Volume 1 Issue 1
Published on April 2025This study examines the relationship between digital transformation (DT) and supply chain resilience (SCR) in small and medium-sized enterprises (SMEs) within the manufacturing sector of China’s Yangtze River Delta (YRD). Drawing on empirical data from surveys and case studies, the research investigates how digital technologies, such as IoT, big data analytics, and cloud computing, enhance SCR capabilities, including adaptability, agility, and risk mitigation. Results indicate a statistically significant positive correlation between DT adoption and SCR improvements, particularly in post-pandemic recovery scenarios. However, challenges such as financial constraints, skill gaps, and organizational inertia hinder SMEs’ digital transition. The study contributes to the literature by contextualizing DT-SCR dynamics in emerging economies and offers actionable insights for policymakers and SME managers.
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This study investigates the non-linear relationship between Environmental, Social, and Governance (ESG) performance and corporate financing costs among China’s A-Share listed companies. Utilizing panel data from 2015 to 2022, the research employs quadratic regression models to explore how varying levels of ESG performance influence debt and equity financing costs. Results reveal a U-shaped relationship: initial improvements in ESG performance reduce financing costs by mitigating risks and enhancing reputation, but beyond a threshold, excessive ESG investments lead to higher costs due to diminishing returns and operational complexities. The findings highlight the importance of optimizing ESG strategies for firms and policymakers in China’s evolving regulatory landscape.
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This study explores how cross - border e - commerce platforms innovate their business models under China’s "Dual Circulation" strategy, which prioritizes domestic economic resilience alongside international market integration. Through comparative case studies of Shein and Temu, the research analyzes how these platforms adapt their value propositions, supply chain configurations, and digital ecosystems to align with domestic demand stimulation and global expansion imperatives. Findings reveal that Shein leverages hyper - fast fashion cycles and AI - driven demand forecasting to balance domestic manufacturing agility with global consumer reach, while Temu capitalizes on ultra - low pricing and gamified social commerce to penetrate overseas markets while relying on China’s industrial clusters. The study highlights the role of platform - driven data analytics, decentralized supply chains, and policy alignment in achieving "dual circulation" objectives. Practical insights are offered for e - commerce firms navigating geopolitical and economic uncertainties.
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This paper explores the dynamics of AI adoption and its impact on labor market polarization through a game-theoretic model incorporating occupational substitution elasticity. By modeling the strategic interaction between firms and heterogeneous labor groups, we demonstrate how differences in substitution elasticity between high-skill, middle-skill, and low-skill occupations lead to divergent outcomes in wage distribution, employment, and firm profitability. The results reveal that when the elasticity of substitution for middle-skill jobs is high, firms have stronger incentives to automate these roles, exacerbating labor market polarization. The findings provide a theoretical foundation to understand how technological advances—particularly in artificial intelligence—reshape labor structures, and suggest implications for education policy, labor regulation, and corporate strategy.
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This study evaluates the impact of green finance policies on investment efficiency in new energy industries using a DEA-Malmquist index approach. By analyzing panel data from 30 Chinese provinces (2015–2022), the research quantifies dynamic changes in investment efficiency and decomposes them into technological progress, technical efficiency, and scale efficiency. The results indicate that green finance policies significantly enhance investment efficiency, with regional heterogeneity observed due to variations in policy implementation and resource endowments. The Malmquist index reveals that technological innovation driven by green financing is the primary contributor to efficiency gains. Policy recommendations are proposed to optimize green financial instruments and address inefficiencies in capital allocation.
