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• The entry of high-tech FDI does promote the robot adoption by domestic manufacturers in China. • A Bartik instrumental variable is constructed to address the endogeneity issue. • Two main influencing channels are detected: demonstration and competition. • The effect is more salient among enterprises with stronger absorptive capacity. • Different levels of dependence on labor and energy inputs lead to heterogeneity. With the intensification of transnational economic activities, industrial robots have been making inroads into developing countries. However, few studies have analyzed how foreign direct investment (FDI) affects the diffusion of industrial robots among domestic enterprises in developing countries. To bridge the gap, we combine several datasets to empirically examine the causal relationship between high-tech FDI and the robot adoption by domestic manufacturers in China. We discover a significantly positive impact of high-tech FDI on the adoption of industrial robots by domestic manufacturers, evidenced by the expansion in both stock and flow, as well as an increase in the variety of robots. Mechanism tests indicate that this effect can be achieved through both proactive learning and absorption of external technology, as well as through passive participation in more intense market competition. Moreover, the impact of high-tech FDI on robot adoption is more salient among enterprises with stronger absorptive capacity as well as those characterized by lower labor intensity and higher energy intensity. [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]

China has experienced a boom of industrial robots in the past decade. Under the shock of robotization on labor market, migration is a critical way to rebalance the economy. While many studies have investigated the influence of robotization on labor market in the automation‐advanced countries, few works shed light on the situation in the emerging market. We provide empirical evidence on the effect of industrial robots on intercity migration in China. We find that, industrial robot adoption has a significant negative effect on the net inflow migration by reducing population inflows, while has little effect on population outflows. The decline in population inflows is concentrated among low‐skilled migrants who are younger, less educated and in manufacturing sectors, because they are more likely to experience unemployment and wage declines in the face of industrial robots. The analysis of migration cost demonstrates that the negative impact of industrial robots on population inflows increases with the longer migration distances, higher living costs, and greater institutional entry barriers caused by Hukou Registration System in China. [ABSTRACT FROM AUTHOR]

Based on an endogenous quality selection model, we investigate the effect of industrial robots on the export product quality of China's multi-product enterprises. The main finding is that there is a nonlinear "inverted U-shaped" relationship between industrial robot applications and export quality. Industrial robots mainly affect export quality through the "productivity improvement effect" and "innovation inhibition effect." The influence channels exhibit heterogeneity, contingent on industries, growth stages, and import orders. We further find that the entry of new products, improvement in the quality of existing products, and reallocation of internal resources within the enterprise account for product quality change in general. [ABSTRACT FROM AUTHOR]

Amidst the global upsurge in industrial robot deployment, there remains a notable gap in our understanding of their environmental impact. This paper explores how the introduction of industrial robots has changed air quality at both the local and neighborhood levels in China. Using the Spatial Durbin Model, we investigate the regional spillovers of PM 2.5 concentration and the diffusion of this innovative technology. Our findings reveal that the rise of robots significantly reduces air pollution in the local area, while exacerbating it in neighboring regions. This contrast is mainly because pollution-intensive industries are more inclined to relocate to neighboring regions than their cleaner counterparts, after the local use of robots increases. Throughout the process, internal costs rather than external costs dominate firms' relocation decisions. This study provides novel insights into the complex environmental externalities associated with the spread of industrial robots and highlights the critical issue of growing environmental inequality in the era of emerging technologies. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta (YRD) bears the vital task of driving the growth of China's equipment manufacturing industry (EMI) intelligence as an advanced region. Fostering the transformation and upgrading of the EMI in the YRD and constructing a modern production mode is vital to developing and reforming China's manufacturing industry. This paper uses industrial robot data to assess the level of intelligence (LoI) in the EMI from 2016 to 2019. The OLS (ordinary least squares) model is used for the measurements, and the MQ (the modified contribution index) is used to estimate the degree of contribution from a host of variables. It is identified that the LoI is on the rise. However, excluding railways, aerospace, shipbuilding, and other transportation equipment manufacturing, the LoI is significantly higher than in other subsectors. It is also identified that technological innovation ability, human capital density, and enterprise cost pressure govern the industry's LoI. Moreover, while there is a difference in the main influencing factors in LoI within different industries, R&D investment, technological innovation ability, and enterprise cost pressure have the most significant impact across most equipment manufacturing sub-industries. [ABSTRACT FROM AUTHOR]

