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In the context of the ongoing process of high-quality development in the new era, which is focused on improving total factor productivity, it is of great importance to explore the spatial and temporal variations of total factor productivity growth and its driving factors in China's county regions' grain cultivation industry. This paper employs a three-stage DEA-Malmquist productivity method, the Gini coefficient method, and a panel fixed-effects model to analyze data from Chinese counties between 2009 and 2019. The analysis indicates that the growth of county food total factor productivity (FTFP) exhibits a fluctuating upward trend during the examination period, with an average annual growth rate of 2.43%. This is primarily driven by technological progress, yet the core driving role of technological efficiency is not effectively played. The average annual growth rate of county FTFP varies across different regions. The highest average annual growth rate of county FTFP in the eastern region and the primary grain-producing area is 2.75 and 3.04%, respectively. The lowest growth rates were observed in the western region and the main grain marketing area, at 1.44 and 1.23%, respectively. Secondly, the Gini coefficient of county FTFP continues to demonstrate a persistent upward trend during the examination period, with an average annual growth rate of 14.729%. The primary factor contributing to the observed variation in total factor productivity growth of the food sector at the regional level is the existence of disparate technological progress. Thirdly, there is a notable positive correlation between county financial deepening and financial self-sufficiency rates and county FTFP growth, with impact coefficients of 0.0503 and 0.0924, respectively. Conversely, county population density, degree of economic development, farmers' income level, and industrial structure exert a significant negative influence on county FTFP growth and technological progress. [ABSTRACT FROM AUTHOR]

• Robot adoption led to a 10 % increase in productivity within China's manufacturing firms. • The impact was more pronounced in the first two years following adoption. • The impact was likely to be greater for small-size firms. • Multi-functional robots had more pronounced effects than single-functional ones. • Industry-city robot exposure had positive spillover effects on non-adopting firms. This study investigates the effect of industrial robots on firm productivity in China. Employing propensity score matching (PSM) and staggered difference-in-difference (SDID) estimations, we find a statistically significant and positive casual effect of robot adoption on firm productivity at the 1 % significance level, leading to an approximate 10 % increase in total factor productivity (TFP) among manufacturing firms in China. The effect was most pronounced in the first two years following adoption but lost statistical significance from the third year onward. Additionally, we find that robot exposure, measured by both adoption rate and adoption intensity, had positive and statistically significant spillover effects on large-scale non-adopting firms within the same industry and city, leading to significant improvements in their TFP. Furthermore, the effect of robot adoption on firm productivity varied by robot type, firm size, and industry. Multi-functional robots (MFRs) exhibited a more substantial effect compared to singlefunctional robots (SFRs). The automotive, plastic/chemical, and metal industries had great productivity gains compared to other industries. These results withstand various rigorous robustness checks, reaffirming the validity and consistency of our findings. [ABSTRACT FROM AUTHOR]

The study re-examines convergence among Indian states by estimating their total factor productivity (TFP) for the period 1990/91–2018/19. The novelty of the study is the decomposition of TFP change into efficiency change and technological change using the Malmquist index in a spatial dependence framework to test convergence. Findings reveal that, on average, productivity increased at an aggregate level for the entire period on account of the impressive growth of technological innovation. However, technological growth convergence could not lead to productivity growth convergence in the second sub-period because of no convergence in efficiency growth. Alongside, while we witness significant spatial spillovers in both technology and efficiency, convergence was observed only with respect to technology growth in the second sub-period. The congruence of technological convergence and significant spatial spillovers indicates that while states may be converging in technology, they do not do so independently but display movements similar to their regional neighbours. [ABSTRACT FROM AUTHOR]

Industrial convergence refers to the dynamic process in which different industries gradually form new industries through mutual penetration and cross. As an advanced form of industrial synergy, industrial convergence is crucial in building a modern economic system. Using a panel data set covering China's 30 provinces during 2006–2018, this study explores the impact of industrial convergence on regional high-quality development. The findings suggest that: (1) Industrial convergence is conducive to high-quality development, and this conclusion remains robust after a series of tests. (2) For heterogeneity, the positive impact of industrial convergence on high-quality development is greater in regions with optimized energy structure and high investment outward, as does the regions with reasonable financial structure and moderate economic agglomeration. (3) Productivity improvement and industrial upgrading are the mediating paths by which industrial convergence promotes high-quality development, and the former plays a greater role. [ABSTRACT FROM AUTHOR]

The Western Taiwan Strait (WTS) Economic Zone connects the Yangtze River Delta and the Pearl River Delta, playing a significant role in China's coastal economy and forming part of the East Asian economic structure. This study used panel data from 20 cities in the WTS Economic Zone, spanning 2011 to 2020, to investigate urban land use efficiency and its dynamic evolution characteristics. The study used a super-efficiency EBM model, which accounts for undesirable outputs, combined with kernel density estimation and Malmquist–Luenberger (ML) index analysis, to thoroughly examine the changes in total factor productivity (TFP) of urban land use and the factors driving these changes within the WTS Economic Zone. The findings are as follows: (1) From 2011 to 2020, the overall trend of urban land use efficiency in the WTS Economic Zone was upward, with coastal areas generally exhibiting higher urban land use efficiency compared to inland areas. (2) The urban land use efficiency of cities in the WTS Economic Zone displayed four types of changes: rising, stable, "U"-shaped, and inverted "U"-shaped. (3) The TEP index of the WTS Economic Zone exhibited a right-leaning "M" trend. Technological change was the primary driver of enhanced urban land use efficiency, although there is still room for improvement in technical efficiency. Based on these findings, this study proposes policy insights to foster high-quality development of urban land use efficiency in the WTS Economic Zone. [ABSTRACT FROM AUTHOR]

The implementation of conservation tillage is crucial for the preservation and utilization of black soil. This study examined 297 new agricultural management entities in five pilot counties in the black soil region of northeast China. Using the SBM-Undesirable model, this study measured and evaluated the agricultural green total factor productivity (AGTFP) of these entities. We further employed the Tobit model to explore the impact of conservation tillage on the AGTFP. The findings revealed that the average AGTFP value of the sample entities was 0.4364, indicating a generally low degree of AGTFP that exhibited significant variation. Improvement in input indicators (such as machinery) and undesirable output indicators (such as net carbon emissions) was particularly needed. Additionally, conservation tillage had a significant positive impact on AGTFP, with a higher number of applied technologies correlating with increased productivity. Material subsidies for conservation tillage offered greater direct cost relief and had a stronger positive effect on AGTFP in comparison with cash subsidies. Furthermore, apart from policy factors, key production and operation characteristics—such as access to agricultural materials—also significantly influenced AGTFP. The results of this study offer a valuable decision-making framework and scientific reference for countries in black soil regions worldwide, enabling them to enhance the conservation and sustainable utilization of this vital resource. [ABSTRACT FROM AUTHOR]

