Search Results (30)

Population aging is a critical demographic trend in China, creating both challenges and opportunities for sustainable development. As aging alters the structure of the workforce and capital demand, understanding its effect on productivity is essential to managing demographic transitions in China. This study investigates the causal impact of population aging on labor productivity, with a focus on the mediating role of the capital–labor ratio and heterogeneities across industries, skill levels, and regions. Using data from Chinese listed firms between 2011 and 2018, this paper employs industry- and year-fixed effects regression models to control for unobservable heterogeneity and conducts a formal causal mediation analysis. The analysis reveals that population aging significantly enhances labor productivity. Specifically, a one-percentage-point increase in the old-age dependency ratio is associated with a 1.47% increase in firm-level labor productivity. The capital–labor ratio emerges as a critical mechanism, mediating the relationship between aging and productivity by incentivizing firms to increase capital intensity in response to labor shortages. Approximately 72.4% of the total effect is mediated through changes in capital intensity. The findings highlight notable heterogeneities. Labor-intensive firms and low-skilled worker segments experience stronger productivity gains from aging compared with their capital-intensive and high-skilled counterparts. At the regional level, the productivity effects are most pronounced in first- and second-tier cities, while third-tier cities show negligible impacts, reflecting resource and structural constraints. This study underscores the dual role of population aging as a challenge and an opportunity. Policy recommendations include (1) expanding targeted fiscal support for capital investment and automation in aging-intensive industries; (2) promoting vocational training programs tailored to older workers and digital skills development; and (3) strengthening infrastructure and institutional capacity in third-tier cities to better absorb productivity spillovers from demographic adjustment. By addressing these demographic and productivity linkages, the study contributes to achieving Sustainable Development Goals 8 (Decent Work and Economic Growth), 9 (Industry, Innovation, and Infrastructure), and 10 (Reduced Inequalities), by promoting inclusive productivity growth, enhancing industrial adaptation to demographic change, and reducing regional and skill-based disparities.These findings offer valuable insights for policymakers and businesses navigating the complexities of aging economies. Full article

The gradual integration of digital technology into traditional Chinese villages has triggered a shift in income distribution from labor to capital, posing challenges to the wage growth of employed peasants. Based on the theory of empowerment, this paper explores the mechanisms of credit availability and talent loss in the interplay between digital capabilities and wage augmentation among employed peasants. This study empirically examines or validates the mechanism of digital capabilities on wage growth for employed peasants through the entropy weight method, the OLS linear model, the mediation effect model, and propensity score matching while using survey data from 490 farmer entrepreneurs as samples. The findings are as follows. (1) The digital capabilities of farmer entrepreneurs have a significant positive impact on the wage growth of employed peasants, and this result remains robust after a series of robustness checks. In terms of hierarchical effects, digital foundational capabilities > digital application capabilities > digital innovation capabilities. (2) Credit availability and talent loss mediate the relationship between digital capabilities and wage growth for employed peasants. (3) The digital capabilities of farmer entrepreneurs who are young, highly educated, and have a low family-dependency ratio exert a more pronounced influence on the wage growth of employed peasants. Additionally, lower policy uncertainty enhances the effect of digital capabilities on wage growth for employed peasants. The study uncovers the empowerment mechanism of digital advancements embedded during the entrepreneurial journey, enriches research on digital capabilities and common prosperity, and provides a feasible path for governments to formulate reasonable entrepreneurship and digital promotion policies. Full article

Optimizing urban land use is of significant practical importance for promoting economic development, enhancing the standard of living for individuals residing in metropolitan areas, enhancing urban infrastructure and public services, driving urban transformation and upgrading, and attaining synchronized progress of the economy, society, and environment. This paper uses the super-efficiency SBM model to measure the urban land use efficiency (ULUE) of 13 cities in the Beijing–Tianjin–Hebei (BTH) urban agglomeration from 2005 to 2020 and explores the spatiotemporal evolution characteristics and influencing factors of ULUE in this urban agglomeration using analysis of spatial data and application of geographic detector methods. The results show that (1) from 2005 to 2020, the ULUE of the BTH urban agglomeration had an initial rise followed by a decline; however, the overall efficiency score is above 1, suggesting an overall effective state; (2) a distribution pattern with Beijing as its core was established, exhibiting greater ULUE in the northern region and poorer efficiency in the southern region, with significant correlation characteristics in efficiency values between adjacent cities; and (3) capital input, labor input, social welfare, and ecological environment are all influencing factors that promote the improvement in ULUE in the BTH region, and the interaction of any two factors explains the ULUE in this region better than a single factor. The empirical research results can provide useful references for improving the input–output ratio of land units and further spatial planning and policy formulation in the BTH region. Full article

