Technology-intensive Industries Research Articles

Talent Introduction Policies, Optimal Labor Allocation, and Corporate Green Innovation

Under the “dual carbon” strategy, innovation driving has become the core force for corporate green transformation, with human resources, a key element of green innovation, increasingly gaining attention. This study utilizes data from A-share listed companies to evaluate the impact of China’s urban talent introduction policies on corporate green innovation, focusing on the three dimensions of green product, process, and management innovation. The results reveal that urban talent introduction policies significantly promote corporate green innovation in three areas: green product innovation, green process innovation (end-of-pipe pollution control), and green management innovation. The influx of high-quality talent and optimization of the labor structure represent vital pathways for achieving this impact. Different talent types play different roles in different dimensions of green innovation. Heterogeneity analysis indicates that talent introduction policies have a stronger promoting effect on the green innovation performance of large enterprises, technology-intensive industries, and enterprises in relatively weak regional economies. For enterprises with public–private partnerships, talent admission policies have a more pronounced impact on their green product innovation and process innovation (end-of-pipe pollution control). Furthermore, the impact of talent policy on corporate green innovations in products and processes varies with the intensity of local government intervention. This study emphasizes the key role of talent introduction policies in promoting green innovation, providing theoretical foundations and policy references for implementing sustainable development strategies and environmental protection objectives.

Achieving pollution abatement and carbon reduction synergistically: How can industrial robots play a role?

Intelligent manufacturing and green development are pivotal issues in China's pursuit of high-quality economic growth. As the core carrier of artificial intelligence-driven production transformations, industrial robots' role in synergizing enterprise pollution control and carbon reduction has rarely been discussed in the literature. Leveraging a unique micro dataset with robot adoption, energy use, emissions, and economic factors, this study investigates the impact and mechanisms of robot adoption on enterprise pollution abatement and carbon reduction. The results unveil simultaneous SO2 and carbon emission intensity reductions after robot adoption. Further analysis attributes such synergistic effects primarily to front-end cleaner production rather than back-end pollution treatment. Promoting lean production, cleaner energy consumption, and technological innovation emerge as critical channels for robot adoption to exert synergistic benefits in pollution abatement and carbon reduction. Additionally, this collaborative abatement effect concentrates in large-scale enterprises, technology-intensive industry enterprises, and non-resource-based region enterprises. By elucidating robotization's micro-level workings, these findings provide valuable insights into green intelligent manufacturing and guide future integration of digital intelligence and green economy.

How do firms adapt their portfolios of external collaborations to changing internal organizational attributes? The moderating role of firm age

Objective of the study: Given the benefits of external collaborations in technology-intensive industries, we explore how firms adapt their portfolios of external collaborations to internal uncertainties. Using the behavioral theory of the firm, this study examines how firms adapt based on innovation performance feedback. Methodology/approach: We built a panel dataset from three sources. Patent data came from The National Bureau of Economic Research (NBER) paper (Kogan, Papanikolaou, Seru, & Stoffman, 2017), which used extensive name-matching tools to link USPTO patents to firms. External collaborations data were collected from the SDC Platinum Joint Ventures and Alliances database, focusing on R&D agreements. Financial data were sourced from Compustat. After processing, the dataset included nearly 900 publicly listed firms from 12 high-tech industries (1990-2010). We tested our hypotheses using two probit models, each predicting a different dependent variable. Originality/Relevance: We shift the focus from the traditional dyad perspective, which centers on individual partnerships, to how firms adjust their entire portfolios of external collaborations in response to their internal dynamics, like innovation performance feedback. While real options and transaction cost theories emphasize the need to maximize efficiency in individual partnerships, we explore how firms adapt their broader set of external collaborations to changing internal conditions. Main results: We find that firms performing above innovation aspirations are more likely to form equity alliances (i.e., joint ventures). However, the magnitude of this effect greatly differs between mature and young firms. Young firms are about four times more likely than their mature counterparts to form equity alliances when they significantly surpass their innovation targets. Theoretical/methodological contributions: Our study contributes to the research on alliance portfolio adaptation by showing that, beyond external factors like technological change and market uncertainty, firms also adjust their portfolios of external collaborations in response to internal factors, specifically innovation performance feedback. Moreover, our findings also demonstrate that firms’ responses to innovation performance relative to aspirations vary based on their lifecycle stage. Social /management contributions: Our study also has several implications for managers. First, managers of well-performing firms should view exceeding innovation aspirations as a signal to pursue collaborations to scale new technologies and knowledge. Their performance gives them a stronger negotiating position for forming joint ventures, allowing them to secure more favorable terms. Additionally, they should, in this case, seek partnerships to share risks associated with cutting-edge innovation projects rather than solely investing in internal innovation prospects. For young firms, which tend to respond more aggressively when outperforming their innovation aspirations, managers should adopt bold partnership strategies. In contrast, managers in mature firms should focus their resources on internal development, mergers and acquisitions, or partnerships that help maintain the autonomy of these firms.

