In order to clarify the effect and mechanism of servitization level and digital transformation on the performance of listed sporting goods manufacturing enterprises in China, the index of the degree of digital transformation is constructed based on the data of 31 sporting goods manufacturing enterprises listed on Shanghai and Shenzhen A shares and the New OTC Market in China, taking the proportion of service business income in enterprise operating income as the index of servitization level, by analyzing the semantic expression of national policy related to digital economy and collecting "digital" category keywords in enterprise annual report with the help of crawler technology, then, the influence of servitization level and digital transformation on enterprise performance is discussed, and whether digital transformation plays a moderating effect between servitization and enterprise performance is tested. The results show that the servitization level suppresses the performance of listed sporting goods manufacturing enterprises, and there is a "Servitization Paradox" phenomenon. The degree of digital transformation has a positive U-shaped impact on enterprise performance, and at the same time, digital transformation has a weak positive moderating effect on servitization level and enterprise performance.

In the context of promoting high-quality economic development, using digital technology to empower industrial transformation and upgrading, thus driving consumption growth has become a key problem that needs to be solved urgently. By using data at the prefecture-level cities in China from 2011 to 2020, the paper has discussed the influence of the digital economy on residents' consumption and its internal mechanism. Theoretical analysis and empirical test results have shown that first of all, the digital economy has significantly improved residents' consumption, and this conclusion is still valid after the endogenous test and robustness test. Secondly, mechanism analysis has shown that the digital economy can increase residents' consumption by promoting the upgrading of the industrial structure. Thirdly, the promotion effect of the digital economy on residents' consumption is heterogeneous between urban and rural areas and between different regions. Compared with urban, and eastern and central regions, the digital economy has a more significant incentive for residents' consumption in rural areas and western regions, indicating that its development is beneficial to narrowing the gap of consumption between urban and rural areas and between regions. Finally, the improvement effect of the digital economy on residents' consumption has marginal increment nonlinear characteristics, which is continuously strengthened with the upgrading of industrial structure. The above research conclusions can provide a theoretical basis for further improving the infrastructure of the digital economy, accelerating the integration of the digital economy with traditional industries, and building a consumer Internet.

Digital economy promotes the modernization of industrial structure by influencing the rationalization and upgrading of industrial structure through technical level and factor level; while excessive credit expansion hinders the modernization of industrial structure. This paper uses panel data from 31 jurisdictions in China to conduct empirical analysis, and finds that digital economy development shows a year-on-year rising trend, and there is a large gap between different regions. The conclusion still holds after the robustness test and regional heterogeneity analysis, thus enriching the understanding of mechanisms and regional differentiation of digital economy, credit expansion on industrial structure modernization.

This study examines whether and how minimum wage hikes affect workers’ strikes in the context of China. We show that minimum wage significantly increases strikes at the city-level, and this effect is mainly motivated by demands for unpaid wages and severance pay. Mechanism analysis reveals that workers’ strikes are caused by inevitable involuntary unemployment arising from wage hikes. In addition, the increase in workers’ strike activities is more significant in tertiary industries, which require a larger share of low-wage workers and in regions with a higher degree of digital economy and innovation. Our findings provide clear policy implications for policymakers concerned with minimum wage and unemployment.

The increasing awareness and adoption of technology, particularly artificial intelligence, are reshaping industries and daily life. This study explores how adopting artificial intelligence (AoAI) influences stock price crash risk for Chinese A-share listed companies between 2010 and 2020. The primary findings emphasize AoAI's significant role in reducing stock price crash likelihood, enhancing financial market performance, and mitigating manager opportunism. Further, the research identifies varied effects of AoAI on crash risk among different enterprise types, notably benefiting non-state-owned and non-foreign businesses. Additionally, the study finding supports the notion that financial analysts enhance transparency, reducing the risk of stock price crashes. These results underscore the Chinese government's role in shaping the digital economy. Overall, the study's findings remain consistent and robust across statistical methods like 2SLS, PSM, SysGMM, and instrumental variable analysis.

