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International agricultural markets are an important part of the global food resource chain. Tapping into the potential of agricultural trade between China and countries along the "Belt and Road" (B&R) is conducive to safeguarding China's and the world's food security, but there is less literature on the potential of bilateral trade demand. This paper ranks the B&R countries according to the scale of imports and exports, and calculates the elasticity of demand for imports, the elasticity of substitution for exports, and, finally, the potential of elasticity of demand for trade between China and the major B&R countries. The results show that China's agricultural export potential to major B&R countries is ranked as follows: Indonesia, Thailand, Russia, Poland, Turkey, Vietnam, Malaysia, Ukraine, India, and Singapore. The major B&R countries are also ranked in terms of their export potential to China: Vietnam, India, Ukraine, Russia, Malaysia, Thailand, Indonesia, Poland, Singapore, and Turkey. The findings of this paper provide a decision-making basis for promoting agricultural trade between China and B&R countries. [ABSTRACT FROM AUTHOR]

This paper examines the role of exchange rate changes on India's trade. The drivers of exports and imports (income, exchange rate including sectoral differences, and exchange rate variability) are estimated for the short and long run including a structural break. Using annual data from 1994 to 2022, the results of dynamic fixed effects estimation show that both exports and imports are income-elastic in the short and long run, but income elasticity is far stronger for exports. Moreover, exports are responsive to the real effective exchange rate in the short run but not in the long run, and the reverse is true for imports. Furthermore, exchange rates have asymmetric effects for high-volume and primary sectors for exports and imports. The combined impacts show the ineffectiveness of using currency depreciation to address trade imbalances. [ABSTRACT FROM AUTHOR]

Since the socio-economic reform in 1978, rural China has undergone drastic spatial restructuring, and the trend of multifunctional development and dynamic evolution of settlements in the countryside have become increasingly obvious. Functions and settlements are the important parts of rural areas. Rural multifunction is a new perspective to explore the diversified development paths of the countryside, and rural settlements provide basic support for rural multifunction. Clarifying the complex coupling coordination relationship between rural functional diversification (RFD) and rural settlement evolution (RSE), and identifying the spatial heterogeneity of their interactions is the key to promoting the rural revitalization strategy. This study analyzes the spatiotemporal changes in rural functions and rural settlements at the township level, alongside assessing various forms and the extent of coupled development. Therein, we consider the advantages of different coupling types of townships and propose four development paths for rural settlements to improve the adaptability of rural functions and settlements. The results show that: (1) The functions and settlements in the study area are characterized by significant spatial and temporal dynamics, indicating that the traditional mountainous countryside is in a process of rapid development and change. (2) The coupling coordination degree of RFD and RSE increases yearly, generally transitioning from the moderate imbalance to the basic coordination stage, and the coordinated townships have obvious spatial agglomeration. (3) Based on the elasticity coefficient model, this paper summarizes four coupling models of RFD and RSE to guide the optimization of rural settlement development paths. This research provides scientific guidance for developing countries in the spatial planning of rural territories and the optimization of rural settlements. [ABSTRACT FROM AUTHOR]

Gansu Province in China has the characteristics of an underdeveloped economy, low forest carbon sink, and rich non-fossil energy, making it a typical area for research to achieve the "double carbon" target. In this paper, the primary energy consumption and carbon emissions and their development trends in Gansu Province during the "double carbon" target period were predicted by the fixed-base energy consumption elasticity coefficient method, and the possibility of achieving the "double carbon" target in Gansu Province was explored. In the three hypothetical scenarios, it was estimated that the total primary energy consumption of Gansu Province will be 91.9–94.81 million tons of standard coal by 2030 and 99.35–110.76 million tons of standard coal by 2060. According to the predicted share of different energy consumption in Gansu Province, the CO2 emissions of Gansu Province in the three scenarios were calculated and predicted to be between 148.60 and 153.31 million tons in 2030 and 42.10 and 46.93 million tons in 2060. The study suggests that Gansu Province can reach the carbon peak before 2030 in the hypothetical scenarios. However, to achieve the goal of carbon neutrality by 2060, it was proposed that, in addition to increasing carbon sinks by afforestation, it is also necessary to increase the share of non-fossil energy. As long as the share is increased by 0.3% on the basis of 2030, the goal of carbon neutrality by 2060 in Gansu Province can be achieved. The results show that the increase in the share of non-fossil energy consumption is the most important way to achieve the goal of carbon neutrality in Gansu Province, and it also needs to be combined with the optimization of industrial structure and improvement of technological progress. Based on the research results, some countermeasures and suggestions are put forward to achieve the goal of carbon neutrality in Gansu Province. [ABSTRACT FROM AUTHOR]