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This paper employs a dynamic game-theoretic framework to analyze anti-monopoly regulation in digital payment markets, characterized by network effects, data-driven monopolies, and rapid technological innovation. By modeling strategic interactions between regulators and dominant platforms (e.g., Alipay, PayPal, Apple Pay), the study examines how multi-stage regulatory interventions—such as data-sharing mandates, interoperability requirements, and ex-ante prohibitions—shape market competition and consumer welfare. Using a combination of backward induction and numerical simulations, the analysis reveals that delayed or inconsistent enforcement amplifies monopolistic behaviors, while proactive, rules-based regulation fosters long-term competition. Case studies from the EU, China, and the U.S. illustrate the trade-offs between innovation incentives and market fairness. Policy recommendations emphasize adaptive regulatory frameworks, cross-jurisdictional coordination, and algorithmic transparency mechanisms.
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This study evaluates the poverty alleviation impact of rural inclusive finance under China’s Rural Revitalization Strategy, employing a Propensity Score Matching-Difference-in-Differences (PSM-DID) approach on panel data from five western provinces (2015–2022). By distinguishing between treated (villages with inclusive finance interventions) and control groups, we quantify the causal effects of financial inclusion on household income, consumption, and multidimensional poverty indices. Results indicate that inclusive finance reduces the poverty headcount ratio by 12.3%, with stronger effects in regions with higher digital financial penetration. Mechanism analysis reveals that improved access to credit and insurance products mediates poverty reduction, particularly for households engaged in agricultural entrepreneurship. The findings underscore the synergistic role of inclusive finance and rural revitalization policies, offering actionable insights for policymakers to optimize financial inclusion programs in underdeveloped regions.
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This study examines the relationship between organizational slack resources and disruptive innovation, with a focus on the moderating effects of absorptive capacity and executive risk appetite. Drawing on resource-based view (RBV) and dynamic capability theory, we hypothesize that different types of slack (financial, human, and operational) exert heterogeneous impacts on firms’ ability to pursue radical innovation. Using panel data from 1,200 technology firms across 15 countries (2010–2022), we employ hierarchical regression and three-way interaction models to test our hypotheses. Results reveal that human resource slack positively drives disruptive innovation, while financial slack exhibits an inverted U-shaped relationship. Absorptive capacity amplifies the innovation-enhancing effects of operational slack, whereas executive risk appetite moderates the link between financial slack and innovation outcomes. The findings advance scholarly understanding of slack resource allocation strategies and provide actionable insights for managing innovation portfolios in volatile markets.
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This study investigates how institutional distance shapes the location choices of China’s outward foreign direct investment (OFDI) in Belt and Road Initiative (BRI) partner countries. By extending the traditional gravity model with institutional variables, we analyze panel data from 63 BRI countries (2005–2022) to assess the nonlinear effects of formal and informal institutional gaps. Results indicate that moderate formal institutional distance (e.g., regulatory frameworks) positively influences OFDI, reflecting Chinese firms’ strategic arbitrage capabilities, while excessive informal institutional distance (e.g., cultural norms) acts as a deterrent. The model further reveals heterogeneous effects across state-owned enterprises (SOEs) and private firms: SOEs prioritize political proximity, whereas private firms leverage market-seeking motives in institutionally distant regions. These findings refine institutional theory in emerging economies and provide actionable insights for cross-border investment policy formulation.
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This study proposes a multi-agent evolutionary game model to optimize carbon pricing mechanisms in electricity markets under carbon neutrality constraints. By simulating strategic interactions among power generators, regulators, and consumers, we analyze how dynamic carbon pricing affects investment decisions, emission reductions, and market stability. The model incorporates heterogeneous agents with adaptive learning behaviors, including coal-fired plants (cost minimizers), renewable energy firms (innovation seekers), and policymakers (emission cap enforcers). Using China’s power sector as a case study (2020–2040), our simulations reveal that a hybrid carbon pricing mechanism—combining a floor price with tradable green certificates—achieves Pareto efficiency, reducing cumulative emissions by 34% while maintaining grid reliability. Sensitivity analysis identifies critical thresholds: when carbon prices exceed $80/ton, coal-to-renewable transitions accelerate nonlinearly. The findings provide a computational toolkit for designing adaptive carbon markets aligned with net-zero transitions.
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