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The "Symposium on Misallocation and Structural Transformation" focuses on the processes of resource allocation and structural change and their impact on economic growth and development. The symposium recognizes the importance of understanding the mechanisms and underlying forces that lead to resource misallocation and structural change, particularly in lower income countries. The articles in the symposium explore topics such as the effects of financial frictions on aggregate productivity, the growth miracle and slowdown in South Korea's manufacturing sector, the decline in business dynamism in China, and the role of family migration in structural transformation. These papers contribute to our understanding of resource allocation and structural change and provide insights into important factors affecting economic growth and development. [Extracted from the article]

We use the DID method to estimate whether the binding pollution control policy can achieve both "pollution reduction" and "efficiency enhancement" for industrial enterprises after implementing this command‐and‐control environmental regulation of the eleventh Five‐Year Plan in China. We also analyze its influence mechanism in detail. It has been shown that (1) Constrained by binding pollution control policies, enterprises could reduce their pollutant emissions but simultaneously suppress their total factor productivity (TFP), which indicates that command‐and‐control environmental regulations do not achieve both "pollution reduction" and "efficiency gains" for firms. (2) The mechanism analysis shows that under the constraint of the binding pollution control policy, enterprises increase the pollution treatment at the front end of production, such as investment in environmental protection facilities, and adjust the production schedule, such as pollution treatment at the end of production. These pollution treatment measures reduce pollutant emissions while bringing "compliance costs" to enterprises. However, the "innovation compensation effect" fails to compensate for the "compliance cost" brought by pollution control. (3) Further study finds that the binding pollution control policy effectively reduces the pollutant emissions of enterprises with low financing constraints. [ABSTRACT FROM AUTHOR]

Improving the efficiency of factor allocation in food production is the foundation for accelerating the formation of new quality productivity and achieving an agricultural green transformation. However, there has been no scholarly focus on their mechanisms and the interactions involved. This exploration is an important reference for enhancing the green production capacity of major grain-producing areas. In this study, 13 prefecture-level cities in Heilongjiang Province, China's largest grain production base, were selected as the research samples. A model for identifying factor misallocation and grain green total factor productivity (AGGTFP) was constructed to identify the spatiotemporal differences in factor misallocation and green total factor productivity. A fixed effects model was used to explore the impact of single-factor misallocation and the interaction of dual-factor misallocation with AGGTFP. The results show that from 2004 to 2022, the AGGTFP in 13 prefecture-level cities in Heilongjiang Province has shown a slow growth trend. The inhibitory effects of single-factor misallocation of land, labor, and capital on green total factor productivity are sequentially enhanced. The interaction effects of capital misallocation and labor misallocation and labor misallocation and land misallocation strengthen the inhibitory effects of misallocation on the AGGTFP. Therefore, it is necessary to further promote the optimization of production factors and improve the green production capacity for grain. [ABSTRACT FROM AUTHOR]

The integration of agriculture and tourism has emerged as a potential strategy to boost agricultural productivity and promote sustainable rural development in China. This study investigates the impact of agricultural tourism integration (ATI) on agricultural green total factor productivity (AGTFP) in China, filling a research gap in understanding the complex dynamic nexus. We examine the mediating role of the agricultural industrial structure adjustment index (AISAI) and the threshold effects of ATI and human capital level (HCL) using a panel dataset of 30 Chinese provinces from 2011 to 2021. The empirical results reveal three key findings: (1) ATI has a significant positive impact on AGTFP growth; (2) the AISAI partially mediates the relationship between ATI and AGTFP; and (3) ATI and HCL have a double-threshold effect and a single-threshold effect on the ATI-AGTFP nexus, respectively. These findings suggest that the effectiveness of ATI in promoting AGTFP varies across different stages of integration and levels of human capital development. The empirical results contribute to the literature on rural development strategies by providing an in-depth understanding of how ATI influences agricultural productivity and sustainability. Based on these findings, we propose targeted policy recommendations to optimize ATI strategies and invest in human capital to improve the resilience and sustainability of rural economies in China. [ABSTRACT FROM AUTHOR]

The impact of climate change on agricultural quality development under the constraint of China's "Double Carbon" target has been widely discussed by policy practitioners and academic theorists. This paper attempts to deconstruct the logic of how climate change affects agricultural total factor productivity (TFP) in three dimensions—the structure of agricultural input factors, the change in the cropping system, and the stability of crop supply. This paper also reveals the mechanism through which biased technological progress increases agricultural TFP by weakening the magnitude of climate change and empirically tests it by using China's provincial-level data from 2000 to 2021. This study showed that average annual temperature and annual precipitation had significant negative effects on agricultural TFP, that the number of sunshine hours had a significant positive effect on agricultural TFP, and that obvious regional differences existed in the effect of climate change on agricultural TFP. Further mechanism tests revealed that biased technological progress positively moderated the effect of climate change on agricultural TFP. Based on these findings, the appropriate countermeasures for improving climate early warning mechanisms, promoting the progress of appropriate technology, and fostering new agricultural management bodies. [ABSTRACT FROM AUTHOR]

The use of Information Communication Technology (ICT) forms a significant component of the Fourth Industrial Revolution (4IR). This study examined the impact of ICT on agricultural development in South Africa utilizing time series data from 1995 to 2022. Agricultural development was measured through agricultural output and agriculture total factor productivity as dependent variables. Traditional factors of production (land, labor, and capital) together with ICT variables (mobile cellphone subscriptions, Internet usage, and fixed telephone subscriptions) were used. Additional variables such as inflation, human development, access to energy and climate change were used. Data analysis was performed using the ARDL approach. The findings revealed that mobile phone subscriptions and Internet usage positively affect agricultural output and ATFP in the short and long run despite having a negative effect through the second lag in the short run. Fixed telephone subscriptions negatively affect ATFP in the long run while affecting output negatively in the short run through the first lag. Land, human development index, access to energy, and capital generally exhibited an increasing effect on both agricultural output and ATFP both in the short and long run through the various models estimated. Climate change and inflation were generally found to affect both agricultural output and ATFP negatively in the short and long run. The study concluded that ICT plays a significant role in promoting agricultural output and total factor productivity growth. Recommendations included that the South African government should promote the digitalization of the agriculture sector through the provision of ICT infrastructure that can be utilized by both smallholder farmers and large-scale agricultural producers. [ABSTRACT FROM AUTHOR]