The integration of large-scale wind power into power systems has exacerbated the challenges associated with peak load regulation. Concurrently, the ongoing advancement of electricity marketization reforms highlights the need to assess the impact of direct electricity procurement by large consumers on enhancing the flexibility of power systems. In this context, this paper introduces a Distributed Robust Optimal Scheduling (DROS) model, which addresses the uncertainties of wind power generation and direct electricity purchases by large consumers. Firstly, to mitigate the effects of wind power uncertainty on the power system, a first-order Markov chain model with interval characteristics is introduced. This approach effectively captures the temporal and variability aspects of wind power prediction errors. Secondly, building upon the day-ahead scenarios generated by the Markov chain, the model then formulates a data-driven optimization framework that spans from day-ahead to intra-day scheduling. In the day-ahead phase, the model leverages the price elasticity of the demand matrix to guide consumer behavior, with the primary objective of maximizing the total revenue of the wind farm. A robust scheduling strategy is developed, yielding an hourly scheduling plan for the day-ahead phase. This plan dynamically adjusts tariffs in the intra-day phase based on deviations in wind power output, thereby encouraging flexible user responses to the inherent uncertainty in wind power generation. Ultimately, the efficacy of the proposed DROS method is validated through extensive numerical simulations, demonstrating its potential to enhance the robustness and flexibility of power systems in the presence of significant wind power integration and market-driven direct electricity purchases. [ABSTRACT FROM AUTHOR]

To realize a carbon-efficient and economically optimized dispatch of the integrated energy system (IES), this paper introduces a highly efficient dispatch strategy that integrates demand response within a tiered carbon trading mechanism. Firstly, an efficient dispatch model making use of CHP and P2G technologies is developed to strengthen the flexibility of the IES. Secondly, an improved demand response model based on the price elasticity matrix and the capacity for the substitution of energy supply modes is constructed, taking into account three different kinds of loads: heat, gas, and electricity. Subsequently, the implementation of a reward and penalty-based tiered carbon trading mechanism regulates the system's carbon trading costs and emissions. Ultimately, the goal of the objective function is to minimize the overall costs, encompassing energy purchase, operation and maintenance, carbon trading, and compensation. The original problem is reformulated into a mixed-integer linear programming problem, which is solved using CPLEX. The simulation results from four example scenarios demonstrate that, compared with the conventional carbon trading approach, the aggregate system costs are reduced by 2.44% and carbon emissions are reduced by 3.93% when incorporating the tiered carbon trading mechanism. Subsequent to the adoption of demand response, there is a 2.47% decrease in the total system cost. The proposed scheduling strategy is validated as valuable to ensure the low-carbon and economically efficient functioning of the integrated energy system. [ABSTRACT FROM AUTHOR]

The residual soil on a slope can slowly move downward under the influence of gravity, forming a creep landslide. These types of landslides are known for their extensive coverage, significant magnitude, and prolonged duration of hazard. A systematic study of the creep properties of creep landslide geotechnical bodies is essential for the analysis of the deformation process and long-term safety evaluation of landslides. This paper focuses on studying a creep landslide involving residual soil in western Henan Province. The creep characteristics of residual soil with different stone content are investigated through direct shear creep experiments. The findings reveal that stone content has a profound impact on the creep behavior of residual soil. As the stone content of the soil increased, the structure of the test soil changed significantly, resulting in a gradual decrease in its shear creep. The Burgers model can effectively fit the deceleration creep and steady-state creep stages of the residual soil. With the increase in stone content, the four parameters of the Burgers model show a significant increase, with the instantaneous elasticity coefficient G1 and the viscosity coefficient η1 experiencing more noticeable changes. The average long-term strength of specimens with different stone content is only 54% of their instantaneous strength. Additionally, as the stone content increases, the ratio of long-term strength to instantaneous strength also increases. Notably, the long-term strength of specimens with 10–30% stone content is significantly lower than that of specimens with 50–70% stone content. [ABSTRACT FROM AUTHOR]

