Industrial policy has returned to the centre of economic debate, yet evidence on how quickly and through which margins it reshapes real activity remains thin. We study firm entry, the margin through which resources first flow into a targeted sector, using a near-universe of 88,133 Chinese low-altitude economy (LAE) firms registered between 1966 and 2025. Over a compressed period the state raised the LAE from a niche concept to a national strategic priority, culminating in its first appearance in the 2024 Government Work Report. Monthly entry exhibits a sharp structural break: a supremum-Wald test dates the trend inflection to April 2024, immediately after the designation, while a level surge crystallises by October 2024 at roughly 2.3 times the counterfactual. The response is concentrated in the policy-named core segment, whose share of new entrants rises from 3% to 24%, and it diffuses spatially away from the incumbent Shenzhen-Guangzhou cluster. Entrants are small and thinly capitalised, a pattern consistent with speculative, subsidy-oriented entry.

The inflation shock in recent years has brought many problems that have altered the ways people buy and spend. Based on macro-economic indicators and transaction data, it can be observed that the expansion in nominal expenditure after the pandemic was a statistical illusion caused by the rise in commodity prices offsetting a large decline in discretionary demand due to the rigid stability of necessity volume. The inflation had different effects for different groups; according to Engel's Law, the low-income group's disposable income fell sharply and localized credit tightened, but wealthier families could use their accumulated funds to maintain a certain level of consumption by changing the quality of goods and services. At the same time, there was a considerable division in the commercial sector; the number of relatively unstable physical stores dropped, and continuous investment flowed into new-type online and offline enterprises. Finally, due to the prolonged price salience and economic anxiety, the psychological structure of consumers has been permanently changed by the framework of the availability hypothesis and procedural rationality; thus, defensive omni-channel behaviour, store-brand substitution, durable asset deferral and socioeconomic polarisation in debt repayment have occurred. Together, the changes are to be expected in the coming years in total demand, credit stability and macroeconomic fairness.

For major listed traditional automobile manufacturers in the European Union, green transition has moved from an emerging strategic choice to a necessary business transformation. This shift is mainly driven by increasingly strict carbon emission requirements and growing consumer acceptance of electrified mobility, which have pushed established carmakers to adjust their product structures, investment priorities, and long-term strategies. This study examines the association between electrification and financial performance among five major manufacturers from 2019 to 2024. Data are drawn from annual reports, vehicle delivery reports, and consolidated financial statements. Descriptive statistics, trend comparisons, and scatterplots are used to compare electrified vehicle sales share with operating profit margin, return on assets, and return on equity. Results show that higher electrification is generally associated with stronger operating margins and asset returns, while the relationship with shareholder returns is weaker. Firm-level patterns remain uneven, and continued growth in electrified sales does not always coincide with continuous financial improvement. Electrification may therefore support financial performance, but its value depends on how effectively the transition is integrated into wider business operations.

Digital knowledge management serves as a core driver of manufacturing firms’ digital transformation and R&D innovation. During digital upgrading, Chinese manufacturers commonly encounter fractured SECI knowledge spirals and stagnant internal knowledge circulation. Extant research largely focuses on cross-firm knowledge collaboration and external knowledge acquisition, yet few systematically investigate internal knowledge transformation bottlenecks within manufacturing Integrated Product Development (IPD) workflows from a SECI perspective. Taking the SECI knowledge spiral as the core framework, this paper integrates the Knowledge Navigator Model (KNM), the people–organizational process–technology barrier framework, and the multi-level Context-Mechanism-Outcome (CMO) analytical framework. Through qualitative benchmarking, it classifies manufacturers into four knowledge management maturity tiers, identifies three surface-level barriers, and untangles root causes across individual, organizational, and industry (external governance) levels. By benchmarking knowledge circulation mechanisms of online platforms and considering industrial data compliance constraints, this paper constructs a tripartite collaborative digital governance framework covering individuals, enterprises and governments. Three core barriers are identified: low practitioners’ willingness to share knowledge, inadequate corporate knowledge management strategies and formal institutions, and poor compatibility of digital tools. Hierarchical industrial data control constitutes a key external constraint. While online platforms’ automatic data logging and human-machine collaboration provide feasible references, such models cannot be directly transplanted to confidential manufacturing R&D scenarios. This paper extends SECI to manufacturing IPD, enriches multi-layer R&D knowledge flow analysis, and offers practical guidance for firms to build hierarchical compliant digital systems and internal knowledge incentives amid industrial data regulation.

Existing studies have reported mixed evidence on the link between Environmental, Social, and Corporate Governance (ESG) performance and stock returns across different markets, leaving the impact of ESG performance on stock returns inconclusive. Based on prior findings, this paper investigates the relationship between ESG performance and stock returns, exploring how ESG effects differ across market environments and the mechanisms driving these differences. In particular, it examines the effects of market development level, institutional environment, ESG information disclosure quality, investor structure, industry characteristics, and market conditions on the efficiency of ESG value transmission in stock markets. The results show that ESG performance can influence stock returns by reducing corporate risk, improving the information environment, and enhancing long-term corporate value, but this effect varies with market maturity, institutional environment, information quality, and industry characteristics, leading to cross-market heterogeneity. Future research can further strengthen comparisons between different markets, improve ESG evaluation and measurement methods, and, combined with stricter causal identification methods, explore the internal mechanisms by which ESG affects stock returns, thereby providing a theoretical basis for investment decisions and ESG regulatory policy formulation.