This research is focused on knowledge-based performance drivers, which are often intertwined with intellectual capital (IC); specifically, the value-added intellectual coefficient (VAIC) and its profound influence on labor productivity (LP), with the pivotal inputs of training and research and development (R&D) as moderating, in the realm of small- and medium-sized (engineering) enterprises (SMEs). The aim is to offer this as a sustainable model for practical implementation to empower engineering managers, donors, and policy researchers. The motivation catalyzes more informed decision-making investing in human or structural capital. It attempts to foster sustainable growth and societal stability through job creation within the knowledge-intensive engineering sector of developing countries. Methodologically, the research draws upon statistical analysis, employing Pearson’s correlation, multivariate regression, and model testing executed through specialized statistical software. The World Bank Enterprise Survey Instrument was used to collect data on 213 aviation-related firms. Primary data were collected for the years 2013–2022. Several hypotheses were developed between the variables expected to relate positively, because intellectual capital, training, and research and development should lead to better labor productivity. The findings revealed the critical issue of the misallocated investments in structural capital that this model brought forth. Furthermore, the notable contribution to national intellectual capital (NIC) studies is the significant VAIC value of 4.58 and an impressive labor productivity value of 6.78 within the knowledge-intensive ecosystem of SMEs. More insightful findings were the modest 17% positive variation attributable to the VAIC on LP, accompanied by an absence of significant influence exerted by training and R&D on this relationship. While underscoring the model’s overall validity, this intriguing discovery emphasizes the impact of intangibles on knowledge firms’ overall sustainability calculations, specifically structural capital, which accounts for a substantial 31% of labor productivity. The practical implication is that this model can be used to expose long-term financial performance hiccups through intellectual capital measures. The novelty is employing the labor productivity metric sourced from the engineering literature instead of the customary asset productivity (ATO) ratio from the IC literature. Full article

Improving agricultural energy efficiency is essential in reducing energy consumption and achieving agricultural sustainable development. This paper aims to measure the agricultural total-factor energy efficiency in China rather than the partial-factor energy efficiency while taking full account of regional heterogeneity and to investigate the driving factors of agricultural total-factor energy efficiency. The empirical results showed that the average value of agricultural total-factor energy efficiency is 0.814 in China, and the technological gap ratio is 0.853. The regional difference in agricultural total-factor energy efficiency was quite obvious. Higher agricultural energy inputs are associated with higher agricultural total-factor productivity. The total value of potential agricultural energy savings in 30 provinces of China reached 1704.41 billion tons of standard coal. In terms of the absolute amount of agricultural energy saving, the amount was largest in the low-energy-input area, which was 113.87 million tons of standard coal, accounting for 66.81% of the total potential saving amount. Furthermore, we used the Tobit model to analyze the influencing factors of agricultural total-factor energy efficiency. We found that the proportion of agriculture to GDP has a positive impact on agricultural total-factor energy efficiency, while the per capita income of farmers, fiscal support for agriculture, the illiteracy rate of farmers, agricultural labor input, and agricultural capital stock have a negative impact on agricultural total-factor energy efficiency. Finally, we proposed policy implications in terms of agricultural technological progress, agricultural infrastructure, technical training, etc. Full article