The establishment of Green Finance Reform and Innovation Pilot Zones represents a novel endeavor aimed at paving a "bottom-up" pathway for the advancement of green finance and, consequently, holds immense significance in fostering economic growth that is environmentally sustainable. Drawing on data spanning the years 2013–2019 from 278 prefecture-level cities across China, we delve into the influence of the Green Finance Reform and Innovation Pilot policy on urban Green Total Factor Productivity. We found that: Firstly, the Green Finance Reform and Innovation Pilot policy has demonstrated a discernible enhancement in Green Total Factor Productivity within the designated pilot regions. Secondly, there is heterogeneity in the promotion effect of this pilot policy on Green Total Factor Productivity. As the geographical advantage and economic development level decrease, this promotional effect gradually diminishes. Thirdly, it is evident that the Green Finance Reform and Innovation Pilot policy primarily elevates Green Total Factor Productivity in the pilot regions by improving resource allocation efficiency, fostering innovation in green technologies, and facilitating the upgrading of industrial structures. This research not only underscores the efficacy of green finance in the context of economic transition but also provides empirical substantiation for the strategic utilization of pilot zones to propel nationwide initiatives aimed at sustainable green development. [ABSTRACT FROM AUTHOR]

We study the currency risk premium and the forward premium bias in a two‐country New Keynesian model with production, no physical capital, and recursive utility. Monetary policy follows an interest rate feedback rule and exogenous total factor productivity (TFP) growth follows a long‐run risk process with stochastic volatility, which we estimate from data. With cross‐country heterogeneity in TFP and monetary policy, reasonable currency risk premia emerge under complete and incomplete markets but the forward premium bias is trivial. We diagnose the challenge faced by this fairly standard production model to explain the forward premium bias. [ABSTRACT FROM AUTHOR]

Although the main reason governments offer subsidies is to guide production activities and enhance the competencies of individual firms, its economic effectiveness and influential mechanism remain unclear. In this study, based on dynamic capability perspective, we introduce knowledge flows (i.e. inflows and outflows) and examine their mediation roles in the relationship between government subsidies and total factor productivity (TFP) growth. Empirical analysis is conducted using panel data from 4,335 Chinese public listed firms during the period from 2007 to 2020. The regression results show that government subsidies have a positive influence on firms' TFP growth. Further analysis confirms that government subsidies can positively affect TFP growth by influencing both knowledge inflows and outflows. This paper enriches the current literature by involving dynamic capability theory, providing novel insights into the influential mechanisms of government subsidies. Additionally, we introduce TFP as a more comprehensive measurement to avoid bias resulting from a one-sided assessment of performance. This study also provides practical inspiration for firms to design appropriate knowledge management systems and leverage the effectiveness of government subsidies in terms of firm growth. [ABSTRACT FROM AUTHOR]

Total factor productivity in the green economy is a major step forward in fostering robust growth in the economy. Urban green total factor productivity (GTFP) may be increased and carbon emissions decreased through the low-carbon transformation of the transportation sector. To analyze how the pilot policy of low-carbon transportation system construction affects urban GTFP, this study builds a DID model and a spatial Durbin model using panel data from 282 Chinese cities between 2006 and 2021. The findings show that low-carbon transportation systems boost urban GTFP. In addition, the mechanism test shows that low-carbon transportation development increases urban GTFP by optimizing urban industrial structure, expediting economic agglomeration, and encouraging technological innovation. Lastly, the geographical correlation test shows that GTFP is geographically associated and that spatial spillover reduces the impact of low-carbon transportation growth on GTFP. The findings affirm the need to vigorously promote low-carbon transportation systems to aid in the achievement of the carbon neutrality target. [ABSTRACT FROM AUTHOR]

In the past, China divided its citizens into "agricultural hukou" and "non‐agricultural hukou" to limit rural–urban migration, which contributed to China's early industrialization. However, the binary household registration system no longer suits China's development, and cities in China have successively carried out hukou reforms. Based on the reforms that trigger rural–urban migration, we investigate the impact of low‐cost and low‐skilled migrant workers on firm‐level total factor productivity (TFP). We employ a staggered difference‐in‐differences (DID) strategy to show the following results: (1) The hukou reform substantially reduces the listed firms' TFP by 6.9%. (2) The hukou reform has increased the number of employees and the labor intensity, as well as reduced average employee salaries, employee responsibility, and R&D in enterprises, revealing the mechanism by which hukou reform affects firm productivity. (3) Our findings are particularly pronounced in non‐state‐owned enterprises (non‐SOEs), enterprises with more stringent financing constraints, and cities with wider rural–urban income gaps. [ABSTRACT FROM AUTHOR]

This paper examines the impact of manufacturing servitization, service trade openness, and their interaction on the total factor productivity (TFP) of the manufacturing industry. Using panel data covering 43 economies, the study finds that higher levels of manufacturing servitization and service trade openness lead to higher TFP in the manufacturing industry. In addition, the positive impact of manufacturing servitization on TFP is greater in economies with higher levels of service trade openness. The study also shows that trade creation and research and development innovation mediate the relationship between manufacturing servitization, service trade openness, and TFP. Finally, the paper finds that the positive impact of manufacturing servitization, service trade openness, and their interaction on TFP is greater in developing countries and in low‐ and high‐TFP manufacturing industries. This research contributes to understanding the intricate relationship between manufacturing servitization, service trade openness, and manufacturing TFP. [ABSTRACT FROM AUTHOR]

