Community-based natural resource governance is often promoted in the name of sustainability, yet long-term outcomes remain elusive. This study examines the impact of various types of trust as the underpinning factor for the long-term resilience of collaborative resource governance. Using a four-type trust framework, dispositional, affinitive, rational, and procedural, the study compares trust trajectories across the prior to-, during-, and post-project phases of matsutake mushroom management in two communities within the S National Protected Area, Yunnan Province, China. Drawing on qualitative interviews and comparative case analysis, the study finds that while neither community sustained co-management mechanisms in full, X Village retained partial continuity through embedded procedural and rational trust. In contrast, Y village experienced accelerated institutional decline after project withdrawal, as market changes and weak enforcement undermined collective norms and trust in formal structures. These findings underscore that institutional resilience is shaped not only by institutional design but also by the evolution and interaction of trust types over time. By tracing trust trajectories across project stages, this study contributes a micro-level explanation of how trust mediates post-project governance outcomes. It emphasizes the importance of layering trust and embedding it within local social and institutional practices. The findings highlight the need to consider how co-management strategies can support trust continuity after project withdrawal, particularly by acknowledging the underlying structural conditions that shape trust resilience.

Cultural tightness measures the extent to which individuals behave according to the broader values shared by other members in society. While cultural tightness has been studied extensively in the context of individuals’ behavior and (cross) country-level outcomes, much less is known about the explanatory power it holds in the setting of organizational structures. Motivated by the ambiguous relationship between cultural tightness and population-level gender equality documented by prior literature, we investigate whether cultural tightness helps explain board gender diversity levels in China. Rooting our hypotheses in institutional theory and the contextual governmental reforms of China, we leverage a large sample of Chinese A-share listed firms and document that firms located in culturally tight provinces have higher levels of board gender diversity. Further analyses reveal that cultural tightness in China partially offsets the impact of more traditional Confucian values, and the relationship becomes more pronounced in settings where firms can realize higher legitimacy gains from adopting women on their boards. Finally, we counter potential critiques of window dressing, by demonstrating that in culturally tighter areas women are more likely to be higher educated, have more experience abroad, hold more board positions, and are less likely to be independent directors.

Purpose – Estimates disclosure of human capital management for Chinese listed companies. Investigate the patterns ofthe disclosure of human capital management acrossindustries and regions. Examine the determinants of human capital management disclosure in China. Examine the association between human capital management disclosure and firm performance. Design/methodology/approach – We employ natural language processing techniques on annual reports’ management discussion and analysissections.We construct exposuremeasuresforten human capitalmanagement dimensions and synthesize them into one comprehensive measure of human capital management disclosure. We conduct empirical analysis on the measure using a sample of Chinese listed companies during 2009–2022. Findings – We construct a measure of human capital management disclosure for 5,153 Chinese companies during 2009–2022. We find that firms with high HCM disclosure are more labor intensive and have more cash holdings and R&D expenditure but have lower sales growth, market-to-book ratio and leverage. HCM disclosure is associated with better future accounting performance but poor future market valuation. There are substantial variations in HCM disclosure across industries, geographic regions and ownership types. HCM disclosure has increased significantly during the COVID-19 pandemic. Social implications – The increased HCM disclosure and its association with firm operating performance and market valuation indicate the relevance of HCM in corporate management and underscore the need for more robust and standardized disclosure of HCM in China. Our findingssupport recent regulatory efforts by CSRC to enhance the transparency and accountability in HCM disclosures and advocate for more explicit and specific HCM disclosure requirements in the future. Originality/value – We propose a quantitative measure of human capital management disclosure, which can be modified to apply to other markets. We construct a comprehensive, ready-to-use dataset for HCM disclosure for Chinese listed companies and conduct descriptive analysis on the dataset. We identify the patterns of human capital management disclosure and its determinants in China.

This paper examines the relationship between award-winning CEOs and the levels of innovation investment in Chinese-listed companies. The findings indicate that CEOs who have received awards are more likely to foster increased corporate innovation. Additionally, these award-winning CEOs are associated with enhanced long-term operating performance for their firms and reinforce the link between current R&D investments and future operational success. Ultimately, our results suggest that CEO awards can enhance corporate innovation through two primary channels: first, by attracting investors, thereby alleviating financing constraints, and second, by promoting greater engagement from academics and overseas talent in innovation initiatives.

We examine whether firms with high organization capital (OC) are more likely to purchase Directors’ and Officers’ (D&O) liability insurance, using a panel of Chinese A-share listed companies from 2009 to 2021. We document a robust positive association between OC and the propensity to carry D&O insurance. The effect remains statistically and economically significant after controlling for firm characteristics and employing multiple identification strategies to address endogeneity. We propose two economic channels through which OC affects D&O insurance demand, namely, agency and information asymmetry. Consistent with these mechanisms, we find that the positive OC–D&O relationship is significantly stronger in firms with weaker internal governance and those facing opaquer information environments. Additional cross-sectional analyses show that this effect is concentrated in privately-owned firms and in regions with more developed market institutions, suggesting that external pressures accentuate the value of insuring key decision-makers. Our results are robust to alternative model specifications and remain stable after using propensity score matching, instrumental variable approaches, and the Heckman two-stage model. Overall, the findings highlight OC as a critical internal driver of corporate insurance decisions. Firms with substantial intangible assets strategically obtain D&O coverage to strengthen governance and reduce information frictions, especially in emerging markets like China where formal investor protections are still evolving.

