Investment In Fixed Assets Research Articles

Analyzing the phased changes of socioeconomic drivers to carbon dioxide and particulate matter emissions in the Yangtze River Delta

Enhancing the environmental collaborative governance to reduce carbon dioxide (CO2) and particulate matter (PM2.5) emissions is an important and significant low-carbon green growth strategy in China. However, few studies have explored the periodical positive and negative impact changes of the drivers in interannual phases on both CO2 and PM2.5 emissions hitherto. With the panel data in the Yangtze River Delta urban agglomeration (YRDUA) from 2005 to 2017, here we analyzed the annual evolution characters of CO2 and PM2.5 emissions and the 10 socioeconomic drivers to these emissions. The spatial Durbin error model (SDEM) by the overall panel was developed to examine the socioeconomic drivers that can synergistically affect CO2 and PM2.5 emissions. Moreover, SDEM by the phased panel was employed to observe the periodical positive and negative impact changes of the drivers. The results reveal that, the drivers that can significantly realize the collaborative governance are normalized difference vegetation index (NDVI), energy intensity (EI), and fixed asset investment (FAI). Main results include: Every 1% increase in the NDVI can reduce CO2 emissions by 0.276% and PM2.5 concentration by 0.223%; every 1% increase in EI can increase CO2 emissions by 0.024% and PM2.5 concentration by 0.003%; and every 1% increase in FAI can increase CO2 emissions by 0.049% and PM2.5 concentration by 0.018%. Increased greening levels, reduced energy intensity, and reduced investment in fixed assets can significantly alleviate CO2 and PM2.5 emissions in the YRD. Furthermore, the phased panel estimation shows that after 2013, the positive impact of economic growth on CO2 and PM2.5 emissions weakens gradually. Similarly, the positive impact of technological upgrading on CO2 emissions begins to diminish, the rise in urbanization still increases CO2 emissions, and the PM2.5 pollution weakens after 2013. Increased traffic loads lead to an increase in PM2.5 emissions, and its effect is gradually enhanced in the later stage. In addition, the positive effect of FAI on CO2 emissions increases gradually and aggravates PM2.5 pollution as well. Therefore, this study suggests that the environmental collaborative governance should focus on reforming the clean energy structure; accelerating the green transformation of industrial structure; and promoting the low-carbon industrial system, energy system, and lifestyle.

The Spatiotemporal Evolution of Ecological Security in Border Areas: A Case Study of Southwest China

Fewer studies on ecological security (ES) in border areas limit the synergistic development of border areas in the context of rapid globalization. The study of ES in border areas of southwest China can enrich the evaluation methods, summarize the knowledge related to ES in border areas, and provide references for similar areas in the world. Therefore, twenty-five international border counties in Yunnan Province were selected to establish a system to evaluate ES; an entropy weight TOPSIS model was used to evaluate the changes in ES from 2004 to 2019. Then, an obstacle degree model was used to diagnose the factors affecting ES. The state of ES was predicted by a gray prediction model (GM) (1,1) in 2025 and 2030. The results show that an improving ES situation presented a spatial distribution pattern of high to low from the southwest to the west and east. Various factors, including fixed assets investment, per-capita fiscal revenue, per-capita GDP, food production, and water regulation, created obstacles to a desirable ES in the study area. Although the ES of border areas will maintain an upward trend under the existing development model, the number of counties that will reach a secure state of ES in 2025 and 2030 is predicted to only be 1 and 2, respectively.

Efficiency of China's urban development under carbon emission constraints: A city-level analysis

This study explores the efficiency of China's urban development under carbon emission constraint from 1996 to 2017. Firstly, it uses the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) and Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nightlight imaging to evaluate the carbon dioxide emission levels of 249 cities in China. Then, it utilises the epsilon-based measure (EBM) superefficiency model and Global Malmquist–Luenberger (GML) index to evaluate the urbanization efficiency and changes in the total factor productivity (TFP) of urban development of the 249 cities under carbon emission constraints. Results show that from 1996 to 2017, the total carbon emissions of the 249 cities grew during a rapid development stage, while the efficiency of urban development under carbon emission constraints showed fluctuation and did not increase significantly. The redundant improvement values of government fiscal expenditure, urban employees, urban fixed asset investment, foreign direct investment, and carbon emission increased in fluctuations. From the regional spatial perspective, the urbanization efficiency of western China was the highest, followed by the northeast region, the central region, and finally the eastern region. In addition, the driving factors of TFP of urbanization in China have improved as a whole. The application of nightlight imaging data and EBM superefficiency model improves the accuracy of urban development efficiency measurement. The findings of this study can provide a scientific basis for different regions and cities of different sizes to formulate carbon emission reduction strategies, and have important policy value for improving urban development efficiency in China. In addition, the research of index system should be deepened to further improve the measurement accuracy.

