Technology-intensive Industries Research Articles

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.

Analysis of the Relationship Between E-Commerce Business and Technology-Based Accounting Information Systems with Company Audit Needs

This study explores the relationship between E-commerce business operations, Technology-Based Accounting Information Systems (AIS) adoption, and corporate audit needs through a quantitative analysis approach. Drawing on data collected from 234 participants representing E-commerce firms and audit professionals, the study employs Structural Equation Modeling (SEM) with Partial Least Squares (PLS) to analyze the relationships among key variables. The findings reveal significant positive associations between E-commerce characteristics and Technology-Based AIS adoption, as well as between Technology-Based AIS adoption and corporate audit needs. Furthermore, mediation analysis demonstrates that Technology-Based AIS adoption partially mediates the relationship between E-commerce characteristics and corporate audit needs. Additionally, moderation analysis indicates that firm size and industry type moderate these relationships, with larger firms and those in technology-intensive industries exhibiting stronger associations. These findings underscore the importance of technological innovation and organizational context in shaping audit readiness and effectiveness within E-commerce environments.

The Role of Higher Education in Science and Technology in the Development of Technology-Intensive Industries in China

Abstract Technology-intensive industries in China have developed rapidly since its economic reform. This article examines the role of higher education institutions (HEI s) in science and technology (S&T) in innovation and the development of technology-intensive industries in China. First, it illustrates the evolution and current status of S&T education at HEI s and their relationship to enterprises and science parks that led to China’s innovation and technological development. Second, it reveals the government’s role in promoting S&T education at HEI s and strengthening the relationship between universities and enterprises. Finally, it derives policy implications for developing countries in light of China’s experience.

Study on the Structure, Efficiency, and Driving Factors of an Eco-Agricultural Park Based on Emergy: A Case Study of Jinchuan Eco-Agricultural Park

The eco-agricultural park is a new comprehensive agricultural technology system integrating agricultural production, rural economic development, ecological environment protection, and efficient resource utilization. Therefore, an in-depth analysis of the ecosystem structure of eco-agricultural parks will help achieve the goal of coordinated symbiosis between human development and environmental protection. This study takes the research area of the Eco-agricultural Park of Jinchuan Town, Huinan County, a typical town in the Changbai Mountains of Northeast China. Based on field surveys, market research, farmer consultation, and related data collection, emergy theory and methods are used to construct an emergy model for the park. The value evaluation index system integrates the unique emergy index of the agricultural ecosystem with the traditional emergy index system to conduct a targeted evaluation of the park’s functional structure and sustainable development capabilities in order to improve the efficiency of material and energy use and provide technical reference for ecological construction and comprehensive development of agricultural industry in mountainous areas in northern China. The research results show that: (1) The annual input total emergy of the eco-agricultural park is 4.04E+24 sej/a, and the emergy of labor input, electricity input, and topsoil loss is relatively high. The park is in a labor-intensive stage. The annual output total emergy is 5.09E+24 sej/a, the park is dominated by planting and forestry industries. (2) The park’s emergy utilization intensity is high—production efficiency is high, economic development is advanced, and the system’s self-control, adjustment, and feedback functions are vital—and plays a significant role in promoting the development of the regional economy. However, the park relies more on investment from external resources, and production in the park puts pressure on the environment. (3) The current sustainable development capability of the study area is weak, and the factors affecting the sustainable development capability are mainly energy loss and uneven distribution of industrial areas in the park. Effective measures to promote the transformation of the park to develop technology-intensive industries and improve the sustainable development performance of the park were proposed. These include: adjusting the proportion of industries in the park; reducing high-energy external input emergy, such as industrial auxiliary emergy; reducing the loss of non-renewable natural resources through ecological engineering measures, such as reducing the depth of slope runoff in the park; and combining modern resource-based production technology and environmentally sound management methods to reduce energy loss and rational use of natural resources.

Does artificial intelligence affect firms’ inner wage gap?

ABSTRACT This paper studies the effect of artificial intelligence on firms’ inner wage gaps. We use data from the International Federation of Robotics (IFR) and China’s A-share listed firms from 2011 to 2019. The results indicate that artificial intelligence is conducive to narrowing the wage gap. After considering the potential endogeneity problems in the relationship between artificial intelligence and the wage gap and a set of robustness tests, the main effect still persists. Mechanism analysis shows such an effect is more pronounced when firms are intensively skilled or have weakened managerial power. Further analysis shows that artificial intelligence primarily reduces the wage gap in technology-intensive industries.