The Evolution and Performance Response of Industrial Land Use Development in China’s Development Zone: The Case of Suzhou Industrial Park

Development zones are crucial spatial carriers driving economic growth and industrial upgrading, playing a key role in China’s development. After years of expansion, these zones face significant challenges in industrial land development and performance enhancement. This paper takes Suzhou Industrial Park (SIP) as a case, which is a model of Sino–Singaporean government cooperation. Using Landsat 4–5 TM data, socioeconomic data, and industrial land use data, spatial analysis and statistical modeling were employed to examine the evolution and phased patterns of industrial land use in SIP from 1994 to 2022. A performance evaluation system encompassing economic benefits, innovation-driven growth, development intensity, green development, and social security was developed to assess land use performance and its responses to spatial transformations. The results reveal that industrial land in SIP experienced a significant change in the intensity of land expansion from 1.031 to 0.352 during 1994–2022, and the peak circle density expanded from 3 km to 15 km. The mean value of the comprehensive performance score during 2017–2022 was 42.18, with the highest economic efficiency (40.54) and a lower innovation capacity (16.98). The development of industrial land in SIP presents the stage characteristics of monocentric polarization, polycentricity, and spatial diffusion toward a generalized development zone, showing significant path dependence, and the difference in the land use performance of different industrial types is obvious. In the future, the optimization and redevelopment of the stock of land should be strengthened to promote the optimization of the spatial layout of technology-intensive industries and the technological upgrading of labor-intensive industries, as well as achieving sustainable economic growth through innovation-driven, green development and enclave economy collaboration. This study provides a reference for the industrial layout and high-quality sustainable development of development zones.

The green innovation effect of industrial robot applications: Evidence from Chinese manufacturing companies

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.

Does the impact of open innovation depend on contextual factors? A case of the Korean biopharmaceutical industry.

Investments in the strategic development of the biopharmaceutical industry are increasing in both developed and developing countries. The biopharmaceutical industry is a technology-intensive industry where securing original technology and intellectual property rights is important. The role of open innovation is becoming more important due to the enormous research and development (R&D) funds and long development period in the early development process, and open innovation (OI) is becoming more important in the corporate world. Many empirical studies have been conducted on the impact on performance. However, the contextual factors that affect the relationship between OI activities and innovation performance have received relatively little attention, and studies from the perspective of developing countries catching up with developed countries are even rarer. Accordingly, this study examined the moderating effects (government R&D support, absorptive capacity, and alliance management capacity) that affect open innovation and innovation performance in the biopharmaceutical industry using data from Korea, one of the most representative latecomer countries in the biopharmaceutical industry. The basic information, OI activities, and patent achievements of Korean biopharmaceutical firms were collected and organized into a database. Samples with missing or incorrect information were excluded, and 527 firms were analyzed. Negative binomial regression analysis was performed considering the characteristics of patent performance, which is the dependent variable, and a time lag of one to two years was assumed considering the time required to generate results. OI in the form of technological cooperation, rather than technology purchasing, has a positive effect on patent performance. Meanwhile, the greater the absorptive capacity and government R&D support, the greater the positive impact of technological cooperation on patent performance. Conversely, the greater the alliance management capacity, the greater the positive impact of technological cooperation. These results indicate that the impact of OI activities on technological innovation performance may vary depending on context.

The Impact of Climate Policy Uncertainty on the ESG Performance of Enterprises

In the context of addressing climate change, the uncertainty of climate policies has intensified the environmental and regulatory risks faced by enterprises, forcing them to adjust their strategies for fulfilling ESG responsibilities in pursuit of sustainable development. This paper uses panel data from listed non-financial enterprises on China’s Shanghai and Shenzhen A-share markets from 2011 to 2022, employing a fixed-effects panel model to examine the impact of climate policy uncertainty on corporate ESG performance. The findings indicate that climate policy uncertainty significantly hampers the ESG performance of enterprises. The mechanism analysis reveals that climate policy uncertainty negatively affects ESG performance by deepening corporate financing constraints and increasing short-term financial performance. The heterogeneity analysis shows that in terms of ownership structure, the negative impact of climate policy uncertainty on the ESG performance of state-owned enterprises is relatively weaker. In terms of industry heterogeneity, climate policy uncertainty suppresses the ESG performance of enterprises in technology-intensive industries. From a regional perspective, climate policy uncertainty has a stronger inhibitory effect on the ESG performance of enterprises in eastern China. This study provides valuable insights for both national climate policy formulation and corporate efforts to enhance ESG performance.

