Executives often hesitate to disclose their company’s cybersecurity investments, fearing lawsuits or negative reactions from investors. Our research shows that transparency in this area actually pays off. Analyzing SEC filings from nearly 2,000 public firms, we find that companies that disclose cybersecurity investments enjoy a lower cost of capital—cheaper access to debt and equity financing. These benefits are strongest when disclosures are specific rather than boilerplate, when the firm is followed by more analysts and more institutional investors, and when disclosed investments in cybersecurity are substantial. The takeaway is clear: Meaningful disclosure builds trust with investors, who reward transparency by lowering financing costs. For leaders and regulators alike, this finding highlights that openness about cybersecurity readiness is not just good governance—It is smart business in a capital market that increasingly values risk management and resilience.

Organizations of all sorts adopt agile software development, but they rarely implement it “by the book.” Instead, agile practices evolve after initial adoption and often drift in different directions as organizations translate agile into their institutional environments. We studied the implementation of agile development in four organizations from much different institutional contexts: a startup technology company, a consulting firm, a government organization, and an industrial manufacturer. We found two core dimensions of their institutional contexts that shape agile translation: dynamism and pluralism. Dynamism refers to how fast requirements and environments change, and pluralism refers to how many diverse stakeholders are involved. These two dimensions influence the direction of agile translation. We show that agile practices evolve through a “ratcheting” process, whereby a sequence of incremental, interdependent changes gradually move teams closer to or further away from canonical agile practices. High pluralism in the institutional context, for example, tends to increase documentation, whereas low dynamism appears to slow iteration cycles. Agile software development is no longer limited to startups or software teams; it is adapted by all sorts of organizations as a way to flexibly innovate. Understanding why agile evolves differently across contexts helps managers move beyond one-size-fits-all prescriptions and set realistic expectations for agile development in their organizations.

Digital crowdfunding platforms operate under substantial uncertainty, where participants must assess platform viability with limited and imperfect information. Using data from the Chinese lending-based crowdfunding market, this study shows that platform growth depends not only on formal risk disclosures (e.g., interest rates, repayment ratios, and capitalization), but also on how users interpret the behavior of others as an informational signal. Specifically, we find that active user participation—particularly on the investor side—serves as a powerful form of “crowd wisdom” that shapes subsequent borrower participation, while borrower growth does not symmetrically attract investors. Importantly, the value of crowd-based signals is contingent: when formal risk indicators suggest greater uncertainty or weaker platform viability, users rely more heavily on observed participation by others; when risk signals are strong and favorable, the incremental influence of crowd cues diminishes. These findings offer several practical insights. Platform operators should recognize investor participation as a credibility signal and prioritize investor acquisition and retention, especially during periods of heightened uncertainty. Platform interface design and disclosure policies should balance formal risk information with transparent participation metrics, rather than treating them as substitutes. From a policy perspective, our results suggest that participation metrics can meaningfully shape user behavior even in the absence of misrepresentation, highlighting the need for regulators to consider how visibility rules, reporting standards, and disclosure requirements interact with social learning dynamics on digital financial platforms.

Cybersecurity failures are increasingly costly, prompting companies to recruit CIOs from other firms to their boards. This study examines whether there any impacts on a firms’ cybersecurity when (a) firms allow their own CIO to serve on an outside board; and (b) when firms appoint a CIO from another company to their own board. Using CIO-firm-year observations, we compare two pathways: (1) receiver firms that appoint an external CIO to their board, and (2) sender firms whose own CIO serves on another company’s board. The findings show asymmetric effects. Receiver firms experience fewer data breaches, suggesting that external CIOs effectively transfer cybersecurity expertise and practices. In contrast, sender firms face higher breach risk, as CIOs who serve externally appear to prioritize educating the recipient firm over acquiring new insights for their home firm. This risk intensifies when the external firm lacks strong cybersecurity practices but is mitigated when the home firm has a dedicated CISO. Conversely, receiver firms benefit most when the sending firm has strong cybersecurity capabilities—or even a past breach—because negative events create valuable lessons. The results offer actionable implications: firms should strategically recruit outside CIOs to improve board-level cyber capabilities and carefully weigh the risks before permitting their own CIOs to serve externally. Policymakers should consider mechanisms that incentivize effective cybersecurity knowledge transfer across board interlocks.

