Labor Input Research Articles

Amounts of Unutilized Forest Biomass Resources Under Sustainable Forest Management, Limited by Labor–Input Constraints

In anticipation of the utilization of logging residues and small-diameter trees after the completion of the Feed-in Tariff Scheme for Renewable Energy (FIT) in Japan, this study (i) calculated the available amount of unutilized forest biomass resources over a long term by using the developed »regional forestry operations management model« and (ii) estimated the period and the ratio of the generation of small-diameter trees during cleaning and pre-commercial thinning operations to the whole biomass resources. These analyses revealed that in the first 60 years, the clearcut and reforestation of 763 ha of planted forests (average age 66 years) with the labor input of approx. 2000 man-days per year were promoted, and thus 71% of the whole area was returned to the regular harvesting cycle. During that period, the average amounts of log production and biomass generation were 7184 m3/y and 875.6 Mg/y on a dry-weight basis, respectively. During the next 60 years, when the clearcut of older, high–accumulation forests and the subsequent reforestation were stabilized, the average amounts of log production and biomass generation under sustainable forest management were 5239 m3/y and 774.8 Mg/y on a dry–weight basis, respectively, exhibiting lower amounts than those of the first 60 years. Small-diameter trees were generated by cleaning and pre-commercial thinning operations stably from 16 years after the beginning of clearcut and reforestation. Especially after 61 years, the average annual amount of small-diameter trees generation accounted for around 10% of that of the whole biomass resources and more than 50% of that of unutilized thinnings.

Optimizing Labor Intensity Improves Economic and Environmental Performances in Pu’er Tea Plantations in China

China stands as the world’s largest producer of both conventional and organic tea. However, the economic and environmental performances of labor input intensity on tea cultivation processes remain understudied at present. For Chinese tea varieties, highly specific distribution of major producing regions always led to variations of tea production under conventional management (CM) and organic management (OM) conditions. Therefore, this study focused on the production of Pu’er tea and thus chose the Yunnan province as the study region, which is the largest Pu’er tea-growing province in China. The study compared the economic and environmental performances between organic and conventional Pu’er tea plantations under different labor intensities by a joint analysis based on economic analysis, emergy evaluation, and environmental footprints. The findings revealed that compared with CM, OM reduced costs by 9.06% ( P < 0.05) and enhanced the ratio of income to cost by 33.00% ( P < 0.05). The emergy sustainability index (ESI) of OM was 33.58% ( P < 0.05) higher than that of CM. The environmental footprint index (EFI) per unit area and per unit economic output for OM decreased by 17.31% ( P < 0.05) and 37.77% ( P < 0.05), respectively, compared to CM. The CM and OM had better economic and ecological benefits when the labor input intensity was 3 to 6 and 8 to 10 persons/hm 2 , respectively. This study provided a novel perspective on understanding the interaction between labor allocation and green income growth in tea production. The findings of this study offered solid scientific evidence and decision support for the green transformation of Chinese tea industry.

КОНЦЕПТУАЛЬНІ ЗАСАДИ КАТЕГОРІЇ «ПЕРСОНАЛ» У КОНТЕКСТІ ЦИФРОВІЗАЦІЇ ТА СОЦІАЛЬНО ВІДПОВІДАЛЬНОГО МЕНЕДЖМЕНТУ

Amid growing organizational complexity, digital transformation, and increasing emphasis on socially responsible governance, the category of “personnel” is undergoing significant theoretical reevaluation. The article explores the conceptual evolution of this term, arguing for a reconceptualization grounded in interdisciplinary perspectives. While traditionally defined through quantitative or functional frameworks, “personnel” today must also be understood as a complex socio-economic and psychological construct that integrates individual traits, motivation, emotional intelligence, communication skills, and adaptability. These personal dimensions are critical not only for effective organizational functioning but also for ensuring long-term sustainability and resilience. The study investigates how the interaction between economic theory, labor sociology, and organizational behavior shapes the modern understanding of personnel. It systematizes existing definitions and approaches, including legal, administrative, and socio-psychological perspectives, each highlighting specific aspects such as contractual status, role flexibility, or interpersonal dynamics. The paper emphasizes the growing relevance of human-centered strategies in HR management, driven by the expanding role of artificial intelligence, platform-based employment, and analytics-based decision-making. Personnel is thus positioned as a hybrid resource – both human and digital – whose value extends beyond labor input to include creativity, ethical conduct, and the capacity for continuous learning. The article contributes to contemporary academic discourse by positioning “personnel” as a multidimensional concept that reflects the complex interplay between human capacities and digital systems, relevant for scholars, HR practitioners, and policymakers seeking sustainable workforce strategies in conditions of uncertainty and innovation. By analyzing current trends in human capital theory and digital workforce integration, the article demonstrates the necessity of redefining personnel as a dynamic organizational asset. This reconceptualization allows HR professionals, researchers, and policymakers to develop more adaptive, inclusive, and strategically aligned approaches to personnel development, especially in the context of agrarian and industrial sectors facing accelerated transformation.