Research on Ecological Restoration Strategies for Abandoned Mines Based on Ecology-Oriented Development

The ecological restoration of abandoned mines poses a significant challenge within China’s broader efforts toward the protection and restoration of the nation’s ecosystems. Based on the ecology-oriented development (EOD) model, a differential game framework for the ecological restoration of abandoned mines was constructed in this study, involving both government and corporate entities as players. Our analysis focused on various factors, including investment levels in ecological restoration quality, the quality of ecological restoration itself, investment levels in environmentally sensitive industry development, the quality of environmentally sensitive industries, environmentally sensitive product pricing strategies, and profit dynamics for both players across four distinct modes. Our findings reveal several key insights. First, extending the government’s concession period incentivizes enterprises to increase investment in both the quality of ecological restoration of abandoned mines and the development of environmentally sensitive industries. Second, the government should prefer the cooperative mode to introduce social capital for the ecology-oriented development of abandoned mines. Third, in noncooperative mode, for technology-intensive industries, the government’s industrial support policy is more mutually beneficial; conversely, for labor-intensive industries, the ecological restoration compensation policy yields higher mutual gains. Lastly, differentiated incentive policies implemented by the government across various modes prompt the input of enterprises in ecological restoration quality and environmentally sensitive industry development. Based on these findings, we offer specific policy recommendations to guide governmental efforts in promoting EOD for the ecological restoration of abandoned mines. Funding: This work was supported by the Sichuan Office of Philosophy and Social Science [Grant SC22C004] and the National Social Science Fund of China [Grant 22XKS015].

Can reverse mixed-ownership reform promote green transformation of private enterprises?

The private sector greatly influences China's economy, which is crucial for fostering consistent economic growth. This paper takes A-share listed private enterprises (PEs) from 2009 to 2022 as the research object, uses the time-series regime-switching detection method to detect the changepoints of reverse mixed-ownership reform (RMOR) of PEs, and utilizes the staggered difference-in-difference (DID) model to investigate the impact effect and mechanism of the RMOR policy on the green transformation (GT) of PEs. The results show that the RMOR significantly promotes the GT of PEs. Additional mechanism tests reveal that the RMOR will lower the level of internal governance and impede the GT of PEs. However, it will help alleviate the financing constraints of PEs and promote their GT. The results of the moderation analysis reveal that RMOR has a greater impact on the GT of small and medium-sized enterprises (SMEs) compared to large-scale enterprises. At the industry level, RMOR exerts a more significant influence on capital-and technology-intensive industries than on labor-intensive ones. Additionally, RMOR impacts the GT of PEs in regions with lower government regulatory intensity than in regions with higher regulatory intensity. The findings provide new empirical insights, decision-making tools, and innovative perspectives for the GT of PEs.

Integration of manufacturing and services: Examining its effect on resource allocation and manufacturing labor productivity

The integration of manufacturing and services is a key factor driving the development of the manufacturing sector. Thus, this study uses Chinese province–industry data to determine the effect of such integration on resource allocation and manufacturing labor productivity. Additionally, heterogeneity is systematically examined, while avenues for its improvement are explored. Based on the results, dividing integration into forward and backward integration shows that both types significantly enhance manufacturing labor productivity by improving resource allocation efficiency, with forward integration demonstrating a more pronounced effect. This mechanism mainly manifests in capital- and technology-intensive industries but not in labor-intensive ones. Notably, while the integration of manufacturing and services enhances both economic and social efficiency by curbing capital over-allocation, it creates the problem of labor over-allocation. These conclusions provide value insights for promoting industrial transformation and upgrading.

Storm clouds over innovation: Typhoon shocks and corporate R&D activities

This study investigates the economic impact of typhoon disasters on corporate innovation activities, a critical driver of economic growth and resilience. Utilizing a comprehensive dataset of Chinese public companies from 2010 to 2022 and employing a wind field model to construct a city-level typhoon destruction index, we apply difference-in-differences and instrumental variable methods to analyze the effects on corporate innovation. Our findings reveal that typhoon disasters significantly reduce both patent filings and R&D investment intensity, particularly in coastal areas and technology-intensive industries. The adverse effects are transmitted through financial constraints, human capital loss, and infrastructure damage. This research contributes to understanding the microeconomic implications of extreme weather events on innovation-driven economic growth, offering insights for disaster resilience policies in vulnerable regions.

