Knowledge that Transforms

Research Summary Strategy scholars have theoretically explored the relationship between legal knowledge protection and modularity of innovation activities in firms, but this relationship has yet to be empirically tested in the literature. Leveraging state‐level changes in US trade secrecy law and using a network modularity measure, this paper examines how trade secret protection affects the modularity of firms' innovation activities. Analyzing intrafirm inventor collaboration patterns in US patent data from 783 high‐tech firms between 1976 and 2017, we find that increased trade secret protection is negatively associated with the modularity of innovation activities within firms. This effect is more pronounced for firms with superior technologies and those geographically collocated with competitors—factors that enhance firms' knowledge appropriability concerns—and less pronounced for firms in industries where alternative appropriability mechanisms are highly effective. Moreover, our findings suggest that the increased betweenness centrality of new hires (skilled and junior) serves as an important underlying mechanism for the treatment effect. These results contribute to the literature by illuminating how firms strategize their internal innovation activities for knowledge protection and by underscoring its underlying mechanism. Managerial Summary Firms often modularize innovation activities to safeguard proprietary knowledge, but this approach can undermine innovation performance by restricting knowledge integration within organizations. This study demonstrates that stronger legal mechanisms alleviating firms' knowledge protection concerns, such as increased trade secret protection, encourage firms to adopt a less modularized, more integrated innovation system. Furthermore, we find that under such protections, firms are more likely to position new hires, including both skilled and junior employees, in central roles to connect innovation communities within the organization. These findings offer valuable insights for managers, illustrating how knowledge protection concerns can shape the structure of firms' innovation activities.

Research Summary This study examines whether training entrepreneurs to apply systematic approaches to strategic decision‐making influences their self‐perception of ability. Using a field experiment in which 151 entrepreneurs in Tanzania were randomly assigned to two different versions of entrepreneurial training (an evidence‐based vs. a theory‐and‐evidence‐based approach), we find entrepreneurs in the theory‐and‐evidence‐based condition experience a larger and more persistent increase in their self‐perception of ability to deal with challenges compared to the evidence‐based condition. Additionally, entrepreneurs across the two conditions respond differently to the training depending on their initial levels of perceived ability. By integrating insights from social cognitive psychology, this study contributes to research on entrepreneurial experimentation by uncovering the effect of strategic decision‐making training on individuals themselves, not just their ventures' outcomes. Managerial Summary Entrepreneurs' self‐perceptions of ability are critical for how they engage with learning opportunities and respond to challenges that arise as they develop their businesses. To explore how different versions of training on strategic decision‐making impact entrepreneurs' self‐perceived abilities to deal with such challenges, we conducted a field experiment with Tanzanian agribusiness entrepreneurs. Results show that entrepreneurs who learn to develop a theory‐of‐value before engaging in experimentation experience a larger increase in self‐perceived ability compared to those who experiment without such a theory‐of‐value, and this effect persists for longer. Our results have practical value for entrepreneurs and support organizations offering training programs and point to self‐perception of ability as an important factor to help entrepreneurs follow the behavioral advice they receive during those trainings.

Research Summary This study investigates how social class background shapes CEO career outcomes. Extending the shifting standards model to post‐appointment evaluation, we theorize that CEOs from lower‐class backgrounds face persistently high confirmatory standards, producing asymmetric consequences. When their performance is strong, the high confirmatory standards amplify their success, resulting in higher initial and subsequent compensation compared to their higher‐class counterparts. When performance falters, the same bar makes shortfalls more readily read as falling short of expectations, resulting in lower compensation and higher dismissal risk. We test these predictions using a novel dataset on CEO social class backgrounds from 1992 to 2018, supplemented with board interviews. The findings support our hypotheses, demonstrating how social class background operates as a double‐edged sword by increasing rewards for success and penalties for failure. Managerial Summary Does social class background affect how a CEO is evaluated? Drawing on compensation and dismissal outcomes for U.S. CEOs from 1992 to 2018, along with interviews with directors, we show that CEOs' social class backgrounds shape how their performance is interpreted. CEOs from lower social class backgrounds receive higher initial compensation and are rewarded more when their firms perform well. But when performance weakens, these same CEOs face steeper pay cuts and higher dismissal risk than their higher‐class peers. The same background that generates recognition when things go well makes shortfalls easier to interpret as underperformance. For boards, this suggests that background can quietly shape evaluations at the highest levels. For CEOs, perceptions of exceptional mobility and capability can become a liability when performance turns.

