Significant Inverted U-shaped Relationship Research Articles

Research on the Impact of Agricultural Production Outsourcing on Farmers’ Fertilizer Application Intensity: An Inverse U-Shaped Relationship

Agricultural production outsourcing services encourage a shift in the way crops are grown in developing countries and make it easier for small farmers to join the social division of labor in agriculture. This makes production more efficient and has a big effect on the inputs used in agriculture, especially fertilizer. This paper empirically tests the impact of production outsourcing on farmers’ fertilizer intensity using the instrumental variables method with non-planar panel data from the 2020–2022 China Land Economy Survey (CLES) of farm plots. The results showed that there was a significant inverted U-shaped relationship between the degree of agricultural production outsourcing and the intensity of fertilization on farmers’ plots. Mechanistic analysis shows that agricultural production outsourcing affects the fertilizer intensity by changing the labor allocation of farmers. Especially as the degree of agricultural production outsourcing increases, the intensity of farm labor inputs by farmers gradually decreases, and the impact of fertilizer intensity on the plots showed a tendency to be promoted first and then suppressed. The moderating effect showed that plot size was a major moderating factor. This means that the bigger the plot, the flatter the inverted U-shaped curve became, and the same level of outsourcing could lead to less fertilizer application. This happened by moving the inflection point of the inverted U-shaped curve to the left, which stopped the fertilizer application at a lower level of outsourcing. Heterogeneity analysis showed that participation in technology-intensive production outsourcing was beneficial in terms of reducing fertilizer intensity, and that an increased degree of agriculture production outsourcing was beneficial for farmers with large plot sizes and younger heads of household.

The impact mechanism of enterprise financialization on firm innovation

Financial market development provided enterprises with more financing options, which affected their innovation activities. This study is based on 1,274 manufacturing companies. We found a significant inverted U-shaped relationship between enterprise financialization and ambidextrous innovation, and financing constraints can negatively regulate this relationship. The inverted U-shaped impact was more significant in enterprises with large-scale financial backgrounds and low innovation willingness. This study provides targeted guidance for improving corporate innovation.

Unraveling Changes of Brachial Artery Residual Stress and Its Relationship to Cardiovascular Disease Risk Factors.

Arterial pressure volume index (API) offers a non-invasive measurement of brachial artery residual stress. This study investigated API distribution characteristics and correlations with cardiovascular disease risk (CVD) factors in a large Chinese population sample. This cross-sectional study surveyed a total of 7620 participants. We analyzed the relationships between API and factors influencing CVD, using regression-based stepwise backward selection and restrictive cubic spline models to express relationships as standardized beta values. Multiple linear regression analysis identified many independent factors influencing API including age, sex, body mass index (BMI), pulse pressure (PP), heart rate (HR), hemoglobin, uric acid (UA), estimated glomerular filtration rate (eGFR), triglyceride (TC), and a history of hypertension. Notably, API values increased at 33 and escalated with advancing age. Increases in API were associated with rises in PP and UA increases, particularly when PP reached 60 mmHg and the UA reached 525 units. Conversely, API was found to decrease with elevated HR and eGFR. Furthermore, there was a significant inverted U-shaped relationship between API and BMI. This study was the first to describe API distribution characteristics in a large sample of the Chinese population, providing references for evaluating API changes in the assessment of residual stress variations in diverse diseases. Notably, API displayed a U-shaped relationship with age and was closely related to traditional CVD risk factors, underscoring its potential as a non-invasive tool for risk assessment in vascular health. This research was registered with the China Clinical Trial Registration Center (Registration Number: ChiCTR2000035937).

Carbon Kuznets curve in China: Nighttime light analysis in prefecture-level cities

Analysing the relationship between economic growth and carbon emissions may help China to determine how to reduce carbon emissions. This study examined 221 Chinese prefecture-level cities using data from 2003 to 2018 to investigate the possible inverted U-shaped relationship between carbon emissions and economic growth, based on per capita nighttime light brightness. This revealed a significant inverted U-shaped relationship between per capita nighttime and carbon emissions with a per capita GDP of 139.8 thousand Yuan corresponding to the turning point. For China to achieve its carbon emissions peak before 2030, the per capita GDP growth rate would need to be at least 6.6 %. Therefore, for help prefecture-level cities to achieve peak carbon, they must strive towards high-quality economic growth and accelerate transformation of economic growth modes to improve low-carbon pilot policies, and such projects should be implemented in more cities. Efforts to achieve peak should be accelerated first in eastern cities and later in western cities.