As China has become the largest user of industrial robots, the need to understand how workers perceive robot-human substitution and how their perceptions influence their job behaviors is becoming increasingly crucial. This paper examined whether workers' fear of being replaced by robots (FRR) is correlated with one aspect of job behavior: turnover intention, which refers to the extent to which an individual intends to change their job within a specific time period. Using a dataset covering 1512 manufacturing workers in Guangdong province of China, we found that workers who fear losing their jobs to robots report significantly higher turnover intention. We also found that the positive effect of FRR on turnover intention increased when robots were already utilised in the workplace. This effect was also found to be increase when workers perceived that their wages did not increase with the rise in productivity due to robotisation. Based on these findings, we provide practical recommendations to organizations on effectively addressing the turnover intention arising from the FRR. [ABSTRACT FROM AUTHOR]

As the hospitality industry has begun adopting service robots to replace frontline human services, service robots' attractiveness becomes a salient factor in their design and implementation. However, it is unclear what consist of service robots' attractiveness and how they affect customer responses. This study examines the effects of multiple dimensions of service robots' attractiveness on customers' emotions using a text mining approach. For the data analysis, we collected 50,629 online reviews on 59 hotels and restaurants using service robots from the largest social commerce platform in China. Using the Linguistic Inquiry and Word Count (LIWC) method, we analyzed 7570 online reviews that are directly related to service robots. With the LIWC outcomes, the relationships between the attractiveness dimensions and customer emotions were investigated. Based on our findings, finally, we provide propositions for understanding the attractiveness of service robots. The theoretical and practical implications of the findings are discussed. [ABSTRACT FROM AUTHOR]

We investigate the impact of higher education expansion policy (HEEP) on robot imports in a developing open economy such as China. First, we treat the HEEP as a quasi-natural experiment and adopt a difference-in-differences strategy to undertake detailed empirical analysis after conducting the common trends tests. Second, we find that the HEEP significantly increases robot imports of firms by both extensive and intensive margins; the impact is mainly concentrated in industries with medium human capital intensity. Specifically, firms in the low (high) human capital intensity sector tend to increase (decrease) robot imports. Third, we explore the underlying mechanism and conduct a series of empirical tests to check robustness; these include adopting a non-linear relationship with the quadratic form, using alternative measures of human capital intensity, excluding observations after 2007, excluding possible distributors, teasing out the potential effects engendered by China's World Trade Organization accession, as well as excluding the confounding effects of 3-year graduates. We obtain similar results. Our findings shed light on the impact of the higher education expansion policy on robot imports in developing and transition countries. [ABSTRACT FROM AUTHOR]

The application of industrial robots is considered a significant factor affecting environmental pollution. Selecting industrial wastewater discharge, industrial SO2 emissions and industrial soot emissions as the evaluation indicators of environmental pollution, this paper uses the panel data model and mediation effect model to empirically examine the impact of industrial robots on environmental pollution and its mechanisms. The conclusions are as follows: (1) Industrial robots can significantly reduce environmental pollution. (2) Industrial robots can reduce environmental pollution by improving the level of green technology innovation and optimizing the structure of employment skills. (3) With the increase in emissions of industrial wastewater, industrial SO2, and industrial dust, the impacts generated by industrial robots are exhibiting trends of a "W" shape, gradual intensification, and progressive weakening. (4) Regarding regional heterogeneity, industrial robots in the eastern region have the greatest negative impact on environmental pollution, followed by the central region, and the western region has the least negative impact on environmental pollution. Regarding time heterogeneity, the emission reduction effect of industrial robots after 2013 is greater than that before 2013. Based on the above conclusions, this paper suggests that the Chinese government and enterprises should increase investment in the robot industry. Using industrial robots to drive innovation in green technology and optimize employment skill structures, reducing environmental pollution. [ABSTRACT FROM AUTHOR]

Promoting the application of industrial robot (IR) is an important module for China to build core competitiveness, and it is also the main grasp of global value chain participation (GVCP). Using China manufacturing industry panel data from 2006–2014, working from the perspective of product upgrading, this paper empirically analyzes the impact of IR applications on GVCP. The empirical results show that IR applications weaken China' incentives to participate in global value chains (GVCs); this weakening effect is reflected in both forward and backward participation in GVCs. On the one hand, the mediation effect test results indicate that the product upgrading effect brought about by IR applications can help China achieves the import substitution of intermediate inputs and uses local intermediate inputs to produce exports. These steps would reduce the backward participation in GVCs. On the other hand, the localization of manufacturing can result in China losing the opportunity to export intermediate inputs to other economies, thus reducing the forward participation of GVCs. Of course, due to sample limitations, the research conclusions of this article are only applicable to interpreting the Chinese economy. [ABSTRACT FROM AUTHOR]