As conflicts between emissions reductions and economic growth intensify, an increasing number of countries and regions are focusing on green total factor productivity (GTFP). Financial agglomeration (QWS), resource endowment (SE), and innovation-driven (ID) are the main factors that cause regional differences in GTFP. However, few scholars have comprehensively considered the impact of the interaction between SE, ID, and QWS on GTFP. This article uses the Global Malmquist-Luenberger (GML) index to calculate the GTFP of 30 Chinese provinces from 2003 to 2020 and constructs a dynamic panel model to present the first comprehensive study of the interactions between SE, ID, and QWS and their relationship with GTFP. The conclusions are as follows. (1) SE is positively correlated with GTFP, which is different from the "resource curse" theory proposed by existing research. (2) There is a crowding-out effect between SE and ID, and their interaction will restrain the growth of GTFP. (3) QWS promotes ID, and the interaction between the two promotes the growth of GTFP. (4) There is a restraining effect between QWS and SE, and their interaction will hinder the growth of GTFP. (5) The key policy directions to improve China's GTFP are to undertake strategic planning from a comprehensive perspective, including encouraging innovation, guiding financial development reasonably, and avoiding excessive consumption of resources. [ABSTRACT FROM AUTHOR]

Under the double pressure of economic downturn and climate deterioration, the Chinese government needs to use the "double carbon" policy to drive the green transformation of the manufacturing industry. This article takes A-share manufacturing listed companies as the research object, constructs the enterprise digital economy investment index by text analysis and expert scoring method, and represents the degree of green transformation by enterprise green total factor productivity. At the theoretical level, the impact mechanism of the digital economy empowering green transformation in the manufacturing industry is hypothesized. The relevant hypotheses were tested through econometric empirical evidence, and the econometric model significantly passed the robustness test, proving that the digital economy empowers the development of green transformation in the manufacturing industry significantly. This article reveals that the digital economy promotes the green total factor productivity of enterprises by enhancing their innovation capability, improving the efficiency of production factor flow, and increasing their emission costs, but the factor intensity and the nature of enterprise owners will have different effects on the green transformation of the manufacturing industry enabled by the digital economy. This article explores the internal mechanism of green transformation development in the digital economy-enabled manufacturing industry and provides empirical evidence for enterprises to formulate development strategies and for governments to issue guiding policies. [ABSTRACT FROM AUTHOR]

Well-designed environmental regulations are a prerequisite for achieving green economic growth. However, the effectiveness of campaign-style environmental regulation—a widely used environmental management instrument in developing nations or even in some developed nations, on green economic growth remains under-researched and has not reached a consistent conclusion. This paper takes advantage of China's Central Environmental Protection Inspector policy—the strictest and largest campaign-style environmental regulation policy in China's history, as a natural experiment and uses the difference-in-differences method to explore the effect of campaign-style environmental regulation on green economic growth, and further analyze its underlying mechanisms and heterogeneity effects. The panel data covering 280 prefecture-level cities in China from 2009 to 2019 are used. Our results show that Central Environmental Protection Inspector can result in an average of 14.2% increase in green economic growth, and this effect is sustainable for a long time. Mechanism analysis shows that Central Environmental Protection Inspector boosts green economic growth mainly by promoting green innovation and optimizing industrial structure. Further heterogeneity analysis reveals that the positive effect of Central Environmental Protection Inspector on green economic growth is greater in eastern China and underdeveloped cities. [ABSTRACT FROM AUTHOR]

This paper studies how firms adapt to demand shocks when facing capacity constraints. I show that increases in government purchases raise total factor productivity in quantity units at the production line level. Productivity gains are concentrated in plants facing tighter capacity constraints, a phenomenon I call "learning by necessity." Evidence is based on newly digitized archival data on US World War II aircraft production. Shifts in demand across aircraft with different strategic roles provide an instrument for aircraft demand. I show that plants adapted to surging demand by improving production methods, outsourcing, and combating absenteeism, primarily when facing tighter capacity constraints. (JEL D22, D24, E62, L93, N12, N42, N62) [ABSTRACT FROM AUTHOR]

China's higher education system is shifting from quantitative expansion to connotative development to advance its quality. Since 2015, Chinese governments have been implementing a strategic policy for higher education called "double first-class", which aims to promote a number of Chinese top universities to construct world-class universities or to establish world-class disciplines. "Double first-class" universities have received a large amount of educational resources through this policy. Taking advantage of resources efficiently is an important element in promoting the development of higher quality higher education. However, research on resource allocation in China's "double first-class" universities is incomplete. Current research has not clarified the level of resource allocation efficiency or the factors affecting China's "double first-class" universities. With the help of the superefficient data envelopment analysis (DEA)-Malmquist–Tobit model, this study actively explores the current status of the resource allocation efficiency of China's "double first-class" universities to fill this gap in the field. Specifically, the development level and change trend of the resource allocation efficiency of 13 "double first-class" universities in China from 2015 to 2019 were measured with the help of the superefficient DEA-Malmquist model. The internal and external factors affecting the resource allocation efficiency of "double first-class" universities are also analysed with the help of the Tobit model. The overall level of resource allocation efficiency of "double first-class" universities is high, but the internal variability is large. From the perspective of efficiency decomposition, it is found that both technical efficiency change (EFch) and technical progress efficiency (TEch) play important roles in improving the total factor productivity (TFP) of resource allocation. Compared with TEch, EFch plays a more significant pulling role. This study confirms that the factors affecting resource allocation efficiency are complex. Among them, the regional economic environment, faculty title structure, and degree of international exchange have significant roles in promoting the resource allocation efficiency of "double first-class" universities, but local financial support and the time of policy implementation have certain negative effects. [ABSTRACT FROM AUTHOR]

There is a growing emphasis on fostering green growth and lowering carbon emissions in order to achieve sustainable economic development. This study uses the Tapio decoupling model and analyzes the factors influencing changes in carbon emissions from manufacturing in India utilizing the log mean Divisia index (LMDI) techniques. Furthermore, the nexus between carbon emission intensity, information and communication technology (ICT), total factor productivity (TFP), skill, and energy intensity has been analyzed using the system-GMM approach. It is based on the plant-level Annual Survey of Industries (ASI) datasets for the organized manufacturing sector of India from 2001 to 2002 to 2019 2020 for the major 21 Indian states/UT. The findings reflect the presence of weak decoupling in the manufacturing sector both at the aggregate level and in states. This indicates that both output and emissions are increasing; however, output growth surpasses emission growth, which signifies an effort to transition towards more environmentally friendly production methods and enhanced energy efficiency. The output and population effect are found to be leading factors in carbon emissions, while energy intensity is found to be reducing the effect. Further, the system-GMM estimates show that ICT and energy intensity positively affect total factor productivity, while with an increase in carbon emission intensity, productivity declines. The study confirms the existence of an inverted N-shaped Kuznets curve in the sector. This present study will contribute to formulating energy and environmental strategies to reduce emissions and promote adopting cleaner energy sources. These efforts will facilitate the attainment of carbon neutrality and enhance energy efficiency within the sector. [ABSTRACT FROM AUTHOR]

