Pattanaporn Chatjuthamard

We explore the impact of artificial intelligence (AI) workforce adoption on shareholder value in the context of climate change, using stock market reactions to the Paris Agreement as a natural experiment. Based on a large sample of publicly listed U.S. companies and leveraging a novel measure of AI-skilled employees derived from large-scale resume data, we provide empirical evidence that AI workforce adoption significantly enhances cumulative abnormal returns during this critical policy event. Firms with greater climate change exposure derive smaller benefits from AI adoption, likely because of competing priorities between investing in AI initiatives and addressing climate-related strategies. Moreover, AI adoption enhances R&D efforts, signaling strong innovation potential, but raises concerns about resource allocation in highly profitable firms. Finally, we demonstrate that abnormal returns attributable to AI workforce adoption predict long-term firm value, emphasizing AI's strategic importance in driving shareholder value and adaptability in a climate-conscious economy.

Exploiting a takeover-threat measure that is less directly subject to managerial choice than firm-chosen governance provisions and a large sample spanning more than half a century, this study examines the association between hostile takeover threats and corporate debt maturity structure. Drawing on the hostile takeover index of Cain, McKeon, and Solomon (2017) and a sample covering the period from 1964 to 2020, we investigate whether variation in takeover threats is associated with differences in firms' debt maturity choices. We find that firms facing greater hostile takeover threats tend to rely more heavily on short-maturity debt, a pattern consistent with, although not demonstrating, the view that takeover threats and short-term debt may serve as complementary governance mechanisms that enhance outside monitoring and constrain managerial discretion. These associations remain robust across firm fixed-effects regressions, propensity score matching, entropy balancing, and instrumental-variable specifications. We also find that the association between takeover threats and shorter debt maturity is stronger among highly levered firms but weaker among firms with greater profitability, larger cash reserves, and higher capital expenditures. Because our design mitigates but does not eliminate endogeneity and alternative explanations, we interpret the evidence as a robust conditional association between hostile takeover threats and firms' debt maturity policies rather than as causal evidence.

Our study examines the influence of corporate integrity on capital structure decisions using a novel text-based measure derived from sophisticated textual analysis of earnings conference calls. Using a large sample of U.S. firms spanning 2001–2018, we document a robust negative association between corporate integrity and leverage. Our results are consistent with the interpretation that firms with stronger corporate integrity tend to adopt more conservative financial policies, viewing debt default as a serious ethical violation. We further analyze interaction effects and find that this negative association is significantly weaker for firms with substantial cash holdings and stronger liquidity positions, suggesting that financial flexibility mitigates the costs of leverage even for high-integrity firms. A comprehensive set of robustness checks, including propensity score matching, entropy balancing, and instrumental-variable analyses, supports the stability of our findings. Finally, we show that leverage attributable to corporate integrity is positively related to firm value, as measured by Tobin's Q. Overall, our study highlights the economically meaningful role of corporate culture, particularly integrity, in shaping capital structure choices and firm value.

This review examines how classified (staggered) boards affect non-financial corporate outcomes and how these outcomes inform the long-standing debate over the value of takeover defenses. We develop a framework based on four competing perspectives: the entrenchment view, the bonding hypothesis, the myopic-markets hypothesis, and the optimal-governance view. These perspectives generate distinct predictions for outcomes that are often obscured by aggregate financial measures such as Tobin's Q and stock returns. We review evidence on innovation, environmental performance, labor investment, corporate social responsibility, corporate culture, inclusion-related policies, and voting premiums, which we treat as direct evidence on managerial entrenchment rather than as a conventional non-financial outcome. The evidence suggests that staggered boards can promote innovation and labor-related outcomes by supporting long-term investment and stakeholder commitment, while also imposing costs in areas such as corporate culture, social capital and corporate social responsibility, inclusion, and private-benefit extraction. Environmental findings remain mixed. Our primary contribution is a mechanism-based synthesis that clarifies when, why, and for which stakeholders staggered boards are likely to create benefits or costs.

We examine how sustainability uncertainty influences firms' adoption of artificial intelligence (AI) by assessing whether companies expand their AI‐skilled workforce when facing ambiguity in environmental, social, and governance (ESG) conditions. Using the ESG‐based Sustainability Uncertainty Index (ESGUI) and the resume‐based AI workforce measure (Babina et al. 2024), we provide firm‐level evidence on this relationship. Employing fixed effects, matching techniques, and instrumental‐variable strategies exploiting exogenous variation in sustainability uncertainty, we find that higher uncertainty leads to a larger AI workforce, consistent with an adaptation hypothesis in which firms strengthen analytical capabilities under ambiguity. The effect is weaker among highly leveraged firms and stronger among firms with greater cash reserves and R&D intensity, indicating that financial flexibility and innovation capacity shape responses to ESG‐related uncertainty.