As the "pearl at the top of the manufacturing industry," the widespread use of robots is affecting the employment decisions of individual workers. This paper contributes to our understanding of this subject by analyzing the impact of imports of industrial robots on employment location choice at the inter-provinces level in China. The analysis applies a logit approach to microdata from the China Customs Database and China Labor Dynamics Survey. The results suggest that robot import positively affects employment location choice, supporting the theory of "coexistence" between intelligent robots and the labor force. Specifically, industrial robots attract skilled workers via the creation effect and drive away routine labor via the substitution effect, but the creation effect is greater than the substitution effect. Finally, the authors discuss the channels from the perspectives of "skill-biased" and "routine-biased." [ABSTRACT FROM AUTHOR]

Green innovation plays a crucial role in transforming economic models and achieving sustainable development in enterprises. As an important embodiment of artificial intelligence technology, how industrial robots can effectively promote the green transformation of enterprises has become an important issue. This paper examines the impact and mechanisms of industrial robot adoption on corporate green innovation, as well as its heterogeneous effects. Using data from Chinese listed companies from 2007 to 2019, we find that industrial robot adoption has a significant positive impact on corporate green innovation, enhancing both its quantity and quality. Furthermore, our mechanism study reveals that industrial robot adoption can promote corporate green innovation by improving productivity and environmental management capabilities. Additionally, we investigate the moderating effects of various factors and conclude that the positive impact of industrial robot adoption on green innovation is more pronounced among the state-owned enterprises, enterprises with the intense market competition, as well as enterprises located in regions with higher carbon emissions intensity. This paper contributes to enrich the research on industrial robots and corporate green innovation, and provides a reference to improve environmental management and achieve a low-carbon economy in emerging markets. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the effect of the utilization of industrial robots on income inequality in urban China. By employing the data of imports of industrial robots and income inequality at the city level in China, we find that the adoption of robots has a positive effect on urban income inequality. This positive effect remains robust when we use instrumental variable estimation to tackle the potential endogeneity problem. In addition, this positive effect is more salient in cities with below average national income per capita. The results have important policy implications for achieving common prosperity in China. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office 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.)

While the diffusion of industrial robots has had a significant impact on the economy and society, more research is needed to understand how robots contribute to sustainable growth. This study uses paired data on China's county‐level carbon emissions and industrial robot installations from 2008 to 2017, employing a Bartik shift‐share instrumental variable design to estimate the economic and sustainable effects of industrial robot diffusion. The study finds that industrial robots significantly promote economic growth and contribute to carbon emission reduction as confirmed by robust IV 2SLS and general PSM‐DID methods. Additionally, a heterogeneity analysis shows that industrial robots have a stronger impact on sustainable growth in underdeveloped and small‐medium cities, especially in low‐skilled industries. Finally, the study identifies industrial structural change, clean energy use, and improved productivity and innovation as key factors that mediate the impact of industrial robots on sustainable development. [ABSTRACT FROM AUTHOR]

Mining robots are a component of mining production, concerning multiple stages such as mining, transportation, production, maintenance, safety control, and rescue, The degree of production automation directly affects the production safety, economic and social benefits of enterprises, With the rapid development and popularization of artificial intelligence in China, mine intelligence has become an important research field, Especially with the promulgation of some policies and regulations in China, intelligent unmanned mining technology has become a key part of mining production in the field of gold mining, To understand the connotation, status, and development trend of intelligent mining robots, this article reviews the underground intelligent robot technologies matching mining operations, including neural networks, binocular vision, and digital twins, from the perspective of the relationship between key technologies and practical engineering applications of intelligent mining robots in China, From the 4 perspectives of basic theories, critical technologies, engineering applications, and overall design system theories, this article reviews the relevant research, On this basis, the current development trend of domestic intelligent mining robots and the future development trend of smart mining models are summarized, [ABSTRACT FROM AUTHOR]

