Knowledge that Transforms

Abstract While prior research on the strategic framing of innovation highlights the cognitive mechanisms underlying novelty evaluation, we know little about the corresponding emotional mechanisms. Drawing on appraisal theory, construal level theory, and the literature on emotions, we theorize two distinct appraisal‐emotion pathways through which the framing of novel ideas evokes hope and awe among investors with different motives. We argue that high‐construal framing supplements economically motivated investors' low‐level feasibility orientation, which evokes hope and increases their willingness to invest. By contrast, low‐construal framing supplements non‐economically motivated investors' high‐level desirability orientation, which evokes awe and increases their willingness to invest. We test and find some support for these within‐motive pathways across three studies. Our study offers new theoretical and practical insights on the strategic framing of novel ideas.

Abstract Reserch Summary We propose that founding partner relationships can leave distinct imprints on organizations that differ in durability and in how they respond to subsequent changes involving the founding partner. Examining South American airlines founded between 1919 and 1984, we argue and find that such relationships simultaneously create an internal capability imprint, enhancing operational performance and facilitating international expansion, and an external identity imprint, constraining expansion by triggering national security concerns among foreign regulators. Internal capabilities persist longer because they are embedded in organizational structures and tacit knowledge, while external identity resides in more malleable stakeholder perceptions. Post‐founding changes to the imprinter reshape these effects asymmetrically: the transition to civilian air traffic control erodes the competitive advantage of military‐derived capabilities by diffusing previously scarce expertise, while military coups intensify the negative consequences of a military‐associated identity. These findings advance a dual imprinting perspective and contribute to strategy research by explaining persistent organizational heterogeneity through founding‐era capabilities and identities. Managerial Summary When launching a venture, founders instinctively seek to collaborate with powerful partners such as celebrated investors and high‐profile board members. Those relationships leave two distinct legacies. The first is operational: the knowledge and systems a powerful partner brings embed themselves deeply, sharpening capabilities that sustain competitive advantage for years. The second is reputational: the outside world immediately begins to categorize your organization through that association, and that categorization can be hard to escape. Our research on South American airlines shows how military‐era founding partners produced operational excellence that fueled international growth, while simultaneously creating a security‐sensitive identity that blocked market access in politically sensitive contexts. The lesson for founders: think several moves ahead. The question is not solely what this partner can give us today, but how will we be seen if his or her reputation shifts tomorrow.

Abstract Reserch Summary Breakthrough inventions are central to firms' competitive advantage, yet what constitutes a breakthrough remains unclear. We examine the relationship between technological quality (measured by forward citations) and economic value (measured by grant‐day abnormal stock‐returns) of patents. Using U.S. patents assigned to publicly listed firms, we find that among the most exceptional inventions—that is, breakthroughs—the correlation between these two measures disappears: technologically outstanding patents are not necessarily the most economically valuable. We attribute this divergence to a structural tension between value creation and value capture in patenting, driven by novelty, the availability of complementary assets, and competitive dynamics. Firms that successfully manage both dimensions earn a disproportionate market premium. This outcome is often associated with firms that diversify their technological portfolios asynchronously across technology S‐curves. Managerial Summary Breakthrough innovations are widely viewed as the lifeblood of corporate success. Yet what truly defines a breakthrough—and how its value should be assessed—remains unclear. Companies typically rely on two indicators: technological quality (measured by forward citations) and economic value (captured by stock market reactions at patent grant). Conventional wisdom assumes these move together. Our analysis of U.S. patents challenges this view. For the most exceptional inventions, technological quality and economic value diverge. We identify the drivers of this tension and show that firms able to manage it earn disproportionate market returns.

Abstract Research Summary In evaluative contexts, evaluatees typically seek to present themselves in a favorable light, while evaluators ask penetrating questions to assess these claims. Here we develop a framework to identify curveball questions : ones that are on‐topic yet perplexing (i.e., difficult to predict) relative to past discourse. We develop a language‐based measure of curveball questions and apply it to a corpus of quarterly earnings calls. After validating this question‐level measure, we next demonstrate that a call‐level curveball measure predicts absolute returns, absolute abnormal returns, and changes in a firm's average analyst rating. Finally, we identify the types of analysts who are most likely to pose curveball questions, the types of firms that are most likely to receive them, and the conditions under which they tend to arise. Managerial Summary Even a carefully crafted presentation can be derailed by a challenging question. What makes a question challenging in ways that can be disruptive and how can such a question be measured? We propose that such questions, which we label curveballs , are on‐topic, and thus difficult to dismiss or deflect, yet difficult to predict based on prior knowledge. We harness the tools of computational linguistics to develop a measure of curveball questions and apply it to the context of quarterly earnings calls. We show that this measure predicts consequential economic outcomes and highlight the conditions under which curveball questions tend to arise. Our measurement strategy can be readily extended to other evaluative contexts such as job interviews and venture capital pitches.