Decarbonization is a new mission that has become significant in recent years in the shipping industry. Due to the need for financial support, companies seek financing opportunities. However, new risks emerge during this process, and greenwashing is one of the most typical and crucial ESG risks. This paper, through a literature review, explores greenwashing risks within incentive and coercive financing mechanisms in the maritime industry. To be specific, this paper collects and synthesizes information on greenwashing behaviors from past research papers and annual reports of maritime industry institutions. This paper arranges common financing tools used in incentive and coercive mechanisms, and concludes the triggers, types, and possible solutions for greenwashing under the two mechanisms. This paper finds that a combination of incentive mechanism and coercive mechanism might result in a smaller chance of greenwashing.

Cross-border disruption is unavoidable, yet foreign retailers often cannot observe suppliers' recovery capability before contracting. This study analyzes auditable blockchain capability investment as both a productive input and a signal of supplier reliability. We develop a manufacturer-led Stackelberg game with asymmetric information that separates exogenous disruption, type-dependent baseline recovery, and investment-driven recovery. Backward induction yields closed-form pricing, demand, and complete-information investment decisions, after which we characterize minimum-cost separation, imitation by the low-reliability type, and the channel-efficiency boundary. A higher perceived delivery probability raises wholesale and retail prices as well as demand, but wholesale price merely responds to the belief induced by investment and is not an independent signal. A digital-cost advantage allows the high-reliability manufacturer to separate credibly, although a larger reliability gap may strengthen imitation incentives and increase the required investment. Because the manufacturer captures only part of the reliability gains accruing to the retailer, signaling investment can correct channel underinvestment until it exceeds the channel optimum. Universal subsidies may stimulate both adoption and imitation, whereas performance-contingent cost sharing better preserves screening incentives. The results inform supplier certification, reliability pricing, digital subsidies, and disruption-risk sharing.

This paper investigates whether digital transformation reduces the price risk exposure of agricultural enterprises. Agricultural firms are subject to pronounced seasonality, biological production cycles, weather shocks, product perishability, and frequent commodity price fluctuations, making their price risk more persistent than that of many manufacturing and service firms. Building on research into digital business strategy, smart farming, agricultural information systems, and financial risk exposure, this study constructs a panel data framework using Chinese A-share listed agricultural enterprises covering the period 2018–2022. Price risk exposure is measured as the sensitivity of firm value to changes in agricultural commodity prices. Digital transformation is primarily proxied by digital technology input scaled by total assets, and can be supplemented by a weighted digital transformation index when disaggregated indicators are available. Empirical evidence indicates that digitalization is significantly associated with lower price risk exposure: the standard deviation of product price fluctuations declines by 15.3%, the lag in market price transmission falls by approximately 23.7%, and highly digitalized firms record a 45.3% reduction in price risk exposure. This mitigating effect is stronger among firms with more complete digital systems and integrated operations covering production, processing, storage, logistics, and sales. The findings suggest that digitalization is not merely a technological upgrade, but a risk management capability that enhances market transparency, shortens decision lags, and strengthens resilience to price shocks.

This study examines which rural households translate digital financial inclusion policies into entrepreneurial action. A balanced 2010–2022 China Family Panel Studies panel is linked to provincial digital finance, digital infrastructure, policy-pilot, and macroeconomic data, yielding a 2012–2022 rural sample. The empirical strategy combines a pre-policy asset-constraint moderated difference-in-differences design, an event study, and an honest causal forest. Average effects of the aggregate digital financial inclusion index and binary policy exposure are unstable. Policy intensity, measured by the number of active related pilots in each province-year, significantly increases entrepreneurship among households with low baseline assets: each additional pilot raises their entrepreneurship probability by about 1.85 percentage points, while the effect for higher-asset households is insignificant. The result survives a stricter entrepreneurship definition and the exclusion of centrally administered municipalities. Post-policy effects for low-asset households reach 5.38–5.74 percentage points, and the complete effect is 7.63 percentage points for low-asset households with baseline internet access. Causal-forest profiles identify younger, healthier, digitally connected households with greater labor supply as high responders. The findings support targeted policy expansion centered on asset constraints and minimum digital access.

Supplier default risk represents a critical concern in supply chain management. This paper systematically reviews three quantitative approaches for supplier default risk assessment: weighted scoring, logistic regression, and Bayesian methods. The weighted scoring method constructs indicator systems with subjective or objective weights to rank suppliers by composite scores. Logistic regression models the log-odds of default as a linear function of supplier characteristics to estimate default probability. Bayesian methods, which are closely related to logistic regression, combine prior distributions with observed data to generate posterior probabilities, enabling dynamic updating and small-sample inference. Based on the comparative analysis, this paper proposes a multi-dimensional framework to guide method selection in procurement decisions. Research gaps and future directions are also identified, including dynamic updating mechanisms, integration of unstructured data, and the convergence of Bayesian methods with machine learning. Future research should explore real-time risk assessment and hybrid approaches that combine methods with machine learning to support more scientific supplier evaluation and enhanced supply chain resilience.