The effective refuge area is a key indicator in the study of emergency shelters. Accurately extracting the effective refuge area and analyzing the effectiveness of emergency shelters are of great significance for site selection, spatial distribution, and the evaluation of suitability. Beijing is one of only three capitals in the world located in a high-seismic-intensity zone of magnitude 8. The fast and accurate monitoring of effective refuge areas and an analysis of the effectiveness of emergency shelters are conducive to evacuation planning and disaster prevention and mitigation, and they promote the construction of a resilient city. However, the extraction of effective refuge areas in existing studies is not only a time-consuming and labor-intensive task but also has accuracy and efficiency problems, resulting in less precise validity analyses. In this paper, a remote sensing monitoring technology system for the effective refuge areas of emergency shelters is proposed based on multi-source data. Different methods were used to extract various land features, such as buildings and collapsed areas, water, dense areas of understory vegetation, and steep slope areas that cannot be evacuated, to obtain the effective refuge area at a detailed scale, in combination with the service radius of emergency shelters, the population distribution, and the actual road network, the criteria for effectiveness analysis were established for the effective open space ratio, capacity, per capita accessible effective refuge area, and population allocation gap. Taking the area within the Fifth Ring Road of Beijing as an example, the effectiveness of emergency shelters was analyzed at both the whole scale and a local scale. The results show that the effective refuge areas of different emergency shelters in Beijing vary significantly, with the smallest effective refuge area being located in Rings 2–3 and the largest one being located in Rings 4–5; between different regions, there are differences in the effectiveness. This study provides a feasible method for the fast, accurate, and detailed extraction of the effective refuge areas of emergency shelters and also provides a reference for emergency planning for disaster prevention and mitigation. Full article

The present study proposes an alternative explanation for the negative natural-resource-growth nexus. Based on the theoretical analysis, the study shows that a balanced capital–labor ratio plays an essential role in the absorption of complex capital goods. It estimates the parameters of the constant elasticity of the substitution production function in Mathcad using nonlinear least squares, i.e., an approximate Marquardt method of optimization. The empirical analysis is based on the time-series data of these countries for the time interval between 2000 and 2020. We conducted analyses by calculating the elasticity of substitution between capital and labor. Specifically, for these countries, the elasticity of substitution of capital and labor appeared to be less than one, which indicates a lack of labor, or, more precisely, a qualified labor force. Each of these countries receives windfall profits from the exploitation of natural resources, which greatly influences the import of capital-intensive products of complex technologies—in other words, the import of capital. However, the lack of an adequate labor force that could utilize the increased capital led to a decrease in the elasticity of capital and labor substitution. A comparison of the optimal and the observed capital–labor ratio coefficient shows that this coefficient is significantly higher than optimal in all three countries. Therefore, while keeping the wage fund in balance with fixed capital costs, investments in the knowledge economy and human capital appear to be the preferred areas for the efficient allocation of oil revenues. Full article

Carbon emission is the focus of global climate change concerns. Population aging changes the level of labor structure, which directly affects the industry adjustment and will also have a long-term impact on carbon emissions. Uncovering the complex association among population aging, labor allocation, and CO₂ emission is crucial for developing effective policies for low-carbon and sustainable development in China. Therefore, this study aims to analyze whether population aging contributes to reducing carbon emission intensity by regulating labor allocation. Based on provincial panel data from 2000 to 2019, the Systematic Generalized Method of Moments (Systematic GMM) model and the Bias Corrected Least Squares Estimation with Nonsymmetric Dependence Structure (Bias Corrected LSDV) model are adopted in this study. The results show that nationwide as a whole, population aging objectively inhibits human capital accumulation and, to some extent, weakens its positive carbon emission reduction effect. Meanwhile, population aging helps to mitigate the increase in carbon emissions caused by the capital-labor endowment structure. Due to the dual impact of aging and population migration, the emission reduction effect of human capital accumulation is significant in the East. The brain drain in the central and western regions further inhibits the positive effect of regional human capital accumulation. Promoting the rationalization of population mobility nationwide, reducing the brain drain in less developed regions, and directing capital into technology-intensive industrial sectors are the core keys to achieving optimal labor allocation in an aging society. This will help China meet its carbon neutrality target on schedule. Full article