StructLayoutFormer: Conditional Structured Layout Generation via Structure Serialization and Disentanglement.

Structured layouts are preferable in many 2D visual contents (e.g., GUIs, webpages) since the structural information allows convenient layout editing. Computational frameworks can help create structured layouts but require heavy labor input. Existing data-driven approaches are effective in automatically generating fixed layouts but fail to produce layout structures. We present StructLayoutFormer, a novel Transformer-based approach for conditional structured layout generation. We use a structure serialization scheme to represent structured layouts as sequences. To better control the structures of generated layouts, we disentangle the structural information from the element placements. Our approach is the first data-driven approach that achieves conditional structured layout generation and produces realistic layout structures explicitly. We compare our approach with existing data-driven layout generation approaches by including post-processing for structure extraction. Extensive experiments have shown that our approach exceeds these baselines in conditional structured layout generation. We also demonstrate that our approach is effective in extracting and transferring layout structures. We will release the code upon the acceptance of this paper.

Assessing the Constraints of COVID-19 Pandemic on Vegetable Growers: A Comprehensive Analysis

The onset of the COVID-19 pandemic raised major concerns for the agricultural sector, particularly for vegetable growers who are highly vulnerable due to the perishable nature of vegetables and reliance on labour-intensive operations that rely mainly on labour-driven operational practices. The research aims to provide a comprehensive analysis of the constraints vegetable growers face due to the COVID-19 Pandemic. Using an ex-post facto research design, we analysed the cause-and-effect relationship between variables among 240 vegetable growers from two districts and eight villages in Odisha, India. The findings reveal that fear of COVID-19 infection with an average garret score of 73.11 is impacting their willingness to work and interact, Restrictions on movement and social gatherings due to lockdown with an average garret score of 72.91 hindered farming operations, high cost of labour and agricultural inputs with an average garret score of 72.02 driven by reduced availability and increased demand, shortage of labour with an average garret score of 71.02, inadequate knowledge and awareness on COVID-19 pandemic with an average garret score of 70.25 and lack of transportation facilities due to mobility restrictions with an average Garrett score of 72.07 are some of the critical constraints faced by vegetable growers. The research findings have several implications for policy or practice to mitigate future disruptions and enhance the resilience of the agricultural sector.

Wages and return to capital in Thailand in a free trade agreement with the EU

Thailand and the EU started negotiating a free trade agreement (FTA) in 2005, but negotiations were subsequently suspended in 2014 after the country’s military coup. The significance of these negotiations are important because of the mutual benefit of achieving higher levels of trade and investment between the world’s largest single market and the second largest ASEAN economy. The Specific Factors (SF) model of production and trade is applied to identify potential winner and loser industries and factors of production in Thailand. The model identifies short-run loses for some labor inputs, return to capital, and output in agriculture and services. In the manufacturing and energy sectors, higher output will benefit some labor inputs and capital owners. Understanding the short-run impact of an FTA could allow policymakers in Thailand to reinforce the institutional infrastructure such as implementing trade adjustment assistance programs (TAA), to help re-train workers who may become unemployed due to free trade.

The Use of Agricultural Services in European Union Regions Differing in Selected Agricultural Characteristics

Agricultural services, understood as the rental of machinery and equipment with appropriate labor, are one of the three types of production services in agriculture distinguished by European Union legislation. The aim of this paper is to identify clusters of regions in the European Union that differ in the level of use of agricultural services on farms and in selected characteristics related to production potential, labor input, and type of agricultural production. For this purpose, Ward’s method, from the group of hierarchical agglomerative cluster analysis methods, was used. Based on data on farms using agricultural services in 124 regions of the European Union, six clusters were formed. The study showed that agricultural services substitute for labor inputs in intensive agricultural production conditions, but in a situation with good technical equipment, farms may more often choose to employ hired workers. Such substitution does not occur in regions that are moderately and less well-equipped with machinery and equipment, because hired labor cannot completely replace the scarcity of machinery. The level of use of agricultural services is also related to the profile of the production carried out and the area of agricultural land, followed by the resources of land, capital, and labor. The level of economic development and historical background are also important.

