Survive the economic downturn: operating flexibility, productivity, and stock crash
Journal of Operations Management, 2025

Yang Li, Xiaojun Wang, Fangming Xu, Tuan Ho Operating flexibility supports a firm's resilience strategy during challenging times by enabling them to promptly cut down operating costs associated with unproductive resources. We employ a real options model to formalize this insight. Our empirically grounding analytics motivate a firm-level proxy for downscale operating flexibility (FLEX), which effectively captures the adjustment frictions across different contexts of firms' operations. Using U.S. data between 1961 and 2020, we show that operating flexibility mitigates the risk of stock price crashes, especially during periods of economic recession. Consistent with the loss-curtailment mechanism, the operating flexibility effect is more pronounced for firms with lower productivity/profitability or higher operating leverage and is further amplified during longer and more severe recessions. Managers may avail themselves of our well-tested empirical measure of operating flexibility to guide their efforts in building a more resilient operations structure.

Does real flexibility help firms navigate the Covid-19 pandemic?
The British Accounting Review, 2023

Tuan Ho, Kirak Kim, Yang Li, Fangming Xu Building on the investment-based asset pricing framework, we show that firms' ability to timely scale down their operations reduces the sensitivity of their equity value to large adverse productivity shocks. Using U.S. data in the times of the COVID-19 pandemic, we provide empirical evidence consistent with our model's predictions. Real flexibility curbs losses in firm value and reduces return volatility, especially for firms with high book-to-market or high COVID-19 exposure, consistent with the idea that the benefits of real flexibility are associated primarily with contraction options during the COVID-19 crisis. Our analysis shows that real flexibility provides incremental and complementary protection beyond financial flexibility. Besides its impact on stock prices, real flexibility also helps firms sustain earnings during 2020, compared with 2019 when the pandemic had not struck. Our work demonstrates that real flexibility is an important tool for corporate managers in navigating episodes of disasters.

How does green credit policy affect polluting firms' dividend policy? The China experience
International Review of Financial Analysis, 2023

Youwei Li, Ming Liao, Yangke Liu We explore how polluting firms alter their dividend policy in response to pressure from green credit policy. The green credit guidelines that China adopted in 2012 aim to promote credit supply in sustainable development. Meanwhile, this green credit policy forced polluting firms to access restricted credit supply and tightened bank monitoring. Using the adoption of the green credit policy as a quasi-natural experiment, we find that polluting firms tend to lower their dividend payments, consistent with the view that dividends act as an effective tool of liquidity management and a substitute to mitigate agency problems. This finding is more pronounced among firms with weaker corporate governance, greater financial constraints, and more green innovation output. Our further analysis suggests that the green credit policy forces polluting firms to engage in less dividend smoothing.

Are the good spared? Corporate social responsibility as insurance against cyber security incidents
Risk Analysis, 2023

Vassiliki Bamiatzi, Michael Dowling, Fabian Gogolin, Fearghal Kearney, Samuel Vigne Despite the increasing consensus that socially responsible behaviour can act as insurance against externally induced shocks, supporting evidence remains somewhat inconsistent. Our study provides a clear demonstration of the insurance-like properties of corporate social responsibility (CSR) in preserving corporate financial performance (CFP), in the event of a data (cyber) breach. Exploring a sample of 230 breached firms, we find that data breaches lead to significantly negative CFP outcomes for low CSR firms, with the dynamic being particularly pronounced in consumer-sensitive industries. Further, we show that firms increase their CSR activities in the aftermath of a breach to recover lost goodwill and regain stakeholder trust. Overall, our results support the use of CSR as a strategic risk-mitigation tool that can curtail the consequences of data breaches, particularly for firms operating in consumer-centric environments.

Married CEOs and stock price crash risk
European Financial Management, 2022

Jeong-Bon Kim, Shushu Liao, Yangke Liu This study examines whether marriage, as a social construct and cultural norm, can affect firm-level stock price crash risk. We find that firms managed by married CEOs are associated with lower future stock price crash risk, after controlling for a set of firm characteristics and CEO traits. We document that CEO marriage reduces crash risk by curbing bad news hoarding and formation activities. Moreover, the attenuating impact of CEO marriage on crash risk is more pronounced among firms with weaker corporate governance and those run by less prominent, higher-delta and lower-paid CEOs.

Corporate diversification, refocusing and shareholder voting
International Review of Financial Analysis, 2021

Yerzhan Tokbolat, Hang Le, Steve Thompson We examine if shareholders' attitude towards firm diversification strategy is revealed in their votes on management-initiated acquisition and divestment proposals using data on voting by shareholders of UK public firms between 1997 and 2019. We find that voting dissent is higher for diversifying acquisitions and lower for refocusing divestments, especially when these involve diversified firms. We also find a negative relationship between diversification premium and voting dissent. Our results provide evidence that diversification characteristics of firms and deals have a significant impact on shareholders' dissent in acquisitions and divestments.

That's Classified! Inventing a New Patent Taxonomy
Industrial and Corporate Change, 2021

Stephen D. Billington, Alan J. Hanna Innovation researchers currently make use of various patent classification schemas, which are hard to replicate. Using machine learning techniques, we construct a transparent, replicable and adaptable patent taxonomy, and a new automated methodology for classifying patents. We contrast our new schema with existing ones using a long-run historical patent dataset. We find quantitative analyses of patent characteristics are sensitive to the choice of classification; our interpretation of regression coefficients is schema dependent. We suggest much of the innovation literature should be carefully interpreted in light of our findings.