In the digital era of governance, few studies have analysed the influence of digital government on micro economies. To fill this gap, we explore the nexus between digital government and firm total factor productivity (TFP), and uncover the potential transmission channels behind this connection by focusing on Chinese listed firms from 2010 to 2017 and utilizing panel regression with firm-, year-, and province-fixed effects. Our findings confirm that digital government has constructive effects on firm TFP. Furthermore, empirical results suggest that this favourable impact can be transmitted through three channels of firm transaction costs and innovation, digital infrastructure construction, and government-market relationships. Further analysis reveals that the beneficial effect of digital government on firms is more significant in provinces with low fiscal transparency and complex topography, indicating that digital government compensates for the disadvantages of low fiscal transparency and inconvenience of steep terrain. Based on these conclusions, we provide suggestions for government digitalization to improve the performance of government-microeconomic complementation. [ABSTRACT FROM AUTHOR]

India is often referred to as the next development superpower, and generally, becoming a large-scale industrialization center is seen as an achievable goal for the country. This article investigates the output elasticity, substitution elasticity, and technological advancement between the various factors (i.e., labor, capital, and energy use) in the industrial sector of India. To investigate the factor's productivity, a trans-log production function was applied; however, ridge regression was used to analyze the various parameters to check the multicollinearity issue. The results show that (1) the analyzed inputs are optimistic and return-to-scale averages of 1.18, 1.41, and 1.24 between labor, capital, and energy, respectively, are increasing; (2) the pairs substitution between labor--industrial energy utilization and capital--industrial energy consumption is found to be 0.96 and 0.98, respectively, on average, indicating that capital, labor, and energy are good substitutes that need more attention in the production process; and (3) the technological progress between factors ranges from -0.4 to 0.02, in which labor--energy and capital--energy utilizations provide quicker outcomes than a capital--labor utilization. Finally, the industrial sector can attain maximum productivity if capital and skilled labor are improved under the sustainable development goals, as energy and capital are optimized for maximum efficiency. Finally, energy substitution and low-carbon technological efforts can be better suited for attaining dual-carbon goals in the industrial sector. [ABSTRACT FROM AUTHOR]

While promoting manufacturing growth is imperative to boost economic growth, potential adverse consequences on natural resources and ecology have created sustainability-related concerns and challenges. In India, with the reform processes deepening further and the business environment becoming more market-oriented over the years, the adoption of appropriate measures for sustainable manufacturing growth under such conditions would require a deeper investigation of the underlying dynamics, particularly to address the impacts of external shocks. This is especially true when external shocks alter market dynamics and, hence, input is used significantly in the manufacturing sector. Given this backdrop, the present paper examines how the major external shocks to the Indian economy during in the post-reform era have altered the resource use patterns in selected manufacturing industries. The paper uses secondary data collected from the KLEMS database of the Reserve Bank of India for the period from 1980–81 to 2019–20 and applies descriptive statistics and econometric techniques to address the research objective. It is found that energy intensity, vertical integration, capital intensity, and rate of growth of total factor productivity decreased over the decades, whereas labour productivity experienced an increasing trend in most industries. However, the trends are mixed in the case of material intensity. Further, the regression results indicate significant effects of external shocks on resource use, factor productivity, and structural changes. There are also industry-specific differences in the nature and extent of such changes. Hence, a deeper investigation of the underlying factors and impacts at a disaggregate industry level is necessary to draw more robust insights. [ABSTRACT FROM AUTHOR]

It has become a new trend for the future development of Chinese agriculture to accelerate the transformation from increasing production to improving quality and realizing green growth. This paper uses the sequential DEA to measure the agricultural green total factor productivity (GTFP) of 306 Chinese cities from 1996 to 2017, then tests its convergence. The results show that the average growth rate of Chinese agricultural GTFP is 0.58%; the main driving force coming from technical progress. The convergence of agricultural GTFP has dual characteristics of stages and regions, and the significant σ convergence only exists in the central region during 1996–2003. There is significant β convergence at the national level, in the eastern and central regions, and neither convergence nor divergence in the western region. However, during 2004–2017, only the eastern region had β convergence. Finally, the conditional convergence speed is higher than the absolute convergence, and the eastern region is higher than the central. [ABSTRACT FROM AUTHOR]

In the study of urban development, it is very important to evaluate the influence of production factors reasonably and efficiently for the region to achieve efficient development. The principal aim of this investigation is to amalgamate the conventional measurement model characterized by robust interpretability with the non-parametric model characterized by limited interpretability, thereby enhancing the precision of research outcomes. Towards this objective, the study employs an optimized directional distance function integrated with a global Malmquist–Luenberger index to formulate a comprehensive total factor productivity measurement framework. In elucidating the homogeneous attributes of regions, departing from prior methodologies reliant on manual or direct algorithmic partitioning, this paper employs the K-means clustering algorithm for index discernment, abstracting the concept of K-means clustering centroids to encapsulate regional homogeneity, thereby delineating results through the visualization of regional development potential maps and the evolution of centroid-based clustering trend maps. The findings of the investigation illuminate common patterns of change across disparate regions, proposing a strategy for leveraging regional resource endowments towards a cohesive framework, thereby transcending constraints imposed by production efficiency limitations. Amidst the backdrop of the COVID-19 pandemic, this study draws upon provincial-level data spanning from 2000 to 2018 in China. The conclusive analytical outcomes underscore the pivotal role of energy factors in regional development efficiency, particularly within high-potential development regions, followed by the capital and labor factors. Concurrently, the study discerns a discernible hierarchical pattern among areas of development potential, which exhibits correlation with factor mobility dynamics. [ABSTRACT FROM AUTHOR]