Spatial Characteristics and Driving Factors of Public–Private Partnership Projects Implemented in China

In recent years, public–private partnership (PPP), as an alternative strategy in the delivery of infrastructure services, has developed rapidly in China. However, the implementation of PPP projects differs significantly between provinces and municipalities. Using the implementation data of national PPP demonstration projects, this study employs spatial autoregression and a spatial Durbin model (SDM) to explore the spatial characteristics and driving factors of PPP projects across China. The results indicate that the PPP project implementation rate in China shows significant spatial clustering, which indicates a spatial spillover effect in the eastern, central, and western regions of the country. The fixed asset investment and infrastructure status exert a significant positive effect on the PPP project implementation rate in a certain region and aid in the implementation of PPP projects in the neighboring regions. Urbanization potentiality, the financial self-sufficiency rate, and regional openness do not have an impact on the local PPP project implementation rate, but they do inhibit the increase in this rate in the adjacent regions. Fiscal capacity, government credibility, and the level of social development do not affect the local PPP project implementation rate, but they do promote the implementation of the PPP projects of these neighboring regions. Local authorities should make additional efforts to build an inter-regional development environment for PPP and promote the implementation of PPP projects.

Fundamental Factors of Financial Ratios and Discretionary Accruals in Influencing the Companies’ Fixed-Asset Investment Decisions

Research aims: This study aims to empirically prove the influence of profitability, solvency, liquidity, activity, dividend policy, and discretionary accruals on fixed-asset investment decisions.Design/Methodology/Approach: The researchers used consumer goods companies listed on the Indonesia Stock Exchange (IDX) from 2013 to 2019. Using the purposive sampling method, this study resulted in 163 bank-year observations. The data were then analyzed utilizing a fixed-effect model.Research findings: The results showed that profitability, liquidity, activity, and discretionary accruals positively affected fixed-asset investment. Meanwhile, the dividend policy negatively affected fixed-asset investment. This study strengthens the pecking order theory. In addition, the research sample used internal funds as a funding source for investment in fixed assets.Theoretical contribution/Originality: The variable added in the study distinguishing it from previous researchers is the discretionary accrual variable. Discretionary accruals have been proven to impact resource allocation, one of which is investment decisions. The additional discretionary accruals variable is expected to strengthen the influence of the consumer goods companies' fundamental factors on investment decisions in fixed assets.Practitioner/Policy implication: Investment in fixed assets in the consumer goods companies uses internal funds because these funds are low risk and support the company's sustainability.Research limitation/Implication: This study used dividend policy as one of the independent variables, and companies that did not distribute dividends could not be sampled.

Spatio-Temporal Evolution and Influencing Factors of High Quality Development in the Yunnan–Guizhou, Region Based on the Perspective of a Beautiful China and SDGs

The high-quality development in the Yunnan–Guizhou region (YGR) is a significant support for the high-quality development of China. It will help shape a new pattern of regional coordinated development. Referring to a Beautiful China and the United Nations Sustainable Development Goals (SDGs) evaluation indexes, we built an evaluation index system that puts the high-quality development at its heart. This system includes the resource load, economic development, ecological environment protection, and social progress. Taking 25 prefecture-level cities of the YGR as study subjects, the authors used the entropy weight–TOPSIS model to evaluate high-quality development and evolution. Then, the authors used the Geographical Detector (GD) method and a Geographic-Weighted Regression (GWR) model to analyze factors and mechanisms of the evolution of high-quality development. The results suggest that the changes of urban built-up area, per capita GDP, total foreign trade value, tourism revenue, and total investment of fixed assets investment are the primary factors of spatial differentiation of this evolution. The influence and direction of each factor are different in different periods, with apparent spatio-temporal heterogeneity. From 2005 to 2018, the synergistic effect of changes in total foreign trade value and tourism revenue is the leading force in shaping the evolution pattern. The high-quality development of the YGR generally presents the spatial pattern of “central Yunnan–central Guizhou core dual drive”, “high in east and low in west”, and the evolution speed presents a development characteristic of “low speed–relatively high speed–high speed”. The research can provide a reference for high-quality and precise development and decision-making in the YGR.