This study examines whether China’s Industrial Internet pilot policy (2017–2023) enhances firm innovation and explores the underlying mechanisms. Exploiting the staggered rollout of the policy across provinces as a quasi-natural experiment, we find that Industrial Internet adoption significantly increases firms’ innovation output. Mechanism tests show that the policy promotes knowledge accumulation, strengthens innovation persistence, and improves human capital allocation. We also document positive economic consequences, as treated firms earn higher returns to innovation. The effects are stronger for capital-intensive firms, those located in regions with advanced digital infrastructure, and firms undertaking joint or substantive innovation activities. Overall, the evidence highlights the Industrial Internet as an effective catalyst for firm innovation by deepening R&D capability and facilitating cross-industry knowledge flows.

Data-factor marketization (DFM) serves as a critical driver for cultivating manufacturing-enterprise new-quality productive forces (ME-NQPF), fundamentally supporting China's transition toward high-quality economic development. Integrating matched panel data from A-share listed Chinese manufacturing firms (2011–2022) with the staggered establishment of regional data trading platforms as a quasi-natural experiment, this study employs a multi-period difference-in-differences (DID) framework to identify the causal impact of DFM on ME-NQPF. Empirical results demonstrate that DFM significantly enhances ME-NQPF, a finding that remains robust across alternative specifications and endogeneity treatments. Mechanism analysis identifies enterprise digital transformation as a pivotal mediator in this relationship, while competitive intensity is found to positively moderate the productivity gains from data marketization. Heterogeneity analysis further indicates that these effects are most pronounced among non-state-owned enterprises, technology-intensive sectors, and firms situated in China's eastern and central regions. These findings suggest that institutionalizing data-factor markets and accelerating digital integration are effective mechanisms for optimizing resource allocation and sustaining advanced industrial productivity.

This paper examines the interactional phenomenon where an institutional complainee initiates a complaint and becomes a co-complainant with their original complainant against a third party that is proposed to have caused grievances to both participants. Institutional complainees initiate their third-party complaints when their complainants repeatedly refuse to affiliate with their attempts to shift responsibility or their proposed solutions. This shift from being the complainee to being a co-complainant is regularly accomplished through practices in which the institutional complainee: 1) produces implicit counter-complaints; 2) partitions complainants and themselves as sharing similar identities; and 3) highlights and upgrades their own grievances. Once complainants affiliate with their complaints, institutional complainees attempt to end the complaint sequences. The interactions end with a sense of solidarity sustained between the participants, even though no satisfying solutions are offered to the original complainants. The findings suggest that institutional actors can make relevant their non-institutional identities and go against what is expected of them as institutional actors to achieve the institutional task of directing blame away from their institutions. Recorded phone conversations between local residents and various institutional actors during COVID-19 lockdowns in China serve as data for this study.

Straddle Option is a financial trading tool that explores volatility premiums in high-volatility markets without predicting price direction. Although deep reinforcement learning has emerged as a powerful approach to trading automation in financial markets, existing work mostly focused on predicting price trends and making trading decisions by combining multidimensional datasets like blogs and videos, which led to high computational costs and unstable performance in high-volatility markets. To tackle this challenge, we develop automated straddle option trading based on reinforcement learning and attention mechanisms to handle unpredictability in high-volatility markets. Firstly, we leverage the attention mechanisms in Transformer DDQN through both self-attention with time series data and channel attention with multi-cycle information. Secondly, a novel reward function considering excess earnings is designed to focus on long-term profits and neglect short-term losses over a stop line. Thirdly, we identify the resistance levels to provide reference information when great uncertainty in price movements occurs with intensified battle between the buyers and sellers. Through extensive experiments on the Chinese stock, Brent crude oil, and Bitcoin markets, our attention-based Transformer-DDQN model exhibits the lowest maximum drawdown across all markets, and outperforms other models by 92.5% in terms of the average return excluding the crude oil market due to relatively low fluctuation.

In this paper, we design two chapters to discuss trade dynamics with heterogeneous fluctuations, contributing new insights to macroeconomic issues related to international trade. In the first chapter, we model general exchange rate fluctuations through stochastic processes and analyze the impact of heterogeneous price shocks on export competitiveness. We find that monetary policy and innovation both show positive effects on export trade, while monetary policy stabilizes exchange rate fluctuations to comprehensively boost provincial export competitiveness, innovation reduces its reliance on exchange rate mechanisms. The optimal policy according to exchange rate fluctuations aims to solve the wealth distribution of exporters, and it suggests that optimal policy should promote dynamic transitions in trade patterns rather than maintain existing comparative advantages in heterogeneous trade structures. In the second chapter, we model labor market fluctuations and the ability to utilize production factors through stochastic processes, and we analyze the impact of heterogeneous aggregate production shocks on general international trade. We find that labor market fluctuations only benefit international trade under the cooperation policy. Moreover, for both sanction and cooperation policy scenarios, positive shocks (i.e., shocks where average wage growth in the labor market exceeds unemployment) strengthen their impact on import trade while weakening their impact on export trade, and vice versa. Regarding the theories proposed in these two chapters, we prove them through empirical analyses using the provincial data of China.