Drug discovery is a complex process that involves sequentially screening and examining a vast array of molecules to identify those with the target properties. This process faces challenges because of the vast search space, the rarity of target molecules, and constraints imposed by limited data and experimental budgets. To overcome these challenges, we propose a human-centered human–algorithm collaboration framework. Notably, both the algorithm and humans have substantial knowledge gaps. The algorithm proposes, and human experts retain decision rights to approve, revise, or override. Our design artifact leverages dual-process theory for attention management, surfaces meta-knowledge as a shared state for coordination, and optimizes a joint team objective. In real-world drug discovery tasks, the human–AI team consistently outperforms all baselines, including human-only and AI-only methods. This demonstrates complementary performance. These findings illustrate that the optimal use of AI in complex decision-making environments is to augment, rather than replace, human expertise. Managers should balance AI integration with the cultivation of deep domain expertise, ensuring that technology enhances decisions without eroding uniquely human strengths. For practice and policy: preserve human agency with clear decision rights, make model uncertainty explicit, and use AI to route scarce expert attention to the most informative experiments.

Leadership transitions often create uncertainty in corporate innovation. Our study shows that artificial intelligence (AI) plays a crucial role in helping firms navigate these transitions. Using data on patents, job postings, and CEO turnover across U.S. public firms, we find that organizations with stronger AI investment are more successful in pursuing explorative innovation after CEO turnover. AI enables this shift by helping leaders overcome two common barriers: managerial myopia, the tendency to rely on familiar past practices, and information overload, which can overwhelm new executives. Firms that leverage AI more effectively reallocate resources to research and development, elevate innovation as a strategic priority, and launch new initiatives. These effects are especially pronounced in manufacturing industries and when CEOs have science, technology, engineering, and mathematics backgrounds. For practice, our findings highlight AI as a strategic capability that helps firms sustain organizational creativity during leadership change. For policy, they suggest that promoting AI adoption could strengthen innovation dynamism and competitiveness in rapidly changing environments.

The touchscreen has become the de facto interface for individuals to interact with digital devices. This research investigates the implications of the profound shift from the mouse-based, nontouch interface to the touch-based interface for human thinking and behavior. Ten studies reveal that using touchscreens, as opposed to a mouse, fosters a more concrete low-level construal. Specifically, using touch interfaces on devices such as iPads and tablets prompts people to interpret actions in a detailed, hands-on manner, viewing locking a door as inserting a key into a lock rather than as a broader concept such as securing a house. Touchscreens also encourage a narrow categorization of concepts and a reliance on local, granular attributes. The concrete mindset evoked by the touch interface elevates individuals’ preference for practicality over complexity, such as choosing a compact camera over an advanced one, and receptiveness to persuasive attempts with feasibility appeals. Given that mental construals fundamentally influence how we perceive and engage with the world, our findings underscore the wide-ranging impacts of touch interfaces. This research provides a theoretical foundation for exploring the broader implications of the widespread adoption of touch technology, especially as digital devices become increasingly integrated into our digitally transformed daily life worldwide.

Generative AI (GenAI) promises to revolutionize creative work, but its value is not universal. Using controlled lab settings with students and real-world tests with professional designers, our research shows that GenAI is a double-edged tool. In the initial brainstorming (ideation) stage, GenAI reliably boosts creativity for all users. However, in the execution (implementation) stage, whereas novice designers continue to benefit from GenAI’s assistance, expert designers encounter inefficiencies—spending significantly more time without improving creativity, because GenAI’s methods conflict with experts’ well-established routines. For firms, this means adoption strategies must be nuanced. GenAI delivers the greatest value when applied to brainstorming, early concept development, and work by less-experienced employees. In contrast, deploying GenAI in later-stage production tasks, especially with seasoned professionals, may reduce efficiency. Managers and tool designers should avoid blanket promotion of GenAI across all tasks and instead develop targeted adoption strategies that align with employees’ expertise and the stage of the creative process. By tailoring GenAI use, organizations can harness its creative potential while minimizing risks of counterproductive outcomes.

Given the remarkable success of personalized recommendations on digital platforms, brick-and-mortar businesses are increasingly exploring artificial intelligence (AI)-powered recommendation services in physical spaces. To address this emerging need, our study introduces a generalized recommendation problem, termed point-of-interest (POI) recommendations in physical spaces with pedestrian movement (P3M). Applicable scenarios for P3M include store recommendations in shopping malls, product shelf recommendations in hypermarkets, and so on. A critical impediment in P3M is exposure bias: When the exposure likelihood of items to users is unevenly distributed, indiscriminately treating all unobserved interactions as negative feedback introduces bias to the learning of recommender systems. To address this issue, we propose a novel recommendation method, unbiased movement-aware pairwise ranking (UMPR), which integrates pedestrian movement modeling with unbiased pairwise learning to achieve effective and unbiased recommendations. Using real-world shopping mall data, we demonstrate that UMPR not only delivers more accurate recommendations compared to state-of-the-art methods but also brings added monetary value for mall owners and promotes humanistic fairness across store tenants. Overall, our study emphasizes the importance of mitigating exposure bias through pedestrian movement modeling, advancing the field of recommendations in physical spaces.