Industrial robots are increasingly used to perform tasks traditionally assigned to humans. Using a sample of Chinese manufacturers, we examine the impact of robot adoption on firm cost stickiness. We find that robot adoption is associated with less sticky costs. The negative impact of robot adoption on cost stickiness is particularly meaningful for state‐owned enterprises and firms with higher labour costs, and becomes significantly stronger after the enactment of China's Labour Contract Law, which significantly increases labour adjustment costs. These findings are consistent with the conjecture that the adoption of robots allows firms to reduce their overall labour adjustment costs. [ABSTRACT FROM AUTHOR]

This paper explores the impact of artificial intelligence and industrial robots on firms' export behaviour and divides the impact mechanism into the productivity effect and labour substitution effect. It examines the effect of industrial robots on firms' export value by using Chinese Customs data, Chinese Industrial Firm data and robot data from the International Robot Federation (IRF). The main findings are as follows: Firstly, the impact of artificial intelligence and industrial robots on Chinese firms' export value is generally negative, which means the negative labour substitution effect dominates the positive productivity effect. Secondly, the impact of artificial intelligence varies significantly by industry, and the export value of firms from high-tech industries benefits from the use of industrial robots. Thirdly, the impact of artificial intelligence on firms' export value also varies by time; before 2003, the use of industrial robots showed mainly an inhibiting effect on firms' exports, which turned into a driving effect thereafter, and after 2006, industrial robots began to significantly promote firms' export. Finally, the higher the quality of export products, the more likely the use of industrial robots will be to promote firms' export value, and the higher the capital–labour ratio is, the more likely firms' export value will be to benefit from the use of artificial intelligence and industrial robots. On the basis of these findings, this study proposes promoting the productivity effect to dominate the labour substitution effect through technological progress and the improvement of export product quality. [ABSTRACT FROM AUTHOR]

How to achieve the goal of "carbon peak and carbon neutrality" and explore the compatibility of industrial and ecological civilization is a major challenge for China today. This study analyzes the impact of industrial intelligence on industrial carbon emissions efficiency in 11 provinces of China's Yangtze River Economic Belt, measuring the efficiency of industrial carbon emissions through the non-expected output slacks-based measure (SBM) model, selecting industrial robot penetration to measure the level of industrial intelligence, establishing a two-way fixed model to verify the impact of industrial intelligence on carbon emission efficiency, and testing for intermediary effects and regional heterogeneity. The results show that: (1) the industrial carbon emission efficiency of the 11 provinces shows year-over-year improvement, with significant differences between upstream, midstream, and downstream, where downstream is the highest and upstream is the lowest. (2) The development of industrial intelligence is highly uneven, with the upstream level being the weakest. (3) Industrial intelligence can improve the efficiency of industrial carbon emissions by enhancing green technological innovation and energy use efficiency. (4) The effect of industrial intelligence on industrial carbon emission efficiency also shows regional heterogeneity. Finally, we present policy recommendations. This research provides mathematical and scientific support for achieving carbon reduction targets at an early stage and helps accelerate the construction of a modern, low-carbon China. [ABSTRACT FROM AUTHOR]

The rising level of automation has increasingly attracted scholars' attention. On the other hand, there are many studies of the consequences of social movements, but relatively fewer studies focus on their economic consequences, and even fewer studies have examined their consequences on automation. This article bridges the gap between the two literatures by hypothesizing that a rising number of labor protests will lead to a higher level of automation. We argue that political economy factors influence the adoption of more automation. Protests anticipate higher wages and labor costs; contest for social power with employers and the state, and, in extreme cases, pose a public relations challenge to employers, which will likely push employers to replace human workers with robots. We empirically test the relationship by using two protest event datasets in China, the China Labor Bulletin and Collective Action from Social Media and robot data from the International Federation of Robotics. Statistical analysis shows that provinces and industries that have more protests also tend to concentrate more robots, and the results are robust to most specifications and placebo tests. The findings have implications for both understanding the mechanism explaining rising automation and the consequences of social protests. [ABSTRACT FROM AUTHOR]

The industrial robot is an essential part of modern manufacturing. Using micro‐level data, this study investigates the effects of industrial robots on the labour market in China. The results show that the adoption of industrial robots increases firm‐level employment by 31.65%. Using the Bartik method, we construct robot penetration as an instrumental variable of robot adoption to tackle endogenous problems. Our results stand up to a series of robustness checks. Moreover, the effects of robots are mainly owing to the expansion of the output scale, increased productivity, and upgraded products. We also find the skill‐biased impact of robots and the spillover effect of industrial robots through production networks. [ABSTRACT FROM AUTHOR]

Copyright of Tourism Tribune / Lvyou Xuekan is the property of Tourism Institute of Beijing Union University 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.)