Does continuous innovation failure lead firm innovation to hesitate to press forward?: Evidence from Chinese-listed technology-intensive industries firms

Continuous innovation failure is a common phenomenon in the process of firm innovation. However, little is known about how continuous innovation failure affects firm innovation, and what factors moderate the relationship between them. Using the empirical data from China’s technology-intensive industries listed firms, we find that continuous innovation failure doesn’t lead firm innovation to hesitate to press forward but promotes firms to increase innovation. Managerial overconfidence strengthens the positive impact of continuous innovation failure on firm innovation. Interestingly, managerial power does not enhance but weakens the regulatory role of managerial overconfidence. Further analysis shows that continuous innovation failure will prompt firms to increase exploratory innovation and reduce exploitative innovation. Heterogeneity analysis finds that the promotion effect of continuous innovation failure on firm innovation will be enhanced in firms with higher financial redundancy, but will be weakened in firms with higher R&D subsidies.

Digital trade liberalization and quality upgrading: evidence from Chinese intermediate imports

ABSTRACT This article investigates how the import quality of intermediate products responds to digital trade liberalization using Chinese Customs data and the composite index of digital trade liberalization obtained from OECD database for 2014–2019. The results reveal that digital trade liberalization has significantly improved the quality of Chinese manufacturing intermediate imports. Further mechanism tests show that digital trade liberalization will boost the improvements through trade cost reduction effects. For the influence path, digital trade liberalization will promote the quality upgrading through both intensive and extensive margins. The heterogeneity analyses find that imports from countries with high economic developments experienced larger quality promotion than those from lower economic area. Meanwhile, the quality upgrading effects of digital trade liberalization are mainly reflected in Chinese non-comparative industries, such as downstream, digital-intensive, R&D-intensive and technology-intensive industries. Moreover, compared to homogeneous products and those by processing trade mode, the quality of intermediate imports for differentiated products by general trade are more responsive to the liberalization of digital trade barriers.

Rethinking Regional High-Quality Development Pathways from a Carbon Emission Efficiency Perspective

Optimizing resource efficiency and mitigating climate change have become consensuses of human society. However, there is still a gap in assessing the carbon emission efficiency (CEE) and identifying the influence of various factors, especially in rapid urbanizing regions. In this paper, we built a stochastic frontier analysis model to assess CEE and conducted a case study in the Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA), a typical area of collaborative development in China. A comprehensive influencing factor index was constructed to analyze and identify the key influencing factors of CEE. The results revealed that the average CEE among the 13 cities increased in volatility from 2000 to 2019. The average CEE in Langfang was lowest, while that in Tangshan was highest. The input-related factors had a negative effect on CEE, including carbon emissions per capita, employment per ten thousand people, total assets per capita, and energy intensity. GDP per capita, the urbanization level, and the proportion of the tertiary sector’s GDP had positive impacts on CEE. Future policy formulation should focus on the transition from labor- and material-intensive industries to knowledge- and technology-intensive industries. All the results can contribute to achieving high-quality development and dual-carbon target of rapid-urbanizing areas.

Do regional tax incentive policies improve productivity?

The difficulty in transforming old industrial areas constitutes a significant factor contributing to regional development imbalances. Can regional tax incentives, as a crucial component of regional policies, polish the "rust belt" regions? This study leverages the inaugural Value-Added Tax (VAT) reform in China as an opportunity to explore the potential of regional tax incentives in achieving sustainable development in traditional industrial areas. Drawing upon a comprehensive industrial enterprise database, we employ a Propensity Score Matching-Difference in Differences (PSM-DID) approach to examine the efficacy of these tax incentives. Our findings reveal that: (1) Regional tax incentives primarily enhance firms productivity by stimulating investment in enterprises, yet they do not contribute to improved investment efficiency or spur innovation within firms. (2) Regional tax incentives have alleviated financing constraints for enterprises in old industrial bases, significantly enhancing the Total Factor Productivity (TFP) of firms with higher financing constraints. This policy has had an even stronger impact on improving the TFP of state-owned and monopolistic enterprises. (3) Regional tax incentives have impeded productivity growth by preventing the exit of low-efficiency firms and the entry of high-efficiency ones. These incentives also increased the likelihood of "zombie firms" forming and failed to promote endogenous economic growth in the Northeast region. Additionally, they have distorted the allocation of resources towards capital and technology-intensive industries in that area. In China's old industrial bases, regional tax incentives should be coordinated with market-oriented reforms; these regional tax incentive policies should also be further enriched.