Assessing spatial–temporal evolution and key factors of urban livability in arid zone: The case study of the Loess Plateau, China

Urban livability (UL) plays an important direction of sustainable cities and society. According to the core connotation of urban sustainable development goals (SDGs), this study deconstructed the relationship between UL and SDGs, and extracted corresponding indicators to construct a universal and scientific evaluation index system for evaluating urban livability in arid zone. The UL system was divided into seven dimensions: economic growth, urban construction and population, urban public service capacity, resource consumption and utilization, living standard of residents, current situation of urban environment, environmental pollution. TOPSIS model and SYS-GMM model were adopted to explore the spatial–temporal evolution and key factors of urban livability in arid areas, 24 cities on the Loess Plateau from 2013 to 2018 were chosen for this study. The evaluation results indicate that the overall livable level of 24 cities is not ideal, the temporal characteristic shows a rising trend of fluctuation, and the spatial characteristic shows central depression. Additionally, the empirical results show that there are six key factors for urban livability in the Loess Plateau, the fixed asset investment and population density have a negative impact on UL, while environmental regulation, industrial structure optimization, income level and Institutional quality play a positive impact on UL. The UL index system can measure the UL situation comprehensively and scientifically, which can provide a universal applicability index system for ecologically sensitive & arid areas to research UL, construct ecological livable cities, and achieve SDGs.

Underlying the influencing factors behind the heterogeneous change of urban landscape patterns since 1990: A multiple dimension analysis

Urbanization brings dramatic changes in land cover and significantly alters urban morphology, which in turn affects the urban ecological processes and environment. To promote urban sustainability, it is necessary to accurately quantify dynamic changes in urban form and reveal the associated influencing factors. This study selected seven periods of urban boundary data and socioeconomic data for 31 provincial capitals in China from 1990 to 2018. The evolution characteristics and influencing factors of urban landscape patterns in different dimensions were analyzed based on stepwise regression method. Results indicated that the patch area and aggregation of urban land showed a significant increasing trend from 1990 to 2018, whereas the landscape fragmentation exhibited a significant decreasing trend. The shape complexity of each city showed an increasing trend from 1990 to 2005, and that of eastern cities and megacities tended to decrease thereafter. This suggest that when urban development reaches a certain level, landscape shape will gradually become regular. There was obvious spatial heterogeneity in the influencing factors of urban landscape pattern evolution. Social and economic development promoted urban expansion whereas reduced urban fragmentation, resulted a negative effect on patch density. For the economically developed cities in the east, after 2005, the urban form has tended to be regularized, and the further increase of the output value of tertiary industry will reduce the landscape shape index (LSI). Urbanization rate played major role in contagion for megacities and other cities were mainly influenced by fixed-asset investment. Therefore, heterogeneous measures should be considered for future urban landscape pattern optimization at various economic zone or hierarchical city scales.

Assessment and dynamic mechanisms of the land-use dominant morphology transition: a case study of Hainan Province, China.

This paper was aimed at providing a perspective on the assessment of land-use dominant transition. Based on the transfer matrix of land-use type, the dynamic degree of dominant morphology transition was measured, and an active degree index was proposed. The spatiotemporal differentiation characteristics were assessed and analyzed by land use change characteristics in different phases. Our assessment resulted in three types of spatiotemporal differentiation of Hainan Province in China. The whole island can be divided into three regions with two parallel lines at 45° based on spatiotemporal differentiation characteristics. The "slow-type" was distributed in four eastern counties (cities), "steady-type" was distributed in 13 central and western counties (cities), and the "active-type" was distributed in four central counties (cities). Over three phases, namely 2010-2011, 2012-2015, and 2015-2018, four levels of spatiotemporal differentiation of the 21 counties (cities) were assessed, and they were relatively stable, leaping, declining, and unstable. Areas of new construction and fixed assets investments consumed by increased construction land were the positive factors of land-use dominant transition, while output values of secondary industries and area of industrial-mining per capita were the negative factors. Based on these results, a more informative examination of LULC was proposed, and all resulting land management policies will be more targeted and effective.