This article deals with the issue of human capital as a factor responsible for the emergence of development inequalities in rural areas. Its main goal is to analyze and evaluate the existing differences in the distribution of human capital resources in rural areas in Poland in relation to their socio-economic situation. The essence of human capital is expressed through the analogy of energy and capital in relation to the concept of homo energeticus. The essence of human capital is also expressed in terms of two components of its structure, i.e., health and the labor market. The level of human capital was expressed using two synthetic measures, i.e., the human capital ratio in the field of health (HCH) and the labor market (HCLM). The obtained research results indicate the existing differences in the spatial distribution of human capital, resulting in a polarization effect in the center-periphery system, and showing relations with the socio-economic structure of rural areas, their agricultural function, and the ongoing population processes. The assumption about the existing relations between the individual components of the structure of human capital, i.e., health and the labor market, with the socio-economic situation of individual communes should be considered correct. The obtained results of the empirical analysis constitute an important contribution to the description of the mechanism explaining the causes of the existing disproportions in the level of rural development; they allow for a more optimal planning of the instruments supporting their development at the local level. The empirical analysis was carried out in spatial terms with regard to rural areas in Poland defined in accordance with the administrative criterion of the Central Statistical Office at the lowest local (rural) level of data aggregation. The analysis covers rural and urban-rural communes in Poland, i.e., 2172 spatial units. The source of data for the synthetic measures (HCH and HCLM) was Local Data Bank Statistics Poland (LDB SP), and that for the indicator of the level of socio-economic development for rural areas (S-EDI) was the European Fund for Polish Rural Development (EFRWP). Full article

Industrialization and urbanization are critical paths to modernization for a country or region. The coordination of industrialization and urbanization fosters the development of a regional economy. In academic circles, this is usually measured by the IU ratio (ratio of labor industrialization rate to urbanization rate) and the NU ratio (ratio of non-agricultural employment rate to urbanization rate). However, these methods are inapplicable to large countries’ inland areas. The traditional methods failed to explain the real situation and produced contradictory results. The IU ratio shows that industrialization lags behind urbanization, while the NU ratio shows that industrialization is ahead of urbanization. According to studies conducted in the Sichuan Province of China, through comparison with Jiangsu Province, it is found that the non-agricultural employment growth is not dependent on the development of local industrialization, and rural-urban migration is not entirely dependent on the evolution of the non-agricultural employment rate. Other factors that promote urbanization, such as the country’s capital policies and funds for migrant labor force transfer, should also be considered. This research attempts to improve the traditional methods for measuring the degree of urbanization and industrialization synergy in inland areas. The new empirical approach can effectively identify the critical characteristics of urbanization in inland provinces, such as the development of non-agricultural employment with external assistance and urban migrants “unrelated to employment opportunities”. Based on these key characteristics, it can provide the basis for local urbanization policy formulation. Full article

The purpose of this study is to explore the impact of pollution control on industrial production efficiency in 31 provinces and cities in the Yellow River and Non-Yellow River basins in China from 2013 to 2017, using the methods of the directional distance function (hereinafter referred to as DDF) and the technology gap ratio (hereinafter referred to as TGR) in parallel, while taking the industrial production sector (labor force, total capital formation, energy consumption and industrial water consumption) and the pollution control sector (wastewater treatment funds and waste gas treatment funds) as input variables. Undesirable outputs (total wastewater discharge, lead, SO₂ and smoke and dust in wastewater) and an ideal output variable (industrial output value) are taken as output variables. It is found that the total efficiency of DDF in the Non-Yellow River Basin is 0.9793, which is slightly better than 0.9688 in the Yellow River Basin. Among the 17 provinces and cities with a total efficiency of 1, only Shandong and Sichuan are located in the Yellow River Basin. The TGR values of 31 provinces, cities and administrative regions are less than 1, and the average TGR value of the Yellow River Basin is 0.3825, which is lower than the average TGR value of the Non-Yellow River Basin of 0.5234. We can start by improving the allocation of manpower and capital, implementing the use of pollution prevention and control funds, improving the technical level of industrial production, improving pollutant emission, and increasing output value to improve overall efficiency performance. This study uses the parallel method, taking the industrial production department and the pollution control department as inputs, to objectively evaluate the changes in industrial production efficiency and technology gap in the Yellow River and Non-Yellow River basins, which is conducive to mastering the situation of pollution control and industrial production efficiency, and provides the reference for SDG-6- and SDG-9-related policy making. Full article

