Based on corporate social responsibility (CSR) reports publicly released by listed companies from 2008 to 2022, the textual content was analyzed using Named Entity Recognition (NER) and Term Frequency-Back Inverse Document Frequency (TF-BIDF) techniques, and the mechanism explored through which the signals transmitted by CSR disclosure affect stock price synchronicity. The analysis showed that two types of signals play important roles. Heterogeneous information content transmits firm-specific information, and the intertemporal consistency index reflects consistent communication. Both signals reduce information asymmetry between firms and the market, thereby decreasing stock price synchronicity. Further analysis indicated that signaling heterogeneity is more significant in non-state-owned enterprises. Higher levels of social responsibility fulfillment strengthen the effects of heterogeneous content and consistency index, while higher disclosure levels may weaken the signaling effect. Robustness tests were conducted by replacing samples and applying the PSM-DID and Heckman models. From the perspective of signal characteristics, internal content analysis and external longitudinal comparison were employed. The findings provide a new perspective on the impact of CSR reports on market performance. The results also offer theoretical support for improving information efficiency in China's capital market and policy suggestions for enhancing the CSR disclosure system.

Deepening the division of labor among Small and Medium-sized Enterprises (SMEs) is a key way to enhance their core competitiveness and an important path to improve the safety and resilience of industrial chains. Against the backdrop of the digital economy, digital transformation not only helps large enterprises achieve standardized restructuring but also profoundly impacts the division of labor methods of SMEs. Among them, specialized, refined, differential and Innovational ("SRDI") enterprises can play an exemplary and leading role in the specialized development of other SMEs. Based on data from A-share listed "SRDI" enterprises from 2000 to 2023, the diverse impact mechanisms of digital transformation on the vertical specialization of SMEs were empirically examined from the perspectives of cost, innovation, and financing. The results reveal that digital transformation significantly improves the vertical specialization of SMEs. This conclusion is still valid after a series of robustness tests. The mechanism analysis finds that digital transformation deepens vertical specialization by reducing external transaction costs, enhancing innovation capabilities, and alleviating financing constraints. The heterogeneity analysis indicates that this promoting effect is more pronounced in non-labor-intensive enterprises, state-owned enterprises, and enterprises located in regions with higher marketization levels and in eastern China. The influence mechanism of digital transformation on the division of labor of SMEs is revealed. It conclusions are considered to provide practical pathways for SMEs to deepen their division of labor. Implications are offered for the formulation of policies related to the digital transformation and high-quality development of SMEs.

Advanced smart manufacturing factory construction is an important path to fully tap the potential of digital and intelligent technologies in empowering high-quality economic development, and an essential foundation for developing newquality productive forces. Samples are taken from international and domestic advanced smart manufacturing factories across 31 provinces (Due to the lack of data, the statistical data mentioned here do not include the Hong Kong Special Administrative Region, the Macao Special Administrative Region and Taiwan Province.). From the perspective of business environment, the combined method of NCA and fsQCA was adopted to analyze regional differences in the construction of international and domestic advanced smart manufacturing factories affected by multiple concurrent factors. Three key findings are identified. Three identical business environment ecological driving models are confirmed for the efficient construction of both international and domestic advanced smart manufacturing factories, namely the market-driven innovation model, the innovation model relying on finance and law, and the government-assisted innovation model relying on the rule of law and human resources. An asymmetric relationship is found between the business environment driving models for inefficient construction and those for efficient construction of international and domestic advanced smart manufacturing factories. Innovation environment is verified as a core condition in all business environment configurations. Noteworthy theoretical and practical implications are provided for optimizing the business environment to fully stimulate the smart manufacturing vitality of market entities.