HGX: the anatomy of high growth exporters

AbstractPrevious work has found that a small number of export superstars contribute disproportionally to the economy’s overall exports. Differently from export superstars, this study is the first to define high growth exporters (HGXs) (that are not export superstars) as a new firm category. We provide their economic importance and depict their micro-level anatomy. By tracking HGXs in Croatia for over a quarter of a century, 44 out of 100 export superstars in 2019 were previously HGXs. HGXs represent only 0.5% of all firms and 18% of high growth firms (HGFs) in the economy, but are responsible for about 25% of new exports and 5% of new jobs. During their growth episode, HGXs hire more employees from technology intensive industries with previous experience in exporting. They often hire on a single year work contract, and more frequently send new employees to work abroad. HGX also increase their presence in more advanced markets, increase the number of new export products and decrease their reliance on the largest product or largest export market. We argue HGXs represent an under-researched category of firms.

The impact of population aging on FDI: A panel data analysis based on 27 segments in China's manufacturing industry.

Foreign Direct Investment (FDI) is an important part of China's new "double-cycle" development pattern. Among the many factors affecting FDI, will the aging population have an impact on manufacturing, the key industry for FDI? This paper examines the direct and indirect effects of an aging population on FDI using panel data from 27 manufacturing sub-industries in China between 2005 and 2020. It is found that (1) the deepening of the population's aging negatively affects FDI inflows and this result continues to hold after a series of robustness tests. (2) Using labor quantity and labor cost as mediating variables, it is found that the population's aging indirectly affects FDI by reducing labor quantity and increasing labor cost. (3) The heterogeneity analysis study finds that the deepening of the population's aging significantly inhibits FDI in labor-intensive and capital-intensive industries among manufacturing sub-industries, and the inhibitory effect on FDI in technology-intensive industries is not significant. This study provides meso-evidence to support the findings of existing studies and provides suggestions and insights for the government to formulate relevant policies to actively cope with aging.

The heterogeneous impact of green public procurement on corporate green innovation

Effectively strengthening support for corporate green innovation and promoting green transformation has become the key to promoting coordinated economic and social development in China. As a demand-oriented innovation incentive policy, green public procurement is vital for promoting green innovation. Data from A-share listed firms (2013–2019) are analyzed to explore the impact of green public procurement on corporate green innovation including the heterogeneous effects under different environmental regulation intensity levels. The results show that green public procurement significantly promotes corporate green innovation, especially in areas with strong environmental regulation. Heterogeneity analyses at the firm, industry, and regional levels show that the promotion effect of green public procurement on corporate green innovation is more significant for non-state-owned, small-scale, and ISO 14001-certified enterprises; technology-intensive industries, and enterprises in eastern China and regions with high financial development levels. This study has implications for improving the effectiveness and accuracy of green public procurement policies.

Digital finance, natural resource constraints and firms' low-carbon behavior: Evidence from listed companies

Digital finance is pivotal in a company's environmentally responsible practices. Given this, we examine the impact of digital finance on firm's carbon emissions using a fixed-effect model using A-share listed companies data from 2011 to 2020. The results report that digital finance significantly dampens a firm's carbon emissions, and a similar effect is observed in the breadth of coverage and digital finance depth of use. Distinguishing the characteristics of firms' samples reveals that the carbon abatement effect resulting from digital finance is more evident in non-state-owned enterprises, remains significant in capital-intensive, technology-intensive industries as well as in manufacturing, yet is insignificant in labour-intensive and non-manufacturing industries. Promoting environmental, social and governance, facilitating digital transformation and incentivizing green innovation are significant digital finance-driven carbon abatement mechanisms. Digital finance's carbon-cutting effect is amplified further by financial regulation constraints and natural resource constraints.

Related variety, region-specific context, and regional economic performance: Empirical evidence from post-socialist Slovakia

ABSTRACT The purpose of the article is to uncover the relationship between related variety in technology-intensive industries in the manufacturing sector and the region-specific context of Slovakia. The authors employed a dynamic panel model covering the 2009–2019 period. The aim was to determine the extent to which the regional context influences the benefits of related variety on regional economic performance. To understand the deeper structures and mechanisms of related variety, it was divided according to the technology-intensive industries. The results indicate that only unrelated variety positively determines regional employment growth. However, in combination with regional context, even the related variety mechanism becomes significant. When the related variety was decomposed, it was found that only the related variety in low-tech industries supported regional employment growth. By contrast, the industrial specialization in high-tech industries had a significant impact on the regional employment growth. When contextual conditions were taken into consideration, the effects of industrial specialization (low value of related variety) in high-tech industries disappeared. The authors conclude that contextual conditions, particularly foreign direct investment, are strong predictors for explaining regional employment growth, as they have the potential to shape the effects of related variety mechanism.