Impacts of digital transformation on enterprise innovation resilience: A study from China

Purpose: This study aims to investigate the impacts of digital transformation on enterprise innovation resilience, with a focus on understanding how digital transformation influences innovation resilience across different stages during the life cycle of an enterprise.Design/methodology/approach: Data were collected from Chinese A-share listed companies from 2012 to 2022. Industries with unique financial reporting characteristics, special treatment (ST) samples, and samples with missing data are excluded to obtain a final dataset of 18 304 observations. A regression model is employed to examine the dual effect of digital transformation on enterprise innovation resilience.Findings/results: The findings reveal a significant inverted U-shaped relationship between digital transformation and enterprise innovation resilience. For companies at different lifecycle stages, digital transformation significantly enhances innovation resilience during the growth phase. However, for mature and declining companies, digital transformation still exhibits an inverted U-shaped relationship with innovation resilience, albeit with a relatively lower empowerment effect during the decline phase.Practical implications: Enterprises are advised to leverage the positive effects of digital transformation on innovation resilience while avoiding the pitfalls of excessive digitisation. Flexibility in adapting digital transformation strategies according to the enterprise lifecycle stage is recommended. Furthermore, enterprises should prioritise the coordinated development of various factors contributing to innovation resilience.Originality/value: This study extends the examination of innovation resilience from macro-industry to micro-enterprise levels and provides insights into the dynamics of digital transformation effects on innovation resilience across different lifecycle stages. Additionally, it highlights the importance of considering multiple pathways through which digital transformation influences innovation resilience.

Spillover Effects of Urban Expansion on Land Green Use Efficiency: An Empirical Study Based on Multi-Source Remote Sensing Data in China

Land is an important carrier of resource elements, and improving land green use efficiency (LGUE) is the key to achieving “smart growth” in cities. This study takes 269 cities in China from 2008 to 2020 as the research object and integrates multisource remote sensing data, GIS spatial analysis, and spatial econometric models to explore the evolutionary characteristics of LGUE and the spatiotemporal effects of urban expansion on LGUE. The results show that (1) urban LGUE increases over time and has certain gradient distribution and spatial dependence characteristics; (2) urban expansion has a significant inverted U-shaped relationship with LGUE, indicating that maintaining reasonable urban expansion is the key to improving LGUE, but excessive urban expansion has a strong negative spatial effect on LGUE. In terms of spillover effect, for every 1% increase in the square term of urban expansion, the LGUE of the local city decreases by 0.0673%, but the neighboring city increases by 0.2283%; and (3) urban expansion has significant spatiotemporal heterogeneous effects on LGUE, and spatial development boundaries must be reasonably determined to achieve “smart growth”. Currently, some cities in China are expanding rapidly, and we hope to provide key support for promoting the “smart growth” of cities and improving LGUE.

Innovation performance feedback and inter-organization knowledge search in high-tech firms: The moderating role of technical knowledge complexity

Building on the knowledge search behaviors exhibited by high-tech firms, this study develops a contingency model to explore the relationship between innovation performance feedback and inter-organization knowledge search. The moderating role of technical knowledge complexity is then examined. Utilizing the sample of high-tech firms in China and employing the negative binomial regression model, this study examines the influences of different states of innovation performance feedback (below and above aspirations) on knowledge search breadth and depth. The results show a significant U-shaped relationship between innovation performance below aspiration and the breadth and depth of inter-organization knowledge search. Moreover, there exists a significant inverted U-shaped relationship between innovation performance above aspiration and the search breadth and depth. Furthermore, the technical knowledge complexity enhances the U-shaped association of innovation performance below aspiration and knowledge search breadth, while strengthening the inverted U-shaped influence of innovation performance above aspiration and knowledge search depth.