Digital transformation serves as a key driver of competitive advantage and plays a vital role in advancing green and high-quality development. Based on the Technology-Organization-Environment (TOE) framework, a meta-analysis of 41 empirical studies (covering 68602 independent samples and 41 effect sizes) was conducted to investigate the relationship between digital transformation and corporate green innovation, focusing on the technological, organizational, and environmental dimensions. The moderating role of various contextual factors were then examined. The findings reveal digital transformation is strongly correlated with corporate green innovation. The influence of digital transformation on green innovation is not significant in different industry. Each dimension (technology, organization, and environment) exerts a significant positive influence on green innovation. Notably, digital transformation's impact on green innovation is more pronounced within firms rooted in Western cultural contexts. The relationship is stronger when digital transformation is assessed using subjective measures. Higher levels of green orientation heighten the efficacy of digital transformation in driving green innovation. It augments and refines existing literature, offering valuable insights for future vertical and contextual inquiries. Furthermore, it furnishes managerial foundations for advancing green innovation within enterprises amid the era of digital transformation.

The social network analysis method was adopted to dynamically describe the structural characteristics of industrial linkage networks using input-output table data of 42 industrial sectors in China from 2012 to 2020, and to establish a network dynamics model based on stochastic actors to identify and analyze the evolution mechanism of industrial linkage networks. The results show that there is no significant difference in the holistic indicators of the 42 industrial networks, and the networks as a whole tend to be stable. Chemical products as well as transportation, warehousing and postal services have been at the center, and the secondary industry, especially the manufacturing industry, is at the core of the network. From 2012 to 2015, China's industrial linkage network could be divided into four segments (bidirectional spillover segments Ⅰ and Ⅱ, broker segment, and net beneficiary segment), and in the period of 2017-2020, the broker segment disappeared, and the net beneficiary segment disappeared. In 2020, the broker segment disappeared and the main beneficiary segment appeared, and the industrial linkage effect within the segment became more obvious. Industry-linked activities are concentrated in the manufacturing industries of metal products, chemical products, communication equipment, computer and other electronic equipment, and electrical machinery and equipment, and the service industries of wholesale and retail, transportation, storage and postal services, and information transmission, software and information technology services. The relative importance of endogenous structural factors is 53.11%, which plays an important role in the evolution of network relationships, the negative out-degree effect indicates that industries with more interconnected relationships are difficult to develop new relationships, and the transmission effect indicates that there is a trend of continuous refinement of the industry, and the relative importance of exogenous attribute factors is 46.89%, of which the influence of labor is the most significant, accounting for 20.52%.

The new quality productive forces brings new goals, new connotations and new needs for the agricultural development of China. A theoretical framework was proposed for the new quality productive forces of agriculture based on three dimensions, labor factor demand, structural carrying and functional orientation, and on the basis of Marxian political economy. Through the innovative combination of fuzzy comprehensive evaluation and entropy weight method, an evaluation system of agricultural new quality productive forces covering 33 specific indicators is established. Based on the evaluation results and the obstacle degree model, a comprehensive analysis was conducted on the development status, the main obstacle factors, and spatial and temporal variations of agricultural new quality productivity in 30 provinces (Due to the lack of data, the statistical data mentioned here do not include the Tibet Autonomous egion, the Hong Kong Special Administrative Region, the Macao Special Administrative Region and Taiwan Province.) and seven geographic regions of China. The results show that the level of new agricultural productivity in China as a whole shows an upward trend and maintains an average annual growth rate of 5.67%, but the northwest and southwest regions are constrained by the economic foundation and resource endowment, and the development is lagging behind. Nowadays, the level of industrial carrying capacity, labor materials and labor objects are insufficient, which become the main factors restricting the development of agricultural new quality productive forces. Finally, a cross-regional modular solution is proposed including four strategies such as transforming economic advantages into technological advantages, cracking the transmission mechanism of different obstacle factors, promoting the rapid development of new agricultural productivity.