Greening the belt and road: How GVCs revolutionize carbon intensity in participating countries?

As a critical link between production and carbon transfers, Global value chains (GVCs) increasingly support the green industrial transformation in the Belt and Road Initiative (BRI) countries. Based on the theoretical analyses, this study estimates the impact of GVCs participation on carbon intensity using the panel data in 22 BRI countries of 40 industries during 2000–2019, it also distinguishes the effects of national-industrial-ownership heterogeneity and clarifies the influence paths. The main findings are: (1) The average carbon intensity level presents a downward trend, and the GVCs position improved gradually recently after a long term decline before 2014 in fluctuation. Both behave differently when distinguishing participants at the country-industry-ownership dimensions. (2) GVCs position has a robust and negative correlation with carbon intensity. (3) At the national scale, developing countries and Annex I countries in the Kyoto Protocol benefit more from GVCs position upgrading in carbon reduction. At the industrial level, increase in GVCs position has significant carbon mitigation effects on agriculture and manufacture (labor and capital intensive) industries, while not significant in service (technology intensive) industries. Considering firm ownership, domestic firms could realize more carbon reduction through GVCs position revolution, while it's not significant for multinational enterprises. (4) From mechanism analyses, the suppression of carbon intensity by GVC upgrading is mainly exerted through its impact on improving capital and labor efficiencies. Policy implications on carbon intensity reduction are finally suggested.

Asymmetric effects of international oil prices on China's PPI in different industries——Research based on NARDL model

In theory, changes in the price of oil, which is a critical raw material for production, can affect the Producer Price Index (PPI). In this study, the PCA method is first employed to extract factors from the PPI of 39 industrial sectors in China, followed by the application of the NARDL model to analyze the nonlinear effects of international oil price fluctuations on the PPI of three industries. The results indicate that the long and short-term fluctuations in international oil prices have a significant impact on the PPI of resource-intensive industries and labor-intensive industries, but the impact on capital and technology-intensive industries is not significant. However, it is worth noting that the long-term increases in oil prices will have a negative impact on the PPI of resource-intensive industries. From the perspective of asymmetry, the positive and negative shocks of international oil prices will have an asymmetric impact on the PPI of labor-intensive industries, while the impact on resource-intensive industries is symmetric. Based on the existing conclusions, this article proposes relevant policy recommendations from the perspectives of both government and enterprises.

The impact of digital economy on green total factor productivity considering the labor-technology-pollution factors

The digital economy provides new impetus for the high-quality development of manufacturing industry. Through the DEA-Malmquist model and panel regression model, this paper confirmed that there is a positive and significant relationship between the development of digital economy and the green total factor productivity (GTFP) of manufacturing industry. The research result is as follows: (1) the development of digital economy can enhance the overall GTFP of manufacturing industry. (2) The green technology progress brought by the development of digital economy is the main path to promote the GTFP of manufacturing industry. (3) The heterogeneity analysis shows that the impact of digital economy on GTFP of high pollution manufacturing industry is significantly positive, the impact of labor-intensive manufacturing industry is significantly negative, and the impact of technology intensive manufacturing industry is not obvious. The contributions of this study are as follow. In terms of theory, this study theoretically continues Solow’s classical theory, demonstrating the scientific nature of digital technology progress in promoting GTFP growth. In empirical analysis, this study build a new digital economy development level evaluation index system based on the perspective of manufacturing industry. In addition, this study also add a labor-technology-pollution perspective for the development of relevant policies.

The role of industrial intelligence in peaking carbon emissions in China

As industrial intelligence empowers economic advancement and technological progress, its capacity to enable decarbonization during China's low-carbon transition remains uncertain. Existing literature concentrates on the environmental impact of information and communication technologies or uses single-dimension measuring indicators, failing to capture the comprehensiveness of industrial intelligence. Based on the concept of full-cycle management, this study constructs a comprehensive index to evaluate industrial intelligence from intelligent inputs, intelligent production capacity, and intelligent outputs. Using 2006–2020 Chinese provincial panel data and fixed-effects models, we analyze the effects, mechanisms and thresholds of industrial intelligence on carbon emissions. The results show that: (1) The level of industrial intelligence plays a role in reducing carbon emissions after a certain threshold. (2) Industrial intelligence reduces carbon emissions by advancing green technology and optimizing production structure. (3) Industrial intelligence mitigates carbon emissions in eastern and north China but not western China. According to current growth rates of industrial intelligence, nine Chinese provinces may achieve a carbon peak through industry intelligence by 2030. (4) Moreover, industrial intelligence's carbon emission reduction effect is significant in labor- and technology-intensive industries but does not work in capital-intensive industries. These revelations have meaningful implications for orienting industrial intelligence development and decarbonization initiatives.