Can Urban Sprawl Promote Enterprise Innovation? Evidence from A-Share Listed Companies in China

Urban sprawl does not invariably impede factor agglomeration; rather, it can foster polycentric urban configurations, thereby enhancing productivity and encouraging enterprise innovation. This study investigates the effect of urban sprawl on enterprise innovation using data for A-share listed Chinese companies from 2010 to 2020. The results reveal a significant inverted U-shaped relationship between urban sprawl and enterprise innovation, particularly among large enterprises, well-established entities, non-state-owned enterprises, and those operating in non-manufacturing sectors. Additionally, the effects of urban sprawl on the inverted U-shaped relationship are more pronounced in the north-eastern regions and small cities. Regional integration significantly moderates the inverted U-shaped relationship between urban sprawl and enterprise innovation. This research contributes new insights to the field of enterprise innovation, offering theoretical and empirical support for analyzing the economic implications of urban sprawl.

CFO age and R&D investment of gem-listed companies: The moderating role of female executives

This study focuses on examining the non-linear association between CFO age and enterprise R&D investment while also investigating the moderating role of female executives in effecting such a link between the two in order to promote enterprises’ R&D investment and increase female executives’ participation in corporate. Taking Chinese GEM-listed companies over 2009-2021 consisting of 5891 firm-year observations as the samples, conduct the empirical analysis. The findings indicate that a significant inverted U-shaped relationship exists between CFO age and R&D intensity. Specifically, the curve relationship initially exhibits a positive effect of CFO age on R&D intensity before the age of 44, and after that, it turns out to be negative. Moreover, and quite critically, female executives have a significant negative moderating effect on the inverted U-shaped relationship mentioned above. The findings were confirmed by rich robustness and endogeneity tests. Additionally, further exploration of the relationship between CEO tenure and R&D intensity reveals a similar inverted U-shaped curve but does not find any moderating effect of female executives. Based on these results, the study provides Chinese GEM-listed enterprises with rich theoretical guidance and practical implications to optimize the allocation and motivation of executive talents, the career planning of CFOs, and the decision-making patterns of female executives.

Promotion incentives, economic growth targets and industrial land supply: evidence from China

ABSTRACT This study examines the impact of officials’ promotion incentives on the industrial land supply and explores the mediating role of economic growth targets, which are greatly influenced by local leaders. Using the panel data of 257 prefecture-level cities across China from 2007 to 2019, we identify the influence of officials’ promotion incentives on industrial land supply using a two-way fixed-effects model and then examine the mediating role played by the setting of economic growth targets using a mediating-effects model. The estimated results indicate that the promotion incentives of local leaders and the supply of industrial land by local governments follow a significant inverted U-shaped relationship, and that the economic growth targets play a partial mediating role. Heterogeneity analysis shows that the impact of promotion incentives for local leaders on industrial land supply is significantly heterogeneous due to differences in the age of local leaders and the economic development across different regions. The findings are important for improving China’s assessment system of officials, formulating economic growth targets, and optimizing the allocation of urban industrial land.

Can fiscal expenditure for agriculture mitigate the impact of climate change on agricultural production?

The profound impact of climate change on agricultural production, and the government’s fiscal expenditure for agriculture, is considered a crucial means to address this challenge. This study utilizes panel data from all prefecture-level cities in Heilongjiang Province from 2000 to 2020. Drawing upon the Cobb–Douglas production function, an economic climate model is constructed to empirically analyze the impact of climate change on grain yield in Heilongjiang Province. Furthermore, the role of fiscal expenditure for agriculture in mitigating the effects of climate change on grain yield is explored. Feasible Generalized Least Squares (FGLS) estimation is employed to address issues of “heteroscedasticity,” “autocorrelation within groups,” and “cross-sectional contemporaneous correlation” present in the model. The results indicate that climate change has a positive impact on rice and corn yields, while exhibiting a negative impact on wheat yield. The influence of climate change on crop yield is both linear and nonlinear. Specifically, temperature demonstrates a linear relationship with rice and corn yields, whereas precipitation shows a significant inverted U-shaped relationship with rice and corn yields. The impact of climate change on grain production in Heilongjiang Province varies significantly across regions. Fiscal expenditure for agriculture has a significant positive effect on the yield of major grain crops in Heilongjiang Province. In addressing the impact of climate change on grain production, agricultural fiscal expenditure enhances the positive effect of precipitation on rice and corn yields, while diminishing the positive impact of temperature on corn yield.