Total factor productivity growth decomposition and its determinants in Ethiopian manufacturing sector

The objective of this study is to examine the performance of the manufacturing firms in terms of productivity growth by accounting for the determining factors. The findings revealed that growth in TFP has an average rate of 4.87% per year and showed significant improvement over the three policy periods (1996–2003, 2004–2010, and 2011–2015), respectively 3.6%, 4.7%, and 6.5%. Total factor productivity has been decomposed into contributing sources of technical progress (1%), scale change (− 0.14%), and technical efficiency change (4.01%). Twelve factors are identified from the literature as determinants of TFP growth. Eight of them are found to statistically affect this growth. The periods from 2004 to 2010 (high economic growth period) and from 2011 to 2015 (GTP I) have a higher TFP growth rate relative to the base period (1996–2003) and similar private ownership. In addition, labor input growth, capital intensity, and growth in average wage contributed positively to TFP growth. Importers of raw material inputs have higher TFP growth rates compared with non-importers. Tone can conclude from this finding that Ethiopian large and medium-scale manufacturing firms are low in terms of TFP growth. There are factors that enhance productivity, and there are also others that hinder improvements. Thus, strategically designed, coordinated with the firms themselves, and focused interventions are required in order to raise the real sales and value added using the existing state-of-the art technology and input combination, along with advancing the technical know-how, improving labor quality, updating, and renovating the capital input.

Study on regional differences and causes of emergency logistics responsiveness under the impact of public emergencies-findings from Chinese samples.

In recent years, the frequency and intensity of natural disasters and public emergencies around the world have been steadily increasing. Emergency logistics plays an irreplaceable role in providing rapid material and service support in the aftermath of disasters. Therefore, systematically analyzing the differences in emergency logistics responsiveness across various regions of China and understanding their underlying causes are of great significance for optimizing emergency logistics systems and improving disaster responsiveness. In order to identify the regional differences and causes of China's emergency logistics responsiveness under the impact of public emergencies, this paper pioneered the development of an index system for evaluating emergency logistics responsiveness. Based on the panel data of 30 provinces in China from 2012 to 2021, this paper used the entropy-weighted TOPSIS method to quantify the emergency logistics responsiveness of various regions in China. In addition, this study uses a panel quantile regression model to evaluate the differences in emergency logistics responsiveness in various regions of China under the impact of public emergencies, and the causes of regional differences are explored. The research results show that: (1) China's emergency logistics responsiveness is upward, but the regional differences are expanding. (2) Compared with the central and eastern regions, the western region's emergency logistics responsiveness has continuously improved due to the expanding scale of public emergencies. However, the emergency logistics responsiveness of the eastern region has constantly been reduced due to the impact of public emergencies. In contrast, the central region has been reduced first and then improved. (3) The level of emergency logistics technology cannot effectively promote emergency logistics responsiveness. Under the impact of public emergencies, the labor input of the logistics industry cannot effectively meet the needs of emergency logistics activities. The administrative command method and the level of marketization inhibit emergency logistics responsiveness. The improvement of the social labor input level, urbanization level, logistics development level, and digitalization level can effectively promote emergency logistics responsiveness. The above results show that China should pay attention to regional differences. Each region should rely on the existing logistics system and plan and build emergency logistics hubs according to the characteristics of emergencies in each region. Continue to strengthen regional exchanges and cooperation to narrow the gap in regional emergency logistics responsiveness. At the same time, this paper plays a driving role in China's joint emergency logistics rescue cooperation with other countries worldwide.

Economic and environmental factors determining spatial variation in soil liming in Poland

The aim of this research was to identify the key factors determining the level of soil liming in Poland. Spatial analyses were conducted using data from the 2020 National Agricultural Census. The study presents regional variations in selected parameters that characterise agricultural production quality and structural features, including the market connections of farms. The Classification and Regression Trees (C&RT) method was employed to identify the factors that most significantly influence the intensity of liming in the examined districts. These factors include the share of permanent grasslands, labour inputs, the percentage of farms engaged in commercial production, farm size, and the level of mineral fertilisation (NPK). The results indicate that regions with larger farms and higher NPK fertilisation tend to apply more lime. In contrast, areas with a higher share of permanent grasslands and labour-intensive activities show lower levels of liming. These findings suggest that improving agricultural practices, particularly in regions with small farms and limited fertilisation, could enhance soil liming efforts and align them with the European Green Deal's goals for sustainable agriculture.

