Search Results (19)

The digital economy is emerging as a transformative force for advancing inclusive sustainable development in rural China, particularly in addressing gender disparities in non-agricultural employment. Using the Digital Inclusive Finance Index and China Family Panel Studies data, this paper analyzes the digital economy’s impact on the gender gap in rural non-agricultural employment. It finds that the digital economy boosts women’s employment and wage, narrowing the gap. This effect is more obvious among groups with medium-high human capital, younger people, married people, and those with kids. The digital economy narrows the gap through the following three mechanisms: reshaping skill demands, reducing info-search cost, and promoting domestic labor socialization. It is an engine for growth and a force for gender equality in rural employment. Full article

In the volatility, uncertainty, complexity, and ambiguity (VUCA) environment, the application of artificial intelligence (AI) technologies is a key engine for shaping supply chain resilience (SCR). This study employs the entropy method to develop an evaluation index system for SCR, incorporating two key dimensions: resistance and recovery capacity. Using a sample of Chinese-listed enterprises from 2009 to 2022, this study reveals that AI significantly enhances SCR, and CEOs’ sports experience can positively moderate the association between AI and SCR. Mechanism examination shows that AI promotes SCR through operational efficiency optimization, information, and knowledge spillover in the supply chain. Heterogeneity analysis reveals that the positive impact of AI is more significant in firms with a high-skilled labor force, firms with high heterogeneity of the executive team’s human capital, high-tech industries, and regions with strong digital infrastructure. Moreover, the AI application has a diffusion effect on the upstream and downstream enterprises of the supply chain, improving AI adoption levels. Our research not only augments the existing literature on the economic ramifications of AI adoption and the strategic value derived from CEOs’ extramural experience but also offers both theoretical frameworks and empirical insights for executive recruitment and fortifying SCR. Full article

An in-depth understanding of the impact of green innovation on the urban–rural income gap is essential for developing countries seeking to address urban–rural imbalances and promote sustainable economic development. This study focuses on China, utilizing provincial panel data from 2007 to 2022, and employs the two-way fixed effects model, the mediating effects model, and the moderating effects model. The study’s key findings are: (1) Green innovation positively reduces the urban–rural income gap. Specifically, the regression results indicate that a one-unit increase in green innovation corresponds to a 0.017-unit reduction in the urban–rural income gap. (2) The heterogeneity analysis reveals that the effect of green innovation on the urban–rural income gap is more pronounced in regions with higher levels of economic development, in non-food-producing areas, and when green utility patents are adopted. Additionally, green innovation narrows the urban–rural income gap predominantly in high-skill regions. (3) Examining the influencing mechanism confirms that green innovation reduces the urban–rural income gap by promoting population urbanization, eco-urbanization, labor force restructuring, and mitigating wage income inequality. (4) The moderating effects analysis indicates that environmental pollution exacerbates the impact of green innovation on the urban–rural income gap; specifically, higher levels of environmental pollution amplify the effect of green innovation in reducing the gap. These findings offer valuable insights for addressing urban–rural income inequality and fostering sustainable socio-economic development in developing countries. Full article

In this study, we construct heterogeneous agent general equilibrium models to investigate the relative importance of labor endowment in driving structural transformation. We aim to explore the following question: beyond the demand-side and supply-side structural transformation driving forces extensively studied in the existing literature, does labor, as a crucial endowment, play a pivotal role in facilitating structural transformation and the energy economy? In contrast to the prevalent partial equilibrium analyses, our study employs a general equilibrium framework to conduct a policy evaluation of college expansion, a significant policy that has altered the labor endowment structure in China. Our approach begins with developing a multi-sector model that integrates a nested CES production function and incorporates workers with different skill levels to assess the macroeconomic impact of college expansion on structural transformation. We calibrate the base model to reflect labor allocations across sectors and skill levels using the simulated method of moments (SMM), ensuring that the model-generated data align closely with actual labor allocation data. Utilizing this calibrated model, we perform counterfactual experiments to assess the impact and relative importance of the college expansion policy. Our counterfactual analysis demonstrates that the policy has resulted in an average decrease of 7.7% in labor allocation in the agricultural sector, alongside an average increase of 8.9% in the industry sector and 28.7% in the services sector. These results highlight the significant, yet often overlooked, contribution of labor in endowment-driven structural transformation. Furthermore, we extend the base model by constructing an industry-level heterogeneous agent general equilibrium model, enabling us to pinpoint which industries have developed as a result of the college expansion policy and recalibrate it at the industry level. This approach allows us to analyze the impact of changes in labor endowment on the energy economy. Counterfactual experiments conducted show that the college expansion policy has prompted a labor shift from industries with low energy efficiency and high pollution to high-end services. This macroeconomic pattern of structural transformation suggests that the college expansion policy has facilitated a transition toward a low-carbon economy by reducing dependency on high energy-consuming industries and promoting high-end services. Full article

