With the refinement of division of labor, manufacturing enterprises are gradually outsourcing non-core processes. This trend not only promotes the specialized development of productive service industries, but also brings opportunities for the upgrading of the manufacturing industry. In the context of the digital economy, digital technology has gradually become a key driving force for industrial integration and development. Based on this, under the conditions of the digital economy, the integrated development mechanism of productive service industry and manufacturing industry was taken as the research object, and a logistic evolution model was constructed to empirically study the integrated development dynamics of various comprehensive economic zones in China from 2019 to 2023. Research has found that the integration of productive services and manufacturing industries in various comprehensive economic zones presents regional differentiated development characteristics. The evolution coefficient of each comprehensive economic zone shows an increasing trend, indicating that the overall development of the integration of the two industries is improving. However, there are significant regional differences, manifested in three typical patterns: fluctuation type (Northeast and Southwest Economic Zones), convergence type (Southern Coastal and Northern Coastal Economic Zones), and convergence type (Eastern Coastal and Yellow River Midstream Economic Zones). Under the conditions of the digital economy, the evolution effect coefficients of various comprehensive economic zones exhibit three scenarios: identical trends, decreasing differences, and fluctuating trends. However, regional differences are significant, showing heterogeneous effects (promoting or inhibiting effects). That is, except for the southern coastal comprehensive economic zone, the digital economy has had varying degrees of hindering effects on the integrated development of the two industries in other comprehensive economic zones. By strengthening digital technology infrastructure and standardization, improving the data governance system, cultivating compound talents, and building an integrated ecosystem, the inhibitory effect of the digital economy on the integration of the two industries can be effectively alleviated, promoting the formation of a high-quality development pattern of "promoting integration with data and promoting innovation through integration". It provides an important basis for formulating differentiated regional digital economy development policies.

Under the global digital transformation, the integration of digital economy and real economy(IDR) is the key to promoting high-quality economic development. The establishment of the big data comprehensive pilot zones, as a major policy initiative in the big data field, has not been adequately examined for its impact on the IDR. Panel data from Chinese cities between 2011 and 2021 were utilized. The entropy-weighted TOPSIS method and a coupling coordination model were employed to measure the level of IDR across 227 cities. A staggered difference-in-differences model and a mediation effect model were applied to verify the promoting effect of the pilot zones on the IDR and to analyze its underlying mechanisms. Multiple robustness tests were conducted, with differential effects examined across city sizes, geographic locations, and establishment batches. The findings show that the construction of big data comprehensive pilot zones enhances the IDR, with effects strengthening over time. The promotion is more pronounced in medium-sized and larger cities, coastal cities, and among the second batch of the big data comprehensive pilot zones. The mechanisms involve the stimulation of technological innovation, increased entrepreneurial activity, and advancement of industrial structure upgrading. The policy effectiveness of the big data comprehensive pilot zones in fostering the IDR is highlighted, and the mechanisms which they operate are clarified. Empirical evidence from Chinese cities is provided, contributing to the understanding of big data policy impacts and factors influencing the IDR, to some extent alleviates the problem of insufficient attention to the IDR of the prefecture-level administrative regions in existing research and offers a new theoretical perspective on how big data policies can promote the IDR.

In April 2025, the United States launched a new round of global tax restructuring, promoting a "reciprocal taxation" mechanism toward multiple trading partners, which quickly triggered countermeasures from China. The institutional reshaping of global tax rules has thus emerged as a novel external shock, intensifying international capital's arbitrage incentives and profit-seeking behavior in the short term and inducing cyclical mismatches and structural shifts in cross-border capital flows. Compared with traditional analytical frameworks based on interest rate differentials and exchange rate fluctuations, such institutional shocks are more likely to generate nonlinear responses through changes in policy expectations and amplified market sentiment, making their dynamic evolution difficult to capture using conventional methods. Against this background, the asymmetric adjustment mechanisms of China's short-term cross-border capital flows under global tax competition was examined. Using quarterly data from 2008 to 2024, a multiple-threshold regression model and introduce generative artificial intelligence was constructed to perform semantic modeling of policy texts, thereby developing a tax policy semantic intensity index (TPSI). The results show that global tax shocks significantly alter the response structure of capital flows to interest rate and exchange rate expectations, exhibiting clear regime shifts and asymmetric effects. The TPSI demonstrates strong leading properties in identifying the direction of capital sentiment and flow dynamics, effectively compensating for the lag of traditional variables in capturing policy expectation changes. Moreover, under high semantic intensity regimes, the marginal effectiveness of existing macroprudential tools weakens, increasing the risk of "high-frequency decoupling" in short-term capital flows. Accordingly, it proposes establishing a cross-border capital early-warning system based on semantic expectation identification, proactively enhancing capital flow governance, and actively participating in the reconstruction of global tax rules to strengthen China's institutional resilience and safeguard its tax sovereignty within the international financial system.