The Impact of Typhoons on Agricultural Productivity—Evidence from Coastal Regions of China

The impact of natural disasters on agricultural production has garnered global attention. This study takes typhoons as an example, employing their movement paths to construct a difference-in-differences (DID) model and combining survey data from Rural Fixed Observation Spots to estimate changes in agricultural productivity from coastal regions of China, including Guangdong, Fujian, and Zhejiang provinces. This study finds that typhoons significantly deteriorate local agricultural productivity. Specifically, the planting income per mu and planting income per capita of rural households have decreased by 11% and 14%, respectively, while agricultural total factor productivity (TFP) has dropped by 3.7%. The decline in productivity can be attributed to two channels. Firstly, typhoons directly damage crops, leading to reduced total output. Secondly, in anticipation of typhoons, rural households increase asset input but reduce labor input and intermediate goods, resulting in the misallocation of agricultural inputs, which further diminishes productivity. The cost-benefit analysis indicates that to compensate for 20% of the negative impact of typhoons on agricultural productivity, local financial funds ranging from 3.4 million to 20 million yuan are required. Therefore, it is imperative for the Chinese government to strengthen the natural disaster warning system and improve farmland water conservancy infrastructure to mitigate the misallocation of agricultural inputs by rural households.

New Quality Productive Forces to Promote the Transformation and Upgrading of Guangdong Manufacturing Industry: Logical Mechanism, Realistic Dilemma and Development Strategy

New quality productive forces, as a driving force for high-quality development, has emerged as a new impetus for the transformation and upgrading of China's manufacturing sector. To facilitate the development of new quality productive forces, it is essential to achieve a qualitative leap in the three key elements: laborers, means of production, and objects of labor. The new quality productive forces are characterized by high technology, high efficiency, and high quality. The logical mechanism through which new quality productive forces facilitate the transformation and upgrading of the manufacturing industry encompasses three dimensions: enhancing the production quality and efficiency by elevating the skills and competencies of workers, advancing the modernization of labor tools to boost the adaptability of labor outputs, and diversifying labor inputs to strengthen the overall comprehensive capabilities of the manufacturing sector. However, at present, in the process of modernizing the manufacturing structure in Guangdong, it faces the dual challenges of pronounced primary characteristics and inadequate optimization momentum. Additionally, the modernization of Guangdong's manufacturing layout is hampered by insufficient synergy and integration. There is an urgent need to optimize and upgrade through new quality productive forces, optimize the manufacturing structure through a concurrent development strategy that integrates talent reserves and capital strength; Enhance the layout of the manufacturing industry through a systematic and collaborative strategy that emphasizes both key breakthroughs and comprehensive progress; Establish a manufacturing circulation model by coordinating domestic and international circulation strategies.

Can Internet Use Increase Rural Women’s Income? Evidence from Underdeveloped Areas of China

Although the widespread use of the Internet in rural areas provides new opportunities for economic growth, whether and how rural women benefit from it remains a question. Guided by Sustainable Development Goal (SDG) 5 and its targets, this study examines the impact of Internet use on rural women’s income by using survey data from 1384 rural households in underdeveloped areas of China. The results indicate that Internet use can significantly increase rural women’s income in underdeveloped areas. Additionally, the income effects of Internet use are heterogeneous across the different purposes of Internet use, income levels, individual characteristics, and family characteristics. Further analysis reveals that increasing labor input and enhancing capital endowment are two important channels through which Internet use increases rural women’s income. The results offer further empirical support for policymakers to utilize the Internet to increase rural women’s income and contribute to poverty alleviation in underdeveloped areas.

Improving mechanization conditions or encouraging non-grain crop production? Strategies for mitigating farmland abandonment in China’s mountainous areas

Improving mechanization conditions or encouraging non-grain crop production? Strategies for mitigating farmland abandonment in China’s mountainous areas

