Department of Accounting and Operations Management

Pacific-Basin Finance Journal 98 p. 103163-103163 Doi: https://doi.org/10.1016/j.pacfin.2026.103163

This paper examines the impact of price limits, a unique feature of market microstructure in the Chinese stock market, on managerial learning from stock prices. We find that price limits hinder the efficiency of managerial learning by reducing the informativeness of stock prices. To address endogeneity concerns and establish causal inference, we exploit a quasi-natural experiment based on the 2020 reform of price limit rules on the ChiNext board, which relaxes daily price fluctuation constraints. We find that this reform significantly increases firms' investment sensitivity to stock prices, suggesting that managers can extract valuable information from market prices better when trading restrictions are loosened. Further analysis indicates that the negative effect of price limits is more pronounced in firms with management shareholding, low-ability management, and less over-confident management. We also find that the price limits hinder firms' investment efficiency. Overall, our findings shed light on the economic consequences of price limit regulation and provide empirical evidence to inform ongoing policy discussions.

Review of Quantitative Finance and Accounting Doi: https://doi.org/10.1007/s11156-026-01503-y

Sustainability reporting has increasingly attracted investors’ attention by providing information critical for informed decision-making regarding a firm’s valuations. However, concerns regarding disclosure quality and the potential for greenwashing have heightened uncertainty around corporate valuations. This study examines how equity investors respond to abnormal sustainability disclosures. We employ textual analysis to generate disclosure measures and explore the relationship between abnormal sustainability disclosures and the cost of equity capital. Using a sample of Swedish listed firms, we find that abnormal disclosures related to uncertainty, negativity, litigiousness, and discretionary disclosure are positively associated with the cost of equity capital. These disclosures also increase cost of equity for firms with high idiosyncratic risk, which may act as a channel to increase the cost of equity capital. By contrast, abnormal positivity is negatively associated with the cost of equity capital among firms with fewer incentives for positive manipulation. Furthermore, investors’ sensitivity to abnormal disclosures is significantly greater following the implementation of the Non-Financial Reporting Directive. Our main findings are robust across alternative measures of abnormal disclosures and multiple robustness tests, indicating that equity investors generally perceive abnormal disclosures unfavorably, effectuating a higher cost of equity capital.

International Journal of Production Research p. 19-19 Doi: https://doi.org/10.1080/00207543.2026.2616663

Magma forskning og viten 29(1) p. 147-158 Doi: https://doi.org/10.23865/magma.v29.1532

The emergence of agentic artificial intelligence (AI) agents—autonomous entities that pursue objectives, execute workflows, and interact across enterprise applications—marks the advent of a digital workforce operating alongside human employees. These systems promise efficiency and innovation, but challenge established assumptions about accountability, transparency, and control within organizations. In this article, we focus on internal corporate governance, understood as the structures, processes, and practices through which organizations direct, control, and assure operational activities. We examine how governance can adapt to the rise of agentic AI through the lens of the Three Lines Model of internal auditing. Our analysis addresses three questions: (1) How does the digital workforce transform internal governance challenges? (2) How must the roles of operational management, risk and compliance, and internal audit be reconceptualized? (3) What practical recommendations can be derived from applying the Three Lines Model to the governance of agentic AI? Our analysis indicates that effective governance of this future workforce requires sustained collaboration across the three lines, as the risks posed by agentic AI systems often span functional boundaries and cannot be managed in isolation. We propose strengthening collaboration in five domains: clarifying accountability, integrating AI agents into control environments, defining the scope of assurance, building cross-functional competencies, and aligning regulatory interpretations and responses. Further research is needed to understand how these mechanisms are institutionalized in practice and how internal governance systems must evolve in increasingly AI-enabled organizations.

European Accounting Review

We find empirical evidence that the temporal increase in the number of institutional investors in the stock market is related to the decrease in the relevance of firms' earnings over time. This relation is: (1) apparent primarily in the short term, (2) unidirectionally Granger-causal, (3) time-invariant, (4) driven by transient and quasi-indexing institutions, and (5) obtained after controlling for time trends, several potential risk factors, and various stock market and economy characteristics. Overall, these results are consistent with the hypothesis that, due to an improvement in the risk sharing among institutional investors, the increase in their quantity in the stock market has weakened their incentives to use earnings information.