Manufacturing upgrading not only aligns with the contemporary implications of the domestic-international "dual circulation" development paradigm, but also serves as a critical driving force in the process of modernization. Using urban panel data from 2005 to 2021, the opening of the "Yixin'ou" China-Europe Railway Express was treated as a quasi-natural experiment. A double machine learning model was constructed to examine the impact of international transportation corridors on manufacturing industry upgrading and its underlying mechanisms. Research has found that the opening of the "Yixin'ou" China-Europe Railway Express can significantly promote the upgrading of the manufacturing industry. Technological innovation and trade growth are important paths for the upgrading of the manufacturing industry affected by the opening of the "Yixin'ou" China-Europe Railway Express. The opening of the "Yixin'ou" China-Europe Railway Express has shown significant heterogeneity in its impact on the upgrading of the manufacturing industry. Specifically, cities located on the northeast side of the "Qing-Da Line", cities with a high degree of manufacturing industry agglomeration, and cities with strong local fiscal autonomy have a more significant upgrading effect on their manufacturing industry. It expands the economic effect dimensions of the China-Europe Railway Express, providing policy implications for the high-quality development of the "Yixin'ou" China-Europe Railway Express.

Digital empowerment of rural consumption is regarded as an important pathway to promote consumption-structure upgrading and to achieve high-quality economic development. Panel data from a longitudinal survey of Chinese rural households were used. The effects of short-video platforms on rural household consumption expansion and quality upgrading were examined by means of theoretical analysis and empirical tests. Short-video exposure was found to significantly increase per-capita total consumption of rural households, effectively achieving consumption expansion. The stimulating effect of short videos is most pronounced for leisure-oriented expenditures, such as cultural, educational, and entertainment consumption, thereby promoting consumption quality upgrading. Mechanism tests indicate that short videos operate through two channels: facilitating online shopping and altering subjective-status perceptions. Further analysis shows that the marginal effect of short videos on consumption first increases and then decreases as the consumption level rises. Significant heterogeneity observes across income groups in the impact on consumption structure, with stronger effects for households with migrant workers. Accordingly, policy recommendations are proposed. Rural residents' digital consumption capabilities should be enhanced. Innovation in short-video content should be guided. Rural e-commerce infrastructure should be strengthened and psychological-empowerment initiatives should be developed. Tailored guidance and precise policy measures should be emphasized to fully leverage short-video technologies in accelerating the expansion and quality upgrading of rural consumption.

The digital economy has become a significant engine for economic development, providing crucial momentum for the development of new quality productive forces. It is of great practical significance to delve into the pathways through which the digital economy empowers the enhancement of new quality productive forces. Based on the three dimensions of informatization, the internet, and digital transactions, an evaluation index system for the digital economy has been constructed. Using the fuzzy-set qualitative comparative analysis method, the impact and enhancement pathways of the digital economy on new quality productive forces from a configurational perspective were explored. The research finds that the digital economy empowers the development of new quality productive forces through three configurational pathways: the informatization impact-digital transaction impact-driven type, the informatization impact-digital transaction foundation-driven type, and the informatization-internet-digital transaction leadership type. Accordingly, it's demonstrated a valuble path that regions should leverage their unique advantages and resource endowments, fully recognize the synergistic interactions among variables, optimize the allocation of various elements, and collaboratively drive the development of the digital economy. This will enable high-quality empowerment of new quality productive forces and jointly promote the advancement of the regional digital economy and the enhancement of new quality productive forces.