Located in the Yangtze River Delta region, Jiangsu Province has become the major grain production area of China and plays an important role in ensuring national food security. With rapid economic development and urbanization, the amount of cultivated land has decreased, which greatly affects food security. Based on the statistical data of grain production in Jiangsu Province since 2000 and the remote sensing data of 2000, 2010, and 2020, this paper used the stochastic frontier production function to calculate the output elasticity of various factors and the technical efficiency of grain production. The agglomeration effect of food production was investigated by using spatial correlation analysis. Finally, regression analysis was applied to examine the impact of land use change on grain yield and the technical efficiency of production. The results show that the grain-sown area is the decisive factor for the increase in grain output in Jiangsu Province. The technical efficiency of grain production in the province has been maintained at a relatively high level since 2000, showing a fluctuating upward trend, and the efficiency value in southern Jiangsu Province is greater than that in central and northern Jiangsu. The analysis of the spatial distribution characteristics of grain production technical efficiency shows that grain production has an agglomeration effect. The regression results showed that the complexity of land use and the density of the cultivated land patch were negatively correlated with grain yield and grain production technical efficiency, while the location of cultivated land was positively correlated with grain yield and grain production technical efficiency. The conclusion of this paper has important policy significance for promoting food production and ensuring food security. [ABSTRACT FROM AUTHOR]

In the context of national efforts to promote country-wide distributed photovoltaics (DPVs), the installation of distributed energy storage systems (DESSs) can solve the current problems of DPV consumption, peak shaving, and valley filling, as well as operation optimization faced by medium-voltage distribution networks (DN). In this paper, firstly, a price elasticity matrix based on the peak and valley tariff mechanism is introduced to establish a master–slave game framework for DN-DESSs under the DPV multi-point access environment. Secondly, the main model optimizes the pricing strategy of peak and valley tariffs with the objective of the lowest annual operating cost of the DN, and the slave model establishes a two-layer optimization model of DESSs with the objective of the maximum investment return of the DESSs and the lowest daily operating costs and call the CPLEX solver and particle swarm optimization algorithm for solving. Finally, the IEEE33 node system is used as a prototype for simulation verification. The results show that the proposed model can not only effectively reduce the operating cost of the distribution network but also play a role in improving the energy storage revenue and DPV consumption capacity, which has a certain degree of rationality and practicality. [ABSTRACT FROM AUTHOR]

This paper considers the agency selling channel in a supply chain under platform service investment. We construct Stackelberg game models to study the impact of the manufacturer's encroachment strategy on supply chain members. Research results indicate that the encroachment strategy always has a positive impact at the levels of the manufacturer and platform service, which should dynamically change in response to the manufacturer's action; the platform may actively implement a service strategy without encroachment, while the platform should be cautious in providing services to avoid backlash when encroachment occurs; the high commission rate may prompt the platform to increase the service effort and hinder manufacturer encroachment; when the channel substitution rate is high, both the manufacturer and platform may suffer from it and hence they should slow down their strategy implementation and consider cooperation; when the elasticity coefficient is large and the service cost is high, it may hinder the platform from providing services and the manufacturer may take the opportunity to encroach and thus seize the market. [ABSTRACT FROM AUTHOR]

This paper modeled the tension fluctuation during automated fiber placement (AFP), which depicted the tension variations under different operating conditions. The stability and validity of the model were demonstrated using Bode plots and experiments, respectively. According to the model, the tension fluctuations of AFP at different stages were obtained. Additionally, the passive dancer parameters with the better system performance were determined using the evaluation methodology presented in this paper. Moreover, it was discovered that the damping coefficient affects the tension variation more significantly than the elasticity coefficient. Finally, the placement experiments showed that the determined passive dancer parameters improved the laying quality significantly. [ABSTRACT FROM AUTHOR]