In light of the growing economic uncertainties worldwide, the use of industrial robots has emerged as a significant opportunity for improving the production efficiency and the international division of labor in China's energy industry. This study employed a two-way fixed-effect model utilizing data from 31 Chinese provinces between 2011 and 2019 to investigate the impact of industrial robots on the energy industry's participation in the international division of labor. The results of the study indicated that the widespread application of industrial robots can boost the international division of labor status of China's energy sector. This conclusion remains robust even after addressing the potential endogeneity issues and conducting a range of sensitivity tests. Furthermore, our findings suggest that the regions that possess abundant energy resources or exhibit a lower carbon intensity are more likely to leverage the use of industrial robots to increase the technological sophistication and enhance their participation in the international division of labor. The application of industrial robots in the energy industry can enhance the international division of labor through two distinct channels: optimizing the factor structure and reducing the export costs. Our findings have important policy implications for ensuring energy security and improving the energy industry's participation in the international division of labor. [ABSTRACT FROM AUTHOR]

Copyright of China Forest Products Industry is the property of China Forest Products Industry Editorial Office 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.)

In this paper, a greenhouse tomato picking robot chassis that meets the path cruising and setpoint positioning requirements of robots engaged in greenhouse tomato picking operations in China is designed. Based on the trellis-cultivation growing environment of tomatoes, the basic parameters of the chassis and operating space are analyzed to determine the chassis requirements during picking operations. According to these requirements, a kinematic model of a robot chassis with front-wheel steering and rear-wheel driving is constructed, and the planar positioning principle of the chassis is introduced. SOLIDWORKS is used to simulate and design three-dimensional models of the chassis parts, and the ANSYS WORKBENCH plug-in is used to simulate and analyze the bearing performance of key chassis components. ADAMS is used to simulate and evaluate the motion trajectory of the chassis, and the reasonableness of parameters such as the chassis size, selected materials, and load-bearing performance are verified. Based on the simulation results, a physical system is constructed to experimentally verify the straight-line motion and steering performance of the chassis. The experimental results show that the chassis has good cruising and positioning accuracy and meets the specific requirements of path cruising and setpoint positioning in greenhouse tomato picking operations. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology 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.)

Artificial intelligence has emerged to revolutionize society in China. Investigating whether industrial robot applications (IRAs) can contribute to Chinese economic prosperity has significant theoretical and practical significance. For this purpose, this study estimates the impact of IRAs on green innovation by decomposing the industry robot stock to the corporate level using global industry robot data and manufacturing data from Chinese manufacturing listed companies by constructing a Bartik instrumental variable. The results show that IRAs notably promote corporate green innovation. However, IRAs do not contribute equally to all corporations in green creation. Its effects on green innovation are mainly observed in larger corporations, technology-intensive industries, and corporations located in developed cities. Digital transformation, management efficiency, and CEO's information technology (IT) background can further strengthen the green innovation effect of IRAs. We conclude that the rational exploitation of artificial intelligence drives the economy towards green development. • Industrial robot applications (IRAs) notably promote corporate green innovation. • Bartik instrumental variable effectively alleviate the endogeneity problem. • Digital transformation, management efficiency enhancement, and CEO's IT background have moderating effects. • Artificial intelligence drives the economy towards green development. [ABSTRACT FROM AUTHOR]

In this paper, we examine how robot adoption and Chinese import competition shaped employment patterns in 352 cities across the United Kingdom. We find that cities whose initial industry composition exposed them to industrial robots and China's integration into the world economy experienced significant employment declines. When pitched against other capital and technologies, the impact of robots remains distinct. Our findings suggest that one more robot per thousand workers reduced the employment-to-population ratio by 0.5 percentage points, while an increase of $1,000 imports from China per worker reduced the employment-to-population ratio by 0.11 percentage points. We also show that while these are sizable effects, penetration of both robots and Chinese imports are too small to account for Brexit. [ABSTRACT FROM AUTHOR]