In the era of the digital economy, digital transformation profoundly influences the sustainable development performance of enterprises. Listed manufacturing companies in China from 2010 to 2023 was selected as the research sample and constructs a scientific measurement framework for corporate sustainable development performance by integrating financial and environmental social responsibility performance. Through theoretical deduction and empirical testing, the results indicate that digital transformation directly fosters a synergistic improvement in both financial and environmental social responsibility performance, thereby enhancing overall corporate sustainable development. These findings remain robust after robustness checks. Furthermore, digital transformation indirectly boosts sustainable development performance by fostering green collaborative and green balanced innovations. The analysis also reveals that the moderating role of environmental dynamism varies by innovation type. It significantly moderates the relationship between green balanced innovation and corporate environmental social responsibility performance but has no significant effect on the link with financial performance. In contrast, regarding green collaborative innovation, environmental dynamism exerts a significant moderating effect on both financial and environmental social responsibility performance. It provides new empirical evidence regarding digital transformation and sustainable development in China and enriches the theoretical understanding of green innovation.

Clarifying the dynamic relationship between local finance and the real economy is an important prerequisite for preventing and resolving macro debt risks. Using government debt data at the city level from 2015 to 2023, the impact of local government debt on cross-regional investment by listed companies and its underlying mechanisms were empirically examined. The results showed that the growth of local government debt significantly suppressed the behavior of enterprises investing in other places. Two distinct mechanisms are identified: "crowding out" and "pulling". On the one hand, local government debt weakens the ability of enterprises to invest in other places through the crowding out of financial resources, resulting in a "crowding out effect" of investing in other places. On the other hand, local government debt enhances the local development stickiness of enterprises through infrastructure construction, generating a "pull effect" on local investment. Heterogeneity analysis found that the inhibitory effect of local government debt on enterprises' out of town investment is more significant in samples of state-owned enterprises, manufacturing industries, and cities registered in the second tier or below. Based on these findings, a theoretical foundation and policy insights are provided for mitigating local debt risks, facilitating internal economic circulation, and advancing the establishment of a new development framework.

Based on data from Chinese A-share listed companies between 2008 and 2022, the existence, mechanism, heterogeneity, and economic consequences of herd behaviour in data asset disclosure among Chinese listed firms was conducted. The findings reveal that firms' data asset disclosure levels are influenced by their industry peers, confirming the presence of herd behaviour in this disclosure practice. Specifically, a dual-level analysis of endogenous drivers and exogenous catalysts reveals that firms' competitive profit-seeking, symbiotic risk avoidance, and reputation management constitute the endogenous drivers of herd behaviour. Concurrently, shared analysts and common shareholders serve as pivotal social networks triggering such collective actions. Furthermore, the industry-specific clustering effect in data asset disclosure exhibits heterogeneity. It is more pronounced in regions with stronger data intellectual property protection, industries rich in data content, and firms with advanced digital application capabilities. Finally, it further examines the economic and non-economic consequences of this group-following effect in data asset disclosure. The findings indicate that such group-following not only improves industry financing environments but also enhances media attention across the entire sector. It expands the boundaries of studies on the determinants and herd effects of data asset information disclosure, highlights the positive impacts of corporate data asset disclosure, and provides crucial empirical evidence for enterprises making data asset disclosure decisions.

Currently, manufacturing enterprises in China are facing significant challenges due to overcapacity. Digital technological innovation is regarded as a critical driver for improving enterprise capacity utilization rates. Based on capacity utilization data for China A-share listed manufacturing firms from 2013 to 2023, digital technology patents were used to measure digital technological innovation to examine its impact on manufacturing firms' capacity utilization rate and transmission channels. The empirical results indicate that digital technological innovation, measured by the number of key digital technology patents, has a statistically significant and positive effect on enhancing enterprise capacity utilization rates. Mechanism analysis demonstrates that digital technological innovation primarily improves capacity utilization through decreasing corporate over-investment and reducing supply chain coordination costs. Heterogeneity analysis further reveals that the positive impact of digital technological innovation on enterprise capacity utilization is more pronounced in firms characterized by greater data resource endowments, higher industry technological dynamism, lower regional economic development levels and weaker market environments. The conclusions not only contribute theoretical support and practical implications for addressing overcapacity in the manufacturing sector but also provide meaningful insights into how digital technologies can facilitate the high-quality development of the real economy.