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Although pre-entry experience is widely regarded as a critical asset that positively influences new entrant performance, empirical support is mixed. To address this inconsistency, we conduct a meta-analysis of the empirical findings in 272 papers. We draw theoretically on the organizational learning literature to argue that the pre-entry experience–new entrant performance relationship is contingent on the characteristics of pre-entry experience, the environmental context of the new entrant, and the interaction between the two. In particular, we examine the effects of two levels of pre-entry experience (firm and founder), four types of founder-level pre-entry experience (entrepreneurial, managerial, industry, and functional experience), and two types of environments (industry and institutional). The meta-analysis results show a significant and positive correlation between founder-level pre-entry experience and economic performance of 0.07. Likewise, the failure rates of spinouts and diversifying entrants are 11% lower than that of start-ups. The moderating analysis results show that the correlation of founder-level pre-entry experience and economic performance is lower in knowledge- or technology-intensive (KTI) industries and higher in low-KTI manufacturing and service industries. The correlation is also higher in institutional environments with high power distance and individualism. These findings provide compelling new evidence for the importance of pre-entry experience and advance our understanding of the boundary conditions on the pre-entry experience–new entrant performance relationship.Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1589 .

This paper develops and tests a model of the effectiveness of selection processes in eliminating less fit organizations from a population when organizations are undergoing adaptive change. Stable organizational traits, such as a search strategy or routine, do not imply that an organization's performance will remain stable over time or that cross-sectional differences in performance will persist. These properties create the possibility that population-level selection processes will be inefficient in that organizations with potentially superior long-run performance will be selected out. We theorize that organizational-level adaptation often results in fluctuations in current performance across time. These fluctuations may attenuate the degree to which current performance differences among organizations are indicative of future performance. As a consequence, search strategies that generate systematically different performance trajectories, even if they share a common long-run outcome, will generate differing survival rates. These ideas are explored using a formal simulation model employing the framework of NK performance landscapes. Our central finding is that selection may be systematically prone to errors and that these selection errors are endogenous to, and differ markedly across, firms' search strategies.

Entrants are often viewed as suffering from a "liability of newness"—at founding, they rarely possess the knowledge and capabilities necessary to compete and survive. They can overcome this liability by learning vicariously from the knowledge of incumbent firms. But how can entrants learn from external knowledge when they lack the prior related knowledge that forms the basis of absorptive capacity? We theorize that the process of internal experiential learning facilitates learning from external knowledge, particularly for entrants. To test this theory, we examine learning using a comprehensive set of U.S. commercial banking firms, including a full census of entrants. Our estimates suggest that the share of vicarious learning realized in the process of experiential learning is twice as large for entrants as for incumbents. In this sense, entrants enjoy an "advantage of newness" in learning.

One of the key mechanisms of firms' strategic renewal is R&D, and a key driver of the intensity of R&D is industry context. A number of theories develop propositions linking industry factors to firm R&D behavior, but these theories lack consensus. To date, empirical tests have been unable to resolve the competing predictions because of lack of time-varying measures of technology. We create new measures for technology and then conduct a test of the competing theories. Our results indicate that the data best match a model of innovative behavior in which firms invest in R&D principally to regain eroded advantage rather than to pursue the new frontier.

Organizational decision making that leverages the collective wisdom and knowledge of multiple individuals is ubiquitous in management practice, occurring in settings such as top management teams, corporate boards, and the teams and groups that pervade modern organizations. Decision-making structures employed by organizations shape the effectiveness of knowledge aggregation. We argue that decision-making structures play a second crucial role in that they shape the learning of individuals that participate in organizational decision making. In organizational decision making, individuals do not engage in learning by doing but, rather, in what we call learning by participating, which is distinct in that individuals learn by receiving feedback not on their own choices but, rather, on the choice made by the organization. We examine how learning by participating influences the efficacy of aggregation and learning across alternative decision-making structures and group sizes. Our central insight is that learning by participating leads to an aggregation–learning trade-off in which structures that are effective in aggregating information can be ineffective in fostering individual learning. We discuss implications for research on organizations in the areas of learning, microfoundations, teams, and crowds.