The results of previous research suggest that the elasticity of employment with respect to output is not constant within each phase of the business cycle and might depend on the maturity of that phase. Nevertheless, empirical evidence is almost non-existent. Using the unemployment gap as the proxy for the maturity of the business cycle phase, this paper seeks to determine heterogeneous elasticity across different business cycle phases. Furthermore, we aim to evaluate specific elasticities for separate demographic groups, considering gender, age, and educational attainment level, to identify the most vulnerable to jobless growth. Our specification is based on the employment version of Okun's law, and estimates are provided for the whole EU-27 panel covering the period from 2000 to 2022. Our results suggest that elasticity is higher when the unemployment gap is positive and increasing and lower when the gap decreases, regardless of the business cycle phase. Thus, it can be argued that the possibility of growth increasing employment is very limited when the economy operates at its potential level (full employment) for all demographic groups. [ABSTRACT FROM AUTHOR]

Water pricing is an economic instrument traditionally used to reduce water demand. However, its effective implementation requires knowledge of the extent to which users reduce water consumption with increasing water prices. The price elasticity of water demand has been estimated using econometric regression, which relies on cross-sectional and time-series water data. As an alternative, we propose the use of agent-based modelling, which does not require reliable historical data on water prices and consumption and enables the simulation of multiple scenarios with different consumer profiles, behaviour profiles and water price changes, thereby allowing comprehensive understanding of price elasticity estimates. To illustrate the potential use of agent-based modelling for the estimation of water demand price elasticity, we performed an empirical application to a residential area in Chile. Price elasticity estimates ranged from −0.0159 to −0.1036 (mean −0.0250), indicating that residential water consumption is inelastic to price changes. This result is consistent with previous findings. Agent-based modelling is an alternative for the ex-ante assessment of the potential effectiveness of water pricing policies intended to reduce residential water demand. [ABSTRACT FROM AUTHOR]

Chicken eggs are a staple food widely consumed directly or indirectly (as an ingredient in other food items) in Saudi Arabia. Due to the importance of eggs in Saudi consumers' diet, this study aimed to determine the sociodemographic factors affecting Saudi consumer demand for eggs and how changes in egg prices and consumer income may influence dietary intake derived from eggs. This study analyzes survey data from 466 respondents. We used a double-log demand model to obtain the price and income elasticities of egg demand. The results show that the price elasticity of egg demand is negative and inelastic, indicating that changes in egg price have a small influence on egg demand. Additionally, income elasticity is positive and <1, implying that eggs are a necessary food item. Cross-price elasticities show that cheese and milk complement egg consumption. Meanwhile, cornflakes (a breakfast cereal) were found to be a good substitute for eggs. Furthermore, the results show that consumer demand for eggs is expected to increase as household size increases. Women exhibited a higher demand for eggs, compared with men. Nutrient income elasticity shows that an increase in consumer income increases protein, fat, and calorie intake from eggs. Nutrient price elasticity shows that an increase in egg price has the greatest negative influence on protein intake, resulting from a decrease in egg consumption. This study recommends that decision makers actively monitor egg prices and take all necessary actions to prevent spikes in egg prices, as this will improve nutritional and food security and help consumers maintain a stable protein intake from egg consumption. [ABSTRACT FROM AUTHOR]

The renowned van der Waals (VDW) state equation quantifies the equilibrium relationship between the pressure P, volume V, and temperature k B T of a real gas. We assign new variable interpretations adapted to the economic context: P → Y , representing price; V → X , representing demand; and k B T → κ , representing income, to describe an economic state equilibrium. With this reinterpretation, the price elasticity of demand (PED) and the income elasticity of demand (YED) are non-constant factors and may exhibit a singularity of the cusp-catastrophe type. Within this economic framework, the counterpart of VDW liquid–gas phase transition illustrates a substitution mechanism where one product or service is replaced by an alternative substitute. The conceptual relevance of this reinterpretation is discussed qualitatively and quantitatively via several illustrations ranging from transport (carpooling), medical context (generic versus original medication), and empirical data drawn from the electricity market in Germany. [ABSTRACT FROM AUTHOR]