This article analyses how local states, electronics manufacturers and low-skilled workers perceive and make decisions about automation under China's techno-developmentalism. Since the early 2010s, local states have made automation – specifically, the substitution of robots for human workers – the linchpin of their techno-developmentalist strategy and set statistical targets to facilitate policy implementation. Although manufacturers realised the limitations of such substitution, most continue to overstate the power of robots in order to receive material and symbolic benefits from local states, which rely on manufacturers to achieve their statistical targets. Meanwhile, most low-skilled workers embrace the state's vision and see automation as beneficial for national progress, although these workers are the most excluded by state policy. Essentially, China's techno-developmentalism has led to symbiotic state-capital relations that marginalise low-skilled workers, while reproducing a national sociotechnical imaginary that prioritises abstract notions of technological progress over the actual efficacy of automation, labour protection and social equality. [ABSTRACT FROM AUTHOR]

With the rapid development of industry 4.0 and the boom of large-scale product customization, the adoption of collaborative robots' innovation becomes a hot topic in research. Previous studies have mainly focused on individuals, but few on enterprises, and in particular, there has been a lack of empirical research on the enterprise level. Based on the combined model of Technology-Organization-Environment Framework (TOE) and Diffusion of Innovations Theory (DOI), this study investigated 373 small and medium-sized enterprises (SMEs) in Guangdong Province, China, to explore the determinants of SMEs' adoption of collaborative robot innovation in technology, organization, and environment. The result shows that the technical factors of relative advantage, compatibility, observability, and trialability have a significant positive correlation with the adoption of collaborative robots, while complexity has a significant negative correlation with the adoption. Among the organizational factors, top management support and organizational readiness have a significant positive correlation with the adoption of collaborative robots. Among the environmental factors, agent support is positively and significantly correlated with adoption. The findings will help practitioners develop appropriate strategies for the adoption of collaborative robot innovation. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology 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.)

The popularization of intelligent machines such as service robot and industrial robot will make human-machine interaction, an essential work mode. This requires employees to adapt to the new work content through learning. However, the research involved human-machine interaction that how influences the employee's learning is still rarely. This paper was to reveal the relationship between human-machine interaction and employee's learning from the perspective of job characteristics and competence perception of employees. We sent questionnaire to 500 employees from 100 artificial intelligence companies in China and received 319 valid and complete responses. Then, we adopted a hierarchical regression for the test. Empirical results show that human-machine interaction has a U-shaped curvilinear relationship with employee learning, and employee's vitality mediates the curvilinear relationship. In addition, job characteristics (skill variety and job autonomy) moderate the U-shaped curvilinear relationship between human-machine interaction and employee's vitality, especially the results of moderating effects varying with employee's competence perception. Exploring the mechanism of the effect of human-machine interaction on employee's learning enriches the socially embedded model. Moreover, it provides managerial implications how to enhance individual adaptability with the introduction of AI into firms. However, our research focuses more on the impact of human-machine interaction on employees at the initial stage of AI development, and the level of machine intelligence in various industries will reach a high degree of autonomy in the future. The future research can explore the impact of human-machine interaction on individual's behavior at different stages, and the results may vary depending on the technologies mastered by different individuals. The study has theoretical and practical significance to human-machine interaction literature by underscoring the important of individual's behavior among individuals with different skills. [ABSTRACT FROM AUTHOR]

Using the micro-level data on China's export enterprises from 2005 to 2013, this paper discusses the impact of industrial robots on the quality upgrading of export products from two aspects: the change of enterprises' costs and the structural effect of labor allocation. We find that there is a U-shaped relationship between the use of industrial robots and export products' quality upgrading, but the enterprises whose robot applications exceed the U-shaped inflection point only account for 22.68%; in other words, most enterprises have not yet realized export products quality upgrading, and there exists a mismatched effect in the initial development stage. The results of mechanism analysis showed that industrial robots have significant effects on the costs and the structure of labor for export enterprises. [ABSTRACT FROM AUTHOR]

China has been the world's largest market for industrial robots since 2013. Industrial robots improve accuracy, safety, and efficiency in industrial production but have a substantial impact on the labor market. This investigation uses the task-based model to explore the relationship between industrial robots and employment across industries. This study uses industrial robot data from the International Federation of Robotics and employment data from the China Statistical Yearbook from 2010 to 2019 to examine robot applications' influencing mechanisms on labor demand in different industries in China. The results show a significant positive correlation between robots' exposure and labor demand for IT, health and social services, science research and technical services, and management of water conservancy and environmental industries. Based on the results, the use of robots promotes high-skilled talent employment and some third-sector employment, like education, food and beverages, utilities, household appliances, and transport. However, multiple regression analysis reveals that the use of robots has reduced employment in traditional industries such as agriculture and mining. [ABSTRACT FROM AUTHOR]