Spatio-Temporal Variation of Economic Drivers of Urban Heat Island Effect in Yangtze River Delta

It is not deep enough that the theoretical and empirical analysis of economic drivers on the urban heat island (UHI) effect have been researched. Consequently, the study of economic drivers of the UHI effect is not only conducive to the governance of the UHI problem but also conducive to deepening the study of related issues in the economic field. The Yangtze River Delta (YRD) region of China has developed economic status and the special geography of estuaries and coasts. Therefore, 26 central cities in the YRD region are selected as research samples, and the period from 2003 to 2017 is taken as the observation period. The Spatio-temporal variability of UHI intensity caused by industrialization and urbanization is analyzed by using MODIS land surface temperature (LST) data and related yearbook data. The conclusions are as follows:(1) The UHI intensity of cities in the YRD region is significant and fluctuates to a certain extent. (2) Empirical analysis shows that the agglomeration of single economic factors in the process of industrialization and urbanization does correlate with the UHI intensity in the YRD region, but the correlation may show a downward trend due to the influence of exogenous factors suc0h as physical geography. (3) In terms of economic drivers, the combination of multiple factors can produce a greater UHI intensity. The model of their impacts on UHI intensity is increasingly-changed, which is from a model of Fixed Asset Investment and the Motor Vehicle Population as dominant factors to a model of multiple overlapping economic factors, and the latter has a greater impact.

Eco-Efficiency Assessment of Beijing-Tianjin-Hebei Urban Agglomeration Based on Emergy Analysis and Two-Layer System Dynamics

In the process of the economic development of the Beijing-Tianjin-Hebei urban agglomeration, ecological and environmental issues are still an important factor restricting high-quality development. The study of eco-efficiency is of great significance for coordinating the relationship between economy, resources and environment. This paper used a combinated method of two-layer system dynamics and emergy analysis to construct an emergy–system dynamics coupling model for eco-efficiency evaluation from the subsystems of resource flow, energy flow, currency flow and population flow of urban system, which is used to simulate and analyze the eco-efficiency of the Beijing-Tianjin-Hebei urban agglomeration. The results show that the overall eco-efficiency of the Beijing-Tianjin-Hebei urban agglomeration is not high, with an average value of 0.3786, and there is a trend of the value rising first and then falling from 2000 to 2035. The index values of emergy waste rate, contaminant emergy ratio, emergy output rate and environmental load rate after the decomposition of the eco-efficiency show that the high environmental pressure, the low re-use rate of pollutants and the low production efficiency of the system are important reasons for the low eco-efficiency in regional economic development. Finally, through scenario simulation, we propose that optimizing the economic structure, adjusting the population size and rationally arranging the fixed assets investment are conducive to improving the eco-efficiency of the Beijing-Tianjin-Hebei urban agglomeration.

Spatiotemporal Evolution and Influencing Factors of the Rural Natural Capital Utilization Efficiency: A Case Study of Chongqing, China

The efficient utilization and optimal allocation of natural capital play an important role in economic development and human well-being. The production process of natural capital is the input and output processing of its ecological resources and the environment. Improving the rural natural capital utilization efficiency (RNCUE) is an important goal of natural capital investment, and the efficient utilization of natural capital is an important factor for the efficient operation of the regional economy and society. This study uses the super slack-based measure (SBM) model based on undesirable outputs to measure the RNCUE, combines the exploratory data analysis method (ESDA) and spatial Markov transfer matrix to analyse the spatiotemporal evolution characteristics of efficiency, and analyses the influencing factors of the change of the RNCUE in Chongqing through a spatial econometric model. The results show that: (1) The RNCUE in Chongqing is still at a low level as a whole and there is a large space for efficiency improvement and efficient operation. There is a certain spatial dependence on the interaction of efficiency between adjacent districts and counties. (2) High-high agglomeration is concentrated in the western area of Chongqing One-hour Economic Circle, and low-low agglomeration is concentrated in Southeast and Northeast Chongqing. The probability of a large change in the RNCUE in consecutive years is small, and it is easy to form the phenomenon of “club convergence” in space. (3) The RNCUE in Chongqing has been affected by rainfall, temperature, NDVI, the per capita GDP, proportion of fixed asset investment, expenditure for agriculture, and proportion of primary industry and rural population. The influencing factors show that the spatial heterogeneity is significant. The RNCUE has a negative correlation with forest coverage and the expenditure for agriculture, is not significantly positive or negative with the proportion of the primary industry and is positively correlated with the rural population density. This study points out that we can improve the RNCUE in Chongqing by optimizing the spatial differentiation control mechanism, clarifying property rights, enhancing liquidity, and strengthening scientific and technological innovation.