This paper investigates the impact on polluting emissions as a result of manufacturing industries in China offering services as well as products. We merge detailed firm-level statistics covering 2000 to 2011, and use two-way linear fixed effects regression to control for firm and year heterogeneities and a host of control variables. The empirical results show that manufacturing servitization significantly reduces the emission intensity of firms. This effect is achieved by improving the total factor productivity of firms, optimizing the efficiency of energy use, and increasing the share of the highly-skilled labour force. Moreover, the emission reduction effect of manufacturing servitization is more profound in the eastern and central regions, pollution-intensive industries, non-state-owned firms, and processing trade firms. In addition, our extended analysis shows that the emission reduction effects of manufacturing servitization can be strengthened through trade liberalization and cohort study. The major policy implication is that governments should undertake industrial policies that reinforce the positive effects of manufacturing servitization in order to achieve win-win outcomes in manufacturing upgrading and environmental protection. [ABSTRACT FROM AUTHOR]

Labour productivity growth in the construction sector has been very weak in recent decades in most OECD countries. This paper addresses this issue based on a panel of 23 countries over the period 1995–2015. First, we use the Ackerberg, Caves, and Frazer (2015) method to propose a multifactor explanation for this lack of productivity growth: (i) average TFP growth is close to zero and even negative for most countries; (ii) average contributions to growth of capital and intermediate inputs are positive but weak, respectively of 0.05% and 0.90% per year, and much smaller than in the manufacturing sector over the same period (respectively of 0.40% and 3.10% per year). Then, we investigate whether reforms of regulations specific to the construction sector might boost productivity there. Using regulation indicators from the 'Doing Business Report', we find a negative impact of these regulations on TFP, but not on the intensities of capital and intermediate inputs. Our results suggest that reducing the construction sector regulations might bolster productivity: a switch to the lightest regulations would lead to a long-term TFP increase of 6% on average. [ABSTRACT FROM AUTHOR]

This study constructs an economic growth model that includes natural resource endowments to theoretically explore the paradox of “resource gospel” and “resource curse.” Based on the theoretical analysis, the influence of natural resources on green total factor productivity is analyzed empirically through an econometric model using Chinese urban panel data from 2010 to 2019. The theoretical analysis shows that the impact of natural resource endowment on green total factor productivity is indecisive. The empirical results show that natural resource endowments significantly lessen urban green total factor efficiency, and the results remain robust after addressing for endogeneity issues and robustness tests. However, this effect is significantly heterogeneous depending on the city level and science and education level; for example, the “resource curse” effect is more pronounced in non‐central cities and cities with average education and science level. Simultaneously, the mechanism analysis shows that natural resource endowment reduces urban total factor productivity by inhibiting innovation and introducing choices in the technological progress approach. Therefore, the research findings bring empirical evidence to promote reforms in natural resource allocation and provide theoretical support for encouraging green total factor productivity in resource‐based cities. [ABSTRACT FROM AUTHOR]

As environmental challenges escalate, green development is crucial for sustainability. This study analyzes China's county-level agricultural green total factor productivity using SBM and ML index, introducing a comprehensive index to quantify the impact of different types of environmental regulations on productivity. The findings reveal the following: baseline analysis reveals that comprehensive environmental regulation notably boosts agricultural green total factor productivity (AGTFP), with regulatory intensity positively linked to productivity growth. Other factors like policy intervention, industrial structure, savings levels, and per capita GDP also favorably impact productivity. All three types of regulations, command, incentive, and voluntary type, substantially enhance AGTFP. The mediating effect test results show that all three types of regulations directly and positively impact AGTFP. Indirect effects vary: command-type regulation's mediating effect through independent R&D is significant, accounting for 39% of the impact. For incentive type, both industry structure upgrading (23.79%) and independent R&D (3.1%) mediate the effect. For voluntary type, technological advancement via independent R&D mediates about 13.0% of the impact. Heterogeneity analysis reveals distinct impacts of different environmental regulations on AGTFP across regions. Command-type regulation is most effective in the west, while in the central region, both command- and incentive-type regulations have similar promotional effects. In the east, incentive- and voluntary-type regulations show stronger impacts. Robustness tests, including endogeneity testing, dependent variable substitution, sample winsorizing, and model substitution, consistently confirm the baseline finding that environmental regulation significantly boosts AGTFP. [ABSTRACT FROM AUTHOR]

The construction of ecological civilization and the realization of common prosperity are two major development strategies in China. In the context of ecological civilization construction, it is essential to achieve common prosperity through reforming the natural resource assets property rights system. This article qualitatively analyzes the functions of the natural resource assets property rights system by adopting the methods of functional analysis and interdisciplinary analysis and empirically analyzes its associated logic with the common prosperity by using the case analysis method. The results indicate that: ① There are four basic functions (marketization, capitalization, resource allocation, and ecologicalization) in the natural resource assets property rights system. ② In the process of utilizing natural resources to achieve common prosperity, the marketization function of the natural resource assets property rights system can transform natural resources into natural assets; the capitalization function can transform natural assets into natural capital; the resource allocation function can optimize the allocation of natural resources; and the ecologicalization function can preserve and increase the value of natural resources, thus achieving a win-win situation between ecological civilization construction and common prosperity. ③ Common prosperity cannot be achieved alone by utilizing natural resources; the achievement of common prosperity by utilizing natural resources is actually the result of the reform of the natural resources system and the property rights system. The policy implications of this study include: ① In terms of perfecting the property rights system, China's natural resource assets property rights system should be improved in the context of total factor productivity. ② In dealing with the relationship between the government and the market, we should make scientific distinctions between market allocation and government guidance according to different types of resource classification, making the market play a decisive role in resource allocation. ③ In maintaining the order of market transactions, the Civil Code should be used to protect the transactions of natural resource assets property rights. [ABSTRACT FROM AUTHOR]

This article investigates the causes of structural change in Brazil, through the rise and the fall of the manufacturing industry, and the consequences for total factor productivity and manufacturing labour productivity, from 1947 to 2021. Our results show that the industrialization of the Brazilian productive structure is positively associated with expansions in infrastructure investments and with the pursuit of a competitive real exchange rate, that is, with policies oriented towards economic development. Our findings also indicate that such variables exert a direct influence on total factor productivity and manufacturing labour productivity and an indirect influence through their impacts on the Brazilian productive structure. Our conclusions suggest that an important cause of the Brazilian premature deindustrialization, and then of its poor performance in terms of total factor productivity and manufacturing labour productivity, is the adoption of policies not oriented towards economic development adopted since the neoliberal reforms of the 1980s and 1990s. [ABSTRACT FROM AUTHOR]