The relationship between energy consumption and economic development is one of the primary indicators for elaborating energy policies. Different countries are at different stages of economic development and have different levels of energy consumption. Since independence, Kazakhstan's economic development has gone through three stages: the unstable stage (1992–2000), the stage of rapid development (2001–2013), and the stage of stable development (2014–present). Kazakhstan's economy is shifting from an industry-led economy to a service-led economy, thus, the relationship between energy consumption and economic growth also changes. By analyzing the data on energy consumption and GDP during 1992–2023, it was found that a 1% growth of GDP caused a 0.3972% growth of energy consumption in Kazakhstan on average. Due to the long period of economic influence on energy consumption, Kazakhstan could realize the adjustment of the energy consumption structure without affecting economic development by eliminating fossil energy subsidies, reducing taxes on projects for the development of renewable energy, and increasing energy-saving facilities. [ABSTRACT FROM AUTHOR]

We report estimates of supply and demand elasticities for houses (i.e., non-strata properties) in three geographic locations of Sydney. In the Inner Ring of Local Government Areas (LGAs)—those closest to the Central Business District (CBD)—our estimates indicate that the supply curve for houses is perfectly inelastic. This finding allows us to condition on the stock of houses and estimate the corresponding Inner Ring demand curve using ordinary least squares. In the Middle and Outer Rings—where the supply curve for houses has positive elasticity—we use instrumental variables to estimate the demand curve for houses. For all three locations, we obtain theoretically reasonable point estimates of standard demand elasticities, although the degree of uncertainty surrounding the Outer Ring estimates is relatively large. Averaging across the three regions of Sydney, the price elasticity of demand for houses is −1.3, cross-price elasticity with units is 1.1, and income elasticity is 2.1. Based on our elasticity estimates, only in the Outer Ring are any of the direct burdens of stamp duty born by buyers (about 40 percent). [ABSTRACT FROM AUTHOR]

The introduction of the concepts of shear elastic strain ( ε − ) and tensile elastic strain ( ε + ) is a catalyst for new horizons of research into supply chain elasticity. Functional formulas encompassing the metrics of ε − and ε + , their critical point, maximum strain value, and similar parameters are established through rigorous mathematical derivations. The supply chain elasticity of agricultural commodities, including grains, apples, and wheat, are assessed by utilizing the derived formulas. The results show that the metrics of supply chain elastic strain serve as direct metrics of measuring the supply chain's anti-interference capability, and they also facilitate an objective assessment of the supply chain's safety and stability. The formula is succinctly derived, and it yields objective outcomes with general applicability, particularly suited for research and application for supply chain elasticity. [ABSTRACT FROM AUTHOR]

The benefits of energy efficiency are recognized in multiple socio-economic spheres. Still, the quantitative impact on macroeconomic performance is not fully understood, as modeling tools are not thermodynamically consistent—failing to explicitly include the useful stage of energy flows and/or thermodynamic efficiencies in primary–final–useful energy transformations. Misspecification in the link between energy use and the economy underplays the role of energy use and efficiency in economic growth. In this work, we develop and implement the Macroeconometric Resource Consumption model for Portugal (MARCO-PT), 1960–2014. Based on the post-Keynesian framework developed for the United Kingdom (MARCO-UK), our model explicitly includes thermodynamic energy efficiency, extending the analysis to the useful stage of energy flows. The model's stochastic equations are econometrically estimated. The historical influence of key variables—namely thermodynamic energy efficiency—on economic output is assessed through counterfactual simulations and computation of year-by-year output elasticities. The MARCO-PT model adequately describes the historical behavior of endogenous variables. Although its influence has decreased over time, thermodynamic efficiency has consistently been the major contributor to economic growth between 1960–2014, with an average output elasticity of 0.46. Total useful exergy is also a major contributing factor, with an average output elasticity of 0.29. Both have a higher influence than capital, labor, or other energy variables (final energy, prices). An adequate integration of thermodynamic efficiency is thus crucial for macroeconomic models. [ABSTRACT FROM AUTHOR]