Research Summary CEO dismissal is a high‐stakes governance decision, yet its implications for corporate reputations remain underexplored. We develop theory explaining how dismissals damage corporate reputation through perceptual processes that arise from features of and reactions to the practice itself, distinct from effects attributable to dismissal's (much studied) economic and strategic consequences. Drawing on expectancy violation theory, we argue that dismissals become salient and generate negative reactions because they deviate from the preferred norm of planned succession and also highlight firm‐level problems, and these factors prompt reputational reassessment. The findings support this prediction: dismissals significantly damage corporate reputation even after controlling for financial performance. This damage intensifies when dismissed CEOs have won awards, received extensive media coverage, or led high‐performing firms. Managerial Summary Firing a CEO is one of the most consequential decisions that boards make, yet we know little about how this action affects a firm's reputation. We find that CEO dismissals meaningfully damage corporate reputation, even after accounting for the firm's financial situation. This damage appears to occur for two reasons: dismissals deviate from the preferred approach of a planned leadership transition, and they draw attention to underlying problems at the firm. The reputational harm intensifies when the dismissed CEO had won industry awards, received extensive media coverage, or led a firm that was performing well. These findings suggest that boards should consider the potential reputational costs of dismissing a CEO alongside the anticipated strategic benefits.

Research Summary The conventional wisdom both in research and in practice is that entrepreneurs need co‐founders, as they bring crucial resources to new ventures. Yet, this same work also suggests that co‐founders introduce destructive conflict, potentially creating as many problems as they solve. Surprisingly, little work examines the counterfactual—that is, the conditions under which solo‐founding is a viable approach. In this paper, we address this gap. We perform two studies; one using data from Y Combinator's renowned accelerator program, and another using large‐scale data from Crunchbase. Across these studies, we find that the solo founder disadvantage is partially attenuated when the founder has either broad or deep experience, or both (i.e., “T‐shaped skills”). Overall, our paper contributes to the literatures on founding teams and strategic human capital. Managerial Summary Co‐founders are beneficial to startups because they bring needed skillsets, knowledge, connections, and other resources. At the same time, however, co‐founders also introduce the potential for interpersonal conflict between the entrepreneur and co‐founders. Thus, in some cases, co‐founders may create as many or more problems as they solve. Surprisingly, very little research examines solo founders. In this paper, we examine the conditions under which solo founding is a viable approach. We find evidence of multiple ways in which solo founders can begin to overcome their performance disadvantages and achieve performance closer to that of co‐founded ventures.

Research Summary Many new employees leave their firms before realizing the returns to experience. One reason is that they cannot see how performance evolves with tenure. We study whether making performance trajectories visible improves retention and firm performance. In a randomized controlled trial at a multinational spa chain in China, workers received twice‐weekly information for 28 weeks about the performance path of a high‐performing senior coworker. The intervention reduces new‐worker attrition by 11–12% and increases revenue by 15% in stores with more new workers. These effects are largely driven by reduced stress and improved mental health, as the information lowers their beliefs about how well senior coworkers performed early in their careers. By contrast, showing only the current performance of a similar‐tenure peer has no detectable effect. Managerial Summary In many firms, new employees leave before realizing the returns to experience because they lack information about how performance evolves with tenure. We examine whether making senior workers’ performance trajectories visible improves retention and firm performance. In a randomized controlled trial involving over 7,000 workers at a multinational spa chain in China, employees received twice‐weekly information for 28 weeks about the performance trajectory of a high‐performing senior coworker. The intervention reduces new‐worker attrition by 11–12% and increases revenue by 15% in stores with more new workers. These effects are driven by reduced stress and improved mental health, as the information lowers beliefs about senior coworkers’ early‐career performance. Overall, our findings show that making senior workers’ performance trajectories visible can mitigate social comparison costs within firms.

Research Summary Although multi‐business firms can benefit from resource redeployment, we know little about the effects of alternative organizational arrangements on profits. This study examines a critical organizational choice, namely the centralization or decentralization of decision making. A formal model demonstrates that in the presence of business unit agency costs and costs of centralization, the profits from centralization versus decentralization depend not only on business relatedness—as emphasized in prior research—but also on return asymmetries between businesses. Moreover, in contrast with much of the research on contemporaneous resource sharing, the profitability of centralization does not increase monotonically with relatedness. The monotonic relationship holds only when relatedness leads to potential profits from redeployment in the intermediate range. As relatedness increases further, the advantage of centralization may decrease. Managerial Summary Diversified firms often redeploy resources from one business to another, and the firms must decide whether to centralize or decentralize their redeployment decisions. Much of the literature on related diversification in general, and with respect to redeployment in particular, suggests that related diversification will lead to higher profits when decisions are centralized. However, the analysis presented here shows that centralization may not lead to higher profits from redeployment for highly related diversification, and firms may be able to obtain equivalent or higher profits by decentralizing these decisions.