From global production network (GPN) theory, this study explores the configurations of emerging Southern market-driven production networks through the case of China's industrial robot industry which has emerged with increasing automation in production. This paper argues that to serve the Chinese high- and middle-end customers, global lead firms from Western economies have established regional production networks by localising production, connecting with global component suppliers in/outside China and collaborating with Chinese system integrators. However, Chinese capable firms have organised domestic production networks for the low and middle-end through integrating with domestic component suppliers and system integrators. This study adapts the GPN framework, mostly highlighting Western markets, by examining markets and firms in the Global South and revealing new configurations of production networks. [ABSTRACT FROM AUTHOR]

Based on China's Industrial Robot and Customs data from 2006 to 2019, this paper conducts an empirical investigation into the impact of industrial robot usage on export trade structures and its working mechanism with the popularization of industrial robots and the expansion of export trade in China. It finds that the use of industrial robots has significantly increased the proportion of general trade, reduced that of processing trade and promoted the transformation from processing-trade into general-trade, or the impact mechanism of industrial robots on export trade structure. After adopting such two methods as lag phase and tool variables to address potential endogenous problems, the results continue to be valid. In addition, the paper also discussed the regional heterogeneity effect of industrial robot trade transformation. Such evidence provides a new perspective for developing countries to explain the transformation of their export trade and are of high significance in optimizing the structure of trade patterns and promoting the transformation of export trade. [ABSTRACT FROM AUTHOR]

The industry is at the heart of a country's development, and robot automation is the key to this. The automation of industrial robots is extremely beneficial to industrial development. Although China has been increasing its investment in industrial robot automation and control research, there are still many problems in the field of automation and control in the application of industrial robot technology, and there is still a certain gap between the developed countries. On the one hand, this is a serious obstacle to the development of industrial robotics in China, and on the other hand, it has a direct impact on the automation of industrial production, which has a very restrictive effect on industrial development. Therefore, it is necessary to focus on the value of computer technology, automation control technology, and sensor technology in the field of automation. The use of industrial robots can replace monotonous manual labour, reduce the intensity of operations, and increase productivity through high operational precision values. Scientific progress has driven the development process of industrial automation to a new level, allowing fully automated production equipment to become mainstream and gradually replace manual operations. In recent years, the development of industrial automation has led to the development of a series of related industries, of which automated manipulators are one. As a new automatic production line operation equipment, the development of manipulators can greatly improve the automation production level of enterprises and improve labour efficiency. This paper explores the development status of automated manipulators and explore the optimal motion path of manipulators in automatic control engineering by combining simulated annealing algorithm and PID algorithm, so as to greatly enhance the application of truss manipulators in production lines. [ABSTRACT FROM AUTHOR]

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We study the effects of higher labor costs on the adoption of industrial robots by Chinese firms. We use the number of robots imported by firms from the customs data to measure the adoption of robots. To address endogeneity concerns, we focus on the effects of higher minimum wages from contiguous city pairs that straddle provincial borders. We find negligible effects of minimum wages on firms' robot adoption over 2004–2007, but much larger and statistically significant effects over 2008–2012. For a 10% increase in the minimum wage over 2008–2012, the probability of a firm adopting robots increases by 0.11 percentage points, compared to an average adoption probability of 0.19% over the same period. The effects of higher minimum wages on robot adoption are stronger for firms with higher productivity, those in the coastal region, those with private ownership, and those from skilled-labor-intensive industries. [ABSTRACT FROM AUTHOR]

The continued development of artificial intelligence (AI) has changed production methods but may also pose challenges related to energy consumption; in addition, the effectiveness of AI differs across industries. Thus, to develop efficient policies, it is necessary to discuss the effect of AI adoption on energy intensity and to identify industries that are more significantly affected. Using data on industrial robots installed in 16 Chinese industrial subsectors from 2006 to 2016, this paper investigates both the effect of AI on energy intensity and the channel through which this effect is transmitted. The empirical results show, first, that boosting applications of AI can significantly reduce energy intensity by both increasing output value and reducing energy consumption, especially for energy intensities at high quantiles. Second, compared with the impacts in capital-intensive sectors (e.g., basic metals, pharmaceuticals, and cosmetics), the negative impacts of AI on energy intensity in labor-intensive sectors (e.g., textiles and paper) and technology-intensive sectors (e.g., industrial machinery and transportation equipment) are more pronounced. Finally, the impact of AI on energy intensity is primarily achieved through its facilitation of technological progress; this accounts for 78.3% of the total effect. To reduce energy intensity, the Chinese government should effectively promote the development of AI and its use in industry, especially in labor-intensive and technology-intensive sectors. [ABSTRACT FROM AUTHOR]