Identifying effective transformations to reduce poverty and approach rural sustainability is at the core of the first sustainable development goal of the United Nations. This article offers scientific support for continued efforts in sustaining rural development and livelihood resilience. Many studies have examined drivers of livelihood transition from farming to non-farm activities, especially participation in tourism against the backdrop of rural tourism development. However, few studies have identified ways to measure the level of tourism participation or have discussed how household-level capital influences decisions regarding tourism participation made by Tibetan ethnic households. This article assesses the role of livelihood capital in the adoption of tourism activities at the household level in Jiaju Tibetan Village, an ethnic region that is experiencing struggling agricultural business and developing tourism sector. Using household survey data, this study presents an ordinal logistic regression model to identify the determinants of the household tourism participation level. The results showed that households’ tourism participation was influenced by physical capital (e.g., proximity to major roads, odds ratio = 2.83 at p = 0.024; fixed capitals, odds ratio = 101.19 at p = 0.039), human capital (e.g., availability of family labor, odds ratio = 0.25 at p = 0.004; availability of skilled member, odds ratio = 2.91 at p = 0.002), and social capital (e.g., relatives in governmental sectors, odds ratio = 5.22 at p = 0.044; government payments, odds ratio = 8.78 at p = 0.04), while the influence of financial capital was not significant. The proximity to major roads, availability of skilled members, fixed assets, and direct and indirect support from the government to households were significantly and positively associated with tourism participation level. The effects of household labor availability and annual family income remain unclear. Overall, household livelihood capital plays a critical role in the enhancement of tourism participation in Jiaju Tibetan Village. Our findings have implications for understanding the shift of on-farm occupation to off-farm activities in tourism and for the pursuit of policies contributing to poverty reduction and rural revitalization in China as well as to the Sustainable Development Goals. Full article

The elderly dependency ratio in China has increased from 10.7% in 2003 to 17.8% in 2019, and there may be a link between the widespread withdrawal of family entrepreneurship in society and the increased dependency burden. Based on China Family Panel Studies, we empirically examine the impact of dependency burden on household entrepreneurial exit behavior. We find that the likelihood of household exit from entrepreneurial activity increases as the population ages. Compared to active exit from entrepreneurship, dependency burden mainly induces failure exit from household entrepreneurship. In addition to reducing physical capital accumulation and labor supply, dependency burden also reduces the household workforce’s mental and physical health, leading to the entrepreneurial exit. The application of digital technology can mitigate the negative effects of dependency burden in household entrepreneurship. The mitigating effect of digital technology will be enhanced with the deepening of the application. Therefore, government and academia need to pay attention to the negative effects of dependency burden on the sustainability of household entrepreneurship. Full article

We proposed an approach to evaluate ecological efficiency of an economy as the ratio of the created output of non-primary goods and services to the input of consumed resources (labor, capital, raw materials, environmental costs) using the DEA. The eco-efficiency of an average Russian region has been growing since 2003. Using econometric calculations, we have established it grew faster in densely populated areas with a high share of high-tech services, investment attractiveness, and intensive technology implementation; it decreased in most northern and Siberian regions. The simultaneous growth of GRP per capita and ecological efficiency in a region was considered as a model of sustainable development. We observed this pattern more than half of the period 1998–2017 in most Russian regions although the Russian economy mainly developed due to the extraction of raw materials. Full article

The goal of the basic business perspective has switched from previously maximizing profit to the current three fields of environment, society, and the economy, within the viewpoint of corporate social responsibility (CSR). This study, from the perspective of sustainability, discusses the current business model of the relationship between CSR and the performance of the Industrial and Commercial Bank of China (ICBC), a state−owned bank, with SBM-DEA and Tobit regression methods, and it puts forward a direction for improvement for future business models. Through the analysis of the years from 2010 to 2018, it has been found that the years with the best performances are 2010, 2011, and 2018, and some empirical evidence from the ICBC is as follows. First, corporate financial leverage closely follows gross domestic product (GDP) growth in terms of utilizing total assets. The ICBC seems to place less attention on its sales and on the number of deposits because of its high ratio of government stock holdings. Second, the ICBC raises labor productivity through education and training of its employees as well as through the proper utilization of capital for input-side management. Lastly, performance has improved as the ICBC has focused more on long-term society contributions, which are directed toward charity donations, loans for poverty alleviation, and green economy development in terms of output-side management. Therefore, through the above three CSR strategies, the ICBC has positively contributed toward environmental innovation and the societal transition of China, and its practices can be used as a sustainable model for future development. Full article