Empirical Analysis on the Development of Ecological Agriculture under the Initiative of "Sustainable Development"

As a large agricultural country, China is promoting the development of agriculture in the direction of modernization and ecology. There are still some problems in the process of vigorous and coordinated development of regional resources. In order to narrow the temporal and spatial differences in the development of ecological agriculture and solve relevant development problems, this study puts forward targeted measures and policies from 18 cities in Henan Province, an important grain producing area in China. The comprehensive evaluation index system including economy, society, environmental and ecology calculated by U-EBM model is constructed for the first time, and the grey weighted clustering model based on improved entropy weight method is used to analyze and evaluate the overall development of ecological agriculture in each city for the first time. This method provides a new evaluation angle, and uses the idea of "less data and grey information" in grey theory to test the development trend and influence mechanism of regional ecological agriculture. It is found that fixed asset investment accounts for a large proportion in water-saving irrigation rate, total power of agricultural machinery and ecological agriculture efficiency, which is the key factor affecting the sustainable development of ecological agriculture. The results of data-driven clustering show that there are significant differences in the development of eco agriculture in various regions of Henan Province, which can be roughly divided into three gray levels. The model conforms to the actual situation of unbalanced development of ecological agriculture in various regions of Henan Province, verifies the reliability of the model, and provides accurate evaluation direction and relevant policies and strategic deployment for the research of agricultural ecological development in the future.

Study on Socio-Economic Factors of Haze Pollution in the Context of Sustainable Development: Based on Asymmetric Interaction Effects Perspective

Haze pollution has been a global problem plaguing people for nearly two centuries, especially in developing countries, where haze pollution is getting worse and has become the culprit that restricts global sustainable development. As the largest developing country in the world, China’s regional characteristics of haze pollution are increasingly prominent, and the coverage is expanding, which means that there is a strong spatial interaction of haze pollution. The real world is composed of asymmetric spatial relationships, and asymmetric spatial interactions are more consistent with the reality of haze pollution. To this end, this paper identifies the asymmetric spatial interaction effects of haze pollution by using the time series econometric analysis framework and then constructs asymmetric spatial weights. In this paper, the spatial panel Durbin model and spatial effect decomposition technique are used for the empirical investigation to provide new empirical evidence to reveal the socio-economic influences of haze pollution. The study finds that haze pollution in China has a significant asymmetric spatial interaction and the degree of influence varies among cities. During the sample period, there is a significant inverted U-shaped relationship between economic development and haze pollution. However, the vast majority of cities have not passed the top inflection point of the inverted U-curve and are still in the stage where haze pollution is gradually intensifying with economic growth. High population density, high energy consumption, and unreasonable energy consumption structure aggravate haze pollution, while fixed-asset investment and science and technology expenditure help to reduce haze pollution. However, only the spatial spillover effect of the energy consumption structure is significant. Therefore, the improvement and implementation of more effective socio-economic prevention and control policies in the case of asymmetric interaction is the key to effectively dealing with heavy pollution weather, fighting the defense of the blue sky, and achieving sustainable development.

Empirical Analysis on Influencing Factors of Financial Revenue in Sichuan Province

Fiscal revenue is an important means of macroeconomic regulation and control of the country. It is the financial guarantee to perform and realize government functions. It can effectively allocate resources and income distribution, and then help the stable and healthy development of national economy. According to the relevant data of Sichuan Province from 2000 to 2020, four explanatory variables, namely fiscal expenditure, regional GDP, tax revenue and fixed asset investment, are selected to construct a multiple regression model. Using Eviews10.0, the multiple regression model is estimated, tested and corrected. The empirical results show that the change of fiscal revenue in Sichuan Province is mainly affected by tax revenue and fixed asset investment. Finally, combined with the analysis results, suggestions are put forward for the fiscal revenue growth and economic development of Sichuan Province.

An Assessment of China's Digital Trade Development and Influencing Factors.

The pattern and scale of commerce worldwide have been greatly transformed by the Fourth Industrial Revolution and technological advancement; digital trade has become the primary form of trade in the digital economy. On the basis of information network infrastructure, information technology level, digital industrialization level, and industrial digitalization level, this study establishes a comprehensive assessment system that applies an entropy–TOPSIS model to evaluate digital trade development level in China. The results indicate that digital trade in China was steadily growing between 2010 and 2019. A principal component analysis is conducted to identify factors affecting the digital trade development level in China. The analysis results suggest that Internet development, population income, industrial structure, payment convenience level, fixed asset investment, online transaction scale, and economic development all have positive effects on the digital trade development level in China, with payment convenience level having the greatest influence. By contrast, state intervention and degree of dependence on foreign trade have a negative effect on digital trade development.