Research on the green innovation effect of digital economy network – Empirical evidence from the manufacturing industry in the Yangtze River Delta

The digital economy is open and borderless, and the development of an urban digital economy forms an associated network. Based on the social network theory, the digital economic association network formed between cities can enable manufacturing enterprises to obtain heterogeneous resources, stabilize the network relationship between nodes, and improve innovation performance. The digital economy's spatial correlation network drives the manufacturing industry's green innovation to improve quality and efficiency. Through the integration of external relations, green innovation, proximity, regional innovation system, and other dimensions of the theory, this study takes 41 prefecture level cities in the Yangtze River Delta from 2006 to 2021 as samples to construct the digital economy correlation network of urban agglomerations and uses the social network analysis method (SNA) to reveal the evolution law of the digital economy correlation networks. We establish the panel fixed effect model to explore the green innovation effect of digital economy networks. The results show that the Yangtze River Delta urban agglomeration constitutes a spatial correlation network of the digital economy, promotes the sharing and exchange of manufacturing resources through factor linkage, and produces a green innovation effect. The network centrality and relationship strength have a significant inverted U-shaped relationship with the green innovation of the manufacturing industry. There is a significant U-shaped relationship between structural holes and the green innovation of the manufacturing industry. Accordingly, we should further improve the design of digital economy development and promote the development of the manufacturing industry.

DOES THE DIGITAL ECONOMY CHANGE THE RELATIONSHIP BETWEEN ECONOMIC GROWTH AND CARBON EMISSIONS? EMPIRICAL EVIDENCE FROM 278 CITIES IN CHINA

The rise of the digital economy has had widespread and profound impacts on the economy and society. Extensive literature exists on digital economy and carbon emissions. However, there is a lack of literature focusing on the impact of the digital economy on the relationship between economic development and carbon emissions. This paper examines whether the digital economy has changed the relationship between economic growth and carbon emissions using panel and spatial econometric modeling. Using a panel dataset of 278 prefecture-level cities in China for the period from 2011 to 2019, the results show that there is a significant inverted U-shaped relationship between economic growth and carbon emissions, which is consistent with the Environmental Kuznets Curve (EKC) model. Moreover, the digital economy brings the turning point forward. In terms of spatial decomposition effects, both direct and indirect effects of economic growth on carbon emissions are significant, suggesting that economic growth has a positive impact on carbon emissions both in local cities and in neighboring areas. Overall, these findings provide valuable policy insights for promoting the synergistic development of the digital economy and accelerating the transition to a low-carbon economy.

Digital transformation and enterprise financial asset allocation

ABSTRACT As a new factor of production, data is a new driving force for China’s economic development. Digital transformation is highly uncertain, and it is crucial to examine the impact of corporate digital transformation on the integration of digital and real economies. Using all non-financial Chinese A-share listed companies from 2012 to 2021 as the research sample, we investigate the impact of digital transformation on corporate financial asset allocation. The study finds that there is a significant inverted U-shaped relationship between digital transformation and defensive financial asset allocation and a significant positive relationship with profit-seeking financial asset allocation. The mechanism analysis shows that digital transformation impacts the allocation of defensive financial assets through the operational risk of enterprises and promotes the allocation of profit-seeking financial assets through the path of financing arbitrage. Furthermore, the impact of digital transformation on the enterprises’ financial asset allocation varies somewhat across property rights, regions, and industries. This finding has some implications for promoting digital transformation and guiding the real economy to transfer from fictitious to substantial.

Influence mechanism of industrial agglomeration on carbon emission intensity-a perspective on borrowing performance.