Using administrative universal business registration data as well as primary offline and online surveys of small businesses (including unregistered self-employments) in China, we examine (i) whether digitization helps small and medium enterprises (SMEs) better cope with the COVID-19 pandemic, and (ii) whether the pandemic has spurred digital technology adoption. We document significant economic benefits of digitization in increasing SMEs' resilience against such a large shock, as seen through mitigated demand decline, sustainable cash flow, ability to quickly reopen, and positive outlook for growth. Post the January 2020 lockdown, firm entries exhibited a V-shaped pattern, with entries of e-commerce firms experiencing a less pronounced immediate drop and a quicker rebound. Moreover, the pandemic has accelerated the digital transformation of existing firms and the industry in multiple dimensions (e.g., altering operation scope to include e-commerce, allowing remote work, and adopting electronic information systems). The effect persists more than one year after reopening, and is more pronounced for certain sectors, firms in industrial clusters, and areas with more digital inclusion but less financial efficiency, constituting initial evidence for the long-term impact of the pandemic and the supposedly transitory mitigation policies.

We study the income inequality among streamers using the administrative data of a leading Chinese live-streaming platform. The live-streaming technology enables a superstar to produce new entertainment products matched with demand and occupies a larger market share. Imagine an extreme case; the best streamer hosts live for 24 hours, earns all possible income, and leaves zero time for other streamers. Our data show that the income distribution of the highest-paid streamers follows Zipf’s Law and appears to be even more concentrated than any offline business: NBA top players, Forbes celebrities, and billionaires. Income inequality increased rapidly as the platform expanded from 2018 to 2020 — for example, the income share of the platform’s top 10 streamers increased from 14.82% to 45.15% as its revenue grew by 142%. To estimate inequality elasticity to the market size, we study four quasi-experimental shocks: potential market size proxied by economic development and Fintech coverage, quarter-end revenue spikes induced by the seasonal incentive regime, user surge induced by capital raising, and the Covid-19 lockdown in Wuhan. Gini coefficient elasticity ranges fromm1.3% to 10.6% estimated from the cross-city variations (local economic development and Covid-19 Wuhan lockdown); the time-series variations (quarter-end and user surge before capital raising) imply an elasticity ranging from 3.6% to 25.5%.

Many studies suggest a positive and monotonic relationship between technological progress and wage income inequality since 1980s for industrialized economies. We examine this topic in the context of the Chinese economy where new technologies like automation, AI and digitalization have witnessed worldís most rapid growth in the last decade. Surprsingly, we Önd an inverted U-Shaped relationship - a "Digital Kuznets Curve", using a panel dataset constructed in line with the newly published "2021 Categorization of Core Industries of Digital Economy". We then set out a task-based growth model with heterogenous human capital and occupational choice, and show that this hump-shaped relationship can emerge either by introducing an erosion e§ect of digitalization on worker ability that increasingly counterveils the skill-biasing e§ect, or by directly adding a dynamic learning cost that captures the externality of digitalization. Our study contributes to the understanding of the nature of digitalization in re-shaping labor market structure.

In the era of digital economy, the development and application of digital intelligence technology are changing rapidly, and human society has entered a new era where digital intelligence technology is rapidly advancing and playing an important role. Workers who master digital intelligence technology play a decisive role in the sustained and healthy development of enterprises, and the human capital possessed by workers has become the driving force for high-quality development of enterprises. The recognition and measurement of the value of human capital possessed by workers is the foundation and prerequisite for motivating workers, and the recognition and measurement of human capital value has become a core issue that urgently needs to be studied in human resource equity accounting. The article briefly introduces the development of human resource accounting theory, expounds that establishing human capital property rights is an important condition for the sustainable development of enterprises in the digital economy era, stimulates the potential of human capital, and is conducive to accelerating economic transformation and upgrading. The dynamic equity distribution mechanism is an important way to stimulate the vitality of human capital.

We build a two-country general equilibrium model to analyze the effects of cross-border data flows and pre-existing development gaps in data economies on each country's production and international trade. Raw data as byproducts of consumption can be transformed into various types of working data (information) to be used by both domestic and foreign producers. Because data constitute a new production factor for intermediate goods, a large extant divide in data utilization can reduce or even freeze trade. Cross-border data flows mitigate the situation and improve welfare when added to international trade. Data-inefficient countries where data are less important in production enjoy a ``latecomer's advantage'' with international trade and data flows, contributing more raw data from which the data-efficient countries generate knowledge for production. Furthermore, cross-border data flows can reverse the cyclicity of working data usage after productivity shocks, whereas shocks to data privacy or import costs have opposite effects on domestic and foreign data sectors. The insights inform future research and policy discussions concerning data divide, data flows, and their implications for trade liberalization, the data labor market, among others.