Abstract Research Summary This study investigates how firms engage in information‐seeking lobbying to address trade policy uncertainty. I argue that lobbying enables firms to gain early insights into forthcoming tariff actions, allowing them to strategically stockpile products likely to be targeted. Using shipping records of US firms during the 2018 US–China trade war, I find that lobbying firms increased imports of soon‐to‐be‐tariffed products before tariff lists were publicly released, compared to non‐lobbying firms. This selective stockpiling pattern disappeared after tariff announcements. Further analysis shows that lobbying firms were less likely to request tariff exemptions for products they had preemptively stockpiled, suggesting that information‐seeking lobbying during policy formulation provides an additional benefit by reducing the need for costly government engagement during the implementation phase. Managerial Summary To manage heightened trade policy uncertainty, firms often adjust global supply chains or engage with the government—but how can they integrate these strategies? This study proposes that firms can engage in lobbying not just to influence policy outcomes, but to gain early insights into pending trade actions. Using data from the 2018 US–China trade war, I find that lobbying firms stockpiled more of the products that were later targeted by tariffs before those tariffs were publicly announced. These firms were also less likely to request tariff exemptions for products they had preemptively stockpiled, indicating potential cost savings by avoiding expensive government engagement. The findings underscore the strategic value of early‐stage lobbying and highlight the importance of coordination between government affairs and operation departments.

Abstract Research Summary Organizations grant stakeholders who provide valuable resources insider status in governance, excluding less valuable outsiders. Firms thereby assemble a value‐maximizing resource portfolio but face challenges when environmental shifts require adaptation that harms some insiders. We combine and extend new stakeholder and social movement theories, hypothesizing how various stakeholders influence such adaptation. Outsiders can enable adaptation depending on organizational governance and the array of insider stakeholders. For‐profit firms are less open to outsider influence, but a wider array of insiders enables outsiders to align with certain groups to overcome the opposition of others who resist change. The nature of these alignments shapes whether adaptation involves transformative divestments or exploratory investments. We test our theory in the context of the Beyond Coal movement to divest coal plants. Managerial Summary To gain access to valuable resources, organizations commit to stakeholders who provide these resources. However, this creates problems when adapting to changes in the environment that undermine the value of these resources. How can managers balance their stakeholder commitments with the need to integrate the concerns of other stakeholders demanding adaptive changes? We find that organizational governance and the configuration of stakeholder interests can create openings for adaptation. Studying a period of rapid environmental change in the US electric utility industry, for‐profit utilities were more likely to retire coal generators when activists aligned with consumer advocates, and more likely to invest in solar generators when activists aligned with prosumers.

Abstract Research Summary This exploratory paper introduces a new type of family business by studying the investment strategies of family‐managed venture capital funds (“Family VCs”) across a multi‐country setting. It shows that Family VCs are more likely to invest in (syndicate with) geographically proximate startups (investors), indicating a preference for local investments. This tendency is stronger when the VC is named after the family and the family is closely involved in the decision‐making process of the fund. I provide suggestive evidence that this pattern reflects both superior local knowledge (rational response) and home bias (non‐rational response), with the latter becoming more pronounced when performance pressure is lower. Managerial Summary Family‐managed VC funds (Family VCs), managing roughly $29 billion, represent an important segment of the venture capital industry. I show that family control shapes both the selection of startups and syndicate partners. Family VCs are indeed more likely to support ventures and partner with investors from their communities, particularly when family members are highly involved in investment decisions and the fund is named after the family. I provide suggestive evidence that this local preference stems from both rational factors, like superior local knowledge and networks, and a non‐rational preference for local investments. Their local focus becomes relatively less pronounced when families must demonstrate strong financial performance, such as when a follow‐on fund has not yet been raised and during competitive market conditions.

Abstract Research Summary We study an important, but largely overlooked, non‐market strategy used by firms in the enforcement stage of policy: “snitching,” that is, providing intelligence about potential violations of their rivals in an attempt to persuade regulators to fine them. Building on political marketplace theory, we develop and test a theoretical model of how firms use snitching during regulatory enforcement. We show that in equilibrium, firms snitch when the rival's violations are likely to cause significant harm to the population. We then derive several boundary conditions outlining when firms will engage in more or less snitching. We find support for our theory in panel data on enforcement actions by the U.S. Environmental Protection Agency for more than 8000 facilities over 12 years. Managerial Summary Firms can use their corporate political activity (CPA) not only to help themselves, but also to snitch on their rivals. Using a formal model, we look at how CPA influences regulatory enforcement. We find firms are most likely to snitch on their rivals when their rivals' potential violations are likely to cause significant harm, since this is when regulators care the most. Our model also outlines when this is most and least likely to occur. We then test our theory using data from the U.S. Environmental Protection Agency (EPA) and find support for our claims. The EPA is more likely to fine facilities for infractions that process many toxic chemicals, but this effect is much greater when a firm's rivals are actively lobbying the EPA.

Abstract Research Summary Strategy research examines the drivers of firm performance. Variance decomposition studies have analyzed industry's impact, with little attention paid to the industry to which a firm is assigned. This study investigates how industry assignment affects the findings about industry's impact. We analyze existing industry classification schemes and introduce a machine learning‐based scheme that leverages an embedding model to process text from annual reports. We find that industry assignment differs substantially across schemes, and that certain firms are more consistently grouped together. Schemes that group more similar firms together exhibit stronger industry effects. Given the literature's frequent reliance on the criticized Standard Industrial Classification scheme, industry's role in firm performance has likely been systematically underestimated. Managerial Summary Understanding what drives a company's success is crucial. Prior research has surprisingly found that a firm's industry plays little role in explaining a firm's performance. However, this study suggests that industry's importance is likely understated due to how firms are grouped into industries. Comparing several existing industry classification schemes alongside a new one we built using machine learning, we find that grouping similar firms in the same industry increases reported industry importance and decreases firm importance. Being more precise about industry membership reveals that industry matters more than previously thought. The implication is that understanding the industry is more important for a firm's performance and could be key to understanding sustained success.