The strategic adoption of digital technologies has increasingly been recognized as a crucial driver of cost reduction and operational efficiency in enterprises. It optimizes production processes and promotes sustainable growth. In this context, understanding the specific impact of digital transformation on enterprises’ environmental, social, and governance (ESG) performance holds significant practical value for promoting sustainable development in China’s economy and society. This study focused on Chinese A-share listed enterprises from 2010 to 2022, specifically exploring the role of digital transformation in enhancing ESG performance from the perspective of human capital. Our findings reveal that digital transformation significantly augments their ESG performance. Notably, the improvements are more pronounced in non-state-owned enterprises compared to state-owned ones. Specifically, digital transformation initiatives contribute to ESG performance enhancement by increasing the extent of high-quality labor and elevating the skill levels of the existing workforce. Furthermore, environmental regulation moderates the positive impact of corporate digital transformation on the quantity and skill level of labor, thus influencing firm-level ESG performance. The study sheds light on the transformative role of digital transformation and its implications for ESG performance improvement by elucidating the mechanisms through which digital transformation affects human capital and interacts with regulatory environments. Full article

The objective of this work is to predict the impact of technology on employment demand by profession in Spain between 2023 and 2035. The evaluation of this effect involved the comparison of two scenarios: a trend scenario obtained by predicting the evolution of occupations in demand and a technological scenario anticipated in the case of technological progress. To accomplish this goal, a new approach was developed in the present study based on previous research. Thus, we estimated the proportion of jobs likely to be automated using a task-based approach. Each occupation was examined based on its components to determine the degree to which these tasks could be automated. The results suggest that technology may influence job demand but with low percentages (between 3% and 5% for both low- and high-qualified workers) in the long term. However, job losses are greater in absolute difference in low-skilled professions, where a great share of the labor force is engaged. Full article

Ethnic areas are special in terms of their geographic type, population size, production mode, etc. Scientific assessment of rural residents’ livelihood resilience and exploration of its influencing factors are significant for tapping the potential of rural residents’ livelihood resilience and promoting sustainable rural development. This research takes the villages in the western Sichuan ethnic area as the study area and, based on the sustainable livelihood framework and the analysis framework of rural residents’ livelihood resilience, constructs an evaluation index system of rural residents’ livelihood resilience and explores the factors affecting its evolution using the OLS parameter estimation method. The results found that: (1) Annual per capita income and livelihood diversification of key livelihood factors of farm households have improved under the rural revitalization strategy. (2) Skill training opportunities, loan opportunities, living conditions, non-agricultural work experience, and traffic accessibility had the most significant impact on livelihood resilience, and were the dominant forces in enhancing the rural residents’ livelihood resilience. (3) There was a divergence of livelihood resilience among different types of rural residents, and those with low altitude, low dependency ratio, strong labor endowment, and high literacy had a higher livelihood resilience; furthermore, the mean value of livelihood resilience of tourism-led rural residents was higher than that of non-tourism-led rural residents under different livelihood strategies. Full article

In the context of the rapid development of digital economy and the promotion of sustainable development, this paper focuses on the impact of digital economy on income levels. Based on the panel data of 195 prefecture-level cities, the “Broadband China” pilot has been regarded as a natural experiment for the measurement of the digital economy. In this paper, a time-varying DID model was established to evaluate the influential effect of “Broadband China” on income growth. It was found that the coming into service of “Broadband China” has increased the overall income level of the Chinese labor force. Further research found that “Broadband China” has done more to raise the income levels of the high-skilled labor force, thus widening the income gap between the high-, medium-, and low-skilled labor force. “Broadband China” can affect the income growth via two mechanisms, namely, “increasing the entrepreneurship rate” and “leading to an increase in the overall number of professional and skilled labor force in China”. In this case, the entrepreneurship rate of the high-skilled labor force may be higher than that of the medium- and low-skilled labor force due to human capital accumulation. The rapid increase in the high-skilled labor force in technical industries will lead to the situation where their income growth effect is higher than that of the medium- and low-skilled labor force. Based on the above research results, this paper puts forward policy suggestions from three aspects: further accelerating the process of digital economy; improving the institutional environment of the broadband network and standardizing the order of the construction of the broadband network; and further stimulating the entrepreneurial motivation of labor force, paying attention to the problem of skill bias and optimizing the employment structure, balancing efficiency and equity, and contributing to the ultimate sustainable development of developing countries. Full article