Within the context of the new development pattern, it is examined whether innovation-driven policies, represented by National Independent Innovation Demonstration Zones (NIIDZs), can effectively function as "testing grounds" for innovation-driven development and thereby facilitate the cultivation and enhancement of corporate new quality productive forces. Based on panel data from Shanghai and Shenzhen A-share listed companies in China between 2011 and 2022, the internal causal relationship between NIIDZ policies and corporate new quality productive forces was explored. It is found that the establishment of NIIDZs significantly promotes the development of corporate new quality productive forces, a conclusion that remains robust after a series of tests. Further mechanism analysis indicates that the establishment of NIIDZs empowers the cultivation of corporate new quality productive forces by advancing corporate digital transformation and enhancing the level of substantive innovation. Heterogeneity analysis reveals that the positive effect of NIIDZ establishment varies significantly across enterprises with different ownership structures, technological attributes, scales, factor intensities, and regional strategies. The findings are helpful for deepening the understanding of innovation-driven policies and corporate new quality productive forces, and provide effective empirical evidence for fostering new quality productive forces in Chinese enterprises.

As main innovation entities, firms cannot be separated from technological interaction with other firms in carrying out their technological innovation, and are more deeply influenced by the technology spillover effect. Based on data of 3737 Shanghai and Shenzhen A-share listed firms in China from 2010 to 2021, a panel model was constructed to analyze the impact of inter-firm technology spillovers and technological innovation outputs of technology spillover-receiving firms, and to examine the moderating effects of digital technology application and market competition on the relationship between them, as well as their joint moderating effect. The results show that inter-firm technology spillovers contribute to improving the technological innovation outputs of spillover-receiving firms. Both digital technology application and market competition exert a positive moderating effect on this relationship. Additionally, the moderating effect of digital technology application also depends on the market competition. In a further analysis, the positive effect of inter-firm technology spillovers on the technological innovation outputs of spillover-receiving firms is found to be more pronounced among state-owned enterprises, high-tech industries, regions with high levels of economic development, and inter-competitive firms. It findings provide micro-level evidence for explaining the relationship between inter-firm technology spillovers and technological innovation outputs of spillover-receiving firms, and provide practical implications for the governments and firms.

To uncover the "black box" of the complex process through which enterprises evolve from achieving a single breakthrough innovation to successfully constructing an innovation ecosystem, thereby realizing multiple breakthrough innovations, a longitudinal single-case analysis focusing on DJI Innovations, a high-tech enterprise was conducted. The mechanisms underlying the construction of an innovation ecosystem driven by breakthrough innovations was explored. The findings reveal three key insights. First, high-tech enterprises' drive to construct an innovation ecosystem through breakthrough innovations follows a spiral iterative pattern "technology-oriented breakthrough innovation → commensalistic innovation ecosystem → market-oriented breakthrough innovation → parasitic symbiotic innovation ecosystem → value-oriented breakthrough innovation→mutualistic symbiotic innovation ecosystem." Second, a firm's core capabilities serve as a crucial bridge linking breakthrough innovations and the innovation ecosystem, while the spillover effects stemming from these breakthroughs constitute the underlying logic that elucidates the relationship between the two. Third, technological leadership and diffusion are prerequisites and key factors in the formation of core enterprises within an innovation ecosystem. It enriches the theoretical research of enterprise innovation ecosystem from the perspective of the relationship between enterprise breakthrough innovation and innovation ecosystem, puts forward the possibility of high-tech enterprises to achieve multiple breakthrough innovations, and provides ideas for high-tech enterprises to lead from technology to innovation system.

How to effectively enhance urban economic resilience at the policy level is a topic worth paying attention to. A staggered difference-in-difference model was employed to integrate innovative city construction, industrial structure, and urban economic resilience into a unified framework. Using data from 283 prefecture-level and above cities in China from 2010 to 2022, the impact of innovative city construction on urban economic resilience was explored, and the mediating effect of industrial structure upgrading was examined. The findings indicate that innovative city construction significantly promotes urban economic resilience, and the conclusion remains valid after a series of robustness tests. Mechanism analysis shows that innovative city construction significantly promotes the upgrading of industrial structure, thereby boosting local economic resilience. The impact path includes two aspects: promoting industrial structure upgrading and rationalization, with the latter being the primary mechanism. Heterogeneity analysis shows that the policy effect is more significant in western cities, non resource-based cities, and large-scale cities.