Research Summary This study investigates how AI recommendation algorithms shape complementor strategies and market equality on digital platforms. Using two quasi‐natural experiments from a food‐sharing platform, we examine impacts of sequential algorithmic upgrades: from a location‐based baseline to popularity‐based (PopRec) and then personalization‐based (PersRec). Analyses of over 1.7 million observations reveal that PopRec drives complementors to concentrate on a few offerings, while PersRec encourages new product introduction; yet these strategic shifts come at the expense of one another. Furthermore, PopRec reduces revenues of superstars but boosts revenues for long‐tail complementors, enhancing market equality. Conversely, PersRec exacerbates market inequality by asymmetrically benefiting superstars. By bridging platform orchestration and AI frontiers, this study demonstrates the strategic potential of AI in platform management while underscoring the importance of algorithmic accountability. Managerial Summary Digital platforms increasingly deploy AI recommendation algorithms to manage ecosystem performance. This study reveals that these algorithms also function as effective orchestration mechanisms, incentivizing and shaping complementor offering strategies at scale. We find that popularity‐based algorithms incentivize complementors to specialize and concentrate on a few core product offerings, while personalization‐based algorithms foster broader new product introduction. Our results demonstrate the vital strategic value of AI for managing platform ecosystems. Crucially, both algorithms present inherent trade‐offs for complementor strategies and trigger unforeseen market dynamics. Platform owners must meticulously design and implement algorithmic systems, balancing ecosystem generativity with operational control and considering far‐reaching market inequality implications.

Research Summary Academic spin‐off (ASO) performance has been studied in relation to either specific university‐level or regional‐level characteristics. However, ASOs originate from universities, which are embedded in regional ecosystems. This nested structure can create an attribution problem when either level is studied in isolation. Consequently, the relative importance of these two different levels for ASO performance has remained ambiguous. To address this ambiguity, we rely on multi‐level modeling and use a novel, hand‐collected dataset of 3164 ASOs founded between 2010 and 2019 from 212 universities nested within 99 European regions. We find that the region effect matters for about 27% for Return on Assets and 16% for Sales, whereas the university effect is negligible. Our study contributes to research at the nexus of academic entrepreneurship and variance decomposition in strategy. Managerial Summary Academic spin‐offs (ASOs) bring innovations from the university to the market, thereby potentially generating new sales, employment, and value. However, once formed, their performance prospects vary significantly, and understanding this variance is important for entrepreneurs and policymakers alike. Our findings from a new European dataset reveal that the region effect matters for ASO performance, but the university effect is negligible. This evidence does not imply that universities lack importance; rather, it suggests that universities in a region may have a collective impact that diffuses into regional resources and networks. Our evidence highlights the importance of fostering a supportive regional ecosystem.

Research Summary Complementing the role of AI in facilitating search and identifying combinations of high value in inventive activity, we argue that AI fundamentally alters the innovation landscape by unlocking new combinations that were previously infeasible. This effect arises because AI acts as a powerful shared layer due to its predictive capabilities and its ability to transmit solutions across domains, thereby creating a bridge between previously unconnected elements. Utilizing a matched sample of patents, we show that inventions incorporating AI exhibit a greater degree of novel recombinations compared to those without AI, and that our proposed bridging mechanism is consistent with these novel recombinations. Our study contributes by identifying a new mechanism by which recombinations emerge in inventive activity while also highlighting the role of enabling technologies such as AI in facilitating such recombinations. Managerial Summary How does AI impact inventive activity? We examine the question by studying the patenting activity of US firms over the period 2005–2023. We argue that AI fundamentally alters the innovation landscape by unlocking new combinations that were previously infeasible. This effect arises because AI acts as a powerful shared layer due to its predictive capabilities and its ability to transmit shared solutions, thereby creating a bridge between previously unconnected technological elements. Our analysis demonstrates that inventions that build on AI involve novel recombinations to a greater degree compared to inventions that don’t, and that AI bridges and connects knowledge domains that were hitherto disparate. These findings indicate that AI is more than just an invention of a new method of invention, and that it fundamentally reshapes the nature of inventive activity.