Impact and mechanism analysis of industrial robot imports on export performance of Chinese firms

Digital import trade is of great practical significance for enhancing the export performance of enterprises and preventing external shocks. This paper empirically examines the impact and mechanism of industrial robot imports on Chinese firms’ export performance based on Chinese microenterprise data from 2004 to 2014. The study shows that the application of imported robots can significantly improve firms’ export performance, and this conclusion still holds after a series of robustness tests. Heterogeneity analysis shows that imported robots have a more significant role in boosting the export performance of state-owned enterprises and enterprises in capital- and technology-intensive industries; at the same time, they have a significant effect on the export performance of enterprises in different modes of trade; and they have a significant role in boosting the export performance of enterprises in eastern China compared with those in central and western regions. Mechanism analysis shows that the enhancement of export performance of enterprises by imported robots is mainly realized by promoting enterprise productivity and human capital efficiency. The policy implication of this paper is that in the era of digital trade, Chinese enterprises should fully utilize the import of digital products to enhance their productivity and promote the high-quality development of foreign trade.

Board gender diversity and innovation performance in manufacturing firms: What is the role of risk-taking?

This study investigates the impact of board gender diversity on innovation performance in Chinese listed manufacturing firms, focusing on the mediating role of firm risk-taking. Analyzing 21,262 firm-year observations from 2010 to 2022, we find that board gender diversity positively influences innovation performance through increased risk-taking. Heterogeneity analysis reveals that the impact is stronger in the Eastern and Central regions and in technology-intensive industries. These findings suggest that gender-diverse boards can foster innovation by promoting balanced risk-taking, particularly in regions with better institutional environments and technology-driven sectors. The results have significant implications for corporate governance practices and policies aimed at enhancing gender diversity and innovation.

Impact of Generative AI on Enterprise Performance in China

This study examines the impact of generative artificial intelligence (GAI) on Chinese enterprises. 320 participants completed electronic surveys, revealing a positive relationship between GAI and corporate performance. Managerial relationships were found to play a crucial role, mediating the influence of GAI on performance. Additionally, the speed of technological change in the industry was identified as a moderator, highlighting the dynamic nature of GAI's impact on managerial relationships and firm performance. These findings underscore the strategic importance of GAI in cultivating managerial relationships and improving enterprise performance, deepening our understanding of the integration of advanced AI technologies and management practices in the Chinese market. Practical implications are offered for decision-makers in technology-intensive industries, providing valuable insights for leveraging GAI to gain a competitive edge and achieve sustainable growth in a rapidly evolving technological landscape.

Relationship Between Environmental Regulations and Global Value Chains in Chinese Manufacturing

While active participation in GVCs can stimulate economic growth, it has also been noted to exacerbate environmental pollution. To address environmental concerns, most countries have strengthened environmental regulations, which in turn may affect the positioning of countries within GVCs. This study empirically analyzes the impact of environmental regulations imposed by the Chinese government on the positioning of the manufacturing sector within GVCs of Chinese manufacturing industries from 2006 to 2018. The findings of the research are as follows: Firstly, the strengthening of environmental regulations has an inverted U-shaped impact on the overall GVC position of Chinese manufacturing sector, demonstrating the combined effects of cost effect and innovation compensation effect. Specifically, when environmental regulations are lower than a certain level, strengthening regulations shifts the GVC position upstream. However, when regulations are more stringent than the level, further strengthening them leads to a downstream shift in GVC position. Secondly, it seems that China's current level of environmental regulation is below the apex of the inverted U-shaped curve, and therefore, it is anticipated that further strengthening of environmental regulations in China will result in a further upstream shift in the GVC position. Thirdly, these analytical results are particularly applicable to technology-intensive industries.

Can the expansion of market size increase firm markup? Evidence from China

ABSTRACT Traditional international trade theory suggests that a larger market size leads to more intense competition, thereby reducing firm markup. However, this conclusion does not hold in our research. Based on the theoretical model constructed by Melitz, this paper makes the following extensions: First, introducing the cost-saving effect outside of the competitive effect discussed in traditional international trade theory. Second, introducing a specific marginal cost function, which deepens the analysis of the operating mechanism. What’s more, earlier models focused solely on the market size of the industry itself (the target industry), whereas our analysis also takes into account the impact of the market size of its upstream and downstream industries. Our model indicates that the impact of market size on firm markup depends on the relative magnitude of the competitive effect and the cost-saving effect. With firm cost following a Pareto distribution, the expansion of market size leads to an increase in firm markup. In addition, this paper presents a spatial econometric model using industrial firms’ data from China. The results indicate that the promoting effect of market size on firm markup is more prominent among top-tier firms, state-owned firms, low export intensity firms, and firms in technology intensive industries.