Artificial intelligence in digital pathology — time for a reality check
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The risk effects of corporate digitalization: exacerbate or mitigate?
This study elaborates on the risk effects of corporate digital transformation (CDT). Using the ratio of added value of digital assets to total intangible assets as a measure of CDT, this study overall reveals an inverse relationship between CDT and revenue volatility, even after employing a range of technical techniques to address potential endogeneity. Heterogeneity analysis highlights that the firms with small size, high capital intensity, and high agency costs benefit more from CDT. It also reveals that advancing information infrastructure, intellectual property protection, and digital taxation enhances the effectiveness of CDT. Mechanism analysis uncovers that CDT not only enhances financial advantages such as bolstering core business and mitigating non-business risks but also fosters non-financial advantages like improving corporate governance and ESG performance. Further inquiries into the side effects of CDT and the dynamics of revenue volatility indicate that CDT might compromise cash flow availability. Excessive digital investments exacerbate operating risks. Importantly, the reduction in operating risk associated with CDT does not sacrifice the potential for enhanced company performance; rather, it appears to augment the value of real options.
An artificial market model for the forex market
As financial markets have transitioned toward electronic trading, there has been a corresponding increase in the number of algorithmic strategies and degree of transaction frequency. This move to high-frequency trading at the millisecond level, propelled by algorithmic strategies, has brought to the forefront short-term market reactions, like market impact, which were previously negligible in low-frequency trading scenarios. Such evolution necessitates a new framework for analyzing and developing algorithmic strategies in these rapidly evolving markets. Employing artificial markets stands out as a solution to this problem. This study aims to construct an artificial foreign exchange market referencing market microstructure theory, without relying on the assumption of information or technical traders. Furthermore, it endeavors to validate the model by replicating stylized facts, such as fat tails, which exhibit a higher degree of kurtosis in the return distribution than that predicted by normal distribution models. The validated artificial market model will be used to simulate market dynamics and algorithm strategies; its generated rates could also be applied to pricing and risk management for currency options and other foreign exchange derivatives. Moreover, this work explores the importance of order flow and the underlying factors of stylized facts within the artificial market model.
Digital infrastructure construction and corporate innovation efficiency: evidence from Broadband China Strategy
Adopting the Broadband China Strategy as a quasi-natural experiment, we construct a multi-period Difference-in-Differences (DID) model to examine the impact of digital infrastructure construction on corporate innovation efficiency with panel data from Chinese listed companies between 2010 to 2022. Our findings indicate that the development of digital infrastructure significantly boosts corporate innovation efficiency. Mechanistic analysis reveals that financing constraints negatively moderates this innovation impact, while human capital positively moderates it. The effects of the Broadband China Strategy are particularly pronounced in non-state-owned enterprises, non-high-tech enterprises, and firms located in the non-eastern region of China. Our research provides important insights for enterprises seeking to enhance their innovation efficiency, while also offering strong empirical evidence on the role of digital infrastructure in fostering corporate innovation. Our study contributes to the literature on digital economy and innovation, with practical implications for policymakers and firms aiming to leverage digital infrastructure for sustained competitive advantage.
When the customers comes to you: mobile apps and corporate investment efficiency
Firms are increasingly shifting towards digital channels, yet the implications of this shift remain underexplored. Using a unique database of customer behaviors extracted from the top 2000 mobile apps developed by companies in China, this study investigates the impact of mobile apps on inefficient corporate investments. The results indicate that metrics such as active user count, usage duration, and app launch frequency can mitigate inefficient investments, notably by curtailing overinvestment. These findings survive a series of robustness checks such as altering the measures of inefficient investment, extending the analysis to include the top five apps, incorporating H-share listed firms, and employing instrumental variables regression. Moreover, the mechanism analysis indicates that mobile apps help reduce inefficient investments by lowering agency costs and relaxing financial constraints. Further analysis examines the business models of these apps (paid vs. free) as well as their reputation mechanisms, revealing that the pricing strategies of apps and the reputation of corporate brands also play a role in how the adoption of mobile apps affects inefficient investment.
Emotions and individual differences shape human foraging under threat
A common behavior in natural environments is foraging for rewards. However, this is often in the presence of predators. Therefore, one of the most fundamental decisions for humans, as for other animals, is how to apportion time between reward-motivated pursuit behavior and threat-motivated checking behavior. To understand what affects how people strike this balance, we developed an ecologically inspired task and looked at both within-participant dynamics (moods) and between-participant individual differences (questionnaires about real-life behaviors) in two large internet samples (n = 374 and n = 702) in a cross-sectional design. For the within-participant dynamics, we found that people regulate task-evoked stress homeostatically by changing behavior (increasing foraging and hiding). Individual differences, even in superficially related traits (apathy–anhedonia and anxiety–compulsive checking) reliably mapped onto unique behaviors. Worse task performance, due to maladaptive checking, was linked to gender (women checked excessively) and specific anxiety-related traits: somatic anxiety (reduced self-reported checking due to worry) and compulsivity (self-reported disorganized checking). While anhedonia decreased self-reported task engagement, apathy, strikingly, improved overall task performance by reducing excessive checking. In summary, we provide a multifaceted paradigm for assessment of checking for threat in a naturalistic task that is sensitive to both moods as they change throughout the task and clinical dimensions. Thus, it could serve as an objective measurement tool for future clinical studies interested in threat, vigilance or behavior–emotion interactions in contexts requiring both reward seeking and threat avoidance.
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