Under the background of urban connectivity, whether there are similarities and differences in the impacts of local industrial agglomeration and inter-city industrial agglomeration borrowing performance on carbon emission intensity(CI), and how cities can fully utilize the external force-borrowing performance to reduce local CI, these issues are of great significance for the cost saving and efficiency enhancement in the process of carbon emission (CE) reduction. Based on panel data of 280 prefecture-level cities in China from 2003 to 2020, the panel dual fixed-effect model, instrumental variable method, and adjustment effect model were used to analyze the impacts of the manufacturing agglomeration (MA), producer service agglomeration (PA), and the collaborative agglomeration (CA) on the CI from the perspective of individual cities and the urban system. The results showed that the influence of MA on CI presents a significant inverted U-shaped relationship, PA significantly reduces CI, and the CA of the two industries increases CI. Further analysis showed that the borrowing MA performance improves CI, especially in newer industrial-based cities, non-resource-based cities, and medium and big cities; the borrowing PA performance reduces CI, especially in old industrial-based cities, non-resource-based cities, and large cities; and the borrowing CA performance has no significant effect on CI. In addition, the development of the Internet strengthens the influence of borrowing performance in MA and PA on CI.

Effect of empowerment: how and when do high-involvement work practices influence elder employees' innovative performance?

In today's fast-paced business environment, innovation from elder employees is increasingly vital to organizations. High-involvement work practices that emphasize engagement and empowerment have a significant impact on the innovation performance of these employees, harnessing their wealth of experience and fostering organizational growth. However, most of the current research on innovation performance focuses on the single factor of the individual or the organization, and most of them focus on the linear relationship; research on the factor of human resource practices, in particular high-involvement work practices, is inadequate. Based on social exchange theory, this paper uses structural equation modeling (SEM) to examine the impact of high-involvement work practices on elder workers' innovation performance using 278 valid samples from three time points, and the non-linear effects of exploratory and exploitative innovation on elder workers' innovation performance. (1) There is no significant relationship between high-involvement work practices and elder employees' innovation performance. (2) Exploratory innovation has a significant U-shaped relationship with innovation performance, i.e., as the level of exploratory innovation increases, the innovation performance of elder employees first decreases and then increases. There is a significant inverted U-shaped relationship between exploitative innovation and innovation performance, i.e., as the level of exploitative innovation increases, innovation performance first increases and then decreases. High-involvement work practices have a U-shaped effect on elder employees' innovation performance through exploitative innovation. (3) Transformational leadership moderates the direct effects of high-involvement on exploratory innovation and elder employees' innovation performance, and transformational leadership moderates the U-shaped effect of high-involvement work practices on elder employees' innovation performance through exploratory innovation. The conclusion is helpful for organizations to enhance elder employees' innovation performance by enriching high-involvement work practices.

The effect of population ageing on technological innovation in emerging market countries

This study reveals a significant inverted U-shaped relationship between population ageing and technological innovation in emerging market countries. The research explores this relationship from two perspectives: religion and region. First, when analysing different groups based on the proportion of religious population, it is observed that both countries with a high and low proportions of religiously affiliated individuals exhibit a significant inverted U-shaped relationship between ageing and innovation. As for regional variations, the Southern hemisphere countries displayed a significant relationship, while the Eastern and Western hemispheres did not. Education and research and development (R&D) investment positively influence innovation, particularly in countries with a lower proportion of religious population. Conversely, economic development and foreign investment hinder innovation in countries with a lower proportion of religious population but have a positive effect in countries with a higher proportion of religious population. This study, through mechanism analysis, found that ageing also has an inverted U-shaped impact on technological innovation by influencing both labour supply and human capital investment. Previous research has not addressed the ageing population and technological innovation in emerging market countries. The analysis establishes a theoretical foundation for emerging market countries' governmental macroeconomic regulation.

Impact of China's digital economy development on the health of middle-aged and older people: an air pollution-based perspective.

China has shown good momentum on the road of digital economy development, however, it is also rapidly entering an aging society. Exploring the health effects of the digital economy is of positive significance for realizing healthy aging in China. This paper focuses on the relationship between the digital economy and the health of middle-aged and older people using microdata from the China Health and Retirement Longitudinal Study (CHARLS) 2011-2018 and macrodata from Chinese cities. The study found that the digital economy showed a significant inverted U-shaped relationship on the health of middle-aged and older people. The results of subgroup regressions indicated heterogeneity in this effect across gender, education level, urban/rural and region. Individual health in female, highly educated, and urban groups is more closely related to the digital economy. Middle-aged and old groups in the western region are better able to enjoy the dividends of the digital economy, while middle-aged and old groups in the eastern region are more negatively affected by the digital economy. In the lead-up to the development of the digital economy, individual health can be promoted by narrowing the urban-rural income gap and increasing basic medical resources, while in the later stage of the development of the digital economy, it manifests itself in inhibiting the level of individual health by widening the urban-rural income gap and lowering the level of basic medical resources. In addition, air pollution exhibits a positive moderating effect between the digital economy and individual health, suggesting that air pollution reinforces the impact of the digital economy on health. Expansive analyses indicate that the digital economy has a negative impact on physiological health.