This paper focused on the decision and regulation for the production-warehousing-selling (P-W-S) model. A novel event-triggered mechanism (ETM) was meticulously developed to determine when to impose control, alongside the development of the corresponding impulsive strategy. By applying the input-to-state stability (ISS) theory, some quantitative relationships between system parameters and ETM were integrated into the estimation of the state of the P-W-S model. It was shown that under the designed ETM and impulsive strategy, the warehouse was able to autonomously adjust inventory levels based on factory production efficiency and market selling trends, and hence the quantity of goods could be maintained within a reasonable range, avoiding excessive inventory while adequately meeting market requirements. At last, an example with numerical simulations was presented to validate our results. [ABSTRACT FROM AUTHOR]

Increasing agricultural productivity and reducing carbon emissions are two major challenges that China faces. This paper explores how agricultural insurance affects agricultural green total factor productivity (AGTFP) that addresses these two challenges. First, we adopt DDF-GML to measure AGTFP, and the Dagum's Gini decompositions results show the large differences in AGTFP, with transvariation between subregions contributing the most. Second, we find the U-shaped effect of agricultural insurance on AGTFP in a large country context. The result remains robust after adjusting for time, sample and estimation method of AGTFP. We also construct instrumental variables from the minimum distance from the centroid of counties within a province to the 45 ports in China and two-stage lagged agricultural insurance penetration (AIP) for AIP, and their squares as instrumental variables for AIP2. The conclusion remains robust in 2SLS model. Third, the findings confirm three channels for agricultural insurance to influence the AGTFP: environmentally friendly production, labor inputs and operation scale. We further propose policy advice to promote China's agricultural modernization and point out further research directions in this field. [ABSTRACT FROM AUTHOR]

Background: With Primary Health Care (PHC) being a cornerstone of accessible, affordable, and effective healthcare worldwide, its efficiency, especially in developing countries like China, is crucial for achieving Universal Health Coverage (UHC). This study evaluates the efficiency of PHC systems in a southwest China municipality post-healthcare reform, identifying factors influencing efficiency and proposing strategies for improvement. Methods: Utilising a 10-year provincial panel dataset, this study employs an enhanced Data Envelopment Analysis (DEA) model integrating Slack-Based Measure (SBM) and Directional Distance Function (DDF) with the Global Malmquist-Luenberger (GML) index for efficiency evaluation. Tobit regression analysis identifies efficiency determinants within the context of China's healthcare reforms, focusing on horizontal integration, fiscal spending, urbanisation rates, and workforce optimisation. Results: The study reveals a slight decline in PHC system efficiency across the municipality from 2009 to 2018. However, the highest-performing county achieved a 2.36% increase in Total Factor Productivity (TFP), demonstrating the potential of horizontal integration reforms and strategic fiscal investments in enhancing PHC efficiency. However, an increase in nurse density per 1,000 population negatively correlated with efficiency, indicating the need for a balanced approach to workforce expansion. Conclusions: Horizontal integration reforms, along with targeted fiscal inputs and urbanisation, are key to improving PHC efficiency in underdeveloped regions. The study underscores the importance of optimising workforce allocation and skillsets over mere expansion, providing valuable insights for policymakers aiming to strengthen PHC systems toward achieving UHC in China and similar contexts. [ABSTRACT FROM AUTHOR]

The carbon emissions trading system (CETS) is a crucial market-based tool aimed at achieving the goals of “carbon peaking” and “carbon neutrality”, and plays a pivotal role in promoting the green development of the logistics industry. The green total factor productivity (GTFP) of the logistics industry is a key indicator used to measure the green development level of the logistics industry. The research on the CETS and the GTFP in the logistics industry(LGTFP) is currently lacking. Accurately assessing the impact of CETS on LGFP is crucial for improving the construction of the CETS and promoting the green transformation of the logistics industry. Utilizing a combined approach of system dynamics and econometrics, this study examines the effects of CETS on the LGFTP. In this study, the impact mechanism of CETS on the LGTFP is analyzed by constructing a causal relationship diagram using system dynamics theory. And then, we construct a multi-period differencein- difference (DID) model using panel data from 30 Chinese provinces spanning from 2010 to 2020 to verify the impact of CETS on LGTFP. The findings reveal that: (1) CETS significantly promotes LGTFP, and this conclusion is consistent even after conducting robustness tests. (2) Green technological innovation is identified as the primary influencing mechanism of CETS in enhancing LGTFP, while industrial upgrading does not play a positive mediating role, contrary to established studies. (3) Heterogeneity analysis reveals that CETS has a significant promotion effect on LGTFP in central and western regions, and resource-based provinces, but not yet in eastern regions and non-resource-based provinces. Based on the empirical analysis, we propose relevant policy recommendations to improve China’s CETS and promote the improvement of LGTFP. [ABSTRACT FROM AUTHOR]

In this article, we analyse India's transport sector policy. The study examines the two important modes of transport, viz., road and rail, and analyses the efficiency of transport infrastructure from 2011 to 2019. Through Data Envelopment Analysis (DEA), we evaluate modes in terms of the capacity of registered road goods vehicles and railway goods wagons, truck km/train km and energy consumption and corresponding freight traffic. The analysis gives valuable insight into the fact that rail infrastructure is more efficient than road infrastructure. Still, current transport sector policies promote energy-intensive carbon-fuel road vehicles rather than energy-efficient alternative transport modes. The study suggests the changes that may be incorporated in inputs to improve the efficiency of the road infrastructure. The Data Envelopment Analysis (DEA)-Malmquist Index analysis reports the need for total factor productivity improvement in rail transport and the introduction of technological innovations in road and rail transport sector management. The study employs a well-to-wheel (WTW) based index to ascertain the energy consumed and pollutants emitted by freight-carrying road and rail modes between two leading business hubs of India, i.e., Ludhiana and Mumbai. The paper identifies policy gaps and suggests a holistic approach for need-based roadway investment and a time-bound development of railway infrastructure in India. Our study generates valuable implications for India's policy planners and government authorities and provides new insights to other countries. • The study examines road and rail transport, and analyses the efficiency and energy consumption of these modes. • The study suggests the changes to improve the efficiency of the road infrastructure. • The Data Envelopment Analysis (DEA)-Malmquist Index analysis and well-to-wheel (WTW) based index have been employed for the analysis. • The paper suggests a need-based roadway investment approach and a time-bound development of railway infrastructure. [ABSTRACT FROM AUTHOR]