The driving effect of informal economies on urbanization in China

This paper examines the rise of informal economies in China, a hidden driving force overlooked in studies on China’s urbanization. Estimating the size of informal economies using the multiple indicators multiple causes model, the paper employs mathematical models to examine the driving effect of informal economies on urbanization and to reveal the paths by which such effect works. The results were as follows. (1) In 2018, the size of the informal economy in China accounted for 23.5% of GDP with an output value of 21.16 trillion yuan. (2) The informal economy had a driving effect on China’s urbanization, and every 1-percentage-point increase in its share of the GDP led to an increase of 0.291 percentage points in the urbanization rate. (3) The informal economy’s effect on urbanization showed regional differences, decreasing in size from the eastern to the central to the western regions. (4) The informal economy drives urbanization through four paths — by promoting foreign direct investment (FDI), fixed asset investment (FAI), social consumption (SC), and secondary sector employment (SSE). Their effect sizes are ranked in descending order as follows: FDI > FAI > SC > SSE. This paper contributes to theories on urbanization dynamics and process in China by highlighting the role of the informal economy as a hidden economic power lurking in the city.

The Contribution Rate of Advanced Scientific and Technological Progress and the Internal Circulation of China's Economy

This study observes the impact of China's advanced scientific and technological progress contribution rate on China's internal circular economy from 1958 to 2020, and formulates China's appropriate economic policies. Firstly, the method of taking logarithm by difference is used to make the variables studied stable, the VAR model is established, and the stability of the model is tested. Then, this study uses the Granger causality test to evaluate the relationship between the contribution rate of advanced science and technology, consumption, social fixed investment, and macroeconomic climate index. The impulse response function shows that in the long run, the contribution rate of advanced scientific and technological progress will not only promote the improvement of consumption but also improve the macroeconomic climate index and social fixed asset investment. Variance decomposition shows that with time, the interaction between consumption and the contribution rate of advanced scientific and technological progress gradually deepens, and the influence of other variables is relatively stable. Therefore, China needs to increase its investment in scientific research and improve the contribution rate of advanced scientific and technological progress, which will help promote China's implementation of the internal circular economy strategy.

Research on Modeling and Simulation System of Economic Factors Based on Swarm Platform

Based on the VAR model, this paper uses the stepwise regression analysis method to analyze the main influencing factors of the economy, and empirically analyzes the impact of Nanning's fixed asset investment on urban and rural economic development in the past ten years. Use eviews statistical analysis software to perform regression analysis on the data to obtain a regression model, and build a VAR model according to investment and income, and finally find out the correlation of variables. On the basis of the existing theory (genetic algorithm, cellular automata and classification system), according to the agent-based modeling and simulation method Swarm, according to the steps of agent-based distributed simulation of complex system, modeling and simulation are carried out. The abstraction level of simulation is established on the big data computing level, and the final simulation results are briefly explained and explained.

Exergy analysis of embodied natural resources use in China and its driving factors: From a production perspective

China has established a complete industrial system to meet with both domestic and international demands, leading to massive natural resource consumption. It is therefore urgent to clarify the features of natural resource utilization in China. However, there is still a lack of a unified natural resources accounting framework on such issues. This study tries to measure embodied natural resource utilization in China for the period of 2002–2017 by combining exergetic analysis and input-output analysis, considering both primary resource inputs and environmental inputs. Logarithmic Mean Divisia Index (LMDI) was applied to identify corresponding driving factors. Results show that exergy equivalent of additional natural resource to treat environmental pollutants (3.07E+20–5.31E+20 Jex) was almost the same magnitude as natural resources use itself (2.98E+20–1.18E+21 Jex). Internal embodied natural resource of production sectors mainly came from intermediate inputs (66.60%–75.34%). Economic scale, labor efficiency and fixed asset investment intensity were the key positive driving factors, while final use level, fixed asset investment efficiency and natural resources intensity were the key negative driving factors. The production system in China had changed from a net exporter of embodied natural resources in 2002 (1.56E+19 Jex) to a net importer in 2017 (−3.38E+18 Jex). Natural resource intensity was the major positive factor for net exports, while trade structure was the major negative factor except 2007. In summary, this study provides valuable insights for making sector-specific policies to alleviate resource crisis, including appropriate policies, technological improvements, economic instruments, and capacity building.