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.

Research Summary: While research has focused primarily on stars as individual contributors, we examine organizational situations where stars must work closely with non‐stars. We argue that, in such situations, building teamwork around a star is an exercise in learning under complexity. In response, organizations prioritize interactions involving the star to simplify learning. This simplification, however, creates organizational myopia. We claim that a star’s temporary absence helps the organization overcome myopia by triggering a search for new routines. When he returns, the organization may combine these new routines with pre‐absence routines to improve teamwork and performance. We exploit injuries to star players in the National Basketball Association as an exogenous shock and find that on average, teams perform better after a star’s return than before his absence. Managerial Summary: This study examines the effect of the temporary absence of a star employee on organizational performance. We find evidence that a star employee’s temporary absence helps the organization overcome an over‐reliance on the star and improve teamwork. Improved teamwork, in turn, enables the organization to perform better upon the star’s return than it did prior to his absence. This result suggests that organizations might want to revisit the tendency to view stars as too valuable to lose, even for a short time. In particular, organizations may want to pull stars from ongoing projects and encourage them to attend professional development programs. A star’s temporary absence and return from such a program improves not only the star’s skills but also the organization’s teamwork.

Empirical evidence suggests that entrepreneurs make mistakes: too many enter markets and, once there, persist too long. Although scholars have largely settled on behavioral bias as the cause, we suggest that this consensus is premature. These mistakes may also arise from a process in which entrepreneurs continually learn about their prospects and make entry and exit decisions based on what they have learned. We develop a computational model of this process that connects pre- and post-entry learning and can be directed to analyze Bayesian-rational or biased entrepreneurs. The model suggests that, to outside observers, rational entrepreneurs may appear overconfident, seem to take too long to exit, and exhibit a positive correlation between entry cost and persistence in the market. When examining confidence biases, the model suggests that entrepreneurs whose biases cause them to perform the worst after entry will be most likely to enter, that pre-entry learning induces a positive correlation between distinct confidence biases among entrants, and that exit changes the prevalence of certain biases in the surviving population of entrants over time. Our study also speaks to recent work on pre-entry experience that documents the transfer of knowledge from parent to progeny firms, suggesting that, in addition to inheritance, differential performance may also be the result of heterogeneity in the length and quality of pre-entry learning during which an opportunity is assessed.

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Research Summary: We develop a behavioral theory of real options that relaxes the informational and behavioral assumptions underlying applications of financial options theory to real assets. To do so, we augment real option theory's focus on uncertain future asset values (prospective uncertainty) with feedback learning theory that considers uncertain current asset values (contemporaneous uncertainty). This enables us to incorporate behavioral bias in the feedback learning process underlying the option execution/termination decision. The resulting computational model suggests that firms that inappropriately account for contemporaneous uncertainty and are subject to learning biases may experience substantial downside risk in undertaking real options. Moreover, contrary to the standard option result, greater uncertainty may decrease option value, making commitment to an investment path more effective than remaining flexible. Managerial Summary: Executives recognize the need to make uncertain investments to grow their business while mitigating downside risk. The analogy between financial options and real corporate investments provides an appealing method to consider the practical challenge of such investment decisions. Unfortunately, the “real options” analogy seems to break down in practice. We identify how a second form of uncertainty confounds real options intuition, leading managers to overestimate the value of uncertain investments. We present a behavioral real options model that accounts for both forms of uncertainty and suggest how uncertainty interacts with behavioral bias in the option execution/termination decision. Our model facilitates assessment of the conditions under which investments in uncertain opportunities are usefully considered as real options, and provides a means to evaluate their attractiveness.