In this work, we develop a trade model that explains the pattern of trade between countries based on differences in total factor productivity (TFP) while also accounting for differences in relative factor endowments. The novelty stems from the introduction of production functions derived by combining the Ricardian and Heckscher–Ohlin–Samuelson (H-O-S) theories, with TFP differences serving as the basis of comparative advantage. To this end, a testable hypothesis is derived. For the empirical measurement of the TFP in each industry and country, a constant elasticity of substitution (CES)-type production function was employed, and the TFP was calculated as the Solow residual from the production function's fixed term. To offer a better understanding, the model was tested for the bilateral trade between Germany and Russia, and Germany and the Czech Republic. It was found that TFP differences can be used as a basis for explaining comparative advantages and, consequently, the bilateral pattern of trade between two countries. [ABSTRACT FROM AUTHOR]

The elasticity matrix and the coefficients of thermal expansion (CTEs) of 8-harness satin-woven (8HS) carbon-fiber-reinforced carbon matrix (C/C) composites at high temperatures were obtained by the asymptotic homogenization method (AHM) and finite element method (FEM). By analyzing the microstructure of the 8HS C/C composites, a representative volume element (RVE) model considering a braided structure was established. The effects of the temperature and component volume fraction on the elasticity matrix and CTEs of the composites were investigated. The sensitivity of model parameters, including the size of RVE model and mesh sensitivity, were studied. The optimal calculation model was employed. In addition, the effects of the 4HS methods and 8HS methods on the elastic constants of the composites were compared. The temperature and variation in the carbon fiber volume fraction were found to have a significant impact on the elasticity matrix and CTEs of composite materials. At the same volume fraction of carbon fibers, some elastic coefficients of the 4HS composite material were slightly lower than those of 8HS composite material. This research affords a computational strategy for the accurate prediction of the themo-mechanical properties of satin-woven C/C composites. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic may have had a negative impact on dairy consumption trends. Many dairy products are perishable and have relatively high income elasticity, causing their susceptibility to market fluctuations in general, including those specifically caused by the pandemic. However, the pandemic has also brought some other prospective possibilities. For example, during the pandemic, people paid more attention to nutrition and health issues and increased the number of meals prepared and eaten at home. In consideration of the particular circumstances during the pandemic, the Chinese government issued several policies to promote the population's dairy consumption, and the Chinese dairy cattle sector actively implemented the policy of "guarantee price, quality, and supply". These factors may have caused the Chinese population to increase their consumption of dairy products during the pandemic. Before the pandemic, the consumption of dairy products in the Chinese population showed an overall upward trend. The question addressed in this study is how has COVID-19 affected dairy consumption trends during the pandemic? This study uses accounting data from the Chinese dairy cattle sector to empirically analyze the impact of the COVID-19 pandemic on dairy consumption trends through economic theories and translog revenue function. Our study found that COVID-19 increased consumers' consumption of dairy products in China, but those people experiencing poverty may still have experienced inadequate dairy intake. This study has contributed to the body of work in this area in the literature and provides response strategies for the dairy cattle sector and the authorities. [ABSTRACT FROM AUTHOR]

Amid the global shift towards sustainable development, this study addresses the burgeoning electric vehicle (EV) market and its infrastructure challenges, particularly the lag in public charging facility development. Focusing on Wuhan, it utilizes big data to analyze EV charging behavior's spatiotemporal aspects and the urban environment's influence on charging efficiency. Employing a random forest regression and multiscale geographically weighted regression (MGWR), the research elucidates the nonlinear interaction between urban infrastructure and charging station usage. Key findings include (1) a direct correlation between EV charging patterns and urban temporal factors, with notable price elasticity; (2) the predominant influence of commuting distance, supplemented by the availability of fast-charging options; and (3) a strategic proposal for increasing slow-charging facilities at key urban locations to balance operational costs and user demand. The study combines spatial analysis and charging behavior to recommend enhancements in public EV charging infrastructure layouts. [ABSTRACT FROM AUTHOR]