Band 14, Heft 2

“The deep integration of the innovation chain, industry chain, capital chain, and talent chain” is a major national strategy at present, and how to achieve deep integration among these different chains has important theoretical and practical value. However, empirical frameworks and measurement methods for quantitatively analyzing the industrial chain are still lacking. Building on the approach of Acemoglu et al . (2012), this study uses artificial intelligence to gather related transaction and equity investment data from AiQiCha, ShangShangCha, regional tendering and bidding public service platforms, and the annual reports of listed enterprises, and then employs a depth-first search algorithm to analyze the industrial chain positions of enterprises. On this basis, combining data from input-output tables and the theory of directed graphs, this study calculates the industrial chain linkage, and further integrates the industrial chain centroid degree to measure the degree of industrial chain integration. The empirical results demonstrate that enterprises’ integration into the industrial chain significantly improves their innovation performance via knowledge spillover and scale effects, and this improvement exhibits significant heterogeneity due to enterprise characteristics. Our analytical process and measurement results offer a relatively scientific quantitative analysis model to construct a modern industrial system and advance industrial chain development.

The slow relative productivity growth in the service sector is at the heart of “Baumol’s disease”, and the integration of services and manufacturing may offer a critical pathway to address this issue. This paper uses China’s tax survey data and OECD-ICIO input-output tables to examine how service inputs enhance the relative productivity of Chinese service firms and help overcome the “Baumol’s disease” trap. Additionally, it validates global patterns of this phenomenon through cross-country data. The results indicate that (1) increasing service sector input to the manufacturing sector improves the relative productivity of the service sector, narrows the wage cost gap between the two industries, and facilitates the crossing of the “Baumol’s disease” trap; (2) service sector input into high-tech manufacturing and into the manufacturing sector in developed countries is particularly effective in overcoming the “Baumol’s disease” trap, with producer services playing a significant role; (3) service sector input into manufacturing enhances competition, scale, and innovation within the service sector, which is vital for improving its relative productivity; and (4) cross-country data support the conclusion that service sector input into manufacturing can enhance the relative productivity of the service sector, establishing a global framework for overcoming the “Baumol’s disease” trap.

Based on the distance between digital technology input in the manufacturing industry and the final product, this study measures digital technology embedding section bias and employs cross-country panel data to study its impact on the Global Value Chain (GVC) postition. The results show that, first, the impact of digital technology embedding section bias on the manufacturing industry’s GVC position has a significant inverted U-shaped feature, and embedding digital technology in the midstream is more conducive to improving GVC position. Second, embedding digital technology in the midstream can amplify the effect of innovation boundary and capability expansion, cost reduction, and production network linkage strengthening, thereby effectively promoting the improvement of the GVC position. Third, further research shows that embedding digital technology in the midstream is more conducive to alleviating the import dependence of high-tech intermediate products and can more effectively improve the domestic value-added rate of exports and economic growth quality. The above conclusions have important policy implications for optimizing China’s digital development strategy and promoting GVC position.

Against the backdrop of production and sales globalization, a country can utilize its trade network position to secure greater benefits from international trade and gradually enhance its economic and trade influence. This process is inseparable from the rational allocation of production factors. As a crucial cornerstone of China’s economic growth, the industrialization system represented by the manufacturing sector has achieved significant development over an extended period. However, in recent years, influenced by multiple factors, the level of factor allocation within the industrial system has shown a rapid decline. Based on theoretical and empirical analyses, this study demonstrated that a rapid decline in the efficiency of production factor allocation has significantly lowered the position of Chinese industries in the global trade network, which is especially evident in the export trade network. A mechanism analysis revealed that an excessive decline in factor allocation efficiency exacerbates resource misallocation, increases production costs, and dampens regional entrepreneurial activity, thereby undermining industries’ positions in the global trade network. However, abundant human capital, the advancement of new industrialization, well-functioning market mechanisms, and proactive industrial policies significantly mitigate these adverse effects.

This study examines the impact of mergers and acquisitions (M&A) on the risk profiles of Chinese acquiring firms and the influence of gender diversity in leadership on risk-taking behavior. Analyzing 256 transactions from 2010 to 2023, the study finds that M&A generally increases the risk profile of acquiring firms. However, gender diversity in top management and on boards significantly reduces this risk. The presence of at least three women on the boards enhances this effect, supporting the critical mass theory. The findings suggest that promoting gender diversity can improve risk management and corporate stability. This study contributes to the existing literature by examining the impact of gender diversity on the risk profiles of Chinese acquiring firms in the specific context of M&A, offering valuable insights for policymakers and practitioners.

The motivational effects of tax incentives in promoting corporate digital transformation have attracted significant attention. Drawing on data from A-share listed companies between 2012 and 2022, this study employs a staggered difference-in-differences model based on the accelerated depreciation policy for fixed assets to examine the impact of tax incentives on corporate digital transformation. The findings indicate that the accelerated depreciation policy significantly enhances digital transformation in enterprises and exhibits robustness across various tests. The policy facilitates corporate digital transformation by improving corporate vitality, increasing innovation investment, and enhancing profitability. Moreover, its effects are more pronounced for enterprises in growth and decline phases, highly competitive industries, and firms facing significant financing constraints. These findings provide valuable insights for the government’s fiscal and tax reforms aimed at empowering corporate digital transformation.