Does cybersecurity risk stifle corporate innovation activities?

Cybersecurity risk has become a major concern for organizations due to its potential impact on a variety of corporate activities. This paper examines the impact of cybersecurity risk on corporate innovation activities and uncovers two important channels: risk-taking and precautionary savings. Employing textual analysis and machine learning techniques to estimate firms' ex-ante cybersecurity risk for a sample of U.S. listed firms, we show that cybersecurity risk is negatively related to corporate innovation. We address potential endogeneity biases and find the results to remain unchanged. Furthermore, our results are robust to alternative proxies, truncation issues, and external cybersecurity risk. We uncover the mechanisms underlying the main result by showing that the effects are more pronounced for firms with lower tolerance to risk and lower cash savings. Innovations of smaller, financially constrained firms and firms belonging to high cybersecurity risk and technology-intensive industries are affected more.

Estimation of sectoral maladjustments linked to the need for innovative transformation of the Ukrainian entrepreneurial sector

The importance of supporting and promoting entrepreneurship development is due to its positive impact on economic growth, innovation processes, and the population welfare, the ability to contribute to the solution of modern challenges. In Ukraine, the entrepreneurial sector – the totality of large, medium, small, and micro-enterprises that carry out entrepreneurial activities in the country – faces problems of premature deindustrialization, slowing down innovation processes and their consequences in the form of a structurally weak, resource-based economy, which are further exacerbated in wartime conditions, when the country suffers from huge destruction and losses. Solving these problems requires a deep economic restructuring – from raw materials to industrial-innovative economy – in which the entrepreneurial sector will play a key role. The article aims to assess sectoral maladjustments of the Ukrainian entrepreneurial sector related to the need for innovative transformation as a basis for economic restructuring in modern and post-war conditions. The assessment was performed based on a set of proposed scientific and methodological foundations using indicators reflecting the level of investment in innovation and proving the effectiveness of enterprises' innovative activities, as of the pre-war period, to further (if relevant statistical information is available) compare the obtained estimates with the structural characteristics of the entrepreneurial sector during the war and post-war periods. It has been established that there are sectoral maladjustments linked to enterprises' economic opportunities in the technological sectors of the manufacturing and high-tech knowledge-intensive services, when it comes to implementing innovative transformation. Sectoral maladjustments in the levels of technological intensity of the sold innovative products in the entrepreneurial sector have been identified. It has been revealed that there are sectoral maladjustments in the levels of the entrepreneurial sector innovative effectiveness by types of economic activities (TEA), which vary significantly by industries depending on their specifics, economic status and other conditions. A grouping of TEA according to the level of innovative effectiveness (IE) has been made. It has been revealed that most of them belong to the group with a low level of IE, which indicates the unbalanced investment and innovation development of the Ukrainian entrepreneurial sector. A comparative analysis of the entrepreneurial sectors of Ukraine, innovatively developed countries, and peer countries in terms of indicators characterizing the state of technology-intensive industries development showed that the national economy lags behind both groups of countries and the need for its restructuring in the direction of increasing the share of gross value added of the manufacturing of high-technology and medium-high-technology industries. This research forms a scientific basis for substantiating and including appropriate actions in state policies to create favorable conditions for the modern and post-war recovery of the Ukrainian economy on a fundamentally new, competitive and innovative, basis.

Acquisitions and Technology Value Revision

Acquisition announcements coincide with upward value revisions for the target firms’ technology peers, which are not due to economic relations based on product market, supply chain, or geographical location. Such a phenomenon is robust across subsample periods, not specific to merger or technology waves, and not related to product-market structure and the unique innovation features of certain technology-intensive industries. Firms experience more dramatic value revisions when they have deeper technology overlaps with their targets, are more dependent on technology, or when a transaction features higher premium or greater technology overlap between the acquirer and target. Our mechanism analysis provides evidence that is primarily consistent with the acquisition-probability hypothesis whereby acquisition announcements elevate expected technology synergies and merger prospects for peers and partially in line with the enhanced-investment hypothesis that peers’ revaluations correlate with increased technology investments. We do not find any evidence in line with the competition-balance hypothesis that attributes peers’ value revisions to the change in industrial competition intensity. Overall, our results demonstrate that acquisition announcements disseminate novel information about the value of technology that is of common interest among firms with close technologies. This paper was accepted by Gustavo Manso, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4890 .