The widespread application of industrial robots has raised our concerns about employment. Based on the data of Chinese micro-enterprises from 2000 to 2019, we use staggered and continuous DID method to measure the impact of industrial robots on the employment in the enterprise level in China. The result of the analysis shows that, under the combined effects of technology substitution and creation, the use of industrial robots has a significant positive impact on the employment of Chinese enterprises. The substitution effect is mainly in medium skilled labor, while the creation effect happens in high skilled and machine auxiliary positions. The analysis of heterogeneity of industry penetration rate of robot shows that, the creation effect in high skill positions and the substitution effect in low and medium skill positions mostly happen in high penetration rate industries, while the substitution effect in high skill positions and the creation effect in low and medium skill positions mostly happen in low and medium penetration rate industries. This result reveals the internal mechanism of the adjustment of employment structure caused by new technology. Based on this, the relevant suggestions are put forward from unemployment security system, corporate social responsibility, training of technical personnel, etc. • We analyzed the employment effect of industrial robots in China's enterprises. • Creation effect mainly occurs in high-skill positions; substitution effect mainly occurs in medium/low-skill positions. • High-skill job creation and medium/low-skill job substitution mainly occur in high penetration rate industries. • Medium/low-skill job creation and high-skill job substitution mainly occur in industries with medium/low penetration rates. • Our research reveals the internal motivation and direction of employment structure adjustment under the new technology. [ABSTRACT FROM AUTHOR]

• Investigated the impact of industrial robot adoption on GTFP in Chinese cities. • Employed the NDDF-GLPI and Bartik IV approach to estimate GTFP and the penetration of industrial robots. • Utilized a combination of two-way fixed effects models, mechanism analysis models, and quantile regression models for causal identification. • Industrial robot adoption enhances GTFP through energy saving, technological innovation, scale output, and industrial linkage. • The positive effect of industrial robots on GTFP is mitigated in areas with high pollution, while it is reinforced in regions with the development of green finance. This study investigates the impact of industrial robot adoption on Green Total Factor Productivity (GTFP) against the backdrop of increasing demand for both robot proliferation and green development utilizing urban panel data from Chinese cities spanning 2007–2019. Findings reveal that industrial robot adoption significantly improves GTFP, exerting its influence through mechanisms such as energy saving, technological innovation, scale output, and industrial linkages. Certain market factors moderate the influence of industrial robot on GTFP. Initially, regions reliant on high-pollution industries and resource-based cities experience minimal effects, which may diminish or even reverse as GTFP improves. Additionally, the positive influence of industrial robots on GTFP is particularly noticeable in regions with advanced development in green finance. This research is significant for understanding the connection between industrial robot adoption and green development at the urban level and for exploring pathways for green transformation. [ABSTRACT FROM AUTHOR]

As a new engine in guiding China's high-quality economic development, it is important to study whether the development of artificial intelligence (AI) will increase the skill premium and affect labor income inequality. Based on Acemoglu and Restrepo's (2018a) task-based model, this study constructs a multi-sector dynamic general equilibrium (DGE) model to analyze the impact and mechanism of AI on the skill premium and performs a numerical simulation using China's industrial panel data from 2010 to 2019. The results show that AI widens the skill premium by substituting low-skilled labor with industrial robots and performing high-skilled labor tasks. The mechanism analysis reveals that AI also affects the skill premium by influencing factor flow and structural transformation. Based on these findings, this study provides policy suggestions for governments to mitigate the impact of AI on the labor market. • The development of artificial intelligence (AI) has a significant positive effect on skill premium. • AI directly affects skill premium through machine replacement and new tasks creation. • AI indirectly affects skill premium by affecting factor flow and structural transformation. • The direction of factor flow depends on the relative speed of machine replacement and new tasks creation. [ABSTRACT FROM AUTHOR]