How can small and medium-sized cities differentiate their carbon peaks?

China's ‘dual carbon’ strategy is of strategic importance in leading global climate governance and promoting China's high-quality and green economic development. Cities are the centres of human activities. However, these are also places where high energy consumption and high carbon emissions are concentrated. This study selected data from 192 small and medium-sized cities in mainland China for the period 2000–2020. It classified these into seven categories using the K-means clustering method, calculated the decoupling status of different types of small and medium-sized cities based on the Tapio decoupling index, and analysed the relationship between carbon emissions and economic growth in various types of small and medium-sized cities based on the EKC curve theory. Finally, the backpropagation neural network (BPNN) model was used to classify and predict the time required to achieve carbon peaking for seven types of small and medium-sized cities. The following conclusions were drawn: (1) The development status of small and medium-sized cities shows a ‘geese echelon pattern’. New dynamic small and medium-sized urban areas may reach peak carbon emissions first, while resource-based small and medium-sized urban areas may be the last to do so. (2) The decoupling of carbon emissions from industrial development in small and medium-sized cities has not been completed. This manifests mainly through the states of declining decoupling, absolute decoupling, and strong negative decoupling. (3) A significant inverted U-shaped relationship exists between economic development and carbon emissions in these cities. (4) These cities may have the disadvantage of premature or excessive de-industrialisation. Additionally, these generally have an inefficient and expansionary economic development status. Therefore, this study contended for a more robust integration of a radical political economy and ecological economics to support the development of such cities in China. The paper proposes differentiated development paths and fundamental recommendations for small and medium-sized cities in the implementation of the ‘double carbon’ strategy. The intention is to provide theoretical guidance and implications for promoting green and low-carbon development in urban and rural areas and for the early achievement of the strategy in China.

The inverted U-shaped relationship between weight loss percentage and cardiovascular health scores

PurposeObesity is a significant risk factor for cardiovascular disease; however, the impact of weight loss on cardiovascular health (CVH) in individuals with specific obesity patterns remains incompletely understood. The objective of our study was to investigate the relationship weight loss percentage and CVH scores across individuals with various obesity patterns.MethodsOur study utilized data from the National Health and Nutrition Examination Survey conducted between 2007 and 2018, involving a total of 12,835 participants aged 16 years or older, to conduct a cross-sectional analysis. Multiple linear regression and multinomial logistic regression methods were used to assess the correlation between the weight loss percentage and the CVH scores. Additionally, restricted cubic spline analysis was employed to examine the nonlinear relationship between the two variables.ResultsCompared to individuals with a weight loss percentage < 0%, participants with weight loss percentages of 0–5% and 5.1–10% showed improved CVH scores, with β values of 2.85 (95% CI 2.32–3.38) and 2.55 (95% CI 1.69–3.4), respectively. Regarding different obesity patterns, compared to participants with a weight loss percentage < 0%, participants with a weight loss percentage of 0–5% showed an increase in CVH scores in the normal weight and overweight/general obesity (OGO) groups, with β values of 1.45 (95% CI 0.7–2.19) and 1.22 (95% CI 0.46–1.97), respectively. Restricted cubic spline analysis revealed a significant inverted U-shaped relationship between the weight loss percentage and the CVH scores (with optimal CVH scores at 3%).ConclusionsThere was an inverted U-shaped relationship between weight loss percentage and CVH scores, with moderate weight loss (0–10%, optimal value of 3%) being associated with improved CVH scores, especially among individuals with OGO.Level VOpinions of respected authorities, based on descriptive studies, narrative reviews, clinical experience, or reports of expert committees.