmental impacts of urbanization and economic development levels. The results demonstrated that there was an inverted U-shaped relationship between urbanization and CO2 emissions in the central and western regions of China. However, we did not confirm the environmental Kuznets curve relationship between urbanization and CO2 emissions in eastern China, where CO2 emissions increase monotonically with urbanization. This study showed that the impacts of urbanization differ considerably. There was a U-shaped relationship between economic growth and CO2 emissions. However, the point of inflexion was very low, which indicates that economic growth will promote CO2 emissions in China. The share of the industry output value had a marginal incremental effect on CO2 emissions. There was a decreasing effect of population scale on CO2 emissions. Energy efficiency is the main factor that restrains CO2 emissions, and the effect was higher in regions with low energy efficiency.

Regional differences in China's CO2 abatement cost

Under a framework of output distance function with multiple outputs, the study discusses the carbon abatement cost at provincial and regional levels in China, using the shadow price analysis. The findings show that the abatement cost, reflecting the marginal opportunity cost of carbon reduction, varies greatly among the provinces. On average, the abatement cost of the eastern region was much higher than that of the mid-western region during the observed period. The findings provide evidence that the carbon prices in the current ETS pilots have been much lower than desired levels, implying inefficiency of the markets. The wide range of the abatement cost estimates supports that the equi-marginal principle does not hold for the regulations on carbon pollution at regional levels. The regional cost differences indicate the huge potential for China to minimize the total abatement cost with policy instruments that may motive the emissions moving from areas of low abatement cost to where the abatement cost is higher. For a few undeveloped provinces that are environmentally fragile and have high abatement cost, supplementary measures will be needed to reduce the negative impact of carbon cutbacks on the poor to the minimum.

Affecting Factors of the Competitive Sports’ Regional Differences in China

National game is the highest level of comprehensive sports games in China which is competed by each province (city and autonomous region) as unitary units. As the imbalance of economy and population among different provinces (cities and autonomous regions), there are imbalance of competitive sports developments. Breaking through the traditional mode of regarding provinces (cities or autonomous regions) as the units for comparison and analysis, this research adopts the approach of comparing six regions in administrative districts and defining seven indicators as factors influencing Chinese regional competitive sports developments. Through the way of linear regression, this essay gradually chooses the factors which exert effects on Chinese competitive sports’ regional differences. It is found that competitive strength, economical strength, in-team player, reserve player and on-the-job coach are the principal factors affecting Chinese competitive sports’ regional differences. Meanwhile, the essay tends to provide references for balance development between regions on China by establishing regression equation MS = 1.601 + 1.159 × XS3 + 0.300 × XS1 + 0.2497 × XS4 + 0.189 × XS5 + 0.181 × XS6 of Chinese competitive sports’ regional differences.