The aim of this article is to present priority themes covered by the Health and Safety training programs of the Greek and European mining industry during the last decade. Mining is considered as an industry presenting high occupational risks. The International Labor Organization (ILO) estimates that 1% of the world’s labor force is engaged in mining, yet mining accounts for 5% of occupational fatalities. Despite the use of advanced technologies in a safer working environment and “the zero harm-zero accidents target”, mining accident statistics indicate that despite the gradual decrease in fatality rate, safety performance has reached a safety plateau. In order to further improve this performance, training and promotion of a safety culture through implementation of mine safety plans and enhancement of technical and non-technical skills at all levels of management are prerequisite measures. Currently, training is increasingly relying on immersive virtual reality to simulate complex operations in potentially dangerous environments. Open-cut or underground mining simulators provide safe, replicable and cost effective environments for miners to be trained and for engineers and managers to test different conditions, new ideas, strategies and scenario outcomes, without exposing employees in real time hazards. High-end training programs have the potential not only to improve workplace safety conditions but also to contribute to more effective management and finally to a more sustainable mining industry. Full article

The large and persistent wage gap between the Bangkok Metropolitan Region and its peripheries remains a major concern for policymakers and civil society. Theoretically, these regional disparities exist due to differences in workforce skills and the local characteristics of the regions. This study empirically investigates the sources of spatial wage disparity in Thailand using data sets from the Labor Force Survey, the Industrial Census, geospatial data, and satellite imagery for the years 2007, 2012, and 2017. The two-stage estimation method was applied, and the soil clay content was used as the instrumental variable for correcting endogeneity and variable bias omission. The results show that workers’ education and experience affect the wage differential. Other than individual skills, workers also benefited from the agglomeration externalities of large cities. Specifically, the effect of agglomeration externalities on wages in Thailand was found to be statistically significant. To overcome the paradox of a low urbanization rate and high urban primacy in Thailand, this study suggests the establishment of multiple regional cities that create high agglomeration externalities. Full article

Kazakhstan has a relatively high level of overall gender development, as well as of female employment in its energy industries. Diverse views and backgrounds are necessary to address the challenges of curbing emissions in Kazakhstan, a major fossil fuel producer and exporter. However, our analysis of the Labor Force Survey indicates that female representation among energy sector managers and overall workforce has been falling over time. Moreover, we find that women in Kazakhstan’s coal mining, petroleum extraction, and power industries are concentrated in low-skilled and non-core occupations. Next, by analyzing data on labor compensation within energy occupations, we discover signs of persistent vertical discrimination, which may reduce incentives for women to upgrade their skills. Finally, we find that major shocks, such as the COVID-19 pandemic, may stall or reverse prior progress in increasing the energy sector’s gender diversity. Our findings contribute to raising gender awareness among the stakeholders in Kazakhstan’s energy sector in order to facilitate evidence-based gender mainstreaming. Full article

Family farms are the “most-desirable”; new-style agricultural production and management entities in China at this stage, as well as their production behaviors, play an important role in achieving sustainability in agricultural development. The scientific evaluation of family farm management efficiency and the identification of an effective path to the high efficiency of family farms with different resource endowments are critical for family farms to transform from quantitative growth to qualitative improvement and develop in a sustainable and healthy way. Based on the data from a rural fixed observation point of the Chinese Ministry of Agriculture and Rural Affairs, this study randomly selected representatives from 532 family farms from 27 provinces, municipalities, and autonomous regions in China as research objects; calculated their total factor productivity based on the DEA model; and employed the Qualitative Comparative Analysis (QCA) method to identify the configuration models for a high total factor productivity, which combines the factors of land investment, capital investment, labor investment, education level of farm leaders, land transfer years, the introduction of new technology and new equipment, and financial support. It is found that the average efficiency of family farms in China is not high yet, and both the pure technical efficiency and scale efficiency have great room for improvement. The efficiency of family farms is not determined by one single condition, but by the combinations of multiple factors. The introduction of new technology and new equipment, long land transfer period, high input of production and labor, and financial support are the driving forces to improve the efficiency of family farms. This demonstrates that although the current family farms are still in the cultivation stage of capital and labor-intensive investment, they do not mainly rely on traditional agricultural productions such as labor to achieve high efficiency. The managerial implications are as follows. First, the strategy of intensive and efficient management instead of the blind expansion of land scale should be considered, the full play to the role of family labor while controlling the scale of employees is highly suggested. Second, attention should be paid to the accumulation of the human capital of family farm practitioners, which implies that more highly educated people for family farm management, as well as high-technical-skilled farm operators, should be employed. Third, it is necessary to create a good institutional environment for the development of family farms and to increase financial support such as credit loans for family farms. Full article