Impact of the Sloping Land Conversion Program on Rural Household Income in China

As the largest Payment for Environmental Services (PESs) program in China, the Sloping Land Conversion Program (SLCP) has exerted a profound impact on both the ecosystems and rural households’ livelihoods. However, the direct impact and indirect impact mechanism of the SLCP on income remain poorly understood. To bridge this research gap, a unique dataset was used in this study, comprising more than 1200 sampled rural households from 1995 to 2016. An estimation was conducted regarding the direct impact of the SLCP and its subsidy changes in different implementation stages on rural household income, as well as the indirect impact mechanism of the SLCP on income. Our results provided twofold findings. First, participation in the first round of the SLCP increased rural household’s income by 4.63% compared with non-participation. However, in the transition period, the SLCP had no significant effect on the total income of rural households. In the subsidy extension and subsidy expiration stages, participation in the SLCP increased rural household total income by 12.53% and 11.77%, respectively. Second, the variables, including farmland area, forestland area, land-based production expenditure, land-based labor input, and off-farm labor input, had significant mediation effects on the impact of the SLCP on rural household income. To improve the implementation of the SLCP, policymakers could pay attention to more integrative approaches, such as forestland transfer, reduction in forestland fragmentation, and promotion of off-farm job opportunities.

The Contribution of Total Factor Productivity on Economic Growth in Selected Southeastern European Countries

This paper delves into the impact of capital accumulation, effective employment, and total factor productivity (TFP) on the economic growth of five Southeastern European countries: Albania, Croatia, North Macedonia, Serbia, and Slovenia. The examination is based on the Solow-Swan neoclassical growth model and the Cobb-Douglas production function, which dissects economic growth into capital, labour, and productivity inputs. The analysis pays particular attention to the growth dynamics of North Macedonia over the entire period (1998-2019) and two sub-periods (1998-2008 and 2009-2019). The article seeks to provide a comprehensive evaluation of the primary drivers of economic growth in Southeastern European countries, emphasising the evolving roles of capital, labour, and productivity over time. Through a detailed analysis of these determinants, the study offers insights into the necessary policy actions to ensure sustainable long-term growth, especially in transition economies. The empirical analysis utilises the growth accounting framework and employs regression analysis to estimate the output elasticities of capital and labour inputs. The data analysis covers the period of 1998-2019, specifically focusing on two sub-periods to investigate shifts in growth drivers over time. Each factor's contributions are presented in absolute terms (percentage points) and relative terms (percentages) to provide a comprehensive understanding of their roles. The findings indicate that capital accumulation has been the predominant growth driver in most countries, especially Albania, Croatia, and North Macedonia. However, in Serbia and Slovenia, total factor productivity (TFP) played a more significant role, contributing substantially to growth. In North Macedonia, TFP showed strong contributions during 1998-2008 but declined sharply in 2009-2019, leading to increasing reliance on capital and labour inputs for growth. This study is valuable in emphasising the shift in growth drivers over time and highlighting the importance for Southeastern European countries to concentrate on productivity enhancements, innovation, and labour market reforms to sustain long-term growth. These findings provide significant insights for policymakers seeking to improve economic performance in transition economies.

Factor productivity impacts of climate change and estimating the technical efficiency of cereal crop yields: Evidence from sub-Saharan African countries.

The world aims to ensure environmental sustainability and consolidate agricultural factor productivity, yet the excruciating impact of climate change coincides and remains a persistent threat. Therefore, the study aims to estimate the technical efficiency of cereal crop yields and investigate the impacts of climate change on agricultural factor productivity. For this purpose, panel data from 35 sub-Saharan African countries between 2005 and 2020 was employed. For analysis, the pooled OLS and stochastic frontier models were employed. The results revealed that in the region, the average efficiency score for producing cereal crops between 2005 and 2020 was 83%. The stochastic frontier model results showed that labour contributed 51.5% and fertilizer contributed 5.7% to raising the technical efficiency of cereal crop yields, whereas arable land per hectare reduced the technical efficiency of cereal yields by 44.7%. The pooled OLS regression result showed that climate change proxies (CO2 and methane emissions) diminish land, labour, and fertilizers productivity at a 1% significance level, whereas GDP per capita boosts significantly the total factor productivity in agriculture. This confirmed how climate change reduced land, labour, and fertilizer input productivity. The results concluded that the region had a high level of technical efficiency; of which labour and fertilizer inputs contributed the largest share; however, their productivity has dwindled due to climate change. To increase cereal crop yield efficiency and limit the adverse effects of climate change on agricultural input productivity, the region should combine skilled and trained labour and fertilizer with sophisticated agriculture technologies, as well as adopt climate resistance technologies (weather- resistant variety seed and planting revolution mechanisms).

