In a paper published in the journal PLOS ONE, researchers investigated the impact of industrial robot (IR) applications on China's global value chain participation (GVCP) using manufacturing industry data from 2006 to 2014. The study revealed that IR applications weakened China's motivation to engage in global value chains, affecting backward and forward participation.
Study: Impact of Industrial Robot Applications on China's Global Value Chain Participation. Image credit: Generated using DALL.E.3
While the upgrading effect of IR facilitated import substitution of intermediate inputs, reducing backward participation, manufacturing localization led to a loss of opportunities for China to export intermediate inputs, diminishing forward participation in global value chains. It is important to note that these conclusions are specific to the Chinese economy due to sample limitations.
Impact of IR on GVC
GVCP is pivotal for fostering international trade expansion, productivity enhancement, and employment growth. Past studies have explored the relationship between emerging technologies, particularly IR applications, and GVCP. Scholars have investigated the dual impact of digital technologies, with AI-driven IR applications considered a focal point.
Existing literature presents a complex scenario, with some studies expressing concerns about the negative consequences on GVCP, while others affirm the positive effects of GVC upgrading. The mechanisms through which IR applications influence GVCP and upgrading involve promoting technological innovation, productivity improvement, and industrial structure optimization.
IR Applications and GVC in China
The approach proposes several methods in formulating research hypotheses regarding the impact of IR applications on China's manufacturing industry's GVCP. Firstly, it suggests that, given the traditional advantages of developed economies in research and development, design, and marketing, the application of IR in manufacturing will likely accelerate innovation in intermediate inputs, increasing import demand for these inputs and enhancing the forward participation of developed economies in GVCs.
However, the study also acknowledges the possibility that developing economies, if innovating intermediate inputs with IR applications, may erode the market share of developed economies, potentially reducing their forward participation. Therefore, the first set of hypotheses (1a, 1b, and 1c) posits that IR applications may impact China's forward, backward, and overall GVCP.
The second set of hypotheses (Hypothesis 2) explores the relationship between IR applications and product upgrading. It argues that as IR applications promote product upgrading, particularly in the context of China's ample market space and internal regional economic development, the need for manufacturing links to shift to countries with lower economic development may decrease. Instead, China's manufacturing industry might experience a gradient transfer of industrial chains between different regions. The study suggests that this dynamic can reduce China's backward GVCP, thereby influencing the overall GVCP.
Lastly, the third set of hypotheses (Hypothesis 3) delves into the mediation effect of product upgrading. It posits that IR applications can weaken China's motivation to participate in GVCs by promoting product upgrading. The study constructs an empirical model to analyze these relationships, incorporating industry-level control variables, fixed effects, and random error terms. The model aims to assess the direct impact of IR applications on GVCP and investigate whether product upgrading mediates this relationship.
For a comprehensive evaluation, the study proposes an active application of the Sobel test and an assessment of the ratio of the mediation effect to the total effect. These analytical approaches aim to enhance the understanding of how IR applications influence GVCP through the intermediate factor of product upgrading.
The study utilizes variables such as GVCP, IR applications measured by the number of robots per 1,000 people employed, and product upgrading assessed through export technological complexity. Control variables include factors like average operating income, labor productivity, the value of export deliveries as a share of operating income, and income tax payable as a share of total profits. Data from the 2016 World Input Output Database (WIOD) and the International Federation of Robotics (IFR) are employed to analyze the impact of IR applications and product upgrading on China's manufacturing industry from 2000 to 2014.
GVC Dynamics in Chinese Manufacturing: IR Impact
Descriptive Analysis: Providing an overview of trends in the number of robot stocks per 1,000 employed population and GVCP across various industries in China from 2006 to 2014, the study reveals significant growth in the adoption of IR in Chinese industries during this period. Across all 13 sampled industries, the number of robots employed per 1,000 workers exhibited an upward trajectory, indicating a consistent trend in integrating intelligent technologies.
Notably, capital and technology-intensive sectors, such as electrical/electronic and non-automotive metal products, demonstrated higher utilization of these technologies. However, GVCP levels showed a varied trend, with most industries experiencing a decline. Forward GVCP exhibited a slight upward trend in some sectors, potentially linked to technological advancements. These descriptive findings highlight the need for rigorous econometric testing to draw reliable conclusions.
Diagnostic Tests and Econometric Analysis: The study commenced with diagnostic tests, ensuring the robustness of variables through correlation analysis, multicollinearity checks, and panel unit-root tests. The application of ordinary least squares regression endorsed the hypothesis that adopting IR harms China's GVCP. Robustness tests, including variable replacement and instrumental variable regression, consistently affirmed the inhibitory influence of IR applications on GVCP.
Further analyses confirmed this negative impact across high-tech and low-tech manufacturing industries. The study also unveiled a mediating effect, indicating that IR applications promote product upgrading, reducing China's participation in GVCs. The empirical evidence underscores the intricate dynamics between IR applications, product upgrading, and GVC participation in China's manufacturing sector.
Conclusion
In summary, this new approach explores the impact of IR applications on China's manufacturing GVCs from 2006 to 2014. Results reveal a simultaneous decrease in forward and backward participation, supported by robustness tests and policy recommendations. Future research could delve deeper into case studies to comprehensively understand the observed effects.
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