Technological change has altered labor market demands within well-developed societies implying global competition for skilled labor and, as a consequence, new forms of labor migration. So far, patterns of this labor migration have been underexplored. Thus, the article analyzes characteristics, geographies and possible underlying drivers of workers migrating from Germany as an exemplary case for a well-developed country. Relying on probability-based and unique data, our findings reveal that, besides demand for people with higher levels of education, performing specific occupational tasks is also in demand in the global competition for talent. Hence, Germans in jobs with a high proportion of analytical non-routine tasks are more likely to emigrate than those with predominantly manual routine tasks. Moreover, the results show that global discrepancies concerning the technological development between the country of origin and the country to which they emigrate are a crucial contextual driver attracting this specifically demanded work force. Workers mainly performing analytical non-routine tasks within their job tend to move to countries which are technologically more developed than Germany while individuals performing jobs with a high share of non-routine manual or interactive tasks tend to emigrate to countries that are less technologically developed than Germany. Full article

The machine tool industry, which is the starting point of all the metal producing activities, is presently undergoing rapid and continuous changes as a result of the fourth industrial revolution Industry 4.0. Manufacturing models are profoundly transforming with emerging digitalization. Smart technologies like artificial intelligence (AI), big data, the Internet of Things (IoT), digital twin, allow the machine tool companies to optimize processes, increase efficiency and reduce waste through a new phase of automation. These technologies, as well, enable the machine tool producers to reach the aim of creating products with improved performance, extended life, high reliability that are eco-efficient. Therefore, Industry 4.0 could be perceived as an invaluable opportunity for the machine tool sector, only if the sector has a competent workforce capable of handling the implementation of new business models and technological developments. The main condition to create this highly qualified workforce is reskilling and upskilling of the current workforce. Once we define the expected evolution of skills requirements, we can clarify the skills mismatch between the workers and job profiles. Only then, we can reduce them by delivering well-developed trainings. For this purpose, this article identifies the current and foreseen skills requirements demanded by the machine tool industry workforce. To this end, we generated an integrated database for the sector with the present and prospective skills needs of the metal processing sector professionals. The presented sectoral database is a fundamental structure that will make the sector acquire targeted industrial reforms. It can also be an essential instrument for machine tool companies, policymakers, academics and education or training centers to build well-designed and effective training programs to enhance the skills of the labor force. Full article

This paper proposes a new idea for the current argument over Florida’s cultural policies, as location choices of the creative class is a complex process involving some basic aspects of socio-economic progress. Based on the European Labor Force Survey (EU LFE) dataset, tolerance and openness indicators which represent the quality of a “people climate” are found to be positively correlated with the creative class’s location in large regions and less so in smaller ones, where business climate-related parameters, i.e., the quality of local governments and the location of universities, have stronger positive effects on locational choices of the creative class. Moreover, graduates with non-creative jobs and creative professionals (i.e., workers who provide creative solutions during the work process such as high-tech technicians or legal and healthcare workers) are concerned more about the people climate, while creative workers with a degree and a creative core (e.g., workers who provide original ideas such as scientists, engineers and artists) are more likely to prioritize a business climate. Therefore, we argue that the promotion of a “tolerant” climate, as Florida advocates, is not a one-size-fits-all solution. Instead, policy makers should appropriately relate different preferences of creative workers to their unique strengths. This provides more insights into defining the concept of creativity beyond prioritized individual success, as well as understanding the preferences and actual needs of highly skilled workers in Europe. Full article