Slow-Release Nitrogen Fertilizer Promotes the Bacterial Diversity to Drive Soil Multifunctionality

The application of slow-release nitrogen fertilizer not only economizes labor input, but also decreases the frequency of use of mechanical intakes, with significant implications in advancing modern intensive agricultural production. Whether slow-release nitrogen fertilizer application can influence the association between microbial diversity and soil multifunctionality remains controversial. This study analyzed the spatial variances of soil environmental factors, soil multifunctionality, and their correlations with bacterial and fungal communities under five nitrogen application rates. The key factors influencing the dominant microbial species and community structures at different spatial locations were determined by the slow-release nitrogen fertilizer application rate, and the driving factors and dominant species of soil multifunctionality were identified. In contrast to the control group, moderate slow-release nitrogen fertilizer application enhanced soil multifunctionality and ameliorated the resilience of microbial diversity loss at diverse spatial locations resulting from irrational nitrogen fertilizer application. The resilience of the fungal community to disturbances caused by fertilization was lower than that of the bacterial community. Bacterial diversity exhibited a significant correlation with soil multifunctionality, and the soil multifunctionality intensity under 240 kg ha−1 treatment increased by 159.01% compared to the CK. The main dominant bacterial communities and the dominant fungal community Ascomycota affected soil multifunctionality through slow-release nitrogen fertilizer application. Structural equation modeling and random forest analysis demonstrated that bacterial community diversity, particularly in bulk soil and the rhizosphere, community composition, and soil nitrogen form are the primary driving factors of soil multifunctionality. Results indicated that the microbial niche alterations induced by slow-release nitrogen fertilizer application positively affect soil multifunctionality.

Effects of Smart Farming on the Productivity of Korean Dairy Farms: A Case Study of Robotic Milking Systems

The Korean agricultural sector faces increasing challenges such as an aging population, labor shortages, and the liberalization of agricultural markets. To overcome these challenges, the Korean government has striven to enhance the competitiveness of agriculture by introducing AI-based technologies to the agricultural sector, labeling this as smart farming. This study estimates farm-level benefits of adopting smart farming technologies, robotic milking systems, in Korean dairy farms. The benefits are estimated by comparing the productivity (i.e., the savings of labor input, increased calf production, and increased milk production) of adopting and non-adopting farms. Our study uses the propensity score matching method to address potential problems from confounding factors, sample selection bias, and the small number of adopters. Our results show that farms that adopted robotic milking systems produced 0.10 to 0.11 more calves per year than farms that did not adopt the system. The adopters also increased milk production by 2.44 kg to 2.88 kg per head/day, while reducing labor input by 0.15 to 0.30 per head/week. However, the reduced labor input was not statistically significant. When the analysis was extended to regard the farm characteristics, the labor input became significant from small and family-run farms. We also found that the increase in the number of calves produced per head was statically significant from small farms, family-run farms, and farms with successors. The increased milk production per head was statistically significant from large farms, farms employing hired workers, and farms with successors. Our findings suggest that the Korean government continue promoting smart farming technologies such as the robotic milking system to increase the adoption rate. The findings can also provide useful information about target markets of this technology, which can be used to increase the adoption rate and ultimately enhance the sustainability and competitiveness of the Korean dairy industry.

The Impact of Weather on Economic Growth: County-Level Evidence from China

While the impact of long-term climate change on economic systems has received substantial attention, the influence of short-term weather variations on economic growth has been comparatively neglected. This study utilizes county-level panel data from 2001 to 2020 to investigate the impact of weather on regional economic growth in China. The findings indicate that average temperature significantly reduces economic growth, whereas average precipitation does not have a significant overall effect. Notably, the adverse impact of temperature on economic growth is nonlinear and is exacerbated at higher temperatures, particularly in wealthier counties. The channel analysis shows that weather influences regional economic growth by affecting sectoral economies, factor inputs and economic productivity. While the primary industry’s overall growth rate remains unaffected by weather, sub-sectors such as grain production and animal husbandry are impacted. The secondary industry, especially large-scale industrial enterprises, is adversely affected by both temperature and precipitation. Conversely, higher average temperatures positively correlate with growth in the tertiary sector, promoting retail sales of consumer goods. The study also finds limited evidence for weather’s impact on investment growth, primarily in real estate development, and no significant effect on labor input growth. Additionally, weather conditions, particularly temperature, negatively affect total factor productivity, labor productivity and capital productivity, with precipitation adversely impacting capital productivity alone. These findings underscore the importance of tailored strategies to mitigate the negative effects of adverse weather conditions on sustaining sustainable regional economic growth.