Digital finance and labor demand of manufacturing enterprises: Theoretical mechanism and heterogeneity analysis

With the new situations and new changes in the employment market in the new era, digital finance must highlight the employment-first policy in promoting high-quality economic development and enhancing targeted services for employment with financial resources. Based on the panel data of 298 prefecture-level cities in China from 2014 to 2019, and the big data on labor demand of manufacturing enterprises from Zhaopin as samples, this paper analyzes the impact of digital finance on the scale and structure of labor demand in China's manufacturing enterprises from the perspectives of theoretical logic and empirical evidence. The mechanism of action and the influence of heterogeneity are also systematically analyzed. Conclusions are drawn based on the research: Firstly, the development of digital finance can significantly and effectively promote the labor demand of manufacturing enterprises. Digital finance affects the scale of labor demand through financing constraints, and affects the structure of labor demand through operating costs, with positive effects on high-skilled labor demand. Secondly, considering the differences at the industry level and the city level, digital finance has a more significant role in improving the labor demand of enterprises in highly financial-dependent and technology-intensive industries and enterprises in small cities. Thirdly, compared with large and medium-sized enterprises and listed enterprises, small and micro-enterprises and non-listed enterprises are more likely to expand their labor demand thanks to the development of digital finance. Fourthly, digital finance is more conducive to promoting employment and increasing corporate demand for people who receive higher education, have no work experience, and apply for financial management positions. The conclusions are of great implications for us to give full play to the power of digital finance to eliminate impediments in the development of enterprises and increase support for them to stabilize and expand employment.

The impact of artificial intelligence on pollution emission intensity-evidence from China.

Artificial intelligence (AI) is a crucial component of sustainable economic development and an indicator of the next wave of technological progress. This study examines the effects and mechanisms of AI on the intensity of pollution emissions, using China as an example. Theoretical analysis demonstrates that the scale expansion effect and the technological innovation effect of AI can reduce the intensity of pollution emissions. In the meantime, AI can have a positive structural influence on reducing the intensity of pollution emissions through the upgrading of industrial structures. Therefore, we use panel data for 30 Chinese provinces from 2006 to 2019 to test the effect of AI on pollution emission intensity using a fixed effects model, employ explanatory variable substitution, endogenous analysis, regression after tailing, and eliminate related policy interference for robustness analysis. The results indicate that AI can significantly decrease the intensity of pollution emissions, with a 6.63% reduction for every 10% increase in AI utilization. We use the mediating effect model to conclude that AI can reduce the intensity of pollution emissions via the rationalization of industrial structure and advanced industrial structure, with the rationalization of industrial structure being the main mechanism. The examination of heterogeneity revealed that the implementation of AI in technology-intensive industries is an effective method for reducing the intensity of pollution emissions and that the positive impact of AI on the intensity of pollution emissions is more pronounced in the western region.

Enhancing export product quality through innovative cities: A firm-level quasi-natural experiment in China

China plays a significant role in the global product supply chain through its exports. To remain competitive, Chinese firms need to manufacture products cost-effectively. Revamping innovative cities can contribute to this goal, but empirical evidence in this area is limited. Therefore, this paper scrutinizes the innovative city pilot policy’s consequences on firms’ export performance and product quality. We employ the time-varying Difference in Difference (DID) model and harness a comprehensive firm-by-product level database to estimate the co-movement between the pilot intervention and the performance of the export product. Based on the findings, we unveil that a smart intervened city can significantly boost firms’ export product quality, which still holds after multiple robustness checks. Furthermore, innovative cities heighten the quality of the manufactured products when we consider firm-level (i.e., private, foreign, and ordinary trade enterprises), industry-level (i.e., low-polluting, capital-intensive, and technology-intensive industries), and regional (i.e., Middle, and Western regions) heterogeneities. In addition, the intervened smart city strategy impacts the efficacy of export product quality through policy and innovation-driven effects. Over and above, policymakers and experts should support state-of-the-art ideas while considering local conditions, providing guidance for decision-making in China’s innovative development strategy.