We examine how organizational maturity shapes firms' strategic responses to biodiversity challenges. We find that older firms exhibit significantly lower biodiversity risk, consistent with the view that organizational maturity facilitates capability development rather than constraining adaptation through inertia. We show that mature firms are systematically less exposed to biodiversity-related challenges. This effect is particularly pronounced for profitable firms with substantial capital investments, suggesting that accumulated resources enable mature firms to more effectively develop and deploy capabilities for managing biodiversity-related pressures. Our findings advance corporate life cycle theory by revealing how organizational maturity shapes environmental risk management and highlight how experience, resource accumulation, and stakeholder integration shape firms' strategic adaptation to emerging ecological constraints. Our study also validates the effectiveness of machine learning-based textual analysis in measuring complex corporate risks.

We analyze the evolution of climate change sentiment in firms over time and the role of independent directors using sentiment metrics developed by Sautner et al. (2023). These metrics, derived from advanced textual analysis of earnings calls, capture overall sentiment, positive sentiment, negative sentiment, and specific metrics for physical risk, regulatory risk, and new business opportunities. Our findings reveal a positive trend in sentiment, driven by increased optimism and reduced negativity. Regulatory risk sentiment shows rising optimism, while physical risk sentiment remains stable. Independent directors initially dampen optimism, but this diminishes over time, highlighting sustainability's strategic value. These findings suggest that climate-related corporate communication is increasingly driven by long-term strategic and economic considerations rather than symbolic statements. The results demonstrate the role of governance in shaping how firms respond to sustainability challenges, with implications for corporate strategy, investor assessment of climate disclosures, and regulatory policy design.

We examine whether Delaware incorporation enhances shareholder value, leveraging the historic and wholly unexpected election of Donald Trump in 2016 as a natural experiment that sharply minimizes endogeneity concerns. This unique research design allows for a cleaner identification of the causal effect of Delaware law. We find that Delaware-incorporated firms experienced significantly more positive stock market reactions to Trump's surprise victory, providing strong support for the "race to the top" hypothesis that attributes a value premium to Delaware law. This effect translates to an average gain of $6.14 million per Delaware-incorporated firm, or a total of $7.86 billion across all Delaware firms in the sample, over the three-day window around the election. The Delaware value premium is especially pronounced when managerial ownership is higher, in line with agency theory. We also investigate Trump's 2024 re-election and again find higher returns for Delaware firms, reinforcing our conclusion.

Purpose: This study examines the evolution of corporate innovation culture, focusing on how board independence and gender diversity impact this trend. It seeks to determine whether innovation culture has strengthened over time and to identify the role of board composition in fostering innovation. Design/Approach: Using a text-based metric from Li et al. (2021), this study analyzes over 50,000 firm-year observations. Temporal trend analysis and regression modeling assess shifts in innovation culture, with a focus on the moderating effects of independent and gender-diverse boards. Findings: The findings reveal a positive trend in corporate innovation culture, supporting the “innovation surge hypothesis.” Independent directors are shown to enhance long-term strategic thinking, while gender-diverse boards contribute varied perspectives, strengthening the culture of innovation. Originality: This study employs the machine learning-based approach developed by Li et al. (2021) to measure corporate innovation culture, providing fresh insights into how board diversity and independence sustain innovation. By leveraging this novel method, we contribute to the understanding of corporate governance’s role in fostering long-term innovative growth.

We examine how sustainability uncertainty influences firms' adoption of artificial intelligence (AI) by assessing whether companies expand their AI-skilled workforce when facing ambiguity in environmental, social, and governance (ESG) conditions. Using the ESG-based Sustainability Uncertainty Index (ESGUI) (Ongan et al., 2025) and the resume-based AI workforce measure (Babina et al., 2024), we provide firm-level evidence on this relationship. Employing fixed effects, matching techniques, and instrumental-variable strategies exploiting exogenous variation in sustainability uncertainty, we find that higher uncertainty leads to a larger AI workforce, consistent with an adaptation hypothesis in which firms strengthen analytical capabilities under ambiguity. The effect is weaker among highly leveraged firms and stronger among firms with greater cash reserves and R&D intensity, indicating that financial flexibility and innovation capacity shape responses to ESG-related uncertainty.