Furniture production is one of the activities that has the potential to generate income for educational institutions. The furniture production process is generally carried out by experienced students utilizing industry-standard facilities, namely the Wood Construction workshop along with its machinery equipment. Therefore, the implementation of Quality Control in the production process is necessary. This study aims to determine the impact of Quality Control implementation on improving the productivity and quality of furniture products. The method used is quantitative with 4 stages of Quality Control, including product design, process planning, Incoming Quality Control (IQC), and In-Process Quality Control (IPQC). Productivity measurement is divided into 3 parts: partial productivity, total factor productivity, and total productivity, which includes labor productivity, time, and production output. Meanwhile, product quality measurement is obtained from assessments by practitioners and product quality testing according to ISO 19682. Data is processed using the path analysis method with the help of a smart PLS application. The research results show that the productivity of production output is 87.5%, categorized as good, with labor productivity of 0.125 pieces/person/day and work hour productivity of 0.25 pieces/hour/day. Product quality based on production processes is categorized as good at 83%. Meanwhile, product quality testing, including visual aspects is good (82.3%), product stability (normal), strength (normal), durability (normal), stiffness (normal 34mm/m), and drop test (normal). Based on path analysis, it is known that quality control including product design, process planning, Incoming Quality Control (IQC), and In-Process Quality Control (IPQC) has an impact on improving the productivity and quality of furniture products. the quality control carried out to increase productivity and product quality can be said to be good with the validation of the final result of 0.188 including in the good category. [ABSTRACT FROM AUTHOR]

Copyright of Agricultural Outlook (1673-3908) is the property of Institute of Agricultural Information, Chinese Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Abant Social Sciences / Abant Sosyal Bilimler Dergisi is the property of Journal of Abant Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper empirically investigates whether zombie firms affect healthy firms' exporting. Using the 1998–2007 Chinese firm‐level dataset, we provide strong evidence that zombie firms significantly decrease exports of healthy firms in each city‐industry cluster, that is, both whether to export and export values are affected by zombie firms. Specifically, non‐stated‐owned enterprises (non‐SOEs) are more vulnerable to the effect than their SOE counterparts. In addition, we also identify government subsidies, financial resources and total factor productivity as the sources of the effect, and the heterogeneous export performances of different types of firms are due to the variation in these sources. [ABSTRACT FROM AUTHOR]

Using empirical data from China, this study examines the impact of local internet development on non-executive employees' salaries. Research findings show that internet development can increase employees' salary and pay-performance sensitivity. This effect can be more significant in non-state-owned enterprises (Non-SOEs for short), firms faced with fierce competition, and firms paid little attention to employee protection. Mechanism analysis finds that the positive impact of internet development on increasing total factor productivity and reducing information asymmetry can partly interpret the effect. From the perspective of employees' salaries, this study sheds light on the impact of technological progress on micro-production relations. [ABSTRACT FROM AUTHOR]

This article explores the impact of Carbon Capture, Utilization, and Storage (CCUS) technology innovation on green total factor productivity (GTFP) in China. The study finds that CCUS technology innovation has a positive effect on GTFP by improving industrial structure and carbon emissions efficiency. Environmental regulations also contribute to this relationship. The author suggests further research to refine the measurement of GTFP and address potential issues in the analysis. They also recommend conducting a heterogeneity analysis and mediation test to understand the mechanism of CCUS technology innovation on GTFP. Overall, this study provides valuable insights into the relationship between CCUS adoption and environmental productivity in China. [Extracted from the article]

Using a panel data set from 2007 to 2019, we empirically evaluate the impact of carbon capture, utilization, and storage (CCUS) technology innovation on green total factor productivity (GTFP). The findings show that (1) CCUS technology innovation significantly improves GTFP. (2) CCUS technology innovation significantly contributes to GTFP by promoting industrial structure upgrading and carbon emissions efficiency. (3) Environmental regulation plays a positive moderating role in the nexus between CCUS technology innovation and GTFP. The findings of this paper provide guidance for China to achieve green energy transition and build a green energy system. [ABSTRACT FROM AUTHOR]

Objective: An organization demands its employees to possess the maximum potential benefits and expects them to meet organizational needs. Therefore, in a new perspective, the creation of an appropriate environment for the retention and maintenance of human capital and its connection to increased organizational productivity has been introduced as an important step towards the realization and achievement of objectives, including organizational productivity. The aim of this paper is to explain the structural model of factors effective in retaining and maintaining human capital based on organizational productivity in the National Iranian Oil Company. Methodology: The research method was descriptive-survey, and the statistical population consisted of senior managers and deputies in the human resources domain from the National Iranian Oil Company in headquarters and field staff (582 individuals), of whom 235 were selected as the sample using Cochran's formula. Interviews and questionnaires were used as data collection tools, validated through content and construct validity, and reliability was established using Cronbach's alpha coefficient. For data analysis, statistical methods and tests such as Pearson correlation coefficient, single variable t-test, Kolmogorov-Smirnov test, exploratory and confirmatory factor analysis were used, employing SPSS and LISREL software. Findings: The results indicate that the investigation into creating an appropriate environment for retaining and maintaining human capital and increasing organizational productivity involves individual factors, organizational factors, and group factors, each including components that significantly impact the productivity of the organization at the National Iranian Oil Company. The research also showed that retaining and maintaining human capital is key to improving and increasing organizational productivity, with the most influential components on productivity in the National Iranian Oil Company being organizational factors--performance management (efficiency and effectiveness) with an impact of 0.85, merit selection with an impact of 0.83, intellectual capital smartization with an impact of 0.80, talent management with an impact of 0.80, and individual factors--ability and knowledge with an impact of 0.79. Conclusion: A comprehensive human resource retention program can play a vital role both in attracting and retaining key employees and in financial turnover and other human resource costs. These factors significantly aid organizational productivity and overall business performance. It is far more efficient to retain a competent employee than to hire, train, and guide a replacement with similar capabilities. [ABSTRACT FROM AUTHOR]

To examine the productivity paradox in the digital era, we explore the impact of digital transformation (DT) on total factor productivity (TFP). Based on a large sample of Chinese manufacturing firms, this study conducts a machine learning approach to examine the effects of DT on TFP at the strategy, technology, and application levels. The results indicate that blockchain, DT strategy, cloud computing, artificial intelligence, DT application, and big data, in ascending order of importance, positively affect TFP. Overall, this study enriches DT literature by verifying the impact of DT indexes on TFP and helps companies make decisions when undertaking DT